@inbook{
 type = {inbook},
 year = {2025},
 keywords = {antenna design,artificial intelligence,evolutionary algorithms,machine learning},
 pages = {227-256},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394227952.ch7},
 publisher = {John Wiley & Sons, Ltd},
 chapter = {Antenna Design Using Artificial Intelligence},
 id = {6ee99a4a-4504-398f-849e-b2b87c09d6e5},
 created = {2024-12-18T14:04:38.634Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-12-18T14:04:38.634Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {doi:https://doi.org/10.1002/9781394227952.ch7},
 source_type = {inbook},
 private_publication = {false},
 abstract = {Abstract The antenna is a key component of the radio frequency (RF) front end of a communication system. This chapter reviews the use of artificial intelligence (AI) in antenna design. We discuss the applications of various AI techniques such as evolutionary algorithms, machine learning, and knowledge representation ontologies. These applications range from antenna design to antenna feature evaluation in a rapidly expanding field. We then summarize the challenges of new AI techniques in antenna design based on the current state-of-the-art and provide predictions for future research directions.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K and Matin, Mohammad A and Karagiannidis, George K},
 doi = {https://doi.org/10.1002/9781394227952.ch7},
 title = {Artificial Intelligence for Future Networks}
}

Abstract The antenna is a key component of the radio frequency (RF) front end of a communication system. This chapter reviews the use of artificial intelligence (AI) in antenna design. We discuss the applications of various AI techniques such as evolutionary algorithms, machine learning, and knowledge representation ontologies. These applications range from antenna design to antenna feature evaluation in a rapidly expanding field. We then summarize the challenges of new AI techniques in antenna design based on the current state-of-the-art and provide predictions for future research directions.

@article{
 title = {Enhancing 3D object detection in autonomous vehicles based on synthetic virtual environment analysis},
 type = {article},
 year = {2025},
 keywords = {Augmented reality,Deep learning,Feature extraction,Object detection,Object recognition,Scene analysis,Scene understanding},
 pages = {105385},
 volume = {154},
 websites = {https://www.sciencedirect.com/science/article/pii/S0262885624004906},
 id = {34831df3-404c-3751-9897-b3deba617a05},
 created = {2024-12-24T08:27:05.636Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-12-24T16:02:07.793Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {LI2024105385},
 source_type = {article},
 private_publication = {false},
 abstract = {Autonomous Vehicles (AVs) rely on real-time processing of natural images and videos for scene understanding and safety assurance through proactive object detection. Traditional methods have primarily focused on 2D object detection, limiting their spatial understanding. This study introduces a novel approach by leveraging 3D object detection in conjunction with augmented reality (AR) ecosystems for enhanced real-time scene analysis. Our approach pioneers the integration of a synthetic dataset, designed to simulate various environmental, lighting, and spatiotemporal conditions, to train and evaluate an AI model capable of deducing 3D bounding boxes. This dataset, with its diverse weather conditions and varying camera settings, allows us to explore detection performance in highly challenging scenarios. The proposed method also significantly improves processing times while maintaining accuracy, offering competitive results in conditions previously considered difficult for object recognition. The combination of 3D detection within the AR framework and the use of synthetic data to tackle environmental complexity marks a notable contribution to the field of AV scene analysis.},
 bibtype = {article},
 author = {Li, Vladislav and Siniosoglou, Ilias and Karamitsou, Thomai and Lytos, Anastasios and Moscholios, Ioannis D and Goudos, Sotirios K and Banerjee, Jyoti S and Sarigiannidis, Panagiotis and Argyriou, Vasileios},
 doi = {https://doi.org/10.1016/j.imavis.2024.105385},
 journal = {Image and Vision Computing}
}

Autonomous Vehicles (AVs) rely on real-time processing of natural images and videos for scene understanding and safety assurance through proactive object detection. Traditional methods have primarily focused on 2D object detection, limiting their spatial understanding. This study introduces a novel approach by leveraging 3D object detection in conjunction with augmented reality (AR) ecosystems for enhanced real-time scene analysis. Our approach pioneers the integration of a synthetic dataset, designed to simulate various environmental, lighting, and spatiotemporal conditions, to train and evaluate an AI model capable of deducing 3D bounding boxes. This dataset, with its diverse weather conditions and varying camera settings, allows us to explore detection performance in highly challenging scenarios. The proposed method also significantly improves processing times while maintaining accuracy, offering competitive results in conditions previously considered difficult for object recognition. The combination of 3D detection within the AR framework and the use of synthetic data to tackle environmental complexity marks a notable contribution to the field of AV scene analysis.

@article{
 title = {A Novel Air-to-Ground Communication Scheme for Advanced Big Data Collection in Smart Farming using UAVs},
 type = {article},
 year = {2025},
 keywords = {air-to-ground communication,flying ad-hoc networks},
 pages = {16564-16583},
 volume = {13},
 id = {f0f6a9eb-89f1-3239-8845-27b1a088760a},
 created = {2025-01-21T07:18:01.772Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-01-31T07:27:30.876Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10848091},
 source_type = {article},
 private_publication = {false},
 abstract = {The evolution of Flying Ad Hoc Networks (FANETs) demands the development of advanced routing protocols that can address the unique challenges associated with UAV missions. This paper proposes a novel Air-to-Ground, Energy-Aware, mission-oriented protocol, leveraging Fuzzy Logic (AERO-FL), to enhance UAV cooperation and optimize network performance in deterministic scanning operations. The study focuses on a Smart Farming (SF) scenario for extensive crop surveillance, which traditionally relies on a single UAV. This conventional approach is often inefficient because of its inability to enable real-time data transmission and its vulnerability to operational failures. The proposed system replaces the single UAV approach with a cooperative FANET comprising multiple UAVs, significantly reducing mission completion time while facilitating real-time data transmission through the cooperation of aerial and ground nodes. The simulation results demonstrate that AERO-FL outperforms established routing protocols in key performance metrics. These findings underscore the potential of AERO-FL in a variety of scanning applications, including traffic monitoring, environmental observation, disaster response, and military operations. By enabling UAV cooperation in a mission-oriented routing framework, this study provides a foundation for future research aimed at achieving full FANET capabilities.},
 bibtype = {article},
 author = {Kakamoukas, Georgios A and Lagkas, Thomas D and Argyriou, Vasileios and Goudos, Sotirios K and Grammatikis, Panagiotis Radoglou and Bibi, Stamatia and Sarigiannidis, Panagiotis G},
 doi = {10.1109/ACCESS.2025.3532393},
 journal = {IEEE Access}
}

The evolution of Flying Ad Hoc Networks (FANETs) demands the development of advanced routing protocols that can address the unique challenges associated with UAV missions. This paper proposes a novel Air-to-Ground, Energy-Aware, mission-oriented protocol, leveraging Fuzzy Logic (AERO-FL), to enhance UAV cooperation and optimize network performance in deterministic scanning operations. The study focuses on a Smart Farming (SF) scenario for extensive crop surveillance, which traditionally relies on a single UAV. This conventional approach is often inefficient because of its inability to enable real-time data transmission and its vulnerability to operational failures. The proposed system replaces the single UAV approach with a cooperative FANET comprising multiple UAVs, significantly reducing mission completion time while facilitating real-time data transmission through the cooperation of aerial and ground nodes. The simulation results demonstrate that AERO-FL outperforms established routing protocols in key performance metrics. These findings underscore the potential of AERO-FL in a variety of scanning applications, including traffic monitoring, environmental observation, disaster response, and military operations. By enabling UAV cooperation in a mission-oriented routing framework, this study provides a foundation for future research aimed at achieving full FANET capabilities.

@article{
 title = {Deep Learning Framework Using Spatial Attention Mechanisms for Adaptable Angle Estimation Across Diverse Array Configurations},
 type = {article},
 year = {2025},
 volume = {13},
 websites = {https://www.mdpi.com/2227-7080/13/2/46},
 id = {360be2a6-6b2c-38ef-a516-7ff721ade4a9},
 created = {2025-01-25T11:02:05.625Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-01-25T11:02:05.625Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies13020046},
 source_type = {article},
 private_publication = {false},
 abstract = {Rapid advancement of wireless communication systems and the increasing need for accurate, real-time signal processing have driven innovations in direction-of-arrival (DoA) estimation techniques. This paper introduces a novel convolutional neural network (CNN) architecture that combines spatial attention mechanisms with a transfer learning framework to enhance both accuracy and versatility in DoA estimation. The model integrates spatial attention layers to dynamically prioritize signal regions with the highest information value, allowing it to isolate relevant signals and suppress interference in noisy or crowded signal environments. In addition, we utilize a transfer learning framework that enables the model to generalize across various antenna array configurations (i.e., planar, linear, and circular arrays) with minimal additional training. Extensive simulation results benchmark the proposed model against existing state-of-the-art methods for DoA estimation, achieving improved absolute error across diverse conditions. This hybrid approach not only enhances DoA estimation precision, but also significantly reduces retraining requirements when adapting to new array configurations, positioning it as a robust, scalable tool for next-generation wireless communication systems.},
 bibtype = {article},
 author = {Mylonakis, Constantinos M and Velanas, Pantelis and Lazaridis, Pavlos I and Sarigiannidis, Panagiotis and Goudos, Sotirios K and Zaharis, Zaharias D},
 doi = {10.3390/technologies13020046},
 journal = {Technologies},
 number = {2}
}

Rapid advancement of wireless communication systems and the increasing need for accurate, real-time signal processing have driven innovations in direction-of-arrival (DoA) estimation techniques. This paper introduces a novel convolutional neural network (CNN) architecture that combines spatial attention mechanisms with a transfer learning framework to enhance both accuracy and versatility in DoA estimation. The model integrates spatial attention layers to dynamically prioritize signal regions with the highest information value, allowing it to isolate relevant signals and suppress interference in noisy or crowded signal environments. In addition, we utilize a transfer learning framework that enables the model to generalize across various antenna array configurations (i.e., planar, linear, and circular arrays) with minimal additional training. Extensive simulation results benchmark the proposed model against existing state-of-the-art methods for DoA estimation, achieving improved absolute error across diverse conditions. This hybrid approach not only enhances DoA estimation precision, but also significantly reduces retraining requirements when adapting to new array configurations, positioning it as a robust, scalable tool for next-generation wireless communication systems.

@article{
 title = {Identification of Greek Orthodox Church Chants Using Fuzzy Entropy},
 type = {article},
 year = {2025},
 volume = {14},
 websites = {https://www.mdpi.com/2073-431X/14/2/39},
 id = {c3a641a6-6bad-3642-b884-b032a50f37e0},
 created = {2025-01-27T17:26:41.737Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-01-27T17:26:41.737Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {computers14020039},
 source_type = {article},
 private_publication = {false},
 abstract = {In this work, a comparison of Greek Orthodox religious chants is performed using fuzzy entropy. Using a dataset of chant performances, each recitation is segmented into overlapping time windows, and the fuzzy entropy of each window in the frequency domain is computed. We introduce a novel audio fingerprinting framework by comparing the variations in the resulting fuzzy entropy vector for the dataset. For this purpose, we use the correlation coefficient as a measure and dynamic time warping. Thus, it is possible to match the performances of the same chant with high probability. The proposed methodology provides a foundation for building an audio fingerprinting method based on fuzzy entropy.},
 bibtype = {article},
 author = {Moysis, Lazaros and Karasavvidis, Konstantinos and Kampelopoulos, Dimitris and Boursianis, Achilles D and Sotiroudis, Sotirios and Nikolaidis, Spiridon and Volos, Christos and Sarigiannidis, Panagiotis and Matin, Mohammad Abdul and Goudos, Sotirios K},
 doi = {10.3390/computers14020039},
 journal = {Computers},
 number = {2}
}

In this work, a comparison of Greek Orthodox religious chants is performed using fuzzy entropy. Using a dataset of chant performances, each recitation is segmented into overlapping time windows, and the fuzzy entropy of each window in the frequency domain is computed. We introduce a novel audio fingerprinting framework by comparing the variations in the resulting fuzzy entropy vector for the dataset. For this purpose, we use the correlation coefficient as a measure and dynamic time warping. Thus, it is possible to match the performances of the same chant with high probability. The proposed methodology provides a foundation for building an audio fingerprinting method based on fuzzy entropy.

@article{
 title = {Testing the Strength of Chaotic Systems as Seeds in a Pseudo Random Bit Generator},
 type = {article},
 year = {2025},
 keywords = {Chaos,discrete map,encryption,pseudo random bit ge},
 pages = {23645-23657},
 volume = {13},
 id = {b31248c0-2440-3088-9f3c-b50a82b4fc35},
 created = {2025-01-31T07:27:30.584Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-02-11T08:05:14.043Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10858710},
 source_type = {article},
 private_publication = {false},
 abstract = {Chaotic random bit generators have become an integral part of chaotic cryptography and other data protection applications, where they are used as sources of deterministic randomness, to secure an information signal. The performance of the generator though will be heavily affected by the chaotic system that is chosen. The statistical performance, key space size, operations per bit ratio, and speed, are all aspects affected by the chosen system. Thus, the same bit generator will vary in efficiency under different chaotic maps. Driven by these facts, this work studies the performance of a common modulo-based bit generator under different chaotic maps. First, the structure of the bit generator’s nonlinear hash is studied. Then, using a collection of different maps, the generator is evaluated with respect to randomness, key space size, operations per bit ratio, and execution speed. The comparison results are evaluated, to provide a series of observations regarding the use of chaotic systems in bit generators. These observations can serve as guidelines for all future chaotic encryption algorithms, and chaos-based security-related applications in general.},
 bibtype = {article},
 author = {Moysis, Lazaros and Lawnik, Marcin and Volos, Christos and Baptista, Murilo S and Goudos, Sotirios K and Fragulis, George F},
 doi = {10.1109/ACCESS.2025.3537182},
 journal = {IEEE Access}
}

Chaotic random bit generators have become an integral part of chaotic cryptography and other data protection applications, where they are used as sources of deterministic randomness, to secure an information signal. The performance of the generator though will be heavily affected by the chaotic system that is chosen. The statistical performance, key space size, operations per bit ratio, and speed, are all aspects affected by the chosen system. Thus, the same bit generator will vary in efficiency under different chaotic maps. Driven by these facts, this work studies the performance of a common modulo-based bit generator under different chaotic maps. First, the structure of the bit generator’s nonlinear hash is studied. Then, using a collection of different maps, the generator is evaluated with respect to randomness, key space size, operations per bit ratio, and execution speed. The comparison results are evaluated, to provide a series of observations regarding the use of chaotic systems in bit generators. These observations can serve as guidelines for all future chaotic encryption algorithms, and chaos-based security-related applications in general.

@inproceedings{
 title = {mm-Wave Metamaterial Antenna Design with Superstrate for B5G FR3 Bands Using Osprey Optimization Algorithm},
 type = {inproceedings},
 year = {2025},
 keywords = {6G mobile communication;Design methodology;Confere},
 pages = {1-4},
 id = {c0b72040-4066-3317-b4e1-418072f9bf8a},
 created = {2025-03-24T21:32:04.199Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-03-24T21:32:04.199Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10931225},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this work, we present an antenna design for operation between 21 and 23 GHz in the FR3 band for B5G and 6G operation. The proposed antenna uses a metamaterial super-strate for gain and bandwidth enhancement. We optimize the geometrical parameters using a recently proposed evolutionary algorithm, namely the Osprey Optimization Algorithm (OOA), which imitates the behavior of osprey in nature. The OOA finds a design with wideband operation and gain enchantment. The proposed low-profile antenna yields a peak gain of about 8.9 dBi around 22 GHz. The antenna exhibits a frequency band with a $S_11 < -10 d B$ ranging from 19.21 to 23.38 GHz.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Boursianis, Achilles D and Koulouridis, Stavros and Zaharis, Zaharias D and Christodoulou, Christos G and Goudos, Sotirios K},
 doi = {10.1109/iWAT64079.2025.10931225},
 booktitle = {2025 IEEE International Workshop on Antenna Technology (iWAT)}
}

In this work, we present an antenna design for operation between 21 and 23 GHz in the FR3 band for B5G and 6G operation. The proposed antenna uses a metamaterial super-strate for gain and bandwidth enhancement. We optimize the geometrical parameters using a recently proposed evolutionary algorithm, namely the Osprey Optimization Algorithm (OOA), which imitates the behavior of osprey in nature. The OOA finds a design with wideband operation and gain enchantment. The proposed low-profile antenna yields a peak gain of about 8.9 dBi around 22 GHz. The antenna exhibits a frequency band with a $S_11 < -10 d B$ ranging from 19.21 to 23.38 GHz.

@article{
 title = {Design of an Ultra-thin Metamaterial Absorber with Machine Learning-Assisted Absorption Prediction},
 type = {article},
 year = {2025},
 keywords = {Absorption;Metamaterials;Machine learning;Electrom},
 pages = {1-15},
 id = {22037c8e-889b-3b31-a346-2ba2a0a0b1d2},
 created = {2025-03-26T20:11:57.284Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-03-26T20:11:57.284Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10938846},
 source_type = {article},
 private_publication = {false},
 abstract = {An absorber is a block of material employed to absorb a portion of the energy of an incident particle. Research on absorbers is rapidly expanding as a result of their prospective applications in several fields, including wireless communications and military purposes. However, conventional absorbers have dense size and design complexity that make them unsuitable for a multitude of practical applications. Metamaterial-based absorbers (MMAs) have garnered significant attention with respect to their low density, narrow layers, and high absorption capacity. In this paper, we introduce a new ultra-thin trilayered Ni–MgF2–Ni metamaterial absorber structure, which is designed using machine learning. It has a balanced and symmetrical layout with a metal-dielectric-metal arrangement and a high-temperature endurance. Its resonator design is defined by mathematical deduction from the Conference matrix. The performance of MMA has been evaluated at wavelengths ranging from 250 nm to 1150 nm, as well as in various modes-TM, TE, and TEM. The results demonstrate that the proposed MMA has exceptional absorption capacities, with an overall absorption of 96.18% within the test range. It offers excellent mean absorption percentages of 99% in the optical region (350 to 750 nm), 95.23% in the ultraviolet (UV) range, and 94.38% in the near-infrared (NIR) range. Furthermore, MMA exhibits an absorption efficiency of 99.99% at a particular wavelength of 424.93 nm. In this work, various machine learning techniques have been applied to predict the absorption of the proposed MMA design. The XGBoost meta-learner-based Stacking ensemble machine learning technique achieves the highest prediction efficiency. Finally, the explainable AI technique with the LIME framework has been used to analyze the predictions of applied machine learning models.},
 bibtype = {article},
 author = {Hossain, Md. Jakir and Mubashsara, Nafisa and Khan, Riasat and Matin, Mohammad Abdul and Sarigiannidis, Panagiotis and Goudos, Sotirios K},
 doi = {10.1109/TAI.2025.3554732},
 journal = {IEEE Transactions on Artificial Intelligence}
}

An absorber is a block of material employed to absorb a portion of the energy of an incident particle. Research on absorbers is rapidly expanding as a result of their prospective applications in several fields, including wireless communications and military purposes. However, conventional absorbers have dense size and design complexity that make them unsuitable for a multitude of practical applications. Metamaterial-based absorbers (MMAs) have garnered significant attention with respect to their low density, narrow layers, and high absorption capacity. In this paper, we introduce a new ultra-thin trilayered Ni–MgF2–Ni metamaterial absorber structure, which is designed using machine learning. It has a balanced and symmetrical layout with a metal-dielectric-metal arrangement and a high-temperature endurance. Its resonator design is defined by mathematical deduction from the Conference matrix. The performance of MMA has been evaluated at wavelengths ranging from 250 nm to 1150 nm, as well as in various modes-TM, TE, and TEM. The results demonstrate that the proposed MMA has exceptional absorption capacities, with an overall absorption of 96.18% within the test range. It offers excellent mean absorption percentages of 99% in the optical region (350 to 750 nm), 95.23% in the ultraviolet (UV) range, and 94.38% in the near-infrared (NIR) range. Furthermore, MMA exhibits an absorption efficiency of 99.99% at a particular wavelength of 424.93 nm. In this work, various machine learning techniques have been applied to predict the absorption of the proposed MMA design. The XGBoost meta-learner-based Stacking ensemble machine learning technique achieves the highest prediction efficiency. Finally, the explainable AI technique with the LIME framework has been used to analyze the predictions of applied machine learning models.

@article{
 title = {Ultra-Wideband Antenna Design for 5G NR Using the Bezier Search Differential Evolution Algorithm},
 type = {article},
 year = {2025},
 volume = {13},
 websites = {https://www.mdpi.com/2227-7080/13/4/133},
 id = {a958f943-0159-3218-9bf1-4897147d9996},
 created = {2025-04-01T07:54:44.123Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-04-01T07:54:44.123Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies13040133},
 source_type = {article},
 private_publication = {false},
 abstract = {As the energy crisis is leading to energy shortages and constant increases in prices, green energy and renewable energy sources are trending as a viable solution to this problem. One of the most rapidly expanding green energy methods is RF (RadioFrequency) energy harvesting, as RF energy and its corresponding technologies are constantly progressing, due to the introduction of 5G and high-speed telecommunications. The usual system for RF energy harvesting is called a rectenna, and one of its main components is an antenna, responsible for collecting ambient RF energy. In this paper, the optimization process of an ultra-wideband antenna for RF energy harvesting applications was studied, with the main goal of broadening the antenna’s operational bandwidth to include 5G New Radio. For this purpose, the Bezier Search Differential Evolution Algorithm (BeSD) was used along with a novel CST-Matlab API, to manipulate the degrees of freedom of the antenna, while searching for the optimal result, which would satisfy all the necessary dependencies to make it capable of harvesting RF energy in the target frequency band. The BeSD algorithm was first tested with benchmark functions and compared to other widely used algorithms, which it successfully outperformed, and hence, it was selected as the optimizer for this research. All in all, the optimization process was successful by producing an ultra-wideband optimal antenna operating from 1.4 GHz to 3.9 GHz, which includes all vastly used telecommunication technologies, like GSM (1.8 GHz), UMTS (2.1 GHz), Wi-Fi (2.4 GHz), LTE (2.6 GHz), and 5G NR (3.5 GHz). Its ultra-wideband properties and the rest of the characteristics that make this design suitable for RF energy harvesting are proven by its S11 response graph, its impedance response graph, its efficiency on the targeted technologies, and its omnidirectionality across its band of operation.},
 bibtype = {article},
 author = {Korompilis, Georgios and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Zaharis, Zaharias D and Siakavara, Katherine and Papadopoulou, Maria S and Matin, Mohammad Abdul and Goudos, Sotirios K},
 doi = {10.3390/technologies13040133},
 journal = {Technologies},
 number = {4}
}

As the energy crisis is leading to energy shortages and constant increases in prices, green energy and renewable energy sources are trending as a viable solution to this problem. One of the most rapidly expanding green energy methods is RF (RadioFrequency) energy harvesting, as RF energy and its corresponding technologies are constantly progressing, due to the introduction of 5G and high-speed telecommunications. The usual system for RF energy harvesting is called a rectenna, and one of its main components is an antenna, responsible for collecting ambient RF energy. In this paper, the optimization process of an ultra-wideband antenna for RF energy harvesting applications was studied, with the main goal of broadening the antenna’s operational bandwidth to include 5G New Radio. For this purpose, the Bezier Search Differential Evolution Algorithm (BeSD) was used along with a novel CST-Matlab API, to manipulate the degrees of freedom of the antenna, while searching for the optimal result, which would satisfy all the necessary dependencies to make it capable of harvesting RF energy in the target frequency band. The BeSD algorithm was first tested with benchmark functions and compared to other widely used algorithms, which it successfully outperformed, and hence, it was selected as the optimizer for this research. All in all, the optimization process was successful by producing an ultra-wideband optimal antenna operating from 1.4 GHz to 3.9 GHz, which includes all vastly used telecommunication technologies, like GSM (1.8 GHz), UMTS (2.1 GHz), Wi-Fi (2.4 GHz), LTE (2.6 GHz), and 5G NR (3.5 GHz). Its ultra-wideband properties and the rest of the characteristics that make this design suitable for RF energy harvesting are proven by its S11 response graph, its impedance response graph, its efficiency on the targeted technologies, and its omnidirectionality across its band of operation.

@article{
 title = {Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation},
 type = {article},
 year = {2025},
 keywords = {Security;Computer security;Heuristic algorithms;Co},
 pages = {65216-65231},
 volume = {13},
 id = {d5640e9c-013f-38d5-994b-7469e0dcea74},
 created = {2025-04-18T19:00:19.107Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-04-18T19:00:19.107Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10960450},
 source_type = {article},
 private_publication = {false},
 abstract = {In the face of increasingly sophisticated and dynamic cyber threats, policy-based cybersecurity deployment has emerged as a critical strategy for securing modern, complex network infrastructures. This approach enables organizations to enforce adaptable, scalable and context-aware security policies that can dynamically respond to evolving threats and operational demands. However, the growing complexity of distributed systems and the interdependencies between diverse security components present significant challenges in ensuring consistent and efficient policy enforcement. Static and centralized security models are no longer sufficient to address these challenges, underscoring the need for intelligent, distributed solutions that can optimize policy deployment in real-time. This paper introduces a novel framework based on Message Passing algorithms that enables decentralized, adapted and optimized policy deployment across complex cybersecurity infrastructures. More specifically, we extend the traditional Min-Sum algorithm by incorporating dynamic trust weights that influence policy enforcement decisions, allowing more reliable nodes to have a greater impact while mitigating the risks posed by untrusted entities. The proposed framework is designed to handle large-scale network environments with minimal computational overhead, relying on localized message exchanges instead of centralized computations. We benchmark our framework against state-of-the-art approaches, demonstrating that the proposed framework achieves lower total enforcement cost while significantly improving convergence speed, particularly in heterogeneous trust environments. Finally, we provide an in-depth evaluation of how trust heterogeneity influences security policy enforcement. Extensive simulations were conducted to evaluate the framework’s effectiveness in optimizing policy deployment for varying network topologies, demonstrating significant improvements in threat detection accuracy, policy consistency and resource efficiency across diverse and dynamic network environments.},
 bibtype = {article},
 author = {Evangelatos, Spyridon and Veroni, Eleni and Konidi, Mariza and Karagiorgou, Sophia and Dede, Georgia and Baklezos, Anargyros and Nikolopoulos, Christos and Sarigiannidis, Panagiotis and Goudos, Sotirios K},
 doi = {10.1109/ACCESS.2025.3559428},
 journal = {IEEE Access}
}

In the face of increasingly sophisticated and dynamic cyber threats, policy-based cybersecurity deployment has emerged as a critical strategy for securing modern, complex network infrastructures. This approach enables organizations to enforce adaptable, scalable and context-aware security policies that can dynamically respond to evolving threats and operational demands. However, the growing complexity of distributed systems and the interdependencies between diverse security components present significant challenges in ensuring consistent and efficient policy enforcement. Static and centralized security models are no longer sufficient to address these challenges, underscoring the need for intelligent, distributed solutions that can optimize policy deployment in real-time. This paper introduces a novel framework based on Message Passing algorithms that enables decentralized, adapted and optimized policy deployment across complex cybersecurity infrastructures. More specifically, we extend the traditional Min-Sum algorithm by incorporating dynamic trust weights that influence policy enforcement decisions, allowing more reliable nodes to have a greater impact while mitigating the risks posed by untrusted entities. The proposed framework is designed to handle large-scale network environments with minimal computational overhead, relying on localized message exchanges instead of centralized computations. We benchmark our framework against state-of-the-art approaches, demonstrating that the proposed framework achieves lower total enforcement cost while significantly improving convergence speed, particularly in heterogeneous trust environments. Finally, we provide an in-depth evaluation of how trust heterogeneity influences security policy enforcement. Extensive simulations were conducted to evaluate the framework’s effectiveness in optimizing policy deployment for varying network topologies, demonstrating significant improvements in threat detection accuracy, policy consistency and resource efficiency across diverse and dynamic network environments.

@article{
 title = {Exploiting Circular Shifts for Efficient Chaotic Image Encryption},
 type = {article},
 year = {2025},
 keywords = {Chaotic communication,Encryption,Generato,Security},
 pages = {92997 - 93016},
 volume = {13},
 id = {81cc667e-e817-3746-8716-d23aff746ce6},
 created = {2025-05-24T07:47:13.202Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-06-05T09:57:36.413Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11009169},
 source_type = {article},
 private_publication = {false},
 abstract = {This work presents a chaotic image encryption algorithm that acts on the binary level of the image for effective permutation, and on the byte level for substitution. The permutation step combines actions of bit level rearranging, and bit shuffling. Circular shift operations are used for bit shuffling, to reduce the execution time. Circular shifts are also applied to shuffle the permutation and substitution rules, effectively increasing security at a very low execution cost. The encryption keys are plaintext dependent, and a key mixing step in included, so that each part of the key affects all the subsequent encryption operations. For the encryption, a new Soboleva hyperbolic tangent based map is first designed. The dynamical behavior of the map is studied and shows robust chaos, and an absence of equilibria, meaning that it can generate hidden attractors. This map is used as an entropy source, along with a chaotic pseudo random number generator. The encryption process shows a good performance under a collection of tests, and has also a low execution time, 0.0134 sec for a 256x256 image, 0.0530 sec for a 512x512 image, and 0.2050 sec for a 1024x1024 image.},
 bibtype = {article},
 author = {Moysis, Lazaros and Lawnik, Marcin and Alexan, Wassim and Goudos, Sotirios K and Baptista, Murilo S and Fragulis, George F},
 doi = {10.1109/ACCESS.2025.3572589},
 journal = {IEEE Access}
}

This work presents a chaotic image encryption algorithm that acts on the binary level of the image for effective permutation, and on the byte level for substitution. The permutation step combines actions of bit level rearranging, and bit shuffling. Circular shift operations are used for bit shuffling, to reduce the execution time. Circular shifts are also applied to shuffle the permutation and substitution rules, effectively increasing security at a very low execution cost. The encryption keys are plaintext dependent, and a key mixing step in included, so that each part of the key affects all the subsequent encryption operations. For the encryption, a new Soboleva hyperbolic tangent based map is first designed. The dynamical behavior of the map is studied and shows robust chaos, and an absence of equilibria, meaning that it can generate hidden attractors. This map is used as an entropy source, along with a chaotic pseudo random number generator. The encryption process shows a good performance under a collection of tests, and has also a low execution time, 0.0134 sec for a 256x256 image, 0.0530 sec for a 512x512 image, and 0.2050 sec for a 1024x1024 image.

@article{
 title = {Artificial Intelligence-Empowered Embryo Selection for IVF Applications: A Methodological Review},
 type = {article},
 year = {2025},
 volume = {7},
 websites = {https://www.mdpi.com/2504-4990/7/2/56},
 id = {2f3234e1-02e4-3ce5-9e4b-6086c7a54c10},
 created = {2025-06-17T09:09:55.141Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-06-17T09:09:55.141Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {make7020056},
 source_type = {article},
 private_publication = {false},
 abstract = {In vitro fertilization (IVF) is a well-established and efficient assisted reproductive technology (ART). However, it requires a series of costly and non-trivial procedures, and the success rate still needs improvement. Thus, increasing the success rate, simplifying the process, and reducing costs are all essential challenges of IVF. These can be addressed by integrating artificial intelligence techniques, like deep learning (DL), with several aspects of the IVF process. DL techniques can help extract important features from the data, support decision making, and perform several other tasks, as architectures can be adapted to different problems. The emergence of AI in the medical field has seen a rise in DL-supported tools for embryo selection. In this work, recent advances in the use of AI and DL-based embryo selection for IVF are reviewed. The different architectures that have been considered so far for each task are presented. Furthermore, future challenges for artificial intelligence-based ARTs are outlined.},
 bibtype = {article},
 author = {Moysis, Lazaros and Iliadis, Lazaros Alexios and Vergos, George and Sotiroudis, Sotirios P and Boursianis, Achilles D and Papatheodorou, Achilleas and Kokkinidis, Konstantinos-Iraklis D and Abdul Matin, Mohammad and Sarigiannidis, Panagiotis and Siniosoglou, Ilias and Argyriou, Vasileios and Goudos, Sotirios K},
 doi = {10.3390/make7020056},
 journal = {Machine Learning and Knowledge Extraction},
 number = {2}
}

In vitro fertilization (IVF) is a well-established and efficient assisted reproductive technology (ART). However, it requires a series of costly and non-trivial procedures, and the success rate still needs improvement. Thus, increasing the success rate, simplifying the process, and reducing costs are all essential challenges of IVF. These can be addressed by integrating artificial intelligence techniques, like deep learning (DL), with several aspects of the IVF process. DL techniques can help extract important features from the data, support decision making, and perform several other tasks, as architectures can be adapted to different problems. The emergence of AI in the medical field has seen a rise in DL-supported tools for embryo selection. In this work, recent advances in the use of AI and DL-based embryo selection for IVF are reviewed. The different architectures that have been considered so far for each task are presented. Furthermore, future challenges for artificial intelligence-based ARTs are outlined.

@article{
 title = {Resource Efficient Federated LoRaWAN Architecture for Far-Edge IoT Applications},
 type = {article},
 year = {2025},
 keywords = {Federated learning,Internet of Things,LoRaWAN,Smar},
 pages = {108766-108785},
 volume = {13},
 id = {3cc7b4d1-b323-31b2-8f24-c569558fcc33},
 created = {2025-06-18T06:29:11.787Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-06-29T16:49:58.802Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11037774},
 source_type = {article},
 private_publication = {false},
 abstract = {This study introduces an innovative, resource-efficient architecture that incorporates advanced technologies to create a lightweight, flexible, and scalable framework for remote and limited data collecting and processing in next-generation Internet of Things (IoT) applications. It specifically proposes an integrated Federated LoRaWAN (LoRA-FL) system that combines hierarchical, privacy-preserving Federated Learning (FL), Knowledge Distillation (KD), and a customised Medium Access Control (MAC) protocol, identified as FCA-LoRa, to address the significant limitations of LoRaWAN networks. These encompass strict duty cycle rules, restricted bandwidth, and energy limitations, elements that conventionally hinder the implementation of intelligent IoT devices in rural or isolated settings. The proposed architecture features a hierarchical FL approach enabling multi-tier Artificial Intelligence (AI) model aggregation across edge nodes, gateways, and a central server. The effectiveness of the proposed system is confirmed by two practical applications, smart agriculture and smart livestock farming, which exemplify standard situations for far-edge intelligence. The results indicate that the distilled model consistently attains over 90% packet delivery success, illustrating the architecture’s capacity to provide scalable and energy-efficient intelligence at the edge. This research addresses a significant gap in previous studies that frequently examine FL, communication optimisation, and model compression independently. This study offers a comprehensive, implementable approach that tackles model scalability, and network-layer issues within a cohesive architecture, enhancing the practical implementation of AI-driven IoT deployments over LoRaWAN.},
 bibtype = {article},
 author = {Triantafyllou, Anna and Siniosoglou, Ilias and Argyriou, Vasileios and Goudos, Sotirios K and Papadopoulos, Georgios Th. and Panitsidis, Konstantinos and Sarigiannidis, Panagiotis},
 doi = {10.1109/ACCESS.2025.3580375},
 journal = {IEEE Access}
}

This study introduces an innovative, resource-efficient architecture that incorporates advanced technologies to create a lightweight, flexible, and scalable framework for remote and limited data collecting and processing in next-generation Internet of Things (IoT) applications. It specifically proposes an integrated Federated LoRaWAN (LoRA-FL) system that combines hierarchical, privacy-preserving Federated Learning (FL), Knowledge Distillation (KD), and a customised Medium Access Control (MAC) protocol, identified as FCA-LoRa, to address the significant limitations of LoRaWAN networks. These encompass strict duty cycle rules, restricted bandwidth, and energy limitations, elements that conventionally hinder the implementation of intelligent IoT devices in rural or isolated settings. The proposed architecture features a hierarchical FL approach enabling multi-tier Artificial Intelligence (AI) model aggregation across edge nodes, gateways, and a central server. The effectiveness of the proposed system is confirmed by two practical applications, smart agriculture and smart livestock farming, which exemplify standard situations for far-edge intelligence. The results indicate that the distilled model consistently attains over 90% packet delivery success, illustrating the architecture’s capacity to provide scalable and energy-efficient intelligence at the edge. This research addresses a significant gap in previous studies that frequently examine FL, communication optimisation, and model compression independently. This study offers a comprehensive, implementable approach that tackles model scalability, and network-layer issues within a cohesive architecture, enhancing the practical implementation of AI-driven IoT deployments over LoRaWAN.

@article{
 title = {Detection of Wild Mushrooms Using Machine Learning and Computer Vision},
 type = {article},
 year = {2025},
 volume = {16},
 websites = {https://www.mdpi.com/2078-2489/16/7/539},
 id = {833d06e0-29ec-3a6f-8e60-c09c40b269a2},
 created = {2025-06-25T19:38:51.957Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-06-25T19:38:51.957Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {info16070539},
 source_type = {article},
 private_publication = {false},
 abstract = {The increasing global demand for sustainable and high-quality agricultural products has driven interest in precision agriculture technologies. This study presents a novel approach to wild mushroom detection, particularly focusing on Macrolepiota procera as a focal species for demonstration and benchmarking. The proposed approach utilises unmanned aerial vehicles (UAVs) equipped with multispectral imaging and the YOLOv5 object detection algorithm. A custom dataset, the wild mushroom detection dataset (WOES), comprising 907 annotated aerial and ground images, was developed to support model training and evaluation. Our method integrates low-cost hardware with advanced deep learning and vegetation index analysis (NDRE) to enable real-time identification of mushrooms in forested environments. The proposed system achieved an identification accuracy exceeding 90% and completed detection tasks within 30 min per field survey. Although the dataset is geographically limited to Western Macedonia, Greece, and focused primarily on a morphologically distinctive species, the methodology is designed to be extendable to other wild mushroom types. This work contributes a replicable framework for scalable, cost-effective mushroom monitoring in ecological and agricultural applications.},
 bibtype = {article},
 author = {Chaschatzis, Christos and Karaiskou, Chrysoula and Iakovidou, Chryssanthi and Radoglou-Grammatikis, Panagiotis and Bibi, Stamatia and Goudos, Sotirios K and Sarigiannidis, Panagiotis G},
 doi = {10.3390/info16070539},
 journal = {Information},
 number = {7}
}

The increasing global demand for sustainable and high-quality agricultural products has driven interest in precision agriculture technologies. This study presents a novel approach to wild mushroom detection, particularly focusing on Macrolepiota procera as a focal species for demonstration and benchmarking. The proposed approach utilises unmanned aerial vehicles (UAVs) equipped with multispectral imaging and the YOLOv5 object detection algorithm. A custom dataset, the wild mushroom detection dataset (WOES), comprising 907 annotated aerial and ground images, was developed to support model training and evaluation. Our method integrates low-cost hardware with advanced deep learning and vegetation index analysis (NDRE) to enable real-time identification of mushrooms in forested environments. The proposed system achieved an identification accuracy exceeding 90% and completed detection tasks within 30 min per field survey. Although the dataset is geographically limited to Western Macedonia, Greece, and focused primarily on a morphologically distinctive species, the methodology is designed to be extendable to other wild mushroom types. This work contributes a replicable framework for scalable, cost-effective mushroom monitoring in ecological and agricultural applications.

@inproceedings{
 title = {A Generalized Attention Deficit Disorder Chaotic Model With Soboleva Hyperbolic Tangent Functions},
 type = {inproceedings},
 year = {2025},
 keywords = {Chaos;Attenuators;Analytical models;Sensitivity;Ci},
 pages = {1-4},
 id = {4342f1f8-c093-3b0a-91f1-243d1fef324d},
 created = {2025-07-23T06:31:36.327Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.327Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083897},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work studies the problem of modeling Attention Deficit Disorder (ADD) using a previously reported one dimensional map, but by replacing its two hyperbolic tangent activation functions, with Soboleva hyperbolic tangent ones. This adds four new control parameters to the system, which significantly enhances its modeling freedom. Afterwards, the effect of these parameters on the model is studied, using tools of nonlinear analysis, like bifurcation, Lyapunov exponent, and phase diagrams. The emergence of chaos is prevalent, indicating the sensitivity of the model to external excitations. Numerous phenomena are also observed, like crisis, antimonotonicity, and shrimps. This new model can help delve deeper into the emergence of chaos in behavioral disorders.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Lawnik, Marcin and Kollias, Konstantinos-Filippos and Volos, Christos and Baptista, Murilo S and Goudos, Sotirios and Radoglou-Grammatikis, Panagiotis and Mourikis, Evangelos and Sarigiannidis, Panagiotis and Fragulis, George F},
 doi = {10.1109/MOCAST65744.2025.11083897},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

This work studies the problem of modeling Attention Deficit Disorder (ADD) using a previously reported one dimensional map, but by replacing its two hyperbolic tangent activation functions, with Soboleva hyperbolic tangent ones. This adds four new control parameters to the system, which significantly enhances its modeling freedom. Afterwards, the effect of these parameters on the model is studied, using tools of nonlinear analysis, like bifurcation, Lyapunov exponent, and phase diagrams. The emergence of chaos is prevalent, indicating the sensitivity of the model to external excitations. Numerous phenomena are also observed, like crisis, antimonotonicity, and shrimps. This new model can help delve deeper into the emergence of chaos in behavioral disorders.

@inproceedings{
 title = {Traffic Sign Recognition for Level-3 Autonomy: Efficient Deep Learning for Class-Imbalanced Datasets},
 type = {inproceedings},
 year = {2025},
 keywords = {Deep learning;Accuracy;Computational modeling;Road},
 pages = {1-5},
 id = {21ec0fdd-194e-38e5-8fe8-ed7cace69a6b},
 created = {2025-07-23T06:31:36.422Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.422Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083730},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Mita, Myrsini E and Iliadis, Lazaros A and Sotiroudis, Sotirios P and Boursianis, Achilles D and Papadopoulou, Maria S and Goudos, Sotirios K},
 doi = {10.1109/MOCAST65744.2025.11083730},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

@inproceedings{
 title = {Efficient Chaotic Image Encryption with Circular Shifting and Soboleva-Modulo Map},
 type = {inproceedings},
 year = {2025},
 keywords = {Resistance;Chaos;Circuits and systems;Generators;E},
 pages = {1-4},
 id = {973e515d-bacd-393e-96a6-7ff6b0d561f0},
 created = {2025-07-23T06:31:36.508Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.508Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083907},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work presents a chaotic image encryption algorithm that acts on the binary level of the image for effective permutation, and on the byte level for substitution. The permutation step combines actions of bit plane rearranging, and bit shuffling via circular shift operations, to reduce the execution time. For the encryption, a Soboleva hyperbolic tangent based map is used, along with a chaotic pseudo random number generator. The encryption process shows a good performance under various tests, and has also a low execution time, 0.0145s for a $256 \times 256$ image, and 0.0565 s for a $512 \times 512$ image.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Lawnik, Marcin and Alexan, Wassim and Goudos, Sotirios and Baptista, Murilo S and Fragulis, George F},
 doi = {10.1109/MOCAST65744.2025.11083907},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

This work presents a chaotic image encryption algorithm that acts on the binary level of the image for effective permutation, and on the byte level for substitution. The permutation step combines actions of bit plane rearranging, and bit shuffling via circular shift operations, to reduce the execution time. For the encryption, a Soboleva hyperbolic tangent based map is used, along with a chaotic pseudo random number generator. The encryption process shows a good performance under various tests, and has also a low execution time, 0.0145s for a $256 \times 256$ image, and 0.0565 s for a $512 \times 512$ image.

@inproceedings{
 title = {Integrated IoT and AI-Driven Smart Refrigerator System},
 type = {inproceedings},
 year = {2025},
 keywords = {Temperature measurement;Temperature distribution;E},
 pages = {1-4},
 id = {5681f657-8d6d-3673-84e2-ad4c642479e8},
 created = {2025-07-23T06:31:36.614Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.614Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083919},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Toliopoulos, Dimitrios and Demkas, Efthimios and Hatzopoulos, Argyrios T and Tsiakmakis, Kyriakos and Boursianis, Achilles D and Nikolaidis, Spyridon and Goudos, Sotirios K and Papadopoulou, Maria S},
 doi = {10.1109/MOCAST65744.2025.11083919},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

@inproceedings{
 title = {ML Methods for SNR Prediction in Vehicular Communications},
 type = {inproceedings},
 year = {2025},
 keywords = {Radio frequency;Maximum likelihood estimation;Accu},
 pages = {1-4},
 id = {5d22b672-34e7-3d02-b6ec-c3a195044ca1},
 created = {2025-07-23T06:31:36.671Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.671Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083927},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Vehicular communication technology serves as a cornerstone of Intelligent Transportation Systems (ITS), enabling efficient data exchange between vehicles (V 2 V) and between vehicles and infrastructure (V2I). This advanced communication paradigm is integral to enhancing traffic flow management, augmenting road safety, and optimizing vehicular operations, thereby transforming contemporary transportation systems. The effectiveness of ITS is contingent on a high-speed, low-latency communication framework that ensures the seamless and realtime transmission of critical vehicular and environmental data, thereby fostering adaptive and resilient network functionality. This research undertakes a rigorous analysis of diverse machine learning (ML) approaches to develop predictive models for estimating the Signal-to-Noise Ratio (SNR) in V2I communication networks.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Boursianis, Achilles D and Papadopoulou, Maria S and Lagkas, Thomas and Sarigiannidis, Panagiotis and Goudos, Sotirios K},
 doi = {10.1109/MOCAST65744.2025.11083927},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Vehicular communication technology serves as a cornerstone of Intelligent Transportation Systems (ITS), enabling efficient data exchange between vehicles (V 2 V) and between vehicles and infrastructure (V2I). This advanced communication paradigm is integral to enhancing traffic flow management, augmenting road safety, and optimizing vehicular operations, thereby transforming contemporary transportation systems. The effectiveness of ITS is contingent on a high-speed, low-latency communication framework that ensures the seamless and realtime transmission of critical vehicular and environmental data, thereby fostering adaptive and resilient network functionality. This research undertakes a rigorous analysis of diverse machine learning (ML) approaches to develop predictive models for estimating the Signal-to-Noise Ratio (SNR) in V2I communication networks.

@inproceedings{
 title = {Two-Layered Ultra-Wideband and High-Gain Metamaterial Antenna for 5G Ka-Band Applications Using the Mountain Gazelle Optimizer},
 type = {inproceedings},
 year = {2025},
 keywords = {Bandwidth;Metasurfaces;Metamaterials;Ultra wideban},
 pages = {1-4},
 id = {5fa3857e-7aef-306b-9f7d-0e1fca3a6d67},
 created = {2025-07-23T06:31:36.728Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-07-23T06:31:36.728Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083901},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {As the demand for higher speed telecommunications is growing faster and faster, telecommunications systems operating in higher frequencies are increasingly deployed. In this paper, a 5 G two-layered antenna with high-gain of 11.25 dB and ultra-wideband properties in the Ka-Band (bandwidth of 10 GHz, from 32.89 to 42.72 GHz) is proposed. This metamaterial antenna design is composed of a substrate and a superstrate, separated by an air gap, and a radiation element consisting of a central large patch, and a set of parasitic patches around it. The final design is the result of an optimization process, with the goal of achieving ultra-wideband properties, while maintaining the high-gain characteristic, in the 5 G Ka -Band. The Mountain Gazelle algorithm was used as an optimizer, due to its outstanding performance in latest research, as also confirmed from the optimal result produced in this research, which successfully operates from 32.89 to 42.72 GHz, while maintaining a high realized gain response, 11.25 dB.},
 bibtype = {inproceedings},
 author = {Korompilis, Georgios and Hlias, Tzouras and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Koulouridis, Stavros and Goudos, Sotirios K},
 doi = {10.1109/MOCAST65744.2025.11083901},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

As the demand for higher speed telecommunications is growing faster and faster, telecommunications systems operating in higher frequencies are increasingly deployed. In this paper, a 5 G two-layered antenna with high-gain of 11.25 dB and ultra-wideband properties in the Ka-Band (bandwidth of 10 GHz, from 32.89 to 42.72 GHz) is proposed. This metamaterial antenna design is composed of a substrate and a superstrate, separated by an air gap, and a radiation element consisting of a central large patch, and a set of parasitic patches around it. The final design is the result of an optimization process, with the goal of achieving ultra-wideband properties, while maintaining the high-gain characteristic, in the 5 G Ka -Band. The Mountain Gazelle algorithm was used as an optimizer, due to its outstanding performance in latest research, as also confirmed from the optimal result produced in this research, which successfully operates from 32.89 to 42.72 GHz, while maintaining a high realized gain response, 11.25 dB.

@inproceedings{
 title = {Novel Periodic Structure Design Using African Vultures Optimization Algorithm for Smart Electromagnetic Environments},
 type = {inproceedings},
 year = {2025},
 keywords = {Reflectivity;Radio frequency;Frequency selective s},
 pages = {1-4},
 id = {a23cf866-b43a-395f-815a-11640660449b},
 created = {2025-07-23T06:31:36.763Z},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {11083909},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Frequency selective surfaces have been utilized in smart electromagnetic environments due to their diverse range of applications. The geometric configuration of these periodic structures can enable them to be used for reflectivity, absorption, or transmission of electromagnetic waves. In this work, we exploit their reflectivity in the Wi-Fi frequency bands $(2.4 \textGHz, 5$ GHz, and 6 GHz) and transmission in 5 G NR FR1 n78, 3.3 -3.8 GHz. A novel nature-inspired metaheuristic algorithm, i.e., the African Vultures optimization algorithm, has been assessed and exhibited satisfactory results in unimodal and multimodal functions. As a result, it is utilized as a promising candidate to optimize the geometry of the proposed surface. Numerical results demonstrate the effectiveness of the proposed approach in enhancing electromagnetic performance, validating its potential for real-world applications.},
 bibtype = {inproceedings},
 author = {Keramaris, Pavlos and Papadopoulou, Maria S and Sarigiannidis, Panagiotis and Samaras, Theodoros and Goudos, Sotirios K and Boursianis, Achilles D},
 doi = {10.1109/MOCAST65744.2025.11083909},
 booktitle = {2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Frequency selective surfaces have been utilized in smart electromagnetic environments due to their diverse range of applications. The geometric configuration of these periodic structures can enable them to be used for reflectivity, absorption, or transmission of electromagnetic waves. In this work, we exploit their reflectivity in the Wi-Fi frequency bands $(2.4 \textGHz, 5$ GHz, and 6 GHz) and transmission in 5 G NR FR1 n78, 3.3 -3.8 GHz. A novel nature-inspired metaheuristic algorithm, i.e., the African Vultures optimization algorithm, has been assessed and exhibited satisfactory results in unimodal and multimodal functions. As a result, it is utilized as a promising candidate to optimize the geometry of the proposed surface. Numerical results demonstrate the effectiveness of the proposed approach in enhancing electromagnetic performance, validating its potential for real-world applications.

@article{
 title = {Dynamic analysis of a generalized attention deficit disorder model with Soboleva activation functions},
 type = {article},
 year = {2025},
 volume = {35},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105012372367&doi=10.1063%2F5.0280557&partnerID=40&md5=20bae525f31515ee152eb533f6332049},
 id = {079265f7-8b1c-387a-969d-17ff3e87dec5},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-08-16T12:02:26.929Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Moysis2025},
 source_type = {article},
 user_context = {Article},
 notes = {Cited by: 0},
 private_publication = {false},
 abstract = {This work studies a modified chaotic neural network model consisting of two neurons for modeling attention deficit disorder. Considering an existing one-dimensional model from the literature, its two activation functions are replaced by the Soboleva hyperbolic tangent function. This change introduces four new control parameters to the system. The effect of these parameters on the system is extensively studied through a collection of phase, bifurcation, and Lyapunov exponent diagrams. Changing each of these parameters brings changes to the model’s behavior, so the modified model is a significant generalization of the original one. Many phenomena are observed, including period doubling route to chaos, period halving route to period-1, crisis, antimonotonicity, coexisting attractors, and shrimps. The newly introduced degrees of freedom could provide a new direction toward modeling behavioral disorders using different activation functions. © 2025 Author(s).},
 bibtype = {article},
 author = {Moysis, L and Lawnik, M and Kollias, K F and Baptista, M S and Goudos, S and Fragulis, G},
 doi = {10.1063/5.0280557},
 journal = {Chaos},
 number = {8}
}

This work studies a modified chaotic neural network model consisting of two neurons for modeling attention deficit disorder. Considering an existing one-dimensional model from the literature, its two activation functions are replaced by the Soboleva hyperbolic tangent function. This change introduces four new control parameters to the system. The effect of these parameters on the system is extensively studied through a collection of phase, bifurcation, and Lyapunov exponent diagrams. Changing each of these parameters brings changes to the model’s behavior, so the modified model is a significant generalization of the original one. Many phenomena are observed, including period doubling route to chaos, period halving route to period-1, crisis, antimonotonicity, coexisting attractors, and shrimps. The newly introduced degrees of freedom could provide a new direction toward modeling behavioral disorders using different activation functions. © 2025 Author(s).

@article{
 title = {Federated detection of open charge point protocol 1.6 cyberattacks},
 type = {article},
 year = {2025},
 volume = {5},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105012945844&doi=10.20517%2Fces.2025.04&partnerID=40&md5=2af114594af6c01400685b3d406e9bab},
 id = {554cbcd8-7d36-3664-8a29-bae790faab4c},
 created = {2025-08-17T21:31:46.881Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-08-17T21:31:46.881Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Dalamagkas2025},
 source_type = {article},
 user_context = {Article},
 notes = {Cited by: 0},
 private_publication = {false},
 abstract = {The ongoing electrification of the transportation sector requires the deployment of multiple Electric Vehicle (EV) charging stations across multiple locations. However, the EV charging stations introduce significant cyber-physical and privacy risks, given the presence of vulnerable communication protocols, such as the Open Charge Point Protocol (OCPP). Meanwhile, the Federated Learning (FL) paradigm showcases a novel approach for improved intrusion detection results that utilize multiple sources of Internet of Things data, while respecting the confidentiality of private information. This paper proposes an FL-based intrusion detection system, which leverages OCPP 1.6 network flows to detect OCPP 1.6 cyberattacks. The evaluation results showcase high detection performance of the proposed FL-based solution. © The Author(s) 2025.},
 bibtype = {article},
 author = {Dalamagkas, Christos and Radoglou-Grammatikis, Panagiotis and Bouzinis, Pavlos and Papadopoulos, Ioannis and Lagkas, Thomas and Argyriou, Vasileios and Goudos, Sotirios and Margounakis, Dimitrios and Fountoukidis, Eleftherios and Sarigiannidis, Panagiotis},
 doi = {10.20517/ces.2025.04},
 journal = {Complex Engineering Systems},
 number = {2}
}

The ongoing electrification of the transportation sector requires the deployment of multiple Electric Vehicle (EV) charging stations across multiple locations. However, the EV charging stations introduce significant cyber-physical and privacy risks, given the presence of vulnerable communication protocols, such as the Open Charge Point Protocol (OCPP). Meanwhile, the Federated Learning (FL) paradigm showcases a novel approach for improved intrusion detection results that utilize multiple sources of Internet of Things data, while respecting the confidentiality of private information. This paper proposes an FL-based intrusion detection system, which leverages OCPP 1.6 network flows to detect OCPP 1.6 cyberattacks. The evaluation results showcase high detection performance of the proposed FL-based solution. © The Author(s) 2025.

@article{
 title = {Trusted Edge Computing System Based on Intelligent Risk Detection for Smart IoT},
 type = {article},
 year = {2024},
 pages = {1445-1454},
 volume = {20},
 id = {a420b51f-9c22-3e45-a10d-8b1bb76fbb36},
 created = {2023-05-18T08:29:21.620Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-01-24T05:25:22.823Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10128754},
 source_type = {article},
 private_publication = {false},
 abstract = {The Internet of Things (IoT) mainly consists of a large number of Internet-connected devices. The proliferation of untrusted third-party IoT applications has led to an increase in IoT-based malware attacks. In addition, it is infeasible for the IoT devices to support the sophisticated detection systems due to the restricted resources. Edge computing is considered to be promising. It provides solutions to the data security and privacy leakage brought by untrusted third-party IoT applications. In this article, an intelligent trusted and secure edge computing (ITEC) system is proposed for IoT malware detection. In this system, a signature-based preidentification mechanism is built for matching and identifying the malicious behaviors of untrusted third-party IoT applications. A delay strategy is then embedded into the risk detection engine in order to “buy time” for threat analysis and rate-limit the impact of suspicious third-party IoT applications in the system. We conduct extensive experiments to verify the effectiveness of the ITEC system and show that we can achieve accuracies of up to 98.52%.},
 bibtype = {article},
 author = {Deng, Xiaoheng and Chen, Bin and Chen, Xuechen and Pei, Xinjun and Wan, Shaohua and Goudos, Sotirios K},
 doi = {10.1109/TII.2023.3245681},
 journal = {IEEE Transactions on Industrial Informatics},
 number = {2}
}

The Internet of Things (IoT) mainly consists of a large number of Internet-connected devices. The proliferation of untrusted third-party IoT applications has led to an increase in IoT-based malware attacks. In addition, it is infeasible for the IoT devices to support the sophisticated detection systems due to the restricted resources. Edge computing is considered to be promising. It provides solutions to the data security and privacy leakage brought by untrusted third-party IoT applications. In this article, an intelligent trusted and secure edge computing (ITEC) system is proposed for IoT malware detection. In this system, a signature-based preidentification mechanism is built for matching and identifying the malicious behaviors of untrusted third-party IoT applications. A delay strategy is then embedded into the risk detection engine in order to “buy time” for threat analysis and rate-limit the impact of suspicious third-party IoT applications in the system. We conduct extensive experiments to verify the effectiveness of the ITEC system and show that we can achieve accuracies of up to 98.52%.

@article{
 title = {Machine Learning for Smart Agriculture: A Comprehensive Survey},
 type = {article},
 year = {2024},
 pages = {2568-2588},
 volume = {5},
 id = {647856d0-5ab1-3109-9528-738e4b38510e},
 created = {2023-12-21T07:27:26.479Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-06-28T16:03:54.610Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10367758},
 source_type = {article},
 private_publication = {false},
 abstract = {As communication technologies and equipment evolve, smart assets become smarter. The agricultural industry is also evolving in line with the implementation of modern communication protocols, intelligent sensors, and equipment. This evolution is enabling large-scale agricultural production processes to operate independently, thus, securing the food supply chain for an ever-growing population. Data processing for such a system with multiple heterogeneous sources requires proper management for effective agricultural operations. Recognizing the advantages of Machine Learning(ML) in performing large-scale data processing, researchers are investigating the implementation of ML to design an effective intelligent agricultural architecture. The aim of this paper is to provide a thorough analysis of the state-of-the-art in smart agriculture, open challenges, and guidelines for the development of further enhanced smart agriculture systems. Specifically, we describe how ML is used to create intelligent agricultural systems supported by state-of-the-art technology.},
 bibtype = {article},
 author = {Mahmood, M Rezwanul and Matin, Mohammad Abdul and Goudos, Sotirios K and Karagiannidis, George},
 doi = {10.1109/TAI.2023.3345278},
 journal = {IEEE Transactions on Artificial Intelligence},
 number = {6}
}

As communication technologies and equipment evolve, smart assets become smarter. The agricultural industry is also evolving in line with the implementation of modern communication protocols, intelligent sensors, and equipment. This evolution is enabling large-scale agricultural production processes to operate independently, thus, securing the food supply chain for an ever-growing population. Data processing for such a system with multiple heterogeneous sources requires proper management for effective agricultural operations. Recognizing the advantages of Machine Learning(ML) in performing large-scale data processing, researchers are investigating the implementation of ML to design an effective intelligent agricultural architecture. The aim of this paper is to provide a thorough analysis of the state-of-the-art in smart agriculture, open challenges, and guidelines for the development of further enhanced smart agriculture systems. Specifically, we describe how ML is used to create intelligent agricultural systems supported by state-of-the-art technology.

@inbook{
 type = {inbook},
 year = {2024},
 pages = {423-454},
 websites = {https://ieeexplore.ieee.org/document/10368415},
 publisher = {IEEE},
 id = {05c840b8-fdea-3903-adaa-124b61106250},
 created = {2023-12-22T05:33:37.314Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10368415},
 source_type = {inbook},
 private_publication = {false},
 abstract = {Phased arrays have emerged as the most suitable antenna technology for several modern wireless communication applications which require highly flexible and high‐performing antennas capable of supporting real‐time adaptive beam reconfiguration, user tracking, and MIMO processing. Achieving these objectives with cost‐effective phased array layouts is crucial to minimize fabrication and maintenance costs. In recent decades, the need of inexpensive but high‐performance antenna systems has driven the research towards unconventional array architectures. Accordingly, a wide set of innovative developing design methodologies have been proposed to properly manage the additional degrees of freedoms which are not present in conventional architectures, such as the array element locations in sparse arrays, or the sub‐array configuration in clustered/tiled arrays. The objective of this Chapter is to review the recent advances and trends in the synthesis of unconventional architectures for wireless applications. Towards this end, the formulation of the associated synthesis problem is discussed, and the theoretical motivations, fundamentals, and applicative guidelines for current state‐of‐the‐art strategies in unconventional phased array synthesis for next generation wireless communications are illustrated.},
 bibtype = {inbook},
 author = {Anselmi, Nicola and Goudos, Sotirios and Oliveri, Giacomo and Poli, Lorenzo and Rocca, Paolo and Salucci, Marco and Massa, Andrea},
 doi = {10.1002/9781394191048.ch14},
 chapter = {Unconventional Array Architectures for Next Generation Wireless Communications},
 title = {Sparse Arrays for Radar, Sonar, and Communications}
}

Phased arrays have emerged as the most suitable antenna technology for several modern wireless communication applications which require highly flexible and high‐performing antennas capable of supporting real‐time adaptive beam reconfiguration, user tracking, and MIMO processing. Achieving these objectives with cost‐effective phased array layouts is crucial to minimize fabrication and maintenance costs. In recent decades, the need of inexpensive but high‐performance antenna systems has driven the research towards unconventional array architectures. Accordingly, a wide set of innovative developing design methodologies have been proposed to properly manage the additional degrees of freedoms which are not present in conventional architectures, such as the array element locations in sparse arrays, or the sub‐array configuration in clustered/tiled arrays. The objective of this Chapter is to review the recent advances and trends in the synthesis of unconventional architectures for wireless applications. Towards this end, the formulation of the associated synthesis problem is discussed, and the theoretical motivations, fundamentals, and applicative guidelines for current state‐of‐the‐art strategies in unconventional phased array synthesis for next generation wireless communications are illustrated.

@article{
 title = {Improving DOA Estimation via An Optimal Deep Residual Neural Network Classifier On Uniform Linear Arrays},
 type = {article},
 year = {2024},
 keywords = {Correla,Direction-of-arrival estimation,Estimation},
 pages = {460-473},
 volume = {5},
 id = {20f85cb3-000e-34a7-8fc5-7b74c8857c16},
 created = {2024-02-06T05:33:02.320Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-26T09:54:46.742Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10421782},
 source_type = {article},
 private_publication = {false},
 abstract = {The main objective of this work is to improve and evaluate the effectiveness of the neural network (NN) architecture in the domain of estimation of direction of arrival (DOA), with an emphasis on a multi-class classification task with grid resolutions of 0.25 and 0.1. Specifically, a comprehensive assessment is performed to determine the competence of a residual NN (ResNet) in predicting the angle of arrival (AOA) of intercepted signals. Such signals are received by a 16-element uniform linear array and are subjected to real-world noise conditions. To this end, the superiority of the ResNet architecture in DOA estimations is substantiated through a comparison analysis with two other highly recognized NNs, namely, the feed-forward NN and the convolutional NN. Numerical results indicate that the ResNet model exhibits notable precision in estimating the AOAs, across various classes within a broad spectrum, along with a rapid temporal response. Finally, it remains consistent and maintains its superior performance even for diverse incoming signals and significantly reduced SNRs.},
 bibtype = {article},
 author = {Kassir, Haya Al and Kantartzis, Nikolaos V and Lazaridis, Pavlos I and Sarigiannidis, Panagiotis and Goudos, Sotirios K and Christodoulou, Christos and Zaharis, Zaharias D},
 doi = {10.1109/OJAP.2024.3362061},
 journal = {IEEE Open Journal of Antennas and Propagation},
 number = {2}
}

The main objective of this work is to improve and evaluate the effectiveness of the neural network (NN) architecture in the domain of estimation of direction of arrival (DOA), with an emphasis on a multi-class classification task with grid resolutions of 0.25 and 0.1. Specifically, a comprehensive assessment is performed to determine the competence of a residual NN (ResNet) in predicting the angle of arrival (AOA) of intercepted signals. Such signals are received by a 16-element uniform linear array and are subjected to real-world noise conditions. To this end, the superiority of the ResNet architecture in DOA estimations is substantiated through a comparison analysis with two other highly recognized NNs, namely, the feed-forward NN and the convolutional NN. Numerical results indicate that the ResNet model exhibits notable precision in estimating the AOAs, across various classes within a broad spectrum, along with a rapid temporal response. Finally, it remains consistent and maintains its superior performance even for diverse incoming signals and significantly reduced SNRs.

@article{
 title = {Physics-informed surrogates for electromagnetic dynamics using Transformers and graph neural networks},
 type = {article},
 year = {2024},
 keywords = {electromagnetic wave propagation,finite difference time-domain analysis,neural nets},
 volume = {n/a},
 websites = {https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/mia2.12463},
 id = {5b4cfd1e-032b-34ed-84a2-7fbc394aa0c4},
 created = {2024-02-16T19:48:44.942Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-02-16T19:49:02.737Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {https://doi.org/10.1049/mia2.12463},
 source_type = {article},
 private_publication = {false},
 abstract = {Abstract A novel use case for two data-driven models, namely, a Transformer and a convolutional graph neural network (CGNN) is proposed. The authors propose to use these models for emulating the dynamics of electromagnetic (EM) propagation and scattering. The Transformer translates a past sequence into a future sequence by constructing representations from the past and using it to predict the future, taking all of its own previous predictions as input at each step of prediction. The CGNN updates the current state of attribute vectors of each node by passing it information (messages) from all of its neighbouring nodes. We train these models with FDTD simulations of plane waves propagating and scattering from PEC objects. The authors demonstrate that, within the bounds of computational resources, the Transformer can be utilised as a surrogate for EM dynamics, providing 14× speed-up, while the CGNN can be utilised as a next-frame predictor, providing 9× speed-up. When comparing the accuracy of these two models with the authors’ previously developed Encoder-Recurrent-Decoder (ERD) model, it is observed that the error for both the Transformer and the CGNN remains within the same bound for the ERD model. To the best of the authors’ knowledge, this work is the first to utilise the Transformer as a surrogate for EM dynamics.},
 bibtype = {article},
 author = {Noakoasteen, O and Christodoulou, C and Peng, Z and Goudos, S K},
 doi = {https://doi.org/10.1049/mia2.12463},
 journal = {IET Microwaves, Antennas \& Propagation},
 number = {n/a}
}

Abstract A novel use case for two data-driven models, namely, a Transformer and a convolutional graph neural network (CGNN) is proposed. The authors propose to use these models for emulating the dynamics of electromagnetic (EM) propagation and scattering. The Transformer translates a past sequence into a future sequence by constructing representations from the past and using it to predict the future, taking all of its own previous predictions as input at each step of prediction. The CGNN updates the current state of attribute vectors of each node by passing it information (messages) from all of its neighbouring nodes. We train these models with FDTD simulations of plane waves propagating and scattering from PEC objects. The authors demonstrate that, within the bounds of computational resources, the Transformer can be utilised as a surrogate for EM dynamics, providing 14× speed-up, while the CGNN can be utilised as a next-frame predictor, providing 9× speed-up. When comparing the accuracy of these two models with the authors’ previously developed Encoder-Recurrent-Decoder (ERD) model, it is observed that the error for both the Transformer and the CGNN remains within the same bound for the ERD model. To the best of the authors’ knowledge, this work is the first to utilise the Transformer as a surrogate for EM dynamics.

@article{
 title = {Cherry Tree Crown Extraction Using Machine Learning Based on Images from UAVs},
 type = {article},
 year = {2024},
 volume = {14},
 websites = {https://www.mdpi.com/2077-0472/14/2/322},
 id = {1900dd7d-bd5f-398a-ac36-0c74dc2d6eb3},
 created = {2024-02-18T20:41:09.160Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-02-18T20:41:09.160Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {agriculture14020322},
 source_type = {article},
 private_publication = {false},
 abstract = {Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral cameras. Especially for orchards, it is helpful to isolate each tree and then calculate the preferred vegetation indices separately. Thus, tree detection and crown extraction is another important research area in the domain of Smart Farming. In this paper, we propose an innovative tree detection method based on machine learning, designed to isolate each individual tree in an orchard. First, we evaluate the effectiveness of Detectron2 and YOLOv8 object detection algorithms in identifying individual trees and generating corresponding masks. Both algorithms yield satisfactory results in cherry tree detection, with the best F1-Score up to 94.85%. In the second stage, we apply a method based on OTSU thresholding to improve the provided masks and precisely cover the crowns of the detected trees. The proposed method achieves 85.30% on IoU while Detectron2 gives 79.83% and YOLOv8 has 75.36%. Our work uses cherry trees, but it is easy to apply to any other tree species. We believe that our approach will be a key factor in enabling health monitoring for each individual tree.},
 bibtype = {article},
 author = {Moysiadis, Vasileios and Siniosoglou, Ilias and Kokkonis, Georgios and Argyriou, Vasileios and Lagkas, Thomas and Goudos, Sotirios K and Sarigiannidis, Panagiotis},
 doi = {10.3390/agriculture14020322},
 journal = {Agriculture},
 number = {2}
}

Remote sensing stands out as one of the most widely used operations in the field. In this research area, UAVs offer full coverage of large cultivation areas in a few minutes and provide orthomosaic images with valuable information based on multispectral cameras. Especially for orchards, it is helpful to isolate each tree and then calculate the preferred vegetation indices separately. Thus, tree detection and crown extraction is another important research area in the domain of Smart Farming. In this paper, we propose an innovative tree detection method based on machine learning, designed to isolate each individual tree in an orchard. First, we evaluate the effectiveness of Detectron2 and YOLOv8 object detection algorithms in identifying individual trees and generating corresponding masks. Both algorithms yield satisfactory results in cherry tree detection, with the best F1-Score up to 94.85%. In the second stage, we apply a method based on OTSU thresholding to improve the provided masks and precisely cover the crowns of the detected trees. The proposed method achieves 85.30% on IoU while Detectron2 gives 79.83% and YOLOv8 has 75.36%. Our work uses cherry trees, but it is easy to apply to any other tree species. We believe that our approach will be a key factor in enabling health monitoring for each individual tree.

@article{
 title = {Leveraging the power of internet of things and artificial intelligence in forest fire prevention, detection, and restoration: A comprehensive survey},
 type = {article},
 year = {2024},
 keywords = {Artificial intelligence,Climate change,Forest fires,Fuzzy logic,Internet of things,Resource allocation,Wildfires},
 pages = {101171},
 volume = {26},
 websites = {https://www.sciencedirect.com/science/article/pii/S2542660524001124},
 id = {bdeb6e10-4a7a-3fd1-b4d9-1a5b6010b6df},
 created = {2024-03-26T19:58:42.178Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-26T19:58:42.178Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {GIANNAKIDOU2024101171},
 source_type = {article},
 private_publication = {false},
 abstract = {Forest fires are a persistent global problem, causing devastating consequences such as loss of human lives, harm to the environment, and substantial economic losses. To mitigate these impacts, the accurate prediction and early detection of forest fires is critical. In response to this challenge and living in the digital era of Artificial Intelligence (AI) and smart economies, there has been a growing interest in utilising AI mechanisms for forest fire management. This study provides an in-depth examination of the use of AI algorithms in the fight against forest fires. In particular, our paper starts with an overview of the forest fire problem, followed by a comprehensive review of various systems and approaches. This review includes a thorough analysis of the various works that have evaluated the factors that influence fire occurrence and severity, as well as those that focus on fire prediction and detection systems. The paper also explores the use of AI in adapting and restoring after the occurrence of forest fires. The paper concludes with an evaluation of the potential impact of AI on forest fire management and suggestions for future research directions, taking full advantage of novel technologies, such as 5G communications, Software Defined Networking (SDN), digital twins, federated learning and blockchain. Finally, the paper draws lessons and insights on the potential and limitations of AI in forest fire management, highlighting the need for further research and development in this field to maximise its impact and benefits.},
 bibtype = {article},
 author = {Giannakidou, Sofia and Radoglou-Grammatikis, Panagiotis and Lagkas, Thomas and Argyriou, Vasileios and Goudos, Sotirios and Markakis, Evangelos K and Sarigiannidis, Panagiotis},
 doi = {https://doi.org/10.1016/j.iot.2024.101171},
 journal = {Internet of Things}
}

Forest fires are a persistent global problem, causing devastating consequences such as loss of human lives, harm to the environment, and substantial economic losses. To mitigate these impacts, the accurate prediction and early detection of forest fires is critical. In response to this challenge and living in the digital era of Artificial Intelligence (AI) and smart economies, there has been a growing interest in utilising AI mechanisms for forest fire management. This study provides an in-depth examination of the use of AI algorithms in the fight against forest fires. In particular, our paper starts with an overview of the forest fire problem, followed by a comprehensive review of various systems and approaches. This review includes a thorough analysis of the various works that have evaluated the factors that influence fire occurrence and severity, as well as those that focus on fire prediction and detection systems. The paper also explores the use of AI in adapting and restoring after the occurrence of forest fires. The paper concludes with an evaluation of the potential impact of AI on forest fire management and suggestions for future research directions, taking full advantage of novel technologies, such as 5G communications, Software Defined Networking (SDN), digital twins, federated learning and blockchain. Finally, the paper draws lessons and insights on the potential and limitations of AI in forest fire management, highlighting the need for further research and development in this field to maximise its impact and benefits.

@inproceedings{
 title = {Modeling Received Power from 4G and 5G Networks in Greece U sing Machine Learning},
 type = {inproceedings},
 year = {2024},
 keywords = {Radio frequency;Power measurement;5G mobile commun},
 pages = {1-5},
 id = {f11a5ebe-781b-34f8-bbd9-9ffd04ecd658},
 created = {2024-04-28T09:05:51.257Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-04-28T09:05:51.257Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10501053},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Wireless propagation modeling is crucial for designing 5G networks and deploying base stations. Traditional models are constrained by different propagation environments, and deterministic models using ray tracing demand extensive computational resources. In recent years, advances in data-driven artificial intelligence (AI) have significantly improved the fitting of intelligent propagation models for 5G systems. Using artificial intelligence (AI) and substantial measured data, we conduct a comparative study of various machine learning (ML) models to perform accurate regression predictions for Reference Signal Receiving Power (RSRP). The results of the proposed ML models are compared and analyzed, exhibiting great accuracy in the prediction of RSRP values in a diverse range of urban, suburban, and rural environments.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Tsoulos, George V and Athanasiadou, Georgia and Boursianis, Achilles D and Zaharis, Zaharias D and Sarigiannids, Panagiotis and Christodoulou, Christos G and Goudos, Sotirios K},
 doi = {10.23919/EuCAP60739.2024.10501053},
 booktitle = {2024 18th European Conference on Antennas and Propagation (EuCAP)}
}

Wireless propagation modeling is crucial for designing 5G networks and deploying base stations. Traditional models are constrained by different propagation environments, and deterministic models using ray tracing demand extensive computational resources. In recent years, advances in data-driven artificial intelligence (AI) have significantly improved the fitting of intelligent propagation models for 5G systems. Using artificial intelligence (AI) and substantial measured data, we conduct a comparative study of various machine learning (ML) models to perform accurate regression predictions for Reference Signal Receiving Power (RSRP). The results of the proposed ML models are compared and analyzed, exhibiting great accuracy in the prediction of RSRP values in a diverse range of urban, suburban, and rural environments.

@inproceedings{
 title = {Wideband Aperture-Coupled Array Design for Automotive Radar Applications},
 type = {inproceedings},
 year = {2024},
 keywords = {Radar antennas;Aperture antennas;Sensor systems;Se},
 pages = {1-5},
 id = {6dd1ceb6-1b74-3d23-975f-a59773cbd1ca},
 created = {2024-04-28T09:05:51.278Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-04-28T09:05:51.278Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10501584},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Advanced driver assistance systems (ADAS) technology has been developed to improve driver safety and is a major part of today's autonomous vehicle functionalities. Automotive radars operate as core sensors in modern ADAS systems since they can detect the speed and range of objects near the vehicle. This work uses a recent variant of the Runge-Kutta algorithm, namely RUN, to design an aperture-coupled antenna array for automotive radars. The proposed array consists of five U-shaped patch elements and achieves low return loss, high gain, and high efficiency at 77 GHz - 81 GHz.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Zaharis, Zaharias D and Sotiroudis, Sotirios P and Papadopoulou, Maria S and Christodoulou, Christos G and Goudos, Sotirios K},
 doi = {10.23919/EuCAP60739.2024.10501584},
 booktitle = {2024 18th European Conference on Antennas and Propagation (EuCAP)}
}

Advanced driver assistance systems (ADAS) technology has been developed to improve driver safety and is a major part of today's autonomous vehicle functionalities. Automotive radars operate as core sensors in modern ADAS systems since they can detect the speed and range of objects near the vehicle. This work uses a recent variant of the Runge-Kutta algorithm, namely RUN, to design an aperture-coupled antenna array for automotive radars. The proposed array consists of five U-shaped patch elements and achieves low return loss, high gain, and high efficiency at 77 GHz - 81 GHz.

@inproceedings{
 title = {Low Complexity Deep Learning Based Coordinated Beamforming for mmWave Massive MIMO Vehicular Networks},
 type = {inproceedings},
 year = {2024},
 keywords = {Training;Wireless communication;Deep learning;Arra},
 pages = {1-4},
 id = {94c4c3a0-c573-3adb-ad01-7c97acd024a9},
 created = {2024-05-26T10:40:57.998Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-05-26T10:40:57.998Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10497006},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Enabling high mobility in millimeter-wave (mmWave) systems is crucial for next-generation wireless communication systems. Challenges arise in applications such as vehicular communications and wireless virtual/augmented reality. MmWave systems grapple with concerns related to narrow beams, signal vulnerability to obstructions that affect coverage, and the necessity for frequent handovers. Additionally, identifying optimal beamforming vectors in large antenna array mmWave systems involves substantial training overhead, impacting efficiency. This paper introduces a novel solution to address challenges in enabling high mobility in mmWave systems. The approach combines deep learning (DL) and coordinated beamforming to support applications such as vehicular communications and wireless virtual/augmented reality. The solution involves multiple coordinating base stations (BSs) serving a mobile user, utilizing a single pilot training sequence. A DL model predicts beamforming vectors based on received signals, providing reliable coverage, low latency, and minimal training overhead for highly mobile mmWave applications. Simulations demonstrate its effectiveness in high-mobility scenarios, approaching the performance of an optimal solution, a genie-aided solution that knows the optimal beamforming vectors without any training overhead.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Sarigiannids, Panagiotis and Karagiannidis, George K and Christodoulou, Christos G and Goudos, Sotirios K},
 doi = {10.1109/PACET60398.2024.10497006},
 booktitle = {2024 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

Enabling high mobility in millimeter-wave (mmWave) systems is crucial for next-generation wireless communication systems. Challenges arise in applications such as vehicular communications and wireless virtual/augmented reality. MmWave systems grapple with concerns related to narrow beams, signal vulnerability to obstructions that affect coverage, and the necessity for frequent handovers. Additionally, identifying optimal beamforming vectors in large antenna array mmWave systems involves substantial training overhead, impacting efficiency. This paper introduces a novel solution to address challenges in enabling high mobility in mmWave systems. The approach combines deep learning (DL) and coordinated beamforming to support applications such as vehicular communications and wireless virtual/augmented reality. The solution involves multiple coordinating base stations (BSs) serving a mobile user, utilizing a single pilot training sequence. A DL model predicts beamforming vectors based on received signals, providing reliable coverage, low latency, and minimal training overhead for highly mobile mmWave applications. Simulations demonstrate its effectiveness in high-mobility scenarios, approaching the performance of an optimal solution, a genie-aided solution that knows the optimal beamforming vectors without any training overhead.

@inproceedings{
 title = {Enhancing Text Anonymisation: A Study on CRF, LSTM, and ELMo for Advanced Entity Recognition},
 type = {inproceedings},
 year = {2024},
 keywords = {Privacy;Text analysis;Recurrent neural networks;Te},
 pages = {1-6},
 id = {87f7f7b3-6b20-380e-8500-afda755ad62a},
 created = {2024-05-26T10:40:58.000Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-05-26T10:40:58.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10497084},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {It is essential to create effective strategies for safeguarding private data while preserving the value of textual data in the face of rising privacy concerns in the digital era. In this research, we give a thorough investigation of Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), and Embeddings from Language Models (ELMo)-based text anonymisation methods [1]. The strengths of CRF, LSTM, and ELMo are combined in the proposed approach to overcome the difficulty of text anonymisation. LSTM is a recurrent neural network architecture that can model long-term dependencies, CRF is a probabilistic graphical model that captures the dependencies among the sequence of words, and ELMo offers contextual word representations utilizing deep bidirectional language models. These models are leveraged in order to identify and subsequently obfuscate sensitive information in the frame of textual anonymisation. Experimental results show that when compared to conventional methods, all three methods—CRF, LSTM, and ELMo—achieve considerable improvements in text anonymisation.},
 bibtype = {inproceedings},
 author = {Siniosoglou, Ilias and Asimopoulos, Dimitris and Argyriou, Vasileios and Lagkas, Thomas and Lytos, Anastasios and Moscholios, Ioannis D and Goudos, Sotirios K and Sarigiannidis, Panagiotis},
 doi = {10.1109/PACET60398.2024.10497084},
 booktitle = {2024 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

It is essential to create effective strategies for safeguarding private data while preserving the value of textual data in the face of rising privacy concerns in the digital era. In this research, we give a thorough investigation of Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), and Embeddings from Language Models (ELMo)-based text anonymisation methods [1]. The strengths of CRF, LSTM, and ELMo are combined in the proposed approach to overcome the difficulty of text anonymisation. LSTM is a recurrent neural network architecture that can model long-term dependencies, CRF is a probabilistic graphical model that captures the dependencies among the sequence of words, and ELMo offers contextual word representations utilizing deep bidirectional language models. These models are leveraged in order to identify and subsequently obfuscate sensitive information in the frame of textual anonymisation. Experimental results show that when compared to conventional methods, all three methods—CRF, LSTM, and ELMo—achieve considerable improvements in text anonymisation.

@inproceedings{
 title = {Two-layered High Gain and Wide Bandwidth Metamaterial Antenna for 5G mm-Wave Applications Using Multi-Trial Vector-Based Differential Evolution},
 type = {inproceedings},
 year = {2024},
 keywords = {5G mobile communication;Patch antennas;Bandwidth;M},
 pages = {354-357},
 id = {3742185c-6a9b-32ed-962e-5926dd215e78},
 created = {2024-05-26T10:40:58.110Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-05-26T10:40:58.110Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10535857},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {A two-layered high gain and wide bandwidth metamaterial antenna working at 24 GHz - 30.5 GHz for mm-Wave applications is presented in this paper. To design the antenna we apply a novel evolutionary algorithm, namely the multi-trial vector-based differential evolution (MTDE). The metamaterial antenna has an overall compact size of 12.4 x 12.4 x 8.38 mm3 including two substrates and the air gap. It is realized with a Rogers Duroid 5880 substrate 0.78 mm thick and a Rogers RO3010 as a superstrate 1.6 mm thick at an optimized distance above the radiation element. The radiation element is composed of a square-cut-at-the-four corners patch antenna. In addition, to enhance the antenna performance, both gain and bandwidth, a metasurface based on periodic metallic mushrooms which surround the radiation element is employed. Interelement distance between the metallic structures, their size and the distance between the two substrates are optimized. Simulated results show a significantly wide bandwidth ranging 24 GHz to 30.5 GHz and a high peak realized gain of 11.76 dB when the MTDE optimizer is applied. These features make the antenna a good candidate for 5G mm-Wave applications.},
 bibtype = {inproceedings},
 author = {Hlias, Tzouras and Griva, Aikaterini I and Korompilis, Georgios and Boursianis, Achilles D and Goudos, Sotirios K and Stavros, Koulouridis},
 doi = {10.1109/iWAT57102.2024.10535857},
 booktitle = {2024 IEEE International Workshop on Antenna Technology (iWAT)}
}

A two-layered high gain and wide bandwidth metamaterial antenna working at 24 GHz - 30.5 GHz for mm-Wave applications is presented in this paper. To design the antenna we apply a novel evolutionary algorithm, namely the multi-trial vector-based differential evolution (MTDE). The metamaterial antenna has an overall compact size of 12.4 x 12.4 x 8.38 mm3 including two substrates and the air gap. It is realized with a Rogers Duroid 5880 substrate 0.78 mm thick and a Rogers RO3010 as a superstrate 1.6 mm thick at an optimized distance above the radiation element. The radiation element is composed of a square-cut-at-the-four corners patch antenna. In addition, to enhance the antenna performance, both gain and bandwidth, a metasurface based on periodic metallic mushrooms which surround the radiation element is employed. Interelement distance between the metallic structures, their size and the distance between the two substrates are optimized. Simulated results show a significantly wide bandwidth ranging 24 GHz to 30.5 GHz and a high peak realized gain of 11.76 dB when the MTDE optimizer is applied. These features make the antenna a good candidate for 5G mm-Wave applications.

@inproceedings{
 title = {Audio Fingerprinting Method for Byzantine Hymn Recognition},
 type = {inproceedings},
 year = {2024},
 keywords = {Resistance;Measurement;Fourier transforms;Database},
 pages = {1-4},
 id = {f652503d-2617-3fa0-9c47-5c8d59dc9c61},
 created = {2024-05-26T10:40:58.122Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-05-26T10:40:58.122Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10497021},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this work, a method for Byzantine hymn recognition is proposed utilizing an audio fingerprinting technique to generate speed and scale invariant fingerprints. The main steps of the process are the two-dimensional Fourier Transform (2DFT) and the calculation of a distance metric based on similarity matrices. The general concept is that by creating a database of fingerprints, it is possible to identify a query recording by extracting its fingerprints and compare them to the database. The method was tested by using a dataset of 351 different recordings of nine Byzantine hymns. Some key parameters of the process were evaluated in terms of accuracy and high scores, up to 99.44%, were achieved by introducing a statistical polling approach for the correct match selection.},
 bibtype = {inproceedings},
 author = {Kampelopoulos, Dimitrios and Moysis, Lazaros and Karasavvidis, Konstantinos and Boursianis, Achilles D and Goudos, Sotirios K and Nikolaidis, Spyridon},
 doi = {10.1109/PACET60398.2024.10497021},
 booktitle = {2024 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

In this work, a method for Byzantine hymn recognition is proposed utilizing an audio fingerprinting technique to generate speed and scale invariant fingerprints. The main steps of the process are the two-dimensional Fourier Transform (2DFT) and the calculation of a distance metric based on similarity matrices. The general concept is that by creating a database of fingerprints, it is possible to identify a query recording by extracting its fingerprints and compare them to the database. The method was tested by using a dataset of 351 different recordings of nine Byzantine hymns. Some key parameters of the process were evaluated in terms of accuracy and high scores, up to 99.44%, were achieved by introducing a statistical polling approach for the correct match selection.

@inproceedings{
 title = {Validating a Chaos Based PRBG Under Different Chaotic Maps},
 type = {inproceedings},
 year = {2024},
 keywords = {Microcontrollers;Web pages;Resists;NIST;Generators},
 pages = {1-4},
 id = {0eace410-e092-311b-bd9a-139a32036e4e},
 created = {2024-05-26T10:40:58.122Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-05-26T10:40:58.122Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10497085},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Chaos-based random bit generators are abundantly used in chaos-based encryption and security applications, as a fast, deterministic source of randomness, to perform actions like permutation and substitution. The chaotic map used as a source of randomness though may heavily affect the bit generator’s statistical randomness, key space, and speed. Thus, any given bit generator may not be equally efficient for all the chaotic maps used as a seed. Motivated by this, the present work considers a bit generator that utilizes a common modulo-based hashing technique, and studies its performance under a plethora of different chaotic maps. For each map, the generator is evaluated with respect to randomness, key space, and operations per bit ratio. This analysis can serve as a guideline for random bit generator usage in future chaos-based encryption designs.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Lawnik, Marcin and Volos, Christos and Baptista, Murilo S and Fragulis, George F and Goudos, Sotirios K},
 doi = {10.1109/PACET60398.2024.10497085},
 booktitle = {2024 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

Chaos-based random bit generators are abundantly used in chaos-based encryption and security applications, as a fast, deterministic source of randomness, to perform actions like permutation and substitution. The chaotic map used as a source of randomness though may heavily affect the bit generator’s statistical randomness, key space, and speed. Thus, any given bit generator may not be equally efficient for all the chaotic maps used as a seed. Motivated by this, the present work considers a bit generator that utilizes a common modulo-based hashing technique, and studies its performance under a plethora of different chaotic maps. For each map, the generator is evaluated with respect to randomness, key space, and operations per bit ratio. This analysis can serve as a guideline for random bit generator usage in future chaos-based encryption designs.

@inproceedings{
 title = {Evaluating the Efficacy of AI Techniques in Textual Anonymization: A Comparative Study},
 type = {inproceedings},
 year = {2024},
 keywords = {Data privacy;Analytical models;Scalability;Transfo},
 pages = {242-246},
 id = {d44f7d2e-36f1-3780-8665-0ca92a4af917},
 created = {2024-06-19T06:02:40.971Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-06-19T06:02:40.971Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10557182},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the digital era, with escalating privacy concerns, it’s imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual information. This research embarks on a comprehensive examination of text anonymisation methods, focusing on Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), Embeddings from Language Models (ELMo), and the transformative capabilities of the Transformers architecture. Each model presents unique strengths since LSTM is modeling long-term dependencies, CRF captures dependencies among word sequences, ELMo delivers contextual word representations using deep bidirectional language models and Transformers introduce self-attention mechanisms that provide enhanced scalability. Our study is positioned as a comparative analysis of these models, emphasising their synergistic potential in addressing text anonymisation challenges. Preliminary results indicate that CRF, LSTM, and ELMo individually outperform traditional methods. The inclusion of Transformers, when compared alongside with the other models, offers a broader perspective on achieving optimal text anonymisation in contemporary settings.},
 bibtype = {inproceedings},
 author = {Asimopoulos, Dimitris and Siniosoglou, Ilias and Argyriou, Vasileios and Goudos, Sotirios K and Psannis, Konstantinos E and Karditsioti, Nikoleta and Saoulidis, Theocharis and Sarigiannidis, Panagiotis},
 doi = {10.1109/BalkanCom61808.2024.10557182},
 booktitle = {2024 7th International Balkan Conference on Communications and Networking (BalkanCom)}
}

In the digital era, with escalating privacy concerns, it’s imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual information. This research embarks on a comprehensive examination of text anonymisation methods, focusing on Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), Embeddings from Language Models (ELMo), and the transformative capabilities of the Transformers architecture. Each model presents unique strengths since LSTM is modeling long-term dependencies, CRF captures dependencies among word sequences, ELMo delivers contextual word representations using deep bidirectional language models and Transformers introduce self-attention mechanisms that provide enhanced scalability. Our study is positioned as a comparative analysis of these models, emphasising their synergistic potential in addressing text anonymisation challenges. Preliminary results indicate that CRF, LSTM, and ELMo individually outperform traditional methods. The inclusion of Transformers, when compared alongside with the other models, offers a broader perspective on achieving optimal text anonymisation in contemporary settings.

@inproceedings{
 title = {Ensembling Probabilistic Regressors for Path Loss Prediction},
 type = {inproceedings},
 year = {2024},
 keywords = {Accuracy;Machine learning;Probabilistic logic;Data},
 pages = {1-4},
 id = {6fe1967f-139e-3ca7-8957-3a33134ce414},
 created = {2024-07-11T19:56:09.568Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-07-11T19:56:09.568Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10584576},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Machine Learning (ML) based Path Loss (PL) prediction is of great importance when designing modern communications networks. As a result of providing a framework for understanding what learning entails, probabilistic modeling has become one of the most prominent theoretical and practical methods for developing machines that acquire knowledge from experience-based data. Our work focuses on combining two probabilistic regressors, namely NGBoost and XGBoost-Distribution, into a stacked generalization ensemble. As opposed to the vast majority of stacked ensemble regressors, the novelty of our proposed ensemble is that each base learner delivers two, instead of one, outputs to the meta-learner. That is, apart from the predicted path loss value, each probabilistic base learner computes the standard deviation of the corresponding prediction. Results show that these additional inputs of the meta-learner (which are the outputs of the base learners) pave the way for more accurate predictions.},
 bibtype = {inproceedings},
 author = {Sotiroudis, Sotirios and Rekkas, Vasileios and Iliadis, Lazaros and Zaharis, Zaharias and Christodoulou, Christos and Goudos, Sotirios},
 doi = {10.46620/URSIATRASC24/JXIK2862},
 booktitle = {2024 4th URSI Atlantic Radio Science Meeting (AT-RASC)}
}

Machine Learning (ML) based Path Loss (PL) prediction is of great importance when designing modern communications networks. As a result of providing a framework for understanding what learning entails, probabilistic modeling has become one of the most prominent theoretical and practical methods for developing machines that acquire knowledge from experience-based data. Our work focuses on combining two probabilistic regressors, namely NGBoost and XGBoost-Distribution, into a stacked generalization ensemble. As opposed to the vast majority of stacked ensemble regressors, the novelty of our proposed ensemble is that each base learner delivers two, instead of one, outputs to the meta-learner. That is, apart from the predicted path loss value, each probabilistic base learner computes the standard deviation of the corresponding prediction. Results show that these additional inputs of the meta-learner (which are the outputs of the base learners) pave the way for more accurate predictions.

@inproceedings{
 title = {Energy Harvesting & Autonomous Energy Systems: A Proposal for RF Energy Harvesting},
 type = {inproceedings},
 year = {2024},
 keywords = {Radio frequency;Vibrations;Temperature sensors;Fri},
 pages = {1-5},
 id = {3ea00d81-c9ff-3758-9d6c-327ade78c035},
 created = {2024-08-06T21:15:34.382Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.382Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615601},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The necessity for permanent use of electrical and electronic devices has generated a greater demand for electricity along with more efficient transmission techniques. Energy from the environment can be radio frequency (RF) signals, friction, solar, thermal, or vibration. The increase in autonomous energy devices and sensors depends on the evolution of Energy Harvesting (EH) techniques. In recent years, many self-developed energy devices have been deployed in various types of systems. With the continuous progress of technology, such autonomous devices accomplish more and more challenging operations (e.g., in agriculture or health care), which can be manufactured by consuming only a few uW or even more pW of power. The capacity to function with minimal power consumption is very important in modern electronics design. We present a rectifier circuit for radio frequency (RF) energy harvesting systems that works at 5 and 5.8 GHz. The proposed circuit provides a high PCE (power conversion efficiency) of 64.56% for an input power equal to 10 dBm.},
 bibtype = {inproceedings},
 author = {Bougas, Ioannis D and Papadopoulou, Maria S and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/MOCAST61810.2024.10615601},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The necessity for permanent use of electrical and electronic devices has generated a greater demand for electricity along with more efficient transmission techniques. Energy from the environment can be radio frequency (RF) signals, friction, solar, thermal, or vibration. The increase in autonomous energy devices and sensors depends on the evolution of Energy Harvesting (EH) techniques. In recent years, many self-developed energy devices have been deployed in various types of systems. With the continuous progress of technology, such autonomous devices accomplish more and more challenging operations (e.g., in agriculture or health care), which can be manufactured by consuming only a few uW or even more pW of power. The capacity to function with minimal power consumption is very important in modern electronics design. We present a rectifier circuit for radio frequency (RF) energy harvesting systems that works at 5 and 5.8 GHz. The proposed circuit provides a high PCE (power conversion efficiency) of 64.56% for an input power equal to 10 dBm.

@inproceedings{
 title = {Web-Based Monitoring of Refrigerator Units Using Microcontroller},
 type = {inproceedings},
 year = {2024},
 keywords = {Temperature measurement;Temperature sensors;Perfor},
 pages = {1-4},
 id = {89b42802-c963-3199-bf15-19441fe37d5d},
 created = {2024-08-06T21:15:34.385Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.385Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615643},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Over the past few decades, manufacturers of freezer units such as fridges and refrigerators have been focusing on improving the performance of their products. These devices are typically large and consume a significant amount of electricity, leaving behind a considerable carbon footprint and requiring high maintenance and operating costs. In recent months, the demand for low-cost freezer units has surged, both from households and businesses, due to the global energy crisis. In this paper, we develop and implement a smart sensor system that controls the cooling mechanism of multiple freezer units in a retail store, such as a supermarket or meat industry, based on the Internet of Things (IoT) technology. The system allows the store manager or an employee to monitor the temperature and humidity inside the unit and manually control its operation. Additionally, the freezer automatically activates or deactivates based on the threshold value determined by the temperature requirements of each unit. The sensor data is transmitted wirelessly to the main controller, an ESP32 micro-controller, which runs a web server that displays the measurements.},
 bibtype = {inproceedings},
 author = {Chatzilabrou, Nikolaos and Koritsoglou, Kyriakos and Griva, Aikaterini I and Vassios, Vassilios D and Tsiakmakis, Kyriakos and Boursianis, Achilles D and Hatzopoulos, Argyrios T and Goudos, Sotirios K and Papadopoulou, Maria S},
 doi = {10.1109/MOCAST61810.2024.10615643},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Over the past few decades, manufacturers of freezer units such as fridges and refrigerators have been focusing on improving the performance of their products. These devices are typically large and consume a significant amount of electricity, leaving behind a considerable carbon footprint and requiring high maintenance and operating costs. In recent months, the demand for low-cost freezer units has surged, both from households and businesses, due to the global energy crisis. In this paper, we develop and implement a smart sensor system that controls the cooling mechanism of multiple freezer units in a retail store, such as a supermarket or meat industry, based on the Internet of Things (IoT) technology. The system allows the store manager or an employee to monitor the temperature and humidity inside the unit and manually control its operation. Additionally, the freezer automatically activates or deactivates based on the threshold value determined by the temperature requirements of each unit. The sensor data is transmitted wirelessly to the main controller, an ESP32 micro-controller, which runs a web server that displays the measurements.

@inproceedings{
 title = {SiHoneypot: A Digital Twin-Based Honeypot for Autonomous Vehicles},
 type = {inproceedings},
 year = {2024},
 keywords = {Emulation;Transportation;Market research;Time meas},
 pages = {1-4},
 id = {db2902d2-0b34-36d4-930d-4c80d74fee17},
 created = {2024-08-06T21:15:34.590Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.590Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615785},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Autonomous Vehicles (AVs) stand as the vanguard of the automotive industry's evolution, offering a multitude of advantages in terms of transportation efficiency and applications of critical importance. Notably, their interconnection with various smart devices, such as smartphones and associated services, is achieved effortlessly. However, these merits are counterbalanced by significant security risks pertaining to human safety and the potential exposure of personal data. This work introduces SiHoneypot, an innovative honeypot system rigorously crafted to address security challenges intrinsic to AVs. SiHoneypot leverages Digital Twins and incorporates state-of-the-art trends in software deployment, providing a faithful emulation of Autonomous Vehicle systems. Demonstrating its efficacy as a strategic decoy, SiHoneypot affords sufficient time for other security systems to enact responsive measures. Experimental results underscore the minimal resources required for the deployment of SiHoneypot, emphasizing its operational efficiency and resource optimization. Moreover, the inherent extensibility and versatility of SiHoney-pot's architecture are showcased, illustrating its adaptability to evolving security challenges within the dynamic landscape of autonomous vehicular technologies.},
 bibtype = {inproceedings},
 author = {Liatifis, Athanasios and Eleftheriadis, Charis and Mpatzos, Zisis and Nanos, Ioannis and Lagkas, Thomas and Goudos, Sotirios and Argyriou, Vasileios and Psannis, Konstantinos E and Moscholios, Ioannis D and Sarigiannidis, Panagiotis},
 doi = {10.1109/MOCAST61810.2024.10615785},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Autonomous Vehicles (AVs) stand as the vanguard of the automotive industry's evolution, offering a multitude of advantages in terms of transportation efficiency and applications of critical importance. Notably, their interconnection with various smart devices, such as smartphones and associated services, is achieved effortlessly. However, these merits are counterbalanced by significant security risks pertaining to human safety and the potential exposure of personal data. This work introduces SiHoneypot, an innovative honeypot system rigorously crafted to address security challenges intrinsic to AVs. SiHoneypot leverages Digital Twins and incorporates state-of-the-art trends in software deployment, providing a faithful emulation of Autonomous Vehicle systems. Demonstrating its efficacy as a strategic decoy, SiHoneypot affords sufficient time for other security systems to enact responsive measures. Experimental results underscore the minimal resources required for the deployment of SiHoneypot, emphasizing its operational efficiency and resource optimization. Moreover, the inherent extensibility and versatility of SiHoney-pot's architecture are showcased, illustrating its adaptability to evolving security challenges within the dynamic landscape of autonomous vehicular technologies.

@inproceedings{
 title = {Fetal Images Trophectoderm Score Prediction Using Deep Learning Methodologies},
 type = {inproceedings},
 year = {2024},
 keywords = {Deep learning;Learning systems;Embryo;Microprocess},
 pages = {1-4},
 id = {6a70fe5e-cda2-3c98-a229-428d63721573},
 created = {2024-08-06T21:15:34.625Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.625Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615610},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In-vitro fertilization (IVF) is an assisted reproductive technology (ART) and is regarded as one of the most successful. The embryo quality is determined by the Gardner system which quantifies three characteristics of embryo morphology: expansion, inner cell mass (ICM), and trophectoderm quality (TE). However, several complex and expensive procedures are involved. Increasing the success and at the same time simplifying the procedure, requires relying on novel technologies, like computer vision and deep learning (DL). DL can automatically extract valuable features from data, are highly adaptable, and perform efficiently across various problems. This has spurred significant research efforts into creating and evaluating DL-powered tools for embryo selection. This work utilizes DL learning methods for the task of TE score prediction.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios and Sotiroudis, Sotirios P and Vergos, George and Kritopoulou, Paraskevi and Papatheodorou, Achilleas and Boursianis, Achilles D and Kokkinidis, Konstantinos-Iraklis D and Papadopoulou, Maria S and Sarigiannidis, Panagiotis G and Goudos, Sotirios K},
 doi = {10.1109/MOCAST61810.2024.10615610},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In-vitro fertilization (IVF) is an assisted reproductive technology (ART) and is regarded as one of the most successful. The embryo quality is determined by the Gardner system which quantifies three characteristics of embryo morphology: expansion, inner cell mass (ICM), and trophectoderm quality (TE). However, several complex and expensive procedures are involved. Increasing the success and at the same time simplifying the procedure, requires relying on novel technologies, like computer vision and deep learning (DL). DL can automatically extract valuable features from data, are highly adaptable, and perform efficiently across various problems. This has spurred significant research efforts into creating and evaluating DL-powered tools for embryo selection. This work utilizes DL learning methods for the task of TE score prediction.

@inproceedings{
 title = {Byzantine Hymn Recognition with Audio Fingerprints Resistant to Noise, Tempo and Scale Changes},
 type = {inproceedings},
 year = {2024},
 keywords = {Resistance;Measurement;Accuracy;Fourier transforms},
 pages = {1-4},
 id = {d172077a-a85b-3d33-95bd-a42f9c353a06},
 created = {2024-08-06T21:15:34.658Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.658Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615909},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this study, an audio fingerprinting approach is utilized that was successfully used for Byzantine hymn recogni tion. The process is based on the extraction of time and scale invariant fingerprints using the two-dimensional Fourier Transform (2DFT). It also involves a matching process between fingerprints based on a distance metric calculated from similarity matrices. The proposed method was evaluated on a database of 351 live hymn recordings as well as different noise scenarios and exhibited high accuracy.},
 bibtype = {inproceedings},
 author = {Kampelopoulos, Dimitrios and Moysis, Lazaros and Karasavvidis, Konstantinos and Boursianis, Achilles D and Goudos, Sotirios K and Nikolaidis, Spyridon},
 doi = {10.1109/MOCAST61810.2024.10615909},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In this study, an audio fingerprinting approach is utilized that was successfully used for Byzantine hymn recogni tion. The process is based on the extraction of time and scale invariant fingerprints using the two-dimensional Fourier Transform (2DFT). It also involves a matching process between fingerprints based on a distance metric calculated from similarity matrices. The proposed method was evaluated on a database of 351 live hymn recordings as well as different noise scenarios and exhibited high accuracy.

@inproceedings{
 title = {Reconfigurable Intelligent Surfaces: A Brief Review on Design Specifications},
 type = {inproceedings},
 year = {2024},
 keywords = {Varactors;Reviews;Transmitters;PIN photodiodes;Gra},
 pages = {1-4},
 id = {b1dc58bb-51d2-3a79-ba45-6a6816f90003},
 created = {2024-08-06T21:15:34.679Z},
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 last_modified = {2024-08-06T21:15:34.679Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615393},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The reconfigurable intelligent surface (RIS) is a key technology for sixth-generation (6G) mobile networks. RIS consists of small, low-cost reflecting elements that can be dynamically adjusted using a programmable controller. Each of these elements can efficiently reflect a phase-shifted version of the incident electromagnetic wave. This study presents a brief review of the design specifications of RISs. An overview of the general properties and evaluation parameters is presented. A comparison between passive and active RISs is included. Design specifications and suitable materials are highlighted. Finally, crucial issues for deploying RISs in higher frequency ranges are discussed.},
 bibtype = {inproceedings},
 author = {Griva, Aikaterini I and Boursianis, Achilles D and Koulouridis, Stavros and Sarigiannidis, Panagiotis and Karagiannidis, George and Goudos, Sotirios K},
 doi = {10.1109/MOCAST61810.2024.10615393},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The reconfigurable intelligent surface (RIS) is a key technology for sixth-generation (6G) mobile networks. RIS consists of small, low-cost reflecting elements that can be dynamically adjusted using a programmable controller. Each of these elements can efficiently reflect a phase-shifted version of the incident electromagnetic wave. This study presents a brief review of the design specifications of RISs. An overview of the general properties and evaluation parameters is presented. A comparison between passive and active RISs is included. Design specifications and suitable materials are highlighted. Finally, crucial issues for deploying RISs in higher frequency ranges are discussed.

@inproceedings{
 title = {3D Direction of Arrival Estimation: An Innovative Deep Neural Network Approach},
 type = {inproceedings},
 year = {2024},
 keywords = {Wireless communication;Solid modeling;Direction-of},
 pages = {1-4},
 id = {de8bb5b2-84fa-3b13-aafa-90274fb18a6c},
 created = {2024-08-06T21:15:34.752Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.752Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615339},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The recent integration of neural networks into the domain of direction of arrival estimation marks a promising fron-tier in the landscape of next-generation wireless communications. Our paper meticulously delves into the architecture of the proposed deep convolutional neural network (DCNN), presenting a novel framework designed to streamline the classification process within the output layer. Operating on correlation matrices created by signals received by a 4 × 4 planar antenna array, our DCNN predicts angles of arrival in 3D space. We assess the model's performance in scenarios involving the simultaneous reception of signals, employing the mean absolute error as a metric to gauge prediction errors in the angle domain. The simulation results affirm the superior performance of the proposed deep learning-based scheme. The model's robustness is rigorously examined across various validation cases, providing conclusive evidence of its potential in real-world applications.},
 bibtype = {inproceedings},
 author = {Mylonakis, Constantinos M and Velanas, Pantelis and Lazaridis, Pavlos I and Sarigiannidis, Panagiotis and Goudos, Sotirios K and Zaharis, Zaharias D},
 doi = {10.1109/MOCAST61810.2024.10615339},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The recent integration of neural networks into the domain of direction of arrival estimation marks a promising fron-tier in the landscape of next-generation wireless communications. Our paper meticulously delves into the architecture of the proposed deep convolutional neural network (DCNN), presenting a novel framework designed to streamline the classification process within the output layer. Operating on correlation matrices created by signals received by a 4 × 4 planar antenna array, our DCNN predicts angles of arrival in 3D space. We assess the model's performance in scenarios involving the simultaneous reception of signals, employing the mean absolute error as a metric to gauge prediction errors in the angle domain. The simulation results affirm the superior performance of the proposed deep learning-based scheme. The model's robustness is rigorously examined across various validation cases, providing conclusive evidence of its potential in real-world applications.

@inproceedings{
 title = {Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches},
 type = {inproceedings},
 year = {2024},
 keywords = {Deep learning;Data privacy;Circuits and systems;Be},
 pages = {1-6},
 id = {03a94ec1-b25a-3044-b840-2a7fa77a0c1d},
 created = {2024-08-06T21:15:34.839Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:34.839Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615642},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there is a burgeoning interest in leveraging these advanced models for text anonymisation tasks. This paper presents a comprehensive benchmarking study comparing the performance of transformer-based models and Large Language Models(LLM) against traditional architectures for text anonymisation. Utilising the CoNLL-2003 dataset, known for its robustness and diversity, we evaluate several models. Our results showcase the strengths and weaknesses of each approach, offering a clear perspective on the efficacy of modern versus traditional methods. Notably, while modern models exhibit advanced capabilities in capturing contextual nuances, certain traditional architectures still keep high performance. This work aims to guide researchers in selecting the most suitable model for their anonymisation needs, while also shedding light on potential paths for future advancements in the field.},
 bibtype = {inproceedings},
 author = {Asimopoulos, Dimitris and Siniosoglou, Ilias and Argyriou, Vasileios and Karamitsou, Thomai and Fountoukidis, Eleftherios and Goudos, Sotirios K and Moscholios, Ioannis D and Psannis, Konstantinos E and Sarigiannidis, Panagiotis},
 doi = {10.1109/MOCAST61810.2024.10615642},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there is a burgeoning interest in leveraging these advanced models for text anonymisation tasks. This paper presents a comprehensive benchmarking study comparing the performance of transformer-based models and Large Language Models(LLM) against traditional architectures for text anonymisation. Utilising the CoNLL-2003 dataset, known for its robustness and diversity, we evaluate several models. Our results showcase the strengths and weaknesses of each approach, offering a clear perspective on the efficacy of modern versus traditional methods. Notably, while modern models exhibit advanced capabilities in capturing contextual nuances, certain traditional architectures still keep high performance. This work aims to guide researchers in selecting the most suitable model for their anonymisation needs, while also shedding light on potential paths for future advancements in the field.

@inproceedings{
 title = {Ultra-Wideband Antenna Design for RF Energy Harvesting Applications Using the Bald Eagle Search Algorithm},
 type = {inproceedings},
 year = {2024},
 keywords = {Radio frequency;Wireless sensor networks;Ultra wid},
 pages = {1-4},
 id = {c8c0e931-84f3-3206-8c86-c257df733cca},
 created = {2024-08-06T21:15:35.249Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-06T21:15:35.249Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10615973},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {RF energy harvesting is constantly expanding in the field of low-power wireless sensors, as it provides a viable and cost-reduction solution for hard-to-maintain cases. In the meantime, significant progress has been made in the field of evolutionary optimization, with brand new and more intelligent optimization algorithms being published, with the Bald Eagle Search Algorithm (BES) being one of them. In this work, an ultra-wideband antenna for RF energy harvesting is optimized using the BES algorithm to maintain its wideband characteristics, while minimizing the complexity of its design.},
 bibtype = {inproceedings},
 author = {Korompilis, George and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Zaharis, Zaharias D and Goudos, Sotirios K and Siakavara, Katerina},
 doi = {10.1109/MOCAST61810.2024.10615973},
 booktitle = {2024 13th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

RF energy harvesting is constantly expanding in the field of low-power wireless sensors, as it provides a viable and cost-reduction solution for hard-to-maintain cases. In the meantime, significant progress has been made in the field of evolutionary optimization, with brand new and more intelligent optimization algorithms being published, with the Bald Eagle Search Algorithm (BES) being one of them. In this work, an ultra-wideband antenna for RF energy harvesting is optimized using the BES algorithm to maintain its wideband characteristics, while minimizing the complexity of its design.

@article{
 title = {Enhancing 3D Indoor Visible Light Positioning With Machine Learning Combined Nyström Kernel Approximation},
 type = {article},
 year = {2024},
 keywords = {Accuracy;Broadcasting;Three-dimensional displays;V},
 pages = {1-15},
 id = {4394f87f-c540-30bd-8a70-d0da39f4fc8a},
 created = {2024-08-07T20:26:25.745Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-07T20:26:25.745Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10628116},
 source_type = {article},
 private_publication = {false},
 abstract = {Optical wireless communication (OWC) is emerging as a pivotal technology for next-generation broadcast networks, with visible light communication (VLC) poised to meet the escalating demands of advanced radio frequency systems. This study focuses on enhancing visible light positioning (VLP), recognized for its precision, simplicity, and cost-effectiveness, which are essential for accurate indoor localization and responsive location-based services. Central to our approach is the integration of advanced machine learning (ML) techniques, which fundamentally transform the accuracy and efficiency of 3D indoor positioning systems. We introduce an advanced VLP framework where ML is leveraged not merely as an adjunct but as the primary driver of innovation, significantly refining the processing of received signal strength (RSS) indicators. The methodology centers around a system comprising four light-emitting diodes (LEDs) arranged in a star geometry, optimized for precise spatial localization. We evaluate three distinct methodologies: a foundational star-shaped configuration for baseline position estimation, a repeated unit cell strategy to extend the four-LED configuration to a larger positioning area, and a sophisticated implementation employing Nyström kernel approximation. This integration of Nyström approximation into our ML framework drastically enhances the system’s predictive accuracy, achieving an exceptional average relative root mean square error (aRRMSE) of 2.1 cm in a simulated setup. The results demonstrate that ML, especially combined with the application of the Nyström kernel approximation, significantly elevates the precision and operational efficiency of traditional VLP systems, setting new benchmarks for accuracy in indoor 3D positioning technologies and fostering advancements towards more sophisticated and adaptable communication networks.},
 bibtype = {article},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Iliadis, Lazaros Alexios and Bastiaens, Sander and Joseph, Wout and Plets, David and Christodoulou, Christos G and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/TBC.2024.3437216},
 journal = {IEEE Transactions on Broadcasting}
}

Optical wireless communication (OWC) is emerging as a pivotal technology for next-generation broadcast networks, with visible light communication (VLC) poised to meet the escalating demands of advanced radio frequency systems. This study focuses on enhancing visible light positioning (VLP), recognized for its precision, simplicity, and cost-effectiveness, which are essential for accurate indoor localization and responsive location-based services. Central to our approach is the integration of advanced machine learning (ML) techniques, which fundamentally transform the accuracy and efficiency of 3D indoor positioning systems. We introduce an advanced VLP framework where ML is leveraged not merely as an adjunct but as the primary driver of innovation, significantly refining the processing of received signal strength (RSS) indicators. The methodology centers around a system comprising four light-emitting diodes (LEDs) arranged in a star geometry, optimized for precise spatial localization. We evaluate three distinct methodologies: a foundational star-shaped configuration for baseline position estimation, a repeated unit cell strategy to extend the four-LED configuration to a larger positioning area, and a sophisticated implementation employing Nyström kernel approximation. This integration of Nyström approximation into our ML framework drastically enhances the system’s predictive accuracy, achieving an exceptional average relative root mean square error (aRRMSE) of 2.1 cm in a simulated setup. The results demonstrate that ML, especially combined with the application of the Nyström kernel approximation, significantly elevates the precision and operational efficiency of traditional VLP systems, setting new benchmarks for accuracy in indoor 3D positioning technologies and fostering advancements towards more sophisticated and adaptable communication networks.

@inproceedings{
 title = {On the Accuracy and Efficiency of Received Signal Strength Modelling for a Forest Environment},
 type = {inproceedings},
 year = {2024},
 keywords = {Accuracy;Wireless networks;Vegetation mapping;Fore},
 pages = {399-404},
 id = {dd67962c-36a7-39cf-a709-24fc63590c6d},
 created = {2024-08-18T10:39:31.158Z},
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 last_modified = {2024-08-18T10:39:31.158Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10624852},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Within telecommunications, the accuracy and efficiency of machine learning models (ML) define their utility, and consequently, the choice of ML mechanisms assumes paramount importance. This study focuses on the exploration and comparison of diverse ML and ensemble learning techniques, with a specific emphasis on their significance in crafting precise and extensive models. To this end, the quality of the received signal and the optimization and functioning of wireless communication networks rely heavily on accurately predicting the received signal strength indicator (RSSI) and path loss (PL). The studied environment, which is highly complex, spans 2000 km2 of the intricate landscapes of the American River Hydrologic Observatory (ARHO) networks and is characterized by a diverse blend of terrain features and vegetation distributions. Notable independent variables under consideration include path distance, canopy coverage, terrain variability, and path angle. The proposed ensemble ML approaches demonstrate remarkable accuracy and efficiency when it comes to modeling and predicting the RSSI values in forested environments.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Koudouridis, Georgios P and Sarigiannidis, Panagiotis and Zaharis, Zaharias D and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/ICMLCN59089.2024.10624852},
 booktitle = {2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN)}
}

Within telecommunications, the accuracy and efficiency of machine learning models (ML) define their utility, and consequently, the choice of ML mechanisms assumes paramount importance. This study focuses on the exploration and comparison of diverse ML and ensemble learning techniques, with a specific emphasis on their significance in crafting precise and extensive models. To this end, the quality of the received signal and the optimization and functioning of wireless communication networks rely heavily on accurately predicting the received signal strength indicator (RSSI) and path loss (PL). The studied environment, which is highly complex, spans 2000 km2 of the intricate landscapes of the American River Hydrologic Observatory (ARHO) networks and is characterized by a diverse blend of terrain features and vegetation distributions. Notable independent variables under consideration include path distance, canopy coverage, terrain variability, and path angle. The proposed ensemble ML approaches demonstrate remarkable accuracy and efficiency when it comes to modeling and predicting the RSSI values in forested environments.

@inproceedings{
 title = {Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings},
 type = {inproceedings},
 year = {2024},
 keywords = {Few-Shot Learning;Green AI;Deep Learning;Model Opt},
 pages = {1-6},
 id = {5a218632-ae0e-308f-b6b0-3770264faa54},
 created = {2024-08-21T10:08:33.722Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-08-21T10:08:33.722Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10628312},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and complexity. However, sustainability and energy efficiency have been critical requirements during deployment in contemporary industrial settings, necessitating the use of data-efficient approaches such as few-shot learning. In this paper, to alleviate the burden of lengthy model training and minimize energy consumption, a finetuning approach to adapt standard object detection models to downstream tasks is examined. Subsequently, a thorough case study and evaluation of the energy demands of the developed models, applied in object detection benchmark datasets from volatile industrial environments, is presented. Specifically, different finetuning strategies, as well as utilization of ancillary evaluation data during training, are examined, and the trade-off between performance and efficiency is highlighted in this low-data regime. Finally, this paper introduces a novel way to quantify this trade-off through a customized Efficiency Factor metric.},
 bibtype = {inproceedings},
 author = {Tsoumplekas, Georgios and Li, Vladislav and Siniosoglou, Ilias and Argyriou, Vasileios and Goudos, Sotirios K and Moscholios, Ioannis D and Radoglou-Grammatikis, Panagiotis and Sarigiannidis, Panagiotis},
 doi = {10.1109/RAGE62451.2024.00016},
 booktitle = {2024 IEEE 3rd Real-Time and Intelligent Edge Computing Workshop (RAGE)}
}

In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and complexity. However, sustainability and energy efficiency have been critical requirements during deployment in contemporary industrial settings, necessitating the use of data-efficient approaches such as few-shot learning. In this paper, to alleviate the burden of lengthy model training and minimize energy consumption, a finetuning approach to adapt standard object detection models to downstream tasks is examined. Subsequently, a thorough case study and evaluation of the energy demands of the developed models, applied in object detection benchmark datasets from volatile industrial environments, is presented. Specifically, different finetuning strategies, as well as utilization of ancillary evaluation data during training, are examined, and the trade-off between performance and efficiency is highlighted in this low-data regime. Finally, this paper introduces a novel way to quantify this trade-off through a customized Efficiency Factor metric.

@inproceedings{
 title = {Human Blastocyst Image Generation Using Generative Adversarial Networks},
 type = {inproceedings},
 year = {2024},
 keywords = {Measurement;Training;In vitro fertilization;Visual},
 pages = {1-4},
 id = {292a5b42-5c54-3a16-9b7f-f52fcef84eb0},
 created = {2024-08-22T20:09:24.268Z},
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 last_modified = {2024-08-22T20:09:24.268Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10635904},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Several medical fields such as In Vitro Fertilization (IVF) suffer from limited databases d require augmentations, to be suitable for machine learning (ML) tasks such as classification. We test the use of various Generative Adversarial Network (GAN) architectures to tackle the problem of limited data by generating high-quality samples. We compare two GAN-based data augmentation techniques for a limited medical image database, utilizing synthetic images. A GAN can create synthetic images by learning to model a probability density function that can represent large data like images. Synthetic samples are then evaluated using metrics and visual evaluation with respect to the original "real" samples.},
 bibtype = {inproceedings},
 author = {Tikas, Evangelos and Iliadis, Lazaros Alexios and Sotiroudis, Sotirios and Boursianis, Achilles and Kokkinidis, Konstantinos-Iraklis D and Papatheodorou, Achilleas and Goudos, Sotirios K},
 doi = {10.1109/ISBI56570.2024.10635904},
 booktitle = {2024 IEEE International Symposium on Biomedical Imaging (ISBI)}
}

Several medical fields such as In Vitro Fertilization (IVF) suffer from limited databases d require augmentations, to be suitable for machine learning (ML) tasks such as classification. We test the use of various Generative Adversarial Network (GAN) architectures to tackle the problem of limited data by generating high-quality samples. We compare two GAN-based data augmentation techniques for a limited medical image database, utilizing synthetic images. A GAN can create synthetic images by learning to model a probability density function that can represent large data like images. Synthetic samples are then evaluated using metrics and visual evaluation with respect to the original "real" samples.

@article{
 title = {A Deep Probabilistic Machine Learning Approach to Ray Tracing Path Loss Prediction at 900 MHz},
 type = {article},
 year = {2024},
 keywords = {Feature extr,Predictive models,Probabilistic logic},
 pages = {8728-8738},
 volume = {72},
 id = {7823e36e-ef81-3e2b-afbb-b276f935b422},
 created = {2024-09-28T08:46:34.394Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-11-05T20:01:16.689Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10697398},
 source_type = {article},
 private_publication = {false},
 abstract = {Machine Learning (ML) is extensively being used in order to tackle the problem of radio propagation. Besides the models that rely on tabular data, Deep Learning (DL) based image-driven models have also emerged. However, significant uncertainty is associated with path loss forecasting and deterministic ML predictions should be combined with a model for predictive uncertainty. As a result, we take a probabilistic approach by estimating prediction intervals using a deep probabilistic framework. The probabilistic framework attempts to address the issue of conditional bias, which frequently characterizes deterministic ML predictions obtained through error minimization. This is accomplished by quantifying uncertainty, making probabilistic predictions, and incorporating robust optimization techniques into the modeling process. The work at hand fuses images and tabular data into a Deep Probabilistic Ensemble (DPE). More precisely, Natural Gradient Boosting (NGBoost) is being used in order to obtain probabilistic predictions from each input modality separately. These unimodal predictions are then ensembled for each estimation point, according to the inverse of their variance. The proposed model’s results show a significant performance boost against the single-mode predictions in terms of prediction error and uncertainty. To the best of our knowledge, this is the first time that images and tabular data are being combined on the basis of a probabilistically structured ensemble model for a path loss modeling problem in electromagnetics.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P and Matin, Mohammad A and Wan, Shaohua and Christodoulou, Christos and Goudos, Sotirios K},
 doi = {10.1109/TAP.2024.3465840},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {11}
}

Machine Learning (ML) is extensively being used in order to tackle the problem of radio propagation. Besides the models that rely on tabular data, Deep Learning (DL) based image-driven models have also emerged. However, significant uncertainty is associated with path loss forecasting and deterministic ML predictions should be combined with a model for predictive uncertainty. As a result, we take a probabilistic approach by estimating prediction intervals using a deep probabilistic framework. The probabilistic framework attempts to address the issue of conditional bias, which frequently characterizes deterministic ML predictions obtained through error minimization. This is accomplished by quantifying uncertainty, making probabilistic predictions, and incorporating robust optimization techniques into the modeling process. The work at hand fuses images and tabular data into a Deep Probabilistic Ensemble (DPE). More precisely, Natural Gradient Boosting (NGBoost) is being used in order to obtain probabilistic predictions from each input modality separately. These unimodal predictions are then ensembled for each estimation point, according to the inverse of their variance. The proposed model’s results show a significant performance boost against the single-mode predictions in terms of prediction error and uncertainty. To the best of our knowledge, this is the first time that images and tabular data are being combined on the basis of a probabilistically structured ensemble model for a path loss modeling problem in electromagnetics.

@inproceedings{
 title = {Machine Learning Based Radio Environment Map Construction for Cellular Networks},
 type = {inproceedings},
 year = {2024},
 keywords = {Wireless communication;Maximum likelihood estimati},
 pages = {1239-1240},
 id = {54881eda-7537-357e-b7a5-88fc1f4089b4},
 created = {2024-10-01T16:28:31.195Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-10-01T16:28:31.195Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10686580},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Radio environment maps (REMs) can characterize a parameter of interest in a communication channel such as the reference signal received power (RSRP) at every point in a given geographical region. High-precision REMs have substantial potential for managing wireless resources and monitoring the spectrum. In this work, we explore various machine learning (ML) models, including an ensemble approach, to construct REMs by first estimating RSRP values in a long-term evolution (LTE) network. The simulation results indicate that the proposed ensemble approach exhibits great accuracy in RSRP estimation in LTE networks.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Zaharis, Zaharias D and Koudouridis, George and Sarigiannids, Panagiotis and Karagiannidis, George K and Christodoulou, Christos G and Goudos, Sotirios K},
 doi = {10.1109/AP-S/INC-USNC-URSI52054.2024.10686580},
 booktitle = {2024 IEEE International Symposium on Antennas and Propagation and INC/USNC‐URSI Radio Science Meeting (AP-S/INC-USNC-URSI)}
}

Radio environment maps (REMs) can characterize a parameter of interest in a communication channel such as the reference signal received power (RSRP) at every point in a given geographical region. High-precision REMs have substantial potential for managing wireless resources and monitoring the spectrum. In this work, we explore various machine learning (ML) models, including an ensemble approach, to construct REMs by first estimating RSRP values in a long-term evolution (LTE) network. The simulation results indicate that the proposed ensemble approach exhibits great accuracy in RSRP estimation in LTE networks.

@article{
 title = {Quad-Band Rectifier Circuit Design for IoT Applications},
 type = {article},
 year = {2024},
 volume = {12},
 websites = {https://www.mdpi.com/2227-7080/12/10/188},
 id = {6e59b174-5377-307e-b929-f8424f74cbad},
 created = {2024-10-02T14:13:52.894Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-10-02T14:13:52.894Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies12100188},
 source_type = {article},
 private_publication = {false},
 abstract = {In this work, a novel quad-band rectifier circuit is introduced for RF energy harvesting and Internet of Things (IoT) applications. The proposed rectifier operates in the Wi-Fi frequency band and can supply low-power sensors and systems used in IoT services. The circuit operates at 2.4, 3.5, 5, and 5.8 GHz. The proposed RF-to-DC rectifier is designed based on Delon theory and Greinacher topology on an RT/Duroid 5880 substrate. The results show that our proposed circuit can harvest RF energy from the environment, providing maximum power conversion efficiency (PCE) greater than 81% when the output load is 0.511 kΩ and the input power is 12 dBm. In this work, we provide a comprehensive design framework for an affordable RF-to-DC rectifier. Our circuit performs better than similar designs in the literature. This rectifier could be integrated into an IoT node to harvest RF energy, thereby proving a green energy source. The IoT node can operate at various frequencies.},
 bibtype = {article},
 author = {Bougas, Ioannis D and Papadopoulou, Maria S and Boursianis, Achilles D and Sotiroudis, Sotirios and Zaharis, Zaharias D and Goudos, Sotirios K},
 doi = {10.3390/technologies12100188},
 journal = {Technologies},
 number = {10}
}

In this work, a novel quad-band rectifier circuit is introduced for RF energy harvesting and Internet of Things (IoT) applications. The proposed rectifier operates in the Wi-Fi frequency band and can supply low-power sensors and systems used in IoT services. The circuit operates at 2.4, 3.5, 5, and 5.8 GHz. The proposed RF-to-DC rectifier is designed based on Delon theory and Greinacher topology on an RT/Duroid 5880 substrate. The results show that our proposed circuit can harvest RF energy from the environment, providing maximum power conversion efficiency (PCE) greater than 81% when the output load is 0.511 kΩ and the input power is 12 dBm. In this work, we provide a comprehensive design framework for an affordable RF-to-DC rectifier. Our circuit performs better than similar designs in the literature. This rectifier could be integrated into an IoT node to harvest RF energy, thereby proving a green energy source. The IoT node can operate at various frequencies.

@article{
 title = {Passive beamforming design for Double RIS-muMIMO System: A Machine Learning Perspective},
 type = {article},
 year = {2024},
 keywords = {Array signal processing,Channel estimation,Reconfi},
 pages = {151737-151748},
 volume = {12},
 id = {7826a660-0607-341e-94e1-5ba51a3b08da},
 created = {2024-10-15T14:27:26.612Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-10-24T17:52:30.380Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10716384},
 source_type = {article},
 private_publication = {false},
 abstract = {Multiple-input multiple-output (MIMO) and reconfigurable intelligent surfaces (RIS) enable network system designers to create intelligent, energy-efficient network systems. Higher-order beamforming gain through the deployment of multiple RISs ensures enhanced system performance. To achieve this, a cooperative design of passive beamforming is required. This paper presents RIS passive beamforming design for a double RIS-assisted multi-user multiple-input multiple-output (muMIMO) system. The authors explore machine learning (ML)-based techniques, specifically fully complex-multilayer perception (FC-MLP) and extreme learning machine (ELM), that do not require any prior knowledge of the mathematical formulations of the network system, for RIS passive beamforming design frameworks. The proposed ML-based frameworks are compared to the alternating optimization (AO) as well as to the deep deterministic policy gradient (DDPG)-based techniques in terms of average spectral efficiency (SE), as a function of transmit power, their configurations, RISs’ locations and number of RISs’ cells, as well as their computational complexities. The proposed ELM framework outperforms the AO and FC-MLP methods, and demonstrates descent performance when compared to the DDPG method.},
 bibtype = {article},
 author = {Rezwanul Mahmood, M and Matin, Mohammad Abdul and Goudos, Sotirios K},
 doi = {10.1109/ACCESS.2024.3479937},
 journal = {IEEE Access}
}

Multiple-input multiple-output (MIMO) and reconfigurable intelligent surfaces (RIS) enable network system designers to create intelligent, energy-efficient network systems. Higher-order beamforming gain through the deployment of multiple RISs ensures enhanced system performance. To achieve this, a cooperative design of passive beamforming is required. This paper presents RIS passive beamforming design for a double RIS-assisted multi-user multiple-input multiple-output (muMIMO) system. The authors explore machine learning (ML)-based techniques, specifically fully complex-multilayer perception (FC-MLP) and extreme learning machine (ELM), that do not require any prior knowledge of the mathematical formulations of the network system, for RIS passive beamforming design frameworks. The proposed ML-based frameworks are compared to the alternating optimization (AO) as well as to the deep deterministic policy gradient (DDPG)-based techniques in terms of average spectral efficiency (SE), as a function of transmit power, their configurations, RISs’ locations and number of RISs’ cells, as well as their computational complexities. The proposed ELM framework outperforms the AO and FC-MLP methods, and demonstrates descent performance when compared to the DDPG method.

@inproceedings{
 title = {A Machine Learning Approach For The Identification Of Olive Fruit Fly in Greece},
 type = {inproceedings},
 year = {2024},
 keywords = {Training;Accuracy;Social networking (online);Insec},
 pages = {58-62},
 id = {cc8ad37f-d4b0-3a91-9396-c6c504c39214},
 created = {2024-11-05T20:01:16.490Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-11-05T20:01:16.490Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10734618},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Contemporary agriculture faces critical challenges to maintain a future that meets global food demand. Precise and early detection of plantations’ pest and disease threats is crucial for controlling their spread, maintaining production quality and volume, minimizing costs, and reducing trade disruptions, sometimes even lessening human health risks. Pest management in agriculture benefits significantly from the application of deep learning (DL) techniques for more efficient detection and monitoring, overcoming the inefficiencies of traditional labor-intensive methods. This study develops a convolutional neural network (CNN) and benchmarks it against state-of-the-art (SOTA) DL models to identify the primary threat to olive trees, Bactrocera oleae (also known as Dacus). Using a data set composed of images that span 102 insect categories, CNN demonstrated a high accuracy of 96. 32% to distinguish Dacus from other insect species.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Kerasidis, Michail and Sotiroudis, Sotirios P and Sarigiannidis, Panagiotis and Psannis, Konstantinos E and Krystallidou, Evdokia and Goudos, Sotirios K},
 doi = {10.1109/SEEDA-CECNSM63478.2024.00019},
 booktitle = {2024 9th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)}
}

Contemporary agriculture faces critical challenges to maintain a future that meets global food demand. Precise and early detection of plantations’ pest and disease threats is crucial for controlling their spread, maintaining production quality and volume, minimizing costs, and reducing trade disruptions, sometimes even lessening human health risks. Pest management in agriculture benefits significantly from the application of deep learning (DL) techniques for more efficient detection and monitoring, overcoming the inefficiencies of traditional labor-intensive methods. This study develops a convolutional neural network (CNN) and benchmarks it against state-of-the-art (SOTA) DL models to identify the primary threat to olive trees, Bactrocera oleae (also known as Dacus). Using a data set composed of images that span 102 insect categories, CNN demonstrated a high accuracy of 96. 32% to distinguish Dacus from other insect species.

@article{
 title = {A LoRaWAN-based IoT platform for smart irrigation in olive groves},
 type = {article},
 year = {2024},
 keywords = {LPWA,data collection,soil moisture,soil temperature,water consumption},
 pages = {100673},
 websites = {https://www.sciencedirect.com/science/article/pii/S2772375524002788},
 id = {dd43f84d-8813-37f8-bcfe-20f301c1ed17},
 created = {2024-11-29T19:09:51.348Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-11-29T19:09:51.348Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {LIOPATSAKALIDI2024100673},
 source_type = {article},
 private_publication = {false},
 abstract = {Summary
Irrigation drives water consumption in agriculture, essential for crop productivity and conserving water resources. Smart irrigation optimizes water usage, enhances yields, and supports sustainability. Integrating Information and Communication Technologies (ICT) and the Internet of Things (IoT) shows potential for reducing water consumption, but hardware, software, and connectivity solutions are still developing. Low-Power Wide-Area Access (LPWA) technologies enable energy-efficient IoT applications with long-range communication. LoRaWAN ensures secure data transmission up to 15 km using a single gateway. This paper presents a LoRaWAN-based prototype irrigation platform developed within the AREThOU5A framework, implemented in a 22-hectare olive grove with Kalamon olives in Greece. The system monitors soil moisture levels using IoT end nodes with low-cost microcontrollers and embedded sensors. Each node measures moisture at depths of 30 cm, 60 cm, and 90 cm, operating on battery power for months and communicating via LoRaWAN. Data is transmitted through a LoRaWAN gateway to a cloud-based infrastructure using 4G connectivity, allowing real-time access via online dashboards. Collected data will inform smart irrigation strategies, maximizing water savings and ensuring reliable connectivity. A robust software development system has integrated IoT subsystems for olive grove management, centralizing measurement data in a web-accessible database. This enables real-time monitoring, trend analysis, and cultivation optimization. The system is hosted on a public cloud platform, using Docker for flexible deployment and data management. In the olive grove in Peta, a specialized InfluxDB routine optimizes water use, operating effectively for two years. An annual dashboard highlights key data points, including soil moisture, temperature readings, and health diagnostics. Water consumption was reduced by 42% in 2020 and 25% in 2021. An identification application secures user data management and supports sustainability.},
 bibtype = {article},
 author = {Liopa-Tsakalidi, Aglaia and Thomopoulos, Vasileios and Barouchas, Pantelis and Boursianis, Achilles D and Goudos, Sotirios K},
 doi = {https://doi.org/10.1016/j.atech.2024.100673},
 journal = {Smart Agricultural Technology}
}

Summary Irrigation drives water consumption in agriculture, essential for crop productivity and conserving water resources. Smart irrigation optimizes water usage, enhances yields, and supports sustainability. Integrating Information and Communication Technologies (ICT) and the Internet of Things (IoT) shows potential for reducing water consumption, but hardware, software, and connectivity solutions are still developing. Low-Power Wide-Area Access (LPWA) technologies enable energy-efficient IoT applications with long-range communication. LoRaWAN ensures secure data transmission up to 15 km using a single gateway. This paper presents a LoRaWAN-based prototype irrigation platform developed within the AREThOU5A framework, implemented in a 22-hectare olive grove with Kalamon olives in Greece. The system monitors soil moisture levels using IoT end nodes with low-cost microcontrollers and embedded sensors. Each node measures moisture at depths of 30 cm, 60 cm, and 90 cm, operating on battery power for months and communicating via LoRaWAN. Data is transmitted through a LoRaWAN gateway to a cloud-based infrastructure using 4G connectivity, allowing real-time access via online dashboards. Collected data will inform smart irrigation strategies, maximizing water savings and ensuring reliable connectivity. A robust software development system has integrated IoT subsystems for olive grove management, centralizing measurement data in a web-accessible database. This enables real-time monitoring, trend analysis, and cultivation optimization. The system is hosted on a public cloud platform, using Docker for flexible deployment and data management. In the olive grove in Peta, a specialized InfluxDB routine optimizes water use, operating effectively for two years. An annual dashboard highlights key data points, including soil moisture, temperature readings, and health diagnostics. Water consumption was reduced by 42% in 2020 and 25% in 2021. An identification application secures user data management and supports sustainability.

@inproceedings{
 title = {A Comparative Analysis between Sentiment Analysis Methods in Stock Prediction of IoT-based companies},
 type = {inproceedings},
 year = {2024},
 keywords = {Measurement;Sentiment analysis;Recurrent neural ne},
 pages = {57-62},
 id = {581b624c-a6f6-32ed-add5-0a0083a92311},
 created = {2025-04-05T17:21:03.917Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-04-05T17:21:03.917Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10945144},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Predictions in financial markets have attracted much of scholars’ interest. Since the stock market is generally defined as dynamic and volatile due to the affect of the well-known "Internet of Things" (IoT). It is a fact that IoT significantly impacts the financial market and stocks in various ways. Therefore, numerous researchers have attempted to detect patterns regarding the way financial markets react to various external factors. In the last decade, the integration of machine learning and sentiment analysis has appeared to be an effective approach for improving IoT-based stock price predictions in the financial field. This paper intends to propose an approach involving financial news as a source of information for forecasting the stock movement of noteworthy IoT-related companies, employing Big Data Analytics (BDA), Machine Learning, and Sentiment Analysis methods as well. A comparative analysis is conducted between lexicon-based and machine learning-based methods of sentiment analysis about their performance, particularly in the domain of IoT-related stock market prediction.},
 bibtype = {inproceedings},
 author = {Pasoi, Georgia E and Talattinis, Kyriacos A and Memos, Vasileios A and Goudos, Sotirios K and Sarigiannidis, Panagiotis G and Ishibashi, Yutaka and Psannis, Konstantinos E},
 doi = {10.1109/WSCE65107.2024.00016},
 booktitle = {2024 7th World Symposium on Communication Engineering (WSCE)}
}

Predictions in financial markets have attracted much of scholars’ interest. Since the stock market is generally defined as dynamic and volatile due to the affect of the well-known "Internet of Things" (IoT). It is a fact that IoT significantly impacts the financial market and stocks in various ways. Therefore, numerous researchers have attempted to detect patterns regarding the way financial markets react to various external factors. In the last decade, the integration of machine learning and sentiment analysis has appeared to be an effective approach for improving IoT-based stock price predictions in the financial field. This paper intends to propose an approach involving financial news as a source of information for forecasting the stock movement of noteworthy IoT-related companies, employing Big Data Analytics (BDA), Machine Learning, and Sentiment Analysis methods as well. A comparative analysis is conducted between lexicon-based and machine learning-based methods of sentiment analysis about their performance, particularly in the domain of IoT-related stock market prediction.

@inproceedings{
 title = {FraMark: A Blockchain Marketplace for a 5G Network Management using Fractional NFTs},
 type = {inproceedings},
 year = {2024},
 keywords = {5G mobile communication;Distributed ledger;Through},
 pages = {15-21},
 id = {4936a6c6-750a-354d-9b05-a21b3942010c},
 created = {2025-04-05T17:21:03.960Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2025-04-05T17:21:03.960Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10945166},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework’s claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management.},
 bibtype = {inproceedings},
 author = {Michoulis, George and Tsourdinis, Kyros and Niotis, George and Kyranou, Konstantinos and Fountoukidis, Eleutherios and Lagkas, Thomas and Argyriou, Vasileios and Sarigiannidis, Panagiotis and Psannis, Konstantinos E and Goudos, Sotirios K},
 doi = {10.1109/WSCE65107.2024.00009},
 booktitle = {2024 7th World Symposium on Communication Engineering (WSCE)}
}

This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework’s claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management.

@article{
 title = {TRUE: A Correlation Analysis Approach for Conducting Optimal Routing Metrics in VANETs},
 type = {article},
 year = {2023},
 pages = {55-58},
 volume = {5},
 id = {523623f9-5df5-3c3f-8719-ffd408603f10},
 created = {2022-11-29T07:13:52.962Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-03-02T21:14:22.422Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9965203},
 source_type = {article},
 private_publication = {false},
 abstract = {In vehicular networks, especially in urban scenarios, road topology-based routing shows great advantages in dealing with the problems of broken links and long delays originating from sparse connections and signal attenuation. However, how road status affect data transmission performance on various routing metrics is still an intricate and vague problem. Concerned with this problem, we propose a correlation analysis approach between road network features and routing metrics (TRUE) to assist in the construction of optimal routing metrics in road-based hierarchical inter-vehicle routing. Simulation results show that TRUE has a strong ability to optimize intermediate road selection.},
 bibtype = {article},
 author = {Bi, Zhenguo and Meng, Guiying and Hawbani, Ammar and Goudos, Sotirios K and Wan, Shaohua and Zhao, Liang},
 doi = {10.1109/LNET.2022.3225297},
 journal = {IEEE Networking Letters},
 number = {1}
}

In vehicular networks, especially in urban scenarios, road topology-based routing shows great advantages in dealing with the problems of broken links and long delays originating from sparse connections and signal attenuation. However, how road status affect data transmission performance on various routing metrics is still an intricate and vague problem. Concerned with this problem, we propose a correlation analysis approach between road network features and routing metrics (TRUE) to assist in the construction of optimal routing metrics in road-based hierarchical inter-vehicle routing. Simulation results show that TRUE has a strong ability to optimize intermediate road selection.

@inbook{
 type = {inbook},
 year = {2023},
 pages = {255-274},
 websites = {https://doi.org/10.1007/978-3-031-13786-0_10},
 publisher = {Springer International Publishing},
 city = {Cham},
 id = {7a7b7be0-1304-340d-af83-3c88d5e3297b},
 created = {2022-12-03T07:59:59.456Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-12-03T07:59:59.456Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2023},
 source_type = {inbook},
 private_publication = {false},
 abstract = {The future 6G wireless communications will need the definition of new spectral bands and the employment of novel advanced physical layer solutions. The millimeter-wave (mmWave) frequency bands have been allocated for the fifth generation (5G) of cellular systems, while additional mmWave sub-bands have been assigned as well. The need to support higher data rates than 5G in the order of terabits per second requires more bandwidth. However, the total consecutive available bandwidth in mmWave bands is still less than 10 GHz, so such data rates cannot be supported. In this context, future 6G communication systems require the use of the terahertz communication band (0.1--10 THz). The THz band is envisioned as a critical wireless technology for meeting future demands in 5G and beyond. For several years, there has been a lack of THz transceivers and antennas, so that the THz band has become one of the electromagnetic (EM) spectrum's least studied frequency ranges in terms of wireless communication. However, the need for 6G communication systems has redefined the requirements for THz antennas. In this book chapter, we provide a complete framework for circular polarized antenna design in the low THz band. This optimization framework is based on a swarm intelligence algorithm, namely, the salp swarm algorithm (SSA). The numerical results show that the SSA has been successfully applied in designing antenna with wide band operation and circular polarization.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K and Matin, Mohammad A},
 editor = {Matin, Mohammad Abdul},
 doi = {10.1007/978-3-031-13786-0_10},
 chapter = {Wide Band THz Antenna Design Using Salp Swarm Algorithm for 6G Communications Systems},
 title = {A Glimpse Beyond 5G in Wireless Networks}
}

The future 6G wireless communications will need the definition of new spectral bands and the employment of novel advanced physical layer solutions. The millimeter-wave (mmWave) frequency bands have been allocated for the fifth generation (5G) of cellular systems, while additional mmWave sub-bands have been assigned as well. The need to support higher data rates than 5G in the order of terabits per second requires more bandwidth. However, the total consecutive available bandwidth in mmWave bands is still less than 10 GHz, so such data rates cannot be supported. In this context, future 6G communication systems require the use of the terahertz communication band (0.1--10 THz). The THz band is envisioned as a critical wireless technology for meeting future demands in 5G and beyond. For several years, there has been a lack of THz transceivers and antennas, so that the THz band has become one of the electromagnetic (EM) spectrum's least studied frequency ranges in terms of wireless communication. However, the need for 6G communication systems has redefined the requirements for THz antennas. In this book chapter, we provide a complete framework for circular polarized antenna design in the low THz band. This optimization framework is based on a swarm intelligence algorithm, namely, the salp swarm algorithm (SSA). The numerical results show that the SSA has been successfully applied in designing antenna with wide band operation and circular polarization.

@article{
 title = {A Novel Deep Learning Model for Medical Report Generation by Inter-Intra Information Calibration},
 type = {article},
 year = {2023},
 pages = {5110-5121},
 volume = {27},
 id = {a1eaa3ea-6058-3cf4-af46-4731c0af6a4b},
 created = {2023-01-13T18:51:08.741Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-10-06T06:28:09.186Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10016250},
 source_type = {article},
 private_publication = {false},
 abstract = {Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the model is widely adopted in previous methods. However, they suffer from two problems: 1) The injected external information is limited in amount and difficult to adequately meet the information needs of medical report generation in content. 2) The injected external information increases the complexity of model and is hard to be reasonably integrated into the generation process of medical reports. Therefore, we propose an Information Calibrated Transformer (ICT) to address the above issues. First, we design a Precursor-information Enhancement Module (PEM), which can effectively extract numerous inter-intra report features from the datasets as the auxiliary information without external injection. And the auxiliary information can be dynamically updated with the training process. Secondly, a combination mode, which consists of PEM and our proposed Information Calibration Attention Module (ICA), is designed and embedded into ICT. In this method, the auxiliary information extracted from PEM is flexibly injected into ICT and the increment of model parameters is small. The comprehensive evaluations validate that the ICT is not only superior to previous methods in the X-Ray datasets, IU-X-Ray and MIMIC-CXR, but also successfully be extended to a CT COVID-19 dataset COV-CTR.},
 bibtype = {article},
 author = {Zhang, Junsan and Shen, Xiuxuan and Wan, Shaohua and Goudos, Sotirios K and Wu, Jie and Cheng, Ming and Zhang, Weishan},
 doi = {10.1109/JBHI.2023.3236661},
 journal = {IEEE Journal of Biomedical and Health Informatics},
 number = {10}
}

Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the model is widely adopted in previous methods. However, they suffer from two problems: 1) The injected external information is limited in amount and difficult to adequately meet the information needs of medical report generation in content. 2) The injected external information increases the complexity of model and is hard to be reasonably integrated into the generation process of medical reports. Therefore, we propose an Information Calibrated Transformer (ICT) to address the above issues. First, we design a Precursor-information Enhancement Module (PEM), which can effectively extract numerous inter-intra report features from the datasets as the auxiliary information without external injection. And the auxiliary information can be dynamically updated with the training process. Secondly, a combination mode, which consists of PEM and our proposed Information Calibration Attention Module (ICA), is designed and embedded into ICT. In this method, the auxiliary information extracted from PEM is flexibly injected into ICT and the increment of model parameters is small. The comprehensive evaluations validate that the ICT is not only superior to previous methods in the X-Ray datasets, IU-X-Ray and MIMIC-CXR, but also successfully be extended to a CT COVID-19 dataset COV-CTR.

@article{
 title = {Artificial intelligence (AI) and machine learning (ML) for beyond 5G/6G communications},
 type = {article},
 year = {2023},
 pages = {22},
 volume = {2023},
 websites = {https://doi.org/10.1186/s13638-023-02212-z},
 id = {bd675380-17bd-3a33-9abe-39f138069272},
 created = {2023-01-28T11:40:23.293Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-01-28T11:40:23.293Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Matin2023},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {Matin, Mohammad Abdul and Goudos, Sotirios K and Wan, Shaohua and Sarigiannidis, Panagiotis and Tentzeris, Emmanouil M},
 doi = {10.1186/s13638-023-02212-z},
 journal = {EURASIP Journal on Wireless Communications and Networking},
 number = {1}
}

@article{
 title = {LoRa-Based IoT Network Assessment in Rural and Urban Scenarios},
 type = {article},
 year = {2023},
 volume = {23},
 websites = {https://www.mdpi.com/1424-8220/23/3/1695},
 id = {75a8678a-622d-379b-ab77-23e17460ca72},
 created = {2023-02-03T21:21:17.488Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-03T21:21:17.488Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {s23031695},
 source_type = {article},
 private_publication = {false},
 abstract = {The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks.},
 bibtype = {article},
 author = {Griva, Aikaterini I and Boursianis, Achilles D and Wan, Shaohua and Sarigiannidis, Panagiotis and Psannis, Konstantinos E and Karagiannidis, George and Goudos, Sotirios K},
 doi = {10.3390/s23031695},
 journal = {Sensors},
 number = {3}
}

The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks.

@article{
 title = {Residual Compensation-based Extreme Learning Machine for MIMO-NOMA Receiver},
 type = {article},
 year = {2023},
 pages = {13398-13407},
 volume = {11},
 id = {1ccac330-42bc-354c-b051-14fca54a9ffd},
 created = {2023-02-07T08:25:38.459Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-15T07:26:56.187Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10038667},
 source_type = {article},
 private_publication = {false},
 abstract = {Extreme learning machine (ELM) uses a simple machine learning (ML) architecture that allows its implementation for smart IoT network operations. However, some inaccuracy lies between the predicted and the actual data during the ELM training, which can be caused due to the limitation of the modeling representation. This paper thus investigates a residual compensation-based ELM (RC-ELM) for its application in designing a receiver for MIMO-NOMA aided IoT systems. In RC-ELM, the base ELM layers determine the relationship between the transmitted and received data and the additional layers of the RC-ELM attempt to compensate the error introduced during the training mechanism. The analysis of the appropriate number of compensation layers for training error minimization is conducted on the basis of the bit error rate (BER) and the error vector magnitude (EVM) performances of the RC-ELM training. A minimum BER improvement of 5% for user 1 and 18% for user 2 is shown with with the aid of RC-ELM for a two-IoT user instance. The EVM is marginally increased by 0.0008% for user 1 and 1.61% for user 2 in training stage. Besides, the RC-ELM receiver is also compared to the minimum mean square error (MMSE), the classic ELM and the trained multilayer perceptron (MLP) receivers in terms of BER and EVM. Both of the ELM receivers show improved performances with respect to the other receivers.},
 bibtype = {article},
 author = {Rezwanul Mahmood, M and Matin, Mohammad Abdul and Sarigiannidis, Panagiotis and Goudos, Sotirios K and Karagiannidis, George K},
 doi = {10.1109/ACCESS.2023.3242917},
 journal = {IEEE Access}
}

Extreme learning machine (ELM) uses a simple machine learning (ML) architecture that allows its implementation for smart IoT network operations. However, some inaccuracy lies between the predicted and the actual data during the ELM training, which can be caused due to the limitation of the modeling representation. This paper thus investigates a residual compensation-based ELM (RC-ELM) for its application in designing a receiver for MIMO-NOMA aided IoT systems. In RC-ELM, the base ELM layers determine the relationship between the transmitted and received data and the additional layers of the RC-ELM attempt to compensate the error introduced during the training mechanism. The analysis of the appropriate number of compensation layers for training error minimization is conducted on the basis of the bit error rate (BER) and the error vector magnitude (EVM) performances of the RC-ELM training. A minimum BER improvement of 5% for user 1 and 18% for user 2 is shown with with the aid of RC-ELM for a two-IoT user instance. The EVM is marginally increased by 0.0008% for user 1 and 1.61% for user 2 in training stage. Besides, the RC-ELM receiver is also compared to the minimum mean square error (MMSE), the classic ELM and the trained multilayer perceptron (MLP) receivers in terms of BER and EVM. Both of the ELM receivers show improved performances with respect to the other receivers.

@article{
 title = {Music Deep Learning: Deep Learning Methods for Music Signal Processing - A Review of The State-of-the-Art},
 type = {article},
 year = {2023},
 pages = {17031-17052},
 volume = {11},
 id = {60a450dc-3571-32f6-a63c-a4419836ab21},
 created = {2023-02-14T08:26:52.047Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-03-02T21:12:07.124Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10043650},
 source_type = {article},
 private_publication = {false},
 abstract = {The discipline of Deep Learning has been recognized for its strong computational tools, which have been extensively used in data and signal processing, with innumerable promising results. Among the many commercial applications of Deep Learning, Music Signal Processing has received an increasing amount of attention over the last decade. This work reviews the most recent developments in Deep Learning in Music signal processing. Two main applications that are discussed are Music Information Retrieval, which spans a plethora of applications, and Music Generation, which can fit a range of musical styles. After a review of both topics, several emerging directions are identified for future research.},
 bibtype = {article},
 author = {Moysis, Lazaros and Iliadis, Lazaros Alexios and Sotiroudis, Sotirios P and Boursianis, Achilles D and Papadopoulou, Maria S and Kokkinidis, Konstantinos-Iraklis D and Volos, Christos and Sarigiannidis, Panagiotis and Nikolaidis, Spiridon and Goudos, Sotirios K},
 doi = {10.1109/ACCESS.2023.3244620},
 journal = {IEEE Access}
}

The discipline of Deep Learning has been recognized for its strong computational tools, which have been extensively used in data and signal processing, with innumerable promising results. Among the many commercial applications of Deep Learning, Music Signal Processing has received an increasing amount of attention over the last decade. This work reviews the most recent developments in Deep Learning in Music signal processing. Two main applications that are discussed are Music Information Retrieval, which spans a plethora of applications, and Music Generation, which can fit a range of musical styles. After a review of both topics, several emerging directions are identified for future research.

@article{
 title = {Dual-Band Rectifier Circuit Design for IoT Communication in 5G Systems},
 type = {article},
 year = {2023},
 volume = {11},
 websites = {https://www.mdpi.com/2227-7080/11/2/34},
 id = {f3b85552-fc32-3fb3-9346-8d0abc099493},
 created = {2023-02-24T14:56:51.642Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-24T14:56:51.642Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies11020034},
 source_type = {article},
 private_publication = {false},
 abstract = {Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More particularly, we designed a dual-band RF to DC rectifier circuit at sub-6 GHz in the 5G bands, able to supply low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at 3.5 GHz and 5 GHz in the 5G cellular network’s frequency band FR1. Numerical results reveal that the system provides maximum power conversion efficiency (PCE) equal to 53% when the output load (sensor or microcontroller) is 1.74 kΩ and the input power is 12 dBm.},
 bibtype = {article},
 author = {Bougas, Ioannis D and Papadopoulou, Maria S and Boursianis, Achilles D and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.3390/technologies11020034},
 journal = {Technologies},
 number = {2}
}

Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More particularly, we designed a dual-band RF to DC rectifier circuit at sub-6 GHz in the 5G bands, able to supply low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at 3.5 GHz and 5 GHz in the 5G cellular network’s frequency band FR1. Numerical results reveal that the system provides maximum power conversion efficiency (PCE) equal to 53% when the output load (sensor or microcontroller) is 1.74 kΩ and the input power is 12 dBm.

@article{
 title = {Beam-Selection for 5G/B5G Networks Using Machine Learning: A Comparative Study},
 type = {article},
 year = {2023},
 volume = {23},
 websites = {https://www.mdpi.com/1424-8220/23/6/2967},
 id = {9c58d5f3-49bd-3780-8fb1-7325b4a8abe9},
 created = {2023-03-09T08:27:21.560Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-03-09T08:27:21.560Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {s23062967},
 source_type = {article},
 private_publication = {false},
 abstract = {A challenging problem in millimeter wave (mmWave) communications for the fifth generation of cellular communications and beyond (5G/B5G) is the beam selection problem. This is due to severe attenuation and penetration losses that are inherent in the mmWave band. Thus, the beam selection problem for mmWave links in a vehicular scenario can be solved as an exhaustive search among all candidate beam pairs. However, this approach cannot be assuredly completed within short contact times. On the other hand, machine learning (ML) has the potential to significantly advance 5G/B5G technology, as evidenced by the growing complexity of constructing cellular networks. In this work, we perform a comparative study of using different ML methods to solve the beam selection problem. We use a common dataset for this scenario found in the literature. We increase the accuracy of these results by approximately 30%. Moreover, we extend the given dataset by producing additional synthetic data. We apply ensemble learning techniques and obtain results with about 94% accuracy. The novelty of our work lies in the fact that we improve the existing dataset by adding more synthetic data and by designing a custom ensemble learning method for the problem at hand.},
 bibtype = {article},
 author = {Chatzoglou, Efstratios and Goudos, Sotirios K},
 doi = {10.3390/s23062967},
 journal = {Sensors},
 number = {6}
}

A challenging problem in millimeter wave (mmWave) communications for the fifth generation of cellular communications and beyond (5G/B5G) is the beam selection problem. This is due to severe attenuation and penetration losses that are inherent in the mmWave band. Thus, the beam selection problem for mmWave links in a vehicular scenario can be solved as an exhaustive search among all candidate beam pairs. However, this approach cannot be assuredly completed within short contact times. On the other hand, machine learning (ML) has the potential to significantly advance 5G/B5G technology, as evidenced by the growing complexity of constructing cellular networks. In this work, we perform a comparative study of using different ML methods to solve the beam selection problem. We use a common dataset for this scenario found in the literature. We increase the accuracy of these results by approximately 30%. Moreover, we extend the given dataset by producing additional synthetic data. We apply ensemble learning techniques and obtain results with about 94% accuracy. The novelty of our work lies in the fact that we improve the existing dataset by adding more synthetic data and by designing a custom ensemble learning method for the problem at hand.

@article{
 title = {Joint QoS Aware Admission Control and Power Allocation in NOMA Downlink Networks},
 type = {article},
 year = {2023},
 pages = {30873-30887},
 volume = {11},
 id = {1f7aa0d0-b48c-30a0-aef9-d12e8a1519a3},
 created = {2023-03-28T07:18:16.121Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-03-31T06:12:22.302Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10081366},
 source_type = {article},
 private_publication = {false},
 abstract = {In this work, we talk about the problem of joint power allocation and user association based on quality-of-service for non-orthogonal multiple access (NOMA) to downlink networks. The problem is especially difficult due to its non-convex form and the large number of optimization variables, which are solved using two different nature-inspired algorithms with low complexity. We investigate the effect of different network parameters on increasing users. Numerical results show that, for a growing number of users, the problem is becoming increasingly difficult, which indicates the increasing network resources required to solve it. The results of the simulations show that using evolutionary algorithms is a fast and effective way to solve this kind of problem. Moreover, the NOMA advantage over OMA becomes clear as the number of users increases. Evolutionary techniques outperform randomly generated solutions, as expected.},
 bibtype = {article},
 author = {Goudos, Sotirios K and Diamantoulakis, Panagiotis D and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Psannis, Konstantinos E and Matin, Mohammad Abdul and Wan, Shaohua and Karagiannidis, George},
 doi = {10.1109/ACCESS.2023.3262117},
 journal = {IEEE Access}
}

In this work, we talk about the problem of joint power allocation and user association based on quality-of-service for non-orthogonal multiple access (NOMA) to downlink networks. The problem is especially difficult due to its non-convex form and the large number of optimization variables, which are solved using two different nature-inspired algorithms with low complexity. We investigate the effect of different network parameters on increasing users. Numerical results show that, for a growing number of users, the problem is becoming increasingly difficult, which indicates the increasing network resources required to solve it. The results of the simulations show that using evolutionary algorithms is a fast and effective way to solve this kind of problem. Moreover, the NOMA advantage over OMA becomes clear as the number of users increases. Evolutionary techniques outperform randomly generated solutions, as expected.

@article{
 title = {Evolutionary Ensemble Learning Pathloss Prediction for 4G and 5G Flying Base Stations with UAVs},
 type = {article},
 year = {2023},
 pages = {5994-6005},
 volume = {71},
 id = {34139781-9126-303f-87e3-e8e989c15c66},
 created = {2023-04-19T07:52:47.805Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-07T12:58:38.863Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10105215},
 source_type = {article},
 private_publication = {false},
 abstract = {The usage of unmanned aerial vehicles (UAVs) as flying base stations (FBSs) for expanding coverage and assisting the terrestrial cellular networks constitutes a promising technology for 5G and beyond. A crucial parameter affecting cellular network design is path loss prediction. An alternative to the accurate, though time-consuming, propagation prediction with deterministic Ray Tracing models could be Machine Learning (ML) based predictions. Ensemble Learning techniques are used in order to optimally combine the predictions of standalone models. That is, they combine the best-performing individual models into a better-performing meta-model. Our proposed method of the evolutionary tuned stacked ensemble optimizes the ensemble as a whole, instead of optimizing its individual base learners. To the best of our knowledge, this is the first time that an evolutionary technique is applied in order to mutually tune an ensemble’s base learners for a path loss modeling problem in electromagnetics. Moreover, we present a model that works in more than one frequency. As opposed to the standard implementation of ensemble learning, our method offers a significant performance boost with low complexity.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P and Athanasiadou, Georgia and Tsoulos, George and Sarigiannidis, Panagiotis and Christodoulou, Christos and Goudos, Sotirios K},
 doi = {10.1109/TAP.2023.3266784},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {7}
}

The usage of unmanned aerial vehicles (UAVs) as flying base stations (FBSs) for expanding coverage and assisting the terrestrial cellular networks constitutes a promising technology for 5G and beyond. A crucial parameter affecting cellular network design is path loss prediction. An alternative to the accurate, though time-consuming, propagation prediction with deterministic Ray Tracing models could be Machine Learning (ML) based predictions. Ensemble Learning techniques are used in order to optimally combine the predictions of standalone models. That is, they combine the best-performing individual models into a better-performing meta-model. Our proposed method of the evolutionary tuned stacked ensemble optimizes the ensemble as a whole, instead of optimizing its individual base learners. To the best of our knowledge, this is the first time that an evolutionary technique is applied in order to mutually tune an ensemble’s base learners for a path loss modeling problem in electromagnetics. Moreover, we present a model that works in more than one frequency. As opposed to the standard implementation of ensemble learning, our method offers a significant performance boost with low complexity.

@article{
 title = {Post-Processing Fairness Evaluation of Federated Models: An Unsupervised Approach in Healthcare},
 type = {article},
 year = {2023},
 pages = {2518-2529},
 volume = {20},
 id = {ceadb4d4-9b87-39f0-838a-89ead65f426b},
 created = {2023-04-26T07:48:39.312Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-08-10T16:07:48.611Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10107702},
 source_type = {article},
 private_publication = {false},
 abstract = {Modern Healthcare cyberphysical systems have begun to rely more and more on distributed AI leveraging the power of Federated Learning (FL). Its ability to train Machine Learning (ML) and Deep Learning (DL) models for the wide variety of medical fields, while at the same time fortifying the privacy of the sensitive information that are present in the medical sector, makes the FL technology a necessary tool in modern health and medical systems. Unfortunately, due to the polymorphy of distributed data and the shortcomings of distributed learning, the local training of Federated models sometimes proves inadequate and thus negatively imposes the federated learning optimization process and in extend in the subsequent performance of the rest Federated models. Badly trained models can cause dire implications in the healthcare field due to their critical nature. This work strives to solve this problem by applying a post-processing pipeline to models used by FL. In particular, the proposed work ranks the model by finding how fair they are by discovering and inspecting micro-Manifolds that cluster each neural model's latent knowledge. The produced work applies a completely unsupervised both model and data agnostic methodology that can be leveraged for general model fairness discovery. The proposed methodology is tested against a variety of benchmark DL architectures and in the FL environment, showing an average 8.75% increase in Federated model accuracy in comparison with similar work.},
 bibtype = {article},
 author = {Siniosoglou, Ilias and Argyriou, Vasileios and Sarigiannidis, Panagiotis and Lagkas, Thomas and Sarigiannidis, Antonios and Goudos, Sotirios K and Wan, Shaohua},
 doi = {10.1109/TCBB.2023.3269767},
 journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
 number = {4}
}

Modern Healthcare cyberphysical systems have begun to rely more and more on distributed AI leveraging the power of Federated Learning (FL). Its ability to train Machine Learning (ML) and Deep Learning (DL) models for the wide variety of medical fields, while at the same time fortifying the privacy of the sensitive information that are present in the medical sector, makes the FL technology a necessary tool in modern health and medical systems. Unfortunately, due to the polymorphy of distributed data and the shortcomings of distributed learning, the local training of Federated models sometimes proves inadequate and thus negatively imposes the federated learning optimization process and in extend in the subsequent performance of the rest Federated models. Badly trained models can cause dire implications in the healthcare field due to their critical nature. This work strives to solve this problem by applying a post-processing pipeline to models used by FL. In particular, the proposed work ranks the model by finding how fair they are by discovering and inspecting micro-Manifolds that cluster each neural model's latent knowledge. The produced work applies a completely unsupervised both model and data agnostic methodology that can be leveraged for general model fairness discovery. The proposed methodology is tested against a variety of benchmark DL architectures and in the FL environment, showing an average 8.75% increase in Federated model accuracy in comparison with similar work.

@article{
 title = {RIS-Assisted Multi-User MIMO Systems Exploiting Extreme Learning Machine},
 type = {article},
 year = {2023},
 pages = {47129-47136},
 volume = {11},
 id = {524dbc37-d39a-3568-989f-c57fc22b8976},
 created = {2023-05-12T20:53:12.493Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-05-20T12:29:35.636Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10123934},
 source_type = {article},
 private_publication = {false},
 abstract = {Massive multiple-input multiple-output (mMIMO), assisted by reconfigurable intelligent surface (RIS), can ensure reliable and energy-efficient data transmission. However, the receiver design for large-scale networks based on traditional mathematical approaches requires complex statistics. Therefore, in this paper, machine learning (ML) approaches are investigated to design receivers for the RIS-assisted multi-user MIMO (muMIMO) systems to avoid complicated channel information requirements. Extreme learning machine (ELM) is an effective ML tool for MIMO receiver design because it simplifies the learning process. However, the learning performance of the ELM can get affected by the random choice of its hidden layer size. To address this issues, this paper proposes an incremental ELM (I-ELM) based receiver for the RIS-mu-MIMO system. The proposed receiver computes the weights between the hidden and the output layer based on the automated incremental addition of hidden neurons and provided conditions. The suggested receiver is contrasted with the multilayer perceptron (MLP), conventional ELM, and minimum mean square error (MMSE) receivers. The simulation results show that the throughput performance of the proposed receiver is satisfactory.},
 bibtype = {article},
 author = {Rezwanul Mahmood, M and Matin, Mohammad Abdul and Goudos, Sotirios K},
 doi = {10.1109/ACCESS.2023.3275755},
 journal = {IEEE Access}
}

Massive multiple-input multiple-output (mMIMO), assisted by reconfigurable intelligent surface (RIS), can ensure reliable and energy-efficient data transmission. However, the receiver design for large-scale networks based on traditional mathematical approaches requires complex statistics. Therefore, in this paper, machine learning (ML) approaches are investigated to design receivers for the RIS-assisted multi-user MIMO (muMIMO) systems to avoid complicated channel information requirements. Extreme learning machine (ELM) is an effective ML tool for MIMO receiver design because it simplifies the learning process. However, the learning performance of the ELM can get affected by the random choice of its hidden layer size. To address this issues, this paper proposes an incremental ELM (I-ELM) based receiver for the RIS-mu-MIMO system. The proposed receiver computes the weights between the hidden and the output layer based on the automated incremental addition of hidden neurons and provided conditions. The suggested receiver is contrasted with the multilayer perceptron (MLP), conventional ELM, and minimum mean square error (MMSE) receivers. The simulation results show that the throughput performance of the proposed receiver is satisfactory.

@article{
 title = {Source detection with multi-label classification},
 type = {article},
 year = {2023},
 pages = {336-345},
 volume = {4},
 id = {bb2b6a06-d407-3702-906b-0275720cd5aa},
 created = {2023-05-30T06:00:24.727Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-06-16T05:45:24.765Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10137757},
 source_type = {article},
 private_publication = {false},
 abstract = {Radio source detection through conventional algorithms has been unreliable when trying to solve for large number of sources in the presence of low SINR and less number of snapshots. We address this by reformulating source detection as a multi-class classification problem solved using deep learning frameworks. Incoming waveforms are sampled using a centro-symmetric linear array with omni-directional elements and the normalized upper triangle of the autocorrelation matrix is extracted as the input feature to a modified convolutional neural network with uni-dimensional filters, trained to detect the sources in the presence of both uncorrelated and correlated signals. Two detection algorithms are introduced and referred to as CNNDetector and RadioNet, and subsequently benchmarked against the conventional source detection algorithms. By including pre-processing in forward backward spatial smoothing, RadioNet can also resolve the number of uncorrelated sources in the presence of correlated paths. Finally, the algorithms are stress tested under challenging operational conditions and extensive evaluations are presented showing the efficacy and contributions of the introduced predictive models. To the best of our knowledge, this is the first time the source detection problem has resolved L-1 sources, for an antenna array of L elements using a deep learning framework.},
 bibtype = {article},
 author = {Vijayamohanan, Jayakrishnan and Gupta, Arjun and Noakoasteen, Oameed and Goudos, Sotirios K and Christodoulou, Christos G},
 doi = {10.1109/OJSP.2023.3280854},
 journal = {IEEE Open Journal of Signal Processing}
}

Radio source detection through conventional algorithms has been unreliable when trying to solve for large number of sources in the presence of low SINR and less number of snapshots. We address this by reformulating source detection as a multi-class classification problem solved using deep learning frameworks. Incoming waveforms are sampled using a centro-symmetric linear array with omni-directional elements and the normalized upper triangle of the autocorrelation matrix is extracted as the input feature to a modified convolutional neural network with uni-dimensional filters, trained to detect the sources in the presence of both uncorrelated and correlated signals. Two detection algorithms are introduced and referred to as CNNDetector and RadioNet, and subsequently benchmarked against the conventional source detection algorithms. By including pre-processing in forward backward spatial smoothing, RadioNet can also resolve the number of uncorrelated sources in the presence of correlated paths. Finally, the algorithms are stress tested under challenging operational conditions and extensive evaluations are presented showing the efficacy and contributions of the introduced predictive models. To the best of our knowledge, this is the first time the source detection problem has resolved L-1 sources, for an antenna array of L elements using a deep learning framework.

@inproceedings{
 title = {Path Loss Modeling for Flying Ad-Hoc Networks:An Ensemble Learning Approach},
 type = {inproceedings},
 year = {2023},
 keywords = {Wireless networks;Urban areas;Predictive models;Ra},
 pages = {1-5},
 id = {b3a51d0c-bd3e-392d-a1d9-efae02a3a120},
 created = {2023-06-01T16:42:48.283Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-06-01T16:42:48.283Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10133008},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Several Machine Learning (ML) approaches have been proposed for path loss (PL) prediction in emerging fifth generation and beyond (5G/B5G) cellular communication networks. In the domain of next-generation high-availability communications, flying ad hoc networks (FANETs), which function as clusters of deployable relays or base stations for the on-demand extension of cellular coverage, represent a promising alternative. Thus, the highly accurate path prediction is crucial for the FANETs deployment and for emerging B5G wireless networks design, planning, and optimization. In this paper, we model the path loss in an urban environment for different heights using different ensemble learning approaches. More specifically, we apply five different boosting approaches are, as well a new ensemble model based on a stacked generalization technique for more robust and accurate predictions. The proposed ensemble approaches exhibit great accuracy and efficiency in predicting the path loss for FANETs deployment in cellular networks.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Boursianis, Achilles D and Athanasiadou, Georgia and Tsoulos, George V and Christodoulou, Christos and Goudos, Sotirios K},
 doi = {10.23919/EuCAP57121.2023.10133008},
 booktitle = {2023 17th European Conference on Antennas and Propagation (EuCAP)}
}

Several Machine Learning (ML) approaches have been proposed for path loss (PL) prediction in emerging fifth generation and beyond (5G/B5G) cellular communication networks. In the domain of next-generation high-availability communications, flying ad hoc networks (FANETs), which function as clusters of deployable relays or base stations for the on-demand extension of cellular coverage, represent a promising alternative. Thus, the highly accurate path prediction is crucial for the FANETs deployment and for emerging B5G wireless networks design, planning, and optimization. In this paper, we model the path loss in an urban environment for different heights using different ensemble learning approaches. More specifically, we apply five different boosting approaches are, as well a new ensemble model based on a stacked generalization technique for more robust and accurate predictions. The proposed ensemble approaches exhibit great accuracy and efficiency in predicting the path loss for FANETs deployment in cellular networks.

@inproceedings{
 title = {Modified Bow-Tie Antenna Design Using Artificial Hummingbird Algorithm for Wireless Power Transfer IoT Applications},
 type = {inproceedings},
 year = {2023},
 keywords = {Wireless communication;Wireless sensor networks;Ti},
 pages = {1-5},
 id = {a8b95a28-76f1-348c-bd35-3abb127967e7},
 created = {2023-06-01T16:42:48.294Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-06-01T16:42:48.294Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10133339},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The advent of the Internet of Things has allowed the re-usability of established techniques combined with emerging technologies. In the TERMINET project, several key-enabling technologies in an IoT ecosystem are explored. The smart farming paradigm is one of the realistic use cases of the project, in which Wireless Power Transfer, assisted by an Unmanned Aerial Vehicle, will be demonstrated as a proof-of-concept, to deliver energy in wireless sensor networks. In this work, we provide a feasible solution of a rectifying antenna module in a rectenna system, which operates in the Wi-Fi 2.4 GHz frequency band. The proposed antenna is optimized by utilizing the Artificial Hummingbird Algorithm. Numerical results demonstrate excellent performance of the proposed antenna, in terms of the key characteristics of reflection coefficient, input impedance, realized gain, and efficiency.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Griva, Aikaterini I and Rekkas, Vasileios P and Iliadis, Lazaros A and Sotiroudis, Sotirios P and Diamantoulakis, Panagiotis and Lagkas, Thomas and Sarigiannidis, Panagiotis and Goudos, Sotirios K and Christodoulou, Christos and Karagiannidis, George K},
 doi = {10.23919/EuCAP57121.2023.10133339},
 booktitle = {2023 17th European Conference on Antennas and Propagation (EuCAP)}
}

The advent of the Internet of Things has allowed the re-usability of established techniques combined with emerging technologies. In the TERMINET project, several key-enabling technologies in an IoT ecosystem are explored. The smart farming paradigm is one of the realistic use cases of the project, in which Wireless Power Transfer, assisted by an Unmanned Aerial Vehicle, will be demonstrated as a proof-of-concept, to deliver energy in wireless sensor networks. In this work, we provide a feasible solution of a rectifying antenna module in a rectenna system, which operates in the Wi-Fi 2.4 GHz frequency band. The proposed antenna is optimized by utilizing the Artificial Hummingbird Algorithm. Numerical results demonstrate excellent performance of the proposed antenna, in terms of the key characteristics of reflection coefficient, input impedance, realized gain, and efficiency.

@inproceedings{
 title = {Triple-band Modified Printed Inverted-F Antenna Design for WI-FI-7 Applications},
 type = {inproceedings},
 year = {2023},
 keywords = {Fabrication;Stripline;Optimization methods;Europe;},
 pages = {1-4},
 id = {212fea64-7511-3134-9a2d-1f21c37bb659},
 created = {2023-06-01T16:42:48.414Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-06-01T16:42:48.414Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10133464},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {WI-FI-6/6E is now commercialized and the WI-FI community is currently developing the IEEE 802.11be standard, namely WI-FI-7, which will offer enhanced throughput and higher data rate than its predecessors. In this article, a compact triple-band printed inverted-F (IF) antenna operating at 2.4 GHz, 5 GHz, and 6 GHz frequency bands is designed for WI-FI-7 applications. We design a novel antenna structure that is well-suited for triple-band operation. The core idea is to use a stripline as a feeder that also couples two modified IF designs. A nature-inspired optimization method, namely the artificial hummingbird algorithm (AHA), is used to achieve an optimal design solution for the triple-band IF antenna. Computed results demonstrate that the proposed antenna achieves satisfactory results regarding the reflection coefficient and the realized gain in all the frequency bands of interest.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros A and Rekkas, Vasileios P and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Karagiannidis, George K and Christodoulou, Christos and Goudos, Sotirios K},
 doi = {10.23919/EuCAP57121.2023.10133464},
 booktitle = {2023 17th European Conference on Antennas and Propagation (EuCAP)}
}

WI-FI-6/6E is now commercialized and the WI-FI community is currently developing the IEEE 802.11be standard, namely WI-FI-7, which will offer enhanced throughput and higher data rate than its predecessors. In this article, a compact triple-band printed inverted-F (IF) antenna operating at 2.4 GHz, 5 GHz, and 6 GHz frequency bands is designed for WI-FI-7 applications. We design a novel antenna structure that is well-suited for triple-band operation. The core idea is to use a stripline as a feeder that also couples two modified IF designs. A nature-inspired optimization method, namely the artificial hummingbird algorithm (AHA), is used to achieve an optimal design solution for the triple-band IF antenna. Computed results demonstrate that the proposed antenna achieves satisfactory results regarding the reflection coefficient and the realized gain in all the frequency bands of interest.

@inproceedings{
 title = {Aperture-coupled Bowtie Patch Antenna Design for Autonomous Driving Applications},
 type = {inproceedings},
 year = {2023},
 pages = {1-4},
 id = {9bf40190-f2e6-3b51-bea0-84f058c30d2a},
 created = {2023-07-11T05:28:41.625Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-11T05:28:41.625Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10171621},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Autonomous driving will reshape transportation networks, offering at the same time many benefits such as safety, reliable vehicle-to-vehicle communication, and extended telecommunications. For a self-driving vehicle to navigate freely and perceive its environment, it is necessary to be equipped with many sensors. Automotive radars and antenna arrays that operate at 76–81 GHz have been proposed as key elements in future autonomous vehicles. In this work, an aperture-coupled bowtie antenna is designed utilizing hunger games search optimization. The proposed element achieves quite satisfactory values of return loss and gain, as well as broadband operation at 76 GHz - 81 GHz.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros A and Boursianis, Achilles D and Rekkas, Vasileios P and Zaharis, Zaharias D and Koulouridis, Stavros and Goudos, Sotirios K},
 doi = {10.1109/iWAT57058.2023.10171621},
 booktitle = {2023 International Workshop on Antenna Technology (iWAT)}
}

Autonomous driving will reshape transportation networks, offering at the same time many benefits such as safety, reliable vehicle-to-vehicle communication, and extended telecommunications. For a self-driving vehicle to navigate freely and perceive its environment, it is necessary to be equipped with many sensors. Automotive radars and antenna arrays that operate at 76–81 GHz have been proposed as key elements in future autonomous vehicles. In this work, an aperture-coupled bowtie antenna is designed utilizing hunger games search optimization. The proposed element achieves quite satisfactory values of return loss and gain, as well as broadband operation at 76 GHz - 81 GHz.

@inproceedings{
 title = {Construction of Piecewise Chaotic Maps With Tunable Statistical Mean},
 type = {inproceedings},
 year = {2023},
 keywords = {Chaos;Interpolation;Circuits and systems;Time seri},
 pages = {1-4},
 id = {db8e0f10-fa58-3c6b-94ff-115b8e4352cf},
 created = {2023-07-18T07:56:57.161Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.161Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176612},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In numerous chaos based applications, it is often important to use chaotic maps that showcase desirable statistical characteristics, that can improve the performance of the designed architecture. Yet, it is hard to design maps that can achieve the desired statistical properties. Motivated by this, this work considers a family of piecewise chaotic maps, and studies how tuning their parameters can affect the mean value of the generated chaotic trajectories. Such a family of maps can be highly practical in future chaos based applications.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Lawnik, Marcin and Baptista, Murilo S and Goudos, Sotirios and Volos, Christos},
 doi = {10.1109/MOCAST57943.2023.10176612},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In numerous chaos based applications, it is often important to use chaotic maps that showcase desirable statistical characteristics, that can improve the performance of the designed architecture. Yet, it is hard to design maps that can achieve the desired statistical properties. Motivated by this, this work considers a family of piecewise chaotic maps, and studies how tuning their parameters can affect the mean value of the generated chaotic trajectories. Such a family of maps can be highly practical in future chaos based applications.

@inproceedings{
 title = {Greek Orthodox Church Hymns Recognition Using Deep Learning Techniques},
 type = {inproceedings},
 year = {2023},
 keywords = {Deep learning;Performance evaluation;Circuits and},
 pages = {1-3},
 id = {dd301592-add8-33ee-a7fb-9162811c4610},
 created = {2023-07-18T07:56:57.194Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.194Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176857},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Deep learning techniques have found numerous applications in the sector of cultural and religious heritage. Greek Orthodox Church hymns are examples of Byzantine religious tradition. Their performance is governed by stringent rules not observed in other cultures. This work trains a novel shallow convolutional neural network to identify Greek Orthodox Church hymns using a private dataset. For ten of the most frequently chanted hymns, the deep learning model achieves over 98% accuracy. AlexNet and MobileNetV2 are trained on the same data to evaluate their performance. Additional analysis is conducted to validate the obtained results.},
 bibtype = {inproceedings},
 author = {Tsakatanis, Nikolaos and Iliadis, Lazaros A and Boursianis, Achilles D and Kokkinidis, Konstantinos-Iraklis D and Patronas, Georgios and Serafeim, Pavlos and Papadopoulou, Maria S and Goudos, Sotirios K},
 doi = {10.1109/MOCAST57943.2023.10176857},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Deep learning techniques have found numerous applications in the sector of cultural and religious heritage. Greek Orthodox Church hymns are examples of Byzantine religious tradition. Their performance is governed by stringent rules not observed in other cultures. This work trains a novel shallow convolutional neural network to identify Greek Orthodox Church hymns using a private dataset. For ten of the most frequently chanted hymns, the deep learning model achieves over 98% accuracy. AlexNet and MobileNetV2 are trained on the same data to evaluate their performance. Additional analysis is conducted to validate the obtained results.

@inproceedings{
 title = {5G Core PFCP Intrusion Detection Dataset},
 type = {inproceedings},
 year = {2023},
 keywords = {Industries;Privacy;Protocols;5G mobile communicati},
 pages = {1-4},
 id = {633736bd-ef3f-3546-be79-385d1ab859a7},
 created = {2023-07-18T07:56:57.424Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.424Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176693},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The rapid evolution of the 5G environments introduces several benefits, such as faster data transfer speeds, lower latency and energy efficiency. However, this situation brings also critical cybersecurity issues, such as the complex and increased attack surface, privacy concerns and the security of the 5G core network functions. Therefore, it is evident that the role of intrusion detection mechanisms empowered with Artificial Intelligence (AI) models is crucial. Therefore, in this paper, we introduce a labelled security dataset called 5GC PFCP Intrusion Detection Dataset. This dataset includes a set of network flow statistics that can be used by AI detection models to recognise cyberattacks against the Packet Forwarding Control Protocol (PFCP). PFCP is used for the N4 interface between the Session Management Function (SMF) and the User Plane Function (UPF) in the 5G core. In particular, four PFCP attacks are investigated in this paper, including the relevant network traffic data in terms of pcap files and the Transmission Control Protocol (TCP)/Internet Protocol (IP) and application-layer statistics. This dataset is already publicly available in IEEE Dataport and Zenodo.},
 bibtype = {inproceedings},
 author = {Amponis, George and Radoglou-Grammatikis, Panagiotis and Nakas, George and Goudos, Sotirios and Argyriou, Vasileios and Lagkas, Thomas and Sarigiannidis, Panagiotis},
 doi = {10.1109/MOCAST57943.2023.10176693},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The rapid evolution of the 5G environments introduces several benefits, such as faster data transfer speeds, lower latency and energy efficiency. However, this situation brings also critical cybersecurity issues, such as the complex and increased attack surface, privacy concerns and the security of the 5G core network functions. Therefore, it is evident that the role of intrusion detection mechanisms empowered with Artificial Intelligence (AI) models is crucial. Therefore, in this paper, we introduce a labelled security dataset called 5GC PFCP Intrusion Detection Dataset. This dataset includes a set of network flow statistics that can be used by AI detection models to recognise cyberattacks against the Packet Forwarding Control Protocol (PFCP). PFCP is used for the N4 interface between the Session Management Function (SMF) and the User Plane Function (UPF) in the 5G core. In particular, four PFCP attacks are investigated in this paper, including the relevant network traffic data in terms of pcap files and the Transmission Control Protocol (TCP)/Internet Protocol (IP) and application-layer statistics. This dataset is already publicly available in IEEE Dataport and Zenodo.

@inproceedings{
 title = {Energy Consumption Assessment in Refrigeration Equipment: The SmartFridge Project},
 type = {inproceedings},
 year = {2023},
 keywords = {Energy consumption;Circuits and systems;Computatio},
 pages = {1-4},
 id = {e0cfc328-fce9-3bac-b95b-c7dc40e0af89},
 created = {2023-07-18T07:56:57.440Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.440Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176514},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Energy consumption is a key factor in environmental sustainability and the economy. In the next 30 years, global food production will need to increase rapidly and, in this context, refrigeration will play a pivotal role. In the SmartFridge project, several aspects of the operating cycle of refrigeration equipment are explored. Energy consumption reduction is one of the most important use cases of the project. For this reason, this work provides an assessment of three scenarios in a refrigerator model, in which the indoor temperature and moisture, as well as the interior temperature, are explored to quantify their impact on energy consumption.},
 bibtype = {inproceedings},
 author = {Griva, Aikaterini I and Rekkas, Vasileios P and Koritsoglou, Kyriakos and Sotiroudis, Sotirios P and Boursianis, Achilles D and Papadopoulou, Maria S and Goudos, Sotirios K},
 doi = {10.1109/MOCAST57943.2023.10176514},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Energy consumption is a key factor in environmental sustainability and the economy. In the next 30 years, global food production will need to increase rapidly and, in this context, refrigeration will play a pivotal role. In the SmartFridge project, several aspects of the operating cycle of refrigeration equipment are explored. Energy consumption reduction is one of the most important use cases of the project. For this reason, this work provides an assessment of three scenarios in a refrigerator model, in which the indoor temperature and moisture, as well as the interior temperature, are explored to quantify their impact on energy consumption.

@inproceedings{
 title = {Model-Agnostic Meta-Learning Techniques: A State-of-The-Art Short Review},
 type = {inproceedings},
 year = {2023},
 keywords = {Metalearning;Training;Memory management;Stability},
 pages = {1-4},
 id = {b642cfac-2a91-32a0-b53d-3711424ba326},
 created = {2023-07-18T07:56:57.471Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.471Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176893},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the last few years, novel meta-learning techniques have established a new field of research. Great emphasis is given to few-shot learning approaches, where the model is trained by using only a few training examples. In this work, a review of several model-agnostic meta-learning methodologies (MAML) is presented. Firstly, we identify and discuss the typical characteristics of the first proposed MAML algorithm. Next, we classify the model-agnostic approaches into three main categories: Regular gradient descent MAML, Hessian-free MAML, and Bayesian MALM, by presenting their advantages and limitations. Finally, we conclude this work with further discussion and highlight the future research directions.},
 bibtype = {inproceedings},
 author = {Griva, Aikaterini I and Boursianis, Achilles D and Iliadis, Lazaros A and Sarigiannidis, Panagiotis and Karagiannidis, George and Goudos, Sotirios K},
 doi = {10.1109/MOCAST57943.2023.10176893},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In the last few years, novel meta-learning techniques have established a new field of research. Great emphasis is given to few-shot learning approaches, where the model is trained by using only a few training examples. In this work, a review of several model-agnostic meta-learning methodologies (MAML) is presented. Firstly, we identify and discuss the typical characteristics of the first proposed MAML algorithm. Next, we classify the model-agnostic approaches into three main categories: Regular gradient descent MAML, Hessian-free MAML, and Bayesian MALM, by presenting their advantages and limitations. Finally, we conclude this work with further discussion and highlight the future research directions.

@inproceedings{
 title = {Evaluating the Effect of Volatile Federated Timeseries on Modern DNNs: Attention over Long/Short Memory},
 type = {inproceedings},
 year = {2023},
 keywords = {Training;Data privacy;Federated learning;Predictiv},
 pages = {1-6},
 id = {e0d313d1-82be-3c1f-828f-0cbb25f80635},
 created = {2023-07-18T07:56:57.495Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.495Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176585},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In regards to the field of trend forecasting in time series, many popular Deep Learning (DL) methods such as Long Short Term Memory (LSTM) models have been the gold standard for a long time. However, depending on the domain and application, it has been shown that a new approach can be implemented and possibly be more beneficial, the Transformer deep neural networks. Moreover, one can incorporate Federated Learning (FL) in order to further enhance the prospective utility of the models, enabling multiple data providers to jointly train on a common model, while maintaining the privacy of their data. In this paper, we use an experimental Federated Learning System that employs both Transformer and LSTM models on a variety of datasets. The sytem receives data from multiple clients and uses federation to create an optimized global model. The potential of Federated Learning in real-time forecasting is explored by comparing the federated approach with conventional local training. Furthermore, a comparison is made between the performance of the Transformer and its equivalent LSTM in order to determine which one is more effective in each given domain, which shows that the Transformer model can produce better results, especially when optimised by the FL process.},
 bibtype = {inproceedings},
 author = {Siniosoglou, Ilias and Xouveroudis, Konstantinos and Argyriou, Vasileios and Lagkas, Thomas and Goudos, Sotirios K and Psannis, Konstantinos E and Sarigiannidis, Panagiotis},
 doi = {10.1109/MOCAST57943.2023.10176585},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In regards to the field of trend forecasting in time series, many popular Deep Learning (DL) methods such as Long Short Term Memory (LSTM) models have been the gold standard for a long time. However, depending on the domain and application, it has been shown that a new approach can be implemented and possibly be more beneficial, the Transformer deep neural networks. Moreover, one can incorporate Federated Learning (FL) in order to further enhance the prospective utility of the models, enabling multiple data providers to jointly train on a common model, while maintaining the privacy of their data. In this paper, we use an experimental Federated Learning System that employs both Transformer and LSTM models on a variety of datasets. The sytem receives data from multiple clients and uses federation to create an optimized global model. The potential of Federated Learning in real-time forecasting is explored by comparing the federated approach with conventional local training. Furthermore, a comparison is made between the performance of the Transformer and its equivalent LSTM in order to determine which one is more effective in each given domain, which shows that the Transformer model can produce better results, especially when optimised by the FL process.

@inproceedings{
 title = {A Real-time Chaos-based Audio Encryption Scheme},
 type = {inproceedings},
 year = {2023},
 keywords = {Circuits and systems;Chaotic communication;Paralle},
 pages = {1-4},
 id = {e80b3c70-e22d-370a-91a1-6f31a27abc7b},
 created = {2023-07-18T07:56:57.513Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.513Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176599},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work introduces a chaos based audio encryption scheme, along with its implementation, which works in real time. Initially, a novel chaotic map is introduced, and using this map a Pseudo-Random Bit generator is defined. The encryption scheme is defined based on the above and utilizes parallel computing to encrypt recorded audio "on the fly", rather than collecting the complete recording and encrypting afterwards, making the method suitable for real-time encryption. The security of the proposed method is evaluated via statistical tests. Finally, an Open-Source implementation of the proposed method using Python is given.},
 bibtype = {inproceedings},
 author = {Kafetzis, Ioannis and Volos, Christos and Nistazakis, Hector E and Goudos, Sotirios and Bardis, Nikolaos G},
 doi = {10.1109/MOCAST57943.2023.10176599},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

This work introduces a chaos based audio encryption scheme, along with its implementation, which works in real time. Initially, a novel chaotic map is introduced, and using this map a Pseudo-Random Bit generator is defined. The encryption scheme is defined based on the above and utilizes parallel computing to encrypt recorded audio "on the fly", rather than collecting the complete recording and encrypting afterwards, making the method suitable for real-time encryption. The security of the proposed method is evaluated via statistical tests. Finally, an Open-Source implementation of the proposed method using Python is given.

@inproceedings{
 title = {The Challenges of Music Deep Learning for Traditional Music},
 type = {inproceedings},
 year = {2023},
 keywords = {Deep learning;Training;Databases;Instruments;Music},
 pages = {1-5},
 id = {f2aa4353-85e1-3347-84e2-9d71b11a7449},
 created = {2023-07-18T07:56:57.545Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.545Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176775},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Numerous applications for music listeners, educators, DJs, and musicians have been created over the past decade as the field of Music Deep Learning has expanded. Evidently, the majority of works rely on training their architectures using well-established databases, which consist primarily of Western popular music genres. This creates a deficiency in applications focusing on traditional and regional music, which are vital to preserving culture. As an increasing number of research groups begin to develop works centered on traditional music, several practical challenges for applying deep learning arise. This work discusses these issues and the future of deep learning in the study of traditional music.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Iliadis, Lazaros Alexios and Sotiroudis, Sotirios P and Kokkinidis, Kostas and Sarigiannidis, Panagiotis and Nikolaidis, Spiridon and Volos, Christos and Boursianis, Achilles D and Babas, Dimitrios and Papadopoulou, Maria S and Goudos, Sotirios K},
 doi = {10.1109/MOCAST57943.2023.10176775},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Numerous applications for music listeners, educators, DJs, and musicians have been created over the past decade as the field of Music Deep Learning has expanded. Evidently, the majority of works rely on training their architectures using well-established databases, which consist primarily of Western popular music genres. This creates a deficiency in applications focusing on traditional and regional music, which are vital to preserving culture. As an increasing number of research groups begin to develop works centered on traditional music, several practical challenges for applying deep learning arise. This work discusses these issues and the future of deep learning in the study of traditional music.

@inproceedings{
 title = {Ensemble Learning Technique for Artificial Intelligence Assisted IVF Applications},
 type = {inproceedings},
 year = {2023},
 keywords = {Deep learning;Circuits and systems;Feature extract},
 pages = {1-4},
 id = {ff531e0d-762d-31fb-bfd2-d2a866ee9b9c},
 created = {2023-07-18T07:56:57.605Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-07-18T07:56:57.605Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10176690},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In-vitro fertilization (IVF) is considered one of the most effective assisted reproductive approaches. However, it involves a series of complex and expensive procedures, that result in approximately 30% success rate. New technological concepts, like deep learning (DL), are required to increase the success rate while simplifying the procedure. DL techniques can automatically extract valuable features from the available data, can be flexible, and can work efficiently on multiple problems. Motivated by these characteristics, in this work, a DL ensemble model is trained on a private dataset to classify blastocysts’ images. Further analysis is conducted to provide insights for future research.},
 bibtype = {inproceedings},
 author = {Vergos, George and Iliadis, Lazaros Alexios and Kritopoulou, Paraskevi and Papatheodorou, Achilleas and Boursianis, Achilles D and Kokkinidis, Konstantinos-Iraklis D and Papadopoulou, Maria S and Goudos, Sotirios K},
 doi = {10.1109/MOCAST57943.2023.10176690},
 booktitle = {2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In-vitro fertilization (IVF) is considered one of the most effective assisted reproductive approaches. However, it involves a series of complex and expensive procedures, that result in approximately 30% success rate. New technological concepts, like deep learning (DL), are required to increase the success rate while simplifying the procedure. DL techniques can automatically extract valuable features from the available data, can be flexible, and can work efficiently on multiple problems. Motivated by these characteristics, in this work, a DL ensemble model is trained on a private dataset to classify blastocysts’ images. Further analysis is conducted to provide insights for future research.

@article{
 title = {Analysis of Public Space in Historic Districts Based on Community Governance and Neural Networks},
 type = {article},
 year = {2023},
 pages = {81021-81032},
 volume = {11},
 id = {d088ef88-bfa3-3c62-9f81-a453f69cddb2},
 created = {2023-07-20T21:29:17.978Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-08-08T13:52:58.396Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10188893},
 source_type = {article},
 private_publication = {false},
 abstract = {Based on the perspective of community governance, this paper explores the research path of public space renewal in historic city districts. Taking the historical public space of Lhasa city as an example, this paper analyzes the causes of the characteristics of public space, analyzes the logical relationship between public space and urban renewal and community governance, applies the neural network evaluation model. Firstly employed cell rasterization, indicator classification, and population density estimation to calculate the score for each indicator. And then the principal component extracted by principal component analysis is used as the input node of the neural networkit determines the weight of each indicator by adopting the entropy method, based on which it built a multi-dimensional indicator system to evaluate public space satisfaction of historic District of Lhasa and finally, optimizes the pattern of historical public space of Lhasa city by improving the spatial structure. The aim is to create intelligent living blocks and optimize the life mode of historical blocks. Regarding significance, first, from the human-oriented perspective, the exploration of public space renewal in historic districts is in essence a process in which people develop continuously and their needs are continuously satisfied. This approach can meet the multilevel needs of residents at different stages. Second, from a social perspective, the innovative pattern of community governance can help achieve self-satisfaction within the district, radiate to the surrounding industries, and relieve the pressure of social employment. Third, from the perspective of urban renewal implementation, research on the public space renewal of historic districts can help promote the balance of the social-ecological environment, improve regional governance and promote the high-quality development of cities. The future outlook is presented.},
 bibtype = {article},
 author = {Ding, Fan and Ren, Yunying and Goudos, Sotirios and Zhao, Ya},
 doi = {10.1109/ACCESS.2023.3297507},
 journal = {IEEE Access}
}

Based on the perspective of community governance, this paper explores the research path of public space renewal in historic city districts. Taking the historical public space of Lhasa city as an example, this paper analyzes the causes of the characteristics of public space, analyzes the logical relationship between public space and urban renewal and community governance, applies the neural network evaluation model. Firstly employed cell rasterization, indicator classification, and population density estimation to calculate the score for each indicator. And then the principal component extracted by principal component analysis is used as the input node of the neural networkit determines the weight of each indicator by adopting the entropy method, based on which it built a multi-dimensional indicator system to evaluate public space satisfaction of historic District of Lhasa and finally, optimizes the pattern of historical public space of Lhasa city by improving the spatial structure. The aim is to create intelligent living blocks and optimize the life mode of historical blocks. Regarding significance, first, from the human-oriented perspective, the exploration of public space renewal in historic districts is in essence a process in which people develop continuously and their needs are continuously satisfied. This approach can meet the multilevel needs of residents at different stages. Second, from a social perspective, the innovative pattern of community governance can help achieve self-satisfaction within the district, radiate to the surrounding industries, and relieve the pressure of social employment. Third, from the perspective of urban renewal implementation, research on the public space renewal of historic districts can help promote the balance of the social-ecological environment, improve regional governance and promote the high-quality development of cities. The future outlook is presented.

@article{
 title = {Low Complexity Deep Learning Framework for Greek Orthodox Church Hymns Classification},
 type = {article},
 year = {2023},
 volume = {13},
 websites = {https://www.mdpi.com/2076-3417/13/15/8638},
 id = {b75e0835-0dcb-3462-9f3b-87fc317cbde7},
 created = {2023-07-27T09:02:11.118Z},
 file_attached = {false},
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 last_modified = {2023-07-27T09:02:11.118Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {app13158638},
 source_type = {article},
 private_publication = {false},
 abstract = {The Byzantine religious tradition includes Greek Orthodox Church hymns, which significantly differ from other cultures’ religious music. Since the deep learning revolution, audio and music signal processing are often approached as computer vision problems. This work trains from scratch three different novel convolutional neural networks on a hymns dataset to perform hymns classification for mobile applications. The audio data are first transformed into Mel-spectrograms and then fed as input to the model. To study in more detail our models’ performance, two state-of-the-art (SOTA) deep learning models were trained on the same dataset. Our approach outperforms the SOTA models both in terms of accuracy and their characteristics. Additional statistical analysis was conducted to validate the results obtained.},
 bibtype = {article},
 author = {Iliadis, Lazaros Alexios and Sotiroudis, Sotirios P and Tsakatanis, Nikolaos and Boursianis, Achilles D and Kokkinidis, Konstantinos-Iraklis D and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.3390/app13158638},
 journal = {Applied Sciences},
 number = {15}
}

The Byzantine religious tradition includes Greek Orthodox Church hymns, which significantly differ from other cultures’ religious music. Since the deep learning revolution, audio and music signal processing are often approached as computer vision problems. This work trains from scratch three different novel convolutional neural networks on a hymns dataset to perform hymns classification for mobile applications. The audio data are first transformed into Mel-spectrograms and then fed as input to the model. To study in more detail our models’ performance, two state-of-the-art (SOTA) deep learning models were trained on the same dataset. Our approach outperforms the SOTA models both in terms of accuracy and their characteristics. Additional statistical analysis was conducted to validate the results obtained.

@inproceedings{
 title = {Explainable AI-Based Intrusion Detection in the Internet of Things},
 type = {inproceedings},
 year = {2023},
 keywords = {Artificial Intelligence,Cybersecurity,Explainable AI,Internet of Things,Intrusion Detection},
 websites = {https://doi.org/10.1145/3600160.3605162},
 publisher = {Association for Computing Machinery},
 city = {New York, NY, USA},
 series = {ARES '23},
 id = {4bf70973-3b48-3686-8ff2-21c10988dc01},
 created = {2023-08-29T19:40:48.944Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-08-29T19:40:48.944Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1145/3600160.3605162},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The revolution of Artificial Intelligence (AI) has brought about a significant evolution in the landscape of cyberattacks. In particular, with the increasing power and capabilities of AI, cyberattackers can automate tasks, analyze vast amounts of data, and identify vulnerabilities with greater precision. On the other hand, despite the multiple benefits of the Internet of Things (IoT), it raises severe security issues. Therefore, it is evident that the presence of efficient intrusion detection mechanisms is critical. Although Machine Learning (ML) and Deep Learning (DL)-based IDS have already demonstrated their detection efficiency, they still suffer from false alarms and explainability issues that do not allow security administrators to trust them completely compared to conventional signature/specification-based IDS. In light of the aforementioned remarks, in this paper, we introduce an AI-powered IDS with explainability functions for the IoT. The proposed IDS relies on ML and DL methods, while the SHapley Additive exPlanations (SHAP) method is used to explain decision-making. The evaluation results demonstrate the efficiency of the proposed IDS in terms of detection performance and explainable AI (XAI).},
 bibtype = {inproceedings},
 author = {Siganos, Marios and Radoglou-Grammatikis, Panagiotis and Kotsiuba, Igor and Markakis, Evangelos and Moscholios, Ioannis and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1145/3600160.3605162},
 booktitle = {Proceedings of the 18th International Conference on Availability, Reliability and Security}
}

The revolution of Artificial Intelligence (AI) has brought about a significant evolution in the landscape of cyberattacks. In particular, with the increasing power and capabilities of AI, cyberattackers can automate tasks, analyze vast amounts of data, and identify vulnerabilities with greater precision. On the other hand, despite the multiple benefits of the Internet of Things (IoT), it raises severe security issues. Therefore, it is evident that the presence of efficient intrusion detection mechanisms is critical. Although Machine Learning (ML) and Deep Learning (DL)-based IDS have already demonstrated their detection efficiency, they still suffer from false alarms and explainability issues that do not allow security administrators to trust them completely compared to conventional signature/specification-based IDS. In light of the aforementioned remarks, in this paper, we introduce an AI-powered IDS with explainability functions for the IoT. The proposed IDS relies on ML and DL methods, while the SHapley Additive exPlanations (SHAP) method is used to explain decision-making. The evaluation results demonstrate the efficiency of the proposed IDS in terms of detection performance and explainable AI (XAI).

@inproceedings{
 title = {Breaching the Defense: Investigating FGSM and CTGAN Adversarial Attacks on IEC 60870-5-104 AI-Enabled Intrusion Detection Systems},
 type = {inproceedings},
 year = {2023},
 keywords = {Adversarial Attacks,Artificial Intelligence,Cybersecurity,Generative Adversarial Networks,Intrusion Detection},
 websites = {https://doi.org/10.1145/3600160.3605163},
 publisher = {Association for Computing Machinery},
 city = {New York, NY, USA},
 series = {ARES '23},
 id = {64927819-82e8-379b-ad84-ce5403b64172},
 created = {2023-08-29T19:40:48.948Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-08-29T19:40:48.948Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1145/3600160.3605163},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the digital age of the hyper-connected Critical Infrastructures (CIs), the role of the smart electrical grid is crucial, providing several benefits, such as improved grid resilience, efficient energy distribution and smart load and response management. However, despite the several advantages, the rapid evolution of the heterogeneous technologies involved in the smart electrical grid increases the attack surface. In this paper, we focus first our attention on how Artificial Intelligence (AI) can be used to protect the smart electrical grid in terms of detecting efficiently potential cyberattacks and anomalies. Secondly, we investigate how AI can be used to trick AI-enabled detection services, thus resulting in false alarms. In particular, we emphasise on cyberattacks against IEC 60870-5-104, an industrial communication protocol which is widely used in the energy domain. Therefore, a relevant AI-powered Intrusion Detection System (IDS) is provided, utilising strong Machine Learning (ML)/Deep Learning (DL) methods, such as Decision Tree, Random Forest, XGBOOST and deep MultiLayer Perceptron (MLP). On the other hand, we investigate how adversarial attacks can affect the detection performance of the previous IDS. For this purpose, the Fast Gradient Signed Method (FGSM) is examined, and a Conditional Tabular Generative Adversarial Network (CTGAN) adversarial attack generator is implemented. The evaluation results demonstrate the efficiency of the proposed IDS and the aforementioned adversarial attacks.},
 bibtype = {inproceedings},
 author = {Asimopoulos, Dimitrios Christos and Radoglou-Grammatikis, Panagiotis and Makris, Ioannis and Mladenov, Valeri and Psannis, Konstantinos E and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1145/3600160.3605163},
 booktitle = {Proceedings of the 18th International Conference on Availability, Reliability and Security}
}

In the digital age of the hyper-connected Critical Infrastructures (CIs), the role of the smart electrical grid is crucial, providing several benefits, such as improved grid resilience, efficient energy distribution and smart load and response management. However, despite the several advantages, the rapid evolution of the heterogeneous technologies involved in the smart electrical grid increases the attack surface. In this paper, we focus first our attention on how Artificial Intelligence (AI) can be used to protect the smart electrical grid in terms of detecting efficiently potential cyberattacks and anomalies. Secondly, we investigate how AI can be used to trick AI-enabled detection services, thus resulting in false alarms. In particular, we emphasise on cyberattacks against IEC 60870-5-104, an industrial communication protocol which is widely used in the energy domain. Therefore, a relevant AI-powered Intrusion Detection System (IDS) is provided, utilising strong Machine Learning (ML)/Deep Learning (DL) methods, such as Decision Tree, Random Forest, XGBOOST and deep MultiLayer Perceptron (MLP). On the other hand, we investigate how adversarial attacks can affect the detection performance of the previous IDS. For this purpose, the Fast Gradient Signed Method (FGSM) is examined, and a Conditional Tabular Generative Adversarial Network (CTGAN) adversarial attack generator is implemented. The evaluation results demonstrate the efficiency of the proposed IDS and the aforementioned adversarial attacks.

@inbook{
 type = {inbook},
 year = {2023},
 pages = {81-96},
 websites = {https://doi.org/10.1007/978-981-99-1059-5_3},
 publisher = {Springer Nature Singapore},
 city = {Singapore},
 id = {7bc3f703-b1c9-3a13-a7b7-770fb028ae4a},
 created = {2023-09-11T17:34:25.794Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-09-11T17:34:25.794Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Cai2023},
 source_type = {inbook},
 private_publication = {false},
 abstract = {In the future of sharing economy, billions of underutilized IoT devices will be deployed to enable a powerful and large-scale sharing market that produces economic, environmental, and social benefits. Given the fact that communications in numerous IoT devices through wireless links are unreliable, blockchain technology, as a promising solution, has emerged to achieve reliable and secure sharing services in a decentralized manner. However, applying blockchain in large-scale wireless networks confronts scalability challenges. This motivates us to propose a real-time, trusted data interactive, and fine-grained transaction supportable sharing framework, the core of which is a novel two-layer scaling blockchain design. In the on-chain layer, sharing-oriented sharding is employed to enable secure and efficient processing of macro-transactions on the chain. In the off-chain layer, cross-zone off-chain channels are set up to provide real-time sharing transactions with high-frequency micro-trading scenarios. Finally, a proof-of-concept case study about electric vehicle sharing data is implemented with experimental results to demonstrate the feasibility of our framework.},
 bibtype = {inbook},
 author = {Cai, Ting and Chen, Wuhui and Psannis, Kostas E and Goudos, Sotirios K and Yu, Yang and Zheng, Zibin and Wan, Shaohua},
 editor = {Chen, Wuhui and Zheng, Zibin and Huang, Huawei},
 doi = {10.1007/978-981-99-1059-5_3},
 chapter = {On-Chain and Off-Chain Scalability Techniques},
 title = {Blockchain Scalability}
}

In the future of sharing economy, billions of underutilized IoT devices will be deployed to enable a powerful and large-scale sharing market that produces economic, environmental, and social benefits. Given the fact that communications in numerous IoT devices through wireless links are unreliable, blockchain technology, as a promising solution, has emerged to achieve reliable and secure sharing services in a decentralized manner. However, applying blockchain in large-scale wireless networks confronts scalability challenges. This motivates us to propose a real-time, trusted data interactive, and fine-grained transaction supportable sharing framework, the core of which is a novel two-layer scaling blockchain design. In the on-chain layer, sharing-oriented sharding is employed to enable secure and efficient processing of macro-transactions on the chain. In the off-chain layer, cross-zone off-chain channels are set up to provide real-time sharing transactions with high-frequency micro-trading scenarios. Finally, a proof-of-concept case study about electric vehicle sharing data is implemented with experimental results to demonstrate the feasibility of our framework.

@article{
 title = {Generating full-stack 5G security datasets: IP-layer and core network persistent PDU session attacks},
 type = {article},
 year = {2023},
 keywords = {5G datasets,5G testbed,Cybersecurity events,PFCP,Radio access networks},
 pages = {154913},
 volume = {171},
 websites = {https://www.sciencedirect.com/science/article/pii/S1434841123003874},
 id = {f4286754-74b0-34e2-8db5-3d4fdecaf875},
 created = {2023-09-21T15:34:32.157Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-09-28T15:50:14.052Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {AMPONIS2023154913},
 source_type = {article},
 private_publication = {false},
 abstract = {With the increasing number of users accessing the Internet over 5G systems, security concerns have become a major challenge that needs to be addressed. This paper proposes a solution to this challenge by proposing a system to train defenders to handle cyber attacks and develop intrusion detection systems that can timely notify of security events, also within the 5G core itself. This paper builds on our previous contributions on a containerized 5G testbed and proposes a novel set of full-stack attacks targeting networked hosts and 5G Network Functions (NFs) alike. Importantly, we identify the potential to generate persistent Packet Forwarding and Control Protocol (PFCP) Denial of Service (DoS) attacks to deprive end users of connectivity to the data network, even in the event of a handover to another gNodeB. This framework is envisaged to facilitate the generation of highly diverse and realistic datasets, containing malicious GPRS Tunneling Protocol (GTP) and PFCP traffic captured over 5G interfaces, thereby enhancing the security of next-generation networks.},
 bibtype = {article},
 author = {Amponis, George and Radoglou-Grammatikis, Panagiotis and Lagkas, Thomas and Ouzounidis, Savas and Zevgara, Maria and Moscholios, Ioannis and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {https://doi.org/10.1016/j.aeue.2023.154913},
 journal = {AEU - International Journal of Electronics and Communications}
}

With the increasing number of users accessing the Internet over 5G systems, security concerns have become a major challenge that needs to be addressed. This paper proposes a solution to this challenge by proposing a system to train defenders to handle cyber attacks and develop intrusion detection systems that can timely notify of security events, also within the 5G core itself. This paper builds on our previous contributions on a containerized 5G testbed and proposes a novel set of full-stack attacks targeting networked hosts and 5G Network Functions (NFs) alike. Importantly, we identify the potential to generate persistent Packet Forwarding and Control Protocol (PFCP) Denial of Service (DoS) attacks to deprive end users of connectivity to the data network, even in the event of a handover to another gNodeB. This framework is envisaged to facilitate the generation of highly diverse and realistic datasets, containing malicious GPRS Tunneling Protocol (GTP) and PFCP traffic captured over 5G interfaces, thereby enhancing the security of next-generation networks.

@article{
 title = {Investigating the Relationship of User Acceptance to the Characteristics and Performance of an Educational Software in Byzantine Music},
 type = {article},
 year = {2023},
 volume = {14},
 websites = {https://www.mdpi.com/2078-2489/14/10/568},
 id = {e10c0744-0760-3446-9b9a-01e07e282786},
 created = {2023-10-16T04:17:58.720Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-10-16T04:17:58.720Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {info14100568},
 source_type = {article},
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 abstract = {The purpose of this study is to examine the impact of educational software characteristics on software performance through the mediating role of user acceptance. Our approach allows for a deeper understanding of the factors that contribute to the effectiveness of educational software by bridging the fields of educational technology, psychology, and human–computer interaction, offering a holistic perspective on software adoption and performance. This study is based on a sample collected from public and private education institutes in Northern Greece and on data obtained from 236 users. The statistical method employed is structural equation models (SEMs), via SPSS—AMOS estimation. The findings of this study suggest that user acceptance and performance appraisal are exceptionally interrelated in regard to educational applications. The study argues that user acceptance is positively related to the performance of educational software and constitutes the nested epicenter mediating construct in the educational software characteristics. Additional findings, such as computer-familiar users and users from the field of choral music, are positively related to the performance of the educational software. Our conclusions help in understanding the psychological and behavioral aspects of technology adoption in the educational setting. Findings are discussed in terms of their practical usefulness in education and further research.},
 bibtype = {article},
 author = {Kokkinidis, Konstantinos-Hercules and Patronas, Georgios and Goudos, Sotirios K and Maikantis, Theodoros and Nikolaidis, Nikolaos},
 doi = {10.3390/info14100568},
 journal = {Information},
 number = {10}
}

The purpose of this study is to examine the impact of educational software characteristics on software performance through the mediating role of user acceptance. Our approach allows for a deeper understanding of the factors that contribute to the effectiveness of educational software by bridging the fields of educational technology, psychology, and human–computer interaction, offering a holistic perspective on software adoption and performance. This study is based on a sample collected from public and private education institutes in Northern Greece and on data obtained from 236 users. The statistical method employed is structural equation models (SEMs), via SPSS—AMOS estimation. The findings of this study suggest that user acceptance and performance appraisal are exceptionally interrelated in regard to educational applications. The study argues that user acceptance is positively related to the performance of educational software and constitutes the nested epicenter mediating construct in the educational software characteristics. Additional findings, such as computer-familiar users and users from the field of choral music, are positively related to the performance of the educational software. Our conclusions help in understanding the psychological and behavioral aspects of technology adoption in the educational setting. Findings are discussed in terms of their practical usefulness in education and further research.

@article{
 title = {Artificial Intelligence in Visible Light Positioning for Indoor IoT: A Methodological Review},
 type = {article},
 year = {2023},
 pages = {2838-2869},
 volume = {4},
 id = {c2a0e090-1e7f-3388-98ef-1d432454c8a2},
 created = {2023-10-25T18:24:07.988Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-11-12T19:59:45.960Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10293149},
 source_type = {article},
 private_publication = {false},
 abstract = {Indoor communication and positioning are significant fields of applications for indoor Internet of Things (IoT) given the rapid growth of IoT in smart cities, smart grids, and smart industries. Visible light positioning (VLP) has become more and more attractive for researchers to provide indoor location-aware IoT services. Additionally, artificial intelligence (AI) has attracted considerable research effort to address the challenges in visible-light communication (VLC) systems. This is an emerging technology in next-generation wireless networks. However, despite the rapid progress, the use of AI in localization, navigation, and position estimation is still underexplored in VLC systems, and various research challenges are still open. This methodological review summarizes the research efforts regarding the use of AI in the field of VLP, to improve the position estimation accuracy in both two-dimensional (2D) and three-dimensional (3D) indoor IoT applications. This treatise also presents open issues and potential future directions for motivating further research in the field. Various databases were utilized in this paper: Scopus, Google Scholar, and IEEE Xplore; obtained 88 papers from 2017 to early 2023. Most (68%) of the AI articles in VLP systems are machine learning (ML) methods applied for localization and position estimation in VLC systems, while the other 32% of the research articles focussed on evolutionary algorithms. ML and evolutionary models may present limitations in terms of complexity and time-consuming nature but offer highly accurate, robust, reliable, and cost-effective results in terms of position estimation over conventional approaches.},
 bibtype = {article},
 author = {Rekkas, Vasileios P and Iliadis, Lazaros A and Sotiroudis, Sotirios P and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Plets, David and Joseph, Wout and Wan, Shaohua and Christodoulou, Christos G and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/OJCOMS.2023.3327211},
 journal = {IEEE Open Journal of the Communications Society}
}

Indoor communication and positioning are significant fields of applications for indoor Internet of Things (IoT) given the rapid growth of IoT in smart cities, smart grids, and smart industries. Visible light positioning (VLP) has become more and more attractive for researchers to provide indoor location-aware IoT services. Additionally, artificial intelligence (AI) has attracted considerable research effort to address the challenges in visible-light communication (VLC) systems. This is an emerging technology in next-generation wireless networks. However, despite the rapid progress, the use of AI in localization, navigation, and position estimation is still underexplored in VLC systems, and various research challenges are still open. This methodological review summarizes the research efforts regarding the use of AI in the field of VLP, to improve the position estimation accuracy in both two-dimensional (2D) and three-dimensional (3D) indoor IoT applications. This treatise also presents open issues and potential future directions for motivating further research in the field. Various databases were utilized in this paper: Scopus, Google Scholar, and IEEE Xplore; obtained 88 papers from 2017 to early 2023. Most (68%) of the AI articles in VLP systems are machine learning (ML) methods applied for localization and position estimation in VLC systems, while the other 32% of the research articles focussed on evolutionary algorithms. ML and evolutionary models may present limitations in terms of complexity and time-consuming nature but offer highly accurate, robust, reliable, and cost-effective results in terms of position estimation over conventional approaches.

@article{
 title = {Chaotic Maps with Tunable Mean Value—Application to a UAV Surveillance Mission},
 type = {article},
 year = {2023},
 volume = {15},
 websites = {https://www.mdpi.com/2073-8994/15/12/2138},
 id = {3517c130-4648-32ac-ad01-3a1744e9b98e},
 created = {2023-12-01T15:57:57.380Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-01T15:57:57.380Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {sym15122138},
 source_type = {article},
 private_publication = {false},
 abstract = {Chaos-related applications are abundant in the literature, and span the fields of secure communications, encryption, optimization, and surveillance. Such applications take advantage of the unpredictability of chaotic systems as an alternative to using true random processes. The chaotic systems used, though, must showcase the statistical characteristics suitable for each application. This may often be hard to achieve, as the design of maps with tunable statistical properties is not a trivial task. Motivated by this, the present study explores the task of constructing maps, where the statistical measures like the mean value can be appropriately controlled by tuning the map’s parameters. For this, a family of piecewise maps is considered, with three control parameters that affect the endpoint interpolations. Numerous examples are given, and the maps are studied through a collection of numerical simulations. The maps can indeed achieve a range of values for their statistical mean. Such maps may find extensive use in relevant chaos-based applications. To showcase this, the problem of chaotic path surveillance is considered as a potential application of the designed maps. Here, an autonomous agent follows a predefined trajectory but maneuvers around it in order to imbue unpredictability to potential hostile observers. The trajectory inherits the randomness of the chaotic map used as a seed, which results in chaotic motion patterns. Simulations are performed for the designed strategy.},
 bibtype = {article},
 author = {Moysis, Lazaros and Lawnik, Marcin and Volos, Christos and Baptista, Murilo S and Goudos, Sotirios K},
 doi = {10.3390/sym15122138},
 journal = {Symmetry},
 number = {12}
}

Chaos-related applications are abundant in the literature, and span the fields of secure communications, encryption, optimization, and surveillance. Such applications take advantage of the unpredictability of chaotic systems as an alternative to using true random processes. The chaotic systems used, though, must showcase the statistical characteristics suitable for each application. This may often be hard to achieve, as the design of maps with tunable statistical properties is not a trivial task. Motivated by this, the present study explores the task of constructing maps, where the statistical measures like the mean value can be appropriately controlled by tuning the map’s parameters. For this, a family of piecewise maps is considered, with three control parameters that affect the endpoint interpolations. Numerous examples are given, and the maps are studied through a collection of numerical simulations. The maps can indeed achieve a range of values for their statistical mean. Such maps may find extensive use in relevant chaos-based applications. To showcase this, the problem of chaotic path surveillance is considered as a potential application of the designed maps. Here, an autonomous agent follows a predefined trajectory but maneuvers around it in order to imbue unpredictability to potential hostile observers. The trajectory inherits the randomness of the chaotic map used as a seed, which results in chaotic motion patterns. Simulations are performed for the designed strategy.

@inproceedings{
 title = {Comparative Evaluation between Accelerated RISC- V and ARM AI Inference Machines},
 type = {inproceedings},
 year = {2023},
 pages = {108-113},
 id = {b8558105-d9de-3640-9fef-4e34f4bf716a},
 created = {2023-12-26T08:10:36.726Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-26T08:10:36.726Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10365853},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Embedded AI development has been rapidly im-proving for the past few years and has had a great impact on edge AI networks. However, as neural networks become deeper and deeper it becomes more difficult to execute complicated tasks without sacrificing a good amount of power and performance. In this paper, we make a comparative evaluation between two AI acceleration devices. The first one features a RISC- V 64-bit processor while the other one is ARM powered. These devices are combined with AI co-processors, or ASICs, with computer vision capabilities. Our benchmark consists of a simple classification task split into multiple versions. The results showed that the RISC- V inference machine had 4 times lower consumption while the ARM machine was up to 15 times faster in our largest network. We discuss the results in great detail while keeping our focus on all aspects equally. Finally, we make recommendations based on their usage and application.},
 bibtype = {inproceedings},
 author = {Christofas, Vasileios and Amanatidis, Petros and Karampatzakis, Dimitris and Lagkas, Thomas and Goudos, Sotirios K and Psannis, Konstantinos E and Sarigiannidis, Panagiotis},
 doi = {10.1109/WSCE59557.2023.10365853},
 booktitle = {2023 6th World Symposium on Communication Engineering (WSCE)}
}

Embedded AI development has been rapidly im-proving for the past few years and has had a great impact on edge AI networks. However, as neural networks become deeper and deeper it becomes more difficult to execute complicated tasks without sacrificing a good amount of power and performance. In this paper, we make a comparative evaluation between two AI acceleration devices. The first one features a RISC- V 64-bit processor while the other one is ARM powered. These devices are combined with AI co-processors, or ASICs, with computer vision capabilities. Our benchmark consists of a simple classification task split into multiple versions. The results showed that the RISC- V inference machine had 4 times lower consumption while the ARM machine was up to 15 times faster in our largest network. We discuss the results in great detail while keeping our focus on all aspects equally. Finally, we make recommendations based on their usage and application.

@inproceedings{
 title = {Image Filtering Techniques for Beam Prediction in a Real-world 6G UAV Scenario},
 type = {inproceedings},
 year = {2023},
 pages = {103-107},
 id = {f268d8f0-5dbc-369f-8f2b-578f9352bf40},
 created = {2023-12-26T08:10:36.734Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-26T08:10:36.734Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10365979},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Millimeter-wave (mm-wave) and terahertz (THz) communication systems can satisfy the high data rate requirements in 5G, 6G, and beyond networks, but still rely on the use of extensive antenna arrays to guarantee sufficient received signal strength. Many antennas incur high beam training overhead; thus, the narrow beams require adjustment to support highly mobile applications. Deep learning (DL) vision-aided solutions can potentially forecast the optimal beams, leveraging raw RGB images captured at the base station. Image filtering techniques have been widely used in computer vision (CV) to modify and enhance the quality of an image, based on specific rules. This work applies different filters to RGB images for accurate mm-wave/THz beam prediction and feature extraction based on pre-trained convolutional neural networks (CNNs). The assessment of the developed framework is conducted on an actual dataset captured by an unmanned aerial vehicle (UAV) operating in the millimeter-wave (mm-wave) frequency range. The dataset comprises RGB images taken at the base station. Ensemble filtering techniques are also studied, enhancing the beam prediction accuracy of two state-of-the-art (SOTA) DL models.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Sarigiannids, Panagiotis and Psannis, Konstantinos E and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/WSCE59557.2023.10365979},
 booktitle = {2023 6th World Symposium on Communication Engineering (WSCE)}
}

Millimeter-wave (mm-wave) and terahertz (THz) communication systems can satisfy the high data rate requirements in 5G, 6G, and beyond networks, but still rely on the use of extensive antenna arrays to guarantee sufficient received signal strength. Many antennas incur high beam training overhead; thus, the narrow beams require adjustment to support highly mobile applications. Deep learning (DL) vision-aided solutions can potentially forecast the optimal beams, leveraging raw RGB images captured at the base station. Image filtering techniques have been widely used in computer vision (CV) to modify and enhance the quality of an image, based on specific rules. This work applies different filters to RGB images for accurate mm-wave/THz beam prediction and feature extraction based on pre-trained convolutional neural networks (CNNs). The assessment of the developed framework is conducted on an actual dataset captured by an unmanned aerial vehicle (UAV) operating in the millimeter-wave (mm-wave) frequency range. The dataset comprises RGB images taken at the base station. Ensemble filtering techniques are also studied, enhancing the beam prediction accuracy of two state-of-the-art (SOTA) DL models.

@inproceedings{
 title = {Improving Communication Systems Through Federated Learning: An Optimization of Decision-Making},
 type = {inproceedings},
 year = {2023},
 pages = {45-48},
 id = {3f17c833-3036-3935-b40f-1c8860191786},
 created = {2023-12-26T08:10:36.852Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-26T08:10:36.852Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10365857},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems.},
 bibtype = {inproceedings},
 author = {Stergiou, Konstantinos D and Ishibashi, Yutaka and Goudos, Sotirios K and Lagkas, Thomas and Sarigiannidis, Panagiotis and Psannis, Konstantinos E},
 doi = {10.1109/WSCE59557.2023.10365857},
 booktitle = {2023 6th World Symposium on Communication Engineering (WSCE)}
}

This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems.

@inproceedings{
 title = {Tactile Internet Security System Architecture for Mobile Networks},
 type = {inproceedings},
 year = {2023},
 pages = {1-6},
 id = {e1dcccce-fd08-34a6-a2d2-e6cb3607edb2},
 created = {2023-12-26T08:10:36.857Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-26T08:10:36.857Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10365815},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The deficiencies of the Fifth Generation (5G) mobile networks are stimulating vendors to focus on the specifications of the next generation of wireless systems. The efficient integration of the Tactile Internet with mobile networks, like the emerging Sixth Generation (6G) wireless systems, is anticipated to achieve global ubiquitous accessibility, extremely low latency, high reliability, and elevated security for haptic communication. Based on the characteristics of the new generation of mobile networks, a novel system architecture is proposed along with a security framework for the utilization of Tactile Internet applications.},
 bibtype = {inproceedings},
 author = {Minopoulos, Georgios and Kokkonis, Georgios and Sarigiannidis, Panagiotis and Goudos, Sotirios and Ishibashi, Yutaka and Psannis, Konstantinos},
 doi = {10.1109/WSCE59557.2023.10365815},
 booktitle = {2023 6th World Symposium on Communication Engineering (WSCE)}
}

The deficiencies of the Fifth Generation (5G) mobile networks are stimulating vendors to focus on the specifications of the next generation of wireless systems. The efficient integration of the Tactile Internet with mobile networks, like the emerging Sixth Generation (6G) wireless systems, is anticipated to achieve global ubiquitous accessibility, extremely low latency, high reliability, and elevated security for haptic communication. Based on the characteristics of the new generation of mobile networks, a novel system architecture is proposed along with a security framework for the utilization of Tactile Internet applications.

@inproceedings{
 title = {Intrusion Detection System Modeling Using Machine Learning : A Comparative Study},
 type = {inproceedings},
 year = {2023},
 pages = {7-14},
 id = {81e968eb-6bd5-3e1b-9981-5e2365a96a2a},
 created = {2023-12-26T08:10:36.858Z},
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 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-12-26T08:10:36.858Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10365909},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In recent years, the adoption of internet-connected devices has experienced a remarkable surge, fundamentally transforming our everyday routines. Nevertheless, this rapid expansion has also captured the interest of cybercriminals, resulting in a notable rise in both the quantity and complexity of attacks aimed specifically at these devices. In this work, a network intrusion detection system (NIDS) is developed, related to information systems security/cyber security. In this context, various machine learning (ML) methods are utilized, namely k-nearest neighbors (knn), adaptive boosting (Adaboost), gradient tree boosting (GTB), logistic regression (LR), Decision Tree (DT), Naive Baye as well as Bagging and Voting Classifiers. The performance of the ML models is evaluated based on various metrics, exhibiting great accuracy results in classifying the abnormal behaviors in a cyber network.},
 bibtype = {inproceedings},
 author = {Akritas, Xenofon and Rekkas, Vasileios P and Sotiroudis, Sotirios P and Sarigiannids, Panagiotis and Psannis, Konstantinos E and Goudos, Sotirios K},
 doi = {10.1109/WSCE59557.2023.10365909},
 booktitle = {2023 6th World Symposium on Communication Engineering (WSCE)}
}

In recent years, the adoption of internet-connected devices has experienced a remarkable surge, fundamentally transforming our everyday routines. Nevertheless, this rapid expansion has also captured the interest of cybercriminals, resulting in a notable rise in both the quantity and complexity of attacks aimed specifically at these devices. In this work, a network intrusion detection system (NIDS) is developed, related to information systems security/cyber security. In this context, various machine learning (ML) methods are utilized, namely k-nearest neighbors (knn), adaptive boosting (Adaboost), gradient tree boosting (GTB), logistic regression (LR), Decision Tree (DT), Naive Baye as well as Bagging and Voting Classifiers. The performance of the ML models is evaluated based on various metrics, exhibiting great accuracy results in classifying the abnormal behaviors in a cyber network.

@inproceedings{
 title = {5GCIDS: An Intrusion Detection System for 5G Core with AI and Explainability Mechanisms},
 type = {inproceedings},
 year = {2023},
 keywords = {Heart;Protocols;5G mobile communication;Intrusion},
 pages = {353-358},
 id = {fdca7556-59ae-33e3-8e9d-5fe4e03947a0},
 created = {2024-03-22T21:40:36.191Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-22T21:40:36.191Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10464667},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The progression of fifth-generation (5G) networks provides multiple advantages, such as faster speed, reduced latency and increased capacity. Towards these advancements, it is clear that 5G Core (5GC) represents the heart of a 5G network, providing a variety of new network services such as Ultra-reliable low-latency communication (URLLC) and Massive machine-type communication (mMTC). However, despite the various benefits, 5GC is prone to several cyberthreats that can result in catastrophic effects. In this paper, an Intrusion Detection System (IDS) for 5GC is introduced. The proposed IDS called 5GCIDS adopts Artificial Intelligence (AI) methods in order to detect potential cyberattacks against Packet Forwarding Control Protocol (PFCP), which is utilised for the N4 interface between Session Management Function (SMF) andUser Plane Function (UPF). For the detection process, both Transmission Control Protocol (TCP)/Internet Protocol (IP) flow statistics and application-layer PFCP flow statistics are used. In the second case, we provide a bidirectional flow statistics generator called PFCPFlowMeter. Finally, the detection outcomes are explained as local and global explanations with the TreeSHAP method. The evaluation results demonstrate the efficiency of the proposed IDS.},
 bibtype = {inproceedings},
 author = {Radoglou-Grammatikis, Panagiotis and Nakas, George and Amponis, George and Giannakidou, Sofia and Lagkas, Thomas and Argyriou, Vasileios and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/GCWkshps58843.2023.10464667},
 booktitle = {2023 IEEE Globecom Workshops (GC Wkshps)}
}

The progression of fifth-generation (5G) networks provides multiple advantages, such as faster speed, reduced latency and increased capacity. Towards these advancements, it is clear that 5G Core (5GC) represents the heart of a 5G network, providing a variety of new network services such as Ultra-reliable low-latency communication (URLLC) and Massive machine-type communication (mMTC). However, despite the various benefits, 5GC is prone to several cyberthreats that can result in catastrophic effects. In this paper, an Intrusion Detection System (IDS) for 5GC is introduced. The proposed IDS called 5GCIDS adopts Artificial Intelligence (AI) methods in order to detect potential cyberattacks against Packet Forwarding Control Protocol (PFCP), which is utilised for the N4 interface between Session Management Function (SMF) andUser Plane Function (UPF). For the detection process, both Transmission Control Protocol (TCP)/Internet Protocol (IP) flow statistics and application-layer PFCP flow statistics are used. In the second case, we provide a bidirectional flow statistics generator called PFCPFlowMeter. Finally, the detection outcomes are explained as local and global explanations with the TreeSHAP method. The evaluation results demonstrate the efficiency of the proposed IDS.

@inproceedings{
 title = {5G-Fuzz: An Attack Generator for Fuzzing 5GC, using Generative Adversarial Networks},
 type = {inproceedings},
 year = {2023},
 keywords = {Privacy;Protocols;5G mobile communication;Network},
 pages = {347-352},
 id = {e9ab5898-b6f7-39c9-8edc-d24e08a83bf7},
 created = {2024-03-22T21:40:36.192Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-22T21:40:36.192Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10464928},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The evolution of fifth-generation (5G) networks represents a significant technological leap towards a seamless and advanced user experience, allowing hyperconnected use cases with faster data transfer, lower latency and better connectivity for a wide range of mobile devices. In particular, a key element of 5G is the 5G Core (5GC) which follows a service-based architecture, enabling network slicing and improved Quality of Service (QoS). However, despite the benefits of 5GC, it also creates important security and privacy concerns. First, 5GC can combine heterogeneous technologies that can increase the growing attack surface. On the other hand, 5G handles a vast amount of sensitive data that may reflect an attractive goal for potential cyberattackers. Based on the previous remarks, in this paper, we introduce 5G-Fuzz. 5G-Fuzz is a smart fuzzer which takes full advantage of historical data in order to fuzz and target the Packet Forwarding Control Protocol (PFCP) communications between the Session Management Function (SMF) and User Plane Function (UPF). For this purpose, two PFCP attacks are used. In contrast to conventional fuzzers, 5G-Fuzz adopts two Generative Adversarial Networks (GANs) in order to identify and generate the appropriate values of Session Endpoint Identifier (SEID) and sequence number (seq) utilised in the PFCP sessions, thus accelerating the PFCP attacks. Finally, 5G-Fuzz composes and replays the malicious PFCP packets against UPF.},
 bibtype = {inproceedings},
 author = {Nakas, George and Radoglou-Grammatikis, Panagiotis and Amponis, George and Lagkas, Thomas and Argyriou, Vasileios and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/GCWkshps58843.2023.10464928},
 booktitle = {2023 IEEE Globecom Workshops (GC Wkshps)}
}

The evolution of fifth-generation (5G) networks represents a significant technological leap towards a seamless and advanced user experience, allowing hyperconnected use cases with faster data transfer, lower latency and better connectivity for a wide range of mobile devices. In particular, a key element of 5G is the 5G Core (5GC) which follows a service-based architecture, enabling network slicing and improved Quality of Service (QoS). However, despite the benefits of 5GC, it also creates important security and privacy concerns. First, 5GC can combine heterogeneous technologies that can increase the growing attack surface. On the other hand, 5G handles a vast amount of sensitive data that may reflect an attractive goal for potential cyberattackers. Based on the previous remarks, in this paper, we introduce 5G-Fuzz. 5G-Fuzz is a smart fuzzer which takes full advantage of historical data in order to fuzz and target the Packet Forwarding Control Protocol (PFCP) communications between the Session Management Function (SMF) and User Plane Function (UPF). For this purpose, two PFCP attacks are used. In contrast to conventional fuzzers, 5G-Fuzz adopts two Generative Adversarial Networks (GANs) in order to identify and generate the appropriate values of Session Endpoint Identifier (SEID) and sequence number (seq) utilised in the PFCP sessions, thus accelerating the PFCP attacks. Finally, 5G-Fuzz composes and replays the malicious PFCP packets against UPF.

@inproceedings{
 title = {Personalisation of Federated Learning Models Through Knowledge Distillation on Decentralised Data},
 type = {inproceedings},
 year = {2023},
 keywords = {Temperature measurement;Training;Temperature distr},
 pages = {56-61},
 id = {5e950151-c5f9-307c-a7e3-57f248374284},
 created = {2024-03-22T21:40:36.333Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-22T21:40:36.333Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10464710},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {A prevalent issue in the field of Machine Learning (ML) remains the extensive time required to train and utilise intricate Machine and Deep Learning (DL) models, optimising them for the various applications that require them. This problem is all the more prevalent in the federated domain, where optimising a model for each different node is a difficult challenge. Towards solving this issue, a lot of techniques have surfaced, aiming at reducing training time and cost, while ensuring optimisation. One of the proposed solutions to address this challenge is Knowledge Distillation, which involves transferring knowledge from a pre-trained complex model to a simpler untrained one. This approach can facilitate the use of smaller models with reduced computational demands, as well as personalise the model with additional local knowledge, enhancing the performance of existing models. The present study delves into the fundamental principles of KD and applies the technique to a selection of ML models, investigating the efficacy of this technique in the local and federated domain. Subsequently, a comparative analysis of the results between the original and optimised, local and federated models is presented. Post-analysis indicates promising results in personalising and optimising the employed models with KD.},
 bibtype = {inproceedings},
 author = {SiniosoGlou, Ilias and Xouveroudis, Konstantinos and Argyriou, Vasileios and Lagkas, Thomas and Saoulidis, Theocharis and Fragulis, George and Goudos, Sotirios K and Sarigiannidis, Panagiotis},
 doi = {10.1109/GCWkshps58843.2023.10464710},
 booktitle = {2023 IEEE Globecom Workshops (GC Wkshps)}
}

A prevalent issue in the field of Machine Learning (ML) remains the extensive time required to train and utilise intricate Machine and Deep Learning (DL) models, optimising them for the various applications that require them. This problem is all the more prevalent in the federated domain, where optimising a model for each different node is a difficult challenge. Towards solving this issue, a lot of techniques have surfaced, aiming at reducing training time and cost, while ensuring optimisation. One of the proposed solutions to address this challenge is Knowledge Distillation, which involves transferring knowledge from a pre-trained complex model to a simpler untrained one. This approach can facilitate the use of smaller models with reduced computational demands, as well as personalise the model with additional local knowledge, enhancing the performance of existing models. The present study delves into the fundamental principles of KD and applies the technique to a selection of ML models, investigating the efficacy of this technique in the local and federated domain. Subsequently, a comparative analysis of the results between the original and optimised, local and federated models is presented. Post-analysis indicates promising results in personalising and optimising the employed models with KD.

@inproceedings{
 title = {Recognition of Greek Orthodox Hymns Using Audio Fingerprint Techniques},
 type = {inproceedings},
 year = {2023},
 keywords = {Design automation;Social networking (online);Instr},
 pages = {1-6},
 id = {d2382562-6e31-33e5-83f9-33d882669003},
 created = {2024-03-22T21:40:36.338Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-22T21:40:36.338Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10470476},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Audio fingerprinting was originally developed for music song identification, and over the years has been used for many more cases. With fingerprinting, an equivalent signature of the audio signal is saved in a simple form, so that it can be easily compared with another fingerprint. In this work, an audio fingerprinting algorithm is developed for the recognition of Greek Orthodox hymns. The main difference between music songs and Greek Orthodox hymns is the absence of music instruments, as there is only the chanter's voice. The test dataset consists of 10 hymns, and for each hymn there are 5 different performances, creating a dataset of 50 performances. Several tunable parameters of the fingerprinting technique are tested, like the parameters of the Hamming window, the frequency spectrum, the sample duration, and the sample noise, to find the differences in Greek Orthodox hymns. The recognition results for all cases are positive. The algorithm, in most cases, had a high recognition rate. even with noisy samples.},
 bibtype = {inproceedings},
 author = {Karasavvidis, Konstantinos and Kampelopoulos, Dimitris and Moysis, Lazaros and Boursianis, Achilles D and Nikolaidis, Spiridon and Sarigiannidis, Panagiotis and Goudos, Sotirios K},
 doi = {10.1109/SEEDA-CECNSM61561.2023.10470476},
 booktitle = {2023 8th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)}
}

Audio fingerprinting was originally developed for music song identification, and over the years has been used for many more cases. With fingerprinting, an equivalent signature of the audio signal is saved in a simple form, so that it can be easily compared with another fingerprint. In this work, an audio fingerprinting algorithm is developed for the recognition of Greek Orthodox hymns. The main difference between music songs and Greek Orthodox hymns is the absence of music instruments, as there is only the chanter's voice. The test dataset consists of 10 hymns, and for each hymn there are 5 different performances, creating a dataset of 50 performances. Several tunable parameters of the fingerprinting technique are tested, like the parameters of the Hamming window, the frequency spectrum, the sample duration, and the sample noise, to find the differences in Greek Orthodox hymns. The recognition results for all cases are positive. The algorithm, in most cases, had a high recognition rate. even with noisy samples.

@inproceedings{
 title = {Surveying Cyber Threat Intelligence and Collaboration: A Concise Analysis of Current Landscape and Trends},
 type = {inproceedings},
 year = {2023},
 keywords = {Cloud computing;Program processors;Weapons;Phishin},
 pages = {309-314},
 id = {67827dd5-966c-3228-afe4-402a9bbb9af0},
 created = {2024-03-26T09:54:46.449Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-03-26T09:54:46.449Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10475684},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The evolution of cyberattacks has been significantly impacted by the rise of Artificial Intelligence (AI). In particular, AI-driven attacks leverage Machine Learning (ML) and Deep Learning (DL) methods to automate tasks like identifying vulnerabilities, crafting convincing phishing emails, and evading conventional security measures. These cyberattacks can adapt in real time, making them more elusive and challenging to detect. Furthermore, AI has enabled the development of AI-powered malware that can learn and evolve, making it even more dangerous. As AI continues to evolve, both attackers and defenders are engaged in a relentless arms race, with cybersecurity professionals striving to harness AI for threat detection and response while cybercriminals seek to exploit AI’s capabilities for their malicious purposes. This ongoing battle underscores the need for proactive and adaptive cybersecurity strategies to mitigate the evolving threats posed by AI-driven cyberattacks. Based on the aforementioned remarks, it is evident that efficient and adaptable countermeasures are necessary. In this paper, we focus our attention on Cyber Threat Intelligence (CTI) mechanisms. CTI is the process of collecting, analysing, and sharing information about potential cybersecurity threats to help organisations proactively defend against cyberattacks. In particular, after providing an overview of the CTI use cases, a brief analysis of existing solutions follows, highlighting the current trends and directions for future work in this research field.},
 bibtype = {inproceedings},
 author = {Radoglou-Grammatikis, Panagiotis and Kioseoglou, Elisavet and Asimopoulos, Dimitrios and Siavvas, Miltiadis and Nanos, Ioannis and Lagkas, Thomas and Argyriou, Vasileios and Psannis, Konstantinos E and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/CloudCom59040.2023.00057},
 booktitle = {2023 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)}
}

The evolution of cyberattacks has been significantly impacted by the rise of Artificial Intelligence (AI). In particular, AI-driven attacks leverage Machine Learning (ML) and Deep Learning (DL) methods to automate tasks like identifying vulnerabilities, crafting convincing phishing emails, and evading conventional security measures. These cyberattacks can adapt in real time, making them more elusive and challenging to detect. Furthermore, AI has enabled the development of AI-powered malware that can learn and evolve, making it even more dangerous. As AI continues to evolve, both attackers and defenders are engaged in a relentless arms race, with cybersecurity professionals striving to harness AI for threat detection and response while cybercriminals seek to exploit AI’s capabilities for their malicious purposes. This ongoing battle underscores the need for proactive and adaptive cybersecurity strategies to mitigate the evolving threats posed by AI-driven cyberattacks. Based on the aforementioned remarks, it is evident that efficient and adaptable countermeasures are necessary. In this paper, we focus our attention on Cyber Threat Intelligence (CTI) mechanisms. CTI is the process of collecting, analysing, and sharing information about potential cybersecurity threats to help organisations proactively defend against cyberattacks. In particular, after providing an overview of the CTI use cases, a brief analysis of existing solutions follows, highlighting the current trends and directions for future work in this research field.

@inproceedings{
 title = {Elevating 5G Network Security: A Profound Examination of Federated Learning Aggregation Strategies for Attack Detection},
 type = {inproceedings},
 year = {2023},
 keywords = {Training;Privacy;Base stations;Federated learning;},
 pages = {1-6},
 id = {d2ad9a2b-2378-3bab-83ae-78de65b0de22},
 created = {2024-12-25T12:50:36.110Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-12-25T12:50:36.110Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10520474},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The popularity of 5G networks has resulted in significant advancement and opportunities in connectivity and reliability of communications, but, concurrently, it raised security challenges and privacy concerns due to the distributed and highly dynamic nature of these networks. In particular, while participating devices and nodes in a 5G network need to be resilient against cyber threats, most of them are not allowed to exchange their data, and, therefore, they are limited only to the corresponding patterns identified locally. To tackle this, this paper proposes a federated learning approach to enable different nodes to collaboratively train a unified intrusion detection system while avoiding the direct exchange of data. In our experiments, we tested a number of different federated learning strategies with two (2) base stations that serve as participating clients in a federated learning scheme, while a server orchestrates the training phase. In terms of evaluation, the proposed solution was tested against the 5G-NIDD dataset and produced a high detection rate of 97.89 % accuracy.},
 bibtype = {inproceedings},
 author = {Makris, Ioannis and Ntampakis, Nikolaos and Lagkas, Thomas and Radoglou-Grammatikis, Panagiotis and Goudos, Sotirios K and Argyriou, Vasileios and Fountoukidis, Eleftherios and Skarmeta, Antonio F and Saura, Pablo Fernandez and Sarigianndis, Panagiotis},
 doi = {10.1109/FNWF58287.2023.10520474},
 booktitle = {2023 IEEE Future Networks World Forum (FNWF)}
}

The popularity of 5G networks has resulted in significant advancement and opportunities in connectivity and reliability of communications, but, concurrently, it raised security challenges and privacy concerns due to the distributed and highly dynamic nature of these networks. In particular, while participating devices and nodes in a 5G network need to be resilient against cyber threats, most of them are not allowed to exchange their data, and, therefore, they are limited only to the corresponding patterns identified locally. To tackle this, this paper proposes a federated learning approach to enable different nodes to collaboratively train a unified intrusion detection system while avoiding the direct exchange of data. In our experiments, we tested a number of different federated learning strategies with two (2) base stations that serve as participating clients in a federated learning scheme, while a server orchestrates the training phase. In terms of evaluation, the proposed solution was tested against the 5G-NIDD dataset and produced a high detection rate of 97.89 % accuracy.

@article{
 title = {Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in smart farming: A comprehensive review},
 type = {article},
 year = {2022},
 pages = {100187},
 websites = {https://www.sciencedirect.com/science/article/pii/S2542660520300238?via%3Dihub},
 month = {3},
 publisher = {Elsevier},
 day = {7},
 id = {f01d22a6-6cf3-3503-ab3a-8041859fb8be},
 created = {2020-04-28T21:46:19.635Z},
 accessed = {2020-04-29},
 file_attached = {true},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:46.665Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2022},
 private_publication = {false},
 abstract = {Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.},
 bibtype = {article},
 author = {Boursianis, Achilles D. and Papadopoulou, Maria S. and Diamantoulakis, Panagiotis and Liopa-Tsakalidi, Aglaia and Barouchas, Pantelis and Salahas, George and Karagiannidis, George and Wan, Shaohua and Goudos, Sotirios K.},
 doi = {10.1016/J.IOT.2020.100187},
 journal = {Internet of Things}
}

Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.

@article{
 title = {Modelling, Detecting and Mitigating Threats against Industrial Healthcare Systems: A combined SDN and Reinforcement Learning Approach},
 type = {article},
 year = {2022},
 pages = {2041-2052},
 volume = {18},
 id = {d87891c9-e1f5-36dd-8a20-46a27de09da1},
 created = {2021-07-02T06:29:13.392Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:49.088Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9470933},
 source_type = {article},
 private_publication = {false},
 abstract = {The rise of the Internet of Medical Things introduces the healthcare ecosystem in a new digital era with multiple benefits, such as remote medical assistance, real-time monitoring, and pervasive control. However, despite the valuable healthcare services, this progression raises significant cybersecurity and privacy concerns. In this article, we focus our attention on the IEC 60 870-5-104 protocol, which is widely adopted in industrial healthcare systems. First, we investigate and assess the severity of the IEC 60 870-5-104 cyberattacks by providing a quantitative threat model, which relies on Attack Defence Trees and Common Vulnerability Scoring System v3.1. Next, we introduce an intrusion detection and prevention system (IDPS), which is capable of discriminating and mitigating automatically the IEC 60 870-5-104 cyberattacks. The proposed IDPS takes full advantage of the machine learning (ML) and software defined networking (SDN) technologies. ML is used to detect the IEC 60 870-5-104 cyberattacks, utilizing 1) Transmission Control Protocol/Internet Protocol network flow statistics and 2) IEC 60 870-5-104 payload flow statistics. On the other side, the automated mitigation is transformed into a multiarmed bandit problem, which is solved through a reinforcement learning method called Thomson sampling and SDN. The evaluation analysis demonstrates the efficiency of the proposed IDPS in terms of intrusion detection accuracy and automated mitigation performance. The detection accuracy and the F1 score of the proposed IDPS reach 0.831 and 0.8258, respectively, while the mitigation accuracy is calculated at 0.923.},
 bibtype = {article},
 author = {Radoglou-Grammatikis, Panagiotis and Robolos, Konstantinos and Sarigiannidis, Panagiotis and Argyriou, Vasileios and Lagkas, Thomas and Sarigiannidis, Antonios and Goudos, Sotirios K and Wan, Shawn},
 doi = {10.1109/TII.2021.3093905},
 journal = {IEEE Transactions on Industrial Informatics},
 number = {3}
}

The rise of the Internet of Medical Things introduces the healthcare ecosystem in a new digital era with multiple benefits, such as remote medical assistance, real-time monitoring, and pervasive control. However, despite the valuable healthcare services, this progression raises significant cybersecurity and privacy concerns. In this article, we focus our attention on the IEC 60 870-5-104 protocol, which is widely adopted in industrial healthcare systems. First, we investigate and assess the severity of the IEC 60 870-5-104 cyberattacks by providing a quantitative threat model, which relies on Attack Defence Trees and Common Vulnerability Scoring System v3.1. Next, we introduce an intrusion detection and prevention system (IDPS), which is capable of discriminating and mitigating automatically the IEC 60 870-5-104 cyberattacks. The proposed IDPS takes full advantage of the machine learning (ML) and software defined networking (SDN) technologies. ML is used to detect the IEC 60 870-5-104 cyberattacks, utilizing 1) Transmission Control Protocol/Internet Protocol network flow statistics and 2) IEC 60 870-5-104 payload flow statistics. On the other side, the automated mitigation is transformed into a multiarmed bandit problem, which is solved through a reinforcement learning method called Thomson sampling and SDN. The evaluation analysis demonstrates the efficiency of the proposed IDPS in terms of intrusion detection accuracy and automated mitigation performance. The detection accuracy and the F1 score of the proposed IDPS reach 0.831 and 0.8258, respectively, while the mitigation accuracy is calculated at 0.923.

@article{
 title = {Towards Fairness-Aware Time-Sensitive Asynchronous Federated Learning for Critical Energy Infrastructure},
 type = {article},
 year = {2022},
 keywords = {Computa,Resource management,Task analysis,Training},
 pages = {3462-3472},
 volume = {18},
 id = {b4785362-33d6-35b0-94f9-c8718dacc615},
 created = {2021-10-10T06:26:03.048Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-02-04T06:23:20.041Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9560090},
 source_type = {article},
 private_publication = {false},
 abstract = {Critical energy infrastructure (CEI) systems are vital to underpin the national economy and social development, but vulnerable to cyber attack and data privacy leakage when distributed machine learning technologies are deployed on them. Although federated learning (FL) has promoted distributed collaborative learning while keeping natural compliance with the privacy protection, it is tremendously difficult to schedule edge nodes of CEI collaboratively when asynchronous FL tasks are applied in CEI system, since the CEI system must make an irrevocable immediate decision on whether to hire a participant who arrives and departs dynamically without knowing future information. We tackle this issue by designing fairness-aware and time-sensitive task allocation mechanisms in asynchronous FL for CEI. First, we design an optimal multi-dimensional contract to guarantee the reliability, honesty and fairness, and maximize the learning accuracy for the fixed deadline scenario. Second, we design a multi-metric participant recruitment mechanism to control time consumption for the limited budget scenario, prove that the problem of optimizing this mechanism is NP-Hard, and propose an e-approximation algorithm accordingly. Finally, extensive experiments using both real-world data and simulated data further demonstrate the effectiveness and efficiency of our proposed mechanisms compared to the state-of-the-art approaches.},
 bibtype = {article},
 author = {Lu, Jianfeng and Liu, Haibo and Zhang, Zhao and Wang, Jiangtao and Goudos, Sotirios K and Wan, Shaohua},
 doi = {10.1109/TII.2021.3117861},
 journal = {IEEE Transactions on Industrial Informatics},
 number = {5}
}

Critical energy infrastructure (CEI) systems are vital to underpin the national economy and social development, but vulnerable to cyber attack and data privacy leakage when distributed machine learning technologies are deployed on them. Although federated learning (FL) has promoted distributed collaborative learning while keeping natural compliance with the privacy protection, it is tremendously difficult to schedule edge nodes of CEI collaboratively when asynchronous FL tasks are applied in CEI system, since the CEI system must make an irrevocable immediate decision on whether to hire a participant who arrives and departs dynamically without knowing future information. We tackle this issue by designing fairness-aware and time-sensitive task allocation mechanisms in asynchronous FL for CEI. First, we design an optimal multi-dimensional contract to guarantee the reliability, honesty and fairness, and maximize the learning accuracy for the fixed deadline scenario. Second, we design a multi-metric participant recruitment mechanism to control time consumption for the limited budget scenario, prove that the problem of optimizing this mechanism is NP-Hard, and propose an e-approximation algorithm accordingly. Finally, extensive experiments using both real-world data and simulated data further demonstrate the effectiveness and efficiency of our proposed mechanisms compared to the state-of-the-art approaches.

@article{
 title = {Blockchain-empowered Decentralized Cross-domain Federated Learning for 5G-enabled UAVs},
 type = {article},
 year = {2022},
 keywords = {Authentication,Blockchains,Industrial Internet of},
 pages = {3582-3592},
 volume = {18},
 id = {16793254-271c-35d5-9930-cb09add65175},
 created = {2021-10-10T06:26:03.057Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-02-04T06:23:20.088Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9551794},
 source_type = {article},
 private_publication = {false},
 abstract = {Motivated by Industry 4.0, 5G-enabled unmanned aerial vehicles (UAVs; also known as drones) are widely applied in various industries. However, the opening 5G network threatens the safe sharing of data. Especially, privacy leakage will bring serious losses to users. As a new machine learning paradigm, federated learning (FL) avoids privacy leakage by sharing data models instead of raw data. Unfortunately, the traditional FL framework is highly dependent on a centralized aggregation server, which will cause the system to crash if the server is compromised. Unauthorized participants may launch poisoning attacks, thereby reducing the usability of the model. In addition, there are communication barriers when a large number of cross-domain devices collaborate to learn. Q1-1: To address the above issues, a blockchain-empowered decentralized horizontal federated learning framework (BE-DHFL) is proposed. The authentication of cross-domain UAVs is accomplished through a multi-signature smart contract. Global model updates are computed by using a smart contract instead of centralized server. Extensive experimental results show that the proposed scheme achieves a high efficiency of cross-domain authentication and good accuracy},
 bibtype = {article},
 author = {Feng, Chaosheng and Liu, Bin and Yu, Keping and Goudos, Sotirios K and Wan, Shaohua},
 doi = {10.1109/TII.2021.3116132},
 journal = {IEEE Transactions on Industrial Informatics},
 number = {5}
}

Motivated by Industry 4.0, 5G-enabled unmanned aerial vehicles (UAVs; also known as drones) are widely applied in various industries. However, the opening 5G network threatens the safe sharing of data. Especially, privacy leakage will bring serious losses to users. As a new machine learning paradigm, federated learning (FL) avoids privacy leakage by sharing data models instead of raw data. Unfortunately, the traditional FL framework is highly dependent on a centralized aggregation server, which will cause the system to crash if the server is compromised. Unauthorized participants may launch poisoning attacks, thereby reducing the usability of the model. In addition, there are communication barriers when a large number of cross-domain devices collaborate to learn. Q1-1: To address the above issues, a blockchain-empowered decentralized horizontal federated learning framework (BE-DHFL) is proposed. The authentication of cross-domain UAVs is accomplished through a multi-signature smart contract. Global model updates are computed by using a smart contract instead of centralized server. Extensive experimental results show that the proposed scheme achieves a high efficiency of cross-domain authentication and good accuracy

@article{
 title = {Drone-Base-Station for Next-Generation Internet-of-Things: A Comparison of Swarm Intelligence Approaches},
 type = {article},
 year = {2022},
 pages = {32-47},
 volume = {3},
 id = {2ffa50d5-3622-3c11-8374-eda6109e1cd9},
 created = {2021-12-08T07:50:19.295Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:48.904Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9638972},
 source_type = {article},
 private_publication = {false},
 abstract = {The emergence of next-generation Internet-of-Things (NG-IoT) applications introduces several challenges for the sixth-generation (6G) mobile networks, such as massive connectivity, increased network capacity, and extremely low-latency. To countermeasure the aforementioned challenges, ultra-dense networking has been widely identified as a possible solution. However, the dense deployment of base stations (BSs) is not always possible or cost-efficient. Drone-base-stations (DBSs) can facilitate network expansion and efficiently address the requirements of NG-IoT. In addition, due to their flexibility, they can provide on-demand connectivity in emergency scenarios or address temporary increases in network traffic. Nevertheless, the optimal placement of a DBS is not a straightforward task due to the limited energy reserves and the increased signal quality degradation in air-to-ground links. To this end, swarm intelligence approaches can be attractive solutions for determining the optimal position of the DBS in the three-dimensional (3D) space. In this work, we explore well-known swarm intelligence approaches, namely the Cuckoo Search (CS), Elephant Herd Optimization (EHO), Grey Wolf Optimization (GWO), Monarch Butterfly Optimization (MBO), Salp Swarm Algorithm (SSA), and Particle Swarm Optimization (PSO) and investigate their performance and efficiency in solving the aforementioned problem. In particular, we investigate the performance of three scenarios in the presence of different swarm intelligence approaches. Additionally, we carry out non-parametric statistical tests, namely the Friedman and Wilcoxon tests, in order to compare the different approaches.},
 bibtype = {article},
 author = {Pliatsios, Dimitrios and Goudos, Sotirios K and Lagkas, Thomas and Argyriou, Vasileios and Boulogeorgos, Alexandros Apostolos A and Sarigiannidis, Panagiotis},
 doi = {10.1109/OJAP.2021.3133459},
 journal = {IEEE Open Journal of Antennas and Propagation}
}

The emergence of next-generation Internet-of-Things (NG-IoT) applications introduces several challenges for the sixth-generation (6G) mobile networks, such as massive connectivity, increased network capacity, and extremely low-latency. To countermeasure the aforementioned challenges, ultra-dense networking has been widely identified as a possible solution. However, the dense deployment of base stations (BSs) is not always possible or cost-efficient. Drone-base-stations (DBSs) can facilitate network expansion and efficiently address the requirements of NG-IoT. In addition, due to their flexibility, they can provide on-demand connectivity in emergency scenarios or address temporary increases in network traffic. Nevertheless, the optimal placement of a DBS is not a straightforward task due to the limited energy reserves and the increased signal quality degradation in air-to-ground links. To this end, swarm intelligence approaches can be attractive solutions for determining the optimal position of the DBS in the three-dimensional (3D) space. In this work, we explore well-known swarm intelligence approaches, namely the Cuckoo Search (CS), Elephant Herd Optimization (EHO), Grey Wolf Optimization (GWO), Monarch Butterfly Optimization (MBO), Salp Swarm Algorithm (SSA), and Particle Swarm Optimization (PSO) and investigate their performance and efficiency in solving the aforementioned problem. In particular, we investigate the performance of three scenarios in the presence of different swarm intelligence approaches. Additionally, we carry out non-parametric statistical tests, namely the Friedman and Wilcoxon tests, in order to compare the different approaches.

@article{
 title = {Artwork Style Recognition Using Vision Transformers and MLP Mixer},
 type = {article},
 year = {2022},
 volume = {10},
 websites = {https://www.mdpi.com/2227-7080/10/1/2},
 id = {5607ddde-49a2-37c5-b568-e6aa9341e1cc},
 created = {2021-12-28T07:48:51.980Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies10010002},
 source_type = {article},
 private_publication = {false},
 abstract = {Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the painting. In this paper, two different Deep Learning architectures—Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)—are trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset. In addition, a comparative study between the most common optimizers was conducted obtaining useful information for future studies.},
 bibtype = {article},
 author = {Iliadis, Lazaros Alexios and Nikolaidis, Spyridon and Sarigiannidis, Panagiotis and Wan, Shaohua and Goudos, Sotirios K},
 doi = {10.3390/technologies10010002},
 journal = {Technologies},
 number = {1}
}

Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the painting. In this paper, two different Deep Learning architectures—Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)—are trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset. In addition, a comparative study between the most common optimizers was conducted obtaining useful information for future studies.

@article{
 title = {From Spatial Urban Site Data to Path Loss Prediction: An Ensemble Learning Approach},
 type = {article},
 year = {2022},
 pages = {6101-6105},
 volume = {70},
 id = {2f6c0652-e08e-3364-a341-161e90a0f0e4},
 created = {2022-01-01T09:47:42.504Z},
 file_attached = {false},
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 last_modified = {2022-07-28T19:02:21.727Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9667264},
 source_type = {article},
 private_publication = {false},
 abstract = {Machine learning (ML) models have become increasingly popular in the field of path loss prediction. Their performance depends profoundly on the data they use as their input. The work at hand proposes and evaluates new input features for urban propagation. These features were obtained via image processing tools. Moreover, we propose a new two-level ensemble model using the concept of stacked generalization. The proposed model is based on seven different basic ML models. To the best of the authors knowledge, this is the first time that a two-level ensemble method is applied to a modeling problem in electromagnetics. The results demonstrate that the new input features, coupled with the new ensemble, provide improved prediction performance.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P and Boursianis, Achilles D and Goudos, Sotirios K and Siakavara, Katherine},
 doi = {10.1109/TAP.2021.3138257},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {7}
}

Machine learning (ML) models have become increasingly popular in the field of path loss prediction. Their performance depends profoundly on the data they use as their input. The work at hand proposes and evaluates new input features for urban propagation. These features were obtained via image processing tools. Moreover, we propose a new two-level ensemble model using the concept of stacked generalization. The proposed model is based on seven different basic ML models. To the best of the authors knowledge, this is the first time that a two-level ensemble method is applied to a modeling problem in electromagnetics. The results demonstrate that the new input features, coupled with the new ensemble, provide improved prediction performance.

@article{
 title = {Guest Editorial: Antenna Systems for 5G and Beyond},
 type = {article},
 year = {2022},
 pages = {12-13},
 volume = {60},
 id = {bc5d12eb-be23-380a-a8a4-7de3e0e59b6b},
 created = {2022-02-12T19:23:40.819Z},
 file_attached = {false},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9711510},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Matin, Mohammad A and Sharawi, Mohammad S and Goudos, Sotirios K and Zhu, Jiang},
 doi = {10.1109/MCOM.2022.9711510},
 journal = {IEEE Communications Magazine},
 number = {1}
}

@inproceedings{
 title = {Ensemble Learning for 5G Flying Base Station Path Loss Modelling},
 type = {inproceedings},
 year = {2022},
 keywords = {Cellular networks;Base stations;5G mobile communic},
 pages = {1-4},
 id = {c544733d-cf08-31d1-8cfe-a5f9a4e36b09},
 created = {2022-05-12T20:33:00.967Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:33:00.967Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9768903},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The usage of unmanned aerial vehicles (UAVs) as flying base stations (FBSs) for expanding coverage and assisting the terrestrial cellular networks constitutes a promising technology for 5G and beyond. The wide range of a flying base station's movement may stretch the boundaries of path loss at the receiver's site and induce the occurrence of extreme values. Thus, using machine learning techniques may help in accurate path loss modeling for this case. In this paper, we use a combination of the techniques of ensemble learning and oversampling to provide a satisfactory path loss model for FBSs. The datasets used have been obtained through Ray Tracing simulations.},
 bibtype = {inproceedings},
 author = {Sotiroudis, Sotirios P and Athanasiadou, Georgia and Tsoulos, George V and Christodoulou, Christos and Goudos, Sotirios K},
 booktitle = {2022 16th European Conference on Antennas and Propagation (EuCAP)}
}

The usage of unmanned aerial vehicles (UAVs) as flying base stations (FBSs) for expanding coverage and assisting the terrestrial cellular networks constitutes a promising technology for 5G and beyond. The wide range of a flying base station's movement may stretch the boundaries of path loss at the receiver's site and induce the occurrence of extreme values. Thus, using machine learning techniques may help in accurate path loss modeling for this case. In this paper, we use a combination of the techniques of ensemble learning and oversampling to provide a satisfactory path loss model for FBSs. The datasets used have been obtained through Ray Tracing simulations.

@inproceedings{
 title = {Frequency Selective Surface Design Using Coot Optimization Algorithm for 5G Applications},
 type = {inproceedings},
 year = {2022},
 pages = {184-187},
 id = {3c648906-1ea7-3c81-bf9d-f3d0bb551eeb},
 created = {2022-07-05T18:00:44.383Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:18:57.336Z},
 read = {false},
 starred = {true},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9810997},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The interest in Frequency Selective Surfaces has been raised during the last years, mostly due to the advent of 5G cellular communication networks. As electromagnetic structures with diverse characteristics, FSSs can provide comparative advantages in 5G communication systems. In this paper, we design and optimize an FSS, which acts as an absorber in the 5G NR n78 frequency band. As an optimizer, we utilize a meta-heuristic swarm intelligence algorithm, i.e., the Coot Optimization Algorithm. The selected algorithm performs the optimization method both to the unit cell and the corresponding FSS structure. Computed results demonstrate quite satisfactory performance of the presented FSS design, in terms of the minimum reflection coefficient, the maximum realized gain, and the maximum efficiency making it a promising candidate for 5G applications.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Salucci, Marco and Polo, Alessandro and Sarigiannidis, Panagiotis and Koulouridis, Stavros and Goudos, Sotirios K},
 doi = {10.1109/iWAT54881.2022.9810997},
 booktitle = {2022 International Workshop on Antenna Technology (iWAT)}
}

The interest in Frequency Selective Surfaces has been raised during the last years, mostly due to the advent of 5G cellular communication networks. As electromagnetic structures with diverse characteristics, FSSs can provide comparative advantages in 5G communication systems. In this paper, we design and optimize an FSS, which acts as an absorber in the 5G NR n78 frequency band. As an optimizer, we utilize a meta-heuristic swarm intelligence algorithm, i.e., the Coot Optimization Algorithm. The selected algorithm performs the optimization method both to the unit cell and the corresponding FSS structure. Computed results demonstrate quite satisfactory performance of the presented FSS design, in terms of the minimum reflection coefficient, the maximum realized gain, and the maximum efficiency making it a promising candidate for 5G applications.

@article{
 title = {Guest Editorial Introduction to the Special Issue on Context Prediction of Autonomous Vehicles},
 type = {article},
 year = {2022},
 pages = {9307-9310},
 volume = {23},
 id = {0ba07c71-35ae-328d-b872-d1afd7c3eec2},
 created = {2022-07-13T21:48:26.203Z},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9826340},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Wan, Shaohua and Goudos, Sotirios K and Jolfaei, Alireza and Joseph, Wout},
 doi = {10.1109/TITS.2022.3185390},
 journal = {IEEE Transactions on Intelligent Transportation Systems},
 number = {7}
}

@inproceedings{
 title = {Antenna Design for Next-generation Internet-of-Things Nodes using Generative Adversarial Networks},
 type = {inproceedings},
 year = {2022},
 pages = {166-167},
 publisher = {ISEM},
 city = {Thessaloniki, Greece},
 id = {80baf021-6e8b-34b5-804f-0ff0b51299b0},
 created = {2022-07-14T18:38:19.058Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:31:20.930Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {ISEM2022},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The advent of NGIoT next-generation Internet-of-Things (NG-IoT) brings different research challenges and priorities. The identified priorities encompass several components of the IoT stack and, as a result, relate to 6G, Distributed Ledgers, Big Data, Artificial Intelligence, Cyber Security, and Cloud Computing. Especially, the emerging sixth-generation (6G) mobile networks require features like massive connectivity, increased network capacity, and extremely low-latency. Antennas represent a crucial part of the NGIoT ecosystem. Thus, the antenna design for NGIoT nodes is a challenging task. Among others possible design options for the NGIoT case are the microstrip patch antennas. Microstrip patch antennas have played a crucial role in the advancements in mobile and satellite communications, due to their appealing characteristics [1]. However, their design demands many hours of trial-and-error simulations with full-wave electromagnetic solvers. One alternative to this standard procedure is the construction of data-driven approximation models, known as surrogate models. Surrogate models imitate the behavior and the performance of the simulation model as closely as possible while being computationally cheaper to evaluate.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios, Sotirios K. Goudos and Sarigiannidis, Panagiotis},
 booktitle = {Proceedings of the 20th International Symposium on applied Electromagnetics and Mechanics}
}

The advent of NGIoT next-generation Internet-of-Things (NG-IoT) brings different research challenges and priorities. The identified priorities encompass several components of the IoT stack and, as a result, relate to 6G, Distributed Ledgers, Big Data, Artificial Intelligence, Cyber Security, and Cloud Computing. Especially, the emerging sixth-generation (6G) mobile networks require features like massive connectivity, increased network capacity, and extremely low-latency. Antennas represent a crucial part of the NGIoT ecosystem. Thus, the antenna design for NGIoT nodes is a challenging task. Among others possible design options for the NGIoT case are the microstrip patch antennas. Microstrip patch antennas have played a crucial role in the advancements in mobile and satellite communications, due to their appealing characteristics [1]. However, their design demands many hours of trial-and-error simulations with full-wave electromagnetic solvers. One alternative to this standard procedure is the construction of data-driven approximation models, known as surrogate models. Surrogate models imitate the behavior and the performance of the simulation model as closely as possible while being computationally cheaper to evaluate.

@inproceedings{
 title = {A Cloud Computing web-based application for Smart Farming based on microservices architecture},
 type = {inproceedings},
 year = {2022},
 keywords = {Smart agriculture;Productivity;Cloud computing;Mac},
 pages = {1-5},
 id = {d118a657-5515-3260-8524-53a1aee7243c},
 created = {2022-07-29T06:57:57.160Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.160Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837727},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The agriculture sector is envisioning a revolution of traditional farming supported by Information and Communications Technologies (ICT) and Cloud Computing is one of them. This tendency is called Smart Farming and promises to boost productivity while reducing production costs and chemical inputs. Cloud Computing aims to provide the necessary resources and the central orchestration of all devices involved in a Smart Farming scenario. To achieve high scalability, usability and performance in Cloud-based applications, we have to move from a monolithic development approach to microservices architecture using cutting edge technologies like containerisation. This paper presents a Smart Farming application based on Cloud Computing that promises to provide useful information to agronomists and farmers to support their decisions based on measurements from ground sensors and images captured from UAVs or ground cameras. Our implementation is based on microservices architecture using Docker Containers as the virtualisation technology. Each microservice runs on a different container and communicates through a RESTful API interface. The proposed architecture is highly scalable in future upgrades and promises high performance and security.},
 bibtype = {inproceedings},
 author = {Moysiadis, Vasileios and Tsakos, Konstantinos and Sarigiannidis, Panagiotis and Petrakis, Euripides G M and Boursianis, Achilles D and Goudos, Sotirios K},
 doi = {10.1109/MOCAST54814.2022.9837727},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The agriculture sector is envisioning a revolution of traditional farming supported by Information and Communications Technologies (ICT) and Cloud Computing is one of them. This tendency is called Smart Farming and promises to boost productivity while reducing production costs and chemical inputs. Cloud Computing aims to provide the necessary resources and the central orchestration of all devices involved in a Smart Farming scenario. To achieve high scalability, usability and performance in Cloud-based applications, we have to move from a monolithic development approach to microservices architecture using cutting edge technologies like containerisation. This paper presents a Smart Farming application based on Cloud Computing that promises to provide useful information to agronomists and farmers to support their decisions based on measurements from ground sensors and images captured from UAVs or ground cameras. Our implementation is based on microservices architecture using Docker Containers as the virtualisation technology. Each microservice runs on a different container and communicates through a RESTful API interface. The proposed architecture is highly scalable in future upgrades and promises high performance and security.

@inproceedings{
 title = {Comparative Performance of Algorithmic Techniques for Optimizing Dual-Band Rectifier},
 type = {inproceedings},
 year = {2022},
 keywords = {RF energy harvesting;rectenna;impedance matching;o},
 pages = {1-4},
 id = {e5a6a85d-17d2-36d8-a10d-bdd5645e0a63},
 created = {2022-07-29T06:57:57.167Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.167Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837645},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Radio Frequency (RF) energy harvesting (EH) is a technique to replenish the source of wireless sensor networks (WSNs). Also, many interdisciplinary fields in the Internet-of-Things (IoT) era use RF-EH, like precision agriculture, biomedical, and robotics. Over the years, various designs have been presented in the literature operating in multi- or wide-band frequencies. Usually, a designed system is optimized using specific goals and optimization parameters to obtain maximization in power conversion efficiency (PCE). In this work, a dual-band RF rectifier system that resonates in the Wi-Fi frequency bands of 2.45 GHz and 5.8 GHz is presented. The proposed system is optimized using four optimization techniques, namely the Gradient algorithm, the Minimax algorithm, the Simulated Annealing, and the Genetic algorithm. A set of comparative results is presented to assess the performance of each technique and to obtain the feasible solution of the proposed design. Numerical results demonstrate that a 42.8% efficiency is achieved, having a 16 dBm input power and a 1.7 kΩ output resistance load.},
 bibtype = {inproceedings},
 author = {Papadopoulou, Maria S and Boursianis, Achilles D and Chatzopoulos, Argyrios and Sarigiannidis, Panagiotis and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/MOCAST54814.2022.9837645},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Radio Frequency (RF) energy harvesting (EH) is a technique to replenish the source of wireless sensor networks (WSNs). Also, many interdisciplinary fields in the Internet-of-Things (IoT) era use RF-EH, like precision agriculture, biomedical, and robotics. Over the years, various designs have been presented in the literature operating in multi- or wide-band frequencies. Usually, a designed system is optimized using specific goals and optimization parameters to obtain maximization in power conversion efficiency (PCE). In this work, a dual-band RF rectifier system that resonates in the Wi-Fi frequency bands of 2.45 GHz and 5.8 GHz is presented. The proposed system is optimized using four optimization techniques, namely the Gradient algorithm, the Minimax algorithm, the Simulated Annealing, and the Genetic algorithm. A set of comparative results is presented to assess the performance of each technique and to obtain the feasible solution of the proposed design. Numerical results demonstrate that a 42.8% efficiency is achieved, having a 16 dBm input power and a 1.7 kΩ output resistance load.

@inproceedings{
 title = {A System-by-Design Approach for Optimal Planning of EM Skins in Smart Urban Areas},
 type = {inproceedings},
 year = {2022},
 keywords = {Circuits and systems;Urban areas;Machine learning;},
 pages = {1-4},
 id = {20b74ab4-8b92-3e9a-86b8-9210878cd61f},
 created = {2022-07-29T06:57:57.311Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.311Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837767},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work deals with the optimal planning of low-cost/low-profile passive and static electromagnetic skins (EMSs) allowing to implement Smart Electromagnetic Environments (SEMEs) in large urban areas. Owing to the high complexity/scale of the EM problem at hand, the planning problem is formulated as a global optimization one efficiently solved thanks to a suitably-customized System-by-Design (SbD) methodology relying on Machine Learning (ML) and Evolutionary Algorithms (EAs). An illustrative example is shown to assess the effectiveness of the proposed SEME planning method in a realistic scenario.},
 bibtype = {inproceedings},
 author = {Salucci, Marco and Benoni, Arianna and Goudos, Sotirios K and Massa, Andrea},
 doi = {10.1109/MOCAST54814.2022.9837767},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

This work deals with the optimal planning of low-cost/low-profile passive and static electromagnetic skins (EMSs) allowing to implement Smart Electromagnetic Environments (SEMEs) in large urban areas. Owing to the high complexity/scale of the EM problem at hand, the planning problem is formulated as a global optimization one efficiently solved thanks to a suitably-customized System-by-Design (SbD) methodology relying on Machine Learning (ML) and Evolutionary Algorithms (EAs). An illustrative example is shown to assess the effectiveness of the proposed SEME planning method in a realistic scenario.

@inproceedings{
 title = {Integration of Information and Communication Technologies in Agriculture for Farm Management and Knowledge Exchange},
 type = {inproceedings},
 year = {2022},
 keywords = {Productivity;Technological innovation;Software arc},
 pages = {1-4},
 id = {30408cd0-cf0e-3e84-ba4c-18e0b4d3a289},
 created = {2022-07-29T06:57:57.317Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.317Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837534},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The demographic growth of the last centuries has been followed by a demand for higher productivity of agriculture activities and an increase in the quality of farming products. Modern consumers seek quality by selecting foods containing high concentrations of healthy nutrients (e.g., antioxidants, vitamins, minerals) while also valuing eco-friendly practices and sustainable consumption. In line with the modern social needs, integrating Information Communication Technologies (ICT) solutions could assist in different levels of the agriculture lifecycle, such as crop monitoring, animal production, food safety, and farm management. Two aspects that are often neglected from many ICT solutions are the compilation of different data sources into the proposed software architecture and the facilitation of knowledge exchange between domain experts. In order to fill the gap of knowledge accumulation in this paper we take into consideration the PestNu architecture, as defined in section V that illustrates the different steps that are required for a complete data analysis life cycle into the development and deployment of the OpenHub platform. The OpenHub aims to cover the knowledge hub between experts with different backgrounds and promote the best practices from different users with hands-on experience.},
 bibtype = {inproceedings},
 author = {Chaschatzis, Christos and Lytos, Anastasios and Bibi, Stamatia and Lagkas, Thomas and Petaloti, Christina and Goudos, Sotirios and Moscholios, Ioannis and Sarigiannidis, Panagiotis},
 doi = {10.1109/MOCAST54814.2022.9837534},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The demographic growth of the last centuries has been followed by a demand for higher productivity of agriculture activities and an increase in the quality of farming products. Modern consumers seek quality by selecting foods containing high concentrations of healthy nutrients (e.g., antioxidants, vitamins, minerals) while also valuing eco-friendly practices and sustainable consumption. In line with the modern social needs, integrating Information Communication Technologies (ICT) solutions could assist in different levels of the agriculture lifecycle, such as crop monitoring, animal production, food safety, and farm management. Two aspects that are often neglected from many ICT solutions are the compilation of different data sources into the proposed software architecture and the facilitation of knowledge exchange between domain experts. In order to fill the gap of knowledge accumulation in this paper we take into consideration the PestNu architecture, as defined in section V that illustrates the different steps that are required for a complete data analysis life cycle into the development and deployment of the OpenHub platform. The OpenHub aims to cover the knowledge hub between experts with different backgrounds and promote the best practices from different users with hands-on experience.

@inproceedings{
 title = {Music Deep Learning: A Survey on Deep Learning Methods for Music Processing},
 type = {inproceedings},
 year = {2022},
 keywords = {Deep Learning;Music Signal Processing;Music Inform},
 pages = {1-4},
 id = {f646b836-377c-3d2c-8a89-215ab0aad9e1},
 created = {2022-07-29T06:57:57.324Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.324Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837541},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Deep Learning has emerged as a powerful set of computational methods achieving great results in a variety of different tasks. Music signal processing, a field with rich commercial applications, seems to benefit too from this data-driven approach. In this paper a review of the state of the art Deep Learning methods applied on music signal processing is provided. A special focus is given in music information retrieval and music generation. In addition, possible future research directions are discussed.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios and Sotiroudis, Sotirios P and Kokkinidis, Kostas and Sarigiannidis, Panagiotis and Nikolaidis, Spiridon and Goudos, Sotirios K},
 doi = {10.1109/MOCAST54814.2022.9837541},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Deep Learning has emerged as a powerful set of computational methods achieving great results in a variety of different tasks. Music signal processing, a field with rich commercial applications, seems to benefit too from this data-driven approach. In this paper a review of the state of the art Deep Learning methods applied on music signal processing is provided. A special focus is given in music information retrieval and music generation. In addition, possible future research directions are discussed.

@inproceedings{
 title = {Smart Refrigeration Equipment based on IoT Technology for Reducing Power Consumption},
 type = {inproceedings},
 year = {2022},
 keywords = {Wireless communication;Performance evaluation;Wire},
 pages = {1-4},
 id = {7e0c4927-8eb2-3014-908b-7fcc9059cc06},
 created = {2022-07-29T06:57:57.324Z},
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 last_modified = {2022-07-29T06:57:57.324Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837760},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In developed countries, companies active in the food retail sector consume about 20% of the total power required for cooling and are therefore ranked among them with the largest energy footprint after the industries. For this reason, refrigeration equipment manufacturers are increasingly focusing on methods that will reduce the power consumption required for its efficient operation. The solutions that are currently implemented mainly focus on interventions in the development phase of freezer units (better insulation, variable frequency compressors, etc.), which, however, do not adequately address the problem. This paper presents the development of an IoT-based technology device which, using machine learning techniques, aims to reduce the power consumption of refrigeration equipment and consecutively, the energy footprint of food retailers.},
 bibtype = {inproceedings},
 author = {Koritsoglou, Kyriakos and Papadopoulou, Maria S and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/MOCAST54814.2022.9837760},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In developed countries, companies active in the food retail sector consume about 20% of the total power required for cooling and are therefore ranked among them with the largest energy footprint after the industries. For this reason, refrigeration equipment manufacturers are increasingly focusing on methods that will reduce the power consumption required for its efficient operation. The solutions that are currently implemented mainly focus on interventions in the development phase of freezer units (better insulation, variable frequency compressors, etc.), which, however, do not adequately address the problem. This paper presents the development of an IoT-based technology device which, using machine learning techniques, aims to reduce the power consumption of refrigeration equipment and consecutively, the energy footprint of food retailers.

@inproceedings{
 title = {Rectifier circuit design for 5G energy harvesting applications},
 type = {inproceedings},
 year = {2022},
 keywords = {Radio frequency;Performance evaluation;5G mobile c},
 pages = {1-4},
 id = {a52decdf-14cf-3327-9327-04e883ed2838},
 created = {2022-07-29T06:57:57.345Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.345Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837524},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The need for electronic devices usage has risen significantly over the years. This has in turn generated greater demands for electricity and in addition for green energy sources. These include Radio-Frequency (RF) energy harvesting. In this concept we design a rectifier circuit for RF to DC conversion suitable for operation at sub-6 GHz 5G bands. Such a circuit can be used to supply low-power electronic devices. The proposed rectifier works at the frequency band FR1 of 5G cellular network and more specifically at 3.5 GHz. The most important problem in the RF energy harvesters is low system efficiency, something that limits the popularity of the power harvest. The proposed design is found to be highly efficient in its current form. Numerical results show that the system in a single-tone signal provides maximum power conversion efficiency equal to 42.5% when the load of the circuit is 1.1 KΩ and the input power reaches 9 dBm. The presented rectifier circuit performs better or equally with similar designs in the literature.},
 bibtype = {inproceedings},
 author = {Bougas, D and Sarigiannidis, Panagiotis and Papadopoulou, Maria S and Nikolaidis, Spyridon and Boursianis, Achilles D and Goudos, Sotirios. K},
 doi = {10.1109/MOCAST54814.2022.9837524},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

The need for electronic devices usage has risen significantly over the years. This has in turn generated greater demands for electricity and in addition for green energy sources. These include Radio-Frequency (RF) energy harvesting. In this concept we design a rectifier circuit for RF to DC conversion suitable for operation at sub-6 GHz 5G bands. Such a circuit can be used to supply low-power electronic devices. The proposed rectifier works at the frequency band FR1 of 5G cellular network and more specifically at 3.5 GHz. The most important problem in the RF energy harvesters is low system efficiency, something that limits the popularity of the power harvest. The proposed design is found to be highly efficient in its current form. Numerical results show that the system in a single-tone signal provides maximum power conversion efficiency equal to 42.5% when the load of the circuit is 1.1 KΩ and the input power reaches 9 dBm. The presented rectifier circuit performs better or equally with similar designs in the literature.

@inproceedings{
 title = {Talking Vine: A Novel Smart Farming Application based on Wireless Distributed Sensing and Communication},
 type = {inproceedings},
 year = {2022},
 keywords = {distributed wireless sensing;internet of things (I},
 pages = {1-4},
 id = {cbb1ae2f-dd42-318f-bf7f-0ced9e60baea},
 created = {2022-07-29T06:57:57.351Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-29T06:57:57.351Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9837621},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This paper introduces "Talking Vine", a novel service that aims to tighten and "humanize" the relationship between users and IoT-enabled plants by means of distributed wireless sensing and communication technologies. The proposed system is under experimental validation within a farm vineyard in Trentino, Italy.},
 bibtype = {inproceedings},
 author = {Polo, Alessandro and Oliveri, Giacomo and Goudos, Sotirios K and Salucci, Marco and Massa, Andrea},
 doi = {10.1109/MOCAST54814.2022.9837621},
 booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

This paper introduces "Talking Vine", a novel service that aims to tighten and "humanize" the relationship between users and IoT-enabled plants by means of distributed wireless sensing and communication technologies. The proposed system is under experimental validation within a farm vineyard in Trentino, Italy.

@article{
 title = {The road to 6G: a comprehensive survey of deep learning applications in cell-free massive MIMO communications systems},
 type = {article},
 year = {2022},
 pages = {68},
 volume = {2022},
 websites = {https://doi.org/10.1186/s13638-022-02153-z},
 id = {c43ac614-9e19-3b86-8ff8-e5895adec812},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {RN481},
 source_type = {article},
 user_context = {Journal Article},
 private_publication = {false},
 abstract = {The fifth generation (5G) of telecommunications networks is currently commercially deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple-Output (M-MIMO) systems. However, future wireless networks are expected to serve a very large number of devices and the current MIMO networks are not scalable, highlighting the need for novel solutions. At this moment, Cell-free Massive MIMO (CF M-MIMO) technology seems to be the most promising idea in this direction. Despite their appealing characteristics, CF M-MIMO systems face their own challenges, such as power allocation and channel estimation. Deep Learning (DL) has been successfully employed to a wide range of problems in many different research areas, including wireless communications. In this paper, a review of the state-of-the-art DL methods applied to CF M-MIMO communications systems is provided. In addition, the basic characteristics of Cell-free networks are introduced, along with the presentation of the most commonly used DL models. Finally, future research directions are highlighted.},
 bibtype = {article},
 author = {Iliadis, Lazaros Alexios and Zaharis, Zaharias D and Sotiroudis, Sotirios and Sarigiannidis, Panagiotis and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1186/s13638-022-02153-z},
 journal = {EURASIP Journal on Wireless Communications and Networking},
 number = {1}
}

The fifth generation (5G) of telecommunications networks is currently commercially deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple-Output (M-MIMO) systems. However, future wireless networks are expected to serve a very large number of devices and the current MIMO networks are not scalable, highlighting the need for novel solutions. At this moment, Cell-free Massive MIMO (CF M-MIMO) technology seems to be the most promising idea in this direction. Despite their appealing characteristics, CF M-MIMO systems face their own challenges, such as power allocation and channel estimation. Deep Learning (DL) has been successfully employed to a wide range of problems in many different research areas, including wireless communications. In this paper, a review of the state-of-the-art DL methods applied to CF M-MIMO communications systems is provided. In addition, the basic characteristics of Cell-free networks are introduced, along with the presentation of the most commonly used DL models. Finally, future research directions are highlighted.

@article{
 title = {Scalable On-Chain and Off-Chain Blockchain for Sharing Economy in Large-Scale Wireless Networks},
 type = {article},
 year = {2022},
 pages = {32-38},
 volume = {29},
 id = {6936cb24-0415-3c2a-95b9-8ff3b379e927},
 created = {2022-08-17T09:35:05.138Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:08:49.133Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9857806},
 source_type = {article},
 private_publication = {false},
 abstract = {In the future sharing economy, billions of underutilized IoT devices will be deployed to enable a powerful and large-scale sharing market that produces economic, environmental, and social benefits. Given the fact that communications in numerous IoT devices through wireless links are unreliable, blockchain technology, as a promising solution, has emerged to achieve reliable and secure sharing services in a decentralized manner. However, applying blockchain in large-scale wireless networks confronts scalability challenges. This motivates us to propose a real-time, trusted data interactive, and fine-grained transaction supportable sharing framework, the core of which is a novel two-layer scaling blockchain design. In the on-chain layer, sharing-oriented sharding is employed to enable secure and efficient processing of macro-transactions on the chain. In the off-chain layer, cross-zone off-chain channels are set up to provide real-time sharing transactions with high-frequency micro-trading scenarios. Finally, a proof-of-concept case study of electric vehicle sharing data is implemented with experimental results to demonstrate the feasibility of our framework.},
 bibtype = {article},
 author = {Cai, Ting and Chen, Wuhui and Psannis, Kostas E and Goudos, Sotirios K and Yu, Yang and Zheng, Zibin and Wan, Shaohua},
 doi = {10.1109/MWC.004.2100616},
 journal = {IEEE Wireless Communications},
 number = {3}
}

In the future sharing economy, billions of underutilized IoT devices will be deployed to enable a powerful and large-scale sharing market that produces economic, environmental, and social benefits. Given the fact that communications in numerous IoT devices through wireless links are unreliable, blockchain technology, as a promising solution, has emerged to achieve reliable and secure sharing services in a decentralized manner. However, applying blockchain in large-scale wireless networks confronts scalability challenges. This motivates us to propose a real-time, trusted data interactive, and fine-grained transaction supportable sharing framework, the core of which is a novel two-layer scaling blockchain design. In the on-chain layer, sharing-oriented sharding is employed to enable secure and efficient processing of macro-transactions on the chain. In the off-chain layer, cross-zone off-chain channels are set up to provide real-time sharing transactions with high-frequency micro-trading scenarios. Finally, a proof-of-concept case study of electric vehicle sharing data is implemented with experimental results to demonstrate the feasibility of our framework.

@inproceedings{
 title = {Towards 6G: Deep Learning in Cell-Free Massive MIMO},
 type = {inproceedings},
 year = {2022},
 keywords = {6G,Cell-Free Massive MIMO,Deep learning,User-centric Cell-Free Massive MIMO},
 pages = {269-273},
 id = {2096b7e9-63f8-3873-b334-e8ea5135fc9d},
 created = {2022-08-25T07:30:49.796Z},
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 last_modified = {2024-10-15T14:38:08.239Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Iliadis2022},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {Massive Multiple-Input-Multiple-Output (MIMO) technology is considered a crucial part of the fifth generation (5G) telecommunications systems. However, moving towards sixth generation (6G) wireless networks, novel solutions have to be incorporated into the current telecommunications' systems. Cell-free Massive MIMO and especially the user-centric approach, seems to be the most promising idea to this direction at this moment. Nevertheless, there are many open issues to be resolved. Deep Learning has been successfully applied to a wide range of problems in many different fields, including wireless communications. In this paper, a review of the state-of-The-Art Deep Learning methods applied to Cell-free Massive MIMO communications systems is provided. In addition future research directions are discussed.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios and Zaharis, Zaharias D and Sotiroudis, Sotirios P and Sarigiannidis, Panagiotis and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/BlackSeaCom54372.2022.9858306},
 booktitle = {2022 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2022}
}

Massive Multiple-Input-Multiple-Output (MIMO) technology is considered a crucial part of the fifth generation (5G) telecommunications systems. However, moving towards sixth generation (6G) wireless networks, novel solutions have to be incorporated into the current telecommunications' systems. Cell-free Massive MIMO and especially the user-centric approach, seems to be the most promising idea to this direction at this moment. Nevertheless, there are many open issues to be resolved. Deep Learning has been successfully applied to a wide range of problems in many different fields, including wireless communications. In this paper, a review of the state-of-The-Art Deep Learning methods applied to Cell-free Massive MIMO communications systems is provided. In addition future research directions are discussed.

@article{
 title = {A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era},
 type = {article},
 year = {2022},
 pages = {87535-87562},
 volume = {10},
 id = {896ba4d7-1771-3ddb-a7c6-584d66ee6720},
 created = {2022-08-27T07:39:28.911Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:08:48.977Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9861650},
 source_type = {article},
 private_publication = {false},
 abstract = {The evolution of the wireless network systems over decades has been providing new services to the users with the help of innovative network and device technologies. In recent times, the 5G network systems are about to be deployed which creates the opportunity to realize massive connectivity with high throughput, low latency, high energy efficiency and security. It also focuses on providing massive Internet of Things (IoT) network connectivity as well as services for good health, large-scale agricultural and industrial production, intelligent traffic control and electricity generation, transmission and distribution systems. However, the ever-increasing number of user devices is directing the researchers towards beyond 5G systems to allocate these user devices with higher bandwidth. Researches on the 6G wireless network systems have already begun to provide higher bandwidth availability for densely connected larger network devices with QoS surety. Researchers are leveraging artificial intelligence (AI)/machine learning (ML) for enhancing future IoT network operations and services. This paper attempts to discuss AI/ML algorithms that can help in developing energy efficient, secured and effective IoT network operations and services. In particular, our article concentrates on the major issues and factors that influence the design of the communication systems for future IoT with the integration of AI/ML. It also highlights application domains, including smart healthcare, smart agriculture, smart transportation, smart grid and smart industry that can operate efficiently and securely. Finally, this paper ends with the discussion on future research scopes with these algorithms in addressing the open issues of the future IoT network systems.},
 bibtype = {article},
 author = {Mahmood, M Rezwanul and Matin, Mohammad Abdul and Sarigiannidis, Panagiotis and Goudos, Sotirios K},
 doi = {10.1109/ACCESS.2022.3199689},
 journal = {IEEE Access}
}

The evolution of the wireless network systems over decades has been providing new services to the users with the help of innovative network and device technologies. In recent times, the 5G network systems are about to be deployed which creates the opportunity to realize massive connectivity with high throughput, low latency, high energy efficiency and security. It also focuses on providing massive Internet of Things (IoT) network connectivity as well as services for good health, large-scale agricultural and industrial production, intelligent traffic control and electricity generation, transmission and distribution systems. However, the ever-increasing number of user devices is directing the researchers towards beyond 5G systems to allocate these user devices with higher bandwidth. Researches on the 6G wireless network systems have already begun to provide higher bandwidth availability for densely connected larger network devices with QoS surety. Researchers are leveraging artificial intelligence (AI)/machine learning (ML) for enhancing future IoT network operations and services. This paper attempts to discuss AI/ML algorithms that can help in developing energy efficient, secured and effective IoT network operations and services. In particular, our article concentrates on the major issues and factors that influence the design of the communication systems for future IoT with the integration of AI/ML. It also highlights application domains, including smart healthcare, smart agriculture, smart transportation, smart grid and smart industry that can operate efficiently and securely. Finally, this paper ends with the discussion on future research scopes with these algorithms in addressing the open issues of the future IoT network systems.

@inbook{
 type = {inbook},
 year = {2022},
 pages = {243-263},
 websites = {https://doi.org/10.1007/978-3-031-07512-4_9},
 publisher = {Springer International Publishing},
 city = {Cham},
 id = {eff16c19-29ef-3afe-bf8f-cacb5dacd439},
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 authored = {true},
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 citation_key = {Goudos2022},
 source_type = {inbook},
 private_publication = {false},
 abstract = {The topic of designing linear arrays with design limitations such as the minimum and maximum distance between two adjacent elements is addressed in this book chapter. We apply a design framework based on Differential Evolution (DE) with ranking-based mutation operators. This DE variant uses a different mutation operator than the original DE. The basic idea in this DE variant is to probabilistically select the vectors for the mutation operator based on their ranking in the current population instead of using a random selection mechanism which is the case in the original DE. We perform a comparative study on four different linear array design cases among different DE variants with and without ranking-based mutation operator. The results indicate the ranking-based mutation operator gives an additional advantage to design process. The ranking-based DE variants obtain in general better results and seem to obtain faster convergence as well.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K and Mohamed, Ali Wagdy},
 editor = {Mohamed, Ali and Oliva, Diego and Suganthan, Ponnuthurai Nagaratnam},
 doi = {10.1007/978-3-031-07512-4_9},
 chapter = {Antenna Array Design Using Differential Evolution with Ranking-Based Mutation Operators},
 title = {Handbook of Nature-Inspired Optimization Algorithms: The State of the Art: Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems}
}

The topic of designing linear arrays with design limitations such as the minimum and maximum distance between two adjacent elements is addressed in this book chapter. We apply a design framework based on Differential Evolution (DE) with ranking-based mutation operators. This DE variant uses a different mutation operator than the original DE. The basic idea in this DE variant is to probabilistically select the vectors for the mutation operator based on their ranking in the current population instead of using a random selection mechanism which is the case in the original DE. We perform a comparative study on four different linear array design cases among different DE variants with and without ranking-based mutation operator. The results indicate the ranking-based mutation operator gives an additional advantage to design process. The ranking-based DE variants obtain in general better results and seem to obtain faster convergence as well.

@inproceedings{
 title = {Dual-Band Frequency Selective Surface Design Using Artificial Hummingbird Algorithm},
 type = {inproceedings},
 year = {2022},
 keywords = {Radio frequency;Performance evaluation;Frequency s},
 pages = {982-983},
 id = {13724281-7933-39ef-88c7-b5c4f88d4bcb},
 created = {2022-09-23T05:26:05.981Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-09-23T05:26:05.981Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9886108},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this work, the design and optimization of an FSS device are presented for dual-band operation in the frequency bands of LTE-2600 and 5G-FR1 cellular communication net-works. The proposed FSS device is designed by utilizing a recently introduced swarm-based meta-heuristic, namely the artificial hummingbird algorithm. The obtained numerical results of the proposed FSS device exhibit resonances at the frequency bands of interest, and quite acceptable values of gain and efficiency. Its overall performance makes it a suitable candidate for a receiving module of a rectenna in RF energy harvesting applications.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Koulouridis, Stavros and Georgiadis, Apostolos and Tentzeris, Manos M and Goudos, Sotirios K},
 doi = {10.1109/AP-S/USNC-URSI47032.2022.9886108},
 booktitle = {2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI)}
}

In this work, the design and optimization of an FSS device are presented for dual-band operation in the frequency bands of LTE-2600 and 5G-FR1 cellular communication net-works. The proposed FSS device is designed by utilizing a recently introduced swarm-based meta-heuristic, namely the artificial hummingbird algorithm. The obtained numerical results of the proposed FSS device exhibit resonances at the frequency bands of interest, and quite acceptable values of gain and efficiency. Its overall performance makes it a suitable candidate for a receiving module of a rectenna in RF energy harvesting applications.

@inproceedings{
 title = {A hybrid CNN-NGBoost model for probabilistic image-driven path loss prediction},
 type = {inproceedings},
 year = {2022},
 keywords = {Roads;Conferences;Estimation;Predictive models;Pro},
 pages = {898-899},
 id = {26bb987b-a91d-3bf5-9d2d-5d52df6e5174},
 created = {2022-09-23T05:26:05.982Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-09-23T05:26:05.982Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9886672},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {We propose a hybrid model for probabilistic path loss prediction, based on the footprint of the urban built-up area. A Convolutional Neural Network (CNN) is being deployed in order to extract information regarding the built-up area in the form of a feature vector. The extracted features are then processed from a Natural Gradient Boosting (NGBoost) regressor, who is inherently capable of performing probabilistic prediction. That is, along with point estimations of the received path loss value, the CNN-NGBoost model additionally calculates the prediction interval which covers a user-defined percentage of the prediction distribution. The proposed model can therefore assist network engineers in calculating the risk of their decisions about network coverage.},
 bibtype = {inproceedings},
 author = {Sotiroudis, Sotirios P and Goudos, Sotirios K and Christodoulou, Christos},
 doi = {10.1109/AP-S/USNC-URSI47032.2022.9886672},
 booktitle = {2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI)}
}

We propose a hybrid model for probabilistic path loss prediction, based on the footprint of the urban built-up area. A Convolutional Neural Network (CNN) is being deployed in order to extract information regarding the built-up area in the form of a feature vector. The extracted features are then processed from a Natural Gradient Boosting (NGBoost) regressor, who is inherently capable of performing probabilistic prediction. That is, along with point estimations of the received path loss value, the CNN-NGBoost model additionally calculates the prediction interval which covers a user-defined percentage of the prediction distribution. The proposed model can therefore assist network engineers in calculating the risk of their decisions about network coverage.

@inproceedings{
 title = {Detecting coherent sources with deep learning},
 type = {inproceedings},
 year = {2022},
 keywords = {Deep learning;Radio frequency;Transforms;Interfere},
 pages = {98-99},
 id = {97c7142b-cba5-3014-9e69-1f5a4c3af047},
 created = {2022-09-23T05:26:06.123Z},
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 last_modified = {2022-09-23T05:26:06.123Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9887433},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Detecting correlated sources in a dynamic radio frequency (RF) environment is both challenging and critical to antenna array processing. We introduce a deep learning framework capable of detecting both correlated and uncorrelated radio frequency sources in the presence of ambient noise and multiple interference signals. The auto-correlation matrix is extracted from the received signal matrix and spatially smoothed using forward-backward averaging. The processed signal is then used as an input to a ResNet34 architecture which detects the number of sources present in the sampled waveform. We transform the source detection problem into a one-vs-all binary classification problem where, the machine predicts a binary label corresponding to the number of detected sources. The designed framework is trained and evaluated on simulation data closely replicating real-time RF environments.},
 bibtype = {inproceedings},
 author = {Vijayamohanan, Jayakrishnan and Gupta, Arjun and Goudos, Sotirios and Christodoulou, Christos},
 doi = {10.23919/USNC-URSI52669.2022.9887433},
 booktitle = {2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)}
}

Detecting correlated sources in a dynamic radio frequency (RF) environment is both challenging and critical to antenna array processing. We introduce a deep learning framework capable of detecting both correlated and uncorrelated radio frequency sources in the presence of ambient noise and multiple interference signals. The auto-correlation matrix is extracted from the received signal matrix and spatially smoothed using forward-backward averaging. The processed signal is then used as an input to a ResNet34 architecture which detects the number of sources present in the sampled waveform. We transform the source detection problem into a one-vs-all binary classification problem where, the machine predicts a binary label corresponding to the number of detected sources. The designed framework is trained and evaluated on simulation data closely replicating real-time RF environments.

@inproceedings{
 title = {Wideband Antenna Design for 5G mmWave Applications Using Enhanced Adaptive Differential Evolution},
 type = {inproceedings},
 year = {2022},
 keywords = {Slot antennas;5G mobile communication;Shape;Adapti},
 pages = {63-64},
 id = {cb9ca4d4-3516-38f2-a747-63dba657a1f5},
 created = {2022-09-23T05:26:06.153Z},
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 authored = {true},
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 citation_key = {9886187},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Antenna design for 5G mmwave applications is a challenging task. Moreover, if the design specifications require wideband behavior the problem becomes more complex. In this paper, we address the above presented design problem by introducing a new modified E-shaped patch antenna that has an additional third slot. We present a design procedure based on Enhanced Adaptive Differential Evolution. The numerical results show that the obtained best design presents wideband behavior that covers the whole frequency range 2 (FR2) zone and expands up to 60GHz.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Boursianis, Achilles and Mohamed, Ali Wagdy and Salucci, Marco and Koulouridis, Stavros and Christodoulou, Christos},
 doi = {10.1109/AP-S/USNC-URSI47032.2022.9886187},
 booktitle = {2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI)}
}

Antenna design for 5G mmwave applications is a challenging task. Moreover, if the design specifications require wideband behavior the problem becomes more complex. In this paper, we address the above presented design problem by introducing a new modified E-shaped patch antenna that has an additional third slot. We present a design procedure based on Enhanced Adaptive Differential Evolution. The numerical results show that the obtained best design presents wideband behavior that covers the whole frequency range 2 (FR2) zone and expands up to 60GHz.

@inproceedings{
 title = {Online Examination and Self-Assessment Tool for EM Teaching},
 type = {inproceedings},
 year = {2022},
 keywords = {Conferences;Education;Electromagnetics},
 pages = {1572-1573},
 id = {21d62f77-336d-3213-9acb-dd2182056da8},
 created = {2022-09-23T05:26:06.170Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-09-23T05:26:06.170Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9887198},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In the framework of modern electromagnetic (EM) education, a showcase of the most recent advances in the development of E-XAM, an online examination and self-assessment web platform created by the teaching staff of the ELEDIA Research Center of the University of Trento, Italy, is provided.},
 bibtype = {inproceedings},
 author = {Polo, Alessandro and Anselmi, Nicola and Azaro, Renzo and Oliveri, Giacomo and Poli, Lorenzo and Rocca, Paolo and Salucci, Marco and Ahmadi, Hanen and Huang, Jin and Li, Peng and Li, Maokun and Goudos, Sotirios K and Yang, Shiwen and Massa, Andrea},
 doi = {10.1109/AP-S/USNC-URSI47032.2022.9887198},
 booktitle = {2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI)}
}

In the framework of modern electromagnetic (EM) education, a showcase of the most recent advances in the development of E-XAM, an online examination and self-assessment web platform created by the teaching staff of the ELEDIA Research Center of the University of Trento, Italy, is provided.

@article{
 title = {Design of Antennas through Artificial Intelligence: State-of-the-Art and Challenges},
 type = {article},
 year = {2022},
 pages = {96-102},
 volume = {60},
 id = {9ade5bd5-781e-3dfc-abc9-9de20f1e7418},
 created = {2022-09-27T06:14:06.234Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-12-13T09:03:37.161Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9903377},
 source_type = {article},
 private_publication = {false},
 abstract = {Antenna is a critical part of the RF front end of a communication system. In this study, we present some of the major applications of artificial intelligence (AI) to antenna design. We review the previous research and applications of several AI techniques such as evolutionary algorithms,machine learning, and knowledge representation ontologies. Applications may vary from antenna design to antenna features evaluation in a research field, which is rapidly growing. Finally, we summarize the challenges of new AI techniques in antenna design based on the current state-of-the-art and predict its future research directions.},
 bibtype = {article},
 author = {Goudos, Sotirios K and Diamantoulakis, Panagiotis D and Matin, Mohammad A and Sarigiannidis, Panagiotis and Wan, Shaohua and Karagiannidis, George K},
 doi = {10.1109/MCOM.006.2200124},
 journal = {IEEE Communications Magazine},
 number = {12}
}

Antenna is a critical part of the RF front end of a communication system. In this study, we present some of the major applications of artificial intelligence (AI) to antenna design. We review the previous research and applications of several AI techniques such as evolutionary algorithms,machine learning, and knowledge representation ontologies. Applications may vary from antenna design to antenna features evaluation in a research field, which is rapidly growing. Finally, we summarize the challenges of new AI techniques in antenna design based on the current state-of-the-art and predict its future research directions.

@inproceedings{
 title = {Detection of Macrolepiota Procera Mushrooms Using Machine Learning},
 type = {inproceedings},
 year = {2022},
 pages = {74-78},
 id = {b6b39c27-d749-3af7-b46e-8ead2e99fbb5},
 created = {2022-10-26T19:55:08.423Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-10-26T19:55:08.423Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9916046},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The overpopulation of the latest centuries and recent technological advancements in the primary sector increased demand for improved productivity and product quality in agricultural activities. Modern customers value eco-friendly activities and sustainable consumption. Thus they choose foods with high concentrations of nutritious ingredients. Machine learning algorithms enable the implementation of numerous potential solutions in precision agriculture in conjunction with new potent mechanisms. One algorithm that offers high-precision real-time object identifications is the YOLOv5 (You Only Look Once). Furthermore, to improve the resilience of precision agriculture, this work presents experimental findings from the machine learning algorithm (Yolov5) on a unique dataset based on mushroom crops, such as Macrolepiota Procera species.},
 bibtype = {inproceedings},
 author = {Chaschatzis, Christos and Karaiskou, Chrysoula and Goudos, Sotirios K and Psannis, Konstantinos E and Sarigiannidis, Panagiotis},
 doi = {10.1109/WSCE56210.2022.9916046},
 booktitle = {2022 5th World Symposium on Communication Engineering (WSCE)}
}

The overpopulation of the latest centuries and recent technological advancements in the primary sector increased demand for improved productivity and product quality in agricultural activities. Modern customers value eco-friendly activities and sustainable consumption. Thus they choose foods with high concentrations of nutritious ingredients. Machine learning algorithms enable the implementation of numerous potential solutions in precision agriculture in conjunction with new potent mechanisms. One algorithm that offers high-precision real-time object identifications is the YOLOv5 (You Only Look Once). Furthermore, to improve the resilience of precision agriculture, this work presents experimental findings from the machine learning algorithm (Yolov5) on a unique dataset based on mushroom crops, such as Macrolepiota Procera species.

@inproceedings{
 title = {5G-Enabled NetApp for Predictive Maintenance in Critical Infrastructures},
 type = {inproceedings},
 year = {2022},
 pages = {129-132},
 id = {4e638a9f-fc1a-341e-9578-2cda833df620},
 created = {2022-10-26T19:55:08.432Z},
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 last_modified = {2022-10-26T19:55:08.432Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9916037},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Predictive Maintenance in critical infrastructure is a fundamental tool for predicting a failure in advance and for avoiding catastrophic equipment damage that can be prevented and the time-consuming repair scheduling can be executed in time. Artificial Intelligence (AI) based predictive maintenance utilises intelligent data for accurate predictions in order to make immediate interventions on critical assets. In this paper, we propose a 5G-enabled Network Application (NetApp) for predictive maintenance in energy-related critical infrastructures. The proposed NetApp consists of several containerised components responsible for retrieving time-series operational data from a power plant and detecting potential outliers/anomalies regarding the operation of energy generators. For the anomaly detection process, an autoencoder is used. The evaluation results demonstrate the efficiency of the proposed NetApp.},
 bibtype = {inproceedings},
 author = {Giannakidou, Sofia and Radoglou-Grammatikis, Panagiotis and Koussouris, Sotirios and Pertselakis, Minas and Kanakaris, Nikolaos and Lekidis, Alexios and Kaltakis, Konstantinos and Koidou, Maria P and Metallidou, Chrysi and Psannis, Konstantinos E and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/WSCE56210.2022.9916037},
 booktitle = {2022 5th World Symposium on Communication Engineering (WSCE)}
}

Predictive Maintenance in critical infrastructure is a fundamental tool for predicting a failure in advance and for avoiding catastrophic equipment damage that can be prevented and the time-consuming repair scheduling can be executed in time. Artificial Intelligence (AI) based predictive maintenance utilises intelligent data for accurate predictions in order to make immediate interventions on critical assets. In this paper, we propose a 5G-enabled Network Application (NetApp) for predictive maintenance in energy-related critical infrastructures. The proposed NetApp consists of several containerised components responsible for retrieving time-series operational data from a power plant and detecting potential outliers/anomalies regarding the operation of energy generators. For the anomaly detection process, an autoencoder is used. The evaluation results demonstrate the efficiency of the proposed NetApp.

@inproceedings{
 title = {Artificial Intelligence of Things; Remote Robot System Interacts with Humans and Vice Versa During Pandemic},
 type = {inproceedings},
 year = {2022},
 pages = {79-83},
 id = {1d27e6dd-0dc4-3326-a8ad-4ae080f5e8ff},
 created = {2022-10-26T19:55:08.602Z},
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 last_modified = {2022-10-26T19:55:08.602Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9916048},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Nowadays., the advancement of artificial intelligence has led to the application of robotic systems in the industry, especially in the hotel industry, with a view to providing intelligent, automated and luxury services. At the same time, the knowledge gained from the Covid19 pandemic outbreak that convulses the world community, highlights the issue of sustainability in the hotel industry, solved by utilizing artificial intelligence achievements, remote robot systems, so as to guarantee reliability and security of a hotel's functionality, by providing not only convenient accommodation to guests, but safety, as well. In this paper, we focus on the development of a remote robot system, utilizing the Internet of Things, that has various kinds of sensors and cameras. Both the owners of the hotel and the guests can collaborate with the robot efficiently and accurately, since the robot is able to react with them. Specifically, the developed robot is able to serve clients, by providing them with hotel supplies and by giving them any requested information. In return, the guests are requested to give feedback to the robot upon check out. In addition, the robot browses throughout the hotel to inspect the normal and efficient functionality of all technical systems. The developed robot is also a Covid19 inspector, since it inspects whether one's pandemic measures are applied among guests in public areas and in case of a patient, the robot detects people connected to the patient, isolates the patient and gives medical care, food and supplies, so as to prevent humans from closely contacting the patient.},
 bibtype = {inproceedings},
 author = {Metallidou, Chrysi and Psannis, Kostas E and Sarigiannidis, Panagiotis and Michalas, Angelos and Vergados, Dimitrios D and Goudos, Sotirios},
 doi = {10.1109/WSCE56210.2022.9916048},
 booktitle = {2022 5th World Symposium on Communication Engineering (WSCE)}
}

Nowadays., the advancement of artificial intelligence has led to the application of robotic systems in the industry, especially in the hotel industry, with a view to providing intelligent, automated and luxury services. At the same time, the knowledge gained from the Covid19 pandemic outbreak that convulses the world community, highlights the issue of sustainability in the hotel industry, solved by utilizing artificial intelligence achievements, remote robot systems, so as to guarantee reliability and security of a hotel's functionality, by providing not only convenient accommodation to guests, but safety, as well. In this paper, we focus on the development of a remote robot system, utilizing the Internet of Things, that has various kinds of sensors and cameras. Both the owners of the hotel and the guests can collaborate with the robot efficiently and accurately, since the robot is able to react with them. Specifically, the developed robot is able to serve clients, by providing them with hotel supplies and by giving them any requested information. In return, the guests are requested to give feedback to the robot upon check out. In addition, the robot browses throughout the hotel to inspect the normal and efficient functionality of all technical systems. The developed robot is also a Covid19 inspector, since it inspects whether one's pandemic measures are applied among guests in public areas and in case of a patient, the robot detects people connected to the patient, isolates the patient and gives medical care, food and supplies, so as to prevent humans from closely contacting the patient.

@inproceedings{
 title = {Towards Illumination-aware Visible Light Positioning Network Planning},
 type = {inproceedings},
 year = {2022},
 pages = {1-8},
 id = {8a269d97-182e-3bcb-951c-0ee103b5e7c9},
 created = {2022-10-27T15:20:22.899Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-10-27T15:20:22.899Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9918127},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {A Visible Light Positioning (VLP) network planner holds tremendous economic potential in that it permits designing a roll-out within given cost, illuminance and accuracy bounds. In this manuscript, the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm is applied to simultaneously optimise a roll-out's maintained illuminance and positioning error, by varying the placement of the VLP-enabled LED transmitters. With simulations that differ in positioning and/or environment parameters, the important illuminance-positioning trade-off is revealed. The corresponding Pareto fronts and LED arrangements are studied. Guidelines regarding where to place the LEDs and which LEDs to select for positioning are provided.},
 bibtype = {inproceedings},
 author = {Bastiaens, Sander and Goudos, Sotirios and Joseph, Wout and Plets, David},
 doi = {10.1109/IPIN54987.2022.9918127},
 booktitle = {2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN)}
}

A Visible Light Positioning (VLP) network planner holds tremendous economic potential in that it permits designing a roll-out within given cost, illuminance and accuracy bounds. In this manuscript, the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm is applied to simultaneously optimise a roll-out's maintained illuminance and positioning error, by varying the placement of the VLP-enabled LED transmitters. With simulations that differ in positioning and/or environment parameters, the important illuminance-positioning trade-off is revealed. The corresponding Pareto fronts and LED arrangements are studied. Guidelines regarding where to place the LEDs and which LEDs to select for positioning are provided.

@inproceedings{
 title = {Efficient Peer-to-Peer Unicasting for VANET Architectures via Enhanced Monolithic Protocols},
 type = {inproceedings},
 year = {2022},
 keywords = {Protocols;Processor scheduling;Social networking (,Real Time Communications},
 pages = {1-8},
 id = {11787134-f740-392c-80e6-63b6f66e4fa4},
 created = {2022-11-03T08:18:40.656Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-11-03T08:18:40.656Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9932897},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {With the advent of vehicular networks and the corresponding requirements, developers are faced with new challenges associated with fundamental protocol attributes and capabilities. In our work, we consider ESP-NOW: a connectionless WiFi communication protocol developed by Espressif and featuring short packet (up to 250 bytes) transmission. It is different from more traditional WiFi protocols, as the upper five layers of the Open Systems Interconnection (OSI) stack are simplified to a single monolithic layer. The data does not need to travel through all the OSI-or Transmission Control Protocol (TCP)-specific layers, which measurably reduces over-head, processing delay all while increasing system responsiveness. The presented work targets the considerable research gap in regards to this protocol and constitutes an attempt to dissect it and provide experimental results, which prove to be promising for highly mobile clusters. Relevant developments find great applicability in ad hoc and vehicular communications, where real-time connectivity and sufficient coverage are pivotal in supporting reliable networking. In this paper, we also investigate the usage of a modified 802.11 standard to enable long-range and low-power interfacing amongst networked vehicular nodes.},
 bibtype = {inproceedings},
 author = {Amponis, George and Lagkas, Thomas and Karampatzakis, Dimitris and Radoglou-Grammatikis, Panagiotis and Argyriou, Vasileios and Moscholios, Ioannis and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/SEEDA-CECNSM57760.2022.9932897},
 booktitle = {2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)}
}

With the advent of vehicular networks and the corresponding requirements, developers are faced with new challenges associated with fundamental protocol attributes and capabilities. In our work, we consider ESP-NOW: a connectionless WiFi communication protocol developed by Espressif and featuring short packet (up to 250 bytes) transmission. It is different from more traditional WiFi protocols, as the upper five layers of the Open Systems Interconnection (OSI) stack are simplified to a single monolithic layer. The data does not need to travel through all the OSI-or Transmission Control Protocol (TCP)-specific layers, which measurably reduces over-head, processing delay all while increasing system responsiveness. The presented work targets the considerable research gap in regards to this protocol and constitutes an attempt to dissect it and provide experimental results, which prove to be promising for highly mobile clusters. Relevant developments find great applicability in ad hoc and vehicular communications, where real-time connectivity and sufficient coverage are pivotal in supporting reliable networking. In this paper, we also investigate the usage of a modified 802.11 standard to enable long-range and low-power interfacing amongst networked vehicular nodes.

@inproceedings{
 title = {Visible Light Positioning: A Machine Learning Approach},
 type = {inproceedings},
 year = {2022},
 keywords = {Radio frequency;Social networking (online);Two dim},
 pages = {1-5},
 id = {449f0aca-60e2-3ab3-9150-d52b765b3e80},
 created = {2022-11-03T08:18:41.079Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-11-03T08:18:41.079Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9932981},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Visible light positioning (VLP) systems have experienced substantial revolutionary progress over the past year because they can offer great positioning accuracy without needing any additional infrastructure, as conventional radio-frequency (RF)-based systems. Received signal strength (RSS)-based VLP systems are a promising approach to many indoor positioning estimation problems, but still suffer from difficulty in providing high accuracy and reliability. A potential solution to these challenges is to combine VLP systems, and machine learning (ML) approaches to enhance the position prediction accuracy in two-dimensional (2-D) spaces, or more complex problems. In this paper, we propose a ML approach to accurately predict the 2-D indoor position of a mobile receiver (eg. an automated guided vehicles-AGV), based on the measured RSS values of 4 photodiodes (PDs) forming a star architecture. We examine and evaluate the performance of different ML learners applied to the above-described problem. The proposed ML and Neural Network (NN) methods exhibit great accuracy results in predicting the 2-D coordinates of a PD-based receiver.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios and Plets, David and Joseph, Wout and Goudos, Sotirios K},
 doi = {10.1109/SEEDA-CECNSM57760.2022.9932981},
 booktitle = {2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)}
}

Visible light positioning (VLP) systems have experienced substantial revolutionary progress over the past year because they can offer great positioning accuracy without needing any additional infrastructure, as conventional radio-frequency (RF)-based systems. Received signal strength (RSS)-based VLP systems are a promising approach to many indoor positioning estimation problems, but still suffer from difficulty in providing high accuracy and reliability. A potential solution to these challenges is to combine VLP systems, and machine learning (ML) approaches to enhance the position prediction accuracy in two-dimensional (2-D) spaces, or more complex problems. In this paper, we propose a ML approach to accurately predict the 2-D indoor position of a mobile receiver (eg. an automated guided vehicles-AGV), based on the measured RSS values of 4 photodiodes (PDs) forming a star architecture. We examine and evaluate the performance of different ML learners applied to the above-described problem. The proposed ML and Neural Network (NN) methods exhibit great accuracy results in predicting the 2-D coordinates of a PD-based receiver.

@article{
 title = {Enhancing the robustness of object detection via 6G vehicular edge computing},
 type = {article},
 year = {2022},
 keywords = {6G,Feature fusion,Model compression,Model deployment,Object detection,Vehicular edge computing},
 pages = {923-931},
 volume = {8},
 websites = {https://www.sciencedirect.com/science/article/pii/S235286482200222X},
 id = {57bcd283-0a53-32b8-975d-fa232b9cca9a},
 created = {2022-11-12T15:18:12.089Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-03-09T16:19:40.004Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {CHEN2022},
 source_type = {article},
 private_publication = {false},
 abstract = {Academic and industrial communities have been paying significant attention to the 6th Generation (6G) wireless communication systems after the commercial deployment of 5G cellular communications. Among the emerging technologies, Vehicular Edge Computing (VEC) can provide essential assurance for the robustness of Artificial Intelligence (AI) algorithms to be used in the 6G systems. Therefore, in this paper, a strategy for enhancing the robustness of AI model deployment using 6G-VEC is proposed, taking the object detection task as an example. This strategy includes two stages: model stabilization and model adaptation. In the former, the state-of-the-art methods are appended to the model to improve its robustness. In the latter, two targeted compression methods are implemented, namely model parameter pruning and knowledge distillation, which result in a trade-off between model performance and runtime resources. Numerical results indicate that the proposed strategy can be smoothly deployed in the onboard edge terminals, where the introduced trade-off outperforms the other strategies available.},
 bibtype = {article},
 author = {Chen, Chen and Yao, Guorun and Wang, Chenyu and Goudos, Sotirios and Wan, Shaohua},
 doi = {https://doi.org/10.1016/j.dcan.2022.10.013},
 journal = {Digital Communications and Networks},
 number = {6}
}

Academic and industrial communities have been paying significant attention to the 6th Generation (6G) wireless communication systems after the commercial deployment of 5G cellular communications. Among the emerging technologies, Vehicular Edge Computing (VEC) can provide essential assurance for the robustness of Artificial Intelligence (AI) algorithms to be used in the 6G systems. Therefore, in this paper, a strategy for enhancing the robustness of AI model deployment using 6G-VEC is proposed, taking the object detection task as an example. This strategy includes two stages: model stabilization and model adaptation. In the former, the state-of-the-art methods are appended to the model to improve its robustness. In the latter, two targeted compression methods are implemented, namely model parameter pruning and knowledge distillation, which result in a trade-off between model performance and runtime resources. Numerical results indicate that the proposed strategy can be smoothly deployed in the onboard edge terminals, where the introduced trade-off outperforms the other strategies available.

@inproceedings{
 title = {Path Loss Prediction Modelling for Next-generation Internet-of-Things Applications Using Different Boosting Machine Learning Methods},
 type = {inproceedings},
 year = {2022},
 pages = {1-4},
 id = {bab5d79d-83fc-38f7-9371-352da9f5941d},
 created = {2022-12-15T16:46:56.437Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-12-15T16:46:56.437Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9976383},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Wireless channel propagation characteristics are crucial for wireless network systems. The accuracy of the path loss (PL) prediction determines the quality of the received signal and optimization of wireless communication networks.In this paper, we apply and compare various machine learning (ML) boosting methods for the prediction of path loss in cellular communications using a flying base station (FBS). We use a ray tracing technique to obtain the dataset for the training process of the models. The work at hand generates prediction models, based on five different boosting ML learners to accurately predict the path loss of an unmanned aerial vehicle (UAV). The proposed approach exhibits great accuracy and efficiency in predicting the path loss.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios P and Athanasiadou, Georgia and Sarigiannidis, Panagiotis and Tsoulos, George V and Goudos, Sotirios K},
 doi = {10.1109/PACET56979.2022.9976383},
 booktitle = {2022 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

Wireless channel propagation characteristics are crucial for wireless network systems. The accuracy of the path loss (PL) prediction determines the quality of the received signal and optimization of wireless communication networks.In this paper, we apply and compare various machine learning (ML) boosting methods for the prediction of path loss in cellular communications using a flying base station (FBS). We use a ray tracing technique to obtain the dataset for the training process of the models. The work at hand generates prediction models, based on five different boosting ML learners to accurately predict the path loss of an unmanned aerial vehicle (UAV). The proposed approach exhibits great accuracy and efficiency in predicting the path loss.

@inproceedings{
 title = {Towards Securing Next-Generation Networks: Attacking 5G Core/RAN Testbed},
 type = {inproceedings},
 year = {2022},
 pages = {1-4},
 id = {6bbf7ce4-2276-3a2f-9534-43507d7e7a73},
 created = {2022-12-15T16:47:15.012Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-12-15T16:47:15.012Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9976365},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {As the networking and communications landscape moves towards 5G and an increasing number of users are already accessing the Internet over 5G systems at an increasing pace, security issues rise and the corresponding vulnerabilities are in need of being addressed. The work presented in this paper constitutes an attempt at addressing the issue of training defenders capable of tackling cyberattacks and detection systems capable of timely notifying of security events. The key contribution of this paper is the proposal of a fully containerized testbed, incorporating a 5G cellular core, a radio access network (RAN), a set of potentially vulnerable hosts, and the appropriate entry points as interfaces. Attackers and defenders alike, can perform attacks or implement defensive measures correspondingly, without needing to exit the established sandbox. The developed testbed and emulation framework is envisaged to pave the path towards facilitating the generation of realistic datasets containing malicious traffic captured over 5G tunnels for enhancing the security of next generation networks.},
 bibtype = {inproceedings},
 author = {Amponis, George and Radoglou-Grammatikis, Panagiotis and Lagkas, Thomas and Ouzounidis, Savvas and Zevgara, Maria and Moscholios, Ioannis and Goudos, Sotirios and Sarigiannidis, Panagiotis},
 doi = {10.1109/PACET56979.2022.9976365},
 booktitle = {2022 Panhellenic Conference on Electronics & Telecommunications (PACET)}
}

As the networking and communications landscape moves towards 5G and an increasing number of users are already accessing the Internet over 5G systems at an increasing pace, security issues rise and the corresponding vulnerabilities are in need of being addressed. The work presented in this paper constitutes an attempt at addressing the issue of training defenders capable of tackling cyberattacks and detection systems capable of timely notifying of security events. The key contribution of this paper is the proposal of a fully containerized testbed, incorporating a 5G cellular core, a radio access network (RAN), a set of potentially vulnerable hosts, and the appropriate entry points as interfaces. Attackers and defenders alike, can perform attacks or implement defensive measures correspondingly, without needing to exit the established sandbox. The developed testbed and emulation framework is envisaged to pave the path towards facilitating the generation of realistic datasets containing malicious traffic captured over 5G tunnels for enhancing the security of next generation networks.

@inproceedings{
 title = {Radio Frequency Energy Harvesting System and the Utilization of Blockchain Technologies in Agriculture},
 type = {inproceedings},
 year = {2022},
 pages = {100 – 105},
 volume = {3293},
 id = {e5da8b9a-7e77-3bd8-a78b-826ff13ffc59},
 created = {2022-12-20T18:28:54.180Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-12-20T18:28:54.180Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Krystallidou2022100},
 source_type = {conference},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Krystallidou, Evdokia and Boursianis, Achilles and Diamantoulakis, Panagiotis and Goudos, Sotirios and Karagiannidis, George and Siachamis, Giorgos and Stavropoulos, Georgios and Ioannidis, Dimosthenis and Tzovaras, Dimitrios},
 booktitle = {CEUR Workshop Proceedings}
}

@inproceedings{
 title = {Patch Antenna Design using Artificial Intelligence Methods for 4G/5G Applications},
 type = {inproceedings},
 year = {2022},
 pages = {497-500},
 id = {e5eed56a-3208-3d01-abea-a8d1e3e54a75},
 created = {2023-01-21T08:16:30.213Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-01-21T08:16:30.213Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10014971},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The advent of fifth generation wireless communications (5G), highlights the need for new priorities in research. Especially, the growing mobile networks require abilities for mas-sive connectivity, advanced security, increased network capacity and extremely low-latency. Antennas play a crucial part of this ecosystem, thus, their design is a challenging task. In this work, a Boundary - Seeking Generative Adversarial Network is trained to serve as a surrogate model for the design of a patch antenna with random slots and two operating frequencies at 2.6 GHz and 3.5 GHz, making it suitable for 4G/5G applications. The outcome of the trained model is used as an initial population for further op-timization using the biogeography-based optimization algorithm. The final design achieves $S_11=-37$ dB and $S_11=-33$ dB at 2.6 GHz and 3.5 GHz respectively.},
 bibtype = {inproceedings},
 author = {Iliadis, Lazaros Alexios and Zaharis, Zaharias D and Sotiroudis, Sotirios P and Sarigiannidis, Panagiotis and Christodoulou, Christos and Goudos, Sotirios K},
 doi = {10.1109/WPMC55625.2022.10014971},
 booktitle = {2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC)}
}

The advent of fifth generation wireless communications (5G), highlights the need for new priorities in research. Especially, the growing mobile networks require abilities for mas-sive connectivity, advanced security, increased network capacity and extremely low-latency. Antennas play a crucial part of this ecosystem, thus, their design is a challenging task. In this work, a Boundary - Seeking Generative Adversarial Network is trained to serve as a surrogate model for the design of a patch antenna with random slots and two operating frequencies at 2.6 GHz and 3.5 GHz, making it suitable for 4G/5G applications. The outcome of the trained model is used as an initial population for further op-timization using the biogeography-based optimization algorithm. The final design achieves $S_11=-37$ dB and $S_11=-33$ dB at 2.6 GHz and 3.5 GHz respectively.

@article{
 title = {An Enhanced and Secure Cloud Infrastructure for e-Health Data Transmission},
 type = {article},
 year = {2021},
 keywords = {Cloud model infrastructure,Cloud security,Layered cloud architecture,Mathematical model,Virtualization,e-Health},
 pages = {109-127},
 volume = {117},
 id = {c20fbb10-376f-3ae7-af04-fbf2833c2880},
 created = {2020-02-29T16:57:43.214Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.470Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Memos2019},
 private_publication = {false},
 abstract = {The daily rapid malware growth and spread has enforced the security community of antivirus companies to introduce cloud computing technology to their existing protection methods so as to be able to deal with efficiently the active malware threats. A new hybrid security model, based on cloud computing, should be developed to offer optimized protection to the connected users. In this research, we describe our proposed cloud infrastructure and analyze it with mathematical models to export significant diagrams about various metrics. Our cloud model architecture consists of four layers: the master cloud server, the slave servers, the virtual subservers and the users connected to the cloud. Experimental results demonstrate that our proposed layered cloud architecture verifies the trust of its implementation and establishment, due to the fact that it makes the current architecture more lightweight, efficient and secure for e-health data transmission.},
 bibtype = {article},
 author = {Memos, Vasileios A. and Psannis, Kostas E. and Goudos, Sotirios K. and Kyriazakos, Sofoklis},
 doi = {10.1007/s11277-019-06874-1},
 journal = {Wireless Personal Communications},
 number = {1}
}

The daily rapid malware growth and spread has enforced the security community of antivirus companies to introduce cloud computing technology to their existing protection methods so as to be able to deal with efficiently the active malware threats. A new hybrid security model, based on cloud computing, should be developed to offer optimized protection to the connected users. In this research, we describe our proposed cloud infrastructure and analyze it with mathematical models to export significant diagrams about various metrics. Our cloud model architecture consists of four layers: the master cloud server, the slave servers, the virtual subservers and the users connected to the cloud. Experimental results demonstrate that our proposed layered cloud architecture verifies the trust of its implementation and establishment, due to the fact that it makes the current architecture more lightweight, efficient and secure for e-health data transmission.

@article{
 title = {Multi-object tracking by mutual supervision of CNN and particle filter},
 type = {article},
 year = {2021},
 keywords = {Intelligent transportation systems,Multi-object tracking,Neural networks,Object detection,Particle filters},
 pages = {979-988},
 volume = {25},
 id = {5ad7bec1-1808-3700-9389-9d3919e40da2},
 created = {2020-02-29T16:57:43.783Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.349Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Xia2019},
 private_publication = {false},
 abstract = {In the multi-object tracking process, a long-term tracking algorithm for traffic scene based on deep learning is proposed to handle several challenging problems, such as the complex variation of background illumination, change of pixel due to partial occlusion, cumulative error and the short-term disappearance of the target. Firstly, we train a CNN to identify and determine the target bounding box in a traffic scene. Secondly, we use a particle filter (PF) as the tracker to implement the preliminary multi-object tracking. Finally, the multi-object tracking trajectory then is generated by the mutual supervision of the PF tracker and CNN detector. In order to evaluate the experimental results, we use the forward-backward (FB) error of our tracker at a certain moment. The experimental results show that the method can track single and multi-objects in long-term tracking in real-time. For the situation of target disappearance and reappearance, the proposed algorithm can also recover its long-term tracking.},
 bibtype = {article},
 author = {Xia, Yu and Qu, Shiru and Goudos, Sotirios and Bai, Yu and Wan, Shaohua},
 doi = {10.1007/s00779-019-01278-1},
 journal = {Personal and Ubiquitous Computing},
 number = {6}
}

In the multi-object tracking process, a long-term tracking algorithm for traffic scene based on deep learning is proposed to handle several challenging problems, such as the complex variation of background illumination, change of pixel due to partial occlusion, cumulative error and the short-term disappearance of the target. Firstly, we train a CNN to identify and determine the target bounding box in a traffic scene. Secondly, we use a particle filter (PF) as the tracker to implement the preliminary multi-object tracking. Finally, the multi-object tracking trajectory then is generated by the mutual supervision of the PF tracker and CNN detector. In order to evaluate the experimental results, we use the forward-backward (FB) error of our tracker at a certain moment. The experimental results show that the method can track single and multi-objects in long-term tracking in real-time. For the situation of target disappearance and reappearance, the proposed algorithm can also recover its long-term tracking.

@article{
 title = {Smart Irrigation System for Precision Agriculture - The AREThOU5A IoT Platform},
 type = {article},
 year = {2021},
 keywords = {IoT technology,precision agriculture,radio frequency energy harvesting,smart irrigation},
 pages = {17539-17547},
 volume = {21},
 id = {33809ee4-e959-3c1a-9909-fa1f3234f8c0},
 created = {2020-10-30T21:19:07.417Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.237Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2020},
 source_type = {ARTICLE},
 private_publication = {false},
 abstract = {Agriculture 4.0, as the future of farming technology, includes several key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. In this paper, we present in detail the subsystems and the architecture of an intelligent irrigation system for precision agriculture, the AREThOU5A IoT platform. We describe the operation of the IoT node that is utilized in the platform. Moreover, we apply the radiofrequency energy harvesting technique to the presented IoT platform, as an alternative technique to deliver power to the IoT node of the platform. To this end, we fabricate and validate a rectenna module for radiofrequency energy harvesting. Experimental results of the fabricated rectenna exhibit a satisfactory performance as a harvester of ambient sources in an outdoor environment.},
 bibtype = {article},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Gotsis, Antonis and Wan, Shaohua and Sarigiannidis, Panagiotis and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/JSEN.2020.3033526},
 journal = {IEEE Sensors Journal},
 number = {16}
}

Agriculture 4.0, as the future of farming technology, includes several key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. In this paper, we present in detail the subsystems and the architecture of an intelligent irrigation system for precision agriculture, the AREThOU5A IoT platform. We describe the operation of the IoT node that is utilized in the platform. Moreover, we apply the radiofrequency energy harvesting technique to the presented IoT platform, as an alternative technique to deliver power to the IoT node of the platform. To this end, we fabricate and validate a rectenna module for radiofrequency energy harvesting. Experimental results of the fabricated rectenna exhibit a satisfactory performance as a harvester of ambient sources in an outdoor environment.

@article{
 title = {Multiband Patch Antenna Design Using Nature-Inspired Optimization Method},
 type = {article},
 year = {2021},
 pages = {151-162},
 volume = {2},
 id = {2e880cca-1d3f-3eea-9167-6316cc07c7f7},
 created = {2021-03-06T21:46:42.527Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.036Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9311660},
 source_type = {article},
 private_publication = {false},
 abstract = {Radio frequency energy harvesting has attracted considerable interest as a technique of enabling self-powered wireless networks. This technique faces several challenges, such as the receiving and the rectifying modules of a rectenna system. Multiband antennas provide several comparative advantages against the goal of maximizing the amount of energy harvesting. In this work, we present a multiband microstrip patch antenna with three slits operating in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. A feasible solution of the antenna is obtained by the application of a recently introduced nature-inspired optimization technique, namely the Coyote Optimization Algorithm. The proposed antenna operates satisfactorily in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Measured results of the proposed antenna exhibit an acceptable performance (multiband frequency operation, maximum gain of 3.94 dBi, broadside operation) and demonstrate features of operation, which make it a strong candidate for various RF energy harvesting applications.},
 bibtype = {article},
 author = {Boursianis, A D and Papadopoulou, M S and Pierezan, J and Mariani, V C and Coelho, L S and Sarigiannidis, P and Koulouridis, S and Goudos, S K},
 doi = {10.1109/OJAP.2020.3048495},
 journal = {IEEE Open Journal of Antennas and Propagation}
}

Radio frequency energy harvesting has attracted considerable interest as a technique of enabling self-powered wireless networks. This technique faces several challenges, such as the receiving and the rectifying modules of a rectenna system. Multiband antennas provide several comparative advantages against the goal of maximizing the amount of energy harvesting. In this work, we present a multiband microstrip patch antenna with three slits operating in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. A feasible solution of the antenna is obtained by the application of a recently introduced nature-inspired optimization technique, namely the Coyote Optimization Algorithm. The proposed antenna operates satisfactorily in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Measured results of the proposed antenna exhibit an acceptable performance (multiband frequency operation, maximum gain of 3.94 dBi, broadside operation) and demonstrate features of operation, which make it a strong candidate for various RF energy harvesting applications.

@article{
 title = {Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach},
 type = {article},
 year = {2021},
 pages = {30441-30451},
 volume = {9},
 id = {30b9dfbb-f91b-3cf1-b95b-d259b43ab11f},
 created = {2021-03-06T21:46:42.541Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:54.997Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9354618},
 source_type = {article},
 private_publication = {false},
 abstract = {Tabular data and images have been used from machine learning models as two diverse types of inputs, in order to perform path loss predictions in urban areas. Different types of models are applied on these distinct modes of input information. The work at hand tries to incorporate both modes of input data within a single prediction model. It therefore manipulates and transforms the vectors of tabular data into images. Each feature of the tabular data vector is spread into several pixels, corresponding to the calculated importance of the particular feature. The resulting synthetic images are then fused with images representing selected regions of the area's map. Compound pseudoimages, having channels of both map-based and tabular data-based images, are then being used as inputs for a Convolutional Neural Network (CNN), which predicts the path loss value at a specific point of the area of interest. The results are clearly better than those obtained from models based on a single mode of input data, as well as from the results produced by other bimodal-input approaches. This approach could be applied for path loss prediction in urban environments for several state-of-art wireless networks like 5G and Internet of Things (IoT).},
 bibtype = {article},
 author = {Sotiroudis, S P and Sarigiannidis, P and Goudos, S K and Siakavara, K},
 doi = {10.1109/ACCESS.2021.3059589},
 journal = {IEEE Access}
}

Tabular data and images have been used from machine learning models as two diverse types of inputs, in order to perform path loss predictions in urban areas. Different types of models are applied on these distinct modes of input information. The work at hand tries to incorporate both modes of input data within a single prediction model. It therefore manipulates and transforms the vectors of tabular data into images. Each feature of the tabular data vector is spread into several pixels, corresponding to the calculated importance of the particular feature. The resulting synthetic images are then fused with images representing selected regions of the area's map. Compound pseudoimages, having channels of both map-based and tabular data-based images, are then being used as inputs for a Convolutional Neural Network (CNN), which predicts the path loss value at a specific point of the area of interest. The results are clearly better than those obtained from models based on a single mode of input data, as well as from the results produced by other bimodal-input approaches. This approach could be applied for path loss prediction in urban environments for several state-of-art wireless networks like 5G and Internet of Things (IoT).

@article{
 title = {Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization},
 type = {article},
 year = {2021},
 volume = {9},
 websites = {https://www.mdpi.com/2227-7080/9/2/35},
 id = {41169a1e-cb0d-3731-ad1d-dd48d1e348fe},
 created = {2021-05-11T07:47:00.215Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-05-11T07:48:06.292Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {technologies9020035},
 source_type = {article},
 private_publication = {false},
 abstract = {Nature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. To extend the classical single-objective ALO, this paper proposes four multiobjective ALO (MOALO) approaches using crowding distance, dominance concept for selecting the elite, and tournament selection mechanism with different schemes to select the leader. Numerical results from a multiobjective constrained brushless direct current (DC) motor design problem show that some MOALO approaches present promising performance in terms of Pareto-optimal solutions.},
 bibtype = {article},
 author = {Pierezan, Juliano and Coelho, Leandro dos S and Mariani, Viviana C and Goudos, Sotirios K and Boursianis, Achilles D and Kantartzis, Nikolaos V and Antonopoulos, Christos. S and Nikolaidis, Spiridon},
 doi = {10.3390/technologies9020035},
 journal = {Technologies},
 number = {2}
}

Nature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. To extend the classical single-objective ALO, this paper proposes four multiobjective ALO (MOALO) approaches using crowding distance, dominance concept for selecting the elite, and tournament selection mechanism with different schemes to select the leader. Numerical results from a multiobjective constrained brushless direct current (DC) motor design problem show that some MOALO approaches present promising performance in terms of Pareto-optimal solutions.

@article{
 title = {Designing Smart Electromagnetic Environments for Next-Generation Wireless Communications},
 type = {article},
 year = {2021},
 pages = {213-221},
 volume = {2},
 websites = {https://www.mdpi.com/2673-4001/2/2/14},
 id = {4eb62331-46cf-39ef-baef-bc0c14f23d03},
 created = {2021-05-12T10:38:24.400Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-05-12T10:38:24.400Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {telecom2020014},
 source_type = {article},
 private_publication = {false},
 abstract = {The design of a smart electromagnetic (EM) environment for next-generation wireless communication systems is addressed in this work. The proposed approach aims at synthesizing a desired EM field distribution over a target region, where the receiving terminals are located, through the opportunistic exploitation of the complex scattering interactions between the EM field generated by a reconfigurable primary source and the objects/scatterers present in the environment, which behave as application-driven passive metastructures. The effectiveness and the potentialities of the proposed design methodology are assessed with a proof-of-concept numerical result obtained by means of advanced and reliable simulation tools.},
 bibtype = {article},
 author = {Massa, Andrea and Benoni, Arianna and Da Rù, Pietro and Goudos, Sotirios K and Li, Baozhu and Oliveri, Giacomo and Polo, Alessandro and Rocca, Paolo and Salucci, Marco},
 doi = {10.3390/telecom2020014},
 journal = {Telecom},
 number = {2}
}

The design of a smart electromagnetic (EM) environment for next-generation wireless communication systems is addressed in this work. The proposed approach aims at synthesizing a desired EM field distribution over a target region, where the receiving terminals are located, through the opportunistic exploitation of the complex scattering interactions between the EM field generated by a reconfigurable primary source and the objects/scatterers present in the environment, which behave as application-driven passive metastructures. The effectiveness and the potentialities of the proposed design methodology are assessed with a proof-of-concept numerical result obtained by means of advanced and reliable simulation tools.

@article{
 title = {Triple-Band Single-Layer Rectenna for Outdoor RF Energy Harvesting Applications},
 type = {article},
 year = {2021},
 volume = {21},
 websites = {https://www.mdpi.com/1424-8220/21/10/3460},
 id = {1175a958-8750-3d71-99e2-26a8f9a68d95},
 created = {2021-05-24T06:03:36.140Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-05-24T06:03:36.140Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {s21103460},
 source_type = {article},
 private_publication = {false},
 abstract = {A triple-band single-layer rectenna for outdoor RF energy applications is introduced in this paper. The proposed rectenna operates in the frequency bands of LoRa, GSM-1800, and UMTS-2100 networks. To obtain a triple-band operation, a modified E-shaped patch antenna is used. The receiving module (antenna) of the rectenna system is optimized in terms of its reflection coefficient to match the RF-to-DC rectifier. The final geometry of the proposed antenna is derived by the application of the Moth Search Algorithm and a commercial electromagnetic solver. The impedance matching network of the proposed system is obtained based on a three-step process, including the minimization of the reflection coefficient versus frequency, as well as the minimization of the reflection coefficient variations and the maximization of the DC output voltage versus RF input power. The proposed RF-to-DC rectifier is designed based on the Greinacher topology. The designed rectenna is fabricated on a single layer of FR-4 substrate. Measured results show that our proposed rectenna can harvest RF energy from outdoor (ambient and dedicated) sources with an efficiency of greater than 52%.},
 bibtype = {article},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Koulouridis, Stavros and Rocca, Paolo and Georgiadis, Apostolos and Tentzeris, Manos M and Goudos, Sotirios K},
 doi = {10.3390/s21103460},
 journal = {Sensors},
 number = {10}
}

A triple-band single-layer rectenna for outdoor RF energy applications is introduced in this paper. The proposed rectenna operates in the frequency bands of LoRa, GSM-1800, and UMTS-2100 networks. To obtain a triple-band operation, a modified E-shaped patch antenna is used. The receiving module (antenna) of the rectenna system is optimized in terms of its reflection coefficient to match the RF-to-DC rectifier. The final geometry of the proposed antenna is derived by the application of the Moth Search Algorithm and a commercial electromagnetic solver. The impedance matching network of the proposed system is obtained based on a three-step process, including the minimization of the reflection coefficient versus frequency, as well as the minimization of the reflection coefficient variations and the maximization of the DC output voltage versus RF input power. The proposed RF-to-DC rectifier is designed based on the Greinacher topology. The designed rectenna is fabricated on a single layer of FR-4 substrate. Measured results show that our proposed rectenna can harvest RF energy from outdoor (ambient and dedicated) sources with an efficiency of greater than 52%.

@article{
 title = {Chaotic Jaya Approaches to Solving Electromagnetic Optimization Benchmark Problems},
 type = {article},
 year = {2021},
 pages = {222-231},
 volume = {2},
 websites = {https://www.mdpi.com/2673-4001/2/2/15},
 id = {ede5df4b-bd9f-3e30-ba8d-b3b2c90c79b9},
 created = {2021-06-02T19:26:42.020Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-06-02T19:26:42.020Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {telecom2020015},
 source_type = {article},
 private_publication = {false},
 abstract = {The Jaya optimization algorithm is a simple, fast, robust, and powerful population-based stochastic metaheuristic that in recent years has been successfully applied in a variety of global optimization problems in various application fields. The essential idea of the Jaya algorithm is that the searching agents try to change their positions toward the best obtained solution by avoiding the worst solution at every generation. The important difference between Jaya and other metaheuristics is that Jaya does not require the tuning of its control, except for the maximum number of iterations and population size parameters. However, like other metaheuristics, Jaya still has the dilemma of an appropriate tradeoff between its exploration and exploitation abilities during the evolution process. To enhance the convergence performance of the standard Jaya algorithm in the continuous domain, chaotic Jaya (CJ) frameworks based on chaotic sequences are proposed in this paper. In order to obtain the performance of the standard Jaya and CJ approaches, tests related to electromagnetic optimization using two different benchmark problems are conducted. These are the Loney’s solenoid benchmark and a brushless direct current (DC) motor benchmark. Both problems are realized to evaluate the effectiveness and convergence rate. The simulation results and comparisons with the standard Jaya algorithm demonstrated that the performance of the CJ approaches based on Chebyshev-type chaotic mapping and logistic mapping can be competitive results in terms of both efficiency and solution quality in electromagnetics optimization.},
 bibtype = {article},
 author = {Coelho, Leandro dos S and Mariani, Viviana C and Goudos, Sotirios K and Boursianis, Achilles D and Kokkinidis, Konstantinos and Kantartzis, Nikolaos V},
 doi = {10.3390/telecom2020015},
 journal = {Telecom},
 number = {2}
}

The Jaya optimization algorithm is a simple, fast, robust, and powerful population-based stochastic metaheuristic that in recent years has been successfully applied in a variety of global optimization problems in various application fields. The essential idea of the Jaya algorithm is that the searching agents try to change their positions toward the best obtained solution by avoiding the worst solution at every generation. The important difference between Jaya and other metaheuristics is that Jaya does not require the tuning of its control, except for the maximum number of iterations and population size parameters. However, like other metaheuristics, Jaya still has the dilemma of an appropriate tradeoff between its exploration and exploitation abilities during the evolution process. To enhance the convergence performance of the standard Jaya algorithm in the continuous domain, chaotic Jaya (CJ) frameworks based on chaotic sequences are proposed in this paper. In order to obtain the performance of the standard Jaya and CJ approaches, tests related to electromagnetic optimization using two different benchmark problems are conducted. These are the Loney’s solenoid benchmark and a brushless direct current (DC) motor benchmark. Both problems are realized to evaluate the effectiveness and convergence rate. The simulation results and comparisons with the standard Jaya algorithm demonstrated that the performance of the CJ approaches based on Chebyshev-type chaotic mapping and logistic mapping can be competitive results in terms of both efficiency and solution quality in electromagnetics optimization.

@article{
 title = {Enhancing Machine Learning Models for Path Loss Prediction Using Image Texture Techniques},
 type = {article},
 year = {2021},
 pages = {1443-1447},
 volume = {20},
 id = {1c519433-0f4d-3fe9-8333-a601230551cc},
 created = {2021-06-08T05:49:54.194Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:54.838Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9446586},
 source_type = {article},
 private_publication = {false},
 abstract = {The performance of machine learning (ML)-based path loss models relies heavily on the data they use at their inputs. Feature engineering is, therefore, essential for the model's success. In this letter, at hand, we extract a new set of input features, based on image texture. The image that we use represents the footprint of the urban built-up area, where the gray scale values of the building blocks are analogue to their heights. We extract texture information by applying the segmentation-based fractal texture analysis algorithm on the orthogonal area that is bounded between the transmitter and the receiver. To the best of our knowledge this is the first time that such a technique is applied to a path loss modeling problem in electromagnetics. The algorithm, thus, delivers a new set of features, based on the image's texture, which eventually reveal the built-up profile of the area. These new features are injected to an already existing feature set. Comparative analysis shows that the addition of texture-based features leads to enhanced predictions, for a diverse set of transmitter heights, ML algorithms, and performance metrics.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios and Siakavara, Katherine and Koudouridis, George and Sarigiannidis, Panagiotis and Goudos, Sotirios},
 doi = {10.1109/LAWP.2021.3086180},
 journal = {IEEE Antennas and Wireless Propagation Letters},
 number = {8}
}

The performance of machine learning (ML)-based path loss models relies heavily on the data they use at their inputs. Feature engineering is, therefore, essential for the model's success. In this letter, at hand, we extract a new set of input features, based on image texture. The image that we use represents the footprint of the urban built-up area, where the gray scale values of the building blocks are analogue to their heights. We extract texture information by applying the segmentation-based fractal texture analysis algorithm on the orthogonal area that is bounded between the transmitter and the receiver. To the best of our knowledge this is the first time that such a technique is applied to a path loss modeling problem in electromagnetics. The algorithm, thus, delivers a new set of features, based on the image's texture, which eventually reveal the built-up profile of the area. These new features are injected to an already existing feature set. Comparative analysis shows that the addition of texture-based features leads to enhanced predictions, for a diverse set of transmitter heights, ML algorithms, and performance metrics.

@book{
 title = {Emerging Evolutionary Algorithms for Antennas and Wireless Communications},
 type = {book},
 year = {2021},
 websites = {https://books.google.gr/books?id=xroJzgEACAAJ},
 publisher = {SciTech Publishing, Incorporated},
 series = {Electromagnetic Waves},
 id = {62f9e369-7654-309c-aca2-f7d9bbe88b2d},
 created = {2021-07-02T06:29:13.488Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:39:28.618Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2021emerging},
 source_type = {book},
 private_publication = {false},
 abstract = {Several evolutionary algorithms (EAs) have emerged in recent decades that mimic the behaviour and evolution of biological entities. EAs are widely used to solve single and multi-objective optimization engineering problems. EAs have also been applied to a variety of microwave components, antenna design, radar design, and wireless communications problems. These techniques, among others, include genetic algorithms (GAs), evolution strategies (ES), particle swarm optimization (PSO), differential evolution (DE), and ant colony optimization (ACO). In addition, new innovative algorithms that are not only biology-based but also physics-based or music-based are also emerging, as are hybrid combinations of EAs. The use of evolutionary algorithms is having an increasing impact on antenna design and wireless communications problems. EAs combined with numerical methods in electromagnetics have obtained significant and successful results. This book aims to present some of the emerging EAs and their variants. Chapter 1 introduces the optimization methods in general and the evolutionary algorithms. Chapter 2 presents briefly some of the most popular evolutionary algorithms, such as particle swarm optimization (PSO), differential evolution (DE), and ant colony optimization (ACO) as well as some emerging ones. Chapter 3 focuses on antenna array synthesis, which constitutes a wide range of antenna design problems. Chapter 4 gives an overview of patch antenna design using evolutionary algorithms. Chapter 5 presents design cases from different microwave structure cases. Chapter 6 discusses on various representative design problems in wireless communications. Chapter 7 deals with design cases for 5G and beyond.},
 bibtype = {book},
 author = {Goudos, S K}
}

Several evolutionary algorithms (EAs) have emerged in recent decades that mimic the behaviour and evolution of biological entities. EAs are widely used to solve single and multi-objective optimization engineering problems. EAs have also been applied to a variety of microwave components, antenna design, radar design, and wireless communications problems. These techniques, among others, include genetic algorithms (GAs), evolution strategies (ES), particle swarm optimization (PSO), differential evolution (DE), and ant colony optimization (ACO). In addition, new innovative algorithms that are not only biology-based but also physics-based or music-based are also emerging, as are hybrid combinations of EAs. The use of evolutionary algorithms is having an increasing impact on antenna design and wireless communications problems. EAs combined with numerical methods in electromagnetics have obtained significant and successful results. This book aims to present some of the emerging EAs and their variants. Chapter 1 introduces the optimization methods in general and the evolutionary algorithms. Chapter 2 presents briefly some of the most popular evolutionary algorithms, such as particle swarm optimization (PSO), differential evolution (DE), and ant colony optimization (ACO) as well as some emerging ones. Chapter 3 focuses on antenna array synthesis, which constitutes a wide range of antenna design problems. Chapter 4 gives an overview of patch antenna design using evolutionary algorithms. Chapter 5 presents design cases from different microwave structure cases. Chapter 6 discusses on various representative design problems in wireless communications. Chapter 7 deals with design cases for 5G and beyond.

@inproceedings{
 title = {Applying One Class Classification for Leak Detection in Noisy Industrial Pipelines},
 type = {inproceedings},
 year = {2021},
 keywords = {acoustic sensors,feature extraction,industrial pipelines,leak detection,machine learning,one class classification},
 pages = {1-4},
 id = {5450b4ab-9ff2-3afd-a98d-651f4196cfab},
 created = {2021-07-29T14:17:13.743Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.207Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493355},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this work, a machine learning approach is proposed for the problem of leak detection in noisy industrial pipelines. The traditional multi-class or binary classification approaches depend on the fact that real training data are required. However, in real pipeline scenarios the data generation for the leak class relies on measurements of artificially generated leaks which are different in nature than actual ones. Also, some pipelines are not equipped with the components to generate these leaks and in some cases, it is difficult to acquire a large and balanced leak dataset. Thus, in this paper, a set of one class classification models are applied that do not require training with real leak data. In this study's case, four one class classification models are trained on a single class representing the pipeline's normal operating noise. Seven time and frequency domain features are extracted from the raw acoustic data acquired by a set of accelerometers. The trained models are then tested on a new dataset containing leak and noise measurements. This dataset is used to evaluate each model's ability to detect leaks as well as the effect that some introduced parameters have on their performance. Overall, high levels of accuracy are exhibited, and all models are able to distinguish between noise and leak data.},
 bibtype = {inproceedings},
 author = {Kampelopoulos, Dimitrios and Kousiopoulos, Georgios Panagiotis and Karagiorgos, Nikolaos and Konstantakos, Vasileios and Goudos, Sotirios and Nikolaidis, Spyridon},
 doi = {10.1109/MOCAST52088.2021.9493355},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

In this work, a machine learning approach is proposed for the problem of leak detection in noisy industrial pipelines. The traditional multi-class or binary classification approaches depend on the fact that real training data are required. However, in real pipeline scenarios the data generation for the leak class relies on measurements of artificially generated leaks which are different in nature than actual ones. Also, some pipelines are not equipped with the components to generate these leaks and in some cases, it is difficult to acquire a large and balanced leak dataset. Thus, in this paper, a set of one class classification models are applied that do not require training with real leak data. In this study's case, four one class classification models are trained on a single class representing the pipeline's normal operating noise. Seven time and frequency domain features are extracted from the raw acoustic data acquired by a set of accelerometers. The trained models are then tested on a new dataset containing leak and noise measurements. This dataset is used to evaluate each model's ability to detect leaks as well as the effect that some introduced parameters have on their performance. Overall, high levels of accuracy are exhibited, and all models are able to distinguish between noise and leak data.

@inproceedings{
 title = {Design of Unit Cells for Intelligent Reflection Surfaces Based on Transparent Materials},
 type = {inproceedings},
 year = {2021},
 keywords = {IRS (reconfigurable intelligent surfaces),ITO,metasurfaces,unit cell},
 pages = {1-4},
 id = {8333bc48-fdcb-39bd-92d0-35550a729463},
 created = {2021-07-29T14:17:13.745Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.183Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493335},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Intelligent reflection surfaces (IRS) facilitate wireless environments by increasing spectrum and energy efficiencies. IRS will be considered a key element in 5G and Beyond cellular networks. IRS design is based on the unit cells. In this paper, we present the design of unit cells based on transparent materials at millimetre-wave frequencies. The transparency of the surface is achieved by using materials such as Indium tin oxide (ITO) and quartz. Simulations have been carried out using CST microwave studio to evaluate the reflection characteristics of the proposed unit cells. Simulations suggest a maximum shift in the reflection phase up to 336° for variation in the dimensions of the unit cell with low reflection losses at 60GHz for 5G and Beyond Wireless Networks.},
 bibtype = {inproceedings},
 author = {Chalkidis, Savvas and Vassos, Evangelos and Boursianis, Achilles D and Feresidis, Alexandros and Goudos, Sotirios K},
 doi = {10.1109/MOCAST52088.2021.9493335},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

Intelligent reflection surfaces (IRS) facilitate wireless environments by increasing spectrum and energy efficiencies. IRS will be considered a key element in 5G and Beyond cellular networks. IRS design is based on the unit cells. In this paper, we present the design of unit cells based on transparent materials at millimetre-wave frequencies. The transparency of the surface is achieved by using materials such as Indium tin oxide (ITO) and quartz. Simulations have been carried out using CST microwave studio to evaluate the reflection characteristics of the proposed unit cells. Simulations suggest a maximum shift in the reflection phase up to 336° for variation in the dimensions of the unit cell with low reflection losses at 60GHz for 5G and Beyond Wireless Networks.

@inproceedings{
 title = {A NB-IoT based platform for smart irrigation in vineyard},
 type = {inproceedings},
 year = {2021},
 keywords = {IoT,NB-IoT,Vineyards,irrigation,sensors},
 pages = {1-4},
 id = {71c26d55-3686-36ee-bcc0-ab9e5ef2b356},
 created = {2021-07-29T14:17:13.797Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.378Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493381},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {A novel prototype NB-IoT-based quasi-smart water management platform for irrigation is proposed. The prototype has been deployed in a vineyard in Peta village, Greece, as part of the AREThOU5A project. An IoT framework for regularly and accurately tracking the status of soil hydration and reporting it to a centralized entity for further processing since water needs are directly related to soil moisture is proposed. The framework is based on specialized IoT hardware that includes low-cost microcontrollers with integrated sensor interfaces and telecommunication modems, open-source applications, open and standardized data transfer protocols, with low capital and operating costs. In the vineyard, an IoT end-node have been placed. Each node: i) collects soil moisture and temperature samples at a depth of 20 cm, ii) is battery-powered and has a battery life of several months on a single charge, and iii) connects to the system back-end via NB-IoT. The sensor measurements from the IoT nodes are forwarded to a cloud-based infrastructure using the Constrained Application Protocol (CoAP)/IPv6 protocol using a public mobile network. Data is maintained on a cloud backend and can be accessed in real-time via dashboards from any Internet-connected individual. In terms of hardware integration, operating solutions, networking and connectivity support, the proposed platform offers numerous novel features.},
 bibtype = {inproceedings},
 author = {Liopa-Tsakalidi, Aglaia and Thomopoulos, Vasileios and Barouchas, Pantelis and Kavga, Angeliki and Boursianis, Achilles D and Goudos, Sotirios K and Kalamaras, Georgios and Gotsis, Antonis and Maliatsos, Konstantinos},
 doi = {10.1109/MOCAST52088.2021.9493381},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

A novel prototype NB-IoT-based quasi-smart water management platform for irrigation is proposed. The prototype has been deployed in a vineyard in Peta village, Greece, as part of the AREThOU5A project. An IoT framework for regularly and accurately tracking the status of soil hydration and reporting it to a centralized entity for further processing since water needs are directly related to soil moisture is proposed. The framework is based on specialized IoT hardware that includes low-cost microcontrollers with integrated sensor interfaces and telecommunication modems, open-source applications, open and standardized data transfer protocols, with low capital and operating costs. In the vineyard, an IoT end-node have been placed. Each node: i) collects soil moisture and temperature samples at a depth of 20 cm, ii) is battery-powered and has a battery life of several months on a single charge, and iii) connects to the system back-end via NB-IoT. The sensor measurements from the IoT nodes are forwarded to a cloud-based infrastructure using the Constrained Application Protocol (CoAP)/IPv6 protocol using a public mobile network. Data is maintained on a cloud backend and can be accessed in real-time via dashboards from any Internet-connected individual. In terms of hardware integration, operating solutions, networking and connectivity support, the proposed platform offers numerous novel features.

@inproceedings{
 title = {Advanced Teaching in Electromagnetics at the ELEDIA Research Center},
 type = {inproceedings},
 year = {2021},
 keywords = {communication systems,electromagnetic (EM) engineering,self-evaluation,teaching},
 pages = {1-3},
 id = {8286c38c-c92c-3198-8053-2cbbda55f22a},
 created = {2021-07-29T14:17:13.893Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.247Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493402},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {An entire long-term educational framework has been designed and implemented by the ELEDIA Research Center to (i) renew the way of teaching electromagnetics (EM) and modern communication systems to future engineers and (ii) increase students' self-confidence and admiration of the applicative and technological aspects of Maxwell's equations. According to authors' expectations and students' feedback, such a training ecosystem will help a computer-naive generation in developing a more natural engineer-oriented thinking mechanism and attitude for continuously adapting to technological advances in EM leading-edge research and industry.},
 bibtype = {inproceedings},
 author = {Polo, Alessandro and Ahmadi, Hanen and Goudos, Sotirios K and Hu, Jun and Huang, Jin and Khan, Moman and Li, Baozhu and Li, Maokun and Oliveri, Giacomo and Rocca, Paolo and Salucci, Marco and Yang, Fan and Yang, Shiwen and Massa, Andrea},
 doi = {10.1109/MOCAST52088.2021.9493402},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

An entire long-term educational framework has been designed and implemented by the ELEDIA Research Center to (i) renew the way of teaching electromagnetics (EM) and modern communication systems to future engineers and (ii) increase students' self-confidence and admiration of the applicative and technological aspects of Maxwell's equations. According to authors' expectations and students' feedback, such a training ecosystem will help a computer-naive generation in developing a more natural engineer-oriented thinking mechanism and attitude for continuously adapting to technological advances in EM leading-edge research and industry.

@inproceedings{
 title = {Dual-Band Frequency Selective Surface Design Using Harris Hawks Optimization},
 type = {inproceedings},
 year = {2021},
 keywords = {Frequency selective surface,Harris Hawk Optimization,RF energy harvesting,dual-slot,optimization method},
 pages = {1-4},
 id = {0b83bdf6-94cf-37ec-837c-f1f35b21e9ab},
 created = {2021-07-29T14:17:13.913Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.207Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493382},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Frequency Selective Surfaces (FSSs) are periodic structures that are designed to reflect, absorb or transmit electromagnetic fields in a variable frequency range. Their performance is strongly dependent on their fundamental structure, i.e. the unit cell. In this paper, we exploit the characteristic of absorption to design a dual-band FSS suitable for indoor RF energy harvesting systems. We combine an optimization technique by utilizing the Harris Hawk Optimization (HHO) algorithm and a high-frequency electromagnetic solver to optimize the geometry of the unit cell and the overall FSS. The proposed system operates in the frequency bands of Wi-Fi 2.4 GHz and Wi-Fi 5 GHz. Numerical results demonstrate that the optimized FSS exhibits quite satisfactory results and makes it a suitable candidate for RF energy harvesting applications.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Salucci, Marco and Koulouridis, Stavros and Georgiadis, Apostolos and Tentzeris, Manos and Goudos, Sotirios K},
 doi = {10.1109/MOCAST52088.2021.9493382},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

Frequency Selective Surfaces (FSSs) are periodic structures that are designed to reflect, absorb or transmit electromagnetic fields in a variable frequency range. Their performance is strongly dependent on their fundamental structure, i.e. the unit cell. In this paper, we exploit the characteristic of absorption to design a dual-band FSS suitable for indoor RF energy harvesting systems. We combine an optimization technique by utilizing the Harris Hawk Optimization (HHO) algorithm and a high-frequency electromagnetic solver to optimize the geometry of the unit cell and the overall FSS. The proposed system operates in the frequency bands of Wi-Fi 2.4 GHz and Wi-Fi 5 GHz. Numerical results demonstrate that the optimized FSS exhibits quite satisfactory results and makes it a suitable candidate for RF energy harvesting applications.

@inproceedings{
 title = {Performance Evaluation of LoRa Networks in an Open Field Cultivation Scenario},
 type = {inproceedings},
 year = {2021},
 keywords = {Data Extraction Rate,Internet of Things (IoT),Long Range (LoRa),Network Energy Consumption,Smart Agriculture},
 pages = {1-5},
 id = {7407cdb8-3c82-399a-9e58-0fe2366f3872},
 created = {2021-07-29T14:17:13.915Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.078Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493416},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The employment of Internet of Things (IoT) technology in agriculture could be beneficial in managing the cultivation production in a highly-customizable way. LoRa (Long Range) is one of the most important technologies in cultivation fields mainly thanks to its ability to provide long-range transmission and low power consumption. In this paper, we evaluate the performance of LoRa networks in an open field cultivation scenario via simulations using FLoRa, an open-source framework in OMNeT++. The number of nodes, the number of gateways, the antenna gain, and the size of the deployment area have a considerable impact on both the data extraction rate and the energy consumption of a LoRa network. Our results show that the optimization of the parameters that affect the performance of a LoRa network could transform traditional agriculture into a new perspective of smart cultivation. Finally, we evaluate the impact of the density and the geometric characteristics of three types of crop (tomatoes, grapes, apples) on the number of intersections that were caused by the insertion of physical objects-obstacles in a LoRa network.},
 bibtype = {inproceedings},
 author = {Griva, Aikaterini and Boursianis, Achilles D and Wan, Shaouha and Sarigiannidis, Panagiotis and Karagiannidis, George and Goudos, Sotirios K},
 doi = {10.1109/MOCAST52088.2021.9493416},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

The employment of Internet of Things (IoT) technology in agriculture could be beneficial in managing the cultivation production in a highly-customizable way. LoRa (Long Range) is one of the most important technologies in cultivation fields mainly thanks to its ability to provide long-range transmission and low power consumption. In this paper, we evaluate the performance of LoRa networks in an open field cultivation scenario via simulations using FLoRa, an open-source framework in OMNeT++. The number of nodes, the number of gateways, the antenna gain, and the size of the deployment area have a considerable impact on both the data extraction rate and the energy consumption of a LoRa network. Our results show that the optimization of the parameters that affect the performance of a LoRa network could transform traditional agriculture into a new perspective of smart cultivation. Finally, we evaluate the impact of the density and the geometric characteristics of three types of crop (tomatoes, grapes, apples) on the number of intersections that were caused by the insertion of physical objects-obstacles in a LoRa network.

@inproceedings{
 title = {Unsupervised Machine Learning in 6G Networks -State-of-the-art and Future Trends},
 type = {inproceedings},
 year = {2021},
 keywords = {6G,Artificial Intelligence,Sixth Generation,Unsupervised Machine Learning,Wireless Communications},
 pages = {1-4},
 id = {f02dff54-9a75-33a1-9063-a50026635b76},
 created = {2021-07-29T14:17:13.919Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.045Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493388},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Wireless communication systems play a very crucial role for business, commercial, health and safety applications. With the commercial deployment of fifth generation (5G), academic and industrial research focuses on the sixth generation (6G) of wireless communication systems. Artificial Intelligence (AI) and especially Machine Learning (ML), will be a key component of 6G systems. Here, we present an up-to-date review of future 6G wireless systems and the role of unsupervised ML techniques in them.},
 bibtype = {inproceedings},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios and Sarigiannidis, Panagiotis and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.1109/MOCAST52088.2021.9493388},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

Wireless communication systems play a very crucial role for business, commercial, health and safety applications. With the commercial deployment of fifth generation (5G), academic and industrial research focuses on the sixth generation (6G) of wireless communication systems. Artificial Intelligence (AI) and especially Machine Learning (ML), will be a key component of 6G systems. Here, we present an up-to-date review of future 6G wireless systems and the role of unsupervised ML techniques in them.

@inproceedings{
 title = {Comparing Machine Learning Methods for Air-to-Ground Path Loss Prediction},
 type = {inproceedings},
 year = {2021},
 keywords = {AdaBoost,Random Forest,Support Vector Regression,k-Nearest Neighbors,machine learning,mobile communications,path loss,ray tracing},
 pages = {1-4},
 id = {04eed7d3-9f3b-368e-8977-cfcd9034ad4c},
 created = {2021-07-29T14:17:13.999Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.205Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493374},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Machine Learning-based models gain increasingly momentum regarding the problem of path loss prediction. The work at hand deploys four machine learning algorithms (k Nearest Neighbors - kNN, Support Vector Regression - SVR, Random Forest - RF and AdaBoost), in order to simulate the radio coverage provided from a flying base station in the greek city of Tripolis. Their comparison shows that tree-based ensemble models (RF and AdaBoost) can be used as fast and reliable alternatives to the Ray Tracing technique.},
 bibtype = {inproceedings},
 author = {Vergos, George and Sotiroudis, Sotirios P and Athanasiadou, Georgia and Tsoulos, George V and Goudos, Sotirios K},
 doi = {10.1109/MOCAST52088.2021.9493374},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

Machine Learning-based models gain increasingly momentum regarding the problem of path loss prediction. The work at hand deploys four machine learning algorithms (k Nearest Neighbors - kNN, Support Vector Regression - SVR, Random Forest - RF and AdaBoost), in order to simulate the radio coverage provided from a flying base station in the greek city of Tripolis. Their comparison shows that tree-based ensemble models (RF and AdaBoost) can be used as fast and reliable alternatives to the Ray Tracing technique.

@inproceedings{
 title = {On the Resource Allocation of Hierarchical NOMA for Fog-RAN with Energy Harvesting},
 type = {inproceedings},
 year = {2021},
 keywords = {convex optimization,energy harvesting,hierarchical noma,non-orthogonal multiple access (noma),resource allocation},
 pages = {1-4},
 id = {630c0920-1ac2-31cd-97c8-860ffd5c4036},
 created = {2021-07-29T14:17:14.046Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.359Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493358},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this paper, we introduce a multiple access protocol, termed hierarchical non-orthogonal multiple access (HiNOMA), optimized for fog-radio access networks (F-RANs). Resource allocation optimization is deemed critical in order to guarantee the users' fairness in the network, while energy efficiency can be increased through energy harvesting (EH) at the user equipment (UE) nodes. Therefore, the HiNOMA protocol with energy harvesting capabilities is examined for F-RANs, leading to the optimization of the proportional fairness metric. Finally, numerical results reveal the effectiveness of the joint design and the interesting trade-off between harvested power and achievable rate in the case of F-RAN.},
 bibtype = {inproceedings},
 author = {Papanikolaou, Vasilis K and Mitsiou, Nikos A and Diamantoulakis, Panagiotis D and Goudos, Sotirios K and Karagiannidis, George K},
 doi = {10.1109/MOCAST52088.2021.9493358},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

In this paper, we introduce a multiple access protocol, termed hierarchical non-orthogonal multiple access (HiNOMA), optimized for fog-radio access networks (F-RANs). Resource allocation optimization is deemed critical in order to guarantee the users' fairness in the network, while energy efficiency can be increased through energy harvesting (EH) at the user equipment (UE) nodes. Therefore, the HiNOMA protocol with energy harvesting capabilities is examined for F-RANs, leading to the optimization of the proportional fairness metric. Finally, numerical results reveal the effectiveness of the joint design and the interesting trade-off between harvested power and achievable rate in the case of F-RAN.

@inproceedings{
 title = {Medical Data Encryption based on a Modified Sinusoidal 1D Chaotic Map and Its Microcontroller Implementation},
 type = {inproceedings},
 year = {2021},
 keywords = {Chaos,eeg,microcontroller,prbg,signal encryption},
 pages = {1-4},
 id = {b60c7d87-adbf-3f12-883f-e7ab504d8a2b},
 created = {2021-07-29T14:17:14.117Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.154Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9493422},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work considers a modification of the map proposed in Wang et al. (2020), by replacing its fixed term by a squared hyperbolic tangent term. The modified map is studied and is shown to have a plethora of chaos related phenomena, like period doubling route to chaos, crisis, antimonotonicity, and an infinite number of equilibrium points inside a bounded domain. Then, a pseudo-random bit generator is designed from the given map and it is applied to the encryption of medical data. Specifically, an electrophysiological signal is considered. The resulting design is finally implemented on a 32 bit microcontroller.},
 bibtype = {inproceedings},
 author = {Iatropoulos, Apostolos and Moysis, Lazaros and Giakoumis, Aggelos and Volos, Christos and Ouannas, Adel and Goudos, Sotirios},
 doi = {10.1109/MOCAST52088.2021.9493422},
 booktitle = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}
}

This work considers a modification of the map proposed in Wang et al. (2020), by replacing its fixed term by a squared hyperbolic tangent term. The modified map is studied and is shown to have a plethora of chaos related phenomena, like period doubling route to chaos, crisis, antimonotonicity, and an infinite number of equilibrium points inside a bounded domain. Then, a pseudo-random bit generator is designed from the given map and it is applied to the encryption of medical data. Specifically, an electrophysiological signal is considered. The resulting design is finally implemented on a 32 bit microcontroller.

@article{
 title = {Metaheuristic Optimization of LED Locations for Visible Light Positioning Network Planning},
 type = {article},
 year = {2021},
 pages = {894-908},
 volume = {67},
 id = {6c460b5f-fe37-32ef-993b-0d3306f0700d},
 created = {2021-08-04T21:01:51.763Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:54.834Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9505014},
 source_type = {article},
 private_publication = {false},
 abstract = {Optical Wireless Communication (OWC) is being explored for application in the next-generation broadcasting networks, where possessing accurately determined user locations becomes increasingly important. Received signal strength (RSS) Visible Light Positioning (VLP)-based localisation systems aim to deliver these centimetre-level location data at a low cost by featuring but a single photodiode (PD). Maximising the VLP accuracy requires optimising the LED transmitter locations, which is missing currently. An evolutionary optimisation algorithm is proposed to determine the optimal LED locations and the associated positioning error values for various configurations. The sensitivity of the planning on the number of VLP-enabled LEDs, the LEDs’ characteristics, the room dimensions and the positioning parameters is investigated. Experimental data, i.e., two datasets with 1572 measurement points each, serve to validate the simulations.},
 bibtype = {article},
 author = {Bastiaens, Sander and Goudos, Sotirios K and Joseph, Wout and Plets, David},
 doi = {10.1109/TBC.2021.3099734},
 journal = {IEEE Transactions on Broadcasting},
 number = {4}
}

Optical Wireless Communication (OWC) is being explored for application in the next-generation broadcasting networks, where possessing accurately determined user locations becomes increasingly important. Received signal strength (RSS) Visible Light Positioning (VLP)-based localisation systems aim to deliver these centimetre-level location data at a low cost by featuring but a single photodiode (PD). Maximising the VLP accuracy requires optimising the LED transmitter locations, which is missing currently. An evolutionary optimisation algorithm is proposed to determine the optimal LED locations and the associated positioning error values for various configurations. The sensitivity of the planning on the number of VLP-enabled LEDs, the LEDs’ characteristics, the room dimensions and the positioning parameters is investigated. Experimental data, i.e., two datasets with 1572 measurement points each, serve to validate the simulations.

@inproceedings{
 title = {Federated Intrusion Detection In NG-IoT Healthcare Systems: An Adversarial Approach},
 type = {inproceedings},
 year = {2021},
 pages = {1-6},
 websites = {https://ieeexplore.ieee.org/document/9500578/},
 month = {6},
 publisher = {IEEE},
 id = {5855fb78-adc8-333f-a942-66225905c340},
 created = {2021-08-06T20:20:42.843Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.030Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9500578},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In recent years and with the advancement of IoT networks, malicious intrusions aiming at disrupting the services and getting access to confidential information in medical environments is ever progressing. To that end, this paper proposes a Federated Layered Architecture to be used in Medical Cyber-Physical Systems (MCPS) Networks that entails the creation of multiple aggregation layers to induce further security to the model training process. Moreover, two Deep Adversarial Neural Networks (GANs) are presented for use with data found in the MCPS environment. The evaluation of the presented work showed that the models trained in the Federated system have an increase in their ability to detect possible intrusions in the MCPS network than the commonly trained models.},
 bibtype = {inproceedings},
 author = {Siniosoglou, Ilias and Sarigiannidis, Panagiotis and Argyriou, Vasilis and Lagkas, Thomas and Goudos, Sotirios K and Poveda, Maria},
 doi = {10.1109/ICC42927.2021.9500578},
 booktitle = {ICC 2021 - IEEE International Conference on Communications}
}

In recent years and with the advancement of IoT networks, malicious intrusions aiming at disrupting the services and getting access to confidential information in medical environments is ever progressing. To that end, this paper proposes a Federated Layered Architecture to be used in Medical Cyber-Physical Systems (MCPS) Networks that entails the creation of multiple aggregation layers to induce further security to the model training process. Moreover, two Deep Adversarial Neural Networks (GANs) are presented for use with data found in the MCPS environment. The evaluation of the presented work showed that the models trained in the Federated system have an increase in their ability to detect possible intrusions in the MCPS network than the commonly trained models.

@article{
 title = {High-Efficiency Triple-Band RF-to-DC Rectifier Primary Design for RF Energy-Harvesting Systems},
 type = {article},
 year = {2021},
 pages = {271-284},
 volume = {2},
 websites = {https://www.mdpi.com/2673-4001/2/3/18},
 id = {76414c4a-7843-31dc-a77d-defce50a6395},
 created = {2021-08-09T14:25:42.716Z},
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 last_modified = {2021-08-09T14:25:42.716Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {telecom2030018},
 source_type = {article},
 private_publication = {false},
 abstract = {Radio Frequency (RF) energy harvesting has been emerged as a potentially reliable method to replace the costly and difficult to maintain source of low-power wireless sensor networks. A plethora of dual-band rectifier designs has been proposed in the literature operating in various frequency bands. In this paper, a triple-band RF-to-DC rectifier that operates in the frequency bands of LoRaWAN, GSM-900, and WiFi 2.4 GHz is presented. The system is composed of an impedance-matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low-power devices, and an output load. The proposed system resonates at three different frequencies of 866 MHz, 948 MHz and 2423 MHz, which fall within the aforementioned frequency bands of interest. The feasible solution of the proposed system was based on a dual-band rectifier operating in the frequency bands of LoRaWAN and GSM-900. A series of shunt stubs was utilized in the initial design to form the feasible solution of the proposed system. The proposed triple-band rectifier was optimized using a powerful optimization algorithm, i.e., the genetic algorithm. The overall system exhibited improved characteristics compared to the initial design in terms of its resonance. Numerical results demonstrated that the overall system exhibited an efficiency of 81% with 3.23 V of the output voltage, for an input power of 0 dBm and a load of 13 kOhm.},
 bibtype = {article},
 author = {Papadopoulou, Maria S and Boursianis, Achilles D and Volos, Christos K and Stouboulos, Ioannis N and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.3390/telecom2030018},
 journal = {Telecom},
 number = {3}
}

Radio Frequency (RF) energy harvesting has been emerged as a potentially reliable method to replace the costly and difficult to maintain source of low-power wireless sensor networks. A plethora of dual-band rectifier designs has been proposed in the literature operating in various frequency bands. In this paper, a triple-band RF-to-DC rectifier that operates in the frequency bands of LoRaWAN, GSM-900, and WiFi 2.4 GHz is presented. The system is composed of an impedance-matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low-power devices, and an output load. The proposed system resonates at three different frequencies of 866 MHz, 948 MHz and 2423 MHz, which fall within the aforementioned frequency bands of interest. The feasible solution of the proposed system was based on a dual-band rectifier operating in the frequency bands of LoRaWAN and GSM-900. A series of shunt stubs was utilized in the initial design to form the feasible solution of the proposed system. The proposed triple-band rectifier was optimized using a powerful optimization algorithm, i.e., the genetic algorithm. The overall system exhibited improved characteristics compared to the initial design in terms of its resonance. Numerical results demonstrated that the overall system exhibited an efficiency of 81% with 3.23 V of the output voltage, for an input power of 0 dBm and a load of 13 kOhm.

@article{
 title = {Encoding Spectral-Spatial Features for Hyperspectral Image Classification in the Satellite Internet of Things System},
 type = {article},
 year = {2021},
 volume = {13},
 websites = {https://www.mdpi.com/2072-4292/13/18/3561},
 id = {14020eb8-e387-3f51-b986-c61bb0fdb0c6},
 created = {2021-09-10T05:43:09.489Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-09-10T05:43:09.489Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {rs13183561},
 source_type = {article},
 private_publication = {false},
 abstract = {Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.},
 bibtype = {article},
 author = {Lv, Ning and Han, Zhen and Chen, Chen and Feng, Yijia and Su, Tao and Goudos, Sotirios and Wan, Shaohua},
 doi = {10.3390/rs13183561},
 journal = {Remote Sensing},
 number = {18}
}

Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.

@article{
 title = {Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers},
 type = {article},
 year = {2021},
 volume = {11},
 websites = {https://www.mdpi.com/2076-3417/11/18/8330},
 id = {f8e33846-e1ba-366d-bfb3-159796a7aa15},
 created = {2021-09-10T05:43:09.493Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-09-10T05:43:09.493Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {app11188330},
 source_type = {article},
 private_publication = {false},
 abstract = {Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands.},
 bibtype = {article},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Salucci, Marco and Polo, Alessandro and Sarigiannidis, Panagiotis and Psannis, Konstantinos and Mirjalili, Seyedali and Koulouridis, Stavros and Goudos, Sotirios K},
 doi = {10.3390/app11188330},
 journal = {Applied Sciences},
 number = {18}
}

Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands.

@inbook{
 type = {inbook},
 year = {2021},
 pages = {251-267},
 websites = {https://doi.org/10.1007/978-3-030-74311-6_8},
 publisher = {Springer International Publishing},
 city = {Cham},
 id = {fdd827e1-b600-3854-9836-d318e20ecbad},
 created = {2021-09-25T15:20:07.126Z},
 file_attached = {false},
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 last_modified = {2021-09-25T15:20:07.126Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2021},
 source_type = {inbook},
 private_publication = {false},
 abstract = {The new expected fifth generation (5G) communication systems will serve users with several Gbps data rates and will allow running new applications from mobile devices. In order to do so, several design challenges must be met. One of these is the antenna design and fabrication for 5G mobile devices, especially in the millimeter-wave frequencies. In this chapter, we address the above issue by designing a patch antennas for mm-wave frequencies. We apply a design procedure based on a new nature-inspired algorithm the Whale Optimization Algorithm (WOA), which is based on the social behavior of humpback whales. We design the antenna using the WOA algorithm. The numerical results show the applicability and validity of the proposed design framework.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 editor = {Matin, Mohammad Abdul},
 doi = {10.1007/978-3-030-74311-6_8},
 chapter = {Application of the Whale Optimization Algorithm to Antenna Design for mm-Wave 5G Communications Systems},
 title = {Wideband, Multiband, and Smart Antenna Systems}
}

The new expected fifth generation (5G) communication systems will serve users with several Gbps data rates and will allow running new applications from mobile devices. In order to do so, several design challenges must be met. One of these is the antenna design and fabrication for 5G mobile devices, especially in the millimeter-wave frequencies. In this chapter, we address the above issue by designing a patch antennas for mm-wave frequencies. We apply a design procedure based on a new nature-inspired algorithm the Whale Optimization Algorithm (WOA), which is based on the social behavior of humpback whales. We design the antenna using the WOA algorithm. The numerical results show the applicability and validity of the proposed design framework.

@article{
 title = {Novel Design Framework for Dual-Band Frequency Selective Surfaces Using Multi-Variant Differential Evolution},
 type = {article},
 year = {2021},
 pages = {2381},
 volume = {9},
 websites = {https://www.mdpi.com/2227-7390/9/19/2381},
 month = {9},
 day = {25},
 id = {2e43fee7-a130-3353-91cb-5642145a4e1b},
 created = {2021-09-25T15:20:07.158Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-10-23T12:19:59.906Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {math9192381},
 source_type = {article},
 private_publication = {false},
 abstract = {Frequency Selective Surfaces (FSSs) have become increasingly popular during the last years due to their combined characteristics, which meet, in general, the requirements of the next-generation wireless communication networks. In this work, a cross-platform design framework for FSS structures is presented and evaluated by utilizing a recently introduced evolutionary optimization algorithm, namely, the Multi-Variant Differential Evolution (MVDE). To the best of the authors knowledge, this is the first time that the MVDE algorithm is applied to a design problem in Electromagnetics. The proposed design framework is described in detail and the utilized evolutionary algorithm is assessed in terms of its performance by applying several benchmark functions. In this context, the MVDE is comparatively evaluated against other popular evolutionary algorithms. Moreover, it is applied to the design and optimization of two different representative examples of FSS structures based on three use cases of unit cell geometry. Optimization results indicate the efficacy of the proposed framework by quantifying the performance of the designed FSS structures in terms of several system metrics. The optimized FSS structures exhibit dual-band operation and quite acceptable results in the ISM frequency bands of 2.45 GHz and 5.8 GHz.},
 bibtype = {article},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Nikolaidis, Spyridon and Sarigiannidis, Panagiotis and Psannis, Konstantinos and Georgiadis, Apostolos and Tentzeris, Manos M and Goudos, Sotirios K},
 doi = {10.3390/math9192381},
 journal = {Mathematics},
 number = {19}
}

Frequency Selective Surfaces (FSSs) have become increasingly popular during the last years due to their combined characteristics, which meet, in general, the requirements of the next-generation wireless communication networks. In this work, a cross-platform design framework for FSS structures is presented and evaluated by utilizing a recently introduced evolutionary optimization algorithm, namely, the Multi-Variant Differential Evolution (MVDE). To the best of the authors knowledge, this is the first time that the MVDE algorithm is applied to a design problem in Electromagnetics. The proposed design framework is described in detail and the utilized evolutionary algorithm is assessed in terms of its performance by applying several benchmark functions. In this context, the MVDE is comparatively evaluated against other popular evolutionary algorithms. Moreover, it is applied to the design and optimization of two different representative examples of FSS structures based on three use cases of unit cell geometry. Optimization results indicate the efficacy of the proposed framework by quantifying the performance of the designed FSS structures in terms of several system metrics. The optimized FSS structures exhibit dual-band operation and quite acceptable results in the ISM frequency bands of 2.45 GHz and 5.8 GHz.

@article{
 title = {State-of-the-Art Techniques in RF Energy Harvesting Circuits},
 type = {article},
 year = {2021},
 pages = {369-389},
 volume = {2},
 websites = {https://www.mdpi.com/2673-4001/2/4/22},
 id = {9f74cc3d-d68b-3024-b64e-ae15797f56ec},
 created = {2021-10-23T12:20:32.698Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-10-23T12:20:32.698Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {telecom2040022},
 source_type = {article},
 private_publication = {false},
 abstract = {The exigency for continuous use of electrical devices has created greater demands for electricity along with more efficient transmission techniques. Energy from natural resources can be solar, thermal, vibration, friction, or Radio Frequencies (RF) signals. This state-of-the-art work provides a summary of RF energy harvesting techniques and can be used as a guide for the manufacture of RF energy scavenging modules. The use of Radio Frequency (RF) Energy Harvesting (EH) technique contributes to the development of autonomous energy devices and sensors. A rectenna system includes three main units: the receiving antenna, the impedance matching network, and the rectifier. We thoroughly analyze how to design a rectenna system with special emphasis given on the design of the rectifier. At the same time many works of the last 10 years are presented. This review article categorizes the used topologies depending on the type of antennas, IMNs, and rectifiers and comparatively presents their advantages and disadvantages.},
 bibtype = {article},
 author = {Bougas, Ioannis D and Papadopoulou, Maria S and Boursianis, Achilles D and Kokkinidis, Konstantinos and Goudos, Sotirios K},
 doi = {10.3390/telecom2040022},
 journal = {Telecom},
 number = {4}
}

The exigency for continuous use of electrical devices has created greater demands for electricity along with more efficient transmission techniques. Energy from natural resources can be solar, thermal, vibration, friction, or Radio Frequencies (RF) signals. This state-of-the-art work provides a summary of RF energy harvesting techniques and can be used as a guide for the manufacture of RF energy scavenging modules. The use of Radio Frequency (RF) Energy Harvesting (EH) technique contributes to the development of autonomous energy devices and sensors. A rectenna system includes three main units: the receiving antenna, the impedance matching network, and the rectifier. We thoroughly analyze how to design a rectenna system with special emphasis given on the design of the rectifier. At the same time many works of the last 10 years are presented. This review article categorizes the used topologies depending on the type of antennas, IMNs, and rectifiers and comparatively presents their advantages and disadvantages.

@article{
 title = {Machine Learning in Beyond 5G/6G Networks—State-of-the-Art and Future Trends},
 type = {article},
 year = {2021},
 volume = {10},
 websites = {https://www.mdpi.com/2079-9292/10/22/2786},
 id = {b28122ad-c8e8-3691-a272-92ca4c2e6ed2},
 created = {2021-11-14T16:10:44.752Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2021-11-14T16:10:44.752Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {electronics10222786},
 source_type = {article},
 private_publication = {false},
 abstract = {Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important role in realizing and optimizing 6G network applications. In this paper, we present a brief summary of ML methods, as well as an up-to-date review of ML approaches in 6G wireless communication systems. These methods include supervised, unsupervised and reinforcement techniques. Additionally, we discuss open issues in the field of ML for 6G networks and wireless communications in general, as well as some potential future trends to motivate further research into this area.},
 bibtype = {article},
 author = {Rekkas, Vasileios P and Sotiroudis, Sotirios and Sarigiannidis, Panagiotis and Wan, Shaohua and Karagiannidis, George K and Goudos, Sotirios K},
 doi = {10.3390/electronics10222786},
 journal = {Electronics},
 number = {22}
}

Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important role in realizing and optimizing 6G network applications. In this paper, we present a brief summary of ML methods, as well as an up-to-date review of ML approaches in 6G wireless communication systems. These methods include supervised, unsupervised and reinforcement techniques. Additionally, we discuss open issues in the field of ML for 6G networks and wireless communications in general, as well as some potential future trends to motivate further research into this area.

@inproceedings{
 title = {Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study},
 type = {inproceedings},
 year = {2021},
 pages = {272-279},
 id = {1737f950-6aeb-3a06-9f3a-b0f79e82e06b},
 created = {2021-11-19T18:01:12.685Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.247Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9600023},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-RDG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Boursianis, Achilles D and Mohamed, Ali Wagdy and Wan, Shaohua and Sarigiannidis, Panagiotis and Karagiannidis, George K and Suganthan, Ponnuthurai N},
 doi = {10.1109/DCOSS52077.2021.00052},
 booktitle = {2021 17th International Conference on Distributed Computing in Sensor Systems (DCOSS)}
}

The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-RDG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.

@inproceedings{
 title = {Online EM Teaching: E-XAM tool for Students' Self-Evaluation and Final Assessment},
 type = {inproceedings},
 year = {2021},
 pages = {1477-1478},
 id = {5de38ce9-a2c4-3329-8943-4c495099afca},
 created = {2022-02-17T06:58:20.570Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:39:01.809Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9704286},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work presents a novel tool for supporting and simplifying electromagnetic (EM) teaching activities related to students' self-evaluation and final examination. The proposed approach has been experimentally validated within the Bachelor course “Electromagnetic Fields” and was recently applied to all courses provided by the ELEDIA Research Center teaching staff.},
 bibtype = {inproceedings},
 author = {Polo, Alessandro and Anselmi, Nicola and Azaro, Renzo and Gottardi, Giorgio and Hannan, Mohammad Abdul and Oliveri, Giacomo and Poli, Lorenzo and Rocca, Paolo and Salucci, Marco and Ahmadi, Hanen and Huang, Jin and Li, Peng and Li, Maokun and Goudos, Sotirios K and Yang, Shiwen and Massa, Andrea},
 doi = {10.1109/APS/URSI47566.2021.9704286},
 booktitle = {2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI)}
}

This work presents a novel tool for supporting and simplifying electromagnetic (EM) teaching activities related to students' self-evaluation and final examination. The proposed approach has been experimentally validated within the Bachelor course “Electromagnetic Fields” and was recently applied to all courses provided by the ELEDIA Research Center teaching staff.

@inproceedings{
 title = {Implantable Antenna Design Using Improved Grey Wolf Optimizer Algorithm},
 type = {inproceedings},
 year = {2021},
 pages = {801-802},
 id = {aad0e845-0ea4-3fb5-aa22-edaad02b896b},
 created = {2022-02-17T06:58:20.670Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T17:35:55.015Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9704184},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Medical implanted sensors coupled with antennas are sought in order to wirelessly transmit crucial health info and operate in a complex environment. Such antennas need to operate in a lossy environment, be robust when embedded in various body types, do not interact with the device electronics, and have very small physical sizes. To satisfy conflicting requirements multiple geometrical parameters should be tuned. While physical insight is always needed, optimization is the key factor for a successful design. Towards this goal, unconventional design techniques like evolutionary algorithms can be used. In this paper, we apply the improved grey wolf optimizer (IGWO) for implantable antenna design.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Goudos, Sotirios K and Matthaiou, Maria and Koulouridis, Stavros and Salucci, Marco},
 doi = {10.1109/APS/URSI47566.2021.9704184},
 booktitle = {2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI)}
}

Medical implanted sensors coupled with antennas are sought in order to wirelessly transmit crucial health info and operate in a complex environment. Such antennas need to operate in a lossy environment, be robust when embedded in various body types, do not interact with the device electronics, and have very small physical sizes. To satisfy conflicting requirements multiple geometrical parameters should be tuned. While physical insight is always needed, optimization is the key factor for a successful design. Towards this goal, unconventional design techniques like evolutionary algorithms can be used. In this paper, we apply the improved grey wolf optimizer (IGWO) for implantable antenna design.

@inproceedings{
 title = {Communication and Security Issues in Online Learning during the COVID-19 Pandemic},
 type = {inproceedings},
 year = {2021},
 keywords = {Learning systems;COVID-19;Privacy;Pandemics;Confer},
 pages = {538-544},
 id = {d34010ca-7ae6-3a33-8a86-bdd3f8f974c1},
 created = {2022-04-04T06:02:05.706Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-04-04T06:02:05.706Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9673972},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This era is characterized by the rapid evolution of technology and its application in all sectors of day to day life. At the same time, the outbreak of the COVID-19 pandemic has highlighted the distance education as vital, compulsory and worldwide, for Educational Institutions. The attainments of technology are set at the service of education and the problem of security and privacy in online learning is emerged. This paper focuses on the development of a secure online learning system, which utilizes edge computing and privacy mechanisms, such as trust evaluation from direct and indirect observations. The proposed system provides to the Educational Institutions the advantage of conducting online courses, by ensuring privacy in communication for students, professors and the organization.},
 bibtype = {inproceedings},
 author = {Metallidou, Chrysi and Psannis, Kostas E and Goudos, Sotirios and Sarigiannidis, Panagiotis and Ishibashi, Yutaka},
 doi = {10.1109/ICICN52636.2021.9673972},
 booktitle = {2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)}
}

This era is characterized by the rapid evolution of technology and its application in all sectors of day to day life. At the same time, the outbreak of the COVID-19 pandemic has highlighted the distance education as vital, compulsory and worldwide, for Educational Institutions. The attainments of technology are set at the service of education and the problem of security and privacy in online learning is emerged. This paper focuses on the development of a secure online learning system, which utilizes edge computing and privacy mechanisms, such as trust evaluation from direct and indirect observations. The proposed system provides to the Educational Institutions the advantage of conducting online courses, by ensuring privacy in communication for students, professors and the organization.

@inproceedings{
 title = {Diverse Implementations of the Lorenz System for Teaching Non-Linear Chaotic Circuits},
 type = {inproceedings},
 year = {2021},
 keywords = {Visualization;Chaotic communication;Simulation;Edu},
 pages = {416-420},
 id = {60d003ef-4033-346f-b521-3b8d4960f2f0},
 created = {2022-04-04T06:02:05.803Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-04-04T06:02:05.803Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9674018},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {It is common knowledge that nature exhibits nonlinear behavior, generally. As a result, non-linear phenomena play a vital role in the control systems in terms of engineering. That is the main reason for considering teaching nonlinear circuits in science and engineering undergraduate programs. In this paper, we present a well-known system that exhibits chaotic behavior. We quote the state equations and mathematical analysis of the Lorenz system. Afterward, we demonstrate simulation results to study and analyze the dynamic behavior of the overall system. The examples indicate a variety of ways in which chaotic behavior can arise in electronic circuits. Finally, we introduce an Arduino-based implementation of the Lorenz system. The comparison between the simulation and experimental results indicates the chaotic dynamics of the system.},
 bibtype = {inproceedings},
 author = {Papadopoulou, Maria S and Rusyn, Volodymyr and Boursianis, Achilles D and Sarigiannidis, Panagiotis and Psannis, Konstantinos and Goudos, Sotirios K},
 doi = {10.1109/ICICN52636.2021.9674018},
 booktitle = {2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)}
}

It is common knowledge that nature exhibits nonlinear behavior, generally. As a result, non-linear phenomena play a vital role in the control systems in terms of engineering. That is the main reason for considering teaching nonlinear circuits in science and engineering undergraduate programs. In this paper, we present a well-known system that exhibits chaotic behavior. We quote the state equations and mathematical analysis of the Lorenz system. Afterward, we demonstrate simulation results to study and analyze the dynamic behavior of the overall system. The examples indicate a variety of ways in which chaotic behavior can arise in electronic circuits. Finally, we introduce an Arduino-based implementation of the Lorenz system. The comparison between the simulation and experimental results indicates the chaotic dynamics of the system.

@inproceedings{
 title = {Efficient Integration of XR with Haptic Feedback and 5G Networks},
 type = {inproceedings},
 year = {2021},
 keywords = {Cellular networks;Wireless communication;5G mobile},
 pages = {240-244},
 id = {7af86c49-a991-3d34-9ef0-3c3a897e6139},
 created = {2022-04-04T06:02:05.870Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-04-04T06:02:05.870Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9674010},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The speedy development of immersive technologies and unexpected situations like the COVID-19 pandemic are expected to boost the application of extended reality (XR) in tourism. Virtualization techniques can create a virtual environment identical to the real one, giving to the user the feeling of actually being there. The aim of haptic systems is to enhance the degree of immersion into a virtual environment by intensifying the skill of physical interaction with people and objects in the distant space. The advancement of cellular networks enables haptic data transmission over high data rate and low latency wireless communication to create ambient haptic experience. The contribution of this research is to describe how XR and haptics are able to reshape tourism industry and present insights for tourism involved parties.},
 bibtype = {inproceedings},
 author = {Minopoulos, Georgios and Psannis, Konstantinos E and Goudos, Sotirios and Nikolaidis, Spiridon and Kokkonis, Georgios and Ishibashi, Yutaka},
 doi = {10.1109/ICICN52636.2021.9674010},
 booktitle = {2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)}
}

The speedy development of immersive technologies and unexpected situations like the COVID-19 pandemic are expected to boost the application of extended reality (XR) in tourism. Virtualization techniques can create a virtual environment identical to the real one, giving to the user the feeling of actually being there. The aim of haptic systems is to enhance the degree of immersion into a virtual environment by intensifying the skill of physical interaction with people and objects in the distant space. The advancement of cellular networks enables haptic data transmission over high data rate and low latency wireless communication to create ambient haptic experience. The contribution of this research is to describe how XR and haptics are able to reshape tourism industry and present insights for tourism involved parties.

@article{
 title = {Faster R-CNN for multi-class fruit detection using a robotic vision system},
 type = {article},
 year = {2020},
 keywords = {Deep learning,Faster R-CNN,Image region selection,Multi-class fruit detection},
 volume = {168},
 id = {463b1407-edd0-33e4-835b-5338e4bb3a80},
 created = {2020-02-29T16:57:41.948Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.910Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wan2020},
 private_publication = {false},
 abstract = {An accurate and real-time image based multi-class fruit detection system is important for facilitating higher level smart farm tasks such as yield mapping and robotic harvesting. Robotic harvesting can reduce the costs of labour and increase fruit quality. This paper proposes a deep learning framework for multi-class fruits detection based on improved Faster R-CNN. The proposed framework includes fruits image library creation, data argumentation, improved Faster RCNN model generation, and performance evaluation. This work is a pioneer to create a multi-labeled and knowledge-based outdoor orchard image library using 4000 images in the real world. Also, improvement of the convolutional and pooling layers is achieved to have a more accurate and faster detection. The test results show the proposed algorithm has achieved higher detecting accuracy and lower processing time than the traditional detectors, which has excellent potential to build an autonomous and real-time harvesting or yield mapping/estimation system.},
 bibtype = {article},
 author = {Wan, Shaohua and Goudos, Sotirios},
 doi = {10.1016/j.comnet.2019.107036},
 journal = {Computer Networks}
}

An accurate and real-time image based multi-class fruit detection system is important for facilitating higher level smart farm tasks such as yield mapping and robotic harvesting. Robotic harvesting can reduce the costs of labour and increase fruit quality. This paper proposes a deep learning framework for multi-class fruits detection based on improved Faster R-CNN. The proposed framework includes fruits image library creation, data argumentation, improved Faster RCNN model generation, and performance evaluation. This work is a pioneer to create a multi-labeled and knowledge-based outdoor orchard image library using 4000 images in the real world. Also, improvement of the convolutional and pooling layers is achieved to have a more accurate and faster detection. The test results show the proposed algorithm has achieved higher detecting accuracy and lower processing time than the traditional detectors, which has excellent potential to build an autonomous and real-time harvesting or yield mapping/estimation system.

@inbook{
 type = {inbook},
 year = {2020},
 keywords = {Cognitive radio (CR),Evolutionary algorithms,Monarch butterfly optimization (MBO),Optimization methods},
 pages = {81-100},
 websites = {https://doi.org/10.1007/978-3-030-42573-9_7},
 publisher = {Springer International Publishing},
 city = {Cham},
 id = {bd7017ed-30ca-3b71-8775-cd52a8f5851b},
 created = {2020-04-28T21:53:35.012Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.659Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2020b},
 source_type = {Inbook},
 private_publication = {false},
 abstract = {The Internet of Things (IoT) paradigm expands the current Internet and enables communication through machine to machine (M2M), while posing new challenges. Cognitive Radio (CR) Systems have received much attention over the last decade, because of their ability to flexibly adapt their transmission parameters to their changing environment. Current technology trends are shifting to the adaptability of Cognitive Radio Networks (CRNs) into IoT. The determination of the appropriate transmission parameters for a given wireless channel environment is the main feature of a cognitive radio engine. For wireless multicarrier transceivers, the problem becomes high dimensional due to the large number of decision variables required. Evolutionary Algorithms (EAs) are suitable techniques to solve the above-mentioned problem. In this chapter, we propose a new approach for designing a CR engine for wireless multicarrier transceivers using monarch butterfly optimization (MBO). Moreover, we also apply a modified MBO version that includes a Greedy strategy and a self-adaptive Crossover operator, called Greedy Crossover MBO (GCMBO). Additionally, the CR engine also uses a fuzzy decision maker for obtaining the best compromised solution. The simulation results show that the GCMBO driven CR engine can obtain better results than the original MBO and outperform other popular algorithms. Moreover, GCMBO is more efficient when applied to high-dimensional problems in cases of multicarrier system.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 editor = {Matin, Mohammad Abdul},
 doi = {10.1007/978-3-030-42573-9_7},
 chapter = {Cognitive Radio Engine Design for IoT Using Monarch Butterfly Optimization and Fuzzy Decision Making},
 title = {Internet of Things}
}

The Internet of Things (IoT) paradigm expands the current Internet and enables communication through machine to machine (M2M), while posing new challenges. Cognitive Radio (CR) Systems have received much attention over the last decade, because of their ability to flexibly adapt their transmission parameters to their changing environment. Current technology trends are shifting to the adaptability of Cognitive Radio Networks (CRNs) into IoT. The determination of the appropriate transmission parameters for a given wireless channel environment is the main feature of a cognitive radio engine. For wireless multicarrier transceivers, the problem becomes high dimensional due to the large number of decision variables required. Evolutionary Algorithms (EAs) are suitable techniques to solve the above-mentioned problem. In this chapter, we propose a new approach for designing a CR engine for wireless multicarrier transceivers using monarch butterfly optimization (MBO). Moreover, we also apply a modified MBO version that includes a Greedy strategy and a self-adaptive Crossover operator, called Greedy Crossover MBO (GCMBO). Additionally, the CR engine also uses a fuzzy decision maker for obtaining the best compromised solution. The simulation results show that the GCMBO driven CR engine can obtain better results than the original MBO and outperform other popular algorithms. Moreover, GCMBO is more efficient when applied to high-dimensional problems in cases of multicarrier system.

@article{
 title = {Teaching Electromagnetics to Next-Generation Engineers - The ELEDIA Recipe- The ELEDIA teaching style},
 type = {article},
 year = {2020},
 keywords = {Antenn,Education,Mathematical model,Solid modeling},
 pages = {50-61},
 volume = {62},
 month = {4},
 id = {5448a0b6-6566-3a6d-bdc9-d134d5031286},
 created = {2020-05-07T07:01:20.068Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.124Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Massa2020},
 source_type = {ARTICLE},
 private_publication = {false},
 abstract = {Innovative teaching methods that address paramount challenges in modern electromagnetic (EM) engineering education are presented. An entire ecosystem of novel and interconnected strategies and tools has been developed by the ELEDIA Research Center to build a long-term educational and training framework for future EM professionals. According to an ELEDIA 'recipe,' students acquire higher self-confidence and admiration for the innovative applicative and technological aspects of Maxwell's equations in everyday life. Moreover, they gradually grow engineering thought mechanisms/attitudes and high-level (HL) professional skills thanks to novel examination (exam) approaches and extracurricular experiences that bridge the gap between academics and industry. Quantitative metrics are reported to highlight the success of the proposed strategies, taking the students' feedback into account as well.},
 bibtype = {article},
 author = {Massa, Andrea and Anselmi, Nicola and Dallasta, Luca and Gottardi, Giorgio and Goudos, Sotirios K and Hannan, Mohammad Abdul and Huang, Jin and Li, Maokun and Oliveri, Giacomo and Poli, Lorenzo and Polo, Alessandro and Rocca, Paolo and Salas-Sanchez, Aaron A and Salucci, Marco and Yang, Shiwen},
 doi = {10.1109/MAP.2020.2970307},
 journal = {IEEE Antennas and Propagation Magazine},
 number = {2}
}

Innovative teaching methods that address paramount challenges in modern electromagnetic (EM) engineering education are presented. An entire ecosystem of novel and interconnected strategies and tools has been developed by the ELEDIA Research Center to build a long-term educational and training framework for future EM professionals. According to an ELEDIA 'recipe,' students acquire higher self-confidence and admiration for the innovative applicative and technological aspects of Maxwell's equations in everyday life. Moreover, they gradually grow engineering thought mechanisms/attitudes and high-level (HL) professional skills thanks to novel examination (exam) approaches and extracurricular experiences that bridge the gap between academics and industry. Quantitative metrics are reported to highlight the success of the proposed strategies, taking the students' feedback into account as well.

@article{
 title = {Deep learning for radio propagation: Using image-driven regression to estimate path loss in urban areas},
 type = {article},
 year = {2020},
 keywords = {Artificial intelligence,Deep learning,Image-driven regression,Path loss prediction,Radio propagation},
 pages = {160-165},
 volume = {6},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084997260&doi=10.1016%2Fj.icte.2020.04.008&partnerID=40&md5=dbf1450e20b6a4f5ebf544586e8c1dfa},
 id = {699f7e9c-18af-3386-b156-0443c32f5b0d},
 created = {2020-08-31T20:28:48.320Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.068Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2020a},
 source_type = {ARTICLE},
 private_publication = {false},
 abstract = {Radio propagation modeling and path loss prediction have been the subject of many machine learning-based estimation attempts. Our current work uses deep learning for the task in question, trying to exploit the potential of applying convolutional neural networks in order to perform predictions based on images. A comparison between data-driven and image-driven estimations has been carried out in order to assess the proposed method. The results show that an appropriately chosen image can, per se, be treated as an alternative to a vector of tabular data and produce reliable predictions. The effect of the image's size has also been examined.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P and Goudos, Sotirios K and Siakavara, Katherine},
 doi = {10.1016/j.icte.2020.04.008},
 journal = {ICT Express},
 number = {3}
}

Radio propagation modeling and path loss prediction have been the subject of many machine learning-based estimation attempts. Our current work uses deep learning for the task in question, trying to exploit the potential of applying convolutional neural networks in order to perform predictions based on images. A comparison between data-driven and image-driven estimations has been carried out in order to assess the proposed method. The results show that an appropriately chosen image can, per se, be treated as an alternative to a vector of tabular data and produce reliable predictions. The effect of the image's size has also been examined.

@inproceedings{
 title = {Wearable 5-Gigahertz Wi-Fi Antenna Design Using Whale Optimization Algorithm},
 type = {inproceedings},
 year = {2020},
 keywords = {nature-inspired algorithms,printed inverted-F antenna,wearable antennas,whale optimization algorithm},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088652910&doi=10.23919%2FEuCAP48036.2020.9135735&partnerID=40&md5=0e00f909e78d1feb587eb5253f41089f},
 id = {5568cb7c-b645-3d8d-870e-801f76f1bd87},
 created = {2020-08-31T20:28:48.321Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.081Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2020d},
 source_type = {CONFERENCE},
 private_publication = {false},
 abstract = {In this paper, we design an antenna for wearable wireless applications. The proposed antenna is a planar inverted- F antenna (PIFA) for operation at 5 GHz. The antenna design procedure is accomplished using a new nature inspired algorithm, the Whale optimization Algorithm. Numerical results exhibit the applicability and validity of the proposed design framework.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Koulouridis, Stavros and Georgoulas, Dimitrios and Goudos, Sotirios K},
 doi = {10.23919/EuCAP48036.2020.9135735},
 booktitle = {14th European Conference on Antennas and Propagation, EuCAP 2020}
}

In this paper, we design an antenna for wearable wireless applications. The proposed antenna is a planar inverted- F antenna (PIFA) for operation at 5 GHz. The antenna design procedure is accomplished using a new nature inspired algorithm, the Whale optimization Algorithm. Numerical results exhibit the applicability and validity of the proposed design framework.

@inproceedings{
 title = {Modelling Ray Tracing Propagation Data Using Different Machine Learning Algorithms},
 type = {inproceedings},
 year = {2020},
 keywords = {Random Forest,Ray tracing,Support Vector Regression,k-Nearest Neighbors,mobile communications},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088630520&doi=10.23919%2FEuCAP48036.2020.9135639&partnerID=40&md5=448e25203d908932d9803ee5bea5bb94},
 id = {14451e24-75d9-3db2-a504-a0b3cc6ba392},
 created = {2020-08-31T20:28:48.387Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.903Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2020a},
 source_type = {CONFERENCE},
 private_publication = {false},
 abstract = {In this paper, we apply different machine learning methods for the prediction of path loss in urban environment for cellular communications with unmanned aerial vehicles (UAVs). We generate the training set using a ray tracing technique assuming a flying base station at different heights within the city of Tripolis, Greece. We produce prediction models for the path loss using three different learners the k-Nearest Neighbors (kNN), the Support Vector Regression (SVR)and the Random Forest (RF). The obtained numerical results are compared with the original data from the test dataset using representative performance indicators and overall they exhibit good precision.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Athanasiadou, Georgia and Tsoulos, George V and Rekkas, Vasileios},
 doi = {10.23919/EuCAP48036.2020.9135639},
 booktitle = {14th European Conference on Antennas and Propagation, EuCAP 2020}
}

In this paper, we apply different machine learning methods for the prediction of path loss in urban environment for cellular communications with unmanned aerial vehicles (UAVs). We generate the training set using a ray tracing technique assuming a flying base station at different heights within the city of Tripolis, Greece. We produce prediction models for the path loss using three different learners the k-Nearest Neighbors (kNN), the Support Vector Regression (SVR)and the Random Forest (RF). The obtained numerical results are compared with the original data from the test dataset using representative performance indicators and overall they exhibit good precision.

@article{
 title = {Differential Evolution in Waveform Design for Wireless Power Transfer},
 type = {article},
 year = {2020},
 keywords = {channel state information,evolutionary algorithms,waveform design,wireless power transfer},
 pages = {96-113},
 volume = {1},
 websites = {http://dx.doi.org/10.3390/telecom1020008},
 month = {8},
 publisher = {MDPI AG},
 id = {629c7fa7-57f3-3838-a160-59f2e87511b2},
 created = {2020-08-31T20:28:48.394Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.246Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Doanis2020a},
 source_type = {article},
 private_publication = {false},
 abstract = {The technique of transmitting multi-tone signals in a radiative Wireless Power Transfer (WPT) system can significantly increase its end-to-end power efficiency. The optimization problem in this system is to tune the transmission according to the receiver rectenna’s nonlinear behavior and the Channel State Information (CSI). This is a non-convex problem that has been previously addressed by Sequential Convex Programming (SCP) algorithms. Nonetheless, SCP algorithms do not always attain globally optimal solutions. To this end, in this paper, we evaluate a set of Evolutionary Algorithms (EAs) with several characteristics. The performance of the optimized multi-tone transmission signals in a WPT system is assessed by means of numerical simulations, utilizing a simplified Single Input Single Output (SISO) model. From the model evaluation, we can deduce that EAs can be successfully applied to the waveform design optimization problem. Moreover, from the presented results, we can derive that EAs can obtain the optimal solutions in the tested cases.},
 bibtype = {article},
 author = {Doanis, Pavlos and Boursianis, Achilles D and Huillery, Julien and Bréard, Arnaud and Duroc, Yvan and Goudos, Sotirios K},
 doi = {10.3390/telecom1020008},
 journal = {Telecom},
 number = {2}
}

The technique of transmitting multi-tone signals in a radiative Wireless Power Transfer (WPT) system can significantly increase its end-to-end power efficiency. The optimization problem in this system is to tune the transmission according to the receiver rectenna’s nonlinear behavior and the Channel State Information (CSI). This is a non-convex problem that has been previously addressed by Sequential Convex Programming (SCP) algorithms. Nonetheless, SCP algorithms do not always attain globally optimal solutions. To this end, in this paper, we evaluate a set of Evolutionary Algorithms (EAs) with several characteristics. The performance of the optimized multi-tone transmission signals in a WPT system is assessed by means of numerical simulations, utilizing a simplified Single Input Single Output (SISO) model. From the model evaluation, we can deduce that EAs can be successfully applied to the waveform design optimization problem. Moreover, from the presented results, we can derive that EAs can obtain the optimal solutions in the tested cases.

@article{
 title = {Feature Importances: A Tool to Explain Radio Propagation and Reduce Model Complexity},
 type = {article},
 year = {2020},
 keywords = {Random Forest,XGBoost,feature importances,feature selection,machine learning,path loss,radio propagation},
 pages = {114-125},
 volume = {1},
 websites = {http://dx.doi.org/10.3390/telecom1020009},
 month = {8},
 publisher = {MDPI AG},
 id = {006b80d1-55bb-390a-ac89-01c1adcdbf72},
 created = {2020-08-31T20:28:48.447Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.280Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2020},
 source_type = {article},
 private_publication = {false},
 abstract = {Machine learning models have been widely deployed to tackle the problem of radio propagation. In addition to helping in the estimation of path loss, they can also be used to better understand the details of various propagation scenarios. Our current work exploits the inherent ranking of feature importances provided by XGBoost and Random Forest as a means of indicating the contribution of the underlying propagation mechanisms. A comparison between two different transmitter antenna heights, revealing the associated propagation profiles, is made. Feature selection is then implemented, leading to models with reduced complexity, and consequently reduced training and response times, based on the previously calculated importances.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P and Goudos, Sotirios K and Siakavara, Katherine},
 doi = {10.3390/telecom1020009},
 journal = {Telecom},
 number = {2}
}

Machine learning models have been widely deployed to tackle the problem of radio propagation. In addition to helping in the estimation of path loss, they can also be used to better understand the details of various propagation scenarios. Our current work exploits the inherent ranking of feature importances provided by XGBoost and Random Forest as a means of indicating the contribution of the underlying propagation mechanisms. A comparison between two different transmitter antenna heights, revealing the associated propagation profiles, is made. Feature selection is then implemented, leading to models with reduced complexity, and consequently reduced training and response times, based on the previously calculated importances.

@inbook{
 type = {inbook},
 year = {2020},
 pages = {950-966},
 websites = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-3479-3.ch066},
 id = {161eef54-d120-37eb-a773-16e320c275f7},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2021a},
 private_publication = {false},
 bibtype = {inbook},
 author = {Goudos, Sotirios K.},
 doi = {10.4018/978-1-7998-3479-3.ch066},
 chapter = {Application of biogeography-based optimization to antennas and wireless communications},
 title = {Encyclopedia of Information Science and Technology, Fifth Edition}
}

@inproceedings{
 title = {Dual-Band Single-Layered Modified E-shaped Patch Antenna for RF Energy Harvesting Systems},
 type = {inproceedings},
 year = {2020},
 keywords = {E-shaped patch antenna,energy harvesting,optimization method,radio frequency,salp swarm algorithm},
 pages = {1-4},
 id = {7e34edc9-f961-37c9-8833-4951170f9b38},
 created = {2020-10-30T21:19:07.415Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:54:03.664Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2020a},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {Radio Frequency Energy Harvesting (RF EH) is an alternative, yet well-promising technique to deliver power in electronic circuits of wireless sensor networks that require small amounts of energy. The design of the receiving module (antenna) in RF EH systems is a demanding and, in most cases, a complex task. As a result, an optimization method is often required. In this paper, we apply The Salp Swarm Algorithm to design and optimize a receiving module (dual-band modified E-shaped antenna) for RF EH systems. The proposed antenna operates in the frequency bands of LTE-2600 and 5G NR mobile communication networks. Numerical results exhibit a satisfactory operation of the optimized antenna as a receiving module in an RF EH system.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Papadopoulou, Maria S and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/ECCTD49232.2020.9218354},
 booktitle = {ECCTD 2020 - 24th IEEE European Conference on Circuit Theory and Design}
}

Radio Frequency Energy Harvesting (RF EH) is an alternative, yet well-promising technique to deliver power in electronic circuits of wireless sensor networks that require small amounts of energy. The design of the receiving module (antenna) in RF EH systems is a demanding and, in most cases, a complex task. As a result, an optimization method is often required. In this paper, we apply The Salp Swarm Algorithm to design and optimize a receiving module (dual-band modified E-shaped antenna) for RF EH systems. The proposed antenna operates in the frequency bands of LTE-2600 and 5G NR mobile communication networks. Numerical results exhibit a satisfactory operation of the optimized antenna as a receiving module in an RF EH system.

@inproceedings{
 title = {Waveform Design for Optimal Wireless Power Transfer Using Evolutionary Algorithms},
 type = {inproceedings},
 year = {2020},
 pages = {1-4},
 id = {5b73e836-5c20-3c25-8fd7-c1c4ac7f5185},
 created = {2020-10-30T21:19:07.576Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:17.935Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Doanis2020},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {One of the possible ways to increase the end-to-end power transfer efficiency in a radiative Wireless Power Transfer (WPT) system is by transmitting multi-tone signals optimized according to the receiver rectenna's nonlinear behavior and the Channel State Information (CSI). This optimization problem is a non-convex problem that has been tackled in the past with Sequential Convex Programming (SCP) algorithms. Since SCP algorithms do not guarantee to track the globally optimal solutions, there is interest in applying some other optimization methods to this problem. Here we apply various Evolutionary Algorithms (EAs) with different characteristics. The performance of the designed waveforms is evaluated in Matlab, using a simplified Single Input Single Output (SISO) system model. EAs are successfully applied to waveform design for WPT and seem to track the optimal solutions in the tested cases. Moreover, the effectiveness of the SCP-QCLP method is verified.},
 bibtype = {inproceedings},
 author = {Doanis, P and Boursianis, A D and Huillery, J and Bréard, A and Duroc, Y and Goudos, S K},
 doi = {10.1109/MOCAST49295.2020.9200277},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

One of the possible ways to increase the end-to-end power transfer efficiency in a radiative Wireless Power Transfer (WPT) system is by transmitting multi-tone signals optimized according to the receiver rectenna's nonlinear behavior and the Channel State Information (CSI). This optimization problem is a non-convex problem that has been tackled in the past with Sequential Convex Programming (SCP) algorithms. Since SCP algorithms do not guarantee to track the globally optimal solutions, there is interest in applying some other optimization methods to this problem. Here we apply various Evolutionary Algorithms (EAs) with different characteristics. The performance of the designed waveforms is evaluated in Matlab, using a simplified Single Input Single Output (SISO) system model. EAs are successfully applied to waveform design for WPT and seem to track the optimal solutions in the tested cases. Moreover, the effectiveness of the SCP-QCLP method is verified.

@inproceedings{
 title = {Pareto-Optimal Resource Allocation in Wireless Powered Networks},
 type = {inproceedings},
 year = {2020},
 keywords = {Multi-objective optimization (MOO),Non-orthogonal multiple access (NOMA),Pareto front,Wireless powered networks (WPNs)},
 pages = {1-4},
 id = {e47b990d-25d2-31a6-8911-30970fd847de},
 created = {2020-10-30T21:19:07.603Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:12.922Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Bouzinis2020},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {In this paper, the uplink of a wireless-powered network is investigated. More specifically, we focus on simultaneously maximizing the sum-throughput and minimum throughput of the network's users, for the case of non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA), by optimizing the allocated time to energy harvesting and information transmission. Since this problem belongs to the category of multi-objective optimization, we transform it into a singleobjective problem, via the scalarization approach, aiming to obtain the Pareto Front. The proposed methodology facilitates the evaluation of the trade-off between the considered conflicted metrics. Finally, simulation results validate the effectiveness of the proposed methodology and provide useful insights for the network's performance.},
 bibtype = {inproceedings},
 author = {Bouzinis, Pavlos S and Vranas, Christos K and Papanikolaou, Vasilis K and Diamantoulakis, Panagiotis D and Goudos, Sotirios K and Karagiannidis, George K},
 doi = {10.1109/MOCAST49295.2020.9200276},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020}
}

In this paper, the uplink of a wireless-powered network is investigated. More specifically, we focus on simultaneously maximizing the sum-throughput and minimum throughput of the network's users, for the case of non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA), by optimizing the allocated time to energy harvesting and information transmission. Since this problem belongs to the category of multi-objective optimization, we transform it into a singleobjective problem, via the scalarization approach, aiming to obtain the Pareto Front. The proposed methodology facilitates the evaluation of the trade-off between the considered conflicted metrics. Finally, simulation results validate the effectiveness of the proposed methodology and provide useful insights for the network's performance.

@inproceedings{
 title = {Triple-band Inverted-F Antenna Using QR-OBL TLBO Algorithm for RF Energy Harvesting Applications},
 type = {inproceedings},
 year = {2020},
 keywords = {Inverted-F antenna,Quasi-Reflected Opposition Based Learning,RF energy harvesting,Teaching Learning Optimization Algorithm,optimization method.},
 pages = {1-4},
 id = {ca4d3aad-023b-3a27-b00f-fcda503a2644},
 created = {2020-10-30T21:19:07.669Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:55:13.074Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Karampatea2020},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {Radio Frequency Energy Harvesting (RF EH) is one of the popular emerging techniques in wireless sensor networks that can sufficiently supply low power electronic circuits. With the evolution of Internet of Things (IoT) technology, which exhibits an exponentially positive growth rate over the last years, RF EH can play a primary role in the next-generation wireless networks. In this paper, we apply an optimization technique by utilizing the Quasi-Reflected (QR) variant of opposition Based Learning (OBL) technique in Teaching Learning Based optimization (TLBO) algorithm to design a triple-band Inverted-F antenna (IFA) for RF energy harvesting applications. The proposed antenna is operating in the cellular communication frequency bands of EGSM-900 and GSM-1800, as well as at the Long Term Evolution (LTE) telecommunication networks frequency band of LTE-2600. Simulation results demonstrate that the designed antenna has features of operation which make it suitable for RF EH applications.},
 bibtype = {inproceedings},
 author = {Karampatea, Apostolia and Boursianis, Achilles D and Goudos, Sotirios K and Siakavara, Katherine},
 doi = {10.1109/MOCAST49295.2020.9200251},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020}
}

Radio Frequency Energy Harvesting (RF EH) is one of the popular emerging techniques in wireless sensor networks that can sufficiently supply low power electronic circuits. With the evolution of Internet of Things (IoT) technology, which exhibits an exponentially positive growth rate over the last years, RF EH can play a primary role in the next-generation wireless networks. In this paper, we apply an optimization technique by utilizing the Quasi-Reflected (QR) variant of opposition Based Learning (OBL) technique in Teaching Learning Based optimization (TLBO) algorithm to design a triple-band Inverted-F antenna (IFA) for RF energy harvesting applications. The proposed antenna is operating in the cellular communication frequency bands of EGSM-900 and GSM-1800, as well as at the Long Term Evolution (LTE) telecommunication networks frequency band of LTE-2600. Simulation results demonstrate that the designed antenna has features of operation which make it suitable for RF EH applications.

@inproceedings{
 title = {Machine Learning Model Comparison for Leak Detection in Noisy Industrial Pipelines},
 type = {inproceedings},
 year = {2020},
 keywords = {Data-acquisition,Feature extraction,Leak detection,Machine learning,Model accuracy,Model analysis,Noisy environments},
 pages = {1-4},
 id = {c89eb35c-79ea-327f-9a98-b80fc1cfce97},
 created = {2020-10-30T21:19:07.732Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.659Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kampelopoulos2020},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {In this paper, two machine learning techniques are applied and compared in order to model leak detection in pipelines in noisy environments. A set of accelerometers, mounted on the surface of the pipes, was deployed for the data acquisition process. Measurements of noise during normal operating conditions were recorded as well as measurements of leaks, generated on various distances from the sensors. Using these measurement data, a training set was created from their time-domain and frequency-domain features. The leak detection process is then modeled as a binary classification problem (leak detection or not). For this problem, two machine learning classification techniques were evaluated, the support vector machines and the decision trees. The results for each learner are compared with the original data from the test dataset using representative performance indicators and, overall, high levels of accuracy are achieved.},
 bibtype = {inproceedings},
 author = {Kampelopoulos, Dimitrios and Papastavrou, George N and Kousiopoulos, George P and Karagiorgos, Nikolaos and Goudos, Sotirios K and Nikolaidis, Spyridon},
 doi = {10.1109/MOCAST49295.2020.9200261},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020}
}

In this paper, two machine learning techniques are applied and compared in order to model leak detection in pipelines in noisy environments. A set of accelerometers, mounted on the surface of the pipes, was deployed for the data acquisition process. Measurements of noise during normal operating conditions were recorded as well as measurements of leaks, generated on various distances from the sensors. Using these measurement data, a training set was created from their time-domain and frequency-domain features. The leak detection process is then modeled as a binary classification problem (leak detection or not). For this problem, two machine learning classification techniques were evaluated, the support vector machines and the decision trees. The results for each learner are compared with the original data from the test dataset using representative performance indicators and, overall, high levels of accuracy are achieved.

@inproceedings{
 title = {A Novel Chaotic System with Application to Secure Communications},
 type = {inproceedings},
 year = {2020},
 keywords = {CSK modulation,Chaos,Hidden attractor,Secure communications},
 pages = {1-4},
 id = {c8d3d6dd-c53e-3a9e-9c46-b6d6eb2bb906},
 created = {2020-10-30T21:30:05.381Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2024-10-15T14:38:07.962Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Moysis2020},
 source_type = {INPROCEEDINGS},
 private_publication = {false},
 abstract = {In this work, a novel three dimensional chaotic system with is proposed. The system has no linear terms and a line equilibrium, so it belongs to the category of systems with hidden attractors. The system's dynamical behavior is analysed through its bifurcations diagrams and maximum Lyapunov exponent diagram. Then, the system is applied to the problem of secure communications using the Symmetric Chaos Shift Keying modulation method.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Volos, Christos and Stouboulos, Ioannis and Goudos, Sotirios and Cicek, Serdar and Pham, Viet Thanh and Mishra, Vikas K},
 doi = {10.1109/MOCAST49295.2020.9200286},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020}
}

In this work, a novel three dimensional chaotic system with is proposed. The system has no linear terms and a line equilibrium, so it belongs to the category of systems with hidden attractors. The system's dynamical behavior is analysed through its bifurcations diagrams and maximum Lyapunov exponent diagram. Then, the system is applied to the problem of secure communications using the Symmetric Chaos Shift Keying modulation method.

@article{
 title = {3D Placement of Drone-mounted Remote Radio Head for Minimum Transmission Power under Connectivity Constraints},
 type = {article},
 year = {2020},
 pages = {1},
 id = {a18e7d68-e0f5-3d39-9446-2e97eff60251},
 created = {2020-11-03T11:16:48.098Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9245517},
 source_type = {article},
 private_publication = {false},
 abstract = {Dense small cell deployment in a cloud radio access network (C-RAN) is an effective approach to satisfy the increasing requirements of the emerging fifth generation (5G) mobile networks. Nevertheless, the optimal deployment of small cells is not always possible due to certain limitations, such as the existence of backbone infrastructure and appropriate power supply. In addition, the increased throughput requirements in a certain area may be temporal, such as in the case of an event such as a sports match or a concert. To this end, the leverage of multiple drone-mounted remote radio heads (D-RRHs), coupled with advanced user scheduling and multiplexing schemes, can be a promising asset in provisioning an on-demand and dynamic C-RAN. Nevertheless, finding the optimal placement of the D-RRHs, under certain quality of service (QoS) constraints can be challenging. In this work, we propose a D-RRH placement approach that minimizes the transmission power by optimally placing the D-RRH. We formulate the placement optimization problem and decouple it into two separate sub-problems, namely the horizontal placement and the vertical placement problems. An implementation of the Weiszfeld algorithm is utilized in order to solve the horizontal placement problem by finding the point that minimizes the sum distances. The vertical placement problem is calculated as a function of the optimal elevation angle and the radius of the coverage area. In order to evaluate the performance of the proposed approach, we carried out extensive evaluations and compare our proposed approach against two similar approaches. The evaluation results show the feasibility of the proposed approach in minimizing the required transmission power and maintaining fairly good performance in terms of user connectivity.},
 bibtype = {article},
 author = {Pliatsios, D and Sarigiannidis, P and Goudos, S K and Psannis, K},
 doi = {10.1109/ACCESS.2020.3034881},
 journal = {IEEE Access}
}

Dense small cell deployment in a cloud radio access network (C-RAN) is an effective approach to satisfy the increasing requirements of the emerging fifth generation (5G) mobile networks. Nevertheless, the optimal deployment of small cells is not always possible due to certain limitations, such as the existence of backbone infrastructure and appropriate power supply. In addition, the increased throughput requirements in a certain area may be temporal, such as in the case of an event such as a sports match or a concert. To this end, the leverage of multiple drone-mounted remote radio heads (D-RRHs), coupled with advanced user scheduling and multiplexing schemes, can be a promising asset in provisioning an on-demand and dynamic C-RAN. Nevertheless, finding the optimal placement of the D-RRHs, under certain quality of service (QoS) constraints can be challenging. In this work, we propose a D-RRH placement approach that minimizes the transmission power by optimally placing the D-RRH. We formulate the placement optimization problem and decouple it into two separate sub-problems, namely the horizontal placement and the vertical placement problems. An implementation of the Weiszfeld algorithm is utilized in order to solve the horizontal placement problem by finding the point that minimizes the sum distances. The vertical placement problem is calculated as a function of the optimal elevation angle and the radius of the coverage area. In order to evaluate the performance of the proposed approach, we carried out extensive evaluations and compare our proposed approach against two similar approaches. The evaluation results show the feasibility of the proposed approach in minimizing the required transmission power and maintaining fairly good performance in terms of user connectivity.

@article{
 title = {Combined Ray-tracing/FDTD and Network planner methods for the design of massive MIMO networks},
 type = {article},
 year = {2020},
 pages = {206371-206387},
 volume = {8},
 id = {a5920c42-b819-3e77-9e15-bec2708c8751},
 created = {2020-11-03T11:16:48.108Z},
 file_attached = {false},
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 last_modified = {2023-02-11T16:55:13.533Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9246544},
 source_type = {article},
 private_publication = {false},
 abstract = {The design of a massive MIMO network requires a channel model that captures the Spatio-temporal dimensions of the propagation environment. In this paper, we propose a novel method combining Hybrid Raytracing - Finite difference time domain (FDTD) and network planner tools to address this requirement. This method provides accurate and realistic EMF exposure models for the design of a massive MIMO network. Using this method, we proceed with the optimization of the BS's locations under the low power consumption and low EMF exposure constraints. Assuming equal preference of the optimization objectives, the simulations show that the uplink localized 10g dose appears to be the dominant factor of the localized 10g EMF exposure. Moreover, a massive MIMO network designed to serve 224 simultaneous active users at the same time-frequency resource is subject to an increase of the total whole-body dose (2 times higher in downlink and +18% in uplink), compared to a design with 14 active users. However, in the same conditions, the downlink localized 10g dose reduces (20 times lower) whereas the uplink localized 10g dose increases (+23%) in comparison with the scenario with fewer users (14). Besides, the electromagnetic field strength in all locations obtained with this new method is 2 times weaker compared to a 4G LTE network, while complying with the international guidelines.},
 bibtype = {article},
 author = {Matalatala, M and Shikhantsov, S and Deruyck, M and Tanghe, E and Plets, D and Goudos, S and Martens, L and Joseph, W},
 doi = {10.1109/ACCESS.2020.3035317},
 journal = {IEEE Access}
}

The design of a massive MIMO network requires a channel model that captures the Spatio-temporal dimensions of the propagation environment. In this paper, we propose a novel method combining Hybrid Raytracing - Finite difference time domain (FDTD) and network planner tools to address this requirement. This method provides accurate and realistic EMF exposure models for the design of a massive MIMO network. Using this method, we proceed with the optimization of the BS's locations under the low power consumption and low EMF exposure constraints. Assuming equal preference of the optimization objectives, the simulations show that the uplink localized 10g dose appears to be the dominant factor of the localized 10g EMF exposure. Moreover, a massive MIMO network designed to serve 224 simultaneous active users at the same time-frequency resource is subject to an increase of the total whole-body dose (2 times higher in downlink and +18% in uplink), compared to a design with 14 active users. However, in the same conditions, the downlink localized 10g dose reduces (20 times lower) whereas the uplink localized 10g dose increases (+23%) in comparison with the scenario with fewer users (14). Besides, the electromagnetic field strength in all locations obtained with this new method is 2 times weaker compared to a 4G LTE network, while complying with the international guidelines.

@inproceedings{
 title = {Modified Printed Bow-Tie Antenna for RF Energy Harvesting Applications},
 type = {inproceedings},
 year = {2020},
 pages = {67-71},
 volume = {1},
 id = {f43c0f11-c2b0-3d05-8074-c9a8c5095644},
 created = {2020-12-22T20:40:32.141Z},
 file_attached = {false},
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 authored = {true},
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 citation_key = {9245049},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {As the power requirements of electronic systems in wireless sensor networks are progressively reducing, radio frequency (RF) energy harvesting (EH) technique is becoming increasingly interesting during the last years. In this paper, we design and optimize a modified printed bow-tie antenna, operating in the frequency band of 5G NR mobile communication networks. For the optimization process, we have selected the Monarch Butterfly Algorithm that combines swarm intelligence and evolutionary characteristics. Computed results exhibit a quite acceptable performance of the optimized antenna as an RF energy harvester in the desired frequency band.},
 bibtype = {inproceedings},
 author = {Boursianis, A D and Papadopoulou, M S and Nikolaidis, S and Goudos, S K},
 doi = {10.1109/MTTW51045.2020.9245049},
 booktitle = {2020 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW)}
}

As the power requirements of electronic systems in wireless sensor networks are progressively reducing, radio frequency (RF) energy harvesting (EH) technique is becoming increasingly interesting during the last years. In this paper, we design and optimize a modified printed bow-tie antenna, operating in the frequency band of 5G NR mobile communication networks. For the optimization process, we have selected the Monarch Butterfly Algorithm that combines swarm intelligence and evolutionary characteristics. Computed results exhibit a quite acceptable performance of the optimized antenna as an RF energy harvester in the desired frequency band.

@inproceedings{
 title = {Dual-Band Rectifier Design for Ambient RF Energy Harvesting},
 type = {inproceedings},
 year = {2020},
 pages = {7-11},
 id = {f0c872fe-cfcd-3032-a496-dc417a961ddc},
 created = {2020-12-22T20:40:32.147Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:17.846Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9275569},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The design of a wireless sensor network (WSN) has several key points to consider. Power management and battery charging, especially when is applied in a harsh environment, are crucial parameters. In this paper, we present an RF energy harvesting system that converts ambient AC electromagnetic energy into DC voltage, which is applicable to supply low power devices. The circuit harvests and reuses ambient wireless energy for several applications. The proposed system resonates in the frequency bands of 4G (2.67 GHz) and 5G (3.591 GHz) mobile communication systems. Numerical results demonstrate that the overall system in a two-tone signal exhibits maximum power conversion efficiency equal to 78.1%, when the load of the circuit is 2 kOhms and the input power reaches 6 dBm. In a single-tone configuration, the maximum achieved efficiency is 56.11% at 2.67 GHz and 57.95% at 3.591 GHz, accordingly.},
 bibtype = {inproceedings},
 author = {Papadopoulou, M S and Boursianis, A D and Goudos, S K and Psannis, K},
 doi = {10.1109/WSCE51339.2020.9275569},
 booktitle = {2020 3rd World Symposium on Communication Engineering (WSCE)}
}

The design of a wireless sensor network (WSN) has several key points to consider. Power management and battery charging, especially when is applied in a harsh environment, are crucial parameters. In this paper, we present an RF energy harvesting system that converts ambient AC electromagnetic energy into DC voltage, which is applicable to supply low power devices. The circuit harvests and reuses ambient wireless energy for several applications. The proposed system resonates in the frequency bands of 4G (2.67 GHz) and 5G (3.591 GHz) mobile communication systems. Numerical results demonstrate that the overall system in a two-tone signal exhibits maximum power conversion efficiency equal to 78.1%, when the load of the circuit is 2 kOhms and the input power reaches 6 dBm. In a single-tone configuration, the maximum achieved efficiency is 56.11% at 2.67 GHz and 57.95% at 3.591 GHz, accordingly.

@article{
 title = {A Novel Chaotic System with a Line Equilibrium: Analysis and Its Applications to Secure Communication and Random Bit Generation},
 type = {article},
 year = {2020},
 pages = {283–296},
 volume = {1},
 id = {85a19f7f-cb17-396f-98d0-c30d4a8ae5d7},
 created = {2020-12-22T20:40:32.324Z},
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 last_modified = {2023-02-11T18:08:48.956Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {moysis2020a},
 source_type = {article},
 private_publication = {false},
 abstract = {In this study, a novel two-parameter, three-dimensional chaotic system is constructed. The system has no linear terms and its equilibrium is a line, so it is a system with hidden attractors. The system is first studied by computation of its bifurcation diagrams and diagram of Lyapunov exponents. Then, the system is applied to two encryption related problems. First, the problem of secure communications is considered, using the symmetric chaos shift keying modulation method. Here, the states of the chaotic system are combined with a binary information signal in order to mask it, safely transmit it through a communication channel, and successfully reconstruct the information at the receiver end. In the second problem, the states of the system are utilized to design a simple rule to generate a bit sequence that possesses random properties, and is thus suitable for encryption related applications. For both applications, simulations are performed through Matlab to verify the soundness of the designs.},
 bibtype = {article},
 author = {Moysis, Lazaros and Volos, Christos and Stouboulos, Ioannis and Goudos, Sotirios and Çiçek, Serdar and Pham, Viet-Thanh and Mishra, Vikas K},
 journal = {Telecom},
 number = {3}
}

In this study, a novel two-parameter, three-dimensional chaotic system is constructed. The system has no linear terms and its equilibrium is a line, so it is a system with hidden attractors. The system is first studied by computation of its bifurcation diagrams and diagram of Lyapunov exponents. Then, the system is applied to two encryption related problems. First, the problem of secure communications is considered, using the symmetric chaos shift keying modulation method. Here, the states of the chaotic system are combined with a binary information signal in order to mask it, safely transmit it through a communication channel, and successfully reconstruct the information at the receiver end. In the second problem, the states of the system are utilized to design a simple rule to generate a bit sequence that possesses random properties, and is thus suitable for encryption related applications. For both applications, simulations are performed through Matlab to verify the soundness of the designs.

@inproceedings{
 title = {State-of-the-Art Technologies in RF Energy Harvesting Circuits – A Review},
 type = {inproceedings},
 year = {2020},
 pages = {18-22},
 id = {a597a66d-fa7f-3001-9367-edc1126613d5},
 created = {2020-12-22T20:40:32.327Z},
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 last_modified = {2023-02-11T16:29:17.611Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9275507},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Nowadays electricity is undoubtedly one of the most important goods. Over the years, the dependence of people on electrical devices has sharply increased. The need for continuous use of these devices has created greater demand for electricity as well as more efficient transmission techniques. Environmental energy scavenging, as well as wireless transmission, is an increasing research field during the last years. The use of Radio Frequency (RF) Energy Harvesting (EH) technique contributes to the development of autonomous energy devices and sensors, to reduce the need of supplying them with power by using batteries or the mains. In this paper, the state-of-the-art technologies of radio frequency energy harvesting are discussed and analyzed.},
 bibtype = {inproceedings},
 author = {Bougas, I D and Papadopoulou, M S and Psannis, K and Sarigiannidis, P and Goudos, S K},
 doi = {10.1109/WSCE51339.2020.9275507},
 booktitle = {2020 3rd World Symposium on Communication Engineering (WSCE)}
}

Nowadays electricity is undoubtedly one of the most important goods. Over the years, the dependence of people on electrical devices has sharply increased. The need for continuous use of these devices has created greater demand for electricity as well as more efficient transmission techniques. Environmental energy scavenging, as well as wireless transmission, is an increasing research field during the last years. The use of Radio Frequency (RF) Energy Harvesting (EH) technique contributes to the development of autonomous energy devices and sensors, to reduce the need of supplying them with power by using batteries or the mains. In this paper, the state-of-the-art technologies of radio frequency energy harvesting are discussed and analyzed.

@inproceedings{
 title = {Multiband Patch Antenna Design for RF Energy Harvesting Applications Using Coyote Optimization Algorithm},
 type = {inproceedings},
 year = {2020},
 id = {c81b204e-fcdf-3c2e-80b6-224e4a34d408},
 created = {2023-01-02T11:46:06.174Z},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Eucap2020B},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Radio frequency energy harvesting is a relatively recent and quite interesting technique for delivering adequate amounts of energy in low power consumption wireless networks. This technique faces several challenges, with most of them are related to the antenna design of the harvesting system. In this paper, we address to these challenges by designing a multiband microstrip patch antenna with three slits. The proposed antenna operates in the LoRaWAN (Long RangeWide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Numerical results demonstrate a satisfactory performance of the proposed patch antenna as an energy harvester in radio frequency environments.},
 bibtype = {inproceedings},
 author = {Boursianis, A D and Georgoulas, D and Papadopoulou, M and Karampatea, A and S, M and Pierezan, J and Mariani, V C and Coelho, L S and Siakavara, A and Goudos, S K},
 booktitle = {14th European Conference on Antennas and Propagation, EuCAP 2020}
}

Radio frequency energy harvesting is a relatively recent and quite interesting technique for delivering adequate amounts of energy in low power consumption wireless networks. This technique faces several challenges, with most of them are related to the antenna design of the harvesting system. In this paper, we address to these challenges by designing a multiband microstrip patch antenna with three slits. The proposed antenna operates in the LoRaWAN (Long RangeWide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Numerical results demonstrate a satisfactory performance of the proposed patch antenna as an energy harvester in radio frequency environments.

@inproceedings{
 title = {MIMO Antenna Design for 5G Communication Systems Using Salp Swarm Algorithm},
 type = {inproceedings},
 year = {2020},
 keywords = {5G mobile communications;bow tie antenna;MIMO ante},
 pages = {1-3},
 id = {5ad9d891-8d34-3663-a8b5-d378d18b32bc},
 created = {2023-02-11T16:29:15.624Z},
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 last_modified = {2023-02-11T16:29:15.624Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9083886},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Multiple Input Multiple Output (MIMO) antennas will be a part of every new user device in 5G networks. In this paper, we design a MIMO antenna for 5G networks using a nature-inspired algorithm, namely the Salp Swarm Algorithm (SSA). We select a bow tie antenna as the element of the MIMO operating in n257 frequency band (center frequency at 28GHz). Firstly, we design and optimize the antenna element using the SSA algorithm. Secondly, a MIMO antenna is designed using the optimal dimensions of the antenna element. Numerical results demonstrate that the proposed MIMO antenna has a small size and exhibits wideband operation in the desired frequency band.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Goudos, Sotirios K and Yioultsis, Traianos V and Siakavara, Katherine and Rocca, Paolo},
 doi = {10.1109/iWAT48004.2020.1570618331},
 booktitle = {2020 International Workshop on Antenna Technology (iWAT)}
}

Multiple Input Multiple Output (MIMO) antennas will be a part of every new user device in 5G networks. In this paper, we design a MIMO antenna for 5G networks using a nature-inspired algorithm, namely the Salp Swarm Algorithm (SSA). We select a bow tie antenna as the element of the MIMO operating in n257 frequency band (center frequency at 28GHz). Firstly, we design and optimize the antenna element using the SSA algorithm. Secondly, a MIMO antenna is designed using the optimal dimensions of the antenna element. Numerical results demonstrate that the proposed MIMO antenna has a small size and exhibits wideband operation in the desired frequency band.

@inproceedings{
 title = {Dual-Band RF-to-DC Rectifier with High Efficiency for RF Energy Harvesting Applications},
 type = {inproceedings},
 year = {2020},
 keywords = {Radio frequency;Dual band;Schottky diodes;Impedanc},
 pages = {1-4},
 id = {ff74cbd8-d08d-37b8-a0d7-cc29f74bc0aa},
 created = {2023-02-11T16:29:15.628Z},
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 last_modified = {2023-02-11T16:29:15.628Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9200262},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Radio Frequency (RF) energy harvesting is emerging as a potentially reliable method to replace the costly and, difficult to maintain, source of low-power wireless sensors networks. In this paper, a dual-band RF-to-DC rectifier, that operates at LoRaWAN and GSM-900 cellular communication frequency bands, is presented. The system is composed of an impedance matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low power devices, and an output load. The proposed system resonates at two different frequencies of 866 MHz and 937 MHz. Numerical results demonstrate that the overall system exhibits an efficiency of 80% with 4.32 V of output voltage at 0 dBm of input power.},
 bibtype = {inproceedings},
 author = {Papadopoulou, Maria S and Boursianis, Achilles D and Skoufa, Anastasia and Volos, Christos K and Stouboulos, Ioannis N and Nikolaidis, Spyridon and Goudos, Sotirios K},
 doi = {10.1109/MOCAST49295.2020.9200262},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

Radio Frequency (RF) energy harvesting is emerging as a potentially reliable method to replace the costly and, difficult to maintain, source of low-power wireless sensors networks. In this paper, a dual-band RF-to-DC rectifier, that operates at LoRaWAN and GSM-900 cellular communication frequency bands, is presented. The system is composed of an impedance matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low power devices, and an output load. The proposed system resonates at two different frequencies of 866 MHz and 937 MHz. Numerical results demonstrate that the overall system exhibits an efficiency of 80% with 4.32 V of output voltage at 0 dBm of input power.

@inproceedings{
 title = {Big Data against Security Threats: The SPEAR Intrusion Detection System},
 type = {inproceedings},
 year = {2020},
 keywords = {Smart grids;Big Data;Feature extraction;Intrusion},
 pages = {12-17},
 id = {40dfb634-7d92-36f1-9c18-248f08a63bab},
 created = {2023-02-11T16:29:15.757Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:15.757Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9275580},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The environmental concerns, the limited availability of conventional energy sources, the integration of alternative energy sources and the increasing number of power-demanding appliances change the way electricity is generated and distributed. Smart Grid (SG) is an appealing concept, which was developed in response to the emerging issues of electricity generation and distribution. By leveraging the latest advancements of Information and Communication Technologies (ICT), it offers significant benefits to energy providers, retailers and consumers. Nevertheless, SG is vulnerable to cyber attacks, that could cause critical economic and ecological consequences. Traditional Intrusion Detection Systems (IDSs) are becoming less efficient in detecting and mitigating cyberattacks, due to their limited capabilities of analyzing the exponentially increasing volume of network traffic. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) platform, which features a Big Data enabled IDS that timely detects and identifies cyber attacks against SG components. In order to validate the efficiency of the SPEAR platform regarding the protection of critical infrastructure, we installed the platform in a small wind power plant.},
 bibtype = {inproceedings},
 author = {Pliatsios, Dimitrios and Sarigiannidis, Panagiotis and Psannis, Konstantinos and Goudos, Sotirios K and Vitsas, Vasileios and Moscholios, Ioannis},
 doi = {10.1109/WSCE51339.2020.9275580},
 booktitle = {2020 3rd World Symposium on Communication Engineering (WSCE)}
}

The environmental concerns, the limited availability of conventional energy sources, the integration of alternative energy sources and the increasing number of power-demanding appliances change the way electricity is generated and distributed. Smart Grid (SG) is an appealing concept, which was developed in response to the emerging issues of electricity generation and distribution. By leveraging the latest advancements of Information and Communication Technologies (ICT), it offers significant benefits to energy providers, retailers and consumers. Nevertheless, SG is vulnerable to cyber attacks, that could cause critical economic and ecological consequences. Traditional Intrusion Detection Systems (IDSs) are becoming less efficient in detecting and mitigating cyberattacks, due to their limited capabilities of analyzing the exponentially increasing volume of network traffic. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) platform, which features a Big Data enabled IDS that timely detects and identifies cyber attacks against SG components. In order to validate the efficiency of the SPEAR platform regarding the protection of critical infrastructure, we installed the platform in a small wind power plant.

@inproceedings{
 title = {Chaotic Motion Control of a Mobile Robot Using a Memory Technique},
 type = {inproceedings},
 year = {2020},
 keywords = {Robots;Chaotic communication;Generators;Physics;Co},
 pages = {506-511},
 id = {f8ee1941-066c-36a2-8764-2cdbcadab96b},
 created = {2023-02-11T16:29:15.760Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:15.760Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9259721},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work addresses the problem of chaotic path planning, using a memory technique to improve performance. In this application, the dynamics of a chaotic system are utilized to generate a series of navigation commands using a simple rule. These commands are then used by an autonomous robot to explore an area. This navigation strategy can bring overall area coverage, but with numerous revisits to the same cells. Here, a memory technique is applied to limit the chaotic motion to cells with the least number of visits, leading to overall improvement in performance. Numerical simulations are performed to evaluate the path planning strategy.},
 bibtype = {inproceedings},
 author = {Petavratzis, Eleftherios and Moysis, Lazaros and Volos, Christos and Gupta, Mahendra Kumar and Stouboulos, Ioannis and Goudos, Sotirios},
 doi = {10.1109/ICSTCC50638.2020.9259721},
 booktitle = {2020 24th International Conference on System Theory, Control and Computing (ICSTCC)}
}

This work addresses the problem of chaotic path planning, using a memory technique to improve performance. In this application, the dynamics of a chaotic system are utilized to generate a series of navigation commands using a simple rule. These commands are then used by an autonomous robot to explore an area. This navigation strategy can bring overall area coverage, but with numerous revisits to the same cells. Here, a memory technique is applied to limit the chaotic motion to cells with the least number of visits, leading to overall improvement in performance. Numerical simulations are performed to evaluate the path planning strategy.

@inproceedings{
 title = {Dualband Patch Antenna Design Using Binary Grey Wolf Optimizer},
 type = {inproceedings},
 year = {2020},
 keywords = {Patch antennas;Meetings;Dual band;Evolutionary com},
 pages = {1777-1778},
 id = {f2347984-b3db-3de8-8701-03853db45671},
 created = {2023-02-11T16:29:15.768Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:15.768Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9330100},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Various antenna design problems are discrete-valued. To address these problems, binary-coded algorithms suited for combinatorial optimization problems are required. Grey Wolf Optimizer (GWO) is a recently proposed evolutionary algorithm based on grey wolves' behavior. Although GWO was originally designed for real-valued problems, discrete versions also exist. In this paper, we apply a binary GWO algorithm (bGWO) for arbitrary-shaped dual-band patch antenna design. Computational results demonstrate that bGWO is quite efficient and can be further applied to discrete valued problems in electromagnetics.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Boursianis, Achilles and Salucci, Marco and Rocca, Paolo},
 doi = {10.1109/IEEECONF35879.2020.9330100},
 booktitle = {2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting}
}

Various antenna design problems are discrete-valued. To address these problems, binary-coded algorithms suited for combinatorial optimization problems are required. Grey Wolf Optimizer (GWO) is a recently proposed evolutionary algorithm based on grey wolves' behavior. Although GWO was originally designed for real-valued problems, discrete versions also exist. In this paper, we apply a binary GWO algorithm (bGWO) for arbitrary-shaped dual-band patch antenna design. Computational results demonstrate that bGWO is quite efficient and can be further applied to discrete valued problems in electromagnetics.

@inproceedings{
 title = {Modified Patch Antenna Design Using Moth Search Algorithm for RF Energy Harvesting Applications},
 type = {inproceedings},
 year = {2020},
 keywords = {patch antenna;RF energy harvesting;moth search alg},
 pages = {1-3},
 id = {c52d292b-8c9d-35e4-a753-fed0f491b482},
 created = {2023-02-11T16:29:15.805Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:15.805Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9083891},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Radio frequency energy harvesting is a well-promising technique to power wireless sensor network devices that require small amounts of energy to operate. It can be utilized as an alternative technique for power-constrained systems, such as wireless sensor networks with limited battery lifetime, by extending their energy supply. In outdoor environments, the dominant ambient radio wave sources are the broadcasting and the mobile communication networks. In this paper, we apply an optimization technique by utilizing Moth Search algorithm to design a modified microstrip patch antenna of three varying slots. The proposed antenna exhibits tuning operation in the LoRa (Long Range) and the cellular communications frequency bands of GSM-1800 and UMTS. Numerical results exhibit an acceptable performance of the proposed antenna for RF energy harvesting applications.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Koulouridis, Stavros and Rocca, Paolo and Goudos, Sotirios K},
 doi = {10.1109/iWAT48004.2020.1570609565},
 booktitle = {2020 International Workshop on Antenna Technology (iWAT)}
}

Radio frequency energy harvesting is a well-promising technique to power wireless sensor network devices that require small amounts of energy to operate. It can be utilized as an alternative technique for power-constrained systems, such as wireless sensor networks with limited battery lifetime, by extending their energy supply. In outdoor environments, the dominant ambient radio wave sources are the broadcasting and the mobile communication networks. In this paper, we apply an optimization technique by utilizing Moth Search algorithm to design a modified microstrip patch antenna of three varying slots. The proposed antenna exhibits tuning operation in the LoRa (Long Range) and the cellular communications frequency bands of GSM-1800 and UMTS. Numerical results exhibit an acceptable performance of the proposed antenna for RF energy harvesting applications.

@inproceedings{
 title = {Joint User Association and Power Allocation Using Swarm Intelligence Algorithms in Non-Orthogonal Multiple Access Networks},
 type = {inproceedings},
 year = {2020},
 keywords = {NOMA;Resource management;Interference;Silicon carb},
 pages = {1-4},
 id = {a1b1b843-4718-3113-b96d-97eddc84bab1},
 created = {2023-02-11T16:29:15.808Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:15.808Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9200248},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In this paper, we address the problem of joint user association and power allocation for non-orthogonal multiple access (NOMA) networks with multiple base stations (BSs). A user grouping procedure into orthogonal clusters, as well as an allocation of different physical resource blocks (PRBs) is considered. The problem of interest is mathematically described using the maximization of the weighted sum rate. We apply two different swarm intelligence algorithms, namely, the recently introduced Grey Wolf Optimizer (GWO), and the popular Particle Swarm Optimization (PSO), in order to solve this problem. Numerical results demonstrate that the above-described problem can be satisfactorily addressed by both algorithms.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Diamantoulakis, Panagiotis D and Boursianis, Achilles D and Papanikolaou, Vasilis K and Karagiannidis, George K},
 doi = {10.1109/MOCAST49295.2020.9200248},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

In this paper, we address the problem of joint user association and power allocation for non-orthogonal multiple access (NOMA) networks with multiple base stations (BSs). A user grouping procedure into orthogonal clusters, as well as an allocation of different physical resource blocks (PRBs) is considered. The problem of interest is mathematically described using the maximization of the weighted sum rate. We apply two different swarm intelligence algorithms, namely, the recently introduced Grey Wolf Optimizer (GWO), and the popular Particle Swarm Optimization (PSO), in order to solve this problem. Numerical results demonstrate that the above-described problem can be satisfactorily addressed by both algorithms.

@inproceedings{
 title = {A LoRaWAN-based IoT Platform for Smart Irrigation in Olive Groves - Abstract},
 type = {inproceedings},
 year = {2020},
 pages = {213-214},
 volume = {2761},
 websites = {http://ceur-ws.org/Vol-2761/HAICTA%5C_2020%5C_paper32.pdf},
 publisher = {CEUR-WS.org},
 series = {CEUR Workshop Proceedings},
 id = {811adcc5-bd42-3301-b5f4-c2db244d84e8},
 created = {2023-02-11T20:58:33.389Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T20:58:33.389Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {DBLP:conf/haicta/Liopa-Tsakalidi20},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Irrigation is the major cause of water consumption in agriculture. It contributes to
increasing crop productivity, but it is also a means to the preservation of water
resources. Therefore, advancing the rational exploitation of water through smart
irrigation in agriculture is essential for improving crop yield, decreasing costs, and
contributing to environmental sustainability. The intense use of Information and
Communication Technologies (ICT) has the potential to reduce the amount of water
supplied to the crop. The Internet of Things (IoT) is the natural choice for irrigation
applications, even though the integration of different hardware, software and
connectivity technologies required for making it work seamlessly in practice, while
keeping the cost at reasonable levels, is still at an early stage. Low-Power Wide-Area
Access (LPWA) is considered an emerging class of connectivity technology,
encompassing radio protocols capable of covering large geographic areas, while
delivering multiple years of operation for devices running on batteries with a single
charge. LPWA technologies have the potential to provide a step change in the
enablement of energy efficient IoT applications. In this respect, LPWA networks are
currently one of the most suitable approach for end-to-end connectivity in the farming
domain. LoRaWAN is probably one of the most promising LPWA technologies,
which offers long range, low power consumption, and secure data transmission, over
license-free frequency bands. It can achieve data transmission ranges up to 15 km in
open areas using a single gateway, and is supported by a wide community of industrial
players, academics, IoT makers, and software developers.},
 bibtype = {inproceedings},
 author = {Liopa-Tsakalidi, Aglaia and Thomopoulos, Vasileios and Barouchas, Pantelis and Boursianis, Achilles and Goudos, Sotirios K and Kalamaras, Georgios and Karydas, Stathis and Gotsis, Antonis G and Maliatsos, Konstantinos},
 editor = {Vlontzos, George and Koutsou, Stavriani},
 booktitle = {Proceedings of the 9th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2020), Thessaloniki, Greece, September 24-27, 2020}
}

Irrigation is the major cause of water consumption in agriculture. It contributes to increasing crop productivity, but it is also a means to the preservation of water resources. Therefore, advancing the rational exploitation of water through smart irrigation in agriculture is essential for improving crop yield, decreasing costs, and contributing to environmental sustainability. The intense use of Information and Communication Technologies (ICT) has the potential to reduce the amount of water supplied to the crop. The Internet of Things (IoT) is the natural choice for irrigation applications, even though the integration of different hardware, software and connectivity technologies required for making it work seamlessly in practice, while keeping the cost at reasonable levels, is still at an early stage. Low-Power Wide-Area Access (LPWA) is considered an emerging class of connectivity technology, encompassing radio protocols capable of covering large geographic areas, while delivering multiple years of operation for devices running on batteries with a single charge. LPWA technologies have the potential to provide a step change in the enablement of energy efficient IoT applications. In this respect, LPWA networks are currently one of the most suitable approach for end-to-end connectivity in the farming domain. LoRaWAN is probably one of the most promising LPWA technologies, which offers long range, low power consumption, and secure data transmission, over license-free frequency bands. It can achieve data transmission ranges up to 15 km in open areas using a single gateway, and is supported by a wide community of industrial players, academics, IoT makers, and software developers.

@article{
 title = {Joint power allocation and user association in non-orthogonal multiple access networks: An evolutionary approach},
 type = {article},
 year = {2019},
 keywords = {5G,Evolutionary algorithms,NOMA,Non-orthogonal multiple access,Power control,User association},
 volume = {37},
 id = {763fb5d0-03c4-3c3e-8fa0-d7fef5616e9c},
 created = {2020-02-29T16:57:41.756Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:45.805Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Goudos2019g},
 private_publication = {false},
 abstract = {© 2019 Elsevier B.V. In this paper, the problem of joint power allocation and user association is studied for non-orthogonal multiple access (NOMA) downlink networks with multiple base stations (BSs). We consider that users are grouped into orthogonal clusters to allocate into different physical resource blocks (PRBs). The problem is formulated using two different utility functions. The first is the maximization of the weighted sum rate and the other is the maximization of the minimum achievable user rate. We apply two different evolutionary algorithms in order to solve this problem. Namely, the recently introduced Salp Swarm Algorithm (SSA) and the popular Particle Swarm Optimization (PSO). The simulation results show that the above-described problem can be effectively solved by both algorithms. SSA is more efficient in average than PSO. The effect of increasing the number of user is also studied. In this case the problem becomes more difficult to solve, which indicates that more network resources are required.},
 bibtype = {article},
 author = {Goudos, S.K.},
 doi = {10.1016/j.phycom.2019.100841},
 journal = {Physical Communication}
}

© 2019 Elsevier B.V. In this paper, the problem of joint power allocation and user association is studied for non-orthogonal multiple access (NOMA) downlink networks with multiple base stations (BSs). We consider that users are grouped into orthogonal clusters to allocate into different physical resource blocks (PRBs). The problem is formulated using two different utility functions. The first is the maximization of the weighted sum rate and the other is the maximization of the minimum achievable user rate. We apply two different evolutionary algorithms in order to solve this problem. Namely, the recently introduced Salp Swarm Algorithm (SSA) and the popular Particle Swarm Optimization (PSO). The simulation results show that the above-described problem can be effectively solved by both algorithms. SSA is more efficient in average than PSO. The effect of increasing the number of user is also studied. In this case the problem becomes more difficult to solve, which indicates that more network resources are required.

@article{
 title = {Application of an Ensemble Method to UAV Power Modeling for Cellular Communications},
 type = {article},
 year = {2019},
 keywords = {Bagging,boosting,ensemble learning,machine learning,mobile communications,unmanned aerial vehicle (UAV)},
 pages = {2340-2344},
 volume = {18},
 id = {2ccc581a-afcb-3e46-91ff-1b19f9b1a718},
 created = {2020-02-29T16:57:41.990Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.736Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019f},
 private_publication = {false},
 abstract = {In this letter, we apply ensemble learning methods for the prediction of the ground (cellular base station) to air (flying node) received signal strength (RSS) at different heights, for future mobile communications. We model the RSS using different ensemble methods. Moreover, we propose a new ensemble method that combines results from five different methods. The proposed method also uses a recently introduced evolutionary algorithm, the Salp Swarm Algorithm, for weight optimization. The proposed method outperforms all the other methods and common ensemble methods. In this context, the produced results are compared to measurements using representative performance indices and exhibit satisfactory accuracy.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Athanasiadou, Georgia},
 doi = {10.1109/LAWP.2019.2926784},
 journal = {IEEE Antennas and Wireless Propagation Letters},
 number = {11}
}

In this letter, we apply ensemble learning methods for the prediction of the ground (cellular base station) to air (flying node) received signal strength (RSS) at different heights, for future mobile communications. We model the RSS using different ensemble methods. Moreover, we propose a new ensemble method that combines results from five different methods. The proposed method also uses a recently introduced evolutionary algorithm, the Salp Swarm Algorithm, for weight optimization. The proposed method outperforms all the other methods and common ensemble methods. In this context, the produced results are compared to measurements using representative performance indices and exhibit satisfactory accuracy.

@inproceedings{
 title = {Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks},
 type = {inproceedings},
 year = {2019},
 keywords = {artificial neural networks,path loss prediction,radio propagation,random forests},
 id = {26283152-f0cc-30b0-8062-d06652933f21},
 created = {2020-02-29T16:57:42.173Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.289Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2019},
 private_publication = {false},
 abstract = {The prediction of propagation path loss is of great importance for all aspects of mobile communication. Machine learning methods, such as Artificial Neural Networks and Random Forests, can play a key role for its estimation. A comparison between the two methods for the frequencies of 900 MHz and 1800 MHz is being carried out in the work at hand. Both methods led to similar results.},
 bibtype = {inproceedings},
 author = {Sotiroudis, Sotirios P. and Goudos, Sotirios K. and Siakavara, Katherine},
 doi = {10.1109/MOCAST.2019.8741751},
 booktitle = {2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019}
}

The prediction of propagation path loss is of great importance for all aspects of mobile communication. Machine learning methods, such as Artificial Neural Networks and Random Forests, can play a key role for its estimation. A comparison between the two methods for the frequencies of 900 MHz and 1800 MHz is being carried out in the work at hand. Both methods led to similar results.

@inproceedings{
 title = {Modelling Received Signal Power in Modern Mobile Communications with UAVs Using Ensemble Learning},
 type = {inproceedings},
 year = {2019},
 keywords = {UAV,bagging,boosting.,ensemble learing,mobile communications},
 id = {42bb84ee-54b8-3f98-abf6-ee53ac49cd3c},
 created = {2020-02-29T16:57:42.220Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.943Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019e},
 private_publication = {false},
 abstract = {In this paper, we apply ensemble learning methods for the prediction of received signal strength (RSS) in mobile communications The training set is obtained by experimental data measurements taken from a unmanned aerial vehicle (UAV). We model the RSS using two different ensemble methods. One of these achieves better performance than a neural network in previous work. In this context, the produced results are compared to measurements using representative performance indices and exhibit satisfactory accuracy.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Tsoulos, George V. and Athanasiadou, Georgia},
 booktitle = {13th European Conference on Antennas and Propagation, EuCAP 2019}
}

In this paper, we apply ensemble learning methods for the prediction of received signal strength (RSS) in mobile communications The training set is obtained by experimental data measurements taken from a unmanned aerial vehicle (UAV). We model the RSS using two different ensemble methods. One of these achieves better performance than a neural network in previous work. In this context, the produced results are compared to measurements using representative performance indices and exhibit satisfactory accuracy.

@inproceedings{
 title = {Prediction of Received Signal Power in Mobile Communications Using Different Machine Learning Algorithms:A Comparative Study},
 type = {inproceedings},
 year = {2019},
 keywords = {UAV,cellular communications,ensemble learning,machine learning,voting regressor},
 id = {7ef523a6-cbcc-3e09-88ec-6b94d94f1756},
 created = {2020-02-29T16:57:43.173Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.386Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Karra2019},
 private_publication = {false},
 abstract = {In this paper, we apply and compare various machine learning techniques to predict the received signal strength (RSS) in cellular communications. We generate the training set using experimental measurements from an unmanned aerial vehicle (UAV). We make a prediction model for the RSS using five base learners. We create a new ensemble method that averages the results from these five base learners. The proposed model outperforms all the original base learners. The obtained numerical results are compared with the original data from the test dataset using representative performance indicators and exhibit good precision.},
 bibtype = {inproceedings},
 author = {Karra, Despoina and Goudos, Sotirios K. and Tsoulos, George V. and Athanasiadou, Georgia},
 doi = {10.1109/PACET48583.2019.8956271},
 booktitle = {5th Panhellenic Conference on Electronics and Telecommunications, PACET 2019}
}

In this paper, we apply and compare various machine learning techniques to predict the received signal strength (RSS) in cellular communications. We generate the training set using experimental measurements from an unmanned aerial vehicle (UAV). We make a prediction model for the RSS using five base learners. We create a new ensemble method that averages the results from these five base learners. The proposed model outperforms all the original base learners. The obtained numerical results are compared with the original data from the test dataset using representative performance indicators and exhibit good precision.

@inproceedings{
 title = {Low-Cost Dual-Band E-shaped Patch Antenna for Energy Harvesting Applications Using Grey Wolf Optimizer},
 type = {inproceedings},
 year = {2019},
 keywords = {E-shaped antenna,Energy harvesting,Grey Wolf Optimizer (GWO) algorithm,LoRaWAN,Mobile communications,Patch antenna},
 id = {f5b42c30-98a3-3c57-b463-2022e1308f9d},
 created = {2020-02-29T16:57:43.226Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:48.809Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2019b},
 private_publication = {false},
 abstract = {Radio frequency energy harvesting is a well promising technique for proactive energy replenishment in next-generation wireless networks. To meet the challenging requirements of power consumption in future wireless networks, new antennas must be designed. In this paper, we refer to the antenna design problem for energy harvesting applications, by introducing a low-cost dual-band E-shaped patch antenna that operates at LoRaWAN and mobile communication frequency bands. The designed antenna is tuned at two different frequencies (866 MHz, 937 MHz) with a satisfactory bandwidth for both frequency bands.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D. and Goudos, Sotirios K. and Yioultsis, Traianos V. and Siakavara, Katherine},
 booktitle = {13th European Conference on Antennas and Propagation, EuCAP 2019}
}

Radio frequency energy harvesting is a well promising technique for proactive energy replenishment in next-generation wireless networks. To meet the challenging requirements of power consumption in future wireless networks, new antennas must be designed. In this paper, we refer to the antenna design problem for energy harvesting applications, by introducing a low-cost dual-band E-shaped patch antenna that operates at LoRaWAN and mobile communication frequency bands. The designed antenna is tuned at two different frequencies (866 MHz, 937 MHz) with a satisfactory bandwidth for both frequency bands.

@inproceedings{
 title = {Patch Antenna Design for C2C Communication Systems Using Monarch Butterfly Optimization},
 type = {inproceedings},
 year = {2019},
 keywords = {C2C communication,E-shaped patch antenna,meta-heuristic algorithm,monarch butterfly optimization},
 pages = {239-241},
 id = {5cddbe75-501f-30a7-b891-5b411808ffa1},
 created = {2020-02-29T16:57:43.258Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.481Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2019a},
 private_publication = {false},
 abstract = {This paper describes an E-shaped patch antenna design which is suitable for Car-to-Car (C2C) communication. The antenna design is obtained by applying a simple and efficient optimization technique, called Monarch Butterfly Optimization. Simulation results demonstrate quite satisfactory values of the antenna's operational bandwidth, maximum gain, and 3 dB beam-width.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D. and Goudos, Sotirios K. and Kantartzis, Nikolaos V. and Koulouridis, Stavros},
 doi = {10.1109/IWAT.2019.8730626},
 booktitle = {2019 International Workshop on Antenna Technology, iWAT 2019}
}

This paper describes an E-shaped patch antenna design which is suitable for Car-to-Car (C2C) communication. The antenna design is obtained by applying a simple and efficient optimization technique, called Monarch Butterfly Optimization. Simulation results demonstrate quite satisfactory values of the antenna's operational bandwidth, maximum gain, and 3 dB beam-width.

@article{
 title = {Fast design of multiband fractal antennas through a system-by-design approach for NB-IoT applications},
 type = {article},
 year = {2019},
 keywords = {Antenna synthesis,Fractals,Internet of Things (IoT),Multi-band antennas,Optimization,System-by-design},
 volume = {2019},
 id = {d72f75ae-5d76-3177-83b0-33e6b28437a2},
 created = {2020-02-29T16:57:43.274Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.098Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Salucci2019},
 private_publication = {false},
 abstract = {The efficient design of compact antennas operating over multiple bands suitable for the Internet of Things (IoT) is addressed by means of an instance of the system-by-design (SbD) paradigm. More specifically, an iterative strategy that combines different software modules for the search spaceexploration, the fast physicalmodeling of the radiators, and the quality evaluation of the guess solutions is proposed. To enable such a SbD instance, an innovative strategy that exploits an orthogonal array (OA) scheme to determine the training set of a Learning-by-Example (LBE) algorithm based on a support vector regressor (SVR) is introduced for the efficient physicalmodeling of the layout to be optimized. The features and the potentialities of the proposed methodological approach are assessed in different applicative scenarios by considering representative numerical and experimental validation examples.},
 bibtype = {article},
 author = {Salucci, Marco and Anselmi, Nicola and Goudos, Sotirios and Massa, Andrea},
 doi = {10.1186/s13638-019-1386-4},
 journal = {Eurasip Journal on Wireless Communications and Networking},
 number = {1}
}

The efficient design of compact antennas operating over multiple bands suitable for the Internet of Things (IoT) is addressed by means of an instance of the system-by-design (SbD) paradigm. More specifically, an iterative strategy that combines different software modules for the search spaceexploration, the fast physicalmodeling of the radiators, and the quality evaluation of the guess solutions is proposed. To enable such a SbD instance, an innovative strategy that exploits an orthogonal array (OA) scheme to determine the training set of a Learning-by-Example (LBE) algorithm based on a support vector regressor (SVR) is introduced for the efficient physicalmodeling of the layout to be optimized. The features and the potentialities of the proposed methodological approach are assessed in different applicative scenarios by considering representative numerical and experimental validation examples.

@inbook{
 type = {inbook},
 year = {2019},
 pages = {55-83},
 issue = {9783030031695},
 id = {9539ed5c-8916-3310-b5a0-8db0aac93e22},
 created = {2020-02-29T16:57:43.313Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.225Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019d},
 private_publication = {false},
 abstract = {The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. The Smart Grid (SG) is the new paradigm that enables highly efficient energy production, transport, and consumption along the whole chain, from the source to the user. SG is the combination of the classical power grid with emerging communication and information technologies. IoT based smart grid will be one of the largest instantiation of the IoT in the next future. In this chapter, we examine, review and present the current IoT enabler technologies for smart grid applications, starting from the physical layer to the application and data layer.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K. and Sarigiannidis, Panagiotis and Dallas, Panagiotis I. and Kyriazakos, Sofoklis},
 doi = {10.1007/978-3-030-03640-9_4},
 chapter = {Communication protocols for the IoT-based smart grid},
 title = {Power Systems}
}

The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. The Smart Grid (SG) is the new paradigm that enables highly efficient energy production, transport, and consumption along the whole chain, from the source to the user. SG is the combination of the classical power grid with emerging communication and information technologies. IoT based smart grid will be one of the largest instantiation of the IoT in the next future. In this chapter, we examine, review and present the current IoT enabler technologies for smart grid applications, starting from the physical layer to the application and data layer.

@article{
 title = {Application of New hybrid jaya grey Wolf optimizer to antenna design for 5G communications systems},
 type = {article},
 year = {2019},
 keywords = {5G,Grey Wolf Optimizer,Jaya algorithm,evolutionary algorithms,mmWave,mobile communications,optimization methods,patch antenna},
 pages = {71061-71071},
 volume = {7},
 id = {d6c25c77-e1bd-3a2f-86ac-8ce962fb472a},
 created = {2020-02-29T16:57:43.798Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.829Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019c},
 private_publication = {false},
 abstract = {The new expected fifth generation (5G) communication systems will serve users with data rates of several Gbps and will allow running new applications in mobile devices. In order to do so, several design challenges have to be met. One of these is the antenna design and fabrication for the 5G mobile devices, especially in the millimeter wave frequencies. In this paper, we address the above issue by designing two different antennas for 3.7 and 26 GHz. We apply a design procedure based on a new proposed evolutionary algorithm, the Grey Wolf Optimizer-Jaya (GWO-Jaya), which combines features from both GWO and Jaya. We evaluate the new algorithm on a set of widely exploited benchmark functions. We design both antennas using the new proposed algorithm. Moreover, we evaluate their performance characteristics through fabrication and measurements. Both antennas are circularly polarized at an acceptable bandwidth and also exhibit wide-band behavior. In both cases, simulation and measurement results are in good agreement.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Yioultsis, Traianos V. and Boursianis, Achilles D. and Psannis, Kostas E. and Siakavara, Katherine},
 doi = {10.1109/ACCESS.2019.2919116},
 journal = {IEEE Access}
}

The new expected fifth generation (5G) communication systems will serve users with data rates of several Gbps and will allow running new applications in mobile devices. In order to do so, several design challenges have to be met. One of these is the antenna design and fabrication for the 5G mobile devices, especially in the millimeter wave frequencies. In this paper, we address the above issue by designing two different antennas for 3.7 and 26 GHz. We apply a design procedure based on a new proposed evolutionary algorithm, the Grey Wolf Optimizer-Jaya (GWO-Jaya), which combines features from both GWO and Jaya. We evaluate the new algorithm on a set of widely exploited benchmark functions. We design both antennas using the new proposed algorithm. Moreover, we evaluate their performance characteristics through fabrication and measurements. Both antennas are circularly polarized at an acceptable bandwidth and also exhibit wide-band behavior. In both cases, simulation and measurement results are in good agreement.

@inproceedings{
 title = {Novel Methodology for Designing Antenna Arrays with Reduced Number of Elements Based on Differential Evolution with Ranking-Based Mutation Operators},
 type = {inproceedings},
 year = {2019},
 id = {2caa4d5a-cb3a-3407-9bbe-741dfc596ec5},
 created = {2020-02-29T16:57:43.831Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.347Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019b},
 private_publication = {false},
 abstract = {This paper addresses the problem of designing linear arrays with reduced number of elements and design constraints including the minimum and maximum distance between two adjacent elements. The proposed design method is based on Differential Evolution (DE) with ranking-based mutation operators. In this case, some of the vectors in the mutation operator are probabilistically selected according to their ranking in the current population instead of recurring to a random selection as in the original DE. A comparative study among different DE algorithms is carried out to define the optimum element geometry and set of excitations that produce the desired pattern with a reduced number of elements. The results show that DE enhanced with ranking-based mutation operator is highly efficient and outperforms the common DE variants.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Boursianis, Achilles and Siakavara, Katherine and Kantartzis, Nikolaos and Psannis, Kostas E.},
 doi = {10.23919/ACESS.2018.8669304},
 booktitle = {2018 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2018}
}

This paper addresses the problem of designing linear arrays with reduced number of elements and design constraints including the minimum and maximum distance between two adjacent elements. The proposed design method is based on Differential Evolution (DE) with ranking-based mutation operators. In this case, some of the vectors in the mutation operator are probabilistically selected according to their ranking in the current population instead of recurring to a random selection as in the original DE. A comparative study among different DE algorithms is carried out to define the optimum element geometry and set of excitations that produce the desired pattern with a reduced number of elements. The results show that DE enhanced with ranking-based mutation operator is highly efficient and outperforms the common DE variants.

@inproceedings{
 title = {Analysis, Synchronization and Microcontroller Implementation of a Generalized Hyperjerk System, with Application to Secure Communications Using a Descriptor Observer},
 type = {inproceedings},
 year = {2019},
 keywords = {Chaos synchronization,descriptor systems,hyperjerk system,microcontroller implementation,observer design},
 id = {1e7044b6-32fa-39fd-aff0-a38504af5e52},
 created = {2020-02-29T16:57:44.818Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.084Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Moysis2019b},
 private_publication = {false},
 abstract = {This work proposes a novel hyperjerk system, as a generalization of a hyperjerk system proposed by Dalkiran and Sprott. Initially an analysis of the dynamical behavior of the system is performed. Then, the system is applied to the problem of secure communications. This is done by considering the transmitting signal as an additional state, leading to a rectangular descriptor system, for which an observer is designed, thus achieving synchronization and safe input reconstruction. The design is illustrated through numerical simulations and a microcontroller implementation.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Volos, Christos and Takhi, Hocine and Kemih, Karim and Goudos, Sotirios and Nistazakis, Hector E.},
 doi = {10.1109/PACET48583.2019.8956261},
 booktitle = {5th Panhellenic Conference on Electronics and Telecommunications, PACET 2019}
}

This work proposes a novel hyperjerk system, as a generalization of a hyperjerk system proposed by Dalkiran and Sprott. Initially an analysis of the dynamical behavior of the system is performed. Then, the system is applied to the problem of secure communications. This is done by considering the transmitting signal as an additional state, leading to a rectangular descriptor system, for which an observer is designed, thus achieving synchronization and safe input reconstruction. The design is illustrated through numerical simulations and a microcontroller implementation.

@misc{
 title = {Guest Editorial: Special Cluster on Machine Learning Applications in Electromagnetics, Antennas, and Propagation},
 type = {misc},
 year = {2019},
 source = {IEEE Antennas and Wireless Propagation Letters},
 pages = {2220-2224},
 volume = {18},
 issue = {11},
 id = {fd9dbf44-e78f-3610-be7d-f40767faf6b5},
 created = {2020-02-29T16:57:44.822Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.412Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Bayraktar2019},
 private_publication = {false},
 bibtype = {misc},
 author = {Bayraktar, Zikri and Anagnostou, DImitris E. and Goudos, Sotirios K. and Campbell, Sawyer D. and Werner, Douglas H. and Massa, Andrea},
 doi = {10.1109/LAWP.2019.2945426}
}

@inproceedings{
 title = {Synchronization of a Chaotic System with Line Equilibrium using a Descriptor Observer for Secure Communication},
 type = {inproceedings},
 year = {2019},
 keywords = {Descriptor systems,chaos synchronization,hidden attractor,observer design,secure communication},
 id = {df3cb83d-aa72-3c33-98b6-af28cabf16e7},
 created = {2020-02-29T16:57:44.870Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.244Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Moysis2019a},
 private_publication = {false},
 abstract = {The problem of secure communication is considered for a chaotic system with hidden attractor, through the observer design approach for descriptor systems. By considering the transmitted signal as an additional state, the nonlinear system is rewritten as a semilinear rectangular descriptor system, for which an observer is constructed. The observer synchronization is feasible under some rank conditions on the system matrices, a common assumption on the nonlinearities and the feasibility of an LMI. The design scheme is showcased through numerical simulations.},
 bibtype = {inproceedings},
 author = {Moysis, Lazaros and Volos, Christos and Pham, Viet Thanh and Goudos, Sotirios and Stouboulos, Ioannis and Gupta, Mahendra Kumar},
 doi = {10.1109/MOCAST.2019.8742059},
 booktitle = {2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019}
}

The problem of secure communication is considered for a chaotic system with hidden attractor, through the observer design approach for descriptor systems. By considering the transmitted signal as an additional state, the nonlinear system is rewritten as a semilinear rectangular descriptor system, for which an observer is constructed. The observer synchronization is feasible under some rank conditions on the system matrices, a common assumption on the nonlinearities and the feasibility of an LMI. The design scheme is showcased through numerical simulations.

@inproceedings{
 title = {Radio Environment Maps for 5G Cognitive Radio Network},
 type = {inproceedings},
 year = {2019},
 keywords = {5G,Cognitive Radio,Network Function Virtualization,REM,SDN},
 id = {11b55a91-0bf4-3271-ad27-d52ada5f5939},
 created = {2020-02-29T16:57:44.873Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.950Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kakalou2019},
 private_publication = {false},
 abstract = {Radio Environment Maps (REMs) have been introduced as a powerful tool in Cognitive Radio Networks to manage inter-transmitter interference. In the evolution of 5G heterogeneous ecosystem REMs are forced to be transformed to a more powerful tool hosting the diverse needs of an immense network. This paper reviews REMs and proposes an enhanced REM architecture for integration in the 5G network.},
 bibtype = {inproceedings},
 author = {Kakalou, Ioanna and Psannis, Kostas and Goudos, Sotirios K. and Yioultsis, Traianos V. and Kantartzis, Nikolaos V. and Ishibashi, Yutaka},
 doi = {10.1109/MOCAST.2019.8741554},
 booktitle = {2019 8th International Conference on Modern Circuits and Systems Technologies, MOCAST 2019}
}

Radio Environment Maps (REMs) have been introduced as a powerful tool in Cognitive Radio Networks to manage inter-transmitter interference. In the evolution of 5G heterogeneous ecosystem REMs are forced to be transformed to a more powerful tool hosting the diverse needs of an immense network. This paper reviews REMs and proposes an enhanced REM architecture for integration in the 5G network.

@article{
 title = {Artificial Neural Network Optimal Modeling and Optimization of UAV Measurements for Mobile Communications Using the L-SHADE Algorithm},
 type = {article},
 year = {2019},
 keywords = {Artificial neural network (ANN),cellular communications,differential evolution (DE),optimization methods,unmanned aerial vehicle (UAV)},
 pages = {4022-4031},
 volume = {67},
 id = {87a504a8-eeac-3ac2-ab15-5c1687465e6d},
 created = {2020-02-29T16:57:44.914Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.401Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019a},
 private_publication = {false},
 abstract = {Channel modeling of wireless communications from unmanned aerial vehicles (UAVs) is an emerging research challenge. In this paper, we propose a solution to this issue by applying a new framework for the prediction of received signal strength (RSS) in mobile communications based on artificial neural networks (ANNs). The experimental data measurements are taken with a UAV at different altitudes. We apply several evolutionary algorithms (EAs) in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm in order to train different ANNs and in particular the L-SHADE algorithm, which self-adapts control parameters and dynamically adjusts population size. Five new hybrid training methods are designed by combining LM with self-adaptive differential evolution (DE) strategies. These new training methods obtain better performance to ANN weight optimization than the original LM method. The received results are compared with the real values using representative ANN performance indices and exhibit satisfactory accuracy.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Tsoulos, George V. and Athanasiadou, Georgia and Batistatos, Michael C. and Zarbouti, Dimitra and Psannis, Kostas E.},
 doi = {10.1109/TAP.2019.2905665},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {6}
}

Channel modeling of wireless communications from unmanned aerial vehicles (UAVs) is an emerging research challenge. In this paper, we propose a solution to this issue by applying a new framework for the prediction of received signal strength (RSS) in mobile communications based on artificial neural networks (ANNs). The experimental data measurements are taken with a UAV at different altitudes. We apply several evolutionary algorithms (EAs) in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm in order to train different ANNs and in particular the L-SHADE algorithm, which self-adapts control parameters and dynamically adjusts population size. Five new hybrid training methods are designed by combining LM with self-adaptive differential evolution (DE) strategies. These new training methods obtain better performance to ANN weight optimization than the original LM method. The received results are compared with the real values using representative ANN performance indices and exhibit satisfactory accuracy.

@inproceedings{
 title = {Multi-cell Massive MIMO Network Optimization towards power consumption in Suburban Scenarios},
 type = {inproceedings},
 year = {2019},
 keywords = {5G,capacity-based deployment tool,coverage,energy efficiency,massive MIMO (Multiple Input Multiple Output),power consumption},
 id = {6825c723-16c1-350c-8358-52f301c0e272},
 created = {2020-02-29T16:57:44.918Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.826Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Matalatala2019a},
 private_publication = {false},
 abstract = {In this paper, we propose a simulation-based method to design low power multi-cell multi-user massive MIMO network by optimizing the positions of the base stations. Two realistic outdoor suburban areas have been considered in Ghent, Belgium (Europe) and Kinshasa, the Democratic Republic of Congo (Africa), in which the power consumption, the energy efficiency, the network capacity and the multiplexing gain are investigated and compared with LTE networks. The results of the simulations demonstrated that massive MIMO networks provide better performance in the crowded scenario where user's mobility is relatively low. A massive MIMO BS consumes 5-8 times less power than the LTE networks, with a pilot reuse pattern of 3 that helps obtaining a good tradeoff between the higher bit rate requested and the low power requirements in cellular environment.},
 bibtype = {inproceedings},
 author = {Matalatala, Michel and Deruyck, Margot and Tanghe, Emmeric and Goudos, Sotirios and Martens, Luc and Joseph, Wout},
 doi = {10.1109/GIIS.2018.8635742},
 booktitle = {2018 Global Information Infrastructure and Networking Symposium, GIIS 2018}
}

In this paper, we propose a simulation-based method to design low power multi-cell multi-user massive MIMO network by optimizing the positions of the base stations. Two realistic outdoor suburban areas have been considered in Ghent, Belgium (Europe) and Kinshasa, the Democratic Republic of Congo (Africa), in which the power consumption, the energy efficiency, the network capacity and the multiplexing gain are investigated and compared with LTE networks. The results of the simulations demonstrated that massive MIMO networks provide better performance in the crowded scenario where user's mobility is relatively low. A massive MIMO BS consumes 5-8 times less power than the LTE networks, with a pilot reuse pattern of 3 that helps obtaining a good tradeoff between the higher bit rate requested and the low power requirements in cellular environment.

@article{
 title = {A Novel Design Approach for 5G Massive MIMO and NB-IoT Green Networks Using a Hybrid Jaya-Differential Evolution Algorithm},
 type = {article},
 year = {2019},
 keywords = {4G,5G,Massive MIMO,NB-IoT,evolutionary algorithms,green networks,hybrid networks,network design,network planning,power consumption},
 volume = {7},
 id = {8f088628-9586-360d-8198-ab753b9973bf},
 created = {2020-02-29T16:57:45.226Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:46.684Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Goudos2019},
 private_publication = {false},
 abstract = {© 2013 IEEE. Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user for 4th Generation (4G) and 5th Generation (5G) Massive MIMO network configurations. Moreover, we present and address the problem of designing green LTE networks with the Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. In this context, we apply emerging evolutionary algorithms in the context of green network design. We investigate three different cases to show the performance of the new proposed algorithm, namely the 4G, 5G Massive MIMO, and the NB-IoT technologies. More specifically, we investigate the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, the self-adaptive differential evolution jDE algorithm, and other hybrid algorithms. We introduce a new hybrid algorithm named Jaya-jDE that uses concepts from both Jaya and jDE algorithms in an effective way. The results show that 5G Massive MIMO networks require about 50% less power consumption than the 4G ones, and the NB-IoT in-band deployment requires about 10% less power than guard-band deployment. Moreover, Jaya-jDE emerges as the best algorithm based on the results.},
 bibtype = {article},
 author = {Goudos, S.K. and Deruyck, M. and Plets, D. and Martens, L. and Psannis, K.E. and Sarigiannidis, P. and Joseph, W.},
 doi = {10.1109/ACCESS.2019.2932042},
 journal = {IEEE Access}
}

© 2013 IEEE. Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user for 4th Generation (4G) and 5th Generation (5G) Massive MIMO network configurations. Moreover, we present and address the problem of designing green LTE networks with the Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. In this context, we apply emerging evolutionary algorithms in the context of green network design. We investigate three different cases to show the performance of the new proposed algorithm, namely the 4G, 5G Massive MIMO, and the NB-IoT technologies. More specifically, we investigate the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, the self-adaptive differential evolution jDE algorithm, and other hybrid algorithms. We introduce a new hybrid algorithm named Jaya-jDE that uses concepts from both Jaya and jDE algorithms in an effective way. The results show that 5G Massive MIMO networks require about 50% less power consumption than the 4G ones, and the NB-IoT in-band deployment requires about 10% less power than guard-band deployment. Moreover, Jaya-jDE emerges as the best algorithm based on the results.

@article{
 title = {Multi-objective optimization of massive MIMO 5G wireless networks towards power consumption, uplink and downlink exposure},
 type = {article},
 year = {2019},
 keywords = {5G,Exposure,Massive MIMO,Multi-objective,Optimization},
 volume = {9},
 id = {b1078d78-9bf3-3b89-ba8c-cc7117e7c593},
 created = {2020-02-29T16:57:45.401Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.144Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Matalatala2019},
 private_publication = {false},
 abstract = {The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (-12% for the electric field and-32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario.},
 bibtype = {article},
 author = {Matalatala, Michel and Deruyck, Margot and Shikhantsov, Sergei and Tanghe, Emmeric and Plets, David and Goudos, Sotirios and Psannis, Kostas E. and Martens, Luc and Joseph, Wout},
 doi = {10.3390/APP9224974},
 journal = {Applied Sciences (Switzerland)},
 number = {22}
}

The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (-12% for the electric field and-32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario.

@inproceedings{
 title = {Advancing Rational Exploitation of Water Irrigation Using 5G-IoT Capabilities: The AREThOU5A Project},
 type = {inproceedings},
 year = {2019},
 keywords = {Internet of Things,Low-power wide-access technology,RF energy harvesting,Smart Agriculture},
 pages = {127-132},
 id = {53ca9c71-16e3-3b0b-b916-4fe3bb33a9ab},
 created = {2020-02-29T16:57:45.444Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.276Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2019},
 private_publication = {false},
 abstract = {Water scarcity and desertification are considered to be among the greatest challenges of humanity over the coming decades. Worldwide, agriculture accounts to 69% of total water usage, while industry accounts for 23%, and urban use to 8%. In Greece, a rural development model and poor farming practices have resulted in an overwhelming 83% of total water consumption to be directed to farming uses. Furthermore, excessive use of water in agriculture combined with existing pesticides and fertilizers usage levels creates exponential problems in the water cycle in Greece. Taking into account the above challenges, the AREThOU5A Project aims to exploit the state-of-the-art technologies and, in particular, the emerging developments in the field of Internet of Things (IoT) as a means to promote rational use of water resources in agriculture. In particular, AREThOU5A Project aims at accelerating penetration of low-power wide-access (LPWA) technologies through a series of research and innovation actions focusing on the design, development, operation and commercial exploitation of relevant hardware/software IoT applications. Preliminary results of the AREThOU5A Project are depicted and future remarks are outlined.},
 bibtype = {inproceedings},
 author = {Boursianis, A. D. and Papadopoulou, M. S. and Damantoulakis, P. and Karampatea, A. and Doanis, P. and Geourgoulas, D. and Skoufa, A. and Valavanis, D. and Apostolidis, C. and Babas, D. G. and Baltzis, K. B. and Kaifas, T. N. and Siozios, K. and Siskos, S. and Samaras, T. and Siakavara, K. and Nikolaidis, S. and Goudos, S. K. and Liopa-Tsakalidi, A. and Barouchas, P. and Kasimis, I. and Kalamaras, G. and Merkouris, D. and Perrakis, G. and Tsirogiannis, C. and Gotsis, A. and Maliatsos, K.},
 doi = {10.1109/PATMOS.2019.8862146},
 booktitle = {2019 IEEE 29th International Symposium on Power and Timing Modeling, Optimization and Simulation, PATMOS 2019}
}

Water scarcity and desertification are considered to be among the greatest challenges of humanity over the coming decades. Worldwide, agriculture accounts to 69% of total water usage, while industry accounts for 23%, and urban use to 8%. In Greece, a rural development model and poor farming practices have resulted in an overwhelming 83% of total water consumption to be directed to farming uses. Furthermore, excessive use of water in agriculture combined with existing pesticides and fertilizers usage levels creates exponential problems in the water cycle in Greece. Taking into account the above challenges, the AREThOU5A Project aims to exploit the state-of-the-art technologies and, in particular, the emerging developments in the field of Internet of Things (IoT) as a means to promote rational use of water resources in agriculture. In particular, AREThOU5A Project aims at accelerating penetration of low-power wide-access (LPWA) technologies through a series of research and innovation actions focusing on the design, development, operation and commercial exploitation of relevant hardware/software IoT applications. Preliminary results of the AREThOU5A Project are depicted and future remarks are outlined.

@article{
 title = {Analysis of a Chaotic System with Line Equilibrium and Its Application to Secure Communications Using a Descriptor Observer},
 type = {article},
 year = {2019},
 volume = {7},
 websites = {%3CGo,to},
 id = {0796f5e6-6d33-384b-b429-957f8b69d891},
 created = {2020-03-03T08:54:40.413Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T12:37:16.050Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Moysis2019},
 source_type = {article},
 private_publication = {false},
 abstract = {In this work a novel chaotic system with a line equilibrium is presented. First, a dynamical analysis on the system is performed, by computing its bifurcation diagram, continuation diagram, phase portraits and Lyapunov exponents. Then, the system is applied to the problem of secure communication. We assume that the transmitted signal is an additional state. For this reason, the nonlinear system is rewritten in a rectangular descriptor form and then an observer is constructed for achieving synchronization and input reconstruction. If we assume some rank conditions (on the nonlinearities and the solvability of a linear matrix inequality (LMI)) on the system matrices then the observer synchronization can be feasible. We evaluate and demonstrate our approach with specific numerical results.},
 bibtype = {article},
 author = {Moysis, L and Volos, C and Pham, V T and Goudos, S and Stouboulos, I and Gupta, M K and Mishra, V K},
 doi = {10.3390/technologies7040076},
 journal = {Technologies},
 number = {4}
}

In this work a novel chaotic system with a line equilibrium is presented. First, a dynamical analysis on the system is performed, by computing its bifurcation diagram, continuation diagram, phase portraits and Lyapunov exponents. Then, the system is applied to the problem of secure communication. We assume that the transmitted signal is an additional state. For this reason, the nonlinear system is rewritten in a rectangular descriptor form and then an observer is constructed for achieving synchronization and input reconstruction. If we assume some rank conditions (on the nonlinearities and the solvability of a linear matrix inequality (LMI)) on the system matrices then the observer synchronization can be feasible. We evaluate and demonstrate our approach with specific numerical results.

@article{
 title = {An Energy Efficient Modulation Scheme for Body-Centric Terahertz (THz) Nanonetworks dagger},
 type = {article},
 year = {2019},
 volume = {7},
 websites = {%3CGo,to},
 id = {0bbfd758-217d-3e6d-8f80-fc6b094e9808},
 created = {2020-03-03T08:54:40.426Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T12:37:16.041Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Vavouris2019},
 source_type = {article},
 private_publication = {false},
 abstract = {In body-centric communications, energy efficiency is a critical performance metric, while the achievable data rate is not of primary concern. In this paper we present a novel modulation scheme, which can be efficiently used in body-centric terahertz (THz) nanonetworks. The proposed scheme is a combination of the time-spread On-Off keying (TS–OOK) and the pulse position modulation (PPM) and presents lower energy consumption, compared to other existing methods as TS–OOK, at a minor cost to the data rate. Furthermore, another important aspect is that the proposed modulation scheme can be effectively used to mitigate the impact of the specific kind of noise in THz body-centric communications, thus leading to better error performance. Finally, we present analytical and simulation results in order to compare the new scheme with the existing TS–OOK.},
 bibtype = {article},
 author = {Vavouris, A K and Dervisi, F D and Papanikolaou, V K and Diamantoulakis, P D and Karagiannidis, G K and Goudos, S K},
 doi = {10.3390/technologies7010014},
 journal = {Technologies},
 number = {1}
}

In body-centric communications, energy efficiency is a critical performance metric, while the achievable data rate is not of primary concern. In this paper we present a novel modulation scheme, which can be efficiently used in body-centric terahertz (THz) nanonetworks. The proposed scheme is a combination of the time-spread On-Off keying (TS–OOK) and the pulse position modulation (PPM) and presents lower energy consumption, compared to other existing methods as TS–OOK, at a minor cost to the data rate. Furthermore, another important aspect is that the proposed modulation scheme can be effectively used to mitigate the impact of the specific kind of noise in THz body-centric communications, thus leading to better error performance. Finally, we present analytical and simulation results in order to compare the new scheme with the existing TS–OOK.

@inproceedings{
 title = {Application of Opposition Teaching Learning Based Optimization for 5G Communication Systems Antenna Design},
 type = {inproceedings},
 year = {2019},
 publisher = {COMPUMAG},
 city = {Paris, France},
 id = {c1e8f8bc-cbb3-3cc3-bb1e-4ad1e56fb5d7},
 created = {2022-07-14T18:38:19.213Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T12:33:11.595Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {bgys19},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {To address the complex optimization problem of antenna design for 5G wireless communication systems, we enhance the Teaching Learning Based Optimization (TLBO) algorithm with Opposition Based Learning (OBL). In this paper, we obtain new TLBO algorithms with different OBL variants. The different opposition schemes are evaluated in order to find the variant with the best performance. Numerical simulation results show that the current optimum opposition scheme outperforms the other algorithms and achieves the highest average ranking. Moreover, the COO-TLBO variant is applied in the design of aperture-coupled E-shaped patch antenna. Preliminary results demonstrate very satisfactory values of return loss in the desired frequencies of 5G wireless communication systems.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles D and Sotirios K. Goudos, undefined and Yioultsis, Traianos V and Siakavara, Katherine},
 booktitle = {Proceedings of the 22nd International Conference on the Computation of Electromagnetic Fields}
}

To address the complex optimization problem of antenna design for 5G wireless communication systems, we enhance the Teaching Learning Based Optimization (TLBO) algorithm with Opposition Based Learning (OBL). In this paper, we obtain new TLBO algorithms with different OBL variants. The different opposition schemes are evaluated in order to find the variant with the best performance. Numerical simulation results show that the current optimum opposition scheme outperforms the other algorithms and achieves the highest average ranking. Moreover, the COO-TLBO variant is applied in the design of aperture-coupled E-shaped patch antenna. Preliminary results demonstrate very satisfactory values of return loss in the desired frequencies of 5G wireless communication systems.

@inproceedings{
 title = {Binary Grey Wolf Optimizer with Migration Operator for Discrete-Valued Antenna Design Problems},
 type = {inproceedings},
 year = {2019},
 publisher = {COMPUMAG},
 city = {Paris, France},
 id = {4608552e-5660-3772-bb6e-18a5d010e582},
 created = {2022-07-14T18:38:19.221Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T12:33:11.624Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {gbkyah19},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Several antenna design problems are discrete-valued. To address these problems binary-coded algorithms suited for combinatorial optimization problems are required. Grey Wolf Optimizer (GWO) is a recently proposed evolutionary algorithm based on grey wolves’ behavior. Although GWO was originally designed for real-valued problems, discrete versions also exist. In this paper, we propose a novel binary GWO algorithm that also uses a migration operator like in Biogeography Based Optimization (BBO). This new hybrid algorithm bGWO-BBO has been applied to several discrete valued problems in electromagnetics. These include array thinning, and a design case of an arbitrary-shaped dual-band patch antenna. The results show that bGWO-BBO is very efficient and outperforms other popular binary algorithms.},
 bibtype = {inproceedings},
 author = {Sotirios K. Goudos, undefined and Boursianis, Achilles D and Kantartzis, Nikolaos V and Yioultsis, Traianos V and Antonopoulos, Christos S and Hybrid, A},
 booktitle = {Proceedings of the 22nd International Conference on the Computation of Electromagnetic Fields}
}

Several antenna design problems are discrete-valued. To address these problems binary-coded algorithms suited for combinatorial optimization problems are required. Grey Wolf Optimizer (GWO) is a recently proposed evolutionary algorithm based on grey wolves’ behavior. Although GWO was originally designed for real-valued problems, discrete versions also exist. In this paper, we propose a novel binary GWO algorithm that also uses a migration operator like in Biogeography Based Optimization (BBO). This new hybrid algorithm bGWO-BBO has been applied to several discrete valued problems in electromagnetics. These include array thinning, and a design case of an arbitrary-shaped dual-band patch antenna. The results show that bGWO-BBO is very efficient and outperforms other popular binary algorithms.

@inproceedings{
 title = {Introducing Quantum Tunneling Optimization in electromagnetics,The Constraint Relaxation Approach},
 type = {inproceedings},
 year = {2019},
 id = {affab330-d981-313a-8332-327d2e553033},
 created = {2023-01-02T11:46:06.286Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T12:25:57.587Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2019f},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {There are two major categories of optimization algorithms employed in EM problems. They are the gradient based and the metaheuristic, (mainly evolution), based algorithms. In the work at hand we use both gradient and metaheuristic algorithms but the latter are not evolutionary. The contributed idea is based on another paradigm drawn from the laws of quantum physics and entails the integration of quantum tunneling concepts into a basic gradient search. It is well known in Quantum Mechanics that, Quantum Tunneling transforms local barriers into (semi-) transparent boundaries allowing the gradient search to pass through and continue to the global extremum. To the authors’ knowledge this is only physical phenomenon able to achieve the non-convex to convex transformation, (by going through and not over the barriers), and as such it deserves thorough study. Our work proves that gradient search equipped with quantum tunneling can be pulled out of the basin of a local extremum to provide high quality optimization results. In the current study we contribute the introduction of quantum tunneling in electromagnetics under the Constraint Relaxation Approach and provide proof of its potential.},
 bibtype = {inproceedings},
 author = {Kaifas, Theodoros N and Babas, Dimitrios G and Goudos, Sotirios K},
 booktitle = {13th European Conference on Antennas and Propagation, EuCAP 2019}
}

There are two major categories of optimization algorithms employed in EM problems. They are the gradient based and the metaheuristic, (mainly evolution), based algorithms. In the work at hand we use both gradient and metaheuristic algorithms but the latter are not evolutionary. The contributed idea is based on another paradigm drawn from the laws of quantum physics and entails the integration of quantum tunneling concepts into a basic gradient search. It is well known in Quantum Mechanics that, Quantum Tunneling transforms local barriers into (semi-) transparent boundaries allowing the gradient search to pass through and continue to the global extremum. To the authors’ knowledge this is only physical phenomenon able to achieve the non-convex to convex transformation, (by going through and not over the barriers), and as such it deserves thorough study. Our work proves that gradient search equipped with quantum tunneling can be pulled out of the basin of a local extremum to provide high quality optimization results. In the current study we contribute the introduction of quantum tunneling in electromagnetics under the Constraint Relaxation Approach and provide proof of its potential.

@inproceedings{
 title = {Artificial neural network optimal modelling of received signal strength in mobile communications using UAV measurements},
 type = {inproceedings},
 year = {2018},
 keywords = {ANN,DE,LM,Mobile communications,Propagation prediction,UAV},
 volume = {2018},
 issue = {CP741},
 id = {a365915c-1912-3029-9777-6e4a4da3262f},
 created = {2020-02-29T16:57:42.220Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.449Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018e},
 private_publication = {false},
 abstract = {In this paper, we apply an alternative procedure for the prediction of received signal strength in mobile communications based on Artificial Neural Networks (ANN). We use experimental data measurements taken from an unmanned aerial vehicle (UAV) for ANN training. We apply several evolutionary algorithms (EAs) in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm in order to train different ANNs. We design two new hybrid training methods by combing LM with self-adaptive Differential Evolution (DE) strategies. These new training methods achieve better convergence of neural network weight optimization than the original LM method. The received results are compared to the real values using representative ANN performance indices and exhibit satisfactory accuracy.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Tsoulos, George and Athanasiadou, Georgia},
 doi = {10.1049/cp.2018.1079},
 booktitle = {IET Conference Publications}
}

In this paper, we apply an alternative procedure for the prediction of received signal strength in mobile communications based on Artificial Neural Networks (ANN). We use experimental data measurements taken from an unmanned aerial vehicle (UAV) for ANN training. We apply several evolutionary algorithms (EAs) in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm in order to train different ANNs. We design two new hybrid training methods by combing LM with self-adaptive Differential Evolution (DE) strategies. These new training methods achieve better convergence of neural network weight optimization than the original LM method. The received results are compared to the real values using representative ANN performance indices and exhibit satisfactory accuracy.

@inproceedings{
 title = {Users Association in Ultra Dense THz Networks},
 type = {inproceedings},
 year = {2018},
 volume = {2018-June},
 id = {a34e30be-407c-3ea5-87ee-5c165e6ee61f},
 created = {2020-02-29T16:57:42.268Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.178Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boulogeorgos2018},
 private_publication = {false},
 abstract = {In this paper, we formulate a novel throughput aware user association scheme for ultra dense terahertz (THz) networks. In more detail, we introduce a user association problem, which takes into account the THz channel particularities, the directivity of the BSs' and UEs' antennas, as well as their position and the UEs' minimum rate requirements. Moreover, we provide the solution framework, which is based on the grey wolf optimizer (GWO) and returns the optimal user association table. Finally, we present comparative simulation results, which validate the superiority of the proposed framework against the commonly-used particle swarm optimizer (PSO) approach.},
 bibtype = {inproceedings},
 author = {Boulogeorgos, Alexandros Apostolos A. and Goudos, Sotirios K. and Alexiou, Angeliki},
 doi = {10.1109/SPAWC.2018.8445950},
 booktitle = {IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC}
}

In this paper, we formulate a novel throughput aware user association scheme for ultra dense terahertz (THz) networks. In more detail, we introduce a user association problem, which takes into account the THz channel particularities, the directivity of the BSs' and UEs' antennas, as well as their position and the UEs' minimum rate requirements. Moreover, we provide the solution framework, which is based on the grey wolf optimizer (GWO) and returns the optimal user association table. Finally, we present comparative simulation results, which validate the superiority of the proposed framework against the commonly-used particle swarm optimizer (PSO) approach.

@article{
 title = {Multi-objective optimization in 5G wireless networks with massive MIMO},
 type = {article},
 year = {2018},
 keywords = {5G,MIMO communications,cellular network,energy efficiency,optimization techniques},
 pages = {2346-2349},
 volume = {22},
 id = {80d9cec6-2b5a-309b-98a9-5b9d4f492f29},
 created = {2020-02-29T16:57:42.270Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.496Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018d},
 private_publication = {false},
 abstract = {The integration of massive multiple-input multiple-output systems in the fifth generation (5G) of wireless networks requires the simultaneous consideration of several conflicting objectives, in order to achieve optimal performance and operation. In this letter, we present a complete optimization framework, which is based on multi-objective evolutionary algorithms (MOEAs), namely, non-dominated sorting genetic algorithm-II and speed-constrained multi-objective particle swarm optimization. In addition, we use a decision maker for the selection of a solution vector that achieves the best compromise solution. The results illustrate that MOEAs are particularly promising techniques for solving such multi-objective problems in 5G networks.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Diamantoulakis, Panagiotis D. and Karagiannidis, George K.},
 doi = {10.1109/LCOMM.2018.2868663},
 journal = {IEEE Communications Letters},
 number = {11}
}

The integration of massive multiple-input multiple-output systems in the fifth generation (5G) of wireless networks requires the simultaneous consideration of several conflicting objectives, in order to achieve optimal performance and operation. In this letter, we present a complete optimization framework, which is based on multi-objective evolutionary algorithms (MOEAs), namely, non-dominated sorting genetic algorithm-II and speed-constrained multi-objective particle swarm optimization. In addition, we use a decision maker for the selection of a solution vector that achieves the best compromise solution. The results illustrate that MOEAs are particularly promising techniques for solving such multi-objective problems in 5G networks.

@article{
 title = {Particle swarm optimization as applied to electromagnetic design problems},
 type = {article},
 year = {2018},
 keywords = {Electromagnetics,Inertia weight PSO,Particle swarm optimization,Social behavior},
 pages = {47-82},
 volume = {9},
 id = {65b2b810-5964-3b5b-911a-019f6a0965ae},
 created = {2020-02-29T16:57:42.320Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.225Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018c},
 private_publication = {false},
 abstract = {Particle swarm optimization (PSO) is a swarm intelligence algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this article, the authors apply different PSO variants to common design problems in electromagnetics. They apply the Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms to real-valued optimization problems, i.e. microwave absorber design, and linear array synthesis. Moreover, the authors use discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with a velocity mutation (BPSO-vm) in order to solve discrete-valued optimization problems, i.e. patch antenna design. Additionally, the authors apply and compare binPSO with different transfer functions to thinning array design problems. In the case of a multi-objective optimization problem, they apply two multi-objective PSO variants to dual-band base station antenna optimization for mobile communications. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. Finally, the authors conclude the paper by providing a discussion on future trends and the conclusion.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Zaharis, Zaharias D. and Baltzis, Konstantinos B.},
 doi = {10.4018/IJSIR.2018040104},
 journal = {International Journal of Swarm Intelligence Research},
 number = {2}
}

Particle swarm optimization (PSO) is a swarm intelligence algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this article, the authors apply different PSO variants to common design problems in electromagnetics. They apply the Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms to real-valued optimization problems, i.e. microwave absorber design, and linear array synthesis. Moreover, the authors use discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with a velocity mutation (BPSO-vm) in order to solve discrete-valued optimization problems, i.e. patch antenna design. Additionally, the authors apply and compare binPSO with different transfer functions to thinning array design problems. In the case of a multi-objective optimization problem, they apply two multi-objective PSO variants to dual-band base station antenna optimization for mobile communications. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. Finally, the authors conclude the paper by providing a discussion on future trends and the conclusion.

@inproceedings{
 title = {A low cost wide band and circularly polarized modifed half e-shaped patch antenna for 5G mobile communications},
 type = {inproceedings},
 year = {2018},
 keywords = {5G,Half E-shaped,Jaya algorithm,MmWave,Mobile communications,Patch antennas},
 volume = {2018},
 issue = {CP741},
 id = {cb6de174-148a-3488-9da7-23f3abbe59b6},
 created = {2020-02-29T16:57:43.331Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.903Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018b},
 private_publication = {false},
 abstract = {The upcoming ſfth generation (5G) technology for mobile communications will offer multi-Gbps data rates for each user. Such data rates require wide spectrum, which is available at millimeter wave frequencies. In order to meet the challenging 5G requirements new antennas have to be designed. In this paper, we address the antenna design problem for 5G mobile communications by designing a low cost half-E-shaped patch antenna that operates at 25GHz. The designed antenna is circularly polarized at a satisfactory bandwidth and also exhibits wide band behavior.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Yioultsis, Traianos V. and Dalidou, Krystalia and Siakavara, Katherine},
 doi = {10.1049/cp.2018.1200},
 booktitle = {IET Conference Publications}
}

The upcoming ſfth generation (5G) technology for mobile communications will offer multi-Gbps data rates for each user. Such data rates require wide spectrum, which is available at millimeter wave frequencies. In order to meet the challenging 5G requirements new antennas have to be designed. In this paper, we address the antenna design problem for 5G mobile communications by designing a low cost half-E-shaped patch antenna that operates at 25GHz. The designed antenna is circularly polarized at a satisfactory bandwidth and also exhibits wide band behavior.

@article{
 title = {Realizing 5G vision through Cloud RAN: technologies, challenges, and trends},
 type = {article},
 year = {2018},
 keywords = {5G,Cloud Radio Access Network,Common Public Radio Interface,Network function virtualization,Software-defined networking},
 volume = {2018},
 id = {11967d37-e19e-3b14-9d92-1e8321520d76},
 created = {2020-02-29T16:57:43.355Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T16:29:16.705Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Pliatsios2018},
 private_publication = {false},
 abstract = {© 2018, The Author(s). Achieving the fifth-generation (5G) vision will introduce new technology innovations and substantial changes in delivering cutting-edge applications and services in current mobile and cellular networks. The Cloud Radio Access Network (C-RAN) concept emerged as one of the most compelling architectures to meet the requirements of the 5G vision. In essence, C-RAN provides an advanced mobile network architecture which can leverage challenging features such as network resource slicing, statistical multiplexing, energy efficiency, and high capacity. The realization of C-RAN is achieved by innovative technologies such as the software-defined networking (SDN) and the network function virtualization (NFV). While SDN technology brings the separation of the control and data planes in the playground, supporting thus advanced traffic engineering techniques such as load balancing, the NFV concept offers high flexibility by allowing network resource sharing in a dynamic way. Although SDN and NFV have many advantages, a number of challenges have to be addressed before the commercial deployment of 5G implementation. In addition, C-RAN introduces a new layer in the mobile network, denoted as the fronthaul, which is adopted from the recent research efforts in the fiber-wireless (Fi-Wi) paradigm. As the fronthaul defines a link between a baseband unit (BBU) and a remote radio unit (RRU), various technologies can be used for this purpose such as optical fibers and millimeter-wave (mm-wave) radios. In this way, several challenges are highlighted which depend on the technology used. In the light of the aforementioned remarks, this paper compiles a list of challenges and open issues of the emerging technologies that realize the C-RAN concept. Moreover, comparative insights between the current and future state of the C-RAN concept are discussed. Trends and advances of those technologies are also examined towards shedding light on the proliferation of 5G through the C-RAN concept.},
 bibtype = {article},
 author = {Pliatsios, D. and Sarigiannidis, P. and Goudos, S. and Karagiannidis, G.K.},
 doi = {10.1186/s13638-018-1142-1},
 journal = {Eurasip Journal on Wireless Communications and Networking},
 number = {1}
}

© 2018, The Author(s). Achieving the fifth-generation (5G) vision will introduce new technology innovations and substantial changes in delivering cutting-edge applications and services in current mobile and cellular networks. The Cloud Radio Access Network (C-RAN) concept emerged as one of the most compelling architectures to meet the requirements of the 5G vision. In essence, C-RAN provides an advanced mobile network architecture which can leverage challenging features such as network resource slicing, statistical multiplexing, energy efficiency, and high capacity. The realization of C-RAN is achieved by innovative technologies such as the software-defined networking (SDN) and the network function virtualization (NFV). While SDN technology brings the separation of the control and data planes in the playground, supporting thus advanced traffic engineering techniques such as load balancing, the NFV concept offers high flexibility by allowing network resource sharing in a dynamic way. Although SDN and NFV have many advantages, a number of challenges have to be addressed before the commercial deployment of 5G implementation. In addition, C-RAN introduces a new layer in the mobile network, denoted as the fronthaul, which is adopted from the recent research efforts in the fiber-wireless (Fi-Wi) paradigm. As the fronthaul defines a link between a baseband unit (BBU) and a remote radio unit (RRU), various technologies can be used for this purpose such as optical fibers and millimeter-wave (mm-wave) radios. In this way, several challenges are highlighted which depend on the technology used. In the light of the aforementioned remarks, this paper compiles a list of challenges and open issues of the emerging technologies that realize the C-RAN concept. Moreover, comparative insights between the current and future state of the C-RAN concept are discussed. Trends and advances of those technologies are also examined towards shedding light on the proliferation of 5G through the C-RAN concept.

@inproceedings{
 title = {Phased Antenna Array Design using Shuffled Frog-Leaping Algorithm},
 type = {inproceedings},
 year = {2018},
 pages = {1845-1846},
 id = {d2164b4c-b7e2-3082-b683-0542086e8183},
 created = {2020-02-29T16:57:43.851Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.571Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Boursianis2018},
 private_publication = {false},
 abstract = {In this paper, we present a new meta-heuristic approach (memetic algorithm) to address multi-objective problems in planar phased arrays. Memetic algorithms are hybrid algorithms that combine the benefits of a global search evolutionary algorithm with a local search method. The Shuffled Frog-Leaping Algorithm (SFLA) consists of a virtual population of frogs partitioned into different memeplexes. It performs a memetic evolution within the memeplex (local search) and a shuffling mix process between memeplexes (global search) to deliver optimum solutions in optimization problems. Derived results show improved characteristics of the antenna array.},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles and Patakakis, Kostas and Goudos, Sotirios K. and Salucci, Marco and Massa, Andrea},
 doi = {10.1109/APUSNCURSINRSM.2018.8609068},
 booktitle = {2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings}
}

In this paper, we present a new meta-heuristic approach (memetic algorithm) to address multi-objective problems in planar phased arrays. Memetic algorithms are hybrid algorithms that combine the benefits of a global search evolutionary algorithm with a local search method. The Shuffled Frog-Leaping Algorithm (SFLA) consists of a virtual population of frogs partitioned into different memeplexes. It performs a memetic evolution within the memeplex (local search) and a shuffling mix process between memeplexes (global search) to deliver optimum solutions in optimization problems. Derived results show improved characteristics of the antenna array.

@inproceedings{
 title = {A novel design approach for NB-IoT networks using hybrid teaching-learning optimization},
 type = {inproceedings},
 year = {2018},
 keywords = {Evolutionary algorithms,Green networks,LTE,NB-IoT,Power consumption,Teaching- learning optimization},
 volume = {2018},
 issue = {CP741},
 id = {10f9f811-3684-3201-be8b-46a3959c8e20},
 created = {2020-02-29T16:57:43.882Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.062Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018a},
 private_publication = {false},
 abstract = {In this paper, we present and address the problem of designing green LTE networks with Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. The main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user and the IoT node. In this context, we apply emerging evolutionary algorithms to the above problem. More specifcally, we apply the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, and a hybrid algorithm. This hybrid algorithm named TLBO-Jaya uses concepts from both algorithms in an effective way. We compare and discuss the preliminary results of these algorithms.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout},
 doi = {10.1049/cp.2018.1056},
 booktitle = {IET Conference Publications}
}

In this paper, we present and address the problem of designing green LTE networks with Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. The main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user and the IoT node. In this context, we apply emerging evolutionary algorithms to the above problem. More specifcally, we apply the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, and a hybrid algorithm. This hybrid algorithm named TLBO-Jaya uses concepts from both algorithms in an effective way. We compare and discuss the preliminary results of these algorithms.

@inproceedings{
 title = {Evaluation of an Artificial Neural Network Approach for Timing Modeling of CMOS Gates},
 type = {inproceedings},
 year = {2018},
 keywords = {component,formatting,insert,style,styling},
 pages = {169-176},
 id = {73aa0c65-2936-329d-9158-7214bfa8076e},
 created = {2020-02-29T16:57:43.902Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.772Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2018},
 private_publication = {false},
 abstract = {The development of reliable and fast timing models for CMOS logic gates is a significant task for the IC technology. Analytical approaches have been proposed to accelerate timing analysis while keeping the accuracy in acceptable levels. However, the complexity of the analytical modeling procedure increases as we are moving towards new technology nodes influencing mostly the provided accuracy. The artificial neural network (ANN) approach could be a solution to this complexity. In this paper, the use of ANNs for timing modeling of CMOS gates is evaluated. Several different ANNs schemes are developed, optimized and studied regarding their accuracy, resource requirements and speed. Moreover, we design a new training method by combing the Particle Swarm Optimization (PSO) a meta-heuristic algorithm in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm. The outcomes show that the new training method obtains better results that the LM algorithm. The efficiency of adopting a common neural network structure, letting the coefficients to distinguish between the different logic gates is investigated.},
 bibtype = {inproceedings},
 author = {Goudos, S. and Karagiorgos, N. and Ntogramatzi, M. and Messaris, I. and Nikolaidis, S.},
 doi = {10.1109/PATMOS.2018.8464162},
 booktitle = {2018 IEEE 28th International Symposium on Power and Timing Modeling, Optimization and Simulation, PATMOS 2018}
}

The development of reliable and fast timing models for CMOS logic gates is a significant task for the IC technology. Analytical approaches have been proposed to accelerate timing analysis while keeping the accuracy in acceptable levels. However, the complexity of the analytical modeling procedure increases as we are moving towards new technology nodes influencing mostly the provided accuracy. The artificial neural network (ANN) approach could be a solution to this complexity. In this paper, the use of ANNs for timing modeling of CMOS gates is evaluated. Several different ANNs schemes are developed, optimized and studied regarding their accuracy, resource requirements and speed. Moreover, we design a new training method by combing the Particle Swarm Optimization (PSO) a meta-heuristic algorithm in conjunction with the Levenberg-Marquardt (LM) backpropagation algorithm. The outcomes show that the new training method obtains better results that the LM algorithm. The efficiency of adopting a common neural network structure, letting the coefficients to distinguish between the different logic gates is investigated.

@inproceedings{
 title = {SDN-based QoS provisioning and interference management in heterogeneous CRN},
 type = {inproceedings},
 year = {2018},
 keywords = {Heterogeneous Cognitive Radio Networks,Software Defined Network},
 pages = {1-4},
 id = {3388d5e4-e5a5-3e33-9179-af1528187380},
 created = {2020-02-29T16:57:43.945Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.836Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kakalou2018},
 private_publication = {false},
 abstract = {Cognitive Radio is a promising technology to maximize spectrum efficiency that can be applied to dense residential infrastructure and heterogeneous networks. This paper proposes a Software Defined Networking (SDN) system model for coordinated adaptive spectrum sharing and interference management; the SDN system model leverages the fact that Primary User (PU) network traffic is bursty with an optimal reinforcement learning scheme and takes into account network topology information and data rate requirements of active flows. The scheme learns PU traffic, and as a result, it optimizes spectrum brokerage to the active flows for QoS provisioning and performs interference mitigation.},
 bibtype = {inproceedings},
 author = {Kakalou, Ioanna and Psannis, Kostas and Siakavara, Katherine and Goudos, Sotirios K. and Ishibashi, Yutaka},
 doi = {10.1109/MOCAST.2018.8376585},
 booktitle = {2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018}
}

Cognitive Radio is a promising technology to maximize spectrum efficiency that can be applied to dense residential infrastructure and heterogeneous networks. This paper proposes a Software Defined Networking (SDN) system model for coordinated adaptive spectrum sharing and interference management; the SDN system model leverages the fact that Primary User (PU) network traffic is bursty with an optimal reinforcement learning scheme and takes into account network topology information and data rate requirements of active flows. The scheme learns PU traffic, and as a result, it optimizes spectrum brokerage to the active flows for QoS provisioning and performs interference mitigation.

@inproceedings{
 title = {Multiobjective lightining search applied to Jiles-Atherton hysteresis model parameter estimation},
 type = {inproceedings},
 year = {2018},
 keywords = {Hysteresis model,lightning search,multiobjective optimization,parameters identification,vector hysteresis},
 pages = {1-4},
 id = {626dd844-ecc3-3fe2-b846-7617cf18b99e},
 created = {2020-02-29T16:57:43.959Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.898Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {DosSantosCoelho2018},
 private_publication = {false},
 abstract = {Hysteresis is a fundamental property commonly encountered in physical systems of a wide variety of engineering and science fields and the parameters determination and/or optimization of hysteresis dynamical models is an essential approach for adequate hysteretic material simulations. In magnetic vector hysteresis models as the Jiles-Atherton (J-A) the work increases in complexity since one must solve a nonlinear system with a relative large number of design variables. In this context, fitting methods based on efficient stochastic optimization metaheuristics is an attractive solution to solv problems related to the phenomena of nonlinear hysteresis applications. In this study, an improved multiobjective lightning search algorithm (IMLSA), a stochastic optimization metaheuristic algorithm, is introduced for solving J-A hysteresis model parameter estimation. The proposed IMLSA based on a mutation operator of the differential evolution is validated using measured hysteresis data from a rotational single sheet tester. In addition, thorough examination of comparison results of IMLSA with optimization results using a multiobjective lightning search showed that the performance of the IMLSA is promising in parameters estimation of nonlinear hysteretic J-A models.},
 bibtype = {inproceedings},
 author = {Dos Santos Coelho, Leandro and Pierezan, Juliano and Batistela, Nelson Jhoe and Leite, Jean Vianei and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST.2018.8376583},
 booktitle = {2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018}
}

Hysteresis is a fundamental property commonly encountered in physical systems of a wide variety of engineering and science fields and the parameters determination and/or optimization of hysteresis dynamical models is an essential approach for adequate hysteretic material simulations. In magnetic vector hysteresis models as the Jiles-Atherton (J-A) the work increases in complexity since one must solve a nonlinear system with a relative large number of design variables. In this context, fitting methods based on efficient stochastic optimization metaheuristics is an attractive solution to solv problems related to the phenomena of nonlinear hysteresis applications. In this study, an improved multiobjective lightning search algorithm (IMLSA), a stochastic optimization metaheuristic algorithm, is introduced for solving J-A hysteresis model parameter estimation. The proposed IMLSA based on a mutation operator of the differential evolution is validated using measured hysteresis data from a rotational single sheet tester. In addition, thorough examination of comparison results of IMLSA with optimization results using a multiobjective lightning search showed that the performance of the IMLSA is promising in parameters estimation of nonlinear hysteretic J-A models.

@inproceedings{
 title = {LTE measurements for flying relays},
 type = {inproceedings},
 year = {2018},
 keywords = {4G/5G networks,Flying relays,LTE,UAV},
 pages = {1-4},
 id = {51feac1a-f5d0-3c90-8864-5a362ef91437},
 created = {2020-02-29T16:57:44.010Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.221Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Batistatos2018},
 private_publication = {false},
 abstract = {Future cellular networks promise high data rates, ubiquitous services everywhere and flexibility. UAV-assisted networks is a promising system architecture that enables network coverage extension and capacity enhancement. The quality of the backhaul link between the flying node and the ground base station is of a great importance for the system performance. Key performance factors for the quality of the backhaul connection are the signal strength and interference levels at the aerial flying node. In order to study the feasibility of such a scenario, a measurement campaign was held using a quadcopter flying over a mid-sized town, measuring the levels of the LTE signal and interference in the air. Results show that the number of the available LTE cells which could be used as a backhaul connection, fluctuates as the UAV ascends to higher altitudes. Altitudes of 60m and 150m offer more handover options, with at least a guaranteed basic 4G data rate, while 40m or 120m are good choices for realizing high capacity backhaul links. At 40m the potential aerial node has good chances to provide high capacity links and have more handover options. At very high altitudes, although the number of the reliable cells decreases, the UAV still detects candidate cells for establishing a 4G connection and provide acceptable QoS.},
 bibtype = {inproceedings},
 author = {Batistatos, Michael C. and Tsoulos, George V. and Zarbouti, Dimitra A. and Athanasiadou, Georgia E. and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST.2018.8376626},
 booktitle = {2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018}
}

Future cellular networks promise high data rates, ubiquitous services everywhere and flexibility. UAV-assisted networks is a promising system architecture that enables network coverage extension and capacity enhancement. The quality of the backhaul link between the flying node and the ground base station is of a great importance for the system performance. Key performance factors for the quality of the backhaul connection are the signal strength and interference levels at the aerial flying node. In order to study the feasibility of such a scenario, a measurement campaign was held using a quadcopter flying over a mid-sized town, measuring the levels of the LTE signal and interference in the air. Results show that the number of the available LTE cells which could be used as a backhaul connection, fluctuates as the UAV ascends to higher altitudes. Altitudes of 60m and 150m offer more handover options, with at least a guaranteed basic 4G data rate, while 40m or 120m are good choices for realizing high capacity backhaul links. At 40m the potential aerial node has good chances to provide high capacity links and have more handover options. At very high altitudes, although the number of the reliable cells decreases, the UAV still detects candidate cells for establishing a 4G connection and provide acceptable QoS.

@inproceedings{
 title = {Spiral inductor design based on fireworks optimization combined with free search},
 type = {inproceedings},
 year = {2018},
 keywords = {fireworks optimization,optimization,radio frequency,spiral inductor,stochastic metaheuristics},
 pages = {1-4},
 id = {6adea789-431e-3a6b-9ee5-c4a3481cbfc9},
 created = {2020-02-29T16:57:44.044Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.543Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Jeronymo2018},
 private_publication = {false},
 abstract = {Over the decades, metaheuristics, such as evolutionary and swarm intelligence paradigmms have been efficiently applied to solve real world engineering problems. Spiral inductors are widely used in radio frequency applications, such as voltage controlled oscillators, telemetry, matching networks and low noise amplifiers. However, the good performance of the spiral inductors represents a designing challenge. Metaheuristic method can be applied, in order to meet the design requirements of a spiral inductor. In this paper, an improved fireworks optimization algorithm (IFOA) combined with free search (FS) and opposition-based learning is proposed. The new algorithm is validated to optimize the number of turns for the spiral, the width of the turns, the separation between turns and the diameter for the inner-most turn of a spiral inductor which operates at 95 MHz. Simulation results indicate the promising performance of the improved FOA when compared with the classical FOA and a genetic algorithm in spiral inductors design application.},
 bibtype = {inproceedings},
 author = {Jeronymo, Daniel Cavalcanti and Leite, Jean Vianei and Mariani, Viviana Cocco and Dos Santos Coelho, Leandro and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST.2018.8376558},
 booktitle = {2018 7th International Conference on Modern Circuits and Systems Technologies, MOCAST 2018}
}

Over the decades, metaheuristics, such as evolutionary and swarm intelligence paradigmms have been efficiently applied to solve real world engineering problems. Spiral inductors are widely used in radio frequency applications, such as voltage controlled oscillators, telemetry, matching networks and low noise amplifiers. However, the good performance of the spiral inductors represents a designing challenge. Metaheuristic method can be applied, in order to meet the design requirements of a spiral inductor. In this paper, an improved fireworks optimization algorithm (IFOA) combined with free search (FS) and opposition-based learning is proposed. The new algorithm is validated to optimize the number of turns for the spiral, the width of the turns, the separation between turns and the diameter for the inner-most turn of a spiral inductor which operates at 95 MHz. Simulation results indicate the promising performance of the improved FOA when compared with the classical FOA and a genetic algorithm in spiral inductors design application.

@inproceedings{
 title = {Joint optimization towards power consumption and electromagnetic exposure for Massive MIMO 5G networks},
 type = {inproceedings},
 year = {2018},
 pages = {1208-1214},
 volume = {2018-Septe},
 id = {3e42220e-5c0a-37eb-94d2-b1b65f7faab4},
 created = {2020-02-29T16:57:44.968Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.849Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Matalatala2018},
 private_publication = {false},
 abstract = {In the next generation of wireless communication networks, Massive MIMO remains the appropriate technology to provide higher throughput to the users with incredible gains in terms of power consumption and energy efficiency. However, current research rarely considers the electromagnetic field exposure during the network design phase. In this paper, we propose a simulation-based method that enables an optimal design of the massive MIMO 5G networks with respect to both power consumption and electromagnetic field exposure. The results of the simulations show that the massive MIMO network achieves the same performance in terms of users coverage with 10 times less power consumption and an electric field strength 17 times weaker in comparison with the traditional 4G network.},
 bibtype = {inproceedings},
 author = {Matalatala, Michel and Deruyck, Margot and Tanghe, Emmeric and Goudos, Sotirios and Martens, Luc and Joseph, Wout},
 doi = {10.1109/PIMRC.2018.8580818},
 booktitle = {IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC}
}

In the next generation of wireless communication networks, Massive MIMO remains the appropriate technology to provide higher throughput to the users with incredible gains in terms of power consumption and energy efficiency. However, current research rarely considers the electromagnetic field exposure during the network design phase. In this paper, we propose a simulation-based method that enables an optimal design of the massive MIMO 5G networks with respect to both power consumption and electromagnetic field exposure. The results of the simulations show that the massive MIMO network achieves the same performance in terms of users coverage with 10 times less power consumption and an electric field strength 17 times weaker in comparison with the traditional 4G network.

@inproceedings{
 title = {Spectrum Allocation in Next Generation Radio Networks using Emerging Nature-inspired Algorithms},
 type = {inproceedings},
 year = {2018},
 id = {aa855703-fefd-3b95-a5d3-3dbf27d3d593},
 created = {2020-02-29T16:57:45.265Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.240Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Tegou2018a},
 private_publication = {false},
 abstract = {The key task of a cognitive radio network (CRN) is the effective allocation of spectrum resources according to user needs and requirements. In order to maximize the utilization of the available spectrum, a dynamic allocation of available channels to secondary users is needed. This problem is known as the spectrum allocation problem and it is a combinatorial optimization problem. A possible optimization algorithm that can be applied is chaotic biogeography-based optimization (CBBO). In this paper, a thorough assessment of CBBO is performed in the sense of comparing CBBO with other popular algorithms. According to the simulation results, the CBBO algorithm outperforms competing algorithms in terms of average convergence rate and accuracy.},
 bibtype = {inproceedings},
 author = {Tegou, Thomas I. and Siakavara, Katherine and Nikolaidis, Spiros and Goudos, Sotirios K. and Vergados, Dimitrios D. and Sarigiannidis, Panagiotis and Obaidat, Mohammad},
 doi = {10.1109/CSNDSP.2018.8471797},
 booktitle = {2018 11th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2018}
}

The key task of a cognitive radio network (CRN) is the effective allocation of spectrum resources according to user needs and requirements. In order to maximize the utilization of the available spectrum, a dynamic allocation of available channels to secondary users is needed. This problem is known as the spectrum allocation problem and it is a combinatorial optimization problem. A possible optimization algorithm that can be applied is chaotic biogeography-based optimization (CBBO). In this paper, a thorough assessment of CBBO is performed in the sense of comparing CBBO with other popular algorithms. According to the simulation results, the CBBO algorithm outperforms competing algorithms in terms of average convergence rate and accuracy.

@article{
 title = {MIMO antenna selection using biogeography-based optimization with nonlinear migration models},
 type = {article},
 year = {2018},
 keywords = {ant colony optimization,antenna selection,biogeography-based optimization,evolutionaryr algorithms,genetic algorithm,multiple-input multiple-output systems},
 volume = {31},
 id = {12b4d4ec-74aa-349a-ab0b-5c79a6e60d5e},
 created = {2020-02-29T16:57:45.278Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.499Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Fountoukidis2018},
 private_publication = {false},
 abstract = {This papers deals with the problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) wireless system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS problem. Moreover, the performance of different BBO migration models is compared with a real valued genetic algorithm (RVGA) as well as with the ant colony optimization (ACO). Representative simulation scenarios are provided in detail, involving selection of 2 × 4,3 × 5,4 × 6,8 × 8 antennas in a 16 × 16 MIMO system. The numerical results demonstrate the efficiency and the applicability of the BBO algorithm in modern MIMO wireless systems.},
 bibtype = {article},
 author = {Fountoukidis, Konstantinos C. and Kalialakis, Christos and Psannis, Kostas E. and Siakavara, Katherine and Goudos, Sotirios K. and Sarigiannidis, Panagiotis and Obaidat, Mohammad},
 doi = {10.1002/dac.3813},
 journal = {International Journal of Communication Systems},
 number = {17}
}

This papers deals with the problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) wireless system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS problem. Moreover, the performance of different BBO migration models is compared with a real valued genetic algorithm (RVGA) as well as with the ant colony optimization (ACO). Representative simulation scenarios are provided in detail, involving selection of 2 × 4,3 × 5,4 × 6,8 × 8 antennas in a 16 × 16 MIMO system. The numerical results demonstrate the efficiency and the applicability of the BBO algorithm in modern MIMO wireless systems.

@article{
 title = {Spectrum allocation in cognitive radio networks using chaotic biogeography-based optimisation},
 type = {article},
 year = {2018},
 pages = {328-335},
 volume = {7},
 id = {44455405-e983-3385-88b1-ffc88a03db2a},
 created = {2020-02-29T16:57:45.343Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.158Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Tegou2018},
 private_publication = {false},
 abstract = {Cognitive radio networks are a promising technology for the improvement of the spectrum utilisation. The basic idea is to maximise the utilisation of the available spectrum by dynamically assigning available channels to secondary users. This problem known as the spectrum allocation problem is non-deterministic polynomial-time hard (NP-hard). Chaotic biogeographybased optimisation (CBBO) is a recently proposed evolutionary algorithm that can be applied to the above-mentioned problem. The authors compare CBBO with other popular algorithms in different spectrum allocation problem cases. The results show that CBBO performs in general better or similar to the other algorithms.},
 bibtype = {article},
 author = {Tegou, Thomas I. and Tsiflikiotis, Antonios and Vergados, Dimitrios D. and Siakavara, Katherine and Nikolaidis, Spiros and Goudos, Sotirios K. and Sarigiannidis, Panagiotis and Obaidat, Mohammad},
 doi = {10.1049/iet-net.2017.0264},
 journal = {IET Networks},
 number = {5}
}

Cognitive radio networks are a promising technology for the improvement of the spectrum utilisation. The basic idea is to maximise the utilisation of the available spectrum by dynamically assigning available channels to secondary users. This problem known as the spectrum allocation problem is non-deterministic polynomial-time hard (NP-hard). Chaotic biogeographybased optimisation (CBBO) is a recently proposed evolutionary algorithm that can be applied to the above-mentioned problem. The authors compare CBBO with other popular algorithms in different spectrum allocation problem cases. The results show that CBBO performs in general better or similar to the other algorithms.

@article{
 title = {An Evaluation of the Equivalent Inverter Modeling Approach},
 type = {article},
 year = {2018},
 keywords = {CCS compatible,CMOS gate modeling,Equivalent inverter,Simulation,Timing/power characterization},
 pages = {2665-2693},
 volume = {37},
 id = {35a9fabd-c02d-3054-8aab-1b88c573da87},
 created = {2020-02-29T16:57:45.363Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.711Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Messaris2018},
 private_publication = {false},
 abstract = {Accurate modeling of CMOS logic gates for timing and power characterization is a very important task in integrated circuits technology since it facilitates significantly the design phase. Parametric models provide flexibility in determining the circuit performance in various design corners. However, the direct analysis of a complex CMOS gate aiming in an analytical and parametric model is a difficult and cumbersome task. An alternative way to model these gates is by using the equivalent inverter approach. According to this, an inverter with appropriate transistor widths is defined in order to present the same response with the complex gate it models. The challenge with this approach is to propose a simple method to predict the appropriate transistor widths of the equivalent inverter. Then, an analytical model for the CMOS inverter can be used to provide estimates for the complex gates. In this paper, a macro-modeling method is proposed for determining the transistor widths of the equivalent inverter and a technique for providing parametric expressions for these widths in terms of input transition time, output capacitive load, initial transistor width, supply voltage and temperature. A tool is developed to provide timing and power characterizations for the cells of a digital cell library, much faster than conventional numerical circuit simulators. The results prove the efficiency of the equivalent inverter approach in modeling complex gates.},
 bibtype = {article},
 author = {Messaris, Ioannis and Galani, Christina and Ntogramatzi, Maria and Karagiorgos, Nikolaos and Chaourani, Panagiotis and Tzormpatzoglou, Andreas and Goudos, Sotirios and Nikolaidis, Spyridon},
 doi = {10.1007/s00034-017-0692-5},
 journal = {Circuits, Systems, and Signal Processing},
 number = {7}
}

Accurate modeling of CMOS logic gates for timing and power characterization is a very important task in integrated circuits technology since it facilitates significantly the design phase. Parametric models provide flexibility in determining the circuit performance in various design corners. However, the direct analysis of a complex CMOS gate aiming in an analytical and parametric model is a difficult and cumbersome task. An alternative way to model these gates is by using the equivalent inverter approach. According to this, an inverter with appropriate transistor widths is defined in order to present the same response with the complex gate it models. The challenge with this approach is to propose a simple method to predict the appropriate transistor widths of the equivalent inverter. Then, an analytical model for the CMOS inverter can be used to provide estimates for the complex gates. In this paper, a macro-modeling method is proposed for determining the transistor widths of the equivalent inverter and a technique for providing parametric expressions for these widths in terms of input transition time, output capacitive load, initial transistor width, supply voltage and temperature. A tool is developed to provide timing and power characterizations for the cells of a digital cell library, much faster than conventional numerical circuit simulators. The results prove the efficiency of the equivalent inverter approach in modeling complex gates.

@inbook{
 type = {inbook},
 year = {2018},
 pages = {614-636},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2990-3.ch026},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
 id = {d942cf71-7119-3524-a01e-a1ddc94604f1},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Vasant2018},
 source_type = {incollection},
 private_publication = {false},
 abstract = {Differential Evolution (DE) is a popular evolutionary algorithm that has been applied to several antenna design problems. However, DE is best suited for continuous search spaces. Therefore, in order to apply it to combinatorial optimization problems for antenna design a binary version of the DE algorithm has to be used. In this chapter, the author presents a design technique based on Novel Binary DE (NBDE). The main benefit of NBDE is reserving the DE updating strategy to binary space. This chapter presents results from design cases that include array thinning, phased array design with discrete phase shifters, and conformal array design with discrete excitations based on NBDE.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 editor = {Vasant, Pandian and Alparslan-Gok, Sirma Zeynep and Weber, Gerhard-Wilhelm},
 doi = {10.4018/978-1-5225-2990-3.ch026},
 chapter = {Optimization of Antenna Design Problems Using Binary Differential Evolution},
 title = {Handbook of Research on Emergent Applications of Optimization Algorithms}
}

Differential Evolution (DE) is a popular evolutionary algorithm that has been applied to several antenna design problems. However, DE is best suited for continuous search spaces. Therefore, in order to apply it to combinatorial optimization problems for antenna design a binary version of the DE algorithm has to be used. In this chapter, the author presents a design technique based on Novel Binary DE (NBDE). The main benefit of NBDE is reserving the DE updating strategy to binary space. This chapter presents results from design cases that include array thinning, phased array design with discrete phase shifters, and conformal array design with discrete excitations based on NBDE.

@inbook{
 type = {inbook},
 year = {2018},
 pages = {5967-5980},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2255-3.ch519},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
 id = {67edbf84-2863-31fc-9714-9f74226b9e9e},
 created = {2023-02-11T21:26:04.074Z},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {KhosrowPour2018},
 source_type = {incollection},
 private_publication = {false},
 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 editor = {Khosrow-Pour D.B.A., Mehdi},
 doi = {10.4018/978-1-5225-2255-3.ch519},
 chapter = {Biogeography-Based Optimization Applied to Wireless Communications Problems},
 title = {Encyclopedia of Information Science and Technology, Fourth Edition}
}

@inbook{
 type = {inbook},
 year = {2018},
 pages = {6595-6608},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2255-3.ch572},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
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 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 editor = {Khosrow-Pour D.B.A., Mehdi},
 doi = {10.4018/978-1-5225-2255-3.ch572},
 chapter = {Optimization of Antenna Arrays and Microwave Filters Using Differential Evolution Algorithms},
 title = {Encyclopedia of Information Science and Technology, Fourth Edition}
}

@inbook{
 type = {inbook},
 year = {2018},
 pages = {755-784},
 publisher = {Institution of Engineering and Technology},
 id = {deb0d02b-53a3-30b2-a287-fe71a5653608},
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 citation_key = {Goudos2018},
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 bibtype = {inbook},
 author = {Goudos, Sotirios K},
 doi = {10.1049/pbce119h_ch26},
 chapter = {Swarm intelligence algorithms for antenna design and wireless communications},
 title = {Swarm Intelligence - Volume 3: Applications}
}

@article{
 title = {Antenna Design Using Binary Differential Evolution: Application to discrete-valued design problems.},
 type = {article},
 year = {2017},
 pages = {74-93},
 volume = {59},
 id = {22407a46-785b-339c-8787-90359847f71b},
 created = {2020-02-29T16:57:41.757Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.475Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2017d},
 private_publication = {false},
 abstract = {Several antenna design problems are discrete valued. Particle swarm optimization (PSO) and differential evolution (DE) are popular evolutionary algorithms that have been applied to a number of design problems in electromagnetics. However, both PSO and DE are best suited for continuous search spaces. Therefore, to apply these to binary-coded combinatorial optimization problems, binary versions of the aforementioned algorithms must be used. In this article, we introduce a design technique based on novel binary DE (NBDE). The main benefit of NBDE is reserving the DE updating strategy to binary space.},
 bibtype = {article},
 author = {Goudos, Sotirios},
 doi = {10.1109/MAP.2016.2630041},
 journal = {IEEE Antennas and Propagation Magazine},
 number = {1}
}

Several antenna design problems are discrete valued. Particle swarm optimization (PSO) and differential evolution (DE) are popular evolutionary algorithms that have been applied to a number of design problems in electromagnetics. However, both PSO and DE are best suited for continuous search spaces. Therefore, to apply these to binary-coded combinatorial optimization problems, binary versions of the aforementioned algorithms must be used. In this article, we introduce a design technique based on novel binary DE (NBDE). The main benefit of NBDE is reserving the DE updating strategy to binary space.

@inproceedings{
 title = {Application of Opposition-Based Learning concepts for arbitrary patch antenna design for wireless communications},
 type = {inproceedings},
 year = {2017},
 keywords = {Biogeography based optimization,Opposition-based learning,Patch antenna},
 pages = {171-174},
 id = {e62c2754-bbaa-3bd1-b240-f9066f9d3270},
 created = {2020-02-29T16:57:42.320Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.744Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2017c},
 private_publication = {false},
 abstract = {We present an arbitrary-shaped patch antenna design procedure. The design technique is based on a variant of Biogeography Based Optimization (BBO) algorithm. In this paper, we apply Opposition-Based Learning (OBL) concepts for antenna design. More specifically, we use a new Modified Biogeography Based Optimization (BBO) algorithm enhanced with OBL techniques. The preliminary results of the proposed method indicate the advantages and applicability of our approach.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Kalialakis, Christos},
 doi = {10.1109/IWAT.2017.7915350},
 booktitle = {2017 International Workshop on Antenna Technology: Small Antennas, Innovative Structures, and Applications, iWAT 2017}
}

We present an arbitrary-shaped patch antenna design procedure. The design technique is based on a variant of Biogeography Based Optimization (BBO) algorithm. In this paper, we apply Opposition-Based Learning (OBL) concepts for antenna design. More specifically, we use a new Modified Biogeography Based Optimization (BBO) algorithm enhanced with OBL techniques. The preliminary results of the proposed method indicate the advantages and applicability of our approach.

@article{
 title = {Hybrid teaching-learning optimization of wireless sensor networks},
 type = {article},
 year = {2017},
 volume = {28},
 id = {15685eb2-8e1e-3d54-8da7-7e10e0a1f4c4},
 created = {2020-02-29T16:57:42.383Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.494Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Tsiflikiotis2017},
 private_publication = {false},
 abstract = {This paper deals with the power allocation of decentralized detection in an optimal wireless sensor network (WSN). The main objective is to find a solution that minimizes the total power consumed by the WSN, so that the error probability at the fusion center would be below a certain threshold. More specifically, we propose a novel stochastic optimization algorithm, called the TLBO-Jaya algorithm, which is a hybrid form of two recently proposed algorithms, ie, the teaching-learning–based optimization (TLBO) and Jaya algorithms. The proposed optimization solution is evaluated for several WSN cases and compared with results from the literature. Additionally, it is compared with both the TLBO and Jaya algorithms, the heat transfer search algorithm, and the popular particle swarm optimization. Numerical results show that the proposed algorithm performs better than other well-known algorithms in almost all tested cases.},
 bibtype = {article},
 author = {Tsiflikiotis, Antonios and Goudos, Sotirios K. and Karagiannidis, George K.},
 doi = {10.1002/ett.3194},
 journal = {Transactions on Emerging Telecommunications Technologies},
 number = {11}
}

This paper deals with the power allocation of decentralized detection in an optimal wireless sensor network (WSN). The main objective is to find a solution that minimizes the total power consumed by the WSN, so that the error probability at the fusion center would be below a certain threshold. More specifically, we propose a novel stochastic optimization algorithm, called the TLBO-Jaya algorithm, which is a hybrid form of two recently proposed algorithms, ie, the teaching-learning–based optimization (TLBO) and Jaya algorithms. The proposed optimization solution is evaluated for several WSN cases and compared with results from the literature. Additionally, it is compared with both the TLBO and Jaya algorithms, the heat transfer search algorithm, and the popular particle swarm optimization. Numerical results show that the proposed algorithm performs better than other well-known algorithms in almost all tested cases.

@article{
 title = {Passive UHF RFID tags with specific printed antennas for dielectric and metallic objects applications},
 type = {article},
 year = {2017},
 keywords = {Printed antennas,RFID tags,Spiral antennas},
 pages = {735-745},
 volume = {26},
 id = {684ada74-5bc6-37b1-aa13-12d94813fde4},
 created = {2020-02-29T16:57:43.380Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.673Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Siakavara2017},
 private_publication = {false},
 abstract = {Design process and respective results for the synthesis of specific Radiofrequency Identification (RFID) tag antennas, suitable for dielectric and metallic objects, are presented. The antennas were designed for the UHF (865 MHz-869 MHz) band and their basic configuration is that of the printed spiral type. Six modification steps to the classical spiral layout are proposed and it was proved that they can lead to tags with high readability and reading distances up to 10 m when designed for dielectric object and up to 7 m in the case of metallic objects. The results of the measurements of the fabricated tags are explained via theoretical evaluations which take into account reflection phenomena, which are present in a real environment at which the tags are used.},
 bibtype = {article},
 author = {Siakavara, Katherine and Goudos, Sotirios and Theopoulos, Argiris and Sahalos, John},
 doi = {10.13164/re.2017.0735},
 journal = {Radioengineering},
 number = {3}
}

Design process and respective results for the synthesis of specific Radiofrequency Identification (RFID) tag antennas, suitable for dielectric and metallic objects, are presented. The antennas were designed for the UHF (865 MHz-869 MHz) band and their basic configuration is that of the printed spiral type. Six modification steps to the classical spiral layout are proposed and it was proved that they can lead to tags with high readability and reading distances up to 10 m when designed for dielectric object and up to 7 m in the case of metallic objects. The results of the measurements of the fabricated tags are explained via theoretical evaluations which take into account reflection phenomena, which are present in a real environment at which the tags are used.

@inproceedings{
 title = {A dual band antenna based on a Quarter Mode Substrate Integrated Waveguide},
 type = {inproceedings},
 year = {2017},
 keywords = {Antennas,Cavity Antennas,Dual Band Antennas,Substrate Integrated Waveguides},
 id = {4303c602-34b1-3f69-b979-5c251152d270},
 created = {2020-02-29T16:57:43.402Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.115Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Alvarez2017},
 private_publication = {false},
 abstract = {In this work, a new dual band antenna is presented. The antenna is implemented on a quarter mode Substrate Integrated Waveguide (SIW) technology by introducing a slit shaped modification. The dual band antenna concept has been demonstrated for the 2.4GHz and 5GHz WiFi bands but the approach is readily applicable to centimeter and millimeter wave applications due to the low loss characteristics of SIW. Good agreement has been observed between simulations and measurements on a prototype.},
 bibtype = {inproceedings},
 author = {Alvarez, Marc and Kalialakis, Christos and Mira, Fermin and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST.2017.7937621},
 booktitle = {2017 6th International Conference on Modern Circuits and Systems Technologies, MOCAST 2017}
}

In this work, a new dual band antenna is presented. The antenna is implemented on a quarter mode Substrate Integrated Waveguide (SIW) technology by introducing a slit shaped modification. The dual band antenna concept has been demonstrated for the 2.4GHz and 5GHz WiFi bands but the approach is readily applicable to centimeter and millimeter wave applications due to the low loss characteristics of SIW. Good agreement has been observed between simulations and measurements on a prototype.

@inproceedings{
 title = {A preliminary coverage study in millimeter wave bands for 5G communication networks},
 type = {inproceedings},
 year = {2017},
 keywords = {5G communication networks,millimeter wave bands,radio propagation models},
 id = {afa9b638-a033-36d6-8444-d2a2c739cafe},
 created = {2020-02-29T16:57:43.422Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:48.776Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kaitatzis2017},
 private_publication = {false},
 abstract = {In this paper, we make a preliminary coverage study for base stations (BS) in millimeter wave bands based on recently proposed propagation models. More specifically, we compute the cell radius and the coverage area of a future fifth generation (5G) cellular network based on the Close-In (CI) and the Alpha-Beta-Gamma (ABG) radio propagation models. Also, the required base station density is calculated corresponding to urban, suburban and rural regions.},
 bibtype = {inproceedings},
 author = {Kaitatzis, C. and Boursianis, A. and Goudos, S. K. and Dallas, P. I.},
 doi = {10.1109/MOCAST.2017.7937634},
 booktitle = {2017 6th International Conference on Modern Circuits and Systems Technologies, MOCAST 2017}
}

In this paper, we make a preliminary coverage study for base stations (BS) in millimeter wave bands based on recently proposed propagation models. More specifically, we compute the cell radius and the coverage area of a future fifth generation (5G) cellular network based on the Close-In (CI) and the Alpha-Beta-Gamma (ABG) radio propagation models. Also, the required base station density is calculated corresponding to urban, suburban and rural regions.

@article{
 title = {Cognitive Radio Engine Design for IoT Using Real-Coded Biogeography-Based Optimization and Fuzzy Decision Making},
 type = {article},
 year = {2017},
 keywords = {Biogeography-based optimization (BBO),Cognitive radio (CR),Evolutionary algorithms,Fuzzy decision making,Real-coded biogeography-based optimization (RCBBO)},
 pages = {1813-1833},
 volume = {97},
 id = {61fe89e9-023b-3a45-be16-fc2200337f21},
 created = {2020-02-29T16:57:43.448Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.113Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Paraskevopoulos2017},
 private_publication = {false},
 abstract = {The Internet of Things (IoT) paradigm expands the current Internet and enables communication through machine to machine, while posing new challenges. Cognitive radio (CR) Systems have received much attention over the last decade, because of their ability to flexibly adapt their transmission parameters to their changing environment. Current technology trends are shifting to the adaptability of cognitive radio networks into IoT. The determination of the appropriate transmission parameters for a given wireless channel environment is the main feature of a cognitive radio engine. For wireless multicarrier transceivers, the problem becomes high dimensional due to the large number of decision variables required. Evolutionary algorithms are suitable techniques to solve the above-mentioned problem. In this paper, we design a CR engine for wireless multicarrier transceivers using real-coded biogeography-based optimization (RCBBO). The CR engine also uses a fuzzy decision maker for obtaining the best compromised solution. RCBBO uses a mutation operator in order to improve the diversity of the population and enhance the exploration ability of the original BBO algorithm. The simulation results show that the RCBBO driven CR engine can obtain better results than the original BBO and outperform results from the literature. Moreover, RCBBO is more efficient when applied to high-dimensional problems in cases of multicarrier system.},
 bibtype = {article},
 author = {Paraskevopoulos, Athanasios and Dallas, Panagiotis I. and Siakavara, Katherine and Goudos, Sotirios K.},
 doi = {10.1007/s11277-017-4646-9},
 journal = {Wireless Personal Communications},
 number = {2}
}

The Internet of Things (IoT) paradigm expands the current Internet and enables communication through machine to machine, while posing new challenges. Cognitive radio (CR) Systems have received much attention over the last decade, because of their ability to flexibly adapt their transmission parameters to their changing environment. Current technology trends are shifting to the adaptability of cognitive radio networks into IoT. The determination of the appropriate transmission parameters for a given wireless channel environment is the main feature of a cognitive radio engine. For wireless multicarrier transceivers, the problem becomes high dimensional due to the large number of decision variables required. Evolutionary algorithms are suitable techniques to solve the above-mentioned problem. In this paper, we design a CR engine for wireless multicarrier transceivers using real-coded biogeography-based optimization (RCBBO). The CR engine also uses a fuzzy decision maker for obtaining the best compromised solution. RCBBO uses a mutation operator in order to improve the diversity of the population and enhance the exploration ability of the original BBO algorithm. The simulation results show that the RCBBO driven CR engine can obtain better results than the original BBO and outperform results from the literature. Moreover, RCBBO is more efficient when applied to high-dimensional problems in cases of multicarrier system.

@article{
 title = {A Survey of IoT Key Enabling and Future Technologies: 5G, Mobile IoT, Sematic Web and Applications},
 type = {article},
 year = {2017},
 keywords = {5G,Internet of Things,LTE,Semantic Web,Smart City},
 pages = {1645-1675},
 volume = {97},
 id = {fc8392fb-e4d3-371c-8188-7f493cf7b658},
 created = {2020-02-29T16:57:43.464Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.491Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2017b},
 private_publication = {false},
 abstract = {The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. In this paper, we examine, review and present the current IoT technologies starting from the physical layer to the application and data layer. Additionally, we focus on future IoT key enabling technologies like the new fifth generation (5G) networks and Semantic Web. Finally, we present main IoT application domains like smart cities, transportation, logistics, and healthcare.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Dallas, Panagiotis I. and Chatziefthymiou, Stella and Kyriazakos, Sofoklis},
 doi = {10.1007/s11277-017-4647-8},
 journal = {Wireless Personal Communications},
 number = {2}
}

The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. In this paper, we examine, review and present the current IoT technologies starting from the physical layer to the application and data layer. Additionally, we focus on future IoT key enabling technologies like the new fifth generation (5G) networks and Semantic Web. Finally, we present main IoT application domains like smart cities, transportation, logistics, and healthcare.

@inproceedings{
 title = {Antenna selection for MIMO systems using biogeography based optimization},
 type = {inproceedings},
 year = {2017},
 keywords = {Ant colony optimization (ACO),Antenna selection (AS),Biogeography-based optimization (BBO),Evolutionary algorithms (EA),Genetic algorithm (GA),Multiple-input multiple-output (MIMO) systems},
 pages = {319-322},
 id = {f30eb608-8f43-3e99-822f-c6adf60e085e},
 created = {2020-02-29T16:57:43.493Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.746Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Fountoukidis2017},
 private_publication = {false},
 abstract = {In this work, we solve a problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS for the channel capacity function. We apply different BBO migration models for simulated channels. The comparisons with other popular evolutionary algorithms such as the genetic algorithm (GA) and the ant colony optimization (ACO) show the efficiency and the applicability of the BBO algorithm. Results are given for three representative scenarios involving selection of 2×4, 3×5, 4×6 antennas in a 16×16 MIMO system.},
 bibtype = {inproceedings},
 author = {Fountoukidis, Konstantinos C. and Siakavara, Katherine and Goudos, Sotirios K. and Kalialakis, Christos},
 doi = {10.1109/IWAT.2017.7915390},
 booktitle = {2017 International Workshop on Antenna Technology: Small Antennas, Innovative Structures, and Applications, iWAT 2017}
}

In this work, we solve a problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS for the channel capacity function. We apply different BBO migration models for simulated channels. The comparisons with other popular evolutionary algorithms such as the genetic algorithm (GA) and the ant colony optimization (ACO) show the efficiency and the applicability of the BBO algorithm. Results are given for three representative scenarios involving selection of 2×4, 3×5, 4×6 antennas in a 16×16 MIMO system.

@article{
 title = {Optimization of Power Consumption in 4G LTE Networks Using a Novel Barebones Self-adaptive Differential Evolution Algorithm},
 type = {article},
 year = {2017},
 keywords = {Barebones differential evolution,Base stations,Coverage,Differential evolution,LTE,Power consumption},
 pages = {109-120},
 volume = {66},
 id = {48cb9a50-1966-3e27-a2ab-4171f984177b},
 created = {2020-02-29T16:57:44.075Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.316Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2017a},
 private_publication = {false},
 abstract = {The power consumption of wireless access networks is an important issue. In this paper, the power consumption of Long Term Evolution (LTE) base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a new Barebones Self-adaptive Differential Evolution. The results of the proposed method indicate the advantages and applicability of our approach.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout},
 doi = {10.1007/s11235-017-0279-2},
 journal = {Telecommunication Systems},
 number = {1}
}

The power consumption of wireless access networks is an important issue. In this paper, the power consumption of Long Term Evolution (LTE) base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a new Barebones Self-adaptive Differential Evolution. The results of the proposed method indicate the advantages and applicability of our approach.

@inproceedings{
 title = {Evolutionary design of a dual band E-shaped patch antenna for 5G mobile communications},
 type = {inproceedings},
 year = {2017},
 keywords = {5G,TLBO algorithm,dual-band operation,mmWave,mobile communications,patch antennas},
 id = {d4ddd908-8ed1-301e-8427-435ddd09270b},
 created = {2020-02-29T16:57:44.972Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.736Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2017},
 private_publication = {false},
 abstract = {Fifth generation (5G) wireless technology is a promising solution for multi-Gbps data rates in future mobile communications. The new devices are expected to operate at millimeter wave frequencies. To address the 5G requirements novel antennas have to be developed. In this paper the Teaching-Learning-Optimization (TLBO) algorithm is applied in order to design a dual-band E-shaped patch antenna. The geometrical parameters of the aperture-coupled antenna are the inputs of the optimization algorithm. The method gives acceptable design solutions achieving simultaneously S11 minimization and low VSWR at the frequencies of interest (25GHz and 37GHz).},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Tsiflikiotis, A. and Babas, D. and Siakavara, K. and Kalialakis, C. and Karagiannidis, G. K.},
 doi = {10.1109/MOCAST.2017.7937640},
 booktitle = {2017 6th International Conference on Modern Circuits and Systems Technologies, MOCAST 2017}
}

Fifth generation (5G) wireless technology is a promising solution for multi-Gbps data rates in future mobile communications. The new devices are expected to operate at millimeter wave frequencies. To address the 5G requirements novel antennas have to be developed. In this paper the Teaching-Learning-Optimization (TLBO) algorithm is applied in order to design a dual-band E-shaped patch antenna. The geometrical parameters of the aperture-coupled antenna are the inputs of the optimization algorithm. The method gives acceptable design solutions achieving simultaneously S11 minimization and low VSWR at the frequencies of interest (25GHz and 37GHz).

@article{
 title = {Experimental optimization of exposure index and quality of service in WLAN networks},
 type = {article},
 year = {2017},
 pages = {394-405},
 volume = {175},
 id = {57944ad9-035e-3b21-a595-78a4f254d248},
 created = {2020-02-29T16:57:45.315Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.163Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Plets2017},
 private_publication = {false},
 abstract = {This paper presents the first real-life optimization of the Exposure Index (EI). A genetic optimization algorithm is developed and applied to three real-life Wireless Local Area Network scenarios in an experimental testbed. The optimization accounts for downlink, uplink and uplink of other users, for realistic duty cycles, and ensures a sufficient Quality of Service to all users. EI reductions up to 97.5% compared to a reference configuration can be achieved in a downlink-only scenario, in combination with an improved Quality of Service. Due to the dominance of uplink exposure and the lack of WiFi power control, no optimizations are possible in scenarios that also consider uplink traffic. However, future deployments that do implement WiFi power control can be successfully optimized, with EI reductions up to 86% compared to a reference configuration and an EI that is 278 times lower than optimized configurations under the absence of power control.},
 bibtype = {article},
 author = {Plets, David and Vermeeren, Günter and De Poorter, Eli and Moerman, Ingrid and Goudos, Sotirios K. and Martens, Luc and Joseph, Wout},
 doi = {10.1093/rpd/ncw363},
 journal = {Radiation Protection Dosimetry},
 number = {3}
}

This paper presents the first real-life optimization of the Exposure Index (EI). A genetic optimization algorithm is developed and applied to three real-life Wireless Local Area Network scenarios in an experimental testbed. The optimization accounts for downlink, uplink and uplink of other users, for realistic duty cycles, and ensures a sufficient Quality of Service to all users. EI reductions up to 97.5% compared to a reference configuration can be achieved in a downlink-only scenario, in combination with an improved Quality of Service. Due to the dominance of uplink exposure and the lack of WiFi power control, no optimizations are possible in scenarios that also consider uplink traffic. However, future deployments that do implement WiFi power control can be successfully optimized, with EI reductions up to 86% compared to a reference configuration and an EI that is 278 times lower than optimized configurations under the absence of power control.

@inproceedings{
 title = {Performance Comparison of 4G and Massive MIMO Network Configurations Using Heuristic and Metaheuristic Approaches},
 type = {inproceedings},
 year = {2017},
 pages = {3172-3176},
 city = {Paris, France},
 id = {744466d4-55a1-3f0b-bfab-0a4c3ca32df5},
 created = {2022-07-14T18:38:19.111Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-07-14T18:38:19.111Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goud1703:Performance},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The reduction of power consumption in wireless access networks is a challenging and important issue, which will also play an important role in future cellular systems. Massive MIMO (multiple-input multiple-output) is one of the key technologies to handle orders of magnitude more data traffic and to be included in the fifth generation (5G) cellular systems. In this paper, we compare 4G and Massive MIMO network configurations. Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user. We study the application of a capacity-based heuristic and an evolutionary algorithm (EA) to the above-mentioned network design problem. Moreover, we introduce a new hybrid approach that uses both an EA and concepts from the capacity-based heuristic. We compare and discuss the preliminary results of both technologies.},
 bibtype = {inproceedings},
 author = {Sotirios Goudos, undefined and Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout},
 booktitle = {2017 11th European Conference on Antennas and Propagation (EUCAP) (EuCAP 2017)}
}

The reduction of power consumption in wireless access networks is a challenging and important issue, which will also play an important role in future cellular systems. Massive MIMO (multiple-input multiple-output) is one of the key technologies to handle orders of magnitude more data traffic and to be included in the fifth generation (5G) cellular systems. In this paper, we compare 4G and Massive MIMO network configurations. Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user. We study the application of a capacity-based heuristic and an evolutionary algorithm (EA) to the above-mentioned network design problem. Moreover, we introduce a new hybrid approach that uses both an EA and concepts from the capacity-based heuristic. We compare and discuss the preliminary results of both technologies.

@article{
 title = {A novel generalized oppositional biogeography-based optimization algorithm: Application to peak to average power ratio reduction in OFDM systems},
 type = {article},
 year = {2016},
 keywords = {Biogeography-based optimization (BBO),Combinatorial optimization,Evolutionary algorithms,OFDM,Opposition based Learning,PAPR,PTS},
 pages = {705-722},
 volume = {14},
 id = {4df91578-6d66-39b8-bed3-65efda26a959},
 created = {2020-02-29T16:57:41.805Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.721Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016g},
 private_publication = {false},
 abstract = {A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization (GOBBO) algorithm which is enhanced with Oppositional Based Learning (OBL) techniques. We apply both the original BBO and the new Generalized Oppositional BBO (GOBBO) to the PTS problem. The GOBBO-PTS method is compared with other PTS schemes for PAPR reduction found in the literature. The simulation results show that GOBBO and BBO are in general highly efficient in producing significant PAPR reduction and reducing the PTS search complexity.},
 bibtype = {article},
 author = {Goudos, Sotirios K.},
 doi = {10.1515/math-2016-0066},
 journal = {Open Mathematics},
 number = {1}
}

A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization (GOBBO) algorithm which is enhanced with Oppositional Based Learning (OBL) techniques. We apply both the original BBO and the new Generalized Oppositional BBO (GOBBO) to the PTS problem. The GOBBO-PTS method is compared with other PTS schemes for PAPR reduction found in the literature. The simulation results show that GOBBO and BBO are in general highly efficient in producing significant PAPR reduction and reducing the PTS search complexity.

@article{
 title = {Design of Large Thinned Arrays Using Different Biogeography-Based Optimization Migration Models},
 type = {article},
 year = {2016},
 volume = {2016},
 id = {d705b4e2-e27f-3a6b-a1ae-756c32971a9d},
 created = {2020-02-29T16:57:41.997Z},
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 authored = {true},
 confirmed = {true},
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 citation_key = {Goudos2016f},
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 abstract = {Array thinning is a common discrete-valued combinatorial optimization problem. Evolutionary algorithms are suitable techniques for above-mentioned problem. Biogeography-Based Optimization (BBO), which is inspired by the science of biogeography, is a stochastic population-based evolutionary algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other nonlinear migration models have been proposed in the literature. In this paper, we apply BBO with four different migration models to five different large array design cases. Additionally we compare results with five other popular algorithms. The problems dimensions range from 150 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other algorithms. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Sahalos, John N.},
 doi = {10.1155/2016/5359298},
 journal = {International Journal of Antennas and Propagation}
}

Array thinning is a common discrete-valued combinatorial optimization problem. Evolutionary algorithms are suitable techniques for above-mentioned problem. Biogeography-Based Optimization (BBO), which is inspired by the science of biogeography, is a stochastic population-based evolutionary algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other nonlinear migration models have been proposed in the literature. In this paper, we apply BBO with four different migration models to five different large array design cases. Additionally we compare results with five other popular algorithms. The problems dimensions range from 150 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other algorithms. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.

@inproceedings{
 title = {Optimal power allocation in wireless sensor networks using emerging nature-inspired algorithms},
 type = {inproceedings},
 year = {2016},
 keywords = {cat swarm optimization,cuckoo search,optimal power allocation,particle swarm optimization,wireless sensor network},
 id = {d9d77a12-3e69-3515-a9d3-baa1b6cb953b},
 created = {2020-02-29T16:57:42.052Z},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Tsiflikiotis2016},
 private_publication = {false},
 abstract = {Optimal power allocation problem for decentralized detection in a wireless sensor network (WSN) is presented. Our goal is to find a numerical solution for the optimal power allocation scheme that minimizes the total power spent by the wireless sensor network so that the detection error probability is below a desired value. We evaluate and compare the performance of two emerging nature inspired algorithms like the Cat Swarm Optimization (CSO), and the Cuckoo Search (CS). Both are also compared with the popular Particle Swarm Optimization (PSO) algorithm. The results show that PSO provides slightly better solutions when the network consists of a small number of sensors, while CSO outperforms the other algorithms as the number of sensors increases.},
 bibtype = {inproceedings},
 author = {Tsiflikiotis, Antonios and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST.2016.7495127},
 booktitle = {2016 5th International Conference on Modern Circuits and Systems Technologies, MOCAST 2016}
}

Optimal power allocation problem for decentralized detection in a wireless sensor network (WSN) is presented. Our goal is to find a numerical solution for the optimal power allocation scheme that minimizes the total power spent by the wireless sensor network so that the detection error probability is below a desired value. We evaluate and compare the performance of two emerging nature inspired algorithms like the Cat Swarm Optimization (CSO), and the Cuckoo Search (CS). Both are also compared with the popular Particle Swarm Optimization (PSO) algorithm. The results show that PSO provides slightly better solutions when the network consists of a small number of sensors, while CSO outperforms the other algorithms as the number of sensors increases.

@inproceedings{
 title = {A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems},
 type = {inproceedings},
 year = {2016},
 keywords = {Linear array synthesis,array thinning,biogeography based optimization,evolutionary algorithms,migration models,optimization methods},
 pages = {270-277},
 id = {c443f0a9-c008-3c88-81c2-554dc64b79e4},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016e},
 private_publication = {false},
 abstract = {Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other non-linear migration models have been proposed in the literature. A popular combinatorial optimization problem in antenna design is array thinning. The purpose of this paper to study the performance of these models on antenna array thinning problems. We apply BBO with four different migration models to five different array design cases. The problems dimensions range from 50 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other models. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/HPCSim.2016.7568346},
 booktitle = {2016 International Conference on High Performance Computing and Simulation, HPCS 2016}
}

Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other non-linear migration models have been proposed in the literature. A popular combinatorial optimization problem in antenna design is array thinning. The purpose of this paper to study the performance of these models on antenna array thinning problems. We apply BBO with four different migration models to five different array design cases. The problems dimensions range from 50 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other models. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.

@misc{
 title = {Evolutionary algorithms applied to antennas and propagation: A review of state of the art},
 type = {misc},
 year = {2016},
 source = {International Journal of Antennas and Propagation},
 volume = {2016},
 id = {754a5ca7-2cb5-3b1a-9b79-de13856a6a59},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016d},
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 abstract = {A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is presented. EAs have emerged as viable candidates for global optimization problems and have been attracting the attention of the research community interested in solving real-world engineering problems, as evidenced by the fact that very large number of antenna design problems have been addressed in the literature in recent years by using EAs. In this paper, our primary focus is on Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), and Differential Evolution (DE), though we also briefly review other recently introduced nature-inspired algorithms. An overview of case examples optimized by each family of algorithms is included in the paper.},
 bibtype = {misc},
 author = {Goudos, Sotirios K. and Kalialakis, Christos and Mittra, Raj},
 doi = {10.1155/2016/1010459}
}

A review of evolutionary algorithms (EAs) with applications to antenna and propagation problems is presented. EAs have emerged as viable candidates for global optimization problems and have been attracting the attention of the research community interested in solving real-world engineering problems, as evidenced by the fact that very large number of antenna design problems have been addressed in the literature in recent years by using EAs. In this paper, our primary focus is on Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), and Differential Evolution (DE), though we also briefly review other recently introduced nature-inspired algorithms. An overview of case examples optimized by each family of algorithms is included in the paper.

@inproceedings{
 title = {A software tool for aging analysis of the CMOS inverter based on hot carrier degradation modeling},
 type = {inproceedings},
 year = {2016},
 keywords = {Degradation model,MATLAB GUI,hot-carrier effect,n-FinFETs},
 id = {6a050bf2-67f9-364e-982e-f639d210ba87},
 created = {2020-02-29T16:57:43.520Z},
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 last_modified = {2023-02-11T18:54:01.919Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Messaris2016},
 private_publication = {false},
 abstract = {It has been made clear that the presence of hot carriers triggers a series of physical processes that affects the FD-SOI and FinFET device characteristics under normal circuit operation. These effects cumulatively build up over prolonged periods, causing the circuit to age with time, resulting in performance degradations that may eventually lead to circuit failure. In this paper we tackle with the HC effects using a software tool that is able to quantify the HC induced degradation of the devices in a design, and furthermore predict the lifetime of the corresponding circuit. We present the Graphical User Interface (GUI) and we give examples of tool operation.},
 bibtype = {inproceedings},
 author = {Messaris, I. and Goudos, S. K. and Nikolaidis, S. and Dimitriadis, C. A.},
 doi = {10.1109/MOCAST.2016.7495148},
 booktitle = {2016 5th International Conference on Modern Circuits and Systems Technologies, MOCAST 2016}
}

It has been made clear that the presence of hot carriers triggers a series of physical processes that affects the FD-SOI and FinFET device characteristics under normal circuit operation. These effects cumulatively build up over prolonged periods, causing the circuit to age with time, resulting in performance degradations that may eventually lead to circuit failure. In this paper we tackle with the HC effects using a software tool that is able to quantify the HC induced degradation of the devices in a design, and furthermore predict the lifetime of the corresponding circuit. We present the Graphical User Interface (GUI) and we give examples of tool operation.

@inproceedings{
 title = {Optimizing wireless access networks towards power consumption: Influence of the optimization algorithm},
 type = {inproceedings},
 year = {2016},
 keywords = {LTE-A,energy efficiency,network design,optimization algorithm,power consumption,wireless access networks},
 pages = {261-265},
 id = {bcc6b70a-83ca-3a89-9ff9-0b317fced2af},
 created = {2020-02-29T16:57:44.091Z},
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 last_modified = {2023-02-11T18:54:03.494Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Deruyck2016},
 private_publication = {false},
 abstract = {Nowadays, wireless access networks are already amongst the top power consumers in the ICT (Information and Communication Technology) sector. As it expected that these networks will further expand in the future due to the extreme growth in mobile devices and the high bit rate demand of the applications running on these devices, it is important to consider power consumption as a key parameter in the network design phase. In this paper, two optimization algorithms are proposed: a capacity-based heuristic which aims to reduce power consumption by responding to the instantaneous bit rate demand by the user and an evolutionary opposition-based learning algorithm focusing on the joint-optimization of power consumption and geometrical coverage. Applying both algorithms on a realistic suburban case in Ghent, Belgium, show that both algorithms are able to design an LTE-A network consuming only 24% and 29%, respectively, of the power consumed by the reference scenario which is representative for today's networks. The evolutionary algorithm outperforms the capacity-based algorithm by obtaining a 5% lower power consumption, while the capacity-based heuristic has a 2 to 3% higher coverage. Future research in joint-optimization algorithms of energy and network performance is definitely needed.},
 bibtype = {inproceedings},
 author = {Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout and Goudos, Sotirios K.},
 doi = {10.1109/HPCSim.2016.7568344},
 booktitle = {2016 International Conference on High Performance Computing and Simulation, HPCS 2016}
}

Nowadays, wireless access networks are already amongst the top power consumers in the ICT (Information and Communication Technology) sector. As it expected that these networks will further expand in the future due to the extreme growth in mobile devices and the high bit rate demand of the applications running on these devices, it is important to consider power consumption as a key parameter in the network design phase. In this paper, two optimization algorithms are proposed: a capacity-based heuristic which aims to reduce power consumption by responding to the instantaneous bit rate demand by the user and an evolutionary opposition-based learning algorithm focusing on the joint-optimization of power consumption and geometrical coverage. Applying both algorithms on a realistic suburban case in Ghent, Belgium, show that both algorithms are able to design an LTE-A network consuming only 24% and 29%, respectively, of the power consumed by the reference scenario which is representative for today's networks. The evolutionary algorithm outperforms the capacity-based algorithm by obtaining a 5% lower power consumption, while the capacity-based heuristic has a 2 to 3% higher coverage. Future research in joint-optimization algorithms of energy and network performance is definitely needed.

@misc{
 title = {Evolutionary Algorithms Applied to Antennas and Propagation: Emerging Trends and Applications},
 type = {misc},
 year = {2016},
 source = {International Journal of Antennas and Propagation},
 volume = {2016},
 id = {414269e1-c32d-392f-89dc-767ca7cdfd44},
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 author = {Goudos, Sotirios K. and Anagnostou, Dimitris E. and Kalialakis, Christos and Vasant, Pandian and Nikolaou, Symeon},
 doi = {10.1155/2016/5279647}
}

@inproceedings{
 title = {Optimization of power consumption in wireless access networks using Differential Evolution with eigenvector based crossover operator},
 type = {inproceedings},
 year = {2016},
 keywords = {LTE,base station,coverage,differential evolution,network planning,power consumption},
 id = {3c07b195-5c09-3d53-8e8f-c2a8fafe8c69},
 created = {2020-02-29T16:57:44.152Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016b},
 private_publication = {false},
 abstract = {The power consumption of wireless access networks is an important issue. In this paper, the power consumption of LTE base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a design framework based on Differential Evolution with eigenvector-based crossover operator. The results of the proposed method indicate the advantages and applicability of our approach.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout},
 doi = {10.1109/EuCAP.2016.7481359},
 booktitle = {2016 10th European Conference on Antennas and Propagation, EuCAP 2016}
}

The power consumption of wireless access networks is an important issue. In this paper, the power consumption of LTE base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a design framework based on Differential Evolution with eigenvector-based crossover operator. The results of the proposed method indicate the advantages and applicability of our approach.

@inproceedings{
 title = {Application of opposition-based learning concepts in reducing the power consumption in wireless access networks},
 type = {inproceedings},
 year = {2016},
 id = {4e821804-cc63-3d8d-99c9-1b589475f103},
 created = {2020-02-29T16:57:44.194Z},
 file_attached = {false},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016a},
 private_publication = {false},
 abstract = {The reduction of power consumption in wireless access networks is a challenging and important issue. In this paper, we apply Opposition-Based Learning (OBL) concepts for reducing the power consumption of LTE base stations. More specifically, we present a new Modified Biogeography Based Optimization (BBO) algorithm enhanced with OBL techniques. We apply both the original BBO and the new Modified Opposition BBO (MOBBO) to network design cases to the city of Ghent, Belgium, with 75 possible LTE base station locations. We optimize the network towards two objectives: coverage maximization and power consumption minimization. Preliminary results indicate the advantages and applicability of our approach.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Deruyck, Margot and Plets, David and Martens, Luc and Joseph, Wout},
 doi = {10.1109/ICT.2016.7500426},
 booktitle = {2016 23rd International Conference on Telecommunications, ICT 2016}
}

The reduction of power consumption in wireless access networks is a challenging and important issue. In this paper, we apply Opposition-Based Learning (OBL) concepts for reducing the power consumption of LTE base stations. More specifically, we present a new Modified Biogeography Based Optimization (BBO) algorithm enhanced with OBL techniques. We apply both the original BBO and the new Modified Opposition BBO (MOBBO) to network design cases to the city of Ghent, Belgium, with 75 possible LTE base station locations. We optimize the network towards two objectives: coverage maximization and power consumption minimization. Preliminary results indicate the advantages and applicability of our approach.

@article{
 title = {Application of Gbest-guided artificial bee colony algorithm to passive UHF RFID tag design},
 type = {article},
 year = {2016},
 keywords = {Antennas and propagation for wireless systems,RFID and sensors},
 pages = {537-545},
 volume = {8},
 id = {a52a0c9b-467b-31d0-8529-c7b7754a7ca5},
 created = {2020-02-29T16:57:44.305Z},
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 last_modified = {2023-02-11T18:54:02.713Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016},
 private_publication = {false},
 abstract = {In this paper, new planar spiral antennas with meander lines and loads for passive Radiofrequency identification tag application at ultra-high-frequency band are designed and optimized using the global best (gbest)-guided Artificial Bee Colony (GABC) algorithm. The GABC is an improved Artificial Bee Colony algorithm, which includes gbest solution information into the search equation to improve the exploitation. The optimization goals are antenna size minimization, gain maximization, and conjugate matching. The antenna dimensions were optimized and evaluated in conjunction with commercial software FEKO. GABC is compared with other popular algorithms. The optimization results produced show that GABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Theopoulos, Argiris and Vafiadis, Elias E. and Sahalos, John N.},
 doi = {10.1017/S1759078715000902},
 journal = {International Journal of Microwave and Wireless Technologies},
 number = {3}
}

In this paper, new planar spiral antennas with meander lines and loads for passive Radiofrequency identification tag application at ultra-high-frequency band are designed and optimized using the global best (gbest)-guided Artificial Bee Colony (GABC) algorithm. The GABC is an improved Artificial Bee Colony algorithm, which includes gbest solution information into the search equation to improve the exploitation. The optimization goals are antenna size minimization, gain maximization, and conjugate matching. The antenna dimensions were optimized and evaluated in conjunction with commercial software FEKO. GABC is compared with other popular algorithms. The optimization results produced show that GABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems.

@inbook{
 type = {inbook},
 year = {2016},
 pages = {236-265},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-9644-0.ch009},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
 id = {a423beff-3725-3e1b-82d3-1ff82120bb85},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Vasant2016},
 source_type = {incollection},
 private_publication = {false},
 abstract = {In this chapter, the Artificial Bee Colony (ABC) algorithm and its variants are presented and applied to spiral antennas design for RFID tag application at the UHF band. The ABC variants include the Improved ABC (I-ABC), which is an improved version of the original ABC algorithm. The I-ABC introduces the best-so-far solution, inertia weight and acceleration coefficients to modify the search process. Furthermore, another ABC variant is the Gbest ABC (ABC), which includes global best (gbest) solution information into the search equation to improve the exploitation. These algorithms are applied to antenna design where the optimization goals are antenna size minimization, gain maximization, and conjugate matching. The algorithms performance is compared with other popular evolutionary algorithms. The optimization results produced show that the ABC family of algorithms is a powerful tool that can be efficiently applied to antenna design problems.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K and Siakavara, Katherine and Sahalos, John N},
 editor = {Vasant, Pandian and Weber, Gerhard-Wilhelm and Dieu, Vo Ngoc},
 doi = {10.4018/978-1-4666-9644-0.ch009},
 chapter = {Application of Artificial Bee Colony Algorithms to Antenna Design Problems for RFID Applications},
 title = {Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics}
}

In this chapter, the Artificial Bee Colony (ABC) algorithm and its variants are presented and applied to spiral antennas design for RFID tag application at the UHF band. The ABC variants include the Improved ABC (I-ABC), which is an improved version of the original ABC algorithm. The I-ABC introduces the best-so-far solution, inertia weight and acceleration coefficients to modify the search process. Furthermore, another ABC variant is the Gbest ABC (ABC), which includes global best (gbest) solution information into the search equation to improve the exploitation. These algorithms are applied to antenna design where the optimization goals are antenna size minimization, gain maximization, and conjugate matching. The algorithms performance is compared with other popular evolutionary algorithms. The optimization results produced show that the ABC family of algorithms is a powerful tool that can be efficiently applied to antenna design problems.

@article{
 title = {Shaped beam pattern synthesis of antenna arrays using composite differential evolution with eigenvector-based crossover operator},
 type = {article},
 year = {2015},
 volume = {2015},
 id = {bb49542f-88ac-379a-8a68-aa2dc581a754},
 created = {2020-02-29T16:57:41.806Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:54:04.582Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2015c},
 private_publication = {false},
 abstract = {This paper addresses the problem of designing shaped beam patterns with arbitrary arrays subject to constraints. The constraints could include the sidelobe level suppression in specified angular intervals, the mainlobe halfpower beamwidth, and the predefined number of elements. In this paper, we propose a new Differential Evolution algorithm, which combines Composite DE with an eigenvector-based crossover operator (CODE-EIG). This operator utilizes eigenvectors of covariance matrix of individual solutions, which makes the crossover rotationally invariant. We apply this novel design method to shaped beam pattern synthesis for linear and conformal arrays. We compare this algorithm with other popular algorithms and DE variants. The results show CODE-EIG outperforms the other DE algorithms in terms of statistical results and convergence speed.},
 bibtype = {article},
 author = {Goudos, Sotirios K.},
 doi = {10.1155/2015/295012},
 journal = {International Journal of Antennas and Propagation}
}

This paper addresses the problem of designing shaped beam patterns with arbitrary arrays subject to constraints. The constraints could include the sidelobe level suppression in specified angular intervals, the mainlobe halfpower beamwidth, and the predefined number of elements. In this paper, we propose a new Differential Evolution algorithm, which combines Composite DE with an eigenvector-based crossover operator (CODE-EIG). This operator utilizes eigenvectors of covariance matrix of individual solutions, which makes the crossover rotationally invariant. We apply this novel design method to shaped beam pattern synthesis for linear and conformal arrays. We compare this algorithm with other popular algorithms and DE variants. The results show CODE-EIG outperforms the other DE algorithms in terms of statistical results and convergence speed.

@article{
 title = {Design of load-ended spiral antennas for RFID UHF passive tags using improved artificial bee colony algorithm},
 type = {article},
 year = {2015},
 keywords = {Artificial bee colony optimization,Evolutionary algorithms,Optimization methods,RFID tag design,Swarm intelligence},
 pages = {206-214},
 volume = {69},
 id = {2db54d33-d275-3b62-bbd1-4276ec1e380c},
 created = {2020-02-29T16:57:42.630Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.584Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2015b},
 private_publication = {false},
 abstract = {In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using a new artificial bee colony (ABC) algorithm. We apply the improved ABC (I-ABC), which is an improved version of the original ABC algorithm. The I-ABC introduces the best-so-far solution, inertia weight and acceleration coefficients to modify the search process. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using I-ABC in conjunction with commercial EM software. We compare the I-ABC with the original ABC algorithm. The obtained results show that both algorithms are powerful optimizers that can be efficiently applied to tag antenna design problems. I-ABC produces better results than the original ABC algorithm in terms of solution accuracy and success rate. RFID tags with dimensions less than 3 cm, maximum gain that reaches the value of 1.46dBi and read distance more than 10m were among those obtained by the algorithm.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1016/j.aeue.2014.09.008},
 journal = {AEU - International Journal of Electronics and Communications},
 number = {1}
}

In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using a new artificial bee colony (ABC) algorithm. We apply the improved ABC (I-ABC), which is an improved version of the original ABC algorithm. The I-ABC introduces the best-so-far solution, inertia weight and acceleration coefficients to modify the search process. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using I-ABC in conjunction with commercial EM software. We compare the I-ABC with the original ABC algorithm. The obtained results show that both algorithms are powerful optimizers that can be efficiently applied to tag antenna design problems. I-ABC produces better results than the original ABC algorithm in terms of solution accuracy and success rate. RFID tags with dimensions less than 3 cm, maximum gain that reaches the value of 1.46dBi and read distance more than 10m were among those obtained by the algorithm.

@inproceedings{
 title = {A multi-objective approach to indoor wireless heterogeneous networks planning},
 type = {inproceedings},
 year = {2015},
 keywords = {Indoor wireless network planning,Pareto optimization,biogeography-based optimization,exposure minimization,heterogeneous networks,multi-objective optimization},
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 abstract = {We present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-based Optimization (MOBBO). The results of the proposed method indicate the advantages and applicability of the multi-objective approach.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Plets, David and Liu, Ning and Martens, Luc and Joseph, Wout},
 booktitle = {2015 9th European Conference on Antennas and Propagation, EuCAP 2015}
}

We present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-based Optimization (MOBBO). The results of the proposed method indicate the advantages and applicability of the multi-objective approach.

@article{
 title = {A multi-objective approach to indoor wireless heterogeneous networks planning based on biogeography-based optimization},
 type = {article},
 year = {2015},
 keywords = {Biogeography-based optimization,Exposure minimization,Heterogeneous networks,Indoor wireless network planning,Multi-objective optimization,Pareto optimization},
 pages = {564-576},
 volume = {91},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2015},
 private_publication = {false},
 abstract = {In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi access points (APs) and long term evolution (LTE) femtocells. We propose a design framework based on multi-objective biogeography-based optimization (MOBBO). We apply the MOBBO algorithm to network planning design cases in a real office environment. To validate this approach we compare results with other multi-objective algorithms like the nondominated sorting genetic algorithm-II (NSGA-II) and the generalized differential evolution (GDE3) algorithm. The results of the proposed method indicate the advantages and applicability of the multi-objective approach.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Plets, David and Liu, Ning and Martens, Luc and Joseph, Wout},
 doi = {10.1016/j.comnet.2015.08.037},
 journal = {Computer Networks}
}

In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi access points (APs) and long term evolution (LTE) femtocells. We propose a design framework based on multi-objective biogeography-based optimization (MOBBO). We apply the MOBBO algorithm to network planning design cases in a real office environment. To validate this approach we compare results with other multi-objective algorithms like the nondominated sorting genetic algorithm-II (NSGA-II) and the generalized differential evolution (GDE3) algorithm. The results of the proposed method indicate the advantages and applicability of the multi-objective approach.

@article{
 title = {Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity},
 type = {article},
 year = {2015},
 keywords = {Coverage,Exposure,Indoor wireless network planning,Optimization algorithm,Power consumption,WiFi (IEEE 802.11n)},
 pages = {841-857},
 volume = {21},
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 authored = {true},
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 citation_key = {Liu2015},
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 abstract = {Due to the huge popularity of wireless networks, future designs will not only consider the provided capacity, but also the induced exposure, the corresponding power consumption, and the economic cost. As these requirements are contradictory, it is not straightforward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. In this paper, a combination of two algorithms, a genetic algorithm and a quasi-particle swarm optimization, is developed, yielding a novel hybrid algorithm that generates further optimizations of indoor wireless network planning solutions, which is named hybrid indoor genetic optimization algorithm. The algorithm is compared with a heuristic network planner and composite differential evolution algorithm for three scenarios and two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage for a user-defined capacity, minimum power consumption, minimal cost, and minimal human exposure.},
 bibtype = {article},
 author = {Liu, Ning and Plets, David and Goudos, Sotirios K. and Martens, Luc and Joseph, Wout},
 doi = {10.1007/s11276-014-0822-y},
 journal = {Wireless Networks},
 number = {3}
}

Due to the huge popularity of wireless networks, future designs will not only consider the provided capacity, but also the induced exposure, the corresponding power consumption, and the economic cost. As these requirements are contradictory, it is not straightforward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. In this paper, a combination of two algorithms, a genetic algorithm and a quasi-particle swarm optimization, is developed, yielding a novel hybrid algorithm that generates further optimizations of indoor wireless network planning solutions, which is named hybrid indoor genetic optimization algorithm. The algorithm is compared with a heuristic network planner and composite differential evolution algorithm for three scenarios and two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage for a user-defined capacity, minimum power consumption, minimal cost, and minimal human exposure.

@inproceedings{
 title = {SNMP Performance Measurements Using Open Source Software},
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@inproceedings{
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@inproceedings{
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@inproceedings{
 title = {Antenna Selection in MIMO Systems using Evolutionary Algorithms},
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}

@inproceedings{
 title = {Optimization of Cognitive Radio Systems using Nature Inspired Algorithms},
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@inproceedings{
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 booktitle = {MOCAST 2015, Proceedings of the 4th International Conference on Modern Circuits and Systems Technologies, Thessaloniki, Greece}
}

@inproceedings{
 title = {Spectrum Allocation using Evolutionary Algorithms},
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}

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 title = {Encyclopedia of Information Science and Technology, Third Edition}
}

@inproceedings{
 title = {Optimizing meandered spiral antennas for RFID tags using gbest-guided Artificial Bee Colony algorithm},
 type = {inproceedings},
 year = {2014},
 keywords = {Antenna,Measurement,Propagation},
 pages = {2962-2965},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
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 abstract = {In this paper, new planar spiral antennas with meander lines and loads for passive RFID tag application at UHF band are designed and optimized using the gbest-guided Artificial Bee Colony (GABC) algorithm. The GABC is an improved ABC algorithm, which includes global best (gbest) solution information into the search equation to improve the exploitation. The optimization goals are antenna size minimization, gain maximization, and conjugate matching. The antenna dimensions were optimized and evaluated in conjunction with FEKO. The optimization results produced show that GABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/EuCAP.2014.6902449},
 booktitle = {8th European Conference on Antennas and Propagation, EuCAP 2014}
}

In this paper, new planar spiral antennas with meander lines and loads for passive RFID tag application at UHF band are designed and optimized using the gbest-guided Artificial Bee Colony (GABC) algorithm. The GABC is an improved ABC algorithm, which includes global best (gbest) solution information into the search equation to improve the exploitation. The optimization goals are antenna size minimization, gain maximization, and conjugate matching. The antenna dimensions were optimized and evaluated in conjunction with FEKO. The optimization results produced show that GABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems.

@article{
 title = {Novel spiral antenna design using artificial bee colony optimization for UHF RFID Applications},
 type = {article},
 year = {2014},
 keywords = {Artificial bee colony optimization,conjugate matching,evolutionary algorithms,gain maximization,optimization methods,radio frequency identification (RFID) tag design,swarm intelligence},
 pages = {528-531},
 volume = {13},
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 hidden = {false},
 citation_key = {Goudos2014},
 private_publication = {false},
 abstract = {In this letter, a new planar spiral antenna for passive radio frequency identification (RFID) tag application at UHF band is designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization, conjugate matching, and in consequence the maximization of the read range. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial electromagnetic (EM) software. The comparison of the results obtained by ABC to respective ones of other popular evolutionary algorithms show that ABC can be efficiently applied to tag antenna design problems. To validate the theoretical results, designed RFID tags were fabricated, and their reading efficiency was evaluated experimentally. The results of simulation and those received via measurements prove that the proposed method for the design of passive RFID tag antennas is efficient, as antennas with dimensions less than 3 cm, gain that reaches the value of 1.6 dBi, and read range about 6 m were obtained. © 2002-2011 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/LAWP.2014.2311653},
 journal = {IEEE Antennas and Wireless Propagation Letters}
}

In this letter, a new planar spiral antenna for passive radio frequency identification (RFID) tag application at UHF band is designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization, conjugate matching, and in consequence the maximization of the read range. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial electromagnetic (EM) software. The comparison of the results obtained by ABC to respective ones of other popular evolutionary algorithms show that ABC can be efficiently applied to tag antenna design problems. To validate the theoretical results, designed RFID tags were fabricated, and their reading efficiency was evaluated experimentally. The results of simulation and those received via measurements prove that the proposed method for the design of passive RFID tag antennas is efficient, as antennas with dimensions less than 3 cm, gain that reaches the value of 1.6 dBi, and read range about 6 m were obtained. © 2002-2011 IEEE.

@inproceedings{
 title = {An analytical model for the CMOS inverter},
 type = {inproceedings},
 year = {2014},
 keywords = {CCS technology,Inverter modeling,output current model,simulation,timing model,transistor current model},
 id = {d6356e63-ad24-3bdb-8143-363d36ef6f36},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Chaourani2014},
 private_publication = {false},
 abstract = {A new analytical model for the CMOS inverter is introduced. This model results by solving analytically the differential equation which describes the inverter operation. It uses new simplified transistor current expressions which are developed taking into account the nanoscale effects and also considering temperature as a parameter. Expressions for the output voltage are derived, which are then used for capturing the output and supply currents, making the model compatible with CCS technology requirements. The proposed model is parametric according to the input signal slew, output load, transistor widths, supply voltage, temperature and process parameters. It presents an average error less than 3% for the typical case.},
 bibtype = {inproceedings},
 author = {Chaourani, P. and Messaris, I. and Fasarakis, N. and Ntogramatzi, M. and Goudos, S. and Nikolaidis, S.},
 doi = {10.1109/PATMOS.2014.6951894},
 booktitle = {2014 24th International Workshop on Power and Timing Modeling, Optimization and Simulation, PATMOS 2014}
}

A new analytical model for the CMOS inverter is introduced. This model results by solving analytically the differential equation which describes the inverter operation. It uses new simplified transistor current expressions which are developed taking into account the nanoscale effects and also considering temperature as a parameter. Expressions for the output voltage are derived, which are then used for capturing the output and supply currents, making the model compatible with CCS technology requirements. The proposed model is parametric according to the input signal slew, output load, transistor widths, supply voltage, temperature and process parameters. It presents an average error less than 3% for the typical case.

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@inproceedings{
 title = {Modified spiral RFID tag antenna optimal design using Artificial Bee Colony optimization},
 type = {inproceedings},
 year = {2013},
 keywords = {RFID tag design,artificial bee colony optimization,conjugate matching,evolutionary algorithms,gain maximaztion,optimization methods,swarm intellingence},
 pages = {1255-1258},
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 abstract = {In this paper, new modified planar spiral antennas with meander lines for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with FEKO. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. © 2013 European Microwave Association.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 booktitle = {European Microwave Week 2013, EuMW 2013 - Conference Proceedings; EuMC 2013: 43rd European Microwave Conference}
}

In this paper, new modified planar spiral antennas with meander lines for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with FEKO. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. © 2013 European Microwave Association.

@inproceedings{
 title = {Synthesis of miniaturized load-ended spiral antennas for UHF passive tags},
 type = {inproceedings},
 year = {2013},
 pages = {927-930},
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 abstract = {In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial EM software. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. RFID tags with dimensions less than 4cm, maximum gain that reaches the value of 1.83 dBi and read distance more than 10m were among those obtained by the algorithm. © 2013 IEEE.},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Siakavara, K. and Sahalos, J. N.},
 doi = {10.1109/APWC.2013.6624919},
 booktitle = {Proceedings of the 2013 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, IEEE APWC 2013}
}

In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial EM software. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. RFID tags with dimensions less than 4cm, maximum gain that reaches the value of 1.83 dBi and read distance more than 10m were among those obtained by the algorithm. © 2013 IEEE.

@inproceedings{
 title = {Novel spiral antennas design using swarm intelligence for passive UHF RFID tags},
 type = {inproceedings},
 year = {2013},
 keywords = {RFID tag design,artificial bee colony optimization,conjugate matching,evolutionary algorithms,gain maximaztion,optimization methods,swarm intellingence},
 pages = {3223-3227},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2013a},
 private_publication = {false},
 abstract = {In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial EM software. Furthermore, a theoretical analysis of the spiral antennas was performed. The input impedance of the printed spiral, was calculated approximately via the Transmission Line Model and the electromotive force induced along the spirals. The theoretical results seem to be in good agreement with the EM solver results. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. RFID tags with dimensions less than 4cm, gain that reaches the value of 2 dBi and read distance about 11.7m were among those obtained by the algorithm. © 2013 EurAAP.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 booktitle = {2013 7th European Conference on Antennas and Propagation, EuCAP 2013}
}

In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial EM software. Furthermore, a theoretical analysis of the spiral antennas was performed. The input impedance of the printed spiral, was calculated approximately via the Transmission Line Model and the electromotive force induced along the spirals. The theoretical results seem to be in good agreement with the EM solver results. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. RFID tags with dimensions less than 4cm, gain that reaches the value of 2 dBi and read distance about 11.7m were among those obtained by the algorithm. © 2013 EurAAP.

@inproceedings{
 title = {Modeling by optimal Artificial Neural Networks the prediction of propagation path loss in urban environments},
 type = {inproceedings},
 year = {2013},
 pages = {599-602},
 id = {e296bf6e-25c8-328a-8a23-dea234a952a8},
 created = {2020-02-29T16:57:44.349Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.937Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2013b},
 private_publication = {false},
 abstract = {In this paper we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on Artificial Neural Networks (ANN). The goal of this work is to synthesize and model ANNs which would require entering at the input nodes a detailed and the same time small amount of information about the propagation environment. We apply the Differential Evolution (DE) algorithm, in conjunction with the Levenberg-Marquardt backpropagation algorithm in order to train different ANNs. The combined DE-LM method achieves better convergence of neural network weight optimization. We present two different ANN design cases with different number of input nodes. The general performance of the both ANNs shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the Ray-Tracing model and exhibit satisfactory accuracy. © 2013 IEEE.},
 bibtype = {inproceedings},
 author = {Sotiroudis, S. P. and Goudos, S. K. and Gotsis, K. A. and Siakavara, K. and Sahalos, J. N.},
 doi = {10.1109/APWC.2013.6624896},
 booktitle = {Proceedings of the 2013 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, IEEE APWC 2013}
}

In this paper we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on Artificial Neural Networks (ANN). The goal of this work is to synthesize and model ANNs which would require entering at the input nodes a detailed and the same time small amount of information about the propagation environment. We apply the Differential Evolution (DE) algorithm, in conjunction with the Levenberg-Marquardt backpropagation algorithm in order to train different ANNs. The combined DE-LM method achieves better convergence of neural network weight optimization. We present two different ANN design cases with different number of input nodes. The general performance of the both ANNs shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the Ray-Tracing model and exhibit satisfactory accuracy. © 2013 IEEE.

@inproceedings{
 title = {Optimal Artificial Neural Network design for propagation path-loss prediction using adaptive evolutionary algorithms},
 type = {inproceedings},
 year = {2013},
 keywords = {Differential Evolution,Neural Network,Self-adaptive Differential Evolution,evolutionary algorithms,mobile communications,optimization methods,propagation path-loss},
 id = {86994c56-5c35-31a9-a615-806779420894},
 created = {2020-02-29T16:57:44.368Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:48.894Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2013a},
 private_publication = {false},
 abstract = {In this paper we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on Artificial Neural Networks (ANN). The size of a neural network must be defined before it can be trained for any application. We apply different adaptive Differential Evolution (DE) algorithms, in order to design an optimal ANN for path loss propagation prediction. We present two different ANN design cases with two and three hidden layers respectively. The general performance of the both ANN shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the Ray-Tracing model and exhibit satisfactory accuracy. © 2013 EurAAP.},
 bibtype = {inproceedings},
 author = {Sotiroudis, S.P. and Goudos, S.K. and Gotsis, K.A. and Siakavara, K. and Sahalos, J.N.},
 booktitle = {2013 7th European Conference on Antennas and Propagation, EuCAP 2013}
}

In this paper we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on Artificial Neural Networks (ANN). The size of a neural network must be defined before it can be trained for any application. We apply different adaptive Differential Evolution (DE) algorithms, in order to design an optimal ANN for path loss propagation prediction. We present two different ANN design cases with two and three hidden layers respectively. The general performance of the both ANN shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the Ray-Tracing model and exhibit satisfactory accuracy. © 2013 EurAAP.

@article{
 title = {A multi-objective approach to subarrayed linear antenna arrays design based on memetic differential evolution},
 type = {article},
 year = {2013},
 keywords = {Differential evolution,Pareto optimization,generalized differential evolution,genetic algorithms,linear array synthesis,memetic algorithms,multi-objective optimization,phase control,subarrayed arrays},
 pages = {3042-3052},
 volume = {61},
 id = {9c2db870-6804-3838-8b39-05054dd03cd3},
 created = {2020-02-29T16:57:44.423Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.485Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2013},
 private_publication = {false},
 abstract = {In this paper we present a multi-objective optimization approach to subarrayed linear antenna arrays design. We define this problem as a bi-objective one. We consider two objective functions for directivity maximization and sidelobe level minimization. Memetic algorithms (MAs) are hybrid algorithms that combine the benefits of a global search Evolutionary Algorithm (EA) with a local search method. In this paper, we introduce a new memetic multi-objective evolutionary algorithm namely the memetic generalized differential evolution (MGDE3). This algorithm is a memetic extension of the popular generalized differential evolution (GDE3) algorithm. Another popular MOEA is the nondominated sorting genetic algorithm-II (NSGA-II). MGDE3, GDE3 and NSGA-II are applied to the synthesis of uniform and nonuniform subarrayed linear arrays, providing an extensive set of solutions for each design case. Depending on the desired array characteristics, the designer can select the most suitable solution. The results of the proposed method are compared with those reported in the literature, indicating the advantages and applicability of the multi-objective approach. © 2013 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Gotsis, Konstantinos A. and Siakavara, Katherine and Vafiadis, Elias E. and Sahalos, John N.},
 doi = {10.1109/TAP.2013.2254437},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {6}
}

In this paper we present a multi-objective optimization approach to subarrayed linear antenna arrays design. We define this problem as a bi-objective one. We consider two objective functions for directivity maximization and sidelobe level minimization. Memetic algorithms (MAs) are hybrid algorithms that combine the benefits of a global search Evolutionary Algorithm (EA) with a local search method. In this paper, we introduce a new memetic multi-objective evolutionary algorithm namely the memetic generalized differential evolution (MGDE3). This algorithm is a memetic extension of the popular generalized differential evolution (GDE3) algorithm. Another popular MOEA is the nondominated sorting genetic algorithm-II (NSGA-II). MGDE3, GDE3 and NSGA-II are applied to the synthesis of uniform and nonuniform subarrayed linear arrays, providing an extensive set of solutions for each design case. Depending on the desired array characteristics, the designer can select the most suitable solution. The results of the proposed method are compared with those reported in the literature, indicating the advantages and applicability of the multi-objective approach. © 2013 IEEE.

@article{
 title = {Application of a composite differential evolution algorithm in optimal neural network design for propagation path-loss prediction in mobile communication systems},
 type = {article},
 year = {2013},
 keywords = {Differential evolution (DE),evolutionary algorithms (EAs),mobile communications,neural network,optimization methods,propagation path loss,self-adaptive differential evolution},
 pages = {364-367},
 volume = {12},
 id = {ffa84700-6eea-3597-9970-445c14670b1a},
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 last_modified = {2023-02-11T18:54:02.119Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sotiroudis2013},
 private_publication = {false},
 abstract = {In this letter, we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on artificial neural networks (ANNs). The correct selection of a neural network size can increase its response speed and therefore increase the overall system performance. We apply a recently proposed Differential Evolution (DE) algorithm, namely the Composite DE (CoDE) in order to design an optimal ANN for path-loss propagation prediction. CoDE uses three different trial-vector generation strategies with three preset control parameter settings. We compare CoDE with other popular DE strategies. We present two different ANN design cases with two and three hidden layers, respectively. The general performance of both the ANNs shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the ray-tracing model and exhibit satisfactory accuracy. © 2002-2011 IEEE.},
 bibtype = {article},
 author = {Sotiroudis, Sotirios P. and Goudos, Sotirios K. and Gotsis, Konstantinos A. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/LAWP.2013.2251994},
 journal = {IEEE Antennas and Wireless Propagation Letters}
}

In this letter, we present an alternative procedure for the prediction of propagation path loss in urban environments, which is based on artificial neural networks (ANNs). The correct selection of a neural network size can increase its response speed and therefore increase the overall system performance. We apply a recently proposed Differential Evolution (DE) algorithm, namely the Composite DE (CoDE) in order to design an optimal ANN for path-loss propagation prediction. CoDE uses three different trial-vector generation strategies with three preset control parameter settings. We compare CoDE with other popular DE strategies. We present two different ANN design cases with two and three hidden layers, respectively. The general performance of both the ANNs shows their effectiveness to yield results with satisfactory accuracy in short time. The received results are compared to the respective ones yielded by the ray-tracing model and exhibit satisfactory accuracy. © 2002-2011 IEEE.

@inproceedings{
 title = {On the worst-case whole-body SAR assessment due to far-field exposure},
 type = {inproceedings},
 year = {2013},
 id = {1fdbc171-b363-3a6a-82b0-4aa7ee652b54},
 created = {2023-02-11T21:11:00.684Z},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {boursianis2013ontheworstcase},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Boursianis, Achilles and Markakis, Ioannis and Goudos, Sotirios K and Samaras, Theodoros},
 booktitle = {Abstract Collection of BioEM 2013, PB-72}
}

@inbook{
 type = {inbook},
 year = {2012},
 pages = {75-101},
 id = {91bb1039-1187-340d-b168-bd920b09ebf6},
 created = {2020-02-29T16:57:41.859Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.496Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2012b},
 private_publication = {false},
 abstract = {Antenna and microwave design problems are, in general, multi-objective. Multi-objective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. Particle Swarm Optimization (PSO) and Differential Evolution (DE) have received increased interest from the electromagnetics community. The fact that both algorithms can efficiently handle arbitrary optimization problems has made them popular for solving antenna and microwave design problems. This chapter presents three different state-of-the-art MOEAs based on PSO and DE, namely: the Multi-objective Particle Swarm Optimization (MOPSO), the Multi-objective Particle Swarm Optimization with fitness sharing (MOPSO-fs), and the Generalized Differential Evolution (GDE3). Their applications to different design cases from antenna and microwave problems are reported. These include microwave absorber, microwave filters and Yagi-uda antenna design. The algorithms are compared and evaluated against other evolutionary multi-objective algorithms like Nondominated Sorting Genetic Algorithm-II (NSGAII). The results show the advantages of using each algorithm. © 2012, IGI Global.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K.},
 doi = {10.4018/978-1-4666-1830-5.ch006},
 chapter = {Application of multi-objective evolutionary algorithms to antenna and microwave design problems},
 title = {Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine}
}

Antenna and microwave design problems are, in general, multi-objective. Multi-objective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. Particle Swarm Optimization (PSO) and Differential Evolution (DE) have received increased interest from the electromagnetics community. The fact that both algorithms can efficiently handle arbitrary optimization problems has made them popular for solving antenna and microwave design problems. This chapter presents three different state-of-the-art MOEAs based on PSO and DE, namely: the Multi-objective Particle Swarm Optimization (MOPSO), the Multi-objective Particle Swarm Optimization with fitness sharing (MOPSO-fs), and the Generalized Differential Evolution (GDE3). Their applications to different design cases from antenna and microwave problems are reported. These include microwave absorber, microwave filters and Yagi-uda antenna design. The algorithms are compared and evaluated against other evolutionary multi-objective algorithms like Nondominated Sorting Genetic Algorithm-II (NSGAII). The results show the advantages of using each algorithm. © 2012, IGI Global.

@inbook{
 type = {inbook},
 year = {2012},
 pages = {100-126},
 id = {e610d14c-80a9-346a-bf2d-76f472cd05ca},
 created = {2020-02-29T16:57:42.677Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.323Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2012a},
 private_publication = {false},
 abstract = {Particle Swarm Optimization (PSO) is an evolutionary optimization algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this chapter, the authors apply different PSO variants to common antenna and microwave design problems. The Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms are applied to real-valued optimization problems. Correspondingly, discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with velocity mutation (BPSO-vm) are used to solve discrete-valued optimization problems. In case of a multi-objective optimization problem, the authors apply two multi-objective PSO variants. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. The design examples presented here include microwave absorber design, linear array synthesis, patch antenna design, and dual-band base station antenna optimization. The conclusion and a discussion on future trends complete the chapter. © 2013, IGI Global.},
 bibtype = {inbook},
 author = {Goudos, Sotirios K. and Zaharis, Zaharias D. and Baltzis, Konstantinos B.},
 doi = {10.4018/978-1-4666-2666-9.ch006},
 chapter = {Particle swarm optimization algorithms applied to antenna and microwave design problems},
 title = {Swarm Intelligence for Electric and Electronic Engineering}
}

Particle Swarm Optimization (PSO) is an evolutionary optimization algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this chapter, the authors apply different PSO variants to common antenna and microwave design problems. The Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms are applied to real-valued optimization problems. Correspondingly, discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with velocity mutation (BPSO-vm) are used to solve discrete-valued optimization problems. In case of a multi-objective optimization problem, the authors apply two multi-objective PSO variants. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. The design examples presented here include microwave absorber design, linear array synthesis, patch antenna design, and dual-band base station antenna optimization. The conclusion and a discussion on future trends complete the chapter. © 2013, IGI Global.

@inproceedings{
 title = {Reducing the number of elements in linear arrays using biogeography-based optimization},
 type = {inproceedings},
 year = {2012},
 keywords = {Biogeograpy-based optimization,array synthesis,linear array design,nonuniform array,sparse array},
 pages = {1615-1618},
 id = {119467af-f9bc-3f2d-92b6-0dcfbbaa98b8},
 created = {2020-02-29T16:57:45.024Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.656Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2012},
 private_publication = {false},
 abstract = {This paper addresses the problem of designing nonuniform linear arrays with reduced number of elements. The synthesis of such arrays has several practical applications in cases where cost and weight reduction is important. The proposed design method is based on Biogeography-based Optimization (BBO). We apply the BBO algorithm in order to find the optimum element positions and amplitudes that produce a desired pattern with a reduced number of elements. Additional design constraints include the minimum and maximum distance between two adjacent elements. Design cases found in the literature are compared with those found by BBO. The results show that BBO is highly efficient in producing the desired radiation pattern using a minimum number of elements. © 2012 IEEE.},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Baltzis, K. B. and Siakavara, K. and Samaras, T. and Vafiadis, E. and Sahalos, J. N.},
 doi = {10.1109/EuCAP.2012.6206314},
 booktitle = {Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012}
}

This paper addresses the problem of designing nonuniform linear arrays with reduced number of elements. The synthesis of such arrays has several practical applications in cases where cost and weight reduction is important. The proposed design method is based on Biogeography-based Optimization (BBO). We apply the BBO algorithm in order to find the optimum element positions and amplitudes that produce a desired pattern with a reduced number of elements. Additional design constraints include the minimum and maximum distance between two adjacent elements. Design cases found in the literature are compared with those found by BBO. The results show that BBO is highly efficient in producing the desired radiation pattern using a minimum number of elements. © 2012 IEEE.

@article{
 title = {Application of boolean PSO with adaptive velocity mutation to the design of optimal linear antenna arrays excited by uniformamplitude current distribution},
 type = {article},
 year = {2011},
 pages = {1422-1436},
 volume = {25},
 id = {d1536169-d77e-3db6-9d68-2d9f787647a5},
 created = {2020-02-29T16:57:42.848Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.442Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Zaharis2011},
 private_publication = {false},
 abstract = {This paper presents a new optimization technique for the design of linear antenna arrays. The proposed technique is based on a novel variant of PSO called Boolean PSO with Adaptive Velocity Mutation. The antenna arrays are optimized under requirements for maximizing the power gain at a desired direction and minimizing the side lobe level of the radiation pattern. The impedance-matching condition of all the array elements is also required by the algorithm. The optimization technique has been developed considering that the array elements are excited by uniform-amplitude current distribution. The radiation characteristics of the antenna array are extracted by using the method of moments. The technique has been applied in several broadside and non-broadside cases of collinear wire-dipole antenna arrays and seems to be capable of improving the radiation characteristics of the antenna arrays in practice. © 2011 VSP.},
 bibtype = {article},
 author = {Zaharis, Z. D. and Goudos, S. K. and Yioultsis, T. V.},
 doi = {10.1163/156939311796351632},
 journal = {Journal of Electromagnetic Waves and Applications},
 number = {10}
}

This paper presents a new optimization technique for the design of linear antenna arrays. The proposed technique is based on a novel variant of PSO called Boolean PSO with Adaptive Velocity Mutation. The antenna arrays are optimized under requirements for maximizing the power gain at a desired direction and minimizing the side lobe level of the radiation pattern. The impedance-matching condition of all the array elements is also required by the algorithm. The optimization technique has been developed considering that the array elements are excited by uniform-amplitude current distribution. The radiation characteristics of the antenna array are extracted by using the method of moments. The technique has been applied in several broadside and non-broadside cases of collinear wire-dipole antenna arrays and seems to be capable of improving the radiation characteristics of the antenna arrays in practice. © 2011 VSP.

@article{
 title = {Design of optimum gain pyramidal horn using self-adaptive differential evolution algorithms},
 type = {article},
 year = {2011},
 keywords = {differential evolution,evolutionary algorithms,optimum gain antenna,pyramidal horn design},
 pages = {59-66},
 volume = {21},
 id = {2aec0192-0f58-3554-be59-808d66f25691},
 created = {2020-02-29T16:57:43.540Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.741Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Pappas2011},
 private_publication = {false},
 abstract = {In this work, we apply classical and new self-adaptive differential evolution (DE) algorithms to the design of optimum gain pyramidal horns. The application of DE algorithms to pyramidal horn design allows the accurate calculation of their physical dimensions in a short amount of time. Moreover, self-adaptive DE does not require the prespecified choice of control parameters reducing significantly the users' effort. Representative examples demonstrate the applicability of our proposal. Our study shows that self-adaptive DE algorithms outperform or produce similar results with other methods in the literature in terms of solution accuracy and convergence speed. © 2010 Wiley Periodicals, Inc.},
 bibtype = {article},
 author = {Pappas, Dimitrios and Goudos, Sotirios K. and Baltzis, Konstantinos B. and Siakavara, Katherine},
 doi = {10.1002/mmce.20487},
 journal = {International Journal of RF and Microwave Computer-Aided Engineering},
 number = {1}
}

In this work, we apply classical and new self-adaptive differential evolution (DE) algorithms to the design of optimum gain pyramidal horns. The application of DE algorithms to pyramidal horn design allows the accurate calculation of their physical dimensions in a short amount of time. Moreover, self-adaptive DE does not require the prespecified choice of control parameters reducing significantly the users' effort. Representative examples demonstrate the applicability of our proposal. Our study shows that self-adaptive DE algorithms outperform or produce similar results with other methods in the literature in terms of solution accuracy and convergence speed. © 2010 Wiley Periodicals, Inc.

@article{
 title = {Sparse linear array synthesis with multiple constraints using differential evolution with strategy adaptation},
 type = {article},
 year = {2011},
 keywords = {Differential evolution (DE),genetic algorithms (GAs),linear array design,sidelobe suppression,sparse array synthesis,unequally spaced array},
 pages = {670-673},
 volume = {10},
 id = {d505c09d-29a1-35dc-8270-469c0d394f20},
 created = {2020-02-29T16:57:44.488Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.537Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2011c},
 private_publication = {false},
 abstract = {This letter addresses the problem of designing sparse linear arrays with multiple constraints. The constraints could include the minimum and maximum distance between two adjacent elements, the total array length, the sidelobe level suppression in specified angular intervals, the main-lobe beamwidth, and the predefined number of elements. Our design method is based on differential evolution (DE) with strategy adaptation. We apply a DE algorithm (SaDE) that uses previous experience in both trial vector generation strategies and control parameter tuning. Design cases found in the literature are compared to those found by SaDE and other DE algorithms. The results show that fewer objective-function evaluations are required than those reported in the literature to obtain better designs. SaDE also outperforms the other DE algorithms in terms of statistical results. © 2011 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Samaras, Theodoros and Vafiadis, Elias E. and Sahalos, John N.},
 doi = {10.1109/LAWP.2011.2161256},
 journal = {IEEE Antennas and Wireless Propagation Letters}
}

This letter addresses the problem of designing sparse linear arrays with multiple constraints. The constraints could include the minimum and maximum distance between two adjacent elements, the total array length, the sidelobe level suppression in specified angular intervals, the main-lobe beamwidth, and the predefined number of elements. Our design method is based on differential evolution (DE) with strategy adaptation. We apply a DE algorithm (SaDE) that uses previous experience in both trial vector generation strategies and control parameter tuning. Design cases found in the literature are compared to those found by SaDE and other DE algorithms. The results show that fewer objective-function evaluations are required than those reported in the literature to obtain better designs. SaDE also outperforms the other DE algorithms in terms of statistical results. © 2011 IEEE.

@article{
 title = {Self-adaptive differential evolution applied to real-valued antenna and microwave design problems},
 type = {article},
 year = {2011},
 keywords = {Differential evolution (DE),evolutionary algorithms (EAs),linear array synthesis,microwave filter design,optimization methods,particle swarm optimization (PSO),patch antenna design},
 pages = {1286-1298},
 volume = {59},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2011b},
 private_publication = {false},
 abstract = {Particle swarm optimization (PSO) is an evolutionary algorithm based on the bird fly. Differential evolution (DE) is a vector population based stochastic optimization method. The fact that both algorithms can handle efficiently arbitrary optimization problems has made them popular for solving problems in electromagnetics. In this paper, we apply a design technique based on a self-adaptive DE (SADE) algorithm to real-valued antenna and microwave design problems. These include linear-array synthesis, patch-antenna design and microstrip filter design. The number of unknowns for the design problems varies from 6 to 60. We compare the self-adaptive DE strategy with popular PSO and DE variants. We evaluate the algorithms' performance regarding statistical results and convergence speed. The results obtained for different problems show that the DE algorithms outperform the PSO variants in terms of finding best optima. Thus, our results show the advantages of the SADE strategy and the DE in general. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics. © 2006 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Samaras, Theodoros and Vafiadis, Elias E. and Sahalos, John N.},
 doi = {10.1109/TAP.2011.2109678},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {4}
}

Particle swarm optimization (PSO) is an evolutionary algorithm based on the bird fly. Differential evolution (DE) is a vector population based stochastic optimization method. The fact that both algorithms can handle efficiently arbitrary optimization problems has made them popular for solving problems in electromagnetics. In this paper, we apply a design technique based on a self-adaptive DE (SADE) algorithm to real-valued antenna and microwave design problems. These include linear-array synthesis, patch-antenna design and microstrip filter design. The number of unknowns for the design problems varies from 6 to 60. We compare the self-adaptive DE strategy with popular PSO and DE variants. We evaluate the algorithms' performance regarding statistical results and convergence speed. The results obtained for different problems show that the DE algorithms outperform the PSO variants in terms of finding best optima. Thus, our results show the advantages of the SADE strategy and the DE in general. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics. © 2006 IEEE.

@inproceedings{
 title = {A comparative study of common and self-adaptive Differential Evolution strategies on numerical benchmark problems},
 type = {inproceedings},
 year = {2011},
 keywords = {Adaptive parameter control,Benchmark functions,Differential Evolution,Global optimization},
 pages = {83-88},
 volume = {3},
 id = {56432921-baf2-3a89-95df-1c1a6e3f5869},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2011a},
 private_publication = {false},
 abstract = {Differential Evolution (DE) is a population-based stochastic global optimization technique that requires the adjustment of a very few parameters in order to produce results. However, the control parameters involved in DE are highly dependent on the optimization problem; in practice, their fine-tuning is not always an easy task. The self-adaptive differential evolution (SADE) variants are those that do not require the pre-specified choice of control parameters. On the contrary, control parameters are self-adapted by using the previous learning experience. In this paper, we discuss and evaluate popular common and self-adaptive differential evolution (DE) algorithms. In particular, we present an empirical comparison between two self-adaptive DE variants and common DE methods. In order to assure a fair comparison, we test the methods by using a number of well-known unimodal and multimodal, separable and non-separable, benchmark optimization problems for different dimensions and population size. The results show that SADE variants outperform, or at least produce similar results, to common differential evolution algorithms in terms of solution accuracy and convergence speed. The advantage of using the self-adaptive methods is that the user does not need to adjust control parameters. Therefore, the total computational effort is significantly reduced. © 2010 Published by Elsevier Ltd.},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Baltzis, K. B. and Antoniadis, K. and Zaharis, Z. D. and Hilas, C. S.},
 doi = {10.1016/j.procs.2010.12.015},
 booktitle = {Procedia Computer Science}
}

Differential Evolution (DE) is a population-based stochastic global optimization technique that requires the adjustment of a very few parameters in order to produce results. However, the control parameters involved in DE are highly dependent on the optimization problem; in practice, their fine-tuning is not always an easy task. The self-adaptive differential evolution (SADE) variants are those that do not require the pre-specified choice of control parameters. On the contrary, control parameters are self-adapted by using the previous learning experience. In this paper, we discuss and evaluate popular common and self-adaptive differential evolution (DE) algorithms. In particular, we present an empirical comparison between two self-adaptive DE variants and common DE methods. In order to assure a fair comparison, we test the methods by using a number of well-known unimodal and multimodal, separable and non-separable, benchmark optimization problems for different dimensions and population size. The results show that SADE variants outperform, or at least produce similar results, to common differential evolution algorithms in terms of solution accuracy and convergence speed. The advantage of using the self-adaptive methods is that the user does not need to adjust control parameters. Therefore, the total computational effort is significantly reduced. © 2010 Published by Elsevier Ltd.

@inproceedings{
 title = {Unequally spaced arrays synthesis using Self-adaptive Differential Evolution},
 type = {inproceedings},
 year = {2011},
 pages = {983-986},
 id = {609db08c-ce41-3c0c-822e-058bdece2b5d},
 created = {2020-02-29T16:57:45.077Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2011},
 private_publication = {false},
 abstract = {In this paper we present uniformly excited unequally spaced linear-array synthesis with sidelobe suppression. We apply different evolutionary algorithms like Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) variants to position-only and position-phase synthesis. The DE algorithms include the common DE/rand/1/bin and the Self-adaptive strategies. The results on different problems show that the DE algorithms outperform the other algorithms in terms of finding best optima. The Self-adaptive DE produces similar or better results than the classical DE algorithm. The obtained results indicate the advantages of this approach. © 2011 EurAAP.},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Nanos, A. A. and Samaras, T. and Siakavara, K. and Vafiadis, E. and Sahalos, J. N.},
 booktitle = {Proceedings of the 5th European Conference on Antennas and Propagation, EUCAP 2011}
}

In this paper we present uniformly excited unequally spaced linear-array synthesis with sidelobe suppression. We apply different evolutionary algorithms like Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) variants to position-only and position-phase synthesis. The DE algorithms include the common DE/rand/1/bin and the Self-adaptive strategies. The results on different problems show that the DE algorithms outperform the other algorithms in terms of finding best optima. The Self-adaptive DE produces similar or better results than the classical DE algorithm. The obtained results indicate the advantages of this approach. © 2011 EurAAP.

@article{
 title = {Distance learning technology and service support in Greece: the case study of the aristotle university over the last decade},
 type = {article},
 year = {2011},
 pages = {25-39},
 volume = {16},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096079124&doi=10.1007%2Fs10639-009-9110-3&partnerID=40&md5=0bdcd906615129a3c1fdedc1d2d881ac},
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 author = {Agorogianni, A Z and Zaharis, Z D and Anastasiadou, S D and Goudos, S K},
 doi = {10.1007/s10639-009-9110-3},
 journal = {Education and Information Technologies},
 number = {1}
}

@inproceedings{
 title = {A Multi-objective Approach to subarrayed linear antenna arrays design},
 type = {inproceedings},
 year = {2011},
 id = {39d3fb97-ca49-3b29-a4e5-8c8b6fcb437d},
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 bibtype = {inproceedings},
 author = {Goudos, S K and Gotsis, K A and Siakavara, K and Vafiadis, E E and Sahalos, J N},
 booktitle = {Proceedings of the 2011 URSI General Assembly and Scientific Symposium, Istanbul, Turkey on August 13-20}
}

@inbook{
 type = {inbook},
 year = {2011},
 pages = {1-47},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60960-593-3.ch001},
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 abstract = {Interoperability is one of the most challenging problems in modern cross-organizational information systems, which rely on heterogeneous information and process models. Interoperability becomes very important for e-Government information systems that support cross-organizational communication especially in a cross-border setting. The main goal in this context is to seamlessly provide integrated services to the user (citizen). In this paper we focus on Pan European e-Services and issues related with their integration. Our analysis uses basic concepts of the generic public service model of the Governance Enterprise Architecture (GEA) and of the Web Service Modeling Ontology (WSMO), to express the semantic description of the e-services. Based on the above, we present a mediation infrastructure capable of resolving semantic interoperability conflicts at a pan-European level. We provide several examples to illustrate both the need to solve such semantic conflicts and the actual solutions we propose.},
 bibtype = {inbook},
 author = {Mocan, Adrian and Facca, Federico M and Loutas, Nikolaos and Peristeras, Vassilios and Goudos, Sotirios K and Tarabanis, Konstantinos},
 editor = {Sheth, Amit},
 doi = {10.4018/978-1-60960-593-3.ch001},
 chapter = {Solving Semantic Interoperability Conflicts in Cross-Border E-Government Services},
 title = {Semantic Services, Interoperability and Web Applications: Emerging Concepts}
}

Interoperability is one of the most challenging problems in modern cross-organizational information systems, which rely on heterogeneous information and process models. Interoperability becomes very important for e-Government information systems that support cross-organizational communication especially in a cross-border setting. The main goal in this context is to seamlessly provide integrated services to the user (citizen). In this paper we focus on Pan European e-Services and issues related with their integration. Our analysis uses basic concepts of the generic public service model of the Governance Enterprise Architecture (GEA) and of the Web Service Modeling Ontology (WSMO), to express the semantic description of the e-services. Based on the above, we present a mediation infrastructure capable of resolving semantic interoperability conflicts at a pan-European level. We provide several examples to illustrate both the need to solve such semantic conflicts and the actual solutions we propose.

@inproceedings{
 title = {Development and evaluation of a VisSim/Comm based minimum shift keying simulator},
 type = {inproceedings},
 year = {2010},
 keywords = {Minimum shift keying,Simulation,Transceiver,Virtual laboratory,VisSim/Comm},
 pages = {661-666},
 volume = {1203},
 id = {501c5ad6-9723-3fb2-b83d-92dec0e4fd9f},
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 file_attached = {false},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Baltzis2010},
 private_publication = {false},
 abstract = {One of the most prominent data transmission techniques in modern digital communications is minimum shift keying (MSK) modulation. In recent years, the method has gained popularity due to several features highly desirable in telecommunications. In this paper, we develop an MSK transceiver in the VisSim/Comm simulation environment. The main benefit of our proposal is the detailed and realistic representation of the transceiver; in contrast to MSK building blocks in the simulation libraries, users can gain information in time and spectral domain at any point in the structure. We present a detailed description of the simulator and give representative examples that exhibit the simulator's performance and accuracy. We also discuss an educational application of the simulator. In that way physics students can study the simulator characteristics and evaluate its efficiency. © 2009 American Institute of Physics.},
 bibtype = {inproceedings},
 author = {Baltzis, Konstantinos B. and Goudos, Sotirios K.},
 doi = {10.1063/1.3322531},
 booktitle = {AIP Conference Proceedings}
}

One of the most prominent data transmission techniques in modern digital communications is minimum shift keying (MSK) modulation. In recent years, the method has gained popularity due to several features highly desirable in telecommunications. In this paper, we develop an MSK transceiver in the VisSim/Comm simulation environment. The main benefit of our proposal is the detailed and realistic representation of the transceiver; in contrast to MSK building blocks in the simulation libraries, users can gain information in time and spectral domain at any point in the structure. We present a detailed description of the simulator and give representative examples that exhibit the simulator's performance and accuracy. We also discuss an educational application of the simulator. In that way physics students can study the simulator characteristics and evaluate its efficiency. © 2009 American Institute of Physics.

@article{
 title = {Pareto optimal microwave filter design using multiobjective differential evolution},
 type = {article},
 year = {2010},
 keywords = {Dielectric filters,Differential evolution (DE),Generalized differential evolution (GDE),Microwave filter design,Multiobjective optimization (MO),Open loop ring resonator (OLRR) filter,Pareto optimization,Particle swarm optimization (PSO)},
 pages = {132-144},
 volume = {58},
 id = {a1965839-02d2-34e2-89ec-d596e3a3da50},
 created = {2020-02-29T16:57:42.117Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:54:02.273Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2010f},
 private_publication = {false},
 abstract = {Microwave filters play an important role in modern wireless communications. A novel method for the design of multilayer dielectric and open loop ring resonator (OLRR) filters under constraints is presented. The proposed design method is based on generalized differential evolution (GDE3), which is a multiobjective extension of differential evolution (DE). GDE3 algorithm can be applied for global optimization to any engineering problem with an arbitrary number of objective and constraint functions. GDE3 is compared against other evolutionary multiobjective algorithms like nondominated sorting genetic algorithm-II (NSGA-II), multiobjective particle swarm optimization (MOPSO) and multiobjective particle swarm optimization with fitness sharing (MOPSO-fs) for a number of microwave filter design cases. In the multilayer dielectric filter design case a predefined database of low loss dielectric materials is used. The results indicate the advantages of this approach and the applicability of this design method.© 2009 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Sahalos, John N.},
 doi = {10.1109/TAP.2009.2032100},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {1}
}

Microwave filters play an important role in modern wireless communications. A novel method for the design of multilayer dielectric and open loop ring resonator (OLRR) filters under constraints is presented. The proposed design method is based on generalized differential evolution (GDE3), which is a multiobjective extension of differential evolution (DE). GDE3 algorithm can be applied for global optimization to any engineering problem with an arbitrary number of objective and constraint functions. GDE3 is compared against other evolutionary multiobjective algorithms like nondominated sorting genetic algorithm-II (NSGA-II), multiobjective particle swarm optimization (MOPSO) and multiobjective particle swarm optimization with fitness sharing (MOPSO-fs) for a number of microwave filter design cases. In the multilayer dielectric filter design case a predefined database of low loss dielectric materials is used. The results indicate the advantages of this approach and the applicability of this design method.© 2009 IEEE.

@inbook{
 type = {inbook},
 year = {2010},
 pages = {983-994},
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 doi = {10.4018/978-1-61520-611-7.ch099},
 chapter = {Application of semantic web technology in e-business: Case studies in public domain data knowledge representation},
 title = {Encyclopedia of E-Business Development and Management in the Global Economy}
}

@article{
 title = {Application of a differential evolution algorithm with strategy adaptation to the design of multi-band microwave filters for wireless communications},
 type = {article},
 year = {2010},
 pages = {123-137},
 volume = {109},
 id = {0270d039-a70e-3b31-8520-d0d9b7db013d},
 created = {2020-02-29T16:57:42.872Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2010d},
 private_publication = {false},
 abstract = {In this paper, we present a new method for the design of multi-band microstrip filters. The proposed design method is based on Differential Evolution (DE) with strategy adaptation. This self-adaptive DE (SaDE) uses previous experience in both trial vector generation strategies and control parameter tuning. We apply this algorithm to two design cases of dual and tri-band filters for WiFi and WiMax applications. We select the Open Loop Ring Resonator (OLRR) filters, which are comprised of two uniform microstrip lines and pairs of open loops between them. The results indicate the advantages of this approach and the applicability of this design method.},
 bibtype = {article},
 author = {Goudos, S. K. and Zaharis, Z. D. and Yioultsis, T. V.},
 doi = {10.2528/PIER10081704},
 journal = {Progress in Electromagnetics Research}
}

In this paper, we present a new method for the design of multi-band microstrip filters. The proposed design method is based on Differential Evolution (DE) with strategy adaptation. This self-adaptive DE (SaDE) uses previous experience in both trial vector generation strategies and control parameter tuning. We apply this algorithm to two design cases of dual and tri-band filters for WiFi and WiMax applications. We select the Open Loop Ring Resonator (OLRR) filters, which are comprised of two uniform microstrip lines and pairs of open loops between them. The results indicate the advantages of this approach and the applicability of this design method.

@article{
 title = {Application of Taguchi's optimization method and self-adaptive differential evolution to the synthesis of linear antenna arrays},
 type = {article},
 year = {2010},
 pages = {159-180},
 volume = {102},
 id = {d1d26c82-9b34-3e9d-9b64-cbe5bad281cc},
 created = {2020-02-29T16:57:42.914Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.980Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Dib2010},
 private_publication = {false},
 abstract = {In this paper, the problem of designing linear antenna arrays for specific radiation properties is dealt with. The design problem is modeled as a single optimization problem. The objectives of this work are to minimize the maximum side lobe level (SLL) and perform null steering for isotropic linear antenna arrays by controlling different parameters of the array elements (position, amplitude, and phase). The optimization is performed using two techniques: Taguchi's optimization method and the self-adaptive differential evolution (SADE) technique. The advantage of Taguchi's optimization technique is the ability of solving problems with a high degree of complexity using a small number of experiments in the optimization process Taguchi's method is easy to implement and converges to the desired goal quickly in comparison with gradient-based methods and particle swarm optimization (PSO) Results obtained using Taguchi's method are in very good agreement with those obtained using the SADE technique.},
 bibtype = {article},
 author = {Dib, N. and Goudos, S. K. and Muhsen, H.},
 doi = {10.2528/PIER09122306},
 journal = {Progress in Electromagnetics Research}
}

In this paper, the problem of designing linear antenna arrays for specific radiation properties is dealt with. The design problem is modeled as a single optimization problem. The objectives of this work are to minimize the maximum side lobe level (SLL) and perform null steering for isotropic linear antenna arrays by controlling different parameters of the array elements (position, amplitude, and phase). The optimization is performed using two techniques: Taguchi's optimization method and the self-adaptive differential evolution (SADE) technique. The advantage of Taguchi's optimization technique is the ability of solving problems with a high degree of complexity using a small number of experiments in the optimization process Taguchi's method is easy to implement and converges to the desired goal quickly in comparison with gradient-based methods and particle swarm optimization (PSO) Results obtained using Taguchi's method are in very good agreement with those obtained using the SADE technique.

@article{
 title = {Pareto optimal yagi-uda antenna design using multi-objective differential evolution},
 type = {article},
 year = {2010},
 pages = {231-251},
 volume = {105},
 id = {63c32e7c-e8e7-321c-8f59-381750b39439},
 created = {2020-02-29T16:57:43.585Z},
 file_attached = {false},
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 last_modified = {2023-02-11T18:54:02.610Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2010c},
 private_publication = {false},
 abstract = {Antenna design problems often require the optimization of several conflicting objectives such as gain maximization, sidelobe level (SLL) reduction and input impedance matching. Multi-objective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. An efficient algorithm is Generalized Differential Evolution (GDE3), which is a multi-objective extension of Differential Evolution (DE). The GDE3 algorithm can be applied to global optimization of any engineering problem with an arbitrary number of objective and constraint functions. Another popular MOEA is Nondominated Sorting Genetic Algorithm-II (NSGA-II). Both GDE3 and NSGA-II are applied to Yagi-Uda antenna design under specified constraints. The numerical solver used for antenna parameters calculations is SuperNEC, an object-oriented version of the numerical electromagnetic code (NEC-2). Three different Yagi-Uda antenna designs are considered and optimized. Pareto fronts are produced for both algorithms. The results indicate the advantages of this approach and the applicability of this design method.},
 bibtype = {article},
 author = {Goudos, S. K. and Siakavara, K. and Vafiadis, E. E. and Sahalos, J. N.},
 doi = {10.2528/PIER10052302},
 journal = {Progress in Electromagnetics Research}
}

Antenna design problems often require the optimization of several conflicting objectives such as gain maximization, sidelobe level (SLL) reduction and input impedance matching. Multi-objective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. An efficient algorithm is Generalized Differential Evolution (GDE3), which is a multi-objective extension of Differential Evolution (DE). The GDE3 algorithm can be applied to global optimization of any engineering problem with an arbitrary number of objective and constraint functions. Another popular MOEA is Nondominated Sorting Genetic Algorithm-II (NSGA-II). Both GDE3 and NSGA-II are applied to Yagi-Uda antenna design under specified constraints. The numerical solver used for antenna parameters calculations is SuperNEC, an object-oriented version of the numerical electromagnetic code (NEC-2). Three different Yagi-Uda antenna designs are considered and optimized. Pareto fronts are produced for both algorithms. The results indicate the advantages of this approach and the applicability of this design method.

@article{
 title = {Cell-to-switch assignment in cellular networks using barebones particle swarm optimization},
 type = {article},
 year = {2010},
 keywords = {Barebones PSO,Cell assignment,Cellular networks,Integer programming,PSO},
 pages = {254-260},
 volume = {7},
 id = {f00a6c45-3836-3e7d-99d6-55f5c4383003},
 created = {2020-02-29T16:57:43.605Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.750Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2010b},
 private_publication = {false},
 abstract = {Cell assignment is an important issue in the area of resource management in cellular networks. The problem is an NP-hard one and requires efficient search techniques for its solution in real-time. In this letter, in order to minimize the cabling and handoff costs, we use two novel discrete particle swarm optimization (PSO) algorithms, the barebones (BB) and the exploiting barebones (BBExp) PSO variants. The impact of network and algorithm parameters on the solution accuracy and computational cost of the methods is investigated. Comparisons with optimization methods in the literature demonstrate the benefits of our proposal. © IEICE 2010.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Baltzis, Konstantinos B. and Bachtsevanidis, Christos and Sahalos, John N.},
 doi = {10.1587/elex.7.254},
 journal = {IEICE Electronics Express},
 number = {4}
}

Cell assignment is an important issue in the area of resource management in cellular networks. The problem is an NP-hard one and requires efficient search techniques for its solution in real-time. In this letter, in order to minimize the cabling and handoff costs, we use two novel discrete particle swarm optimization (PSO) algorithms, the barebones (BB) and the exploiting barebones (BBExp) PSO variants. The impact of network and algorithm parameters on the solution accuracy and computational cost of the methods is investigated. Comparisons with optimization methods in the literature demonstrate the benefits of our proposal. © IEICE 2010.

@inproceedings{
 title = {Aperture array model for rapid assessment of Base Station Antennas near field based on half power beam width equivalence},
 type = {inproceedings},
 year = {2010},
 id = {1b08b0f8-aba8-3310-b0b6-d3299902e76c},
 created = {2020-02-29T16:57:44.565Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.489Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Nanos2010},
 private_publication = {false},
 abstract = {In this work a fast method is presented, for the approximate estimation of the near field in the vicinity of mobile Base Station Antennas (BSA) comprised of reflector type unit cells. The method is based on the substitution of each unit cell of the BSA with a uniformly excited rectangular aperture of suitable dimensions, so that both have equal half power beam widths in the two main radiation planes. The method utilizes the fast numerical evaluation of the near field of uniformly excited apertures, and comes as an enhancement to similar synthetic based model.},
 bibtype = {inproceedings},
 author = {Nanos, Apostolos A. and Goudos, Sotirios K. and Siakavara, Katherine and Samaras, Theodoros and Sahalos, John N.},
 booktitle = {EuCAP 2010 - The 4th European Conference on Antennas and Propagation}
}

In this work a fast method is presented, for the approximate estimation of the near field in the vicinity of mobile Base Station Antennas (BSA) comprised of reflector type unit cells. The method is based on the substitution of each unit cell of the BSA with a uniformly excited rectangular aperture of suitable dimensions, so that both have equal half power beam widths in the two main radiation planes. The method utilizes the fast numerical evaluation of the near field of uniformly excited apertures, and comes as an enhancement to similar synthetic based model.

@inproceedings{
 title = {Wideband E-shaped patch antenna design for wireless communications using self-adaptive differential evolution},
 type = {inproceedings},
 year = {2010},
 id = {cbc6abe1-e5ab-3cff-9855-3a5206e974dc},
 created = {2020-02-29T16:57:44.598Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.083Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Goudos2010a},
 private_publication = {false},
 abstract = {Wideband E-shaped patch antenna design is presented. The design technique is based on a self-adaptive Differential Evolution (DE) algorithm. In order to evaluate the algorithm's performance we compare results with three other common evolutionary algorithms regarding statistical results and convergence speed. The results show that the self-adaptive DE algorithm outerperforms other global optimizers like Particle swarm optimization (PSO) variants and the DE rand/1/bin strategy. Therefore, the results indicate the advantages of this approach and the applicability of this design method to other optimization problems in electromagnetics.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Nanos, Apostolos A. and Samaras, Theodoros and Siakavara, Katherine and Sahalos, John N.},
 booktitle = {EuCAP 2010 - The 4th European Conference on Antennas and Propagation}
}

Wideband E-shaped patch antenna design is presented. The design technique is based on a self-adaptive Differential Evolution (DE) algorithm. In order to evaluate the algorithm's performance we compare results with three other common evolutionary algorithms regarding statistical results and convergence speed. The results show that the self-adaptive DE algorithm outerperforms other global optimizers like Particle swarm optimization (PSO) variants and the DE rand/1/bin strategy. Therefore, the results indicate the advantages of this approach and the applicability of this design method to other optimization problems in electromagnetics.

@article{
 title = {Application of a comprehensive learning particle swarm optimizer to unequally spaced linear array synthesis with sidelobe level suppression and null control},
 type = {article},
 year = {2010},
 keywords = {Array synthesis,Comprehensive learning particle swarm optimizer (C,Genetic algorithms (GAs),Linear array design,Null control,Particle swarm optimization (PSO),Sidelobe suppression},
 pages = {125-129},
 volume = {9},
 id = {9d2a5145-9eac-3cf6-81c0-0c1ea5443e7e},
 created = {2020-02-29T16:57:44.617Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.127Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2010},
 private_publication = {false},
 abstract = {We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA). © 2006 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Moysiadou, Vasiliki and Samaras, Theodoros and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/LAWP.2010.2044552},
 journal = {IEEE Antennas and Wireless Propagation Letters}
}

We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA). © 2006 IEEE.

@article{
 title = {Design of Microwave broadband absorbers using a self-adaptive differential evolution algorithm},
 type = {article},
 year = {2009},
 keywords = {Evolutionary algorithms,Microwave absorber design,Multilayer coatings,Particle swarm optimization differential evolution,Radar absorbing materials},
 pages = {364-372},
 volume = {19},
 id = {f145d4e4-7359-3b29-8a3b-32e1d350e792},
 created = {2020-02-29T16:57:41.897Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.343Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2009b},
 private_publication = {false},
 abstract = {Microwave broadband absorber design for a desired frequency and angle range is presented. The design technique is based on a self-adaptive Differential Evolution (DE) algorithm. Numerical examples are compared with the existing in the literature and with those found by the other evolutionary algorithms. The results show that the new DE algorithm version outerperforms other global optimizers like Particle swarm optimization (PSO) variants and the classical DE algorithm. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE 19: 364-372, 2009.},
 bibtype = {article},
 author = {Goudos, Sotirios K.},
 doi = {10.1002/mmce.20357},
 journal = {International Journal of RF and Microwave Computer-Aided Engineering},
 number = {3}
}

Microwave broadband absorber design for a desired frequency and angle range is presented. The design technique is based on a self-adaptive Differential Evolution (DE) algorithm. Numerical examples are compared with the existing in the literature and with those found by the other evolutionary algorithms. The results show that the new DE algorithm version outerperforms other global optimizers like Particle swarm optimization (PSO) variants and the classical DE algorithm. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE 19: 364-372, 2009.

@misc{
 title = {Model-driven eGovernment interoperability: A review of the state of the art},
 type = {misc},
 year = {2009},
 source = {Computer Standards and Interfaces},
 keywords = {Data modelling,Domain modelling,Ontologies,Process modelling,Semantic web,eGovernment interoperability},
 pages = {613-628},
 volume = {31},
 issue = {4},
 id = {597bd958-a346-3a3e-9e4e-74f2ec191808},
 created = {2020-02-29T16:57:42.940Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.917Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Peristeras2009a},
 private_publication = {false},
 abstract = {This paper reviews the state of the art in the area of enhancing eGovernment interoperability by using common models and/or ontologies. This area has currently become a very active research field. We identify and present a significant number (> 40) of relevant efforts. These initiatives are grouped into categories based on the owner, scope and modelling perspective of each project. We then focus on the cases that build generic and universal eGovernment representations and models. We analyse, evaluate and rate them using an additional set of criteria. We end up with conclusions and possible directions for the exploitation and usage of these models. © 2008 Elsevier B.V. All rights reserved.},
 bibtype = {misc},
 author = {Peristeras, Vassilios and Tarabanis, Konstantinos and Goudos, Sotirios K.},
 doi = {10.1016/j.csi.2008.09.034}
}

This paper reviews the state of the art in the area of enhancing eGovernment interoperability by using common models and/or ontologies. This area has currently become a very active research field. We identify and present a significant number (> 40) of relevant efforts. These initiatives are grouped into categories based on the owner, scope and modelling perspective of each project. We then focus on the cases that build generic and universal eGovernment representations and models. We analyse, evaluate and rate them using an additional set of criteria. We end up with conclusions and possible directions for the exploitation and usage of these models. © 2008 Elsevier B.V. All rights reserved.

@article{
 title = {An ontological representation of public services: Models, technologies and use cases},
 type = {article},
 year = {2009},
 keywords = {OWL,Ontology,Public administration service provision,Semantic discovery,Semantic web applications,eGovernment},
 pages = {245-267},
 volume = {8},
 id = {30d7c6fd-19d3-3d29-8a86-7372ea9d11d5},
 created = {2020-02-29T16:57:43.562Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.090Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Peristeras2009},
 private_publication = {false},
 abstract = {This paper presents our effort to "ontologize" a conceptual public service model in order to express in a formal way domain specific semantics and create a reusable service ontology for eGovernment applications. The conceptual model we have used comes from a broader public administration domain modeling effort, called Governance Enterprise Architecture (GEA). With this as a starting point, we document our experience of using the Web Ontology Language (OWL) for the ontological representation of the model. Moreover, we present a use case and a platform that is based and uses this ontology for the discovery of eGovernment services. These services are discovered by semantically matching citizens' profiles with formally described public services. The proposed domain ontology is reusable and can be exploited by a variety of semantic web applications for eGovernment whenever a formal and standardized model for public services is needed. © Rinton Press.},
 bibtype = {article},
 author = {Peristeras, Vassilios and Goudos, Sotirios K. and Loutas, Nikolaos and Tarabanis, Konstantinos},
 journal = {Journal of Web Engineering},
 number = {3}
}

This paper presents our effort to "ontologize" a conceptual public service model in order to express in a formal way domain specific semantics and create a reusable service ontology for eGovernment applications. The conceptual model we have used comes from a broader public administration domain modeling effort, called Governance Enterprise Architecture (GEA). With this as a starting point, we document our experience of using the Web Ontology Language (OWL) for the ontological representation of the model. Moreover, we present a use case and a platform that is based and uses this ontology for the discovery of eGovernment services. These services are discovered by semantically matching citizens' profiles with formally described public services. The proposed domain ontology is reusable and can be exploited by a variety of semantic web applications for eGovernment whenever a formal and standardized model for public services is needed. © Rinton Press.

@inproceedings{
 title = {Level change detection in time series using higher order statistics},
 type = {inproceedings},
 year = {2009},
 keywords = {Change point detection,Heuristic methods,Higher order statistics,Interrupted time series},
 id = {b8f8910a-3e71-3c3b-9c67-72971b9d49bd},
 created = {2020-02-29T16:57:44.657Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.295Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Hilas2009},
 private_publication = {false},
 abstract = {Changes in the level of a time series are usually attributed to an intervention that interrupts its evolution. The resulting time series are referred to as interrupted time series and they are studied in order to measure, e.g. the impact of new laws or medical treatments. In the present paper a heuristic method for level change detection in non-stationary time series is presented. The method uses higher order statistics, namely the skewness and the kurtosis, and can identify both the existence of a change in the level of the time series as well as the time point it has happened. The technique is tested with both simulated and real world data and is straightforward applicable to the detection of outliers in time series. © 2009 IEEE.},
 bibtype = {inproceedings},
 author = {Hilas, C. S. and Rekanos, I. T. and Goudos, S. K. and Mastorocostas, P. A. and Sahalos, J. N.},
 doi = {10.1109/ICDSP.2009.5201260},
 booktitle = {DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings}
}

Changes in the level of a time series are usually attributed to an intervention that interrupts its evolution. The resulting time series are referred to as interrupted time series and they are studied in order to measure, e.g. the impact of new laws or medical treatments. In the present paper a heuristic method for level change detection in non-stationary time series is presented. The method uses higher order statistics, namely the skewness and the kurtosis, and can identify both the existence of a change in the level of the time series as well as the time point it has happened. The technique is tested with both simulated and real world data and is straightforward applicable to the detection of outliers in time series. © 2009 IEEE.

@inproceedings{
 title = {A comparative study of particle swarm optimization and differential evolution on radar absorbing materials design for EMC applications},
 type = {inproceedings},
 year = {2009},
 keywords = {Differential evolution,Evolutionary algorithms,Microwave absorber design,Multi-layer coatings,Particle swarm optimization,Radar absorbing materials},
 id = {d626d22b-e4a1-32f6-bb46-45a76cd4d7fb},
 created = {2020-02-29T16:57:44.685Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.951Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Goudos2009a},
 private_publication = {false},
 abstract = {Radar Absorbing Materials (RAM) design for a desired frequency and angle range is presented. We evaluate the performance of Particle Swarm Optimization (PSO) and Differential Evolution (DE) regarding their applicability to absorber design. The results show that the DE algorithm outerperforms PSO variants. © 2009 IEEE.},
 bibtype = {inproceedings},
 author = {Goudos, S. K. and Zaharis, Z. D. and Baltzis, K. B. and Hilas, C. S. and Sahalos, J. N.},
 doi = {10.1109/EMCEUROPE.2009.5189697},
 booktitle = {2009 International Symposium on Electromagnetic Compatibility - EMC Europe}
}

Radar Absorbing Materials (RAM) design for a desired frequency and angle range is presented. We evaluate the performance of Particle Swarm Optimization (PSO) and Differential Evolution (DE) regarding their applicability to absorber design. The results show that the DE algorithm outerperforms PSO variants. © 2009 IEEE.

@article{
 title = {Pareto optimal design of dual-band base station antenna arrays using multi-objective particle swarm optimization with fitness sharing},
 type = {article},
 year = {2009},
 keywords = {Dual-band antenna array design,Multi-objective optimization,Pareto optimization,Particle swarm optimization},
 pages = {1522-1525},
 volume = {45},
 id = {8d1be6ac-f5e9-3f06-b050-88c0dc4a723f},
 created = {2020-02-29T16:57:44.717Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.629Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2009},
 private_publication = {false},
 abstract = {The design of dual-band base station antennas under constraints for mobile communications is addressed in this paper. Given the antenna geometry, the method of moments (MoM) is used to compute the antenna characteristics. Two distinct multi-objective evolutionary algorithms are applied in order to find the Pareto front of the feasible solutions that satisfy the design constraints. In the present work, the Multi-Objective Particle Swarm Optimization with fitness sharing (MOPSO-fs) is compared with the Nondominated Sorting Genetic Algorithm-II (NSGA-II) in order to optimize the antenna geometry. Two design cases are presented. The first case is a five-element array operating in GSM1800/UMTS frequency bands. The second base station antenna array consists of six elements operating in UMTS/WLAN (2.4 GHz) frequency bands. © 2006 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Zaharis, Zaharias D. and Kampitaki, Dimitra G. and Rekanos, Ioannis T. and Hilas, Costas S.},
 doi = {10.1109/TMAG.2009.2012695},
 journal = {IEEE Transactions on Magnetics},
 number = {3}
}

The design of dual-band base station antennas under constraints for mobile communications is addressed in this paper. Given the antenna geometry, the method of moments (MoM) is used to compute the antenna characteristics. Two distinct multi-objective evolutionary algorithms are applied in order to find the Pareto front of the feasible solutions that satisfy the design constraints. In the present work, the Multi-Objective Particle Swarm Optimization with fitness sharing (MOPSO-fs) is compared with the Nondominated Sorting Genetic Algorithm-II (NSGA-II) in order to optimize the antenna geometry. Two design cases are presented. The first case is a five-element array operating in GSM1800/UMTS frequency bands. The second base station antenna array consists of six elements operating in UMTS/WLAN (2.4 GHz) frequency bands. © 2006 IEEE.

@article{
 title = {Solving semantic interoperability conflicts in cross-border E-government services},
 type = {article},
 year = {2009},
 keywords = {Data integration,IT in public administration,Knowledge integration,Ontologies,Semantic matching,Web applications},
 pages = {1-47},
 volume = {5},
 id = {70789606-30c4-3813-b7b3-1a64f17d0aff},
 created = {2020-02-29T16:57:45.085Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.901Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Mocan2009},
 private_publication = {false},
 abstract = {Interoperability is one of the most challenging problems in modern cross-organizational information systems, which rely on heterogeneous information and process models. Interoperability becomes very important for e-Government information systems that support cross-organizational communication especially in a cross-border setting. The main goal in this context is to seamlessly provide integrated services to the user (citizen). In this paper we focus on Pan European e-Services and issues related with their integration. Our analysis uses basic concepts of the generic public service model of the Governance Enterprise Architecture (GEA) and of the Web Service Modeling Ontology (WSMO), to express the semantic description of the e-services. Based on the above, we present a mediation infrastructure capable of resolving semantic interoperability conflicts at a pan-European level. We provide several examples to illustrate both the need to solve such semantic conflicts and the actual solutions we propose. [Article copies are available for purchase from InfoSci-on-Demand.com]. Copyright © 2009, IGI Global.},
 bibtype = {article},
 author = {Mocan, Adrian and Facca, Federico M. and Loutas, Nikolaos and Peristeras, Vassilios and Goudos, Sotirios K. and Tarabanis, Konstantinos},
 doi = {10.4018/jswis.2009010101},
 journal = {International Journal on Semantic Web and Information Systems},
 number = {1}
}

Interoperability is one of the most challenging problems in modern cross-organizational information systems, which rely on heterogeneous information and process models. Interoperability becomes very important for e-Government information systems that support cross-organizational communication especially in a cross-border setting. The main goal in this context is to seamlessly provide integrated services to the user (citizen). In this paper we focus on Pan European e-Services and issues related with their integration. Our analysis uses basic concepts of the generic public service model of the Governance Enterprise Architecture (GEA) and of the Web Service Modeling Ontology (WSMO), to express the semantic description of the e-services. Based on the above, we present a mediation infrastructure capable of resolving semantic interoperability conflicts at a pan-European level. We provide several examples to illustrate both the need to solve such semantic conflicts and the actual solutions we propose. [Article copies are available for purchase from InfoSci-on-Demand.com]. Copyright © 2009, IGI Global.

@article{
 title = {Thinned planar array design using boolean PSO with velocity mutation},
 type = {article},
 year = {2009},
 keywords = {Artificial immune system,Particle swarm optimization (PSO),Planar arrays,Thinned arrays},
 pages = {1490-1493},
 volume = {45},
 id = {6ce6ac36-8482-3b05-b990-d05bb0c87e68},
 created = {2020-02-29T16:57:45.121Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.191Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Deligkaris2009},
 private_publication = {false},
 abstract = {The design of thinned planar microstrip arrays under specific constraints concerning the impedance-matching condition of the array elements and the radiation pattern is presented. The radiation characteristics of the structure are extracted by applying the method-of-moments. The array design is based on a novel optimization method, which is a modified version of the boolean particle swarm optimization that employs velocity mutation (BPSO-vm). Apart from the optimization of the array geometry, the proposed method is applicable to other discrete-variable optimization problems. Moreover, the planar array design is coped with by means of other techniques, namely, a binary coded Genetic Algorithm, the binary Particle Swarm Optimization, and the Boolean PSO. The comparison of the above methods and the BPSO-vm shows the efficiency of the proposed technique. © 2006 IEEE.},
 bibtype = {article},
 author = {Deligkaris, Kosmas V. and Zaharis, Zaharias D. and Kampitaki, Dimitra G. and Goudos, Sotirios K. and Rekanos, Ioannis T. and Spasos, Michalis N.},
 doi = {10.1109/TMAG.2009.2012687},
 journal = {IEEE Transactions on Magnetics},
 number = {3}
}

The design of thinned planar microstrip arrays under specific constraints concerning the impedance-matching condition of the array elements and the radiation pattern is presented. The radiation characteristics of the structure are extracted by applying the method-of-moments. The array design is based on a novel optimization method, which is a modified version of the boolean particle swarm optimization that employs velocity mutation (BPSO-vm). Apart from the optimization of the array geometry, the proposed method is applicable to other discrete-variable optimization problems. Moreover, the planar array design is coped with by means of other techniques, namely, a binary coded Genetic Algorithm, the binary Particle Swarm Optimization, and the Boolean PSO. The comparison of the above methods and the BPSO-vm shows the efficiency of the proposed technique. © 2006 IEEE.

@inbook{
 type = {inbook},
 year = {2009},
 pages = {615-633},
 websites = {https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60566-194-0.ch040},
 publisher = {IGI Global},
 city = {Hershey, PA, USA},
 id = {8e105eb6-9e47-3854-a2f8-6237a7e07e63},
 created = {2023-02-11T21:19:22.082Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:19:22.082Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Lee2009},
 source_type = {incollection},
 private_publication = {false},
 abstract = {Network planning and management in a large organization such as a university, is a complex task. A large university is an inherently demanding environment in terms of telecommunications services offered and technologies used. This chapter presents and discusses network management and planning issues in the Aristotle University of Thessaloniki, Greece. Examples of network management procedures are given. We present the data model for service provision. The network expansion and cost reduction case studies are discussed. A SWOT analysis about University’s Telecommunications Center is given. Finally, we discuss the migration analysis for future upgrades that will fully enable the use of emerging technologies such as Voice over IP (VoIP).},
 bibtype = {inbook},
 author = {Goudos, Sotirios K and Agorogianni, Angeliki Z and Zaharis, Zaharias D},
 editor = {Lee, In},
 doi = {10.4018/978-1-60566-194-0.ch040},
 chapter = {Telecommunications Network Planning and Operations Management in an Academic Environment: The Case Study of the Aristotle University of Thessaloniki},
 title = {Handbook of Research on Telecommunications Planning and Management for Business}
}

Network planning and management in a large organization such as a university, is a complex task. A large university is an inherently demanding environment in terms of telecommunications services offered and technologies used. This chapter presents and discusses network management and planning issues in the Aristotle University of Thessaloniki, Greece. Examples of network management procedures are given. We present the data model for service provision. The network expansion and cost reduction case studies are discussed. A SWOT analysis about University’s Telecommunications Center is given. Finally, we discuss the migration analysis for future upgrades that will fully enable the use of emerging technologies such as Voice over IP (VoIP).

@article{
 title = {EMI reduction and ICs optimal arrangement inside high-speed networking equipment using particle swarm optimization},
 type = {article},
 year = {2008},
 keywords = {Electromagnetic interference (EMI),Monte Carlo simulation,Numerical techniques,Particle swarm optimization (PSO),Printed circuit board (PCB) design},
 pages = {586-596},
 volume = {50},
 id = {94c0ed3b-e08c-3b44-8763-53b4beb677b5},
 created = {2020-02-29T16:57:42.955Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.858Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2008},
 private_publication = {false},
 abstract = {In this paper, a numerical approach to the modeling of electromagnetic interference (EMI) from the emissions of integrated circuits (ICs) and printed circuit boards (PCBs), inside rectangular metallic enclosures of communication devices, is presented. The ICs are modeled as small magnetic dipoles, and their interaction with the enclosures are formulated by means of dyadic Green's functions. Given the probability distribution describing the magnetic dipole sources, a Monte Carlo simulation is employed to derive the electric current density on the metallic walls as well as to perform a worse-case analysis. The EMI in a network switch and a network router are investigated by means of sources-device models developed for each one of the devices. These models are based on data obtained from magnetic probe measurements in various types of network equipment. Finally, the particle swarm optimization algorithm is utilized to indicate the optimal arrangement of ICs that results in significant reduction of the electric current density induced on the metallic walls. © 2008 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Rekanos, Ioannis T. and Sahalos, Sotirios N.},
 doi = {10.1109/TEMC.2008.924389},
 journal = {IEEE Transactions on Electromagnetic Compatibility},
 number = {3 PART 2}
}

In this paper, a numerical approach to the modeling of electromagnetic interference (EMI) from the emissions of integrated circuits (ICs) and printed circuit boards (PCBs), inside rectangular metallic enclosures of communication devices, is presented. The ICs are modeled as small magnetic dipoles, and their interaction with the enclosures are formulated by means of dyadic Green's functions. Given the probability distribution describing the magnetic dipole sources, a Monte Carlo simulation is employed to derive the electric current density on the metallic walls as well as to perform a worse-case analysis. The EMI in a network switch and a network router are investigated by means of sources-device models developed for each one of the devices. These models are based on data obtained from magnetic probe measurements in various types of network equipment. Finally, the particle swarm optimization algorithm is utilized to indicate the optimal arrangement of ICs that results in significant reduction of the electric current density induced on the metallic walls. © 2008 IEEE.

@article{
 title = {A conceptual analysis of semantic conflicts in pan-European e-government services},
 type = {article},
 year = {2008},
 keywords = {Cross-border services,Pan-European e-government services,Pan-European public services,Semantic conflict types,Semantic interoperability},
 pages = {877-891},
 volume = {34},
 id = {dd3db816-a893-32ac-afe2-17d34af2d0be},
 created = {2020-02-29T16:57:43.664Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.271Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Peristeras2008},
 private_publication = {false},
 abstract = {This paper presents research in Pan-European Public Services (PEPS) and Pan-European E-Government Services (PEGS). We examine different types of semantic interoperability issues that may arise when actors, information and services from different Member States (MS) need to cooperate and/or interoperate during the public service provision process. The semantic conflict types that arise in these cases are identified and classified according to a typology that is based on the combination of a known classification for semantic conflicts and domain specific concepts from the Governance Enterprise Architecture object model. This conceptual modelling describes and organizes the problem space, documents the requirements and can thus provide the basis for engineering solutions to resolve the identified conflicts. © CILIP.},
 bibtype = {article},
 author = {Peristeras, Vassilios and Loutas, Nikolaos and Goudos, Sotirios K. and Tarabanis, Konstantinos},
 doi = {10.1177/0165551508091012},
 journal = {Journal of Information Science},
 number = {6}
}

This paper presents research in Pan-European Public Services (PEPS) and Pan-European E-Government Services (PEGS). We examine different types of semantic interoperability issues that may arise when actors, information and services from different Member States (MS) need to cooperate and/or interoperate during the public service provision process. The semantic conflict types that arise in these cases are identified and classified according to a typology that is based on the combination of a known classification for semantic conflicts and domain specific concepts from the Governance Enterprise Architecture object model. This conceptual modelling describes and organizes the problem space, documents the requirements and can thus provide the basis for engineering solutions to resolve the identified conflicts. © CILIP.

@inproceedings{
 title = {Thinned Planar Array Design Using Boolean PSO with Velocity Mutation},
 type = {inproceedings},
 year = {2008},
 pages = {324},
 id = {4587981d-9b97-3d16-9673-0aeb2a50f8a6},
 created = {2023-02-11T21:11:00.677Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:11:00.677Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {deligkaris2008thinned},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Deligkaris, Kosmas V and Zaharis, Zaharias D and Kampitaki, Dimitra G and Goudos, Sotirios K and Rekanos, Ioannis T and Spasos, Michalis N},
 booktitle = {Proceedings of the 13th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC2008)}
}

@inproceedings{
 title = {Pareto Optimal Design of Dual Band Base Station Antenna Arrays Using Multi-Objective Particle Swarm Optimization with Fitness Sharing},
 type = {inproceedings},
 year = {2008},
 pages = {472},
 id = {b7019b1a-6fbc-3fdd-b006-414de8d5c607},
 created = {2023-02-11T21:11:00.694Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:11:00.694Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2008pareto},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Zaharis, Zaharias D and Kampitaki, Dimitra G and Rekanos, Ioannis T and Hilas, Costas S},
 booktitle = {Proceedings of the 13th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC2008)}
}

@article{
 title = {A versatile software tool for microwave planar radar absorbing materials design using global optimization algorithms},
 type = {article},
 year = {2007},
 keywords = {CAD tool,Microwave multi-layer absorber design,Particle swarm optimization,Radar absorbing materials},
 volume = {28},
 id = {2d648526-4fb9-37e5-b41b-5a1d1fb17bef},
 created = {2020-02-29T16:57:41.902Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:46.180Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007k},
 private_publication = {false},
 abstract = {A computer-aided design (CAD) tool for the design of planar multi-layer coatings with high absorption for a desired frequency and angle range is presented. The tool uses deterministic and evolutionary optimization design methods. Both single and multi-objective design algorithms can be used and a single absorber design or the Pareto front can be found accordingly. A novel design technique utilizing PSO is also presented. A user-defined or a pre-defined design case can be selected interchangeably. The choice of selecting materials from pre-defined database is also available. The tool can be useful for both educational and research purposes. The efficiency of the tool is demonstrated through several design cases that are in agreement with existing literature data. © 2006 Elsevier Ltd. All rights reserved.},
 bibtype = {article},
 author = {Goudos, S.K.},
 doi = {10.1016/j.matdes.2006.10.016},
 journal = {Materials and Design},
 number = {10}
}

A computer-aided design (CAD) tool for the design of planar multi-layer coatings with high absorption for a desired frequency and angle range is presented. The tool uses deterministic and evolutionary optimization design methods. Both single and multi-objective design algorithms can be used and a single absorber design or the Pareto front can be found accordingly. A novel design technique utilizing PSO is also presented. A user-defined or a pre-defined design case can be selected interchangeably. The choice of selecting materials from pre-defined database is also available. The tool can be useful for both educational and research purposes. The efficiency of the tool is demonstrated through several design cases that are in agreement with existing literature data. © 2006 Elsevier Ltd. All rights reserved.

@article{
 title = {Application of a particle swarm optimizer to the design of microwave broadband absorbers},
 type = {article},
 year = {2007},
 keywords = {Microwave absorber design,Multi-layer coatings,Particle swarm optimization,Radar absorbing materials},
 pages = {312-317},
 volume = {6},
 id = {91be0c63-97a8-32c0-87b2-61f4113d8e76},
 created = {2020-02-29T16:57:41.943Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.466Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007j},
 private_publication = {false},
 abstract = {Microwave broadband absorber design for a desired frequency and angle range is presented. The novel design technique is based on a Particle swarm optimization (PSO) algorithm. PSO is an evolutionary optimization algorithm based on the bird fly. Several design cases are presented. Numerical results are compared with the existing in the literature. Finally the advantages of this approach and the applicability of this design method are discussed.},
 bibtype = {article},
 author = {Goudos, Sotirios K.},
 journal = {WSEAS Transactions on Communications},
 number = {2}
}

Microwave broadband absorber design for a desired frequency and angle range is presented. The novel design technique is based on a Particle swarm optimization (PSO) algorithm. PSO is an evolutionary optimization algorithm based on the bird fly. Several design cases are presented. Numerical results are compared with the existing in the literature. Finally the advantages of this approach and the applicability of this design method are discussed.

@article{
 title = {Numerical modeling and measurements of radiated emissions from integrated circuits inside telecommunications equipment},
 type = {article},
 year = {2007},
 keywords = {Electromagnetic compatibility,Electromagnetic interference,Green's functions calculation,Magnetic probe measurements,Numerical modeling},
 pages = {499-504},
 volume = {6},
 id = {11724eba-3614-3a83-aca5-1d2b46a63d1a},
 created = {2020-02-29T16:57:42.122Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.571Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007i},
 private_publication = {false},
 abstract = {A numerical approach to the modeling of Electromagnetic Interference (EMI) from the emissions of Integrated Circuits (ICs) inside rectangular metallic enclosures of communications devices is presented. The ICs are modeled as small magnetic or electric dipoles. Radiated emissions from ICs are examined and measured using magnetic probes on various types of network equipment. Based on these measurements source amplitude and existence probabilistic models are created. Closed form expressions for the induced electric field on the metallic walls are given. Electric field calculation examples show the major trends in a multiple source system and help perform a worst-case analysis. The applications of the above approach to the PCB design process are discussed.},
 bibtype = {article},
 author = {Goudos, S. K. and Hilas, C. S.},
 journal = {WSEAS Transactions on Communications},
 number = {4}
}

A numerical approach to the modeling of Electromagnetic Interference (EMI) from the emissions of Integrated Circuits (ICs) inside rectangular metallic enclosures of communications devices is presented. The ICs are modeled as small magnetic or electric dipoles. Radiated emissions from ICs are examined and measured using magnetic probes on various types of network equipment. Based on these measurements source amplitude and existence probabilistic models are created. Closed form expressions for the induced electric field on the metallic walls are given. Electric field calculation examples show the major trends in a multiple source system and help perform a worst-case analysis. The applications of the above approach to the PCB design process are discussed.

@article{
 title = {A semantic web approach for mapping citizen profiles to public administration services based on Governance Enterprise Architecture (GEA) model},
 type = {article},
 year = {2007},
 keywords = {E-Government,Governance Enterprise Architecture,OWL,Semantic matching,Semantic web},
 pages = {1283-1289},
 volume = {4},
 id = {e646e150-27de-31ee-a08e-22f66f0607b9},
 created = {2020-02-29T16:57:42.986Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.041Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007h},
 private_publication = {false},
 abstract = {This paper discusses the common public administration problem of matching a citizen's needs with the available public services. The Governance Enterprise Architecture (GEA) object model, a technology independent data model for public administration domain, is used in conjunction with semantic web technologies. An ontology representation of the above object model in OWL Web Ontology Language is created. This ontology serves as the knowledge base for a semantic web application. The input to the application consists of the user profile, while the output returned consists of the public services that match the specified profile.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Peristeras, Vassilios and Tarabanis, Konstantinos},
 journal = {WSEAS Transactions on Information Science and Applications},
 number = {6}
}

This paper discusses the common public administration problem of matching a citizen's needs with the available public services. The Governance Enterprise Architecture (GEA) object model, a technology independent data model for public administration domain, is used in conjunction with semantic web technologies. An ontology representation of the above object model in OWL Web Ontology Language is created. This ontology serves as the knowledge base for a semantic web application. The input to the application consists of the user profile, while the output returned consists of the public services that match the specified profile.

@article{
 title = {A semantic web application for public administration using OWL for public domain data knowledge representation},
 type = {article},
 year = {2007},
 keywords = {E-government,OWL,Public administration,Semantic web},
 pages = {725-730},
 volume = {4},
 id = {540e924a-bb14-32b2-a3c4-816b9e2a40e3},
 created = {2020-02-29T16:57:43.004Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.912Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007g},
 private_publication = {false},
 abstract = {This paper contributes to the more general problem of supplying the citizen with the correct information from public administration in a quick and easy way. Specifically, getting the information about all the benefits that someone is entitled to is a very complex task in many countries. To address this problem, a domain ontology is created. The ontology is used as the knowledge base for a semantic application that uses a reasoner. This latter component queries the knowledge base through a web interface by receiving the user's profile as input, and providing as output the benefits that match the specified profile. The application is highly reconfigurable in order to easily accommodate legislation changes. Moreover, the application is transferable to a large number of similar service provision cases in the public administration domain. In light of these, the advantages of semantic web technology and its application to the e-government domain are presented.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Peristeras, Vassilios and Tarabanis, Konstantinos},
 journal = {WSEAS Transactions on Information Science and Applications},
 number = {4}
}

This paper contributes to the more general problem of supplying the citizen with the correct information from public administration in a quick and easy way. Specifically, getting the information about all the benefits that someone is entitled to is a very complex task in many countries. To address this problem, a domain ontology is created. The ontology is used as the knowledge base for a semantic application that uses a reasoner. This latter component queries the knowledge base through a web interface by receiving the user's profile as input, and providing as output the benefits that match the specified profile. The application is highly reconfigurable in order to easily accommodate legislation changes. Moreover, the application is transferable to a large number of similar service provision cases in the public administration domain. In light of these, the advantages of semantic web technology and its application to the e-government domain are presented.

@article{
 title = {Web based laboratory in electromagnetic compatibility using a java applet},
 type = {article},
 year = {2007},
 keywords = {Electromagnetic compatibility,Lava applets,Virtual laboratory,Web-based training},
 pages = {269-280},
 volume = {14},
 id = {d70b55d4-d2cc-3a0c-bfc5-bd3763c4745d},
 created = {2020-02-29T16:57:43.030Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.699Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007f},
 private_publication = {false},
 abstract = {A web based virtual laboratory in electromagnetic compatibility using a lava applet is presented. The Java applet makes use of Green's functions calculations inside a rectangular cavity. The induced electric fields and surface currents on cavity walls are calculated and visualized in a user-friendly manner. Various source configurations are examined. A number of laboratory exercises using the applet is given. © 2006 Wiley Periodicals, Inc.},
 bibtype = {article},
 author = {Goudos, S. K. and Samaras, T. and Sahalos, J. N.},
 doi = {10.1002/cae.20087},
 journal = {Computer Applications in Engineering Education},
 number = {4}
}

A web based virtual laboratory in electromagnetic compatibility using a lava applet is presented. The Java applet makes use of Green's functions calculations inside a rectangular cavity. The induced electric fields and surface currents on cavity walls are calculated and visualized in a user-friendly manner. Various source configurations are examined. A number of laboratory exercises using the applet is given. © 2006 Wiley Periodicals, Inc.

@article{
 title = {On the orthogonal nonuniform synthesis from a set of uniform linear arrays},
 type = {article},
 year = {2007},
 keywords = {Analog beamforming,Array synthesis,Linear array design,Orthogonal method},
 pages = {313-315},
 volume = {6},
 id = {23830dba-5cdd-3d48-bbee-59157e4a0fc8},
 created = {2020-02-29T16:57:43.626Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.082Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007e},
 private_publication = {false},
 abstract = {Synthesis of uniform linear arrays by using the orthogonal method is presented. Composing functions similar to that of Woodward-Lawson technique are used. In Woodward-Lawson technique, sampling of the desired pattern is made. In this letter, instead of sampling, the orthogonal method is applied. The number of composing functions can be the same as or different than the elements of the arrays. Also, the progressive phase of each function can be derived in several ways. Numerical examples for the synthesis of different array patterns are presented, and the results show the usefulness of the method. © 2007 IEEE.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Miaris, George S. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/LAWP.2007.899915},
 journal = {IEEE Antennas and Wireless Propagation Letters}
}

Synthesis of uniform linear arrays by using the orthogonal method is presented. Composing functions similar to that of Woodward-Lawson technique are used. In Woodward-Lawson technique, sampling of the desired pattern is made. In this letter, instead of sampling, the orthogonal method is applied. The number of composing functions can be the same as or different than the elements of the arrays. Also, the progressive phase of each function can be derived in several ways. Numerical examples for the synthesis of different array patterns are presented, and the results show the usefulness of the method. © 2007 IEEE.

@inproceedings{
 title = {Semantic interoperability conflicts in paneuropean public services},
 type = {inproceedings},
 year = {2007},
 keywords = {Cross-border services,GEA object model,Pan-European EGovernment Service,Pan-European Public Services,Semantic conflict types,Semantic gateway,Semantic interoperability},
 pages = {2173-2184},
 id = {1b1d7cd3-f29d-35ec-8906-177bff5ee866},
 created = {2020-02-29T16:57:43.650Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.739Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Peristeras2007},
 private_publication = {false},
 abstract = {This work presents ongoing research in Pan-European Public Services (PEPS) and Pan-European EGovernment Services (PEGS). This field of work is relatively new and has attracted the attention of the European Commission and of many research organizations and businesses as well. The semantic interoperability issues that may arise when a citizen of one Member State requests a public service from the public administration of another Member State are examined in this paper. The semantic conflict types that may arise in this case are identified and classified according to the Governance Enterprise Architecture (GEA) object model concepts. This conceptual modeling can be the basis for the building of a semantic gateway that will resolve these issues at a pan-European level.},
 bibtype = {inproceedings},
 author = {Peristeras, Vassilios and Loutas, Nikolaos and Goudos, Sotirios and Tarabanis, Konstantinos},
 booktitle = {Proceedings of the 15th European Conference on Information Systems, ECIS 2007}
}

This work presents ongoing research in Pan-European Public Services (PEPS) and Pan-European EGovernment Services (PEGS). This field of work is relatively new and has attracted the attention of the European Commission and of many research organizations and businesses as well. The semantic interoperability issues that may arise when a citizen of one Member State requests a public service from the public administration of another Member State are examined in this paper. The semantic conflict types that may arise in this case are identified and classified according to the Governance Enterprise Architecture (GEA) object model concepts. This conceptual modeling can be the basis for the building of a semantic gateway that will resolve these issues at a pan-European level.

@inproceedings{
 title = {Facilitating the semantic discovery of eGovernment services: The SemanticGov portal},
 type = {inproceedings},
 year = {2007},
 pages = {157-164},
 id = {db57c3fc-1708-3b3f-8a66-42da98824d82},
 created = {2020-02-29T16:57:43.692Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.290Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Loutas2007},
 private_publication = {false},
 abstract = {In this paper we propose a way to facilitate the issue of discovering the eGovernment services that address a citizen's need. This approach is implemented in an application, which we call a semantic portal. The semantic portal is part of our SemanticGov project architecture. The portal's components and its architecture are presented and explained. The portal's conceptual modeling is based on the generic public service object model of Governance Enterprise Architecture (GEA) while Web Service Modeling Ontology (WSMO) is used as the semantic web services framework for application implementation. . We describe the ontologies required using the Web Service Modeling Language (WSML). The reasoning tasks are performed accordingly using a WSML reasoner. Goals are WSMO elements that describe aspects related to user desires. The input to the application consists of information regarding the user's profile, i.e. age, marital status etc., while the output is a concrete WSMO Goal that expresses the citizen's need. This Goal is forwarded to the discovery engine, which has to discover all the services that address this Goal and return them to the citizen. ©2008 IEEE.},
 bibtype = {inproceedings},
 author = {Loutas, Nikolaos and Peristeras, Vassilios and Goudos, Sotirios K. and Tarabanis, Konstantinos},
 doi = {10.1109/EDOCW.2007.12},
 booktitle = {Proceedings - IEEE International Enterprise Distributed Object Computing Workshop, EDOC}
}

In this paper we propose a way to facilitate the issue of discovering the eGovernment services that address a citizen's need. This approach is implemented in an application, which we call a semantic portal. The semantic portal is part of our SemanticGov project architecture. The portal's components and its architecture are presented and explained. The portal's conceptual modeling is based on the generic public service object model of Governance Enterprise Architecture (GEA) while Web Service Modeling Ontology (WSMO) is used as the semantic web services framework for application implementation. . We describe the ontologies required using the Web Service Modeling Language (WSML). The reasoning tasks are performed accordingly using a WSML reasoner. Goals are WSMO elements that describe aspects related to user desires. The input to the application consists of information regarding the user's profile, i.e. age, marital status etc., while the output is a concrete WSMO Goal that expresses the citizen's need. This Goal is forwarded to the discovery engine, which has to discover all the services that address this Goal and return them to the citizen. ©2008 IEEE.

@inproceedings{
 title = {A public administration domain ontology for semantic discovery of eGovernment services},
 type = {inproceedings},
 year = {2007},
 pages = {260-265},
 volume = {1},
 id = {69a01730-97ff-32d9-a415-f4f70bbb0f1f},
 created = {2020-02-29T16:57:43.713Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.104Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007d},
 private_publication = {false},
 abstract = {In this paper we present a top level Public Administration (PA) domain ontology. For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing PA domain specific semantics. We represent this service model using the Web Ontology Language (OWL). This domain ontology may serve as the knowledge base for eGovernment semantic web applications. A sample application is presented that finds the public services that can be executed by a citizen based on his/hers profile using semantic discovery. The input to the application consists of the user profile, while the output returned consists of the public services that match the specified profile. ©2007 IEEE.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Peristeras, Vassilios and Loutas, Nikolaos and Tarabanis, Konstantinos},
 doi = {10.1109/ICDIM.2007.4444233},
 booktitle = {2007 2nd International Conference on Digital Information Management, ICDIM}
}

In this paper we present a top level Public Administration (PA) domain ontology. For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing PA domain specific semantics. We represent this service model using the Web Ontology Language (OWL). This domain ontology may serve as the knowledge base for eGovernment semantic web applications. A sample application is presented that finds the public services that can be executed by a citizen based on his/hers profile using semantic discovery. The input to the application consists of the user profile, while the output returned consists of the public services that match the specified profile. ©2007 IEEE.

@article{
 title = {Optimization of integrated circuits placement for electric field reduction inside telecommunications equipment using Monte Carlo simulation and parallel recombinative simulated annealing},
 type = {article},
 year = {2007},
 keywords = {Electromagnetic compatibility,Genetic algorithms,Green's functions calculation,Monte Carlo simulation,Parallel programming,Simulated annealing},
 pages = {3049-3055},
 volume = {49},
 id = {dfbe5cf3-aaa2-3dd7-8835-cc1dc369ce66},
 created = {2020-02-29T16:57:43.736Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.743Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007c},
 private_publication = {false},
 abstract = {This article presents a novel approach to the modeling and reduction of electromagnetic interference (EMI) caused by radiated emissions of integrated circuits (ICs) inside rectangular metallic enclosures of telecommunications devices. This type of analysis applies for several types of modern telecommunications equipment found in highspeed networks as well as in mobile communications. A generic model of such a device is created. The ICs are modeled as small electric dipoles and their interaction with the enclosure walls is studied by using the dyadic Green's functions. The electric field on the enclosure walls is computed and its reduction is studied as optimization problem using evolutionary algorithms. Two algorithms are employed: Genetic algorithms (GAs) and parallel recombinative simulated annealing (PRSA). PRSA is a hybrid evolutionary strategy that inherits properties from both GAs and simulated annealing. Monte Carlo simulation is subsequently applied to the optimization results to derive the electric field on the metallic walls and also to perform a worst-case analysis. The applications of the above approach in early PCB design process are discussed. © 2007 Wiley Periodicals, Inc.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Zaharis, Zaharias D. and Lazaridis, Pavios I. and Gallion, Philippe B.},
 doi = {10.1002/mop.22893},
 journal = {Microwave and Optical Technology Letters},
 number = {12}
}

This article presents a novel approach to the modeling and reduction of electromagnetic interference (EMI) caused by radiated emissions of integrated circuits (ICs) inside rectangular metallic enclosures of telecommunications devices. This type of analysis applies for several types of modern telecommunications equipment found in highspeed networks as well as in mobile communications. A generic model of such a device is created. The ICs are modeled as small electric dipoles and their interaction with the enclosure walls is studied by using the dyadic Green's functions. The electric field on the enclosure walls is computed and its reduction is studied as optimization problem using evolutionary algorithms. Two algorithms are employed: Genetic algorithms (GAs) and parallel recombinative simulated annealing (PRSA). PRSA is a hybrid evolutionary strategy that inherits properties from both GAs and simulated annealing. Monte Carlo simulation is subsequently applied to the optimization results to derive the electric field on the metallic walls and also to perform a worst-case analysis. The applications of the above approach in early PCB design process are discussed. © 2007 Wiley Periodicals, Inc.

@inproceedings{
 title = {Public administration domain ontology for a semantic web services E-government framework},
 type = {inproceedings},
 year = {2007},
 pages = {270-277},
 id = {07e7c817-86e2-3ecd-b179-a74d6f90a4c1},
 created = {2020-02-29T16:57:43.753Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:01.905Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007b},
 private_publication = {false},
 abstract = {In this paper we present a generic Public Administration (PA) domain ontology. We define a formal model for a Public Administration service on the basis of the Web Service Modeling Ontology (WSMO). For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing PA domain specific semantics. We describe the ontology using the Web Service Modeling Language (WSML). This domain ontology is implemented in order to be used in semantic web services architecture for e-government. © 2007 IEEE.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Loutas, Nikolaos and Peristeras, Vassilios and Tarabanis, Konstantinos},
 doi = {10.1109/SCC.2007.89},
 booktitle = {Proceedings - 2007 IEEE International Conference on Services Computing, SCC 2007}
}

In this paper we present a generic Public Administration (PA) domain ontology. We define a formal model for a Public Administration service on the basis of the Web Service Modeling Ontology (WSMO). For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing PA domain specific semantics. We describe the ontology using the Web Service Modeling Language (WSML). This domain ontology is implemented in order to be used in semantic web services architecture for e-government. © 2007 IEEE.

@inproceedings{
 title = {Dynamic workflow generation with semantic web services: A case study in public administration service provision},
 type = {inproceedings},
 year = {2007},
 keywords = {BPEL4WS,Dynamic workflow generation,OWL-S,Public service provision,Semantic Web Services,UDDI},
 pages = {121-130},
 id = {afc72d38-bb72-3608-88eb-9c04f1cf1155},
 created = {2020-02-29T16:57:44.317Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.387Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007a},
 private_publication = {false},
 abstract = {In this paper we present an automated workflow service composition framework for the Public Administration (PA) domain. We define a conceptual model for a Public Administration service workflow. This model can be implemented using existing web service technologies. In the PA domain complex services exist that require inputs evaluated from other services. Such a nested service type can be implemented using an automatic web service workflow composition. Semantic service discovery, which is based on service inputs and outputs, is also used. The final result is the complete service workflow that can be executed in any web service process engine. Our approach is based on a semantically enriched UDDI registry and an automated workflow composition of complex services. A real-life example of our framework is given for a complex Public Administration service in Greece.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios and Peristeras, Vassilios and Tektonidis, Dimitrios and Tambouris, Efthimios and Tarabanis, Konstantinos},
 booktitle = {ICEG 2007 - 3rd International Conference on e-Government}
}

In this paper we present an automated workflow service composition framework for the Public Administration (PA) domain. We define a conceptual model for a Public Administration service workflow. This model can be implemented using existing web service technologies. In the PA domain complex services exist that require inputs evaluated from other services. Such a nested service type can be implemented using an automatic web service workflow composition. Semantic service discovery, which is based on service inputs and outputs, is also used. The final result is the complete service workflow that can be executed in any web service process engine. Our approach is based on a semantically enriched UDDI registry and an automated workflow composition of complex services. A real-life example of our framework is given for a complex Public Administration service in Greece.

@article{
 title = {Dielectric filter optimal design suitable for microwave communications by using multiobjective evolutionary algorithms},
 type = {article},
 year = {2007},
 keywords = {Dielectric filters,Evolutionary programming,Genetic algorithms,Microwave filters,Mutltiobjective optimization,Pareto optimization,Particle swarm optimization},
 pages = {2324-2329},
 volume = {49},
 id = {770ad387-f475-378e-8412-d867b856ff74},
 created = {2020-02-29T16:57:44.756Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.892Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2007},
 private_publication = {false},
 abstract = {A multiobjective evolutionary technique is applied to design dielectric filters useful in microwave communications technology. The optimal geometry of the filters is derived by utilizing two different multiobjective optimization algorithms. The first one is the Nondominated Sorting Genetic Algorithm-II (NSGA-II). which is a popular multiobjective genetic algorithm. The second algorithm is based tin multiobjective Particle Swarm Optimization with fitness sharing (MOPSO-fs). MOPSO-fs algorithm is a novel Pareto PSO algorithm that produces the Pareto front in a fast and efficient way. In the present work, MOPSO-fs is compared with NSGA-II to optimize the geometry of the filters under specific requirements concerning the frequency response of the filters. Several examples are studied to exhibit the efficiency of the multiobjective evolutionary optimizers and also the ability of the technique to derive optimal structures that can be used in practice. © 2007 Wiley Periodicals. Inc.},
 bibtype = {article},
 author = {Goudos, S. K. and Zaharis, Z. D. and Salazar-Lechuga, M. and Lazaridis, P. I. and Gallion, P. B.},
 doi = {10.1002/mop.22755},
 journal = {Microwave and Optical Technology Letters},
 number = {10}
}

A multiobjective evolutionary technique is applied to design dielectric filters useful in microwave communications technology. The optimal geometry of the filters is derived by utilizing two different multiobjective optimization algorithms. The first one is the Nondominated Sorting Genetic Algorithm-II (NSGA-II). which is a popular multiobjective genetic algorithm. The second algorithm is based tin multiobjective Particle Swarm Optimization with fitness sharing (MOPSO-fs). MOPSO-fs algorithm is a novel Pareto PSO algorithm that produces the Pareto front in a fast and efficient way. In the present work, MOPSO-fs is compared with NSGA-II to optimize the geometry of the filters under specific requirements concerning the frequency response of the filters. Several examples are studied to exhibit the efficiency of the multiobjective evolutionary optimizers and also the ability of the technique to derive optimal structures that can be used in practice. © 2007 Wiley Periodicals. Inc.

@inproceedings{
 title = {WSMO-PA: Formal specification of public administration service model on semantic web service ontology},
 type = {inproceedings},
 year = {2007},
 id = {e38fa0e3-441a-3fd7-bf87-36dcef46761a},
 created = {2020-02-29T16:57:45.135Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.062Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Xia2007},
 private_publication = {false},
 abstract = {In this paper we define a formal model for a Public Administration service on the basis of the Web Service Modeling Ontology (WSMO). For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing a PA domain specific semantics. We investigate conceptual mappings between PA entities and WSMO elements, and on the real-world use case present the detailed formal PA service model based on the WSMO service model. © 2007 IEEE.},
 bibtype = {inproceedings},
 author = {Xia, Wang and Vitvar, Tomas and Peristeras, Vassilios and Mocan, Adrian and Goudos, Sotirios K. and Tarabanis, Konstantinos},
 doi = {10.1109/HICSS.2007.618},
 booktitle = {Proceedings of the Annual Hawaii International Conference on System Sciences}
}

In this paper we define a formal model for a Public Administration service on the basis of the Web Service Modeling Ontology (WSMO). For this purpose we employ the generic public service object model of the Governance Enterprise Architecture (GEA) providing a PA domain specific semantics. We investigate conceptual mappings between PA entities and WSMO elements, and on the real-world use case present the detailed formal PA service model based on the WSMO service model. © 2007 IEEE.

@inproceedings{
 title = {A public administration reference domain ontology in the web service modeling language},
 type = {inproceedings},
 year = {2007},
 pages = {238-239},
 volume = {228},
 websites = {http://dl.acm.org/citation.cfm?id=1248498},
 publisher = {Digital Government Research Center},
 series = {ACM International Conference Proceeding Series},
 id = {529deb69-600a-329b-8a81-6915ea315868},
 created = {2023-02-11T21:08:08.952Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:08.952Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {DBLP:conf/dgo/LoutasGPT07},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Loutas, Nikos and Goudos, Sotirios K and Peristeras, Vassilios and Tarabanis, Konstantinos A},
 editor = {Cushing, Judith Bayard and Pardo, Theresa A},
 booktitle = {Proceedings of the 8th Annual International Conference on Digital Government Research, Bridging Disciplines \& Domains, DG.O 2007, Philadelphia, Pennsylvania, USA, May 20-23, 2007}
}

@inproceedings{
 title = {A Distributed Enterprise Information System for Cross-Border eGovernment Service Provision},
 type = {inproceedings},
 year = {2007},
 pages = {264-268},
 publisher = {CSREA Press},
 id = {7dc699a5-8485-308c-8713-395f52c1b551},
 created = {2023-02-11T21:08:09.223Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.223Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {DBLP:conf/csreaEEE/TambourisPGT07},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Tambouris, Efthimios and Peristeras, Vassilios and Goudos, Sotirios K and Tarabanis, Konstantinos A},
 editor = {Arabnia, Hamid R and Bahrami, Azita},
 booktitle = {Proceedings of the 2007 International Conference on E-Learning, E-Business, Enterprise Information Systems, and E-Government, EEE 2007, June 25-28, 2007, Las Vegas, Nevada, USA}
}

@article{
 title = {Calculation and modeling of EMI from integrated circuits inside high-speed network devices},
 type = {article},
 year = {2006},
 keywords = {Electromagnetic interference,Monte carlo simulation,Numerical techniques,Printed circuit board design},
 pages = {2-8},
 volume = {15},
 id = {9e8609c9-ebd9-3c1a-a125-7c5bd2f09235},
 created = {2020-02-29T16:57:41.854Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.100Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2006b},
 private_publication = {false},
 abstract = {This work presents a numerical approach to the modeling of Electromagnetic Interference (EMI) from the emissions of ICs and PCBs inside rectangular metallic enclosures of network devices. The ICs are modeled as small magnetic and electric dipoles. Their interaction with the enclosures is studied with the dyadic Green's functions. Several calculation examples of surface current density on the metallic walls are given due to dipoles parallel to all directions. A Probabilistic Model is created from magnetic probe measurements in various types of router devices. Monte Carlo simulation is applied in order to perform a worst-case analysis. The applications of the above ap-proach in PCB design are discussed.},
 bibtype = {article},
 author = {Goudos, Sotirios K.},
 journal = {Radioengineering},
 number = {4}
}

This work presents a numerical approach to the modeling of Electromagnetic Interference (EMI) from the emissions of ICs and PCBs inside rectangular metallic enclosures of network devices. The ICs are modeled as small magnetic and electric dipoles. Their interaction with the enclosures is studied with the dyadic Green's functions. Several calculation examples of surface current density on the metallic walls are given due to dipoles parallel to all directions. A Probabilistic Model is created from magnetic probe measurements in various types of router devices. Monte Carlo simulation is applied in order to perform a worst-case analysis. The applications of the above ap-proach in PCB design are discussed.

@article{
 title = {Microwave absorber optimal design using multi-objective particle swarm optimization},
 type = {article},
 year = {2006},
 keywords = {Microwave absorber design,Multiobjective optimization,Multiobjective particle swarm optimization,Pareto optimization,Particle swarm optimization},
 pages = {1553-1558},
 volume = {48},
 id = {f7b67208-da08-3a92-aef7-0499c79768b3},
 created = {2020-02-29T16:57:42.168Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.767Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2006a},
 private_publication = {false},
 abstract = {The design of planar multilayer coatings with high absorption for a desired range of frequencies and angles is presented. The design technique is based on multiobjective particle swarm optimization (MOPSO). Particle swarm optimization (PSO) is an evolutionary optimization algorithm based on bird flight. Multiobjective PSO (MOPSO) is a Pareto PSO algorithm which produces the Pareto front fast and efficiently. MOPSO is used for several design cases and is compared with multiobjective genetic algorithms. Numerical results that are also compared with those existing in the literature show the advantages of this approach and the applicability of this design method. © 2006 Wiley Periodicals, Inc.},
 bibtype = {article},
 author = {Goudos, S. K. and Sahalos, J. N.},
 doi = {10.1002/mop.21727},
 journal = {Microwave and Optical Technology Letters},
 number = {8}
}

The design of planar multilayer coatings with high absorption for a desired range of frequencies and angles is presented. The design technique is based on multiobjective particle swarm optimization (MOPSO). Particle swarm optimization (PSO) is an evolutionary optimization algorithm based on bird flight. Multiobjective PSO (MOPSO) is a Pareto PSO algorithm which produces the Pareto front fast and efficiently. MOPSO is used for several design cases and is compared with multiobjective genetic algorithms. Numerical results that are also compared with those existing in the literature show the advantages of this approach and the applicability of this design method. © 2006 Wiley Periodicals, Inc.

@inproceedings{
 title = {A semantic web application for matching a citizen's profile to entitled public services},
 type = {inproceedings},
 year = {2006},
 keywords = {Matching profiles,OWL,Public administration,Semantic web},
 pages = {90-98},
 id = {e4be3a87-428d-3ae6-8ecb-f838386ad0bd},
 created = {2020-02-29T16:57:42.585Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.004Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2006},
 private_publication = {false},
 abstract = {This paper contributes to the more general problem of supplying the citizen with the correct information from the public administration in a quick and easy way. Specifically, getting the information about all the benefits that someone is entitled of is a very complex task in many countries. To address this problem, a domain ontology is first created in OWL (Web Ontology Language). The ontology is used as the knowledge base for a semantic application that uses a reasoner. This latter queries the knowledge base through a web interface by receiving the user's profile as input, and providing the benefits that match to the specified profile as output. A list of the required documents and the procedure for receiving the various benefits from the appropriate service provider is also returned. In this way, a complex procedure is simplified and a serious overload on the client's side (being business or citizen). is relaxed The application is highly reconfigurable in order to e.g. easily accommodate legislation changes. It accommodates law changes by ontology modifications. Moreover, the application is transferable to a large number of similar service provision cases in the public administration domain. In light of these, the advantages of semantic web technology and their application to the e-government domain are discussed.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios and Peristeras, Vassilios and Tarabanis, Konstantinos},
 booktitle = {ICEG 2006 - 2nd International Conference on e-Government}
}

This paper contributes to the more general problem of supplying the citizen with the correct information from the public administration in a quick and easy way. Specifically, getting the information about all the benefits that someone is entitled of is a very complex task in many countries. To address this problem, a domain ontology is first created in OWL (Web Ontology Language). The ontology is used as the knowledge base for a semantic application that uses a reasoner. This latter queries the knowledge base through a web interface by receiving the user's profile as input, and providing the benefits that match to the specified profile as output. A list of the required documents and the procedure for receiving the various benefits from the appropriate service provider is also returned. In this way, a complex procedure is simplified and a serious overload on the client's side (being business or citizen). is relaxed The application is highly reconfigurable in order to e.g. easily accommodate legislation changes. It accommodates law changes by ontology modifications. Moreover, the application is transferable to a large number of similar service provision cases in the public administration domain. In light of these, the advantages of semantic web technology and their application to the e-government domain are discussed.

@article{
 title = {Seasonal decomposition and forecasting of telecommunication data: A comparative case study},
 type = {article},
 year = {2006},
 keywords = {Call data pattern recognition,Forecast evaluation,Model selection,Seasonal adjustment,Time series},
 pages = {495-509},
 volume = {73},
 id = {7fa58d5e-5622-36fd-b989-a5965df6cd25},
 created = {2020-02-29T16:57:43.049Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:08:48.917Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Hilas2006},
 private_publication = {false},
 abstract = {In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University. © 2005 Elsevier Inc. All rights reserved.},
 bibtype = {article},
 author = {Hilas, Constantinos S. and Goudos, Sotirios K. and Sahalos, John N.},
 doi = {10.1016/j.techfore.2005.07.002},
 journal = {Technological Forecasting and Social Change},
 number = {5}
}

In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University. © 2005 Elsevier Inc. All rights reserved.

@article{
 title = {On the base stations antenna system design for mobile communications},
 type = {article},
 year = {2006},
 keywords = {Base station antennas,Beam forming,Beam tilting,Mobile communications,Orthogonal method},
 pages = {157-163},
 volume = {88},
 id = {dccaba78-404c-3e28-b9d0-810c40319881},
 created = {2020-02-29T16:57:45.174Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.058Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Miaris2006},
 private_publication = {false},
 abstract = {The design of a base station antenna for mobile communications is presented. The orthogonal method (OM) is applied under constraints on nulls of the radiation pattern. In the synthesis process the mutual coupling between the elements of the antenna array could be taken into account. Beam tilting and direction of arrival are also considered. The whole design is completed by implementing a special architecture of the antenna. Finally, some examples show the applicability of our technique.},
 bibtype = {article},
 author = {Miaris, George S. and Siachalou, Eleftheria and Samaras, Theodoros and Goudos, Sotirios K. and Vafiadis, Elias and Panas, Stavros},
 doi = {10.1007/s00202-004-0267-x},
 journal = {Electrical Engineering},
 number = {2}
}

The design of a base station antenna for mobile communications is presented. The orthogonal method (OM) is applied under constraints on nulls of the radiation pattern. In the synthesis process the mutual coupling between the elements of the antenna array could be taken into account. Beam tilting and direction of arrival are also considered. The whole design is completed by implementing a special architecture of the antenna. Finally, some examples show the applicability of our technique.

@inproceedings{
 title = {Towards Semantic Web Services for Public Administration based on the Web Service Modeling Ontology (WSMO) and the Governance Enterprise Architecture (GEA)},
 type = {inproceedings},
 year = {2006},
 pages = {155-162},
 id = {e99ddc6e-3111-34c0-a253-ec5a33d859e7},
 created = {2023-02-11T21:08:09.087Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.087Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {peristeras2006towards},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Peristeras, Vassilios and Mocan, Adrian and Vitvar, Tomas and Nazir, Sanullah and Goudos, Sotirios and Tarabanis, Konstantinos},
 booktitle = {Proceedings of International EGOV Conference 2006 (DEXA), Poland, Trauner Verlag, Electronic Government}
}

@inproceedings{
 title = {EMI from ICs and PCBs inside High Speed Networking Equipment,},
 type = {inproceedings},
 year = {2006},
 pages = {437-442},
 id = {4c48b9ef-dfca-3471-af9a-b626915e5ac9},
 created = {2023-02-11T21:08:09.206Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.206Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2006emi},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, S K and Hilas, C S and Rekanos, J and Sahalos, J N},
 booktitle = {EMC Europe 2006 International Symposium on Electromagnetic Compatibility}
}

@inproceedings{
 title = {Mapping Citizen Profiles to Public Administration Services Using Ontology Implementations of the Governance Enterprise Architecture (GEA) models},
 type = {inproceedings},
 year = {2006},
 pages = {25-37},
 id = {4930e682-5284-39d2-9f3e-fa795c98a0d9},
 created = {2023-02-11T21:08:09.214Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.214Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2006mapping},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Peristeras, Vassilios and Tarabanis, Konstantinos},
 booktitle = {Proceedings of 3rd Annual European Semantic Web Conference}
}

@inproceedings{
 title = {A Framework of Public Administration Domain Data Interoperability Using Semantic Web Technology},
 type = {inproceedings},
 year = {2006},
 id = {b4519eca-d22f-372b-83f1-ac28dbd159dd},
 created = {2023-02-11T21:08:09.217Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.217Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2006framework},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K and Peristeras, Vassileios and Tarabanis, Konstantinos},
 booktitle = {Proceedings of Interoperability for Enterprise Software and Applications Conference 2006 (I-ESA 06), Bordeaux, France}
}

@inproceedings{
 title = {Design of Broadband Radar Absorbing Materials using Particle Swarm Optimization},
 type = {inproceedings},
 year = {2006},
 pages = {1111-1116},
 id = {05bd3161-62a0-3fde-bbcd-d1726ea4be80},
 created = {2023-02-11T21:08:09.219Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:08:09.219Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2006design},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, S K and Sahalos, J N},
 booktitle = {EMC Europe 2006 International Symposium on Electromagnetic Compatibility}
}

@article{
 title = {A test lab for the performance analysis of TCP over ethernet LAN on windows operating system},
 type = {article},
 year = {2005},
 keywords = {Benchmarking,Computer networks,IPv6,Network performance,Network traffic,Throughput,Transmission control protocol/internet protocol (T},
 pages = {318-328},
 volume = {48},
 id = {895c9b97-e746-3a3f-a8e7-47390a0f3175},
 created = {2020-02-29T16:57:43.073Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.714Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Gotsis2005},
 private_publication = {false},
 abstract = {A test laboratory for the performance analysis of the Transmission Control Protocol (TCP) and the teaching of its basic concepts is proposed. The laboratory environment is a small Ethernet local area network (LAN) with PCs running different versions of the Windows operating system (95/98/NT/2000). To support the Internet Protocol Version 6 (IPv6) for Windows and to improve flexibility, the Netperf TCP software tool has been modified. Based on the modified Netperf and a protocol analyzer, students perform traffic measurements on a real network. Various aspects of the Microsoft TCP implementation for Windows are discovered and clearly explained. The IPv6 for Windows 2000 is also examined, and comparisons with IPv4 are made. © 2005 IEEE.},
 bibtype = {article},
 author = {Gotsis, Konstantinos A. and Goudos, Sotirios K. and Sahalos, John N.},
 doi = {10.1109/TE.2004.842897},
 journal = {IEEE Transactions on Education},
 number = {2}
}

A test laboratory for the performance analysis of the Transmission Control Protocol (TCP) and the teaching of its basic concepts is proposed. The laboratory environment is a small Ethernet local area network (LAN) with PCs running different versions of the Windows operating system (95/98/NT/2000). To support the Internet Protocol Version 6 (IPv6) for Windows and to improve flexibility, the Netperf TCP software tool has been modified. Based on the modified Netperf and a protocol analyzer, students perform traffic measurements on a real network. Various aspects of the Microsoft TCP implementation for Windows are discovered and clearly explained. The IPv6 for Windows 2000 is also examined, and comparisons with IPv4 are made. © 2005 IEEE.

@article{
 title = {Wireless corner: On mobile communications smart base-station system design},
 type = {article},
 year = {2005},
 keywords = {Antenna arrays,Direction of arrival estimation,Land mobile radio cellular systems,Land mobile radio equipment,Microstrip arrays,Shaped beam antennas,Smart antennas},
 pages = {139-144},
 volume = {47},
 id = {373273e7-3f54-38e8-baf8-d92038009db4},
 created = {2020-02-29T16:57:45.217Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.526Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Miaris2005},
 private_publication = {false},
 abstract = {A design technique for mobile base-station antennas is presented. Beam tilting to avoid intersymbol interference is considered, and the orthogonal method (OM) under constraints on the radiation pattern is applied. The adaptive architecture of the mobile system, in conjunction with the direction of arrival (DoA) and the least mean square algorithms, is explained. A set of useful examples shows the applicability of the whole design.},
 bibtype = {article},
 author = {Miaris, George and Siachalou, Eleftheria and Samaras, Theodoros and Goudos, Sotirios and Vafiadis, Elias and Panas, Stavros},
 doi = {10.1109/MAP.2005.1487814},
 journal = {IEEE Antennas and Propagation Magazine},
 number = {2}
}

A design technique for mobile base-station antennas is presented. Beam tilting to avoid intersymbol interference is considered, and the orthogonal method (OM) under constraints on the radiation pattern is applied. The adaptive architecture of the mobile system, in conjunction with the direction of arrival (DoA) and the least mean square algorithms, is explained. A set of useful examples shows the applicability of the whole design.

@article{
 title = {Orthosynthesis : On the Beamforming from a set of Uniform Linear Arrays by the Orthogonal Method},
 type = {article},
 year = {2005},
 pages = {9-12},
 volume = {7},
 id = {26d98767-94c6-3e5b-834c-eb48d5292132},
 created = {2020-03-03T08:46:35.487Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:43.614Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Margaritis2005},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Margaritis, H and Goudos, S and Miaris, G S and Samaras, T and Sahalos, J N},
 journal = {Journal of Applied Electromagnetism}
}

@article{
 title = {On the design of switched-beam wideband base stations},
 type = {article},
 year = {2004},
 keywords = {Adaptive arrays,Broadband communication,Butler matrix,Land mobile radio cellular systems,Land mobile radio equipment,Signal processing antennas,Smart antennas,Wireless networks},
 pages = {158-167},
 volume = {46},
 id = {57772e47-3156-3a12-a6ee-86b360ede08b},
 created = {2020-02-29T16:57:45.180Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:05.256Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Siachalou2004},
 private_publication = {false},
 abstract = {A switched-beam base-station antenna is presented. The antenna is an improvement on the Butler matrix. The input ports of the antenna are excited with equal or unequal amplitudes. The feed network is analyzed and presented in a simple manner. The antenna comprises the main part of a base station, and is useful for broadband communications. The architecture of the base station is described, and the services that can be provided are given. Finally, comments are made about the tradeoffs and benefits of the antenna is comparison to the classical Butler-matrix switched-beam and adaptive arrays.},
 bibtype = {article},
 author = {Siachalou, Eleftheria and Vafiadis, Elias and Goudos, Sotirios S. and Samaras, Theodoros and Koukourlis, Christos S. and Panas, Stavros},
 doi = {10.1109/MAP.2004.1296180},
 journal = {IEEE Antennas and Propagation Magazine},
 number = {1}
}

A switched-beam base-station antenna is presented. The antenna is an improvement on the Butler matrix. The input ports of the antenna are excited with equal or unequal amplitudes. The feed network is analyzed and presented in a simple manner. The antenna comprises the main part of a base station, and is useful for broadband communications. The architecture of the base station is described, and the services that can be provided are given. Finally, comments are made about the tradeoffs and benefits of the antenna is comparison to the classical Butler-matrix switched-beam and adaptive arrays.

@inproceedings{
 title = {A Computer tool for EM planar absorber design},
 type = {inproceedings},
 year = {2004},
 id = {3132818a-d8df-3447-b0c4-f542a616d20c},
 created = {2023-02-11T21:03:57.133Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:03:57.133Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2004computer},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, S K and Samaras, T and Sahalos, J N},
 booktitle = {EMC Europe 2004 International Symposium on Electromagnetic Compatibility, Eindhoven}
}

@inproceedings{
 title = {Web-based visualization of electric fields and currents inside a rectangular cavity},
 type = {inproceedings},
 year = {2004},
 id = {bf46b164-2a9b-311c-b1f3-f772d14d9d62},
 created = {2023-02-11T21:03:57.290Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:03:57.290Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2004webbased},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, S K and Samaras, T and Sahalos, J N},
 booktitle = {EMC Europe 2004 International Symposium on Electromagnetic Compatibility, Eindhoven}
}

@inproceedings{
 title = {Numerical approaches for EMI reduction of ICs and PCBs inside metallic enclosures},
 type = {inproceedings},
 year = {2003},
 pages = {513-516 Vol.1},
 websites = {%3CGo},
 publisher = {Ieee},
 id = {6f8c8659-6591-33c8-aff3-a790477b08f9},
 created = {2020-03-03T08:46:35.431Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T20:59:41.564Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2003},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work presents a numerical approach to the reduction of Electromagnetic Interference (EMI) from the emissions of 1Cs and PCBs inside rectangular metallic enclosures. The ICs are modeled as small magnetic dipoles. Their interaction with the enclosures is studied with the dyadic Green's functions. The Monte Carlo procedure in conjunction with optimization techniques is used in order to achieve optimal placement configurations for the ICs. by minimizing the electric current density on the metallic walls. The applications of the above approach in PCB design are discussed.},
 bibtype = {inproceedings},
 author = {Goudos, S and Samaras, T and Vafiadis, E and Sahalos, J.N.},
 doi = {10.1109/icsmc2.2003.1428305},
 booktitle = {IEEE International Symposium on Electromagnetic Compatibility (EMC)}
}

This work presents a numerical approach to the reduction of Electromagnetic Interference (EMI) from the emissions of 1Cs and PCBs inside rectangular metallic enclosures. The ICs are modeled as small magnetic dipoles. Their interaction with the enclosures is studied with the dyadic Green's functions. The Monte Carlo procedure in conjunction with optimization techniques is used in order to achieve optimal placement configurations for the ICs. by minimizing the electric current density on the metallic walls. The applications of the above approach in PCB design are discussed.

@article{
 title = {Monte Carlo simulation for the prediction of the emission level from multiple sources inside shielded enclosures},
 type = {article},
 year = {2002},
 keywords = {EMC,EMI,Electrical equipment enclosures,Green's function,Monte Carlo methods,PCB design,Simulated annealing},
 volume = {44},
 id = {50b091ed-dbae-3bd1-b5c1-f6f930d7e620},
 created = {2020-02-29T16:57:43.100Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:45.679Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Goudos2002},
 private_publication = {false},
 abstract = {The emission level from multiple sources inside shielded enclosures is presented. Fields are expressed through the dyadic Green's function. Integrated circuits are modeled as electric and magnetic dipoles. Induced electric current magnitudes on the walls of the enclosures are analytically calculated. Probabilistic models based on measurement data for various source configurations are derived and Monte Carlo simulations are produced. The results are used for the prediction of possible emission margins. Applications in PCB design are discussed and suggestions are made.},
 bibtype = {article},
 author = {Goudos, S.K. and Vafiadis, E.E. and Sahalos, J.N.},
 doi = {10.1109/TEMC.2002.1003394},
 journal = {IEEE Transactions on Electromagnetic Compatibility},
 number = {2}
}

The emission level from multiple sources inside shielded enclosures is presented. Fields are expressed through the dyadic Green's function. Integrated circuits are modeled as electric and magnetic dipoles. Induced electric current magnitudes on the walls of the enclosures are analytically calculated. Probabilistic models based on measurement data for various source configurations are derived and Monte Carlo simulations are produced. The results are used for the prediction of possible emission margins. Applications in PCB design are discussed and suggestions are made.

@article{
 title = {Direct solution and Monte Carlo simulation of the inverse problem in two-layered half-space},
 type = {article},
 year = {2002},
 volume = {84},
 id = {32c730f7-c453-3b61-8065-91dabbeff668},
 created = {2020-02-29T16:57:43.128Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:46.431Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Mertzanides2002},
 private_publication = {false},
 abstract = {A direct method is developed for determining the dielectric properties and thickness of lossy two-layered media. The technique is based on the study of the frequency response of the complex reflection coefficient. The frequency span must contain at least two adjacent extreme values of the real part of the input impedance. Monte Carlo simulations were produced in order to test the accuracy of the method. Applications in hydrology, engineering and environmental geology are discussed.},
 bibtype = {article},
 author = {Mertzanides, I.C. and Goudos, S.K. and Sahalos, J.N.},
 doi = {10.1007/s002020100081},
 journal = {Electrical Engineering},
 number = {1}
}

A direct method is developed for determining the dielectric properties and thickness of lossy two-layered media. The technique is based on the study of the frequency response of the complex reflection coefficient. The frequency span must contain at least two adjacent extreme values of the real part of the input impedance. Monte Carlo simulations were produced in order to test the accuracy of the method. Applications in hydrology, engineering and environmental geology are discussed.

@article{
 title = {Orthogonal advanced methods for antennas: The ORAMA computer tool},
 type = {article},
 year = {2002},
 keywords = {Antenna arrays,Antenna radiation patterns,Linear arrays},
 volume = {44},
 id = {bd2db0ca-da23-397e-9501-479082fc6386},
 created = {2020-02-29T16:57:44.772Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2022-05-12T20:32:47.232Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Miaris2002},
 private_publication = {false},
 abstract = {A computer tool (ORAMA) for the synthesis of linear antenna arrays is presented. The Orthogonal Method (OM) and the Orthogonal Perturbation (OP) Method are used. The Orthogonal Method derives the excitations of the elements of the array, while the Orthogonal Perturbation Method quantizes the excitation and determines the position of the elements. The user has the options to select the array geometry, the case study for a specific desired pattern, the method to be used, and the element type. Several design cases with various constraints are presented. ORAMA [a demo of the software is available at http://rcl.physics.auth.gr] has been designed as a Windows MDI application for the academic classroom, as well as for professional antenna engineers. A set of examples for different array patterns shows the usefulness of the tool.},
 bibtype = {article},
 author = {Miaris, G.S. and Goudos, S.K. and Lakovidis, Chr. and Vafiadis, E. and Sahalos, J.N.},
 doi = {10.1109/MAP.2002.1077777},
 journal = {IEEE Antennas and Propagation Magazine},
 number = {5}
}

A computer tool (ORAMA) for the synthesis of linear antenna arrays is presented. The Orthogonal Method (OM) and the Orthogonal Perturbation (OP) Method are used. The Orthogonal Method derives the excitations of the elements of the array, while the Orthogonal Perturbation Method quantizes the excitation and determines the position of the elements. The user has the options to select the array geometry, the case study for a specific desired pattern, the method to be used, and the element type. Several design cases with various constraints are presented. ORAMA [a demo of the software is available at http://rcl.physics.auth.gr] has been designed as a Windows MDI application for the academic classroom, as well as for professional antenna engineers. A set of examples for different array patterns shows the usefulness of the tool.

@inproceedings{
 title = {Orthosynthesis: On the Beamforming from a set of Uniform Linear Arrays by the Orthogonal Method},
 type = {inproceedings},
 year = {2002},
 id = {d3f287a7-3f68-30cb-93cc-f74c088bb68f},
 created = {2023-02-11T21:03:57.096Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:03:57.096Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {margaritis2002orthosynthesis},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Margaritis, H and Goudos, S K and Miaris, G S and Sahalos, J N},
 booktitle = {URSI 2002 General Assembly, Session B8}
}

@inproceedings{
 title = {Placement of ICs on PCBs inside Rectangular Enclosures using Stochastic and Optimization Approaches},
 type = {inproceedings},
 year = {2002},
 id = {916af0fb-851b-3d49-b51f-da04688ed9b2},
 created = {2023-02-11T21:03:57.294Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T21:03:57.294Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {goudos2002placement},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Goudos, S K and Samaras, T and Vafiadis, E and Sahalos, J N},
 booktitle = {URSI 2002 General Assembly, Session E6}
}

@article{
 title = {On the quantized excitation and the geometry synthesis of a linear array by the orthogonal method},
 type = {article},
 year = {2001},
 keywords = {Antenna arrays,Antenna radiation patterns,Antenna theory},
 pages = {298-303},
 volume = {49},
 id = {17f005ba-22ff-3d48-b815-e92e728aa48b},
 created = {2020-02-29T16:57:43.162Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:04.061Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2001},
 private_publication = {false},
 abstract = {A method for the geometry synthesis of a linear array is presented. We start from an initial array with quantized amplitudes. After this, we perturb the element positions by combining an iterative technique with the orthogonal method. The final position of the elements is found from the last iteration where the desired approximation of the pattern is obtained. Arrays with more constraints on the pattern need more quantized amplitudes. Several examples for different cases show the applicability of our method.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Miaris, George S. and Sahalos, John N.},
 doi = {10.1109/8.914297},
 journal = {IEEE Transactions on Antennas and Propagation},
 number = {2}
}

A method for the geometry synthesis of a linear array is presented. We start from an initial array with quantized amplitudes. After this, we perturb the element positions by combining an iterative technique with the orthogonal method. The final position of the elements is found from the last iteration where the desired approximation of the pattern is obtained. Arrays with more constraints on the pattern need more quantized amplitudes. Several examples for different cases show the applicability of our method.