@article{
 title = {Static Analysis and Design of a Flight Control with Oleopneumatic Centering for a Sidestick CPT/FO in A320 Simulators},
 type = {article},
 year = {2025},
 volume = {12},
 websites = {https://www.iieta.org/journals/mmep/paper/10.18280/mmep.120301},
 month = {3},
 day = {31},
 id = {f06c5662-c784-3f57-b2a8-19eaea157bcc},
 created = {2025-07-22T03:20:59.801Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2025-07-22T03:20:59.801Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {Cordovés-García, Alexis and Palacios-Luna, José Luís and Paredes-Loor, Raúl Vicente and Cordovés-Rodríguez, Alexis and Lorente-Leyva, Leandro L},
 doi = {10.18280/mmep.120301},
 journal = {Mathematical Modelling of Engineering Problems},
 number = {3}
}

@article{
 title = {Automation of Filter Press Drive Control for Enhanced Palm Oil Extraction},
 type = {article},
 year = {2025},
 pages = {121-126},
 volume = {58},
 websites = {https://iieta.org/journals/jesa/paper/10.18280/jesa.580114},
 month = {1},
 day = {31},
 id = {304c27fd-dfc1-3349-a3e7-67597c476908},
 created = {2025-07-22T03:20:59.841Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2025-07-22T03:20:59.841Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {García, Alexis Cordovés and Orellana, Agustín Moreira and Rodríguez, Alexis Cordovés and Rondon, Ricardo Avila and Lorente-Leyva, Leandro L},
 doi = {10.18280/jesa.580114},
 journal = {Journal Européen des Systèmes Automatisés},
 number = {01}
}

@inbook{
 type = {inbook},
 year = {2025},
 pages = {16-22},
 websites = {https://link.springer.com/10.1007/978-3-031-82334-3_4},
 publisher = {Springer Nature Switzerland},
 city = {Cham},
 id = {6fe07244-0905-30e1-8a3d-ac208a336fc1},
 created = {2025-07-22T03:20:59.904Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2025-07-22T03:20:59.904Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-3-031-82334-3_4},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This study provides a comprehensive overview of the current state of research in the design and operations planning optimization of textile supply chains. This paper includes a bibliometric analysis of 42 selected papers that reveals a focus on tactical decision-making, with an emphasis on the manufacturing stage. The bibliometric analysis exposes the influence of prominent authors and journals in this field. A co-occurrence map graphically represents the keywords used in the papers. The literature review results suggest that models are primarily developed in a deterministic context, with a focus on cost minimization and limited use of artificial intelligence techniques. The solution context exhibits a preference for static approaches and periodic replanning.},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro L and Alemany, María del Mar Eva and Peluffo-Ordóñez, Diego H},
 editor = {Carrasco-Gallego, Ruth and Moreno-Serna, Jaime and Gutierrez, Miguel and Avilés-Palacios, Carmen},
 doi = {10.1007/978-3-031-82334-3_4},
 chapter = {Optimization of Textile SCs Design and Planning: A Bibliometric Analysis},
 title = {Organizational Engineering, Coping with Complexity}
}

This study provides a comprehensive overview of the current state of research in the design and operations planning optimization of textile supply chains. This paper includes a bibliometric analysis of 42 selected papers that reveals a focus on tactical decision-making, with an emphasis on the manufacturing stage. The bibliometric analysis exposes the influence of prominent authors and journals in this field. A co-occurrence map graphically represents the keywords used in the papers. The literature review results suggest that models are primarily developed in a deterministic context, with a focus on cost minimization and limited use of artificial intelligence techniques. The solution context exhibits a preference for static approaches and periodic replanning.

@article{
 title = {A conceptual framework for the operations planning of the textile supply chains: Insights for sustainable and smart planning in uncertain and dynamic contexts},
 type = {article},
 year = {2024},
 keywords = {Conceptual framework,Industry 4.0,Literature review,Sustainable, smart and dynamic operations planning,Textile industry,Uncertainty,smart and dynamic operations planning},
 pages = {109824},
 volume = {187},
 websites = {https://www.sciencedirect.com/science/article/pii/S0360835223008483,https://linkinghub.elsevier.com/retrieve/pii/S0360835223008483},
 month = {1},
 id = {06e653ea-b63c-3db9-be09-fc23e78b4fb6},
 created = {2024-02-17T05:20:23.416Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2024-12-03T03:34:35.055Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic dimension, but fundamentally in its environmental and social ones. One of the key management processes that affect sustainability is the SC operations planning since its fundamental role in achieving a balance between supply and demand in a sustainable manner. Moreover, in an uncertain and dynamic environment such as the textile sector, it is necessary to provide a certain learning capability to the operations planning techniques used to increase the speed and quality of response of the textile SC to unexpected situations. In this context, mathematical programming models, heuristics and artificial intelligence techniques have proven their validity to achieve sustainable, robust and smart supply chains. Despite their potential, neither a conceptual framework (CF) nor a literature review have been detected to support the development and study of such models in the textile supply chain operations planning. In view of these gaps, this paper proposes a CF for supporting the sustainable and smart operations planning of the textile supply chains in a dynamic and uncertain context based on a set of dimensions, categories and elements that reflect the specific characteristics of the textile sector. Firstly, a tentative CF is predefined based on other generic works on SC operations planning in uncertain context and the own authors’ knowledge. Secondly, a structured literature review based on this CF has been made resulting, at the same time, in the updating of some of its dimensions, categories and elements to reflect some textile specific characteristics. Consequently, the CF is not only predefined but also logically derived from the literature analysis. The results of the literature review show that there is a great opportunity to contribute to making textile supply chains more sustainable, smart, flexible, robust and resilient in dynamic and uncertain environments.},
 bibtype = {article},
 author = {Lorente-Leyva, Leandro L and Alemany, M.M.E. and Peluffo-Ordóñez, Diego H},
 doi = {10.1016/j.cie.2023.109824},
 journal = {Computers & Industrial Engineering}
}

Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic dimension, but fundamentally in its environmental and social ones. One of the key management processes that affect sustainability is the SC operations planning since its fundamental role in achieving a balance between supply and demand in a sustainable manner. Moreover, in an uncertain and dynamic environment such as the textile sector, it is necessary to provide a certain learning capability to the operations planning techniques used to increase the speed and quality of response of the textile SC to unexpected situations. In this context, mathematical programming models, heuristics and artificial intelligence techniques have proven their validity to achieve sustainable, robust and smart supply chains. Despite their potential, neither a conceptual framework (CF) nor a literature review have been detected to support the development and study of such models in the textile supply chain operations planning. In view of these gaps, this paper proposes a CF for supporting the sustainable and smart operations planning of the textile supply chains in a dynamic and uncertain context based on a set of dimensions, categories and elements that reflect the specific characteristics of the textile sector. Firstly, a tentative CF is predefined based on other generic works on SC operations planning in uncertain context and the own authors’ knowledge. Secondly, a structured literature review based on this CF has been made resulting, at the same time, in the updating of some of its dimensions, categories and elements to reflect some textile specific characteristics. Consequently, the CF is not only predefined but also logically derived from the literature analysis. The results of the literature review show that there is a great opportunity to contribute to making textile supply chains more sustainable, smart, flexible, robust and resilient in dynamic and uncertain environments.

@article{
 title = {Data-enabled Bayesian inference for strategic maintenance decisions in industrial operations},
 type = {article},
 year = {2024},
 keywords = {Intelligent predictive maintenance,Maintenance management,Maintenance strategy selection,Monte Carlo simulation},
 pages = {111058},
 volume = {57},
 websites = {https://www.sciencedirect.com/science/article/pii/S2352340924010205,https://linkinghub.elsevier.com/retrieve/pii/S2352340924010205},
 month = {12},
 id = {4026eab3-102d-338b-8c5f-5c288f286613},
 created = {2024-12-03T03:38:10.419Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2024-12-03T03:38:10.419Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {TORRESSAINZ2024111058},
 source_type = {article},
 private_publication = {false},
 abstract = {Efficient management of industrial assets and equipment depends heavily on the selection of appropriate maintenance strategies. This research presents a dataset generated through Monte Carlo simulations to evaluate 12 key criteria relevant to maintenance strategy selection. The dataset covers a wide range of potential maintenance scenarios, providing comprehensive data for researchers to explore various strategies in industrial settings. The data were normalized and structured in a way that facilitates their use for further modeling or analysis. The dataset offers an opportunity for researchers to reproduce the data collection process, enabling comparisons with their own studies. By providing this dataset, we aim to support the development of new models for maintenance strategy selection and encourage further exploration of data-driven approaches in industrial maintenance. Additionally, the dataset can serve educational purposes, assisting in the teaching of decision-making in the context of maintenance operations.},
 bibtype = {article},
 author = {Torres-Sainz, Raúl and Lorente-Leyva, Leandro L and Arbella-Feliciano, Yorley and Trinchet-Varela, Carlos Alberto and Pérez-Vallejo, Lidia María and Pérez-Rodríguez, Roberto},
 doi = {10.1016/j.dib.2024.111058},
 journal = {Data in Brief}
}

Efficient management of industrial assets and equipment depends heavily on the selection of appropriate maintenance strategies. This research presents a dataset generated through Monte Carlo simulations to evaluate 12 key criteria relevant to maintenance strategy selection. The dataset covers a wide range of potential maintenance scenarios, providing comprehensive data for researchers to explore various strategies in industrial settings. The data were normalized and structured in a way that facilitates their use for further modeling or analysis. The dataset offers an opportunity for researchers to reproduce the data collection process, enabling comparisons with their own studies. By providing this dataset, we aim to support the development of new models for maintenance strategy selection and encourage further exploration of data-driven approaches in industrial maintenance. Additionally, the dataset can serve educational purposes, assisting in the teaching of decision-making in the context of maintenance operations.

@article{
 title = {Conceptual design vulnerability assessment of the housing light roofs to strong winds},
 type = {article},
 year = {2024},
 pages = {133-140},
 volume = {12},
 websites = {http://www.growingscience.com/esm/Vol12/esm_2023_42.pdf},
 id = {d8405be9-54fa-34d1-aae7-384cca7aff5b},
 created = {2024-12-03T03:40:06.418Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2024-12-03T03:40:06.418Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {Hurricanes are one of the most significant causes of human and material losses in the Caribbean region. These events have demonstrated their devastating impact on housing and infrastructure. The assessment of the vulnerability of buildings with light roofs, at the initial design stage, is considered to be a fundamental step in the mitigation of these damages and losses. This paper presents the introduction of an indicator-based vulnerability assessment in an effort to mitigate these damages in advance. This indicator facilitates the design team's decision to select the appropriate light roof alternative subject to strong winds at the conceptual stage of the process. The indicators that contribute to the conceptual assessment of vulnerability were identified based on a comprehensive review of the literature and numerical simulations of the risk scenarios using CFD/FEM software’s. The ranking of indicator weights was determined by the Kano method according to experts' opinions. A desktop application has been developed for the assessment of the vulnerability of light roof variants for buildings at the conceptual design stage. The results reported in a case study demonstrate the viability of the desktop application based on the vulnerability indicator to assist decision making in the conceptual design stage.},
 bibtype = {article},
 author = {Reyes-Ramírez, Anabel and Estrada-Cingualbres, Roberto Andrés and Zúñiga-Igarza, Libys Martha and Pérez-Rodríguez, Roberto and Lorente-Leyva, Leandro L.},
 doi = {10.5267/j.esm.2023.10.004},
 journal = {Engineering Solid Mechanics},
 number = {2}
}

Hurricanes are one of the most significant causes of human and material losses in the Caribbean region. These events have demonstrated their devastating impact on housing and infrastructure. The assessment of the vulnerability of buildings with light roofs, at the initial design stage, is considered to be a fundamental step in the mitigation of these damages and losses. This paper presents the introduction of an indicator-based vulnerability assessment in an effort to mitigate these damages in advance. This indicator facilitates the design team's decision to select the appropriate light roof alternative subject to strong winds at the conceptual stage of the process. The indicators that contribute to the conceptual assessment of vulnerability were identified based on a comprehensive review of the literature and numerical simulations of the risk scenarios using CFD/FEM software’s. The ranking of indicator weights was determined by the Kano method according to experts' opinions. A desktop application has been developed for the assessment of the vulnerability of light roof variants for buildings at the conceptual design stage. The results reported in a case study demonstrate the viability of the desktop application based on the vulnerability indicator to assist decision making in the conceptual design stage.

@article{
 title = {Condition Monitoring of Wind Turbines: A Case Study of the Gibara II Wind Farm},
 type = {article},
 year = {2023},
 pages = {329-335},
 volume = {56},
 websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560218},
 month = {4},
 day = {30},
 id = {448258f4-1c64-3cd4-bea9-cf8c24dc1497},
 created = {2023-06-14T00:31:48.550Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-06-14T00:31:48.550Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {Arbella-Feliciano, Yorley and Trinchet-Varela, Carlos A and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.18280/jesa.560218},
 journal = {Journal Européen des Systèmes Automatisés},
 number = {2}
}

@article{
 title = {A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network},
 type = {article},
 year = {2023},
 pages = {255},
 volume = {8},
 websites = {https://www.mdpi.com/2313-7673/8/2/255},
 month = {6},
 publisher = {MDPI},
 day = {14},
 id = {bc280936-a306-3d69-968b-ae34bb214fe6},
 created = {2023-06-25T03:09:17.995Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-06-25T03:09:17.995Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.},
 bibtype = {article},
 author = {Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/biomimetics8020255},
 journal = {Biomimetics},
 number = {2}
}

About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.

@article{
 title = {A Novel Linear-Model-Based Methodology for Predicting the Directional Movement of the Euro-Dollar Exchange Rate},
 type = {article},
 year = {2023},
 pages = {67249-67284},
 volume = {11},
 websites = {https://ieeexplore.ieee.org/document/10147811/},
 id = {e09e8f99-932b-3a16-9fa2-d48ba448dc12},
 created = {2023-07-20T01:55:56.281Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-07-20T01:55:56.281Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10147811},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Argotty-Erazo, Mauricio and Blázquez-Zaballos, Antonio and Argoty-Eraso, Carlos A and Lorente-Leyva, Leandro L and Sánchez-Pozo, Nadia N and Peluffo-Ordóñez, Diego H},
 doi = {10.1109/ACCESS.2023.3285082},
 journal = {IEEE Access}
}

@article{
 title = {Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology},
 type = {article},
 year = {2023},
 volume = {14},
 websites = {http://dx.doi.org/10.14569/IJACSA.2023.0140829},
 publisher = {The Science and Information Organization},
 id = {6389fff5-598a-3720-a729-b57d290201f0},
 created = {2023-09-01T02:24:05.280Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-09-01T02:24:05.280Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Pontón2023},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.14569/IJACSA.2023.0140829},
 journal = {International Journal of Advanced Computer Science and Applications},
 number = {8}
}

@article{
 title = {Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor},
 type = {article},
 year = {2023},
 pages = {434},
 volume = {8},
 websites = {https://www.mdpi.com/2313-7673/8/5/434},
 month = {9},
 day = {19},
 id = {f918c06f-e7de-36d1-8b77-b4681b7511ca},
 created = {2023-09-21T02:07:46.519Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-09-21T02:07:46.519Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {biomimetics8050434},
 source_type = {article},
 private_publication = {false},
 abstract = {Automated industrial processes require a controller to obtain an output signal similar to the reference indicated by the user. There are controllers such as PIDs, which are efficient if the system does not change its initial conditions. However, if this is not the case, the controller must be retuned, affecting production times. In this work, an adaptive PID controller is developed for a DC motor speed plant using an artificial intelligence algorithm based on reinforcement learning. This algorithm uses an actor–critic agent, where its objective is to optimize the actor’s policy and train a critic for rewards. This will generate the appropriate gains without the need to know the system. The Deep Deterministic Policy Gradient with Twin Delayed (DDPG TD3) was used, with a network composed of 300 neurons for the agent’s learning. Finally, the performance of the obtained controller is compared with a classical control one using a cost function.},
 bibtype = {article},
 author = {Alejandro-Sanjines, Ulbio and Maisincho-Jivaja, Anthony and Asanza, Victor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/biomimetics8050434},
 journal = {Biomimetics},
 number = {5}
}

Automated industrial processes require a controller to obtain an output signal similar to the reference indicated by the user. There are controllers such as PIDs, which are efficient if the system does not change its initial conditions. However, if this is not the case, the controller must be retuned, affecting production times. In this work, an adaptive PID controller is developed for a DC motor speed plant using an artificial intelligence algorithm based on reinforcement learning. This algorithm uses an actor–critic agent, where its objective is to optimize the actor’s policy and train a critic for rewards. This will generate the appropriate gains without the need to know the system. The Deep Deterministic Policy Gradient with Twin Delayed (DDPG TD3) was used, with a network composed of 300 neurons for the agent’s learning. Finally, the performance of the obtained controller is compared with a classical control one using a cost function.

@article{
 title = {MILimbEEG: A dataset of EEG signals related to upper and lower limb execution of motor and motor imagery tasks},
 type = {article},
 year = {2023},
 keywords = {Brain–computer interface,Electroencephalography,Experimental methodology,Motor imagery task,Motor task,OpenBCI},
 pages = {109540},
 volume = {50},
 websites = {https://www.sciencedirect.com/science/article/pii/S2352340923006406,https://linkinghub.elsevier.com/retrieve/pii/S2352340923006406},
 month = {10},
 id = {3f24dbfb-17f5-3897-ba7f-f1b668f14511},
 created = {2023-09-21T02:07:46.524Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-09-21T02:07:46.524Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {ASANZA2023109540},
 source_type = {article},
 private_publication = {false},
 abstract = {Biomedical Electroencephalography (EEG) signals are the result of measuring the electric potential difference generated on the scalp surface by neural activity corresponding to each brain area. Accurate and automatic detection of neural activity from the upper and lower limbs using EEG may be helpful in rehabilitating people suffering from mobility limitations or disabilities. This article presents a dataset containing 7440 CSV files from 60 test subjects during motor and motor imagery tasks. The motor and motor imagery tasks performed by the test subjects were: Closing Left Hand (CLH), Closing Right Hand (CRH), Dorsal flexion of Left Foot (DLF), Plantar flexion of Left Foot (PLF), Dorsal flexion of Right Foot (DRF), Plantar flexion of Right Foot (PRF) and Resting in between tasks (Rest). The volunteers were recruited from research colleagues at ESPOL and patients at the Luis Vernaza Hospital in Guayaquil, Ecuador. Each CSV file has 501 rows, of which the first one lists the electrodes from 0 to 15, and the remaining 500 rows correspond to 500 data recorded during the task is performed due to sample rate. In addition, each file has 17 columns, of which the first one indicates the sampling number and the remaining 16 columns represent 16 surface EEG electrodes. As a data recording equipment, the OpenBCI is used in a monopolar setup with a sampling rate of 125 Hz. This work includes statistical measures about the demographic information of all recruited test subjects. Finally, we outline the experimental methodology used to record EEG signals during upper and lower limb task execution. This dataset is called MILimbEEG and contains microvolt (µV) EEG signals acquired during motor and motor imagery tasks. The collected data may facilitate the evaluation of EEG signal detection and classification models dedicated to task recognition.},
 bibtype = {article},
 author = {Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Montoya, Daniel and Gonzalez, Kleber},
 doi = {10.1016/j.dib.2023.109540},
 journal = {Data in Brief}
}

Biomedical Electroencephalography (EEG) signals are the result of measuring the electric potential difference generated on the scalp surface by neural activity corresponding to each brain area. Accurate and automatic detection of neural activity from the upper and lower limbs using EEG may be helpful in rehabilitating people suffering from mobility limitations or disabilities. This article presents a dataset containing 7440 CSV files from 60 test subjects during motor and motor imagery tasks. The motor and motor imagery tasks performed by the test subjects were: Closing Left Hand (CLH), Closing Right Hand (CRH), Dorsal flexion of Left Foot (DLF), Plantar flexion of Left Foot (PLF), Dorsal flexion of Right Foot (DRF), Plantar flexion of Right Foot (PRF) and Resting in between tasks (Rest). The volunteers were recruited from research colleagues at ESPOL and patients at the Luis Vernaza Hospital in Guayaquil, Ecuador. Each CSV file has 501 rows, of which the first one lists the electrodes from 0 to 15, and the remaining 500 rows correspond to 500 data recorded during the task is performed due to sample rate. In addition, each file has 17 columns, of which the first one indicates the sampling number and the remaining 16 columns represent 16 surface EEG electrodes. As a data recording equipment, the OpenBCI is used in a monopolar setup with a sampling rate of 125 Hz. This work includes statistical measures about the demographic information of all recruited test subjects. Finally, we outline the experimental methodology used to record EEG signals during upper and lower limb task execution. This dataset is called MILimbEEG and contains microvolt (µV) EEG signals acquired during motor and motor imagery tasks. The collected data may facilitate the evaluation of EEG signal detection and classification models dedicated to task recognition.

@article{
 title = {Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals},
 type = {article},
 year = {2023},
 pages = {641-649},
 volume = {56},
 websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413},
 month = {8},
 day = {31},
 id = {ffeebb68-28fb-38f8-b902-4ba22070b4b5},
 created = {2023-11-12T05:26:48.463Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-11-12T05:26:48.463Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {Torres, Karen and Espinoza, Jhon and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.18280/jesa.560413},
 journal = {Journal Européen des Systèmes Automatisés​},
 number = {4}
}

@article{
 title = {Metodología para la identificación biométrica a partir de señales EEG en múltiples estados emocionales},
 type = {article},
 year = {2023},
 pages = {281-288},
 websites = {https://www.proquest.com/docview/2880949468?fromopenview=true&pq-origsite=gscholar},
 publisher = {Associação Ibérica de Sistemas e Tecnologias de Informacao},
 id = {dbc9c206-3159-3f4c-bf6e-a1591327cc30},
 created = {2023-11-12T05:26:48.464Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2023-11-12T05:30:43.701Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 bibtype = {article},
 author = {Duque-Mejía, Carolina and Castro, Andrés and Duque, Eduardo and Serna-Guarín, Leonardo and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego and Becerra, Miguel A},
 doi = {https://www.proquest.com/docview/2880949468?fromopenview=true&pq-origsite=gscholar},
 journal = {Revista Ibérica de Sistemas e Tecnologias de Informação},
 number = {E62}
}

@article{
 title = {Identification of Lower-Limb Motor Tasks via Brain–Computer Interfaces: A Topical Overview},
 type = {article},
 year = {2022},
 pages = {2028},
 volume = {22},
 websites = {https://www.mdpi.com/1424-8220/22/5/2028},
 month = {3},
 day = {4},
 id = {0b2f3600-2c05-32a1-9d2d-65dd6b9bcedd},
 created = {2022-03-08T02:54:32.016Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-03-08T02:54:32.016Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {s22052028},
 source_type = {article},
 private_publication = {false},
 abstract = {Recent engineering and neuroscience applications have led to the development of brain–computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy.},
 bibtype = {article},
 author = {Asanza, Víctor and Peláez, Enrique and Loayza, Francis and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/s22052028},
 journal = {Sensors},
 number = {5}
}

Recent engineering and neuroscience applications have led to the development of brain–computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy.

@article{
 title = {Pineapple Drying Analysis in Packing Plants Through Computational Fluid Dynamics},
 type = {article},
 year = {2022},
 keywords = {cad,cae integration,cfd,computational fluid dynamics,packing plants,pineapple drying,ventilation system},
 pages = {29-35},
 volume = {17},
 websites = {https://www.iieta.org/journals/ijdne/paper/10.18280/ijdne.170104},
 month = {2},
 day = {28},
 id = {409523c3-9047-38b9-86ac-9e3122184d44},
 created = {2022-03-15T02:33:29.937Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-03-15T02:33:29.937Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The aim of this research is to determine the average fluid velocity values and the average total pressure at the outlet of the ventilation system conduit for the drying, by air impulsion, of pineapples in packing plants, in order to ensure the required humidity level of the crown for its proper packaging. The CAD model of the air conduction was obtained in Solidworks and Computational Fluid Dynamics (CFD) techniques were applied to simulate the performance of the ventilation system. Air was indicated as the type of fluid, and an internal analysis of the pipe with roughness Rz = 3.2 μm. As a computational domain, the pipeline was established, from the connection to the fan to the outlet diffuser. As boundary conditions were established; a W and Z Manufacturing regenerative fan at the inlet of the flow pipe 618,439 m3/h, and at the outlet of the pipe the value of atmospheric pressure. As a result of the simulation, an average velocity value at the diffuser outlet of 127.294 m/s was obtained, higher than the required 96.06 m/s. An average total pressure value of 111718.73 Pa was obtained in the conduit suitable for the proposed purposes. For the conveyor belt, it is recommended to use, in each row of pineapples, the simulated fan with a simple diffuser with a rectangular section of 1 x 20 cm, or a regenerative fan with a flow of 1248.77 m3/h and a diffuser with two-outlet bifurcation.},
 bibtype = {article},
 author = {García, Alexis Cordovés and Rodríguez, Alexis Cordovés and Buñay, Karla Tatiana Núñez and Aleaga, Arlys M. Lastre and Lorente-Leyva, Leandro L.},
 doi = {10.18280/ijdne.170104},
 journal = {International Journal of Design & Nature and Ecodynamics},
 number = {1}
}

The aim of this research is to determine the average fluid velocity values and the average total pressure at the outlet of the ventilation system conduit for the drying, by air impulsion, of pineapples in packing plants, in order to ensure the required humidity level of the crown for its proper packaging. The CAD model of the air conduction was obtained in Solidworks and Computational Fluid Dynamics (CFD) techniques were applied to simulate the performance of the ventilation system. Air was indicated as the type of fluid, and an internal analysis of the pipe with roughness Rz = 3.2 μm. As a computational domain, the pipeline was established, from the connection to the fan to the outlet diffuser. As boundary conditions were established; a W and Z Manufacturing regenerative fan at the inlet of the flow pipe 618,439 m3/h, and at the outlet of the pipe the value of atmospheric pressure. As a result of the simulation, an average velocity value at the diffuser outlet of 127.294 m/s was obtained, higher than the required 96.06 m/s. An average total pressure value of 111718.73 Pa was obtained in the conduit suitable for the proposed purposes. For the conveyor belt, it is recommended to use, in each row of pineapples, the simulated fan with a simple diffuser with a rectangular section of 1 x 20 cm, or a regenerative fan with a flow of 1248.77 m3/h and a diffuser with two-outlet bifurcation.

@article{
 title = {Controller Modeling of a Quadrotor},
 type = {article},
 year = {2022},
 keywords = {controller modeling,quadrotor,space states},
 pages = {21-28},
 volume = {27},
 websites = {https://www.iieta.org/journals/isi/paper/10.18280/isi.270103},
 month = {2},
 day = {28},
 id = {c676ac2f-1790-3ebc-a3a6-acfb0333c542},
 created = {2022-03-21T22:12:37.420Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-03-21T22:14:11.352Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Dynamic modeling and control are research fields that hake kept the attention of researchers over the last decades. In this paper we describe a detailed approach to model, design and simulate a feedback controller for a quadrotor with the aim of giving the reader a detailed procedure to obtain the dynamic model and link this model with a controller design strategy. For this purpose, the dynamic model of the Parrot AR. Drone 2.0 was obtained using the Newton-Euler formulations. Next, the model was converted to the state space, and it was linearized to get the equations to perform a controller gain estimation process. Finally, the performance of state feedback controller visualized for both the linear and nonlinear models. Results shown that, the challenging goal of stabilizing the quadrotor at a desired trajectory, in short time without overshoot problems, can be achieved by means of a simple control strategy.},
 bibtype = {article},
 author = {Herrera-Granda, Erick P. and Lorente-Leyva, Leandro L. and Yambay, Jenny and Aranguren, Jesús and Ibarra, Marcelo and Peña, Julio},
 doi = {10.18280/isi.270103},
 journal = {Ingénierie des systèmes d information},
 number = {1}
}

Dynamic modeling and control are research fields that hake kept the attention of researchers over the last decades. In this paper we describe a detailed approach to model, design and simulate a feedback controller for a quadrotor with the aim of giving the reader a detailed procedure to obtain the dynamic model and link this model with a controller design strategy. For this purpose, the dynamic model of the Parrot AR. Drone 2.0 was obtained using the Newton-Euler formulations. Next, the model was converted to the state space, and it was linearized to get the equations to perform a controller gain estimation process. Finally, the performance of state feedback controller visualized for both the linear and nonlinear models. Results shown that, the challenging goal of stabilizing the quadrotor at a desired trajectory, in short time without overshoot problems, can be achieved by means of a simple control strategy.

@article{
 title = {An MPPT Strategy Based on a Surface-Based Polynomial Fitting for Solar Photovoltaic Systems Using Real-Time Hardware},
 type = {article},
 year = {2021},
 pages = {206},
 volume = {10},
 websites = {https://www.mdpi.com/2079-9292/10/2/206},
 month = {1},
 day = {17},
 id = {67907dd4-5f24-3b54-b215-ae43b64ce1af},
 created = {2021-01-31T16:33:44.688Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:33:44.688Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper presents an optimal design of a surface-based polynomial fitting for tracking the maximum power point (MPPT) of a photovoltaic (PV) system, here named surface-based polynomial fitting (MPPT-SPF). The procedure of the proposed MPPT-SPF strategy is based on a polynomial model to characterize data from the PV module with a global fit. The advantage of using polynomials is that they provide a good fit within a predefined data range even though they can diverge greatly from that range. The MPPT-SPF strategy is integrated with a DC-DC boost converter to verify its performance and its interaction with different control loops. Therefore, the MPPT strategy is applied to the reference outer PI control loop, which in turn provides the current reference to the inner current loop based on a discrete-time sliding current control. A real-time and high-speed simulator (PLECS RT Box 1) and a digital signal controller (DSC) are used to implement the hardware-in-the-loop system to obtain the results. The proposed strategy does not have a high computational cost and can be implemented in a commercial low-cost DSC (TI 28069M). The proposed MPPT strategy is compared with a conventional perturb and observe method to prove its effectiveness under demanding tests.},
 bibtype = {article},
 author = {González-Castaño, Catalina and Lorente-Leyva, Leandro L. and Muñoz, Javier and Restrepo, Carlos and Peluffo-Ordóñez, Diego H.},
 doi = {10.3390/electronics10020206},
 journal = {Electronics},
 number = {2}
}

This paper presents an optimal design of a surface-based polynomial fitting for tracking the maximum power point (MPPT) of a photovoltaic (PV) system, here named surface-based polynomial fitting (MPPT-SPF). The procedure of the proposed MPPT-SPF strategy is based on a polynomial model to characterize data from the PV module with a global fit. The advantage of using polynomials is that they provide a good fit within a predefined data range even though they can diverge greatly from that range. The MPPT-SPF strategy is integrated with a DC-DC boost converter to verify its performance and its interaction with different control loops. Therefore, the MPPT strategy is applied to the reference outer PI control loop, which in turn provides the current reference to the inner current loop based on a discrete-time sliding current control. A real-time and high-speed simulator (PLECS RT Box 1) and a digital signal controller (DSC) are used to implement the hardware-in-the-loop system to obtain the results. The proposed strategy does not have a high computational cost and can be implemented in a commercial low-cost DSC (TI 28069M). The proposed MPPT strategy is compared with a conventional perturb and observe method to prove its effectiveness under demanding tests.

@inproceedings{
 title = {A Dynamic Programming Approach for Power Curtailment Decision Making on PV Systems},
 type = {inproceedings},
 year = {2021},
 pages = {77-86},
 websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_6},
 publisher = {Springer Singapore},
 city = {Singapore},
 id = {910e71f1-3bcd-34bb-8d7f-9ecff613b446},
 created = {2021-03-30T04:38:58.568Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-30T04:38:58.568Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-981-33-4909-4_6},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The new grid codes for large-scale photovoltaic power plants require power curtailment despite the variation of solar irradiance. This power curtailment is been developed considering one reference of active power. However, this value is chosen according to the demand, but it is not considering other aspects as solar irradiance or cloudiness. Therefore, this article presents a novel approach to tackle this issue. For this, stochastic dynamic programming is considered to optimize the decision of the power reference every hour considering the solar irradiance and cloudiness during different stages of the day. The results obtained are compared with the performance of the photovoltaic power plant, and it is a referential approach that uses the maximum power point tracking algorithms for the construction of referential power intervals over longer time intervals.},
 bibtype = {inproceedings},
 author = {Fernández-Fernández, Yasmany and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Álvarez, Elia N Cabrera},
 editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},
 booktitle = {International Conference on Communication, Computing and Electronics Systems}
}

The new grid codes for large-scale photovoltaic power plants require power curtailment despite the variation of solar irradiance. This power curtailment is been developed considering one reference of active power. However, this value is chosen according to the demand, but it is not considering other aspects as solar irradiance or cloudiness. Therefore, this article presents a novel approach to tackle this issue. For this, stochastic dynamic programming is considered to optimize the decision of the power reference every hour considering the solar irradiance and cloudiness during different stages of the day. The results obtained are compared with the performance of the photovoltaic power plant, and it is a referential approach that uses the maximum power point tracking algorithms for the construction of referential power intervals over longer time intervals.

@inproceedings{
 title = {A Brief Review on Instance Selection Based on Condensed Nearest Neighbors for Data Classification Tasks},
 type = {inproceedings},
 year = {2021},
 pages = {313-324},
 websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_23},
 publisher = {Springer Singapore},
 city = {Singapore},
 id = {c11d7da4-f338-3399-90b9-fd7c448e7bae},
 created = {2021-03-30T04:38:58.570Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-30T04:38:58.570Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-981-33-4909-4_23},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The condensed nearest neighbor (CNN) classifier is one of the techniques used and known to perform recognition tasks. It has also proven to be one of the most interesting algorithms in the field of data mining despite its simplicity. However, CNN suffers from several drawbacks, such as high storage requirements and low noise tolerance. One of the characteristics of CNN is that it focuses on the selection of prototypes, which consists of reducing the set of training data. One of the goals of CNN seeks to achieve the reduction of information in such a way that the reduced information can represent large amounts of data to exercise decision-making on them. This paper mentions some of the most recent contributions to CNN-based unsupervised algorithms in a review that builds on the mathematical principles of condensed methods.},
 bibtype = {inproceedings},
 author = {Fernández-Fernández, Yasmany and Peluffo-Ordóñez, Diego H and Umaquinga-Criollo, Ana C and Lorente-Leyva, Leandro L and Cabrera-Alvarez, Elia N},
 editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},
 booktitle = {International Conference on Communication, Computing and Electronics Systems}
}

The condensed nearest neighbor (CNN) classifier is one of the techniques used and known to perform recognition tasks. It has also proven to be one of the most interesting algorithms in the field of data mining despite its simplicity. However, CNN suffers from several drawbacks, such as high storage requirements and low noise tolerance. One of the characteristics of CNN is that it focuses on the selection of prototypes, which consists of reducing the set of training data. One of the goals of CNN seeks to achieve the reduction of information in such a way that the reduced information can represent large amounts of data to exercise decision-making on them. This paper mentions some of the most recent contributions to CNN-based unsupervised algorithms in a review that builds on the mathematical principles of condensed methods.

@article{
 title = {Evaluation of Working Temperature in Wind Turbine Bearings by Simulation of Lubricant Level},
 type = {article},
 year = {2021},
 keywords = {bearing,cfd,heat,lubricant,simulation,wind turbines,working temperature},
 pages = {99-104},
 volume = {16},
 websites = {http://www.iieta.org/journals/ijdne/paper/10.18280/ijdne.160113},
 month = {2},
 day = {28},
 id = {81bbf1aa-e18c-3f2f-906e-52ff3864ab2b},
 created = {2021-03-30T04:38:58.797Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-30T04:38:58.797Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {After studies related to the technical state and behavior of the temperatures manifested by the bearings of the generators that make up the Goldwind wind turbines models S50-750, installed in the Gibara II Wind Farm (PE). It was identified and validated as a tool that enables early diagnosis of anomalous bearing behaviors, SolidWorks (SW) computer-aided design and engineering software (CAD-CAE) and the Flow Simulation add-on. Since it allows studies based on the computational fluid dynamics (CFD), of the temperatures that are manifested in the lubricant during the different working regimes of the generator. The studies carried out evaluated the environmental conditions of exploitation in Cuba. It works on obtaining and predicting the values of the thermal state using the principles and methods for the calculation of heat transfer, the forecast statistics apply. The research supports its theories and postulates in a sample of 6 installed equipment, from China, for it had a historical database that collects temperature measurements in different working conditions which allowed to establish correlation between theoretical predictions and real behaviors.},
 bibtype = {article},
 author = {Feliciano, Yorley Arbella and Varela, Carlos A Trinchet and Guativas, Javier A Vargas and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H.},
 doi = {10.18280/ijdne.160113},
 journal = {International Journal of Design & Nature and Ecodynamics},
 number = {1}
}

After studies related to the technical state and behavior of the temperatures manifested by the bearings of the generators that make up the Goldwind wind turbines models S50-750, installed in the Gibara II Wind Farm (PE). It was identified and validated as a tool that enables early diagnosis of anomalous bearing behaviors, SolidWorks (SW) computer-aided design and engineering software (CAD-CAE) and the Flow Simulation add-on. Since it allows studies based on the computational fluid dynamics (CFD), of the temperatures that are manifested in the lubricant during the different working regimes of the generator. The studies carried out evaluated the environmental conditions of exploitation in Cuba. It works on obtaining and predicting the values of the thermal state using the principles and methods for the calculation of heat transfer, the forecast statistics apply. The research supports its theories and postulates in a sample of 6 installed equipment, from China, for it had a historical database that collects temperature measurements in different working conditions which allowed to establish correlation between theoretical predictions and real behaviors.

@inproceedings{
 title = {An Interactive Framework to Compare Multi-criteria Optimization Algorithms: Preliminary Results on NSGA-II and MOPSO},
 type = {inproceedings},
 year = {2021},
 pages = {61-76},
 websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_5},
 publisher = {Springer Singapore},
 city = {Singapore},
 id = {98e479b1-904b-3d10-a8b3-5692fbd42045},
 created = {2021-03-30T04:38:58.836Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-30T04:49:39.674Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-981-33-4909-4_5},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {A problem of multi-criteria optimization, according to its approach, can mean either minimizing or maximizing a group of at least two objective functions to find the best possible set of solutions. There are several methods of multi-criteria optimization, in which the resulting solutions' quality varies depending on the method used and the complexity of the posed problem. A bibliographical review allowed us to notice that the methods derived from the evolutionary computation deliver good results and are commonly used in research works. Although comparative studies among these optimization methods have been found, the conclusions that these offer to the reader do not allow us to define a general rule that determines when one method is better than another. Therefore, the choice of a well-adapted optimization method can be a difficult task for non-experts in the field. To implement a graphical interface that allows non-expert users in multi-objective optimization is proposed to interact and compare the performance of the NSGA-II and MOPSO algorithms. It is chosen qualitatively from a group of five preselected algorithms as members of evolutionary algorithms and swarm intelligence. Therefore, a comparison methodology has been proposed to allow the user for analyzing the graphical and numerical results, which will observe the behavior of algorithms and determine the best suited one according to their needs.},
 bibtype = {inproceedings},
 author = {Dorado-Sevilla, David F and Peluffo-Ordóñez, Diego H and Lorente-Leyva, Leandro L and Herrera-Granda, Erick P. and Herrera-Granda, Israel D},
 editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},
 booktitle = {International Conference on Communication, Computing and Electronics Systems}
}

A problem of multi-criteria optimization, according to its approach, can mean either minimizing or maximizing a group of at least two objective functions to find the best possible set of solutions. There are several methods of multi-criteria optimization, in which the resulting solutions' quality varies depending on the method used and the complexity of the posed problem. A bibliographical review allowed us to notice that the methods derived from the evolutionary computation deliver good results and are commonly used in research works. Although comparative studies among these optimization methods have been found, the conclusions that these offer to the reader do not allow us to define a general rule that determines when one method is better than another. Therefore, the choice of a well-adapted optimization method can be a difficult task for non-experts in the field. To implement a graphical interface that allows non-expert users in multi-objective optimization is proposed to interact and compare the performance of the NSGA-II and MOPSO algorithms. It is chosen qualitatively from a group of five preselected algorithms as members of evolutionary algorithms and swarm intelligence. Therefore, a comparison methodology has been proposed to allow the user for analyzing the graphical and numerical results, which will observe the behavior of algorithms and determine the best suited one according to their needs.

@inproceedings{
 title = {Analysis of Business Behavior in the Australian Market Under an Approach of Statistical Techniques and Economic Dimensions for Sustainable Business: A Case Study},
 type = {inproceedings},
 year = {2021},
 pages = {595-605},
 websites = {https://link.springer.com/chapter/10.1007/978-981-33-4355-9_44},
 publisher = {Springer Singapore},
 city = {Singapore},
 id = {37307342-bc8a-320d-8daf-8e58f36f679e},
 created = {2021-04-02T19:44:24.550Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-04-02T19:44:24.550Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-981-33-4355-9_44},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This paper provides a current and future business analysis of small food services and products company. Analysis methods include tabulation of the dataset, as well as hypothesis testing by comparison between directly proportional variables such as price/quality and recommendations/customer loyalty. Other calculations include key economic dimensions, decisions influenced by the JobKeeper payment scheme, data on capital expenditure expectations, and future business conditions. The results of the analyzed data show that customer and company behavior is in parallel with global trade. In particular, the growth of the digital market and customer loyalty where they find a product that meets their quality needs. The analysis finds that the company's prospects in its current position are positive. Of the four variables identified, two will be reinforced by the economic and market strategies to be implemented. The work also investigates the fact that the analysis carried out has possible limitations. Some of the limitations are that not all the company was able to register in the JobKeeper payment scheme and the lack of use of key tools for sustainable marketing.},
 bibtype = {inproceedings},
 author = {Patiño-Alarcón, Delio R and Patiño-Alarcón, Fernando A and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 booktitle = {Proceedings of International Conference on Sustainable Expert Systems}
}

This paper provides a current and future business analysis of small food services and products company. Analysis methods include tabulation of the dataset, as well as hypothesis testing by comparison between directly proportional variables such as price/quality and recommendations/customer loyalty. Other calculations include key economic dimensions, decisions influenced by the JobKeeper payment scheme, data on capital expenditure expectations, and future business conditions. The results of the analyzed data show that customer and company behavior is in parallel with global trade. In particular, the growth of the digital market and customer loyalty where they find a product that meets their quality needs. The analysis finds that the company's prospects in its current position are positive. Of the four variables identified, two will be reinforced by the economic and market strategies to be implemented. The work also investigates the fact that the analysis carried out has possible limitations. Some of the limitations are that not all the company was able to register in the JobKeeper payment scheme and the lack of use of key tools for sustainable marketing.

@inproceedings{
 title = {Unsupervised Barter Model Based on Natural Human Interaction},
 type = {inproceedings},
 year = {2021},
 pages = {387-400},
 websites = {https://link.springer.com/chapter/10.1007/978-981-16-1685-3_32},
 publisher = {Springer Singapore},
 city = {Singapore},
 id = {cd3e554b-d8ff-33b8-a95f-c178c64c0ad7},
 created = {2021-04-06T18:55:03.276Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-04-06T18:55:03.276Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {fernandez2021unsupervisedbarter},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Human interaction is a natural process in business management. In various indigenous cultures, the natives still use a barter system to reach consensus or balances that determine the essence of their economies. The present investigation consists of the presentation of an unsupervised model based on pure barter. The main contribution sought is to visualize the balance that is achieved in an unsupervised environment of two entities that are close to reaching an agreement. Both Game Theory and Walrasian Theory deal with the problem of exchange of goods. However, the current objective is to show the barter model from its simplest bases for the construction of an unsupervised automatic learning scheme where a system of pairs of agents represent a basic model for decision making when guaranteeing an agreement.},
 bibtype = {inproceedings},
 author = {Fernández-Fernández, Yasmany and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Pérez, Ridelio Miranda and Álvarez, Elia N Cabrera},
 editor = {Hong, Tzung-Pei and Wojtkiewicz, Krystian and Chawuthai, Rathachai and Sitek, Pawel},
 booktitle = {Recent Challenges in Intelligent Information and Database Systems}
}

Human interaction is a natural process in business management. In various indigenous cultures, the natives still use a barter system to reach consensus or balances that determine the essence of their economies. The present investigation consists of the presentation of an unsupervised model based on pure barter. The main contribution sought is to visualize the balance that is achieved in an unsupervised environment of two entities that are close to reaching an agreement. Both Game Theory and Walrasian Theory deal with the problem of exchange of goods. However, the current objective is to show the barter model from its simplest bases for the construction of an unsupervised automatic learning scheme where a system of pairs of agents represent a basic model for decision making when guaranteeing an agreement.

@inbook{
 type = {inbook},
 year = {2021},
 pages = {pp. 181-194},
 websites = {https://link.springer.com/chapter/10.1007/978-3-030-73280-6_15,https://link.springer.com/10.1007/978-3-030-73280-6_15},
 id = {924d7d5d-5b69-3482-ab31-8f602a2f43a9},
 created = {2021-04-06T18:55:03.277Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-04-19T05:01:14.164Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {leyva2021demandforecasting},
 folder_uuids = {d6f17673-4083-4776-9179-aa288af3fd07},
 private_publication = {false},
 abstract = {The generation of an accurate forecast model to estimate the future demand for textile products that favor decision-making around an organization's key processes is very important. The minimization of the model's uncertainty allows the generation of reliable results, which prevent the textile industry's economic commitment and improve the strategies adopted around production planning and decision making. That is why this work is focused on the demand forecasting for textile products through the application of artificial neural networks, from a statistical analysis of the time series and disaggregation in different time horizons through temporal hierarchies, to develop a more accurate forecast. With the results achieved, a comparison is made with statistical methods and machine learning algorithms, providing an environment where there is an adequate development of demand forecasting, improving accuracy and performance. Where all the variables that affect the productive environment of this sector under study are considered. Finally, as a result of the analysis, multilayer perceptron achieved better performance compared to conventional and machine learning algorithms. Featuring the best behavior and accuracy in demand forecasting of the analyzed textile products.},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro L and Alemany, M M E and Peluffo-Ordóñez, Diego H and Araujo, Roberth A},
 doi = {10.1007/978-3-030-73280-6_15},
 chapter = {Demand Forecasting for Textile Products Using Statistical Analysis and Machine Learning Algorithms},
 title = {Nguyen N.T., Chittayasothorn S., Niyato D., Trawiński B. (eds) Intelligent Information and Database Systems. ACIIDS 2021, 12672 LNCS}
}

The generation of an accurate forecast model to estimate the future demand for textile products that favor decision-making around an organization's key processes is very important. The minimization of the model's uncertainty allows the generation of reliable results, which prevent the textile industry's economic commitment and improve the strategies adopted around production planning and decision making. That is why this work is focused on the demand forecasting for textile products through the application of artificial neural networks, from a statistical analysis of the time series and disaggregation in different time horizons through temporal hierarchies, to develop a more accurate forecast. With the results achieved, a comparison is made with statistical methods and machine learning algorithms, providing an environment where there is an adequate development of demand forecasting, improving accuracy and performance. Where all the variables that affect the productive environment of this sector under study are considered. Finally, as a result of the analysis, multilayer perceptron achieved better performance compared to conventional and machine learning algorithms. Featuring the best behavior and accuracy in demand forecasting of the analyzed textile products.

@article{
 title = {Control of Pollutant Emissions from a Boiler Through the Percentage of Oxygen},
 type = {article},
 year = {2021},
 keywords = {HMI display,Lambda sensor,Programmable logic control,Steam boiler},
 pages = {469-474},
 volume = {54},
 websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.540310},
 month = {6},
 day = {25},
 id = {42fb9d9f-4def-34c5-8b80-17781d70cda3},
 created = {2021-08-14T15:38:15.842Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-08-14T15:38:15.842Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The goal of this paper is to obtain an automated system for the control of the quality of the combustion gases of a boiler. The concentration of oxygen present in the combustion gases is detected by means of a lambda sensor, and a proportional PID controller automatically regulates, through an actuator, the air inlet to the boiler, thus ensuring the emission of CO2 and other polluting gases into the atmosphere within the parameters established by the current environmental regulations. The control system has an HMI display and a modular PLC. The results achieved also ensure the reduction of fuel consumption of the boiler.},
 bibtype = {article},
 author = {García, Alexis Cordovés and Alban, Carlos A. Pérez and Benalcázar, Jorge R. Terán and Rodríguez, Alexis Cordovés and Lorente-Leyva, Leandro L. and Aleaga, Arlys M. Lastre},
 doi = {10.18280/jesa.540310},
 journal = {Journal Européen des Systèmes Automatisés},
 number = {3}
}

The goal of this paper is to obtain an automated system for the control of the quality of the combustion gases of a boiler. The concentration of oxygen present in the combustion gases is detected by means of a lambda sensor, and a proportional PID controller automatically regulates, through an actuator, the air inlet to the boiler, thus ensuring the emission of CO2 and other polluting gases into the atmosphere within the parameters established by the current environmental regulations. The control system has an HMI display and a modular PLC. The results achieved also ensure the reduction of fuel consumption of the boiler.

@inbook{
 type = {inbook},
 year = {2021},
 pages = {293-304},
 websites = {https://link.springer.com/10.1007/978-3-030-86271-8_25},
 publisher = {Springer International Publishing},
 city = {Cham},
 id = {a670d5c9-778b-3a13-b5ab-441a06c2dead},
 created = {2021-10-07T22:53:04.066Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-10-07T22:54:49.488Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1007/978-3-030-86271-8_25},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This paper presents a comparative analysis of predictive models applied to air quality estimation. Currently, among other global issues, there is a high concern about air pollution, for this reason, there are several air quality indicators, with carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3) being the main ones. When the concentration level of an indicator exceeds an established air quality safety threshold, it is considered harmful to human health, therefore, in cities like London, there are monitoring systems for air pollutants. This study aims to compare the efficiency of stochastic and heuristic predictive models for forecasting ozone (O3) concentration to estimate London's air quality by analyzing an open dataset retrieved from the London Datastore portal. Models based on data analysis have been widely used in air quality forecasting. This paper develops four predictive models (autoregressive integrated moving average - ARIMA, support vector regression - SVR, neural networks (specifically, long-short term memory - LSTM) and Facebook Prophet). Experimentally, ARIMA models and LSTM are proved to reach the highest accuracy in predicting the concentration of air pollutants among the considered models. As a result, the comparative analysis of the loss function (root-mean-square error) reveled that ARIMA and LSTM are the most suitable, accomplishing a low error rate of 0.18 and 0.20, respectively.},
 bibtype = {inbook},
 author = {Sánchez-Pozo, Nadia N and Trilles-Oliver, Sergi and Solé-Ribalta, Albert and Lorente-Leyva, Leandro L and Mayorca-Torres, Dagoberto and Peluffo-Ordóñez, Diego H},
 editor = {Sanjurjo González, Hugo and Pastor López, Iker and García Bringas, Pablo and Quintián, Héctor and Corchado, Emilio},
 doi = {10.1007/978-3-030-86271-8_25},
 chapter = {Algorithms Air Quality Estimation: A Comparative Study of Stochastic and Heuristic Predictive Models},
 title = {Hybrid Artificial Intelligent Systems}
}

This paper presents a comparative analysis of predictive models applied to air quality estimation. Currently, among other global issues, there is a high concern about air pollution, for this reason, there are several air quality indicators, with carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3) being the main ones. When the concentration level of an indicator exceeds an established air quality safety threshold, it is considered harmful to human health, therefore, in cities like London, there are monitoring systems for air pollutants. This study aims to compare the efficiency of stochastic and heuristic predictive models for forecasting ozone (O3) concentration to estimate London's air quality by analyzing an open dataset retrieved from the London Datastore portal. Models based on data analysis have been widely used in air quality forecasting. This paper develops four predictive models (autoregressive integrated moving average - ARIMA, support vector regression - SVR, neural networks (specifically, long-short term memory - LSTM) and Facebook Prophet). Experimentally, ARIMA models and LSTM are proved to reach the highest accuracy in predicting the concentration of air pollutants among the considered models. As a result, the comparative analysis of the loss function (root-mean-square error) reveled that ARIMA and LSTM are the most suitable, accomplishing a low error rate of 0.18 and 0.20, respectively.

@inproceedings{
 title = {Monitoring a turkey hatchery based on a cyber-physical system},
 type = {inproceedings},
 year = {2021},
 pages = {1-6},
 websites = {https://ieeexplore.ieee.org/document/9542899/},
 month = {9},
 publisher = {IEEE},
 day = {7},
 id = {58b4f8ad-9a9d-3cb7-b2e3-2a9a551e9e2d},
 created = {2021-10-07T22:54:49.140Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-10-07T22:54:49.140Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9542899},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Victor and Toscano-Quiroga, Tonny and Sanchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L and Peluffo-Ordonez, Diego Hernan},
 doi = {10.23919/AE51540.2021.9542899},
 booktitle = {2021 International Conference on Applied Electronics (AE)}
}

@inproceedings{
 title = {Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system},
 type = {inproceedings},
 year = {2021},
 pages = {1-4},
 websites = {https://ieeexplore.ieee.org/document/9542907/},
 month = {9},
 publisher = {IEEE},
 day = {7},
 id = {2e614ad8-a2f6-377c-bacd-815fa145d608},
 created = {2021-10-07T22:54:49.140Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-10-07T22:54:49.140Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {9542907},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Capelo, Jesus and Ruiz, Erick and Asanza, Victor and Toscano-Quiroga, Tonny and Sanchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L and Peluffo-Ordonez, Diego Hernan},
 doi = {10.23919/AE51540.2021.9542907},
 booktitle = {2021 International Conference on Applied Electronics (AE)}
}

@article{
 title = {A Fast-Tracking Hybrid MPPT Based on Surface-Based Polynomial Fitting and P&O Methods for Solar PV under Partial Shaded Conditions},
 type = {article},
 year = {2021},
 pages = {2732},
 volume = {9},
 websites = {https://www.mdpi.com/2227-7390/9/21/2732},
 month = {10},
 day = {28},
 id = {78a99bfd-656e-3496-8461-7c378589d8ed},
 created = {2021-11-01T17:35:47.185Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-11-01T17:35:47.185Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {math9212732},
 source_type = {article},
 private_publication = {false},
 abstract = {The efficiency of photovoltaic (PV) systems depends directly on solar irradiation, so drastic variations in solar exposure will undoubtedly move its maximum power point (MPP). Furthermore, the presence of partial shading conditions (PSCs) generates local maximum power points (LMPPs) and one global maximum power point (GMPP) in the P-V characteristic curve. Therefore, a proper maximum power point tracking (MPPT) technique is crucial to increase PV system efficiency. There are classical, intelligent, optimal, and hybrid MPPT techniques; this paper presents a novel hybrid MPPT technique that combines Surface-Based Polynomial Fitting (SPF) and Perturbation and Observation (P&O) for solar PV generation under PSCs. The development of the experimental PV system has two stages: (i) Modeling the PV array with the DC-DC boost converter using a real-time and high-speed simulator (PLECS RT Box), (ii) and implementing the proposed GMPPT algorithm with the double-loop controller of the DC-DC boost converter in a commercial low-priced digital signal controller (DSC). According to the simulation and the experimental results, the suggested hybrid algorithm is effective at tracking the GMPP under both uniform and nonuniform irradiance conditions in six scenarios: (i) system start-up, (ii) uniform irradiance variations, (iii) sharp change of the (PSCs), (iv) multiple peaks in the P-V characteristic, (v) dark cloud passing, and (vi) light cloud passing. Finally, the experimental results—through the standard errors and the mean power tracked and tracking factor scores—proved that the proposed hybrid SPF-P&O MPPT technique reaches the convergence to GMPP faster than benchmark approaches when dealing with PSCs.},
 bibtype = {article},
 author = {González-Castaño, Catalina and Restrepo, Carlos and Revelo-Fuelagán, Javier and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},
 doi = {10.3390/math9212732},
 journal = {Mathematics},
 number = {21}
}

The efficiency of photovoltaic (PV) systems depends directly on solar irradiation, so drastic variations in solar exposure will undoubtedly move its maximum power point (MPP). Furthermore, the presence of partial shading conditions (PSCs) generates local maximum power points (LMPPs) and one global maximum power point (GMPP) in the P-V characteristic curve. Therefore, a proper maximum power point tracking (MPPT) technique is crucial to increase PV system efficiency. There are classical, intelligent, optimal, and hybrid MPPT techniques; this paper presents a novel hybrid MPPT technique that combines Surface-Based Polynomial Fitting (SPF) and Perturbation and Observation (P&O) for solar PV generation under PSCs. The development of the experimental PV system has two stages: (i) Modeling the PV array with the DC-DC boost converter using a real-time and high-speed simulator (PLECS RT Box), (ii) and implementing the proposed GMPPT algorithm with the double-loop controller of the DC-DC boost converter in a commercial low-priced digital signal controller (DSC). According to the simulation and the experimental results, the suggested hybrid algorithm is effective at tracking the GMPP under both uniform and nonuniform irradiance conditions in six scenarios: (i) system start-up, (ii) uniform irradiance variations, (iii) sharp change of the (PSCs), (iv) multiple peaks in the P-V characteristic, (v) dark cloud passing, and (vi) light cloud passing. Finally, the experimental results—through the standard errors and the mean power tracked and tracking factor scores—proved that the proposed hybrid SPF-P&O MPPT technique reaches the convergence to GMPP faster than benchmark approaches when dealing with PSCs.

@article{
 title = {Classification of Subjects with Parkinson’s Disease using Finger Tapping Dataset},
 type = {article},
 year = {2021},
 keywords = {Classification,Finger Tapping,Machine Learning,Parkinson’s disease},
 pages = {376-381},
 volume = {54},
 websites = {https://www.sciencedirect.com/science/article/pii/S2405896321016906,https://linkinghub.elsevier.com/retrieve/pii/S2405896321016906},
 id = {9ce0ad0a-c635-33c7-84cc-dcd6f4ec4cc1},
 created = {2021-11-03T17:14:24.307Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-11-03T17:15:36.394Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {Parkinson’s disease is the second most common neurodegenerative disorder and affects more than 7 million people globally. In this work, we classify subjects with Parkinson’s disease using data from finger-tapping on a keyboard. We use a free database by Physionet with more than 9 million records, preprocessed to delete atypical data. In the feature extraction stage, we obtained 48 features. We use Google Colaboratory to train, validate, and test nine supervised learning algorithms that detect the disease. As a result, we achieve a degree of accuracy higher than 98%.},
 bibtype = {article},
 author = {Asanza, Víctor and Sánchez-Pozo, Nadia N and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego Hernan and Loayza, Fancis R and Peláez, Enrique},
 doi = {10.1016/j.ifacol.2021.10.285},
 journal = {IFAC-PapersOnLine},
 number = {15}
}

Parkinson’s disease is the second most common neurodegenerative disorder and affects more than 7 million people globally. In this work, we classify subjects with Parkinson’s disease using data from finger-tapping on a keyboard. We use a free database by Physionet with more than 9 million records, preprocessed to delete atypical data. In the feature extraction stage, we obtained 48 features. We use Google Colaboratory to train, validate, and test nine supervised learning algorithms that detect the disease. As a result, we achieve a degree of accuracy higher than 98%.

@article{
 title = {Dynamic Modeling of a Proton-Exchange Membrane Fuel Cell Using a Gaussian Approach},
 type = {article},
 year = {2021},
 keywords = {Gaussian model,diffusive model,evolution strategy,proton exchange membrane fuel cell,voltage-current dynamic response},
 pages = {953},
 volume = {11},
 websites = {https://www.mdpi.com/2077-0375/11/12/953},
 month = {12},
 day = {1},
 id = {d16218ef-7b13-38f5-be2d-523d1aea81dc},
 created = {2021-12-02T22:49:43.181Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-12-02T22:49:43.181Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {EJOU},
 private_publication = {false},
 abstract = {This paper proposes a Gaussian approach for the proton-exchange membrane fuel cell (PEMFC) model that estimates its voltage behavior from the operating current value. A multi-parametric Gaussian model and an unconstrained optimization formulation based on a conventional non-linear least squares optimizer is mainly considered. The model is tested using experimental data from the Ballard Nexa 1.2 kW fuel cell (FC). This methodology offers a promising approach for static and current-voltage, characteristic of the three regions of operation. A statistical study is developed to evaluate the effectiveness and superiority of the proposed FC Gaussian model compared with the Diffusive Global model and the Evolution Strategy. In addition, an approximation to the exponential function for a Gaussian model simplification can be used in systems that require real-time emulators or complex long-time simulations.},
 bibtype = {article},
 author = {González-Castaño, Catalina and Lorente-Leyva, Leandro L and Alpala, Janeth and Revelo-Fuelagán, Javier and Peluffo-Ordóñez, Diego H and Restrepo, Carlos},
 doi = {10.3390/membranes11120953},
 journal = {Membranes},
 number = {12}
}

This paper proposes a Gaussian approach for the proton-exchange membrane fuel cell (PEMFC) model that estimates its voltage behavior from the operating current value. A multi-parametric Gaussian model and an unconstrained optimization formulation based on a conventional non-linear least squares optimizer is mainly considered. The model is tested using experimental data from the Ballard Nexa 1.2 kW fuel cell (FC). This methodology offers a promising approach for static and current-voltage, characteristic of the three regions of operation. A statistical study is developed to evaluate the effectiveness and superiority of the proposed FC Gaussian model compared with the Diffusive Global model and the Evolution Strategy. In addition, an approximation to the exponential function for a Gaussian model simplification can be used in systems that require real-time emulators or complex long-time simulations.

@inproceedings{
 title = {Statistical quality control in MSMEs of recycled plastic wood},
 type = {inproceedings},
 year = {2020},
 keywords = {Control,Control charts,Process cards,Quality,Variables},
 volume = {0},
 issue = {March},
 websites = {http://www.ieomsociety.org/ieom2020/papers/206.pdf},
 id = {740d33ff-efba-31c1-8619-4441afd636a0},
 created = {2020-12-09T06:11:18.396Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:27.533Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. The application of statistical quality control in plastic wood MSMEs in Ecuador is the first implementation carried out for this productive sector. Where the fundamental problem is the variation of the results of recycled plastic wood in tensile analysis, where the coefficient of variation is 51.38% with a maximum force of 605.42 N. In this case study, the methodology composed by the diagnosis Current of the production process, the identification of qualitative-quantitative variables and the implementation of statistical quality control. I provoke the standardization of the productive process in the criteria of selection of recycled plastics, optimum values of temperature, pressure and time in each of the subprocesses. Thus, improvements were obtained in the tensile analysis of recycled plastic wood where the coefficient of variation after the improvement is 7.26% with a maximum force of 751.03 N.},
 bibtype = {inproceedings},
 author = {Herrera, A.R.C. and Cuasapud, L.P.T. and Aguirre, J.P.U. and Palacios, S.M.V. and Lorente Leyva, L.L.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. The application of statistical quality control in plastic wood MSMEs in Ecuador is the first implementation carried out for this productive sector. Where the fundamental problem is the variation of the results of recycled plastic wood in tensile analysis, where the coefficient of variation is 51.38% with a maximum force of 605.42 N. In this case study, the methodology composed by the diagnosis Current of the production process, the identification of qualitative-quantitative variables and the implementation of statistical quality control. I provoke the standardization of the productive process in the criteria of selection of recycled plastics, optimum values of temperature, pressure and time in each of the subprocesses. Thus, improvements were obtained in the tensile analysis of recycled plastic wood where the coefficient of variation after the improvement is 7.26% with a maximum force of 751.03 N.

@article{
 title = {Analysis of the thermal behavior in the goldwind S50/750 wind turbines installed in the wind farm gibara ii using cad-cae tools},
 type = {article},
 year = {2020},
 keywords = {CAD/CAE Tools,Goldwind Wind Turbines,Temperatures &amp,Thermal Behavior,Wind Farm},
 volume = {10},
 websites = {http://www.tjprc.org/view_paper.php?id=12471},
 id = {88721d8e-e804-37a3-8510-a8f99d5ca899},
 created = {2020-12-09T06:11:18.401Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:08:02.054Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© TJPRC Pvt. Ltd. This study indicates the thermal behavior inside the gondola for models S50–750 of Goldwind wind turbines installed in the Wind Farm Gibara II. It allows the early diagnosis of incipient failures that occur in the studied devices because of the high temperatures generated in its components under the operating conditions of Cuba. It works in the obtention of the values of the thermal state using forecast statistics and computer-aided design and engineering software (CAD-CAE), such as SolidWorks and its Flow Simulation add-on. This research supports its theories and postulates in the study of six assembled devices of Chinese origin, which have been in operation for nine years. For that purpose, we used a database that collects the temperature measurements in different working conditions and points inside the gondola.},
 bibtype = {article},
 author = {Feliciano, Y.A. and Trinchet, C.A. and Meléndez, E. and Lorente-Leyva, L.L. and Peluffo-Ordóñez, D.H.},
 doi = {10.24247/ijmperdapr202032},
 journal = {International Journal of Mechanical and Production Engineering Research and Development},
 number = {2}
}

© TJPRC Pvt. Ltd. This study indicates the thermal behavior inside the gondola for models S50–750 of Goldwind wind turbines installed in the Wind Farm Gibara II. It allows the early diagnosis of incipient failures that occur in the studied devices because of the high temperatures generated in its components under the operating conditions of Cuba. It works in the obtention of the values of the thermal state using forecast statistics and computer-aided design and engineering software (CAD-CAE), such as SolidWorks and its Flow Simulation add-on. This research supports its theories and postulates in the study of six assembled devices of Chinese origin, which have been in operation for nine years. For that purpose, we used a database that collects the temperature measurements in different working conditions and points inside the gondola.

@article{
 title = {Optimization of urban solid waste collection under a geographic information systems approach, a case study},
 type = {article},
 year = {2020},
 keywords = {Logistics,Optimization,Routes,Sustainable development,Territorial planning,Urban solid waste},
 volume = {2020},
 websites = {https://search.proquest.com/openview/a2803956d6c8a33b6d862dd6708e284b/1?pq-origsite=gscholar&cbl=1006393},
 id = {4ef9ab2f-e0eb-3503-b12f-c1d305753839},
 created = {2020-12-09T06:11:18.945Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:08:02.058Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. The present work shows a proposal of urban solid waste collection routes for the Ibarra city, using territorial districting concepts to level the workload among the collection trucks and ensure access to the collection service for all residents. In this proposal, 11 micro collection routes are implemented, considering aspects such as waste generation rates, collection frequencies and operational costs of the trucks. To this end, in the first steps an updated geographic database is consolidated and then this information is processed in the Arc-GIS under the focus of capacited arcs. The results obtained are contrasted with the model currently established in the canton through indicators of cost per ton collected in each collection route, going from an average cost of 37.53 $/t to an average cost of 8.27 $/t with the present proposal, as well as a balance in the mentioned costs.},
 bibtype = {article},
 author = {León-Jácome, J.C. and Herrera-Granda, I.D. and Lorente-Leyva, L.L. and Montero-Santos, Y. and Herrera-Granda, E.P. and Esparza, D.E.I. and León, J.G.J.},
 journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},
 number = {E29}
}

© 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. The present work shows a proposal of urban solid waste collection routes for the Ibarra city, using territorial districting concepts to level the workload among the collection trucks and ensure access to the collection service for all residents. In this proposal, 11 micro collection routes are implemented, considering aspects such as waste generation rates, collection frequencies and operational costs of the trucks. To this end, in the first steps an updated geographic database is consolidated and then this information is processed in the Arc-GIS under the focus of capacited arcs. The results obtained are contrasted with the model currently established in the canton through indicators of cost per ton collected in each collection route, going from an average cost of 37.53 $/t to an average cost of 8.27 $/t with the present proposal, as well as a balance in the mentioned costs.

@article{
 title = {Applying Lean Manufacturing in the Production Process of Rolling Doors: A Case Study},
 type = {article},
 year = {2020},
 keywords = {Improvement proposal,Lean manufacturing,Production capacity,Production process,Productivity,Rolling doors},
 pages = {1774-1781},
 volume = {13},
 websites = {https://medwelljournals.com/abstract/?doi=jeasci.2018.1774.1781},
 month = {2},
 day = {17},
 id = {e6b85dde-5bbe-3890-a5d9-8a3844329983},
 created = {2020-12-09T06:11:19.471Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:04.072Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Medwell Journals, 2018. The lean manufacturing seeks to ensure the quality of the service and the supplier's products by the companies that implement this methodology, through the improvement of the research environment and the elimination of the classic wastes present in any process. The research was developed in a metalworking company which presents as main problem the delay in the delivery of the finished product (rolling doors), generating complaints and nonconformities. For this reason, the need arises to make a proposal for improvement in its production process which allows to reduce the delivery time of the product to its customers and to guarantee its efficiency and productivity, using the tools and techniques of lean manufacturing. The methodology assumed in the study, corresponds to the philosophy of lean thinking to develop an improvement proposal where the following tools were used: value stream mapping, 9'S, single minute exchange of die, total productive maintenance, Kanban which provided the following possible results: total production process time would improve by 6.10%, value added time by 2.13%. The production increases from 24-26 doors per month, giving an improvement of 7.4% and mainly, the delivery time would decrease 590-554 min with a reduction of 6.10%, all these results lead to faster and more efficient deliveries to the customer. A case study was carried out in the metalworking company in Ibarra, Ecuador. The results also indicate that lean thinking contribute substantially to the operating performance of company is decreased about 7% of the time in operational performance.},
 bibtype = {article},
 author = {Lorente Leyva, Leandro L. and Yerovi Huaca, Mishell A. and Montero Santos, Yakcleem and Saraguro Piarpuezan, Ramiro V. and Herrera Granda, Israel D. and Machado Orges, Carlos A. and Lastre Aleaga, Arlys M. and Cordoves Garcia, Alexis},
 doi = {10.36478/jeasci.2018.1774.1781},
 journal = {Journal of Engineering and Applied Sciences},
 number = {7}
}

© Medwell Journals, 2018. The lean manufacturing seeks to ensure the quality of the service and the supplier's products by the companies that implement this methodology, through the improvement of the research environment and the elimination of the classic wastes present in any process. The research was developed in a metalworking company which presents as main problem the delay in the delivery of the finished product (rolling doors), generating complaints and nonconformities. For this reason, the need arises to make a proposal for improvement in its production process which allows to reduce the delivery time of the product to its customers and to guarantee its efficiency and productivity, using the tools and techniques of lean manufacturing. The methodology assumed in the study, corresponds to the philosophy of lean thinking to develop an improvement proposal where the following tools were used: value stream mapping, 9'S, single minute exchange of die, total productive maintenance, Kanban which provided the following possible results: total production process time would improve by 6.10%, value added time by 2.13%. The production increases from 24-26 doors per month, giving an improvement of 7.4% and mainly, the delivery time would decrease 590-554 min with a reduction of 6.10%, all these results lead to faster and more efficient deliveries to the customer. A case study was carried out in the metalworking company in Ibarra, Ecuador. The results also indicate that lean thinking contribute substantially to the operating performance of company is decreased about 7% of the time in operational performance.

@inbook{
 type = {inbook},
 year = {2020},
 pages = {77-90},
 volume = {1307 CCIS},
 websites = {http://link.springer.com/10.1007/978-3-030-62833-8_7},
 id = {bbbfe35b-6b96-3c45-bf72-987d1acebf82},
 created = {2021-01-04T23:28:59.881Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.272Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {inbook},
 author = {Patiño-Alarcón, Delio R. and Patiño-Alarcón, Fernando A. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H.},
 doi = {10.1007/978-3-030-62833-8_7},
 chapter = {Clustering of Reading Ability Performance Variables in the English Language Based on TBL Methodology and Behavior in the Left Hemisphere of the Brain},
 title = {Communications in Computer and Information Science}
}

@article{
 title = {Influences of the Temperature Variations in the Gondola of the Goldwing S50/750 Wind},
 type = {article},
 year = {2020},
 pages = {2634},
 volume = {10},
 websites = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=11340},
 month = {12},
 day = {29},
 id = {a9e84ebf-ee64-3d89-8a99-833bac4abc76},
 created = {2021-02-01T15:17:24.534Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-01T15:17:24.534Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The use of wind energy is a decisive factor for human development, associated with the environment and capacity of people exploiting this vital resource. The investigation is part of predicting the behavior of the temperatures inside the nacelle of the Goldwind wind turbines S50 / 750 models installed in the Gibara Wind Farm. It supports its theories and analysis of computer-aided design (CAD), by monitoring the working temperatures, which interact with the forced ventilation system in the studied devices. The values analyzed result from continuous measurements carried out by the SCADA systems (Supervisory Control and Data Acquisition) of the studied machines. Which allows the diagnosis and early visualization of unforeseen incipient failures that currently occur under operating conditions standardized by the manufacturer. When the wind reaches speeds that exceed 11.5 m/s, major aggregates such as the gearbox and the generator fail. The results obtained in the investigation will allow to correct the program in the PLC (Logical Control Program) for the start-up and stop of the cooling system of the wind turbines in order to generate an ideal thermal balance for the working condition activities in Cuba, inside the nacelle, reducing the frequent occurrence of critical temperature values in the maximum limit that put the wind turbines out of service and therefore providing the wind farm with a higher coefficient of technical availability.},
 bibtype = {article},
 author = {Arbella Feliciano, Yorley and Trinchet, Carlos A. and Vargas, Javier A. and Lorente-Leyva, Leandro L.},
 doi = {10.18517/ijaseit.10.6.11340},
 journal = {International Journal on Advanced Science, Engineering and Information Technology},
 number = {6}
}

The use of wind energy is a decisive factor for human development, associated with the environment and capacity of people exploiting this vital resource. The investigation is part of predicting the behavior of the temperatures inside the nacelle of the Goldwind wind turbines S50 / 750 models installed in the Gibara Wind Farm. It supports its theories and analysis of computer-aided design (CAD), by monitoring the working temperatures, which interact with the forced ventilation system in the studied devices. The values analyzed result from continuous measurements carried out by the SCADA systems (Supervisory Control and Data Acquisition) of the studied machines. Which allows the diagnosis and early visualization of unforeseen incipient failures that currently occur under operating conditions standardized by the manufacturer. When the wind reaches speeds that exceed 11.5 m/s, major aggregates such as the gearbox and the generator fail. The results obtained in the investigation will allow to correct the program in the PLC (Logical Control Program) for the start-up and stop of the cooling system of the wind turbines in order to generate an ideal thermal balance for the working condition activities in Cuba, inside the nacelle, reducing the frequent occurrence of critical temperature values in the maximum limit that put the wind turbines out of service and therefore providing the wind farm with a higher coefficient of technical availability.

@inbook{
 type = {inbook},
 year = {2020},
 pages = {131-142},
 volume = {12566 LNCS},
 websites = {http://link.springer.com/10.1007/978-3-030-64580-9_11},
 id = {d5fff0dc-a827-3b94-9d3c-44647710c0d2},
 created = {2021-03-04T16:54:21.240Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-04-19T05:01:12.722Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 folder_uuids = {d6f17673-4083-4776-9179-aa288af3fd07},
 private_publication = {false},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro L. and Alemany, M. M. E. and Peluffo-Ordóñez, Diego H. and Herrera-Granda, Israel D.},
 doi = {10.1007/978-3-030-64580-9_11},
 chapter = {A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry},
 title = {Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2020,}
}

@inbook{
 type = {inbook},
 year = {2020},
 pages = {245-258},
 volume = {12566 LNCS},
 websites = {http://link.springer.com/10.1007/978-3-030-64580-9_21},
 id = {1d6bfe09-577e-3f24-a823-0537c476fe36},
 created = {2021-03-04T16:55:03.138Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-04T17:01:22.826Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {inbook},
 author = {Herrera-Granda, Israel D. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H. and Alemany, M. M. E.},
 doi = {10.1007/978-3-030-64580-9_21},
 chapter = {A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

@inproceedings{
 title = {Application of six sigma in improving the quality of recyclable polymer in collection centers},
 type = {inproceedings},
 year = {2019},
 keywords = {Collection centers,DMAIC,Polymers,Post-consumer,Six sigma},
 issue = {July},
 websites = {http://ieomsociety.org/pilsen2019/papers/278.pdf},
 id = {b9d1ac33-4d90-3c69-bf21-249db3de4236},
 created = {2020-12-09T06:11:18.287Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:28.471Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, IEOM Society International. The research aims to apply Six Sigma to solve the quality problem of the collection center. It does not meet the final recycler's specification for 3% +/-0.15% impurities in the delivered post-consumer polymer bales. By applying the first two phases of DMAIC a Cp = 0.26 and Cpk = -4.9 was determined. After applying the last three phases, the improved indices are Cp = 1.8 and Cpk = 1.78. Therefore, it can be concluded that the post-consumer polymer collection center has an adequate and satisfactory process. With an average of 3% +/-0.022% so it meets the impurity specifications of the final recycler.},
 bibtype = {inproceedings},
 author = {Herrera, A.R.C. and Aguirre, J.D.P.U. and Leyva, L.L.L.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© 2019, IEOM Society International. The research aims to apply Six Sigma to solve the quality problem of the collection center. It does not meet the final recycler's specification for 3% +/-0.15% impurities in the delivered post-consumer polymer bales. By applying the first two phases of DMAIC a Cp = 0.26 and Cpk = -4.9 was determined. After applying the last three phases, the improved indices are Cp = 1.8 and Cpk = 1.78. Therefore, it can be concluded that the post-consumer polymer collection center has an adequate and satisfactory process. With an average of 3% +/-0.022% so it meets the impurity specifications of the final recycler.

@inproceedings{
 title = {Development of post-consumer polymer suppliers},
 type = {inproceedings},
 year = {2019},
 keywords = {Developmet,Performance,Post-consumer polymers,Recycler,Suppliers},
 volume = {2019},
 issue = {MAR},
 websites = {http://www.ieomsociety.org/ieom2019/papers/466.pdf},
 id = {4c794f4d-7a7c-3985-a88d-10a031b06e06},
 created = {2020-12-09T06:11:18.287Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:27.775Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. The development of post-consumer polymers suppliers is defined as any effort made by the buyer company to its suppliers, to improve their performance or capacity, which guarantees the fulfillment of the supply in the short or long term. The main objective of the study is to improve the performance of matter that is outside impurity and density specifications through criteria of selection, intervention and evaluation of suppliers. These criteria were implemented with the following method: identification of needs for improvement of raw material by the final recycler, establishment of criteria for the evaluation of suppliers, intervention of suppliers, evaluation of results and development of a program of monitoring suppliers. At the end of the intervention, 12.5% of impurities were reduced and 400% density was increased, which caused an average increase of 8% in the raw material yield factor of the final recycler.},
 bibtype = {inproceedings},
 author = {Herrera, A.R.C. and Aguirre, J.P.U. and Leyva, L.L.L.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. The development of post-consumer polymers suppliers is defined as any effort made by the buyer company to its suppliers, to improve their performance or capacity, which guarantees the fulfillment of the supply in the short or long term. The main objective of the study is to improve the performance of matter that is outside impurity and density specifications through criteria of selection, intervention and evaluation of suppliers. These criteria were implemented with the following method: identification of needs for improvement of raw material by the final recycler, establishment of criteria for the evaluation of suppliers, intervention of suppliers, evaluation of results and development of a program of monitoring suppliers. At the end of the intervention, 12.5% of impurities were reduced and 400% density was increased, which caused an average increase of 8% in the raw material yield factor of the final recycler.

@inproceedings{
 title = {Improvement production capacity of recycled plastic wood through six sigma DMAIC},
 type = {inproceedings},
 year = {2019},
 keywords = {Capacity,DMAIC,Improvement,Production,Recycled plastic wood,Six sigma},
 issue = {July},
 websites = {http://ieomsociety.org/pilsen2019/papers/342.pdf},
 id = {6e542936-1a1b-398e-bac7-3cb07637ffb1},
 created = {2020-12-09T06:11:18.345Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:27.853Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, IEOM Society International. This research aims to increase production capacity of wood plastic through Six Sigma DMAIC implementation, within the simulation laboratory of production of recycled plastic wood sheets of the Universidad Te´cnica del Norte, Ecuador. Where they simulated the conditions of the current problem, which reflects the lack of strategies to improve production capacity, and three steps were determined as project methodology based on DIMAC (define, measure, implement and control). First, the current diagnosis was carried out where it was identified that the final client has excessive waiting times for the product. With which they measured and calculated: production time in 214.3 minutes + / -15.7, Cp=0.91 and Cpk = 0.49. Combined these results mean that production times are not suitable for the job and are off-center to the upper limit. Second, improvements were implemented from root cause analysis, which determined the lack of: maintenance, work method, training and design / construction of larger capacity molds. Third, the results were evaluated after the improvements, where a production time of 173.4 minutes was obtained, that is, an improvement of 19%, Cp=1.09 and Cpk = 0.99. These indicators mean that the production times are capable for the job and is slightly displaced to the upper limit.},
 bibtype = {inproceedings},
 author = {Herrera, A.R.C. and Benavides, E.P. and Aguirre, J.D.P.U. and Leyva, L.L.L.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© 2019, IEOM Society International. This research aims to increase production capacity of wood plastic through Six Sigma DMAIC implementation, within the simulation laboratory of production of recycled plastic wood sheets of the Universidad Te´cnica del Norte, Ecuador. Where they simulated the conditions of the current problem, which reflects the lack of strategies to improve production capacity, and three steps were determined as project methodology based on DIMAC (define, measure, implement and control). First, the current diagnosis was carried out where it was identified that the final client has excessive waiting times for the product. With which they measured and calculated: production time in 214.3 minutes + / -15.7, Cp=0.91 and Cpk = 0.49. Combined these results mean that production times are not suitable for the job and are off-center to the upper limit. Second, improvements were implemented from root cause analysis, which determined the lack of: maintenance, work method, training and design / construction of larger capacity molds. Third, the results were evaluated after the improvements, where a production time of 173.4 minutes was obtained, that is, an improvement of 19%, Cp=1.09 and Cpk = 0.99. These indicators mean that the production times are capable for the job and is slightly displaced to the upper limit.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},
 pages = {686-696},
 volume = {11734 LNAI},
 websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},
 id = {fff937e2-0197-366c-9023-cb6f13f05599},
 created = {2020-12-09T06:11:18.462Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.254Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.},
 bibtype = {inbook},
 author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Lorente-Leyva, Leandro L. and Blanco-Valencia, X. P.},
 doi = {10.1007/978-3-030-29859-3_58},
 chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© 2019, Springer Nature Switzerland AG. This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.

@inproceedings{
 title = {Work organization through methods engineering and time study to increase productivity in a floriculture company: A case study},
 type = {inproceedings},
 year = {2019},
 keywords = {Floriculture company,Methods engineering,Productivity,Standard time,Time study,Work organization},
 volume = {2019},
 issue = {MAR},
 websites = {http://www.ieomsociety.org/ieom2019/papers/458.pdf},
 id = {94958c0c-82b5-3958-9ad3-bc08cd3f1a03},
 created = {2020-12-09T06:11:18.464Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:27.835Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. This research was carried out through a methodology to diagnose and improve the work organization, based on methods engineering tools and time study. A case study was carried out in the floriculture company in La Esperanza-Ibarra, Ecuador. With the aim of increasing productivity, optimizing working methods and setting standards of time and performance. The bibliographical review allowed us to support the theoretical and scientific bases concerning the engineering of methods and study of times necessary to carry out the Investigation. With a diagnosis of the company case study, through tools of diagrams of processes and routes, were able to visualize the activities in each one of the workstations of the post-harvest area, such as: reception of roses, take off leafs, classification, bunch, cutting of stems, quality control and packaging. In addition, the times were taken in each of the operations of the operations of the above processes. According to the data obtained from the diagnosis, the company carried out a production of 11 893 stems per day according to the limiting capacity, for a demand of 12 500. As a result, improvements were made in the physical distribution of the post-harvest area, the standardization of times and with it, time and performance standards, and working methods are proposed. All the above proposed would allow us to achieve a decrease of cycle time from 2.01 minutes to 1.79 minutes per unit, estimating as a result the increase in production capacity to 13 400 stems per day, and increasing productivity by 12.67%; achieving the main objective of this case study.},
 bibtype = {inproceedings},
 author = {Orges, C.A.M. and Leyva, L.L.L. and Iles, J.C.M. and Guisao, J.P.T. and Pérez, I.C.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. This research was carried out through a methodology to diagnose and improve the work organization, based on methods engineering tools and time study. A case study was carried out in the floriculture company in La Esperanza-Ibarra, Ecuador. With the aim of increasing productivity, optimizing working methods and setting standards of time and performance. The bibliographical review allowed us to support the theoretical and scientific bases concerning the engineering of methods and study of times necessary to carry out the Investigation. With a diagnosis of the company case study, through tools of diagrams of processes and routes, were able to visualize the activities in each one of the workstations of the post-harvest area, such as: reception of roses, take off leafs, classification, bunch, cutting of stems, quality control and packaging. In addition, the times were taken in each of the operations of the operations of the above processes. According to the data obtained from the diagnosis, the company carried out a production of 11 893 stems per day according to the limiting capacity, for a demand of 12 500. As a result, improvements were made in the physical distribution of the post-harvest area, the standardization of times and with it, time and performance standards, and working methods are proposed. All the above proposed would allow us to achieve a decrease of cycle time from 2.01 minutes to 1.79 minutes per unit, estimating as a result the increase in production capacity to 13 400 stems per day, and increasing productivity by 12.67%; achieving the main objective of this case study.

@inproceedings{
 title = {Improvement plant layout of production line in textile company: A case study},
 type = {inproceedings},
 year = {2019},
 keywords = {CORELAP,CRAFT,Lay out,Plant distribution,SLP},
 issue = {July},
 websites = {http://ieomsociety.org/pilsen2019/papers/212.pdf},
 id = {0151f186-05c3-333c-8ae9-6ca33afc862d},
 created = {2020-12-09T06:11:18.574Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:12:27.847Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, IEOM Society International. This research took place of a textile company, its primary object was to design a layout for a specific area of production line, applying methods of plant distribution. The project began with the description of basic theories which were used to enable the research, continuing realizing diagnosing the production system where the flow of materials was examined, and the current layout was observed. Alternative solutions were created and a practicable solution for the layout was established by using Systematic Layout Planning; to test the solution mentioned above, the quantitative methods called Computer Relative Allocation of Facilities Technique and Computerized Relationship Layout Planning were applied. Furthermore, a final solution for the layout was proposed in which the organization of two working departments was designed with a production flow of the U-type.},
 bibtype = {inproceedings},
 author = {Santos, Y.M. and Torres, O.V.C. and Leyva, L.L.L. and Granda, I.D.H. and Orges, C.A.M. and Piarpuezan, R.V.S.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© 2019, IEOM Society International. This research took place of a textile company, its primary object was to design a layout for a specific area of production line, applying methods of plant distribution. The project began with the description of basic theories which were used to enable the research, continuing realizing diagnosing the production system where the flow of materials was examined, and the current layout was observed. Alternative solutions were created and a practicable solution for the layout was established by using Systematic Layout Planning; to test the solution mentioned above, the quantitative methods called Computer Relative Allocation of Facilities Technique and Computerized Relationship Layout Planning were applied. Furthermore, a final solution for the layout was proposed in which the organization of two working departments was designed with a production flow of the U-type.

@article{
 title = {Artificial Neural Networks for Urban Water Demand Forecasting: A Case Study},
 type = {article},
 year = {2019},
 pages = {012004},
 volume = {1284},
 websites = {https://iopscience.iop.org/article/10.1088/1742-6596/1284/1/012004},
 month = {8},
 id = {105f7db1-24e1-3992-b0bb-d163b9d41e90},
 created = {2020-12-09T06:11:18.609Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.268Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019 Published under licence by IOP Publishing Ltd. This paper presents an application of an artificial neural network model in forecasting urban water demand using MATLAB software. Considering that in any planning process, the demand forecast plays a fundamental role, being one of the premises to organize and control a set of activities or processes. The versatility of the short, medium and long-term prediction that is provided to the company that offers the water distribution service to determine the supply capacity, maintenance activities, and system improvements as a strategic planning tool. Shown to improve network performance by using time series water demand data, the model can provide excellent fit and forecast without relying on the explicit inclusion of climatic factors and number of consumers. The excellent accuracy of the model indicates the effectiveness of forecasting over different time horizons. Finally, the results obtained from the Artificial Neural Network are compared with traditional statistical models.},
 bibtype = {article},
 author = {Lorente-Leyva, Leandro L and Pavón-Valencia, Jairo F and Montero-Santos, Yakcleem and Herrera-Granda, Israel D and Herrera-Granda, Erick P and Peluffo-Ordóñez, Diego H},
 doi = {10.1088/1742-6596/1284/1/012004},
 journal = {Journal of Physics: Conference Series},
 number = {1}
}

© 2019 Published under licence by IOP Publishing Ltd. This paper presents an application of an artificial neural network model in forecasting urban water demand using MATLAB software. Considering that in any planning process, the demand forecast plays a fundamental role, being one of the premises to organize and control a set of activities or processes. The versatility of the short, medium and long-term prediction that is provided to the company that offers the water distribution service to determine the supply capacity, maintenance activities, and system improvements as a strategic planning tool. Shown to improve network performance by using time series water demand data, the model can provide excellent fit and forecast without relying on the explicit inclusion of climatic factors and number of consumers. The excellent accuracy of the model indicates the effectiveness of forecasting over different time horizons. Finally, the results obtained from the Artificial Neural Network are compared with traditional statistical models.

@article{
 title = {Implementation of an artificial vision system and monitoring of human objectives using a quadricopter},
 type = {article},
 year = {2019},
 keywords = {Artificial vision,Detection,Monitoring,Segmentation,Threshold},
 volume = {2019},
 websites = {https://search.proquest.com/openview/ca355d43bc1ac0d236ca8da769393332/1?pq-origsite=gscholar&cbl=1006393},
 id = {15d60888-7654-3300-9e27-a302428fd74b},
 created = {2020-12-09T06:11:18.662Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:04.046Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. In the present project an artificial vision system was developed, with the main purpose of demonstrating that its application is possible in the detection of human faces, in real time, through a video input. By means of image processing the control signals were obtained, in order to controlling the drone in real time. To achieve this goal, this project was carried out in stages. Considering that the detection methodology was a cascade detector using the algorithm of Viola Jones. Initially, the equipment and software necessary, for the acquisition of the video captured by the camera, were selected. Later, an image processing system was developed, in order to improve the quality of the image and prepare it for detection. Then, through the segmentation of colors of each frame, thresholding, binarization and edge detection, the program was able to automatically define a region for each image in which the human objective is located. In this way, having the region where the face is most likely to be found, a cascade classifier was trained, which through a tracking algorithm, will allow to obtain the position and area where the face is located from the center of the image.},
 bibtype = {article},
 author = {Herrera-Granda, E.P. and Herrera-Granda, I.D. and Lorente-Leyva, L.L. and Granda-Gudiño, P.D. and Caraguay-Procel, J.A. and García-Santillán, I.},
 journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},
 number = {19}
}

© 2019, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. In the present project an artificial vision system was developed, with the main purpose of demonstrating that its application is possible in the detection of human faces, in real time, through a video input. By means of image processing the control signals were obtained, in order to controlling the drone in real time. To achieve this goal, this project was carried out in stages. Considering that the detection methodology was a cascade detector using the algorithm of Viola Jones. Initially, the equipment and software necessary, for the acquisition of the video captured by the camera, were selected. Later, an image processing system was developed, in order to improve the quality of the image and prepare it for detection. Then, through the segmentation of colors of each frame, thresholding, binarization and edge detection, the program was able to automatically define a region for each image in which the human objective is located. In this way, having the region where the face is most likely to be found, a cascade classifier was trained, which through a tracking algorithm, will allow to obtain the position and area where the face is located from the center of the image.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Collection network,Facility Location Problem,NP-hard,Optimization,Reverse logistics,Urban solid waste},
 pages = {578-589},
 volume = {895},
 websites = {http://link.springer.com/10.1007/978-3-030-05532-5_44},
 id = {ac705b68-c666-3527-9ed2-2356fef8ceab},
 created = {2020-12-09T06:11:18.845Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.031Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer Nature Switzerland AG 2019. This paper presents the results of the optimization of the urban solid waste container network in the urban sector of the Ibarra City, Ecuador by the implementation of an optimization model, which consists of a multi-objective mixed integer programming model which has been successfully used in the context of recycling in past studies. This model was modified so that possible locations of the containers at each corner of the blocks containing the constructed buildings were considered. As well, a restriction to count the containers to be installed was added. Furthermore, to add robustness to the model, it was also considered the filling of the container based on the density of the deposited waste and the model objective functions – being, a weighted sum of the cost of the installation of the network along with the average walking distance between users and the assigned containers. The outputs of the model are the total number of containers and a map with the optimal locations of municipal solid waste containers for Ibarra city. The model was implemented in GAMS platform wherein parameters can be permanently revised so that the results may be updated in case of variations of the initial conditions.},
 bibtype = {inbook},
 author = {Herrera-Granda, Israel D. and Imbaquingo-Usiña, Wilson G. and Lorente-Leyva, Leandro L. and Herrera-Granda, Erick P. and Peluffo-Ordóñez, Diego H. and Rossit, Diego G.},
 doi = {10.1007/978-3-030-05532-5_44},
 chapter = {Optimization of the Network of Urban Solid Waste Containers: A Case Study},
 title = {Communications in Computer and Information Science}
}

© Springer Nature Switzerland AG 2019. This paper presents the results of the optimization of the urban solid waste container network in the urban sector of the Ibarra City, Ecuador by the implementation of an optimization model, which consists of a multi-objective mixed integer programming model which has been successfully used in the context of recycling in past studies. This model was modified so that possible locations of the containers at each corner of the blocks containing the constructed buildings were considered. As well, a restriction to count the containers to be installed was added. Furthermore, to add robustness to the model, it was also considered the filling of the container based on the density of the deposited waste and the model objective functions – being, a weighted sum of the cost of the installation of the network along with the average walking distance between users and the assigned containers. The outputs of the model are the total number of containers and a map with the optimal locations of municipal solid waste containers for Ibarra city. The model was implemented in GAMS platform wherein parameters can be permanently revised so that the results may be updated in case of variations of the initial conditions.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Artificial neural networks,Long-term demand forecasting,Small business},
 pages = {362-373},
 volume = {11507 LNCS},
 websites = {http://link.springer.com/10.1007/978-3-030-20518-8_31},
 id = {e9e39395-2c9b-3318-8c59-7512d8f75c7b},
 created = {2020-12-09T06:11:19.107Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.506Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. This paper shows a neural networks-based demand forecasting model designed for a small manufacturer of bottled water in Ecuador, which currently doesn’t have adequate demand forecast methodologies, causing problems of customer orders non-compliance, inventory excess and economic losses. However, by working with accurate predictions, the manufacturer will have an anticipated vision of future needs in order to satisfy the demand for manufactured products, in other words, to guarantee on time and reasonable use of the resources. To solve the problems that this small manufacturer has to face a historic demand data acquisition process was done through the last 36 months costumer order records. In the construction of the historical time series, that was analyzed, demand dates and volumes were established as input variables. Then the design of forecast models was done, based on classical methods and multi-layer neural networks, which were evaluated by means of quantitative error indicators. The application of these methods was done through the R programming language. After this, a stage of training and improvement of the network is included, it was evaluated against the results of the classic forecasting methods, and the next 12 months were predicted by means of the best obtained model. Finally, the feasibility of the use of neural networks in the forecast of demand for purified water bottles, is demonstrated.},
 bibtype = {inbook},
 author = {Herrera-Granda, Israel D. and Chicaiza-Ipiales, Joselyn A. and Herrera-Granda, Erick P. and Lorente-Leyva, Leandro L. and Caraguay-Procel, Jorge A. and García-Santillán, Iván D. and Peluffo-Ordóñez, Diego H.},
 doi = {10.1007/978-3-030-20518-8_31},
 chapter = {Artificial Neural Networks for Bottled Water Demand Forecasting: A Small Business Case Study},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© 2019, Springer Nature Switzerland AG. This paper shows a neural networks-based demand forecasting model designed for a small manufacturer of bottled water in Ecuador, which currently doesn’t have adequate demand forecast methodologies, causing problems of customer orders non-compliance, inventory excess and economic losses. However, by working with accurate predictions, the manufacturer will have an anticipated vision of future needs in order to satisfy the demand for manufactured products, in other words, to guarantee on time and reasonable use of the resources. To solve the problems that this small manufacturer has to face a historic demand data acquisition process was done through the last 36 months costumer order records. In the construction of the historical time series, that was analyzed, demand dates and volumes were established as input variables. Then the design of forecast models was done, based on classical methods and multi-layer neural networks, which were evaluated by means of quantitative error indicators. The application of these methods was done through the R programming language. After this, a stage of training and improvement of the network is included, it was evaluated against the results of the classic forecasting methods, and the next 12 months were predicted by means of the best obtained model. Finally, the feasibility of the use of neural networks in the forecast of demand for purified water bottles, is demonstrated.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Alarm,Artificial intelligence,Drowsiness detection,Human eye,Image processing},
 pages = {626-637},
 volume = {11431 LNAI},
 websites = {http://link.springer.com/10.1007/978-3-030-14799-0_54},
 id = {716964de-fc65-3e63-9580-79a9f57508c4},
 created = {2020-12-09T06:11:19.152Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.266Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. At a global level, drowsiness is one of the main causes of road accidents causing frequent deaths and economic losses. To solve this problem an application developed in Matlab environment was made, which processes real time acquired images in order to determine if the driver is awake or drowsy. Using AdaBoost training Algorithm for Viola-Jones eyes detection, a cascade classifier finds the location and the area of the driver eyes in each frame of the video. Once the driver eyes are detected, they are analyzed whether are open or closed by color segmentation and thresholding based on the sclera binarized area. Finally, it was implemented as a drowsiness detection system which aims to prevent driver fall asleep while driving a vehicle by activating an audible alert, reaching speeds up to 14.5 fps.},
 bibtype = {inbook},
 author = {Herrera-Granda, Erick P. and Caraguay-Procel, Jorge A. and Granda-Gudiño, Pedro D. and Herrera-Granda, Israel D. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H. and Revelo-Fuelagán, Javier},
 doi = {10.1007/978-3-030-14799-0_54},
 chapter = {Drowsiness Detection in Drivers Through Real-Time Image Processing of the Human Eye},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© 2019, Springer Nature Switzerland AG. At a global level, drowsiness is one of the main causes of road accidents causing frequent deaths and economic losses. To solve this problem an application developed in Matlab environment was made, which processes real time acquired images in order to determine if the driver is awake or drowsy. Using AdaBoost training Algorithm for Viola-Jones eyes detection, a cascade classifier finds the location and the area of the driver eyes in each frame of the video. Once the driver eyes are detected, they are analyzed whether are open or closed by color segmentation and thresholding based on the sclera binarized area. Finally, it was implemented as a drowsiness detection system which aims to prevent driver fall asleep while driving a vehicle by activating an audible alert, reaching speeds up to 14.5 fps.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Collection network,GIS,Logistics,Municipal solid waste,Optimization,Subregion districting},
 pages = {225-237},
 volume = {884},
 websites = {http://link.springer.com/10.1007/978-3-030-02828-2_17},
 id = {9390fc8d-64c6-3feb-87bc-2b9f12ed096f},
 created = {2020-12-09T06:11:19.325Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:22.768Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. This paper proposes the implementation of a subregion district model to optimize the collection of solid waste generated in the residential and commercial zones of the Ibarra city in Ecuador. The work begins with a review of cases and methodologies previously applied. Later, the initial condition was determined and the optimum number of districts or sub-areas in which the zones should be divided, starting from the model proposed by the Pan American Health Organization, The City Development and Zoning Plan, and some guidelines given by the Department of Social Development of Mexico in the year 1997. Furthermore, the homogeneous distribution of the districts on the city was also carried out taking into account of factors such as: the components of the collection network, area of each district, current and available road network, surface slopes, waste production rates, collection frequency, and optimal vehicle fleet dedicated to harvesting operations. As support tools for the analyses carried out QGIS 2.18.2, MS-Excel, Global Mapper and LingoV17 were used. Finally, it proposes an optimal distribution of the districts in which the waste collection crews would operate in the city.},
 bibtype = {inbook},
 author = {Herrera-Granda, Israel D. and León-Jácome, Juan C. and Lorente-Leyva, Leandro L. and Lucano-Chávez, Fausto and Montero-Santos, Yakcleem and Oviedo-Pantoja, Winston G. and Díaz-Cajas, Christian S.},
 doi = {10.1007/978-3-030-02828-2_17},
 chapter = {Subregion Districting to Optimize the Municipal Solid Waste Collection Network: A Case Study},
 title = {Advances in Intelligent Systems and Computing}
}

© 2019, Springer Nature Switzerland AG. This paper proposes the implementation of a subregion district model to optimize the collection of solid waste generated in the residential and commercial zones of the Ibarra city in Ecuador. The work begins with a review of cases and methodologies previously applied. Later, the initial condition was determined and the optimum number of districts or sub-areas in which the zones should be divided, starting from the model proposed by the Pan American Health Organization, The City Development and Zoning Plan, and some guidelines given by the Department of Social Development of Mexico in the year 1997. Furthermore, the homogeneous distribution of the districts on the city was also carried out taking into account of factors such as: the components of the collection network, area of each district, current and available road network, surface slopes, waste production rates, collection frequency, and optimal vehicle fleet dedicated to harvesting operations. As support tools for the analyses carried out QGIS 2.18.2, MS-Excel, Global Mapper and LingoV17 were used. Finally, it proposes an optimal distribution of the districts in which the waste collection crews would operate in the city.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry},
 pages = {674-685},
 volume = {11734 LNAI},
 websites = {http://link.springer.com/10.1007/978-3-030-29859-3_57},
 id = {114702f3-23b2-3c85-866e-8bb90410b4eb},
 created = {2020-12-09T06:11:19.395Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2022-04-19T04:58:08.227Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Lorente-Leyva2019},
 folder_uuids = {d6f17673-4083-4776-9179-aa288af3fd07,a5e5940a-a9ac-4eb2-afb5-a73436234c61},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro L. and Murillo-Valle, Jefferson R. and Montero-Santos, Yakcleem and Herrera-Granda, Israel D. and Herrera-Granda, Erick P. and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, Diego H. and Blanco-Valencia, Xiomara P.},
 doi = {10.1007/978-3-030-29859-3_57},
 chapter = {Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm},
 title = {Hybrid Artificial Intelligent Systems. HAIS 2019}
}

© 2019, Springer Nature Switzerland AG. In a competitive environment, an industry’s success is directly related to the level of optimization of its processes, how production is planned and developed. In this area, the master production scheduling (MPS) is the key action for success. The object of study arises from the need to optimize the medium-term production planning system in a textile company, through genetic algorithms. This research begins with the analysis of the constraints, mainly determined by the installed capacity and the number of workers. The aggregate production planning is carried out for the T-shirts families. Due to such complexity, the application of bioinspired optimization techniques demonstrates their best performance, before industries that normally employ exact and simple methods that provide an empirical MPS but can compromise efficiency and costs. The products are then disaggregated for each of the items in which the MPS is determined, based on the analysis of the demand forecast, and the orders made by customers. From this, with the use of genetic algorithms, the MPS is optimized to carry out production planning, with an improvement of up to 96% of the level of service provided.

@inbook{
 type = {inbook},
 year = {2019},
 keywords = {Bayes,Case-based reasoning,Classification,Parametric,Probability},
 pages = {339-350},
 volume = {11431 LNAI},
 websites = {http://link.springer.com/10.1007/978-3-030-14799-0_29},
 id = {1002bd45-cc3b-30b0-acd3-39e1b3dfc13a},
 created = {2020-12-09T06:11:19.408Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.285Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Springer Nature Switzerland AG. When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. This article seeks to improve these systems through the use of parametric and non-parametric probability estimation methods, particularly, at their recovery and adaptation stages. To this end, a set of experiments are conducted with two essentially different, medical databases (Cardiotocography and Cleveland databases), in order to find good parametric and non-parametric estimators. The results are remarkable as a high accuracy rate is achieved when using explored approaches: Naive Bayes and Nearest Neighbors (K-NN) estimators. In addition, a decrease on the involved processing time is reached, which suggests that proposed estimators incorporated into the recovery and adaptation stage becomes suitable for CBR systems, especially when dealing with support for medical diagnosis applications.},
 bibtype = {inbook},
 author = {Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, Diego H. and Blanco Valencia, X. and Revelo-Fuelagán, Javier and Becerra, M. A. and Castro-Ospina, A. E. and Lorente-Leyva, Leandro L.},
 doi = {10.1007/978-3-030-14799-0_29},
 chapter = {Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© 2019, Springer Nature Switzerland AG. When searching for better solutions that improve the medical diagnosis accuracy, Case-Based reasoning systems (CBR) arise as a good option. This article seeks to improve these systems through the use of parametric and non-parametric probability estimation methods, particularly, at their recovery and adaptation stages. To this end, a set of experiments are conducted with two essentially different, medical databases (Cardiotocography and Cleveland databases), in order to find good parametric and non-parametric estimators. The results are remarkable as a high accuracy rate is achieved when using explored approaches: Naive Bayes and Nearest Neighbors (K-NN) estimators. In addition, a decrease on the involved processing time is reached, which suggests that proposed estimators incorporated into the recovery and adaptation stage becomes suitable for CBR systems, especially when dealing with support for medical diagnosis applications.

@article{
 title = {Intelligent adaptation of technological routes for symmetrical parts with cavities by case based reasoning},
 type = {article},
 year = {2019},
 keywords = {CAD/CAPP Systems,Case Based Reasoning (CBR),Form Features,Technological Routes},
 id = {a76e8421-86ca-3130-9797-6332b4ecfb63},
 created = {2021-03-30T04:45:18.302Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-30T04:45:18.302Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This research deals with the problem of the technological conception routes in the machining process planning (CAPP) for symmetrical parts with cavities under the approach of Case Based Reasoning (CBR). It includes shaft, bushing and disc type parts because of their frequent use in the metal-mechanical industry. A data model for feature-based representation was created, which contains the geometric, dimensional and technological information required for its elaboration. The technological machining route of a case study was obtained from the adaptation of the route of a prototype piece recovered from a base of cases by means of Artificial Intelligence (AI), based on the peripheral cutting index (PCI-2D) and the index of geometric form (IGF) that is supported by the Feature-based Representation. Its application extends to conventional and CNC technology.},
 bibtype = {article},
 author = {García, Alexis Cordovés and Lastre Aleaga, Arlys M. and Lorente Leyva, Leandro L. and Rodríguez, Alexis Cordovés and Ávila Rondón, Ricardo L. and Crespo, Remberto Rodríguez},
 journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}
}

This research deals with the problem of the technological conception routes in the machining process planning (CAPP) for symmetrical parts with cavities under the approach of Case Based Reasoning (CBR). It includes shaft, bushing and disc type parts because of their frequent use in the metal-mechanical industry. A data model for feature-based representation was created, which contains the geometric, dimensional and technological information required for its elaboration. The technological machining route of a case study was obtained from the adaptation of the route of a prototype piece recovered from a base of cases by means of Artificial Intelligence (AI), based on the peripheral cutting index (PCI-2D) and the index of geometric form (IGF) that is supported by the Feature-based Representation. Its application extends to conventional and CNC technology.

@inproceedings{
 title = {Design of a lab-scale anaerobic biodigester for renewable energy from municipal solid waste},
 type = {inproceedings},
 year = {2018},
 keywords = {Anaerobic digestion,Biodigester,Biogas,Design,Municipal solid waste},
 volume = {2018},
 issue = {SEP},
 id = {1a0dedb4-644e-36fc-918f-1601093eea15},
 created = {2020-12-09T06:11:18.722Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2020-12-09T06:11:18.722Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. The energy sector is in constant search of new clean sources of energy, both to supplement its production, as well as to reduce dependence on fossil fuels and its gradual replacement based on sustainable development methods. In this context, municipal waste is considered as a renewable energy source, since they have a high biomass content (paper, cardboard, food waste, wood, straw, leaves). A renewable source alternative with great prospects for the future is the use and energetic valuation of municipal solid waste. This research aims at the design of a lab-scale biodigester for the energetic industrialization of municipal solid waste, serving as a basis for the construction of a prototype on a pilot scale or a plant for the anaerobic treatment of these generated wastes. In this way, it will be possible to recover the energy contained in them, in order to reduce the flow of the waste destined to the landfills and to provide a production rate for the obtaining of biogas, taking as fundamental basis for the calculations of design and the improvement of laboratory-level production, through co-digestion with other types of organic waste and use of alkaline inoculating substances and determination of the most appropriate anaerobic digestion technology for waste treatment municipal solids.},
 bibtype = {inproceedings},
 author = {Leyva, L.L.L. and Santos, Y.M. and Granda, I.D.H. and Orges, C.A.M. and Palacios, S.M.V. and Chapi, R.M.V.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. The energy sector is in constant search of new clean sources of energy, both to supplement its production, as well as to reduce dependence on fossil fuels and its gradual replacement based on sustainable development methods. In this context, municipal waste is considered as a renewable energy source, since they have a high biomass content (paper, cardboard, food waste, wood, straw, leaves). A renewable source alternative with great prospects for the future is the use and energetic valuation of municipal solid waste. This research aims at the design of a lab-scale biodigester for the energetic industrialization of municipal solid waste, serving as a basis for the construction of a prototype on a pilot scale or a plant for the anaerobic treatment of these generated wastes. In this way, it will be possible to recover the energy contained in them, in order to reduce the flow of the waste destined to the landfills and to provide a production rate for the obtaining of biogas, taking as fundamental basis for the calculations of design and the improvement of laboratory-level production, through co-digestion with other types of organic waste and use of alkaline inoculating substances and determination of the most appropriate anaerobic digestion technology for waste treatment municipal solids.

@inproceedings{
 title = {Supply model design for a dairy company: A case study},
 type = {inproceedings},
 year = {2018},
 keywords = {Dairy company,Inventory,Logistics,Store,Supply model},
 volume = {2018},
 issue = {SEP},
 websites = {http://ieomsociety.org/dc2018/papers/237.pdf},
 id = {83e220ed-8360-3deb-8a22-91c00311356b},
 created = {2020-12-09T06:11:18.760Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:04.120Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. This research was developed in a dairy company, with the purpose of providing tools that allow the continuous improvement of supplies necessary for daily production, to ensure the quality of the finished product and customer satisfaction. A Case study was carried out in the dairy company in Cayambe, Ecuador. In order to determine the supply management model, a survey was applied to identify the deficiencies and weaknesses that directly affect the management system within the company. With the help of the management the historical data of 3 years for the classification of the inputs was collected through the ABC method, giving a total of 45 inputs and a total cost of USD 126,351.54, within this group of inputs 8 types of yogurt containers were found. Using the FORECAST PRO TRAC software, the best forecast models were determined. Through the forecast, the variability coefficient (CV) was calculated, an indicator that allows us to choose the inventory management model to be used; obtaining as a result the use of the EOQ model. With the application of this model, it has reached the decrease of orders per month and reducing supply costs.},
 bibtype = {inproceedings},
 author = {Orges, C.A.M. and Morales, D.J.H. and Leyva, L.L.L. and Santos, Y.M. and Granda, I.D.H. and Pérez, I.C.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. This research was developed in a dairy company, with the purpose of providing tools that allow the continuous improvement of supplies necessary for daily production, to ensure the quality of the finished product and customer satisfaction. A Case study was carried out in the dairy company in Cayambe, Ecuador. In order to determine the supply management model, a survey was applied to identify the deficiencies and weaknesses that directly affect the management system within the company. With the help of the management the historical data of 3 years for the classification of the inputs was collected through the ABC method, giving a total of 45 inputs and a total cost of USD 126,351.54, within this group of inputs 8 types of yogurt containers were found. Using the FORECAST PRO TRAC software, the best forecast models were determined. Through the forecast, the variability coefficient (CV) was calculated, an indicator that allows us to choose the inventory management model to be used; obtaining as a result the use of the EOQ model. With the application of this model, it has reached the decrease of orders per month and reducing supply costs.

@inproceedings{
 title = {A linear programming model to optimize the production process in software development},
 type = {inproceedings},
 year = {2018},
 keywords = {Costs,Linear programming,Optimization,Production,SLOC,Software development},
 volume = {2018},
 issue = {SEP},
 websites = {http://ieomsociety.org/dc2018/papers/219.pdf},
 id = {27a1a57c-0c22-3d3a-8a37-a54df90e3730},
 created = {2020-12-09T06:11:18.781Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:03.843Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. In the present work a Linear Programming model to optimize the costs and times incurred in a software development project considering the lines of source code as a metric of the effort made by the group of available programmers was proposed, for the modeling of the problem a limit for the execution budget was assumed, a productivity rate that reflects the real percentage of a programmer's contribution to the development of the project. The acquisition of the data for the model was done through the system called SISCOST, and using surveys and statistics on the salary of the programmers as well as applications such as COCOMO II and SLOCCount to estimate the total Source lines of code of a system. Finally, the optimal amounts of participation of the different types of programmers in software development were determined and the possible implications of implementing the model are analyzed.},
 bibtype = {inproceedings},
 author = {Granda, I.D.H. and Querembas, J.A.C. and Grijalva, C.S.E. and Quishpe, R.M.A. and Leyva, L.L.L. and Orges, C.A.M.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. In the present work a Linear Programming model to optimize the costs and times incurred in a software development project considering the lines of source code as a metric of the effort made by the group of available programmers was proposed, for the modeling of the problem a limit for the execution budget was assumed, a productivity rate that reflects the real percentage of a programmer's contribution to the development of the project. The acquisition of the data for the model was done through the system called SISCOST, and using surveys and statistics on the salary of the programmers as well as applications such as COCOMO II and SLOCCount to estimate the total Source lines of code of a system. Finally, the optimal amounts of participation of the different types of programmers in software development were determined and the possible implications of implementing the model are analyzed.

@inproceedings{
 title = {Lean Manufacturing application in textile industry},
 type = {inproceedings},
 year = {2018},
 keywords = {Efficiency,Lead time,Lean Manufacturing,Manufacturing cells,Productivity,Takt time,Textile industry},
 volume = {2018},
 issue = {JUL},
 websites = {https://www.researchgate.net/profile/Leandro-Lorente/publication/328861132_Lean_Manufacturing_Application_in_Textile_Industry/links/5fea04a645851553a0015d25/Lean-Manufacturing-Application-in-Textile-Industry.pdf},
 id = {a644c9df-d5e6-3414-ba7a-189b17e92936},
 created = {2020-12-09T06:11:18.824Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:03.797Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© IEOM Society International. The main objective of this research is to raise a proposal for the application of Lean Manufacturing tools for the reduction of waste in the textile industry. This paper presents of seeking the theoretical foundation of the philosophy of Lean Manufacturing, followed by a diagnosis was developed in a textile company where the main problem of 31% of non-fulfillment of orders is established, reaching measurements of activities that add value and does not add value, getting to elaborate the current Value Stream Mapping of the situation this company. Finally, the prioritization of the tools with criteria of cost, time, feasibility of the implementation, achieving definition of the proposal of 5S's and Manufacturing Cells. The 5S's Lean Manufacturing Tool, will reduce waste or activities that do not add value to the product. This implies that the cycle time of the cutting process decreases from 4'04" to 3'50", stamping, of 4'24" at 4'16" and packing from 2'40" to 2'36" to himself, the work environment will be improved, from 46% to 87%. By implementing the Manufacturing Cells in the manufacturing process, the cycle time will reduce from 8'28'' /pajamas to 4'55''/pajamas, this implies that the production capacity of the process will increase from 1.080 pajamas for month to 1.964 monthly pajamas, exceeding the customer demand with 23% which will reduce the order failure from 31% to 0%. This will allow the company to fully comply with the 1,589 monthly pajamas demanded by the customer.},
 bibtype = {inproceedings},
 author = {Leyva, L.L.L. and Perugachi, E.P.C. and Piarpuezan, R.V.S. and Orges, C.A.M. and Montenegro, E.P.O. and Burgos, G.},
 booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management}
}

© IEOM Society International. The main objective of this research is to raise a proposal for the application of Lean Manufacturing tools for the reduction of waste in the textile industry. This paper presents of seeking the theoretical foundation of the philosophy of Lean Manufacturing, followed by a diagnosis was developed in a textile company where the main problem of 31% of non-fulfillment of orders is established, reaching measurements of activities that add value and does not add value, getting to elaborate the current Value Stream Mapping of the situation this company. Finally, the prioritization of the tools with criteria of cost, time, feasibility of the implementation, achieving definition of the proposal of 5S's and Manufacturing Cells. The 5S's Lean Manufacturing Tool, will reduce waste or activities that do not add value to the product. This implies that the cycle time of the cutting process decreases from 4'04" to 3'50", stamping, of 4'24" at 4'16" and packing from 2'40" to 2'36" to himself, the work environment will be improved, from 46% to 87%. By implementing the Manufacturing Cells in the manufacturing process, the cycle time will reduce from 8'28'' /pajamas to 4'55''/pajamas, this implies that the production capacity of the process will increase from 1.080 pajamas for month to 1.964 monthly pajamas, exceeding the customer demand with 23% which will reduce the order failure from 31% to 0%. This will allow the company to fully comply with the 1,589 monthly pajamas demanded by the customer.

@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Clustering algorithms,Contraction hierarchies,Free software,K-means,Optimization,University transportation,Vehicle routing},
 pages = {95-107},
 volume = {10870 LNAI},
 websites = {http://link.springer.com/10.1007/978-3-319-92639-1_9},
 id = {4f29bfc6-b247-3061-a6b8-081e4f73585e},
 created = {2020-12-09T06:11:19.349Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.036Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer International Publishing AG, part of Springer Nature 2018. This research work focuses on the study of different models of solution reflected in the literature, which treat the optimization of the routing of vehicles by nodes and the optimal route for the university transport service. With the recent expansion of the facilities of a university institution, the allocation of the routes for the transport of its students, became more complex. As a result, geographic information systems (GIS) tools and operations research methodologies are applied, such as graph theory and vehicular routing problems, to facilitate mobilization and improve the students transport service, as well as optimizing the transfer time and utilization of the available transport units. An optimal route management procedure has been implemented to maximize the level of service of student transport using the K-means clustering algorithm and the method of node contraction hierarchies, with low cost due to the use of free software.},
 bibtype = {inbook},
 author = {Herrera-Granda, Israel D. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H. and Valencia-Chapi, Robert M. and Montero-Santos, Yakcleem and Chicaiza-Vaca, Jorge L. and Castro-Ospina, Andrés E.},
 doi = {10.1007/978-3-319-92639-1_9},
 chapter = {Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorithms},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© Springer International Publishing AG, part of Springer Nature 2018. This research work focuses on the study of different models of solution reflected in the literature, which treat the optimization of the routing of vehicles by nodes and the optimal route for the university transport service. With the recent expansion of the facilities of a university institution, the allocation of the routes for the transport of its students, became more complex. As a result, geographic information systems (GIS) tools and operations research methodologies are applied, such as graph theory and vehicular routing problems, to facilitate mobilization and improve the students transport service, as well as optimizing the transfer time and utilization of the available transport units. An optimal route management procedure has been implemented to maximize the level of service of student transport using the K-means clustering algorithm and the method of node contraction hierarchies, with low cost due to the use of free software.

@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Eigenvectors,Graph-based clustering,Normalized cut clustering,Quadratic forms},
 pages = {318-328},
 volume = {10878 LNCS},
 websites = {http://link.springer.com/10.1007/978-3-319-92537-0_37},
 id = {f38b1229-638a-3b64-9e47-e8bbf86aab57},
 created = {2020-12-09T06:11:19.495Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.307Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer International Publishing AG, part of Springer Nature 2018. Normalized-cut clustering (NCC) is a benchmark graph-based approach for unsupervised data analysis. Since its traditional formulation is a quadratic form subject to orthogonality conditions, it is often solved within an eigenvector-based framework. Nonetheless, in some cases the calculation of eigenvectors is prohibitive or unfeasible due to the involved computational cost – for instance, when dealing with high dimensional data. In this work, we present an overview of recent developments on approaches to solve the NCC problem with no requiring the calculation of eigenvectors. Particularly, heuristic-search and quadratic-formulation-based approaches are studied. Such approaches are elegantly deduced and explained, as well as simple ways to implement them are provided.},
 bibtype = {inbook},
 author = {Lorente-Leyva, Leandro Leonardo and Herrera-Granda, Israel David and Rosero-Montalvo, Paul D. and Ponce-Guevara, Karina L. and Castro-Ospina, Andrés Eduardo and Becerra, Miguel A. and Peluffo-Ordóñez, Diego Hernán and Rodríguez-Sotelo, José Luis},
 doi = {10.1007/978-3-319-92537-0_37},
 chapter = {Developments on Solutions of the Normalized-Cut-Clustering Problem Without Eigenvectors},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

© Springer International Publishing AG, part of Springer Nature 2018. Normalized-cut clustering (NCC) is a benchmark graph-based approach for unsupervised data analysis. Since its traditional formulation is a quadratic form subject to orthogonality conditions, it is often solved within an eigenvector-based framework. Nonetheless, in some cases the calculation of eigenvectors is prohibitive or unfeasible due to the involved computational cost – for instance, when dealing with high dimensional data. In this work, we present an overview of recent developments on approaches to solve the NCC problem with no requiring the calculation of eigenvectors. Particularly, heuristic-search and quadratic-formulation-based approaches are studied. Such approaches are elegantly deduced and explained, as well as simple ways to implement them are provided.

@article{
 title = {Intelligent Adaptation of Axisymmetric Solid Parts in Machining Process Planning by Case Based Reasoning},
 type = {article},
 year = {2017},
 keywords = {CAD/CAPP system,CBR,Cutting schemes,Form features,Geometric information},
 pages = {245-253},
 volume = {10},
 month = {6},
 day = {30},
 id = {bff1ce9c-11ba-37bd-834c-5e7645610bef},
 created = {2020-12-09T06:11:18.548Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-02-23T05:16:47.398Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The goal of this paper is the adaptation of plans of manufacturing processes of Axisymmetric Solid Parts under the approach of Case Based Reasoning (CBR). To this end, a data model for feature-based representation has been developed, which contains the geometric, dimensional and technological information required for the preparation of the one-piece process plan. As a result, an algorithm to generate new parts process plans from a similar plan retrieved from the case base is presented, which is based on the specific information of the Primitive Form Features (PFF) and considers the possible interaction between neighboring PFFs. The computer support of the developed algorithm was implemented in AutoLISP as programming language of the CAD system used and the interface was created in OpenDCL.},
 bibtype = {article},
 author = {García, Alexis and Lancho, Ricardo and Aleaga, Arlys and Rodríguez, Alexis and Leyva, Leonardo},
 doi = {10.22266/ijies2017.0630.27},
 journal = {International Journal of Intelligent Engineering and Systems},
 number = {3}
}

The goal of this paper is the adaptation of plans of manufacturing processes of Axisymmetric Solid Parts under the approach of Case Based Reasoning (CBR). To this end, a data model for feature-based representation has been developed, which contains the geometric, dimensional and technological information required for the preparation of the one-piece process plan. As a result, an algorithm to generate new parts process plans from a similar plan retrieved from the case base is presented, which is based on the specific information of the Primitive Form Features (PFF) and considers the possible interaction between neighboring PFFs. The computer support of the developed algorithm was implemented in AutoLISP as programming language of the CAD system used and the interface was created in OpenDCL.

@article{
 title = {Intelligent Adaptation of Axisymmetric Solid Parts in Machining Process Planning by Case Based Reasoning},
 type = {article},
 year = {2017},
 keywords = {CAD/CAPP Systems,Case Based Reasoning (CBR),Form Features,Technological Routes},
 pages = {245-253},
 volume = {10},
 websites = {http://www.inass.org/2017/2017063027.pdf},
 month = {6},
 day = {30},
 id = {4d81603a-20ba-356e-89b9-587fbaaf6b17},
 created = {2020-12-09T06:11:18.630Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-01-31T16:39:23.476Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2019, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. This research deals with the problem of the technological conception routes in the machining process planning (CAPP) for symmetrical parts with cavities under the approach of Case Based Reasoning (CBR). It includes shaft, bushing and disc type parts because of their frequent use in the metal-mechanical industry. A data model for feature-based representation was created, which contains the geometric, dimensional and technological information required for its elaboration. The technological machining route of a case study was obtained from the adaptation of the route of a prototype piece recovered from a base of cases by means of Artificial Intelligence (AI), based on the peripheral cutting index (PCI-2D) and the index of geometric form (IGF) that is supported by the Feature-based Representation. Its application extends to conventional and CNC technology.},
 bibtype = {article},
 author = {García, Alexis and Lancho, Ricardo and Aleaga, Arlys and Rodríguez, Alexis and Leyva, Leonardo},
 doi = {10.22266/ijies2017.0630.27},
 journal = {International Journal of Intelligent Engineering and Systems},
 number = {3}
}

© 2019, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. This research deals with the problem of the technological conception routes in the machining process planning (CAPP) for symmetrical parts with cavities under the approach of Case Based Reasoning (CBR). It includes shaft, bushing and disc type parts because of their frequent use in the metal-mechanical industry. A data model for feature-based representation was created, which contains the geometric, dimensional and technological information required for its elaboration. The technological machining route of a case study was obtained from the adaptation of the route of a prototype piece recovered from a base of cases by means of Artificial Intelligence (AI), based on the peripheral cutting index (PCI-2D) and the index of geometric form (IGF) that is supported by the Feature-based Representation. Its application extends to conventional and CNC technology.

@inproceedings{
 title = {Ant Colony method for cutting sheet metal parts},
 type = {inproceedings},
 year = {2016},
 pages = {58-63},
 websites = {http://www.iiis.org/CDs2016/CD2016Summer/papers/CA932DN.pdf},
 id = {430d14ba-04d2-36c0-9e39-d31e6ca84bd8},
 created = {2020-12-09T06:11:18.337Z},
 file_attached = {false},
 profile_id = {f4bee9c8-c485-33cf-b9d4-7424ce07c46d},
 last_modified = {2021-03-01T00:51:43.082Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Lastre Aleaga, A.M. and Lorente Leyva, L.L. and Cordovés García, A.},
 booktitle = {CISCI 2016 - Decima Quinta Conferencia Iberoamericana en Sistemas, Cibernetica e Informatica, Decimo Tercer Simposium Iberoamericano en Educacion, Cibernetica e Informatica, SIECI 2016 - Memorias}
}