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\n \n \n\n \n \n \n \n \n \n Exploring the Potential of Genetic Algorithms for Optimizing Academic Schedules at the School of Mechatronic Engineering: Preliminary Results.\n \n \n \n \n\n\n \n Alarcón, J.; Buitrón, S.; Carrillo, A.; Chuquimarca, M.; Ortiz, A.; Guachi, R.; Peluffo-Ordóñez, D., H.; and Guachi-Guachi, L.\n\n\n \n\n\n\n In Florez, H.; and Leon, M., editor(s), Applied Informatics, pages 390-402, 2024. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \n \n![\"Exploring](\"//bibbase.org/img/filetypes/link.svg\"\n\t "\\"Website\\"\n\t")
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\n\n\n@inproceedings{\n title = {Exploring the Potential of Genetic Algorithms for Optimizing Academic Schedules at the School of Mechatronic Engineering: Preliminary Results},\n type = {inproceedings},\n year = {2024},\n pages = {390-402},\n websites = {https://rd.springer.com/chapter/10.1007/978-3-031-46813-1_26},\n publisher = {Springer Nature Switzerland},\n city = {Cham},\n id = {b0217559-38fd-37e7-b83b-a6e6d796ad3c},\n created = {2023-10-23T16:58:05.673Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-10-23T16:58:05.673Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-46813-1_26},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The generation of schedules is a complex challenge, particularly in academic institutions aiming for equitable scheduling. The goal is to achieve fair and balanced schedules that meet the requirements of all parties involved, such as workload, class distribution, shifts, and other relevant criteria. To address this challenge, a genetic algorithm specifically designed for optimal schedule generation has been proposed as a solution. Adjusting genetic algorithm parameters impacts performance, and employing parameter optimization techniques effectively tackles this issue. This work introduces a genetic algorithm for optimal schedule generation, utilizing suitable encoding and operators, and evaluating quality through fitness techniques. Optimization efforts led to reduced execution time, improved solution quality, and positive outcomes like faster execution, fewer generations, increased stability, and convergence to optimal solutions.},\n bibtype = {inproceedings},\n author = {Alarcón, Johan and Buitrón, Samantha and Carrillo, Alexis and Chuquimarca, Mateo and Ortiz, Alexis and Guachi, Robinson and Peluffo-Ordóñez, D H and Guachi-Guachi, Lorena},\n editor = {Florez, Hector and Leon, Marcelo},\n booktitle = {Applied Informatics}\n}\n\n The generation of schedules is a complex challenge, particularly in academic institutions aiming for equitable scheduling. The goal is to achieve fair and balanced schedules that meet the requirements of all parties involved, such as workload, class distribution, shifts, and other relevant criteria. To address this challenge, a genetic algorithm specifically designed for optimal schedule generation has been proposed as a solution. Adjusting genetic algorithm parameters impacts performance, and employing parameter optimization techniques effectively tackles this issue. This work introduces a genetic algorithm for optimal schedule generation, utilizing suitable encoding and operators, and evaluating quality through fitness techniques. Optimization efforts led to reduced execution time, improved solution quality, and positive outcomes like faster execution, fewer generations, increased stability, and convergence to optimal solutions.\n
\n\n\n\n \n\n \n \n \n \n \n \n Joint Exploration of Kernel Functions Potential for Data Representation and Classification: A First Step Toward Interactive Interpretable Dimensionality Reduction.\n \n \n \n \n\n\n \n Aalaila, Y.; Bachchar, I.; Raki, H.; Bamansour, S.; Elhamdi, M.; Benghzial, K.; Ortega-Bustamante, M.; Guachi-Guachi, L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n SN Computer Science, 5(1): 75. 2024.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Joint Exploration of Kernel Functions Potential for Data Representation and Classification: A First Step Toward Interactive Interpretable Dimensionality Reduction},\n type = {article},\n year = {2024},\n pages = {75},\n volume = {5},\n websites = {https://doi.org/10.1007/s42979-023-02405-9},\n id = {82e92157-edee-313a-b479-afc38b380c1d},\n created = {2023-12-12T18:37:08.075Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2024-02-09T17:57:50.195Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n source_type = {JOUR},\n private_publication = {false},\n abstract = {Dimensionality reduction (DR) approaches are often a crucial step in data analysis tasks, particularly for data visualization purposes. DR-based techniques are essentially designed to retain the inherent structure of high-dimensional data in a lower-dimensional space, leading to reduced computational complexity and improved pattern recognition accuracy. Specifically, Kernel Principal Component Analysis (KPCA) is a widely utilized dimensionality reduction technique due to its capability to effectively handle nonlinear data sets. It offers an easily interpretable formulation from both geometric and functional analysis perspectives. However, Kernel PCA relies on free hyperparameters, which are usually tuned in advance. The relationship between these hyperparameters and the structure of the embedded space remains undisclosed. This work presents preliminary steps to explore said relationship by jointly evaluating the data classification and representation abilities. To do so, an interactive visualization framework is introduced. This study highlights the importance of creating interactive interfaces that enable interpretable dimensionality reduction approaches for data visualization and analysis.},\n bibtype = {article},\n author = {Aalaila, Yahya and Bachchar, Ismail and Raki, Hind and Bamansour, Sami and Elhamdi, Mouad and Benghzial, Kaoutar and Ortega-Bustamante, MacArthur and Guachi-Guachi, Lorena and Peluffo-Ordóñez, Diego H},\n doi = {10.1007/s42979-023-02405-9},\n journal = {SN Computer Science},\n number = {1}\n}\n\n Dimensionality reduction (DR) approaches are often a crucial step in data analysis tasks, particularly for data visualization purposes. DR-based techniques are essentially designed to retain the inherent structure of high-dimensional data in a lower-dimensional space, leading to reduced computational complexity and improved pattern recognition accuracy. Specifically, Kernel Principal Component Analysis (KPCA) is a widely utilized dimensionality reduction technique due to its capability to effectively handle nonlinear data sets. It offers an easily interpretable formulation from both geometric and functional analysis perspectives. However, Kernel PCA relies on free hyperparameters, which are usually tuned in advance. The relationship between these hyperparameters and the structure of the embedded space remains undisclosed. This work presents preliminary steps to explore said relationship by jointly evaluating the data classification and representation abilities. To do so, an interactive visualization framework is introduced. This study highlights the importance of creating interactive interfaces that enable interpretable dimensionality reduction approaches for data visualization and analysis.\n
\n\n\n\n \n\n \n \n \n \n \n \n A conceptual framework for the operations planning of the textile supply chains: Insights for sustainable and smart planning in uncertain and dynamic contexts.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Alemany, M., M., E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Computers & Industrial Engineering, 187: 109824. 2024.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@article{\n title = {A conceptual framework for the operations planning of the textile supply chains: Insights for sustainable and smart planning in uncertain and dynamic contexts},\n type = {article},\n year = {2024},\n keywords = {Conceptual framework,Industry 4.0,Literature review,Sustainable,Textile industry,Uncertainty,smart and dynamic operations planning},\n pages = {109824},\n volume = {187},\n websites = {https://www.sciencedirect.com/science/article/pii/S0360835223008483},\n id = {db025270-15cf-3b91-b521-684dc448a627},\n created = {2024-02-08T21:44:48.903Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2024-02-08T21:44:48.903Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {LORENTELEYVA2024109824},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Lorente-Leyva, Leandro L and Alemany, M M E and Peluffo-Ordóñez, Diego H},\n doi = {https://doi.org/10.1016/j.cie.2023.109824},\n journal = {Computers & Industrial Engineering}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Combining AI Tools with Non-Destructive Technologies for Crop-Based Food Safety: A Comprehensive Review.\n \n \n \n \n\n\n \n Raki, H.; Aalaila, Y.; Taktour, A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Foods, 13(1). 2024.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Combining AI Tools with Non-Destructive Technologies for Crop-Based Food Safety: A Comprehensive Review},\n type = {article},\n year = {2024},\n volume = {13},\n websites = {https://www.mdpi.com/2304-8158/13/1/11},\n id = {e553f825-5c76-3c05-bc86-6855392212c0},\n created = {2024-02-09T17:27:05.260Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2024-02-09T17:27:05.260Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {foods13010011},\n source_type = {article},\n private_publication = {false},\n abstract = {On a global scale, food safety and security aspects entail consideration throughout the farm-to-fork continuum, considering food’s supply chain. Generally, the agrifood system is a multiplex network of interconnected features and processes, with a hard predictive rate, where maintaining the food’s safety is an indispensable element and is part of the Sustainable Development Goals (SDGs). It has led the scientific community to develop advanced applied analytical methods, such as machine learning (ML) and deep learning (DL) techniques applied for assessing foodborne diseases. The main objective of this paper is to contribute to the development of the consensus version of ongoing research about the application of Artificial Intelligence (AI) tools in the domain of food-crop safety from an analytical point of view. Writing a comprehensive review for a more specific topic can also be challenging, especially when searching within the literature. To our knowledge, this review is the first to address this issue. This work consisted of conducting a unique and exhaustive study of the literature, using our TriScope Keywords-based Synthesis methodology. All available literature related to our topic was investigated according to our criteria of inclusion and exclusion. The final count of data papers was subject to deep reading and analysis to extract the necessary information to answer our research questions. Although many studies have been conducted, limited attention has been paid to outlining the applications of AI tools combined with analytical strategies for crop-based food safety specifically.},\n bibtype = {article},\n author = {Raki, Hind and Aalaila, Yahya and Taktour, Ayoub and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/foods13010011},\n journal = {Foods},\n number = {1}\n}\n\n On a global scale, food safety and security aspects entail consideration throughout the farm-to-fork continuum, considering food’s supply chain. Generally, the agrifood system is a multiplex network of interconnected features and processes, with a hard predictive rate, where maintaining the food’s safety is an indispensable element and is part of the Sustainable Development Goals (SDGs). It has led the scientific community to develop advanced applied analytical methods, such as machine learning (ML) and deep learning (DL) techniques applied for assessing foodborne diseases. The main objective of this paper is to contribute to the development of the consensus version of ongoing research about the application of Artificial Intelligence (AI) tools in the domain of food-crop safety from an analytical point of view. Writing a comprehensive review for a more specific topic can also be challenging, especially when searching within the literature. To our knowledge, this review is the first to address this issue. This work consisted of conducting a unique and exhaustive study of the literature, using our TriScope Keywords-based Synthesis methodology. All available literature related to our topic was investigated according to our criteria of inclusion and exclusion. The final count of data papers was subject to deep reading and analysis to extract the necessary information to answer our research questions. Although many studies have been conducted, limited attention has been paid to outlining the applications of AI tools combined with analytical strategies for crop-based food safety specifically.\n
\n\n\n\n \n\n \n \n \n \n \n \n Instance Selection Framework for Alzheimer’s Disease Classification Using Multiple Regions of Interest and Atlas Integration.\n \n \n \n \n\n\n \n Castro-Silva., J., A.; Moreno-García., M.; Guachi-Guachi., L.; and Peluffo-Ordóñez., D., H.\n\n\n \n\n\n\n In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM, pages 453-460, 2024. SciTePress\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Instance Selection Framework for Alzheimer’s Disease Classification Using Multiple Regions of Interest and Atlas Integration},\n type = {inproceedings},\n year = {2024},\n pages = {453-460},\n websites = {https://www.scitepress.org/Link.aspx?doi=10.5220/0012469600003654},\n publisher = {SciTePress},\n institution = {INSTICC},\n id = {59cc79f0-24ee-3605-bda9-c66d267bfbe3},\n created = {2024-03-06T14:15:40.341Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2024-03-06T14:15:40.341Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {icpram24},\n source_type = {conference},\n private_publication = {false},\n abstract = {Optimal selection of informative instances from a dataset is critical for constructing accurate predictive models. As databases expand, leveraging instance selection techniques becomes imperative to condense data into a more manageable size. This research unveils a novel framework designed to strategically identify and choose the most informative 2D brain image slices for Alzheimer’s disease classification. Such a framework integrates annotations from multiple regions of interest across multiple atlases. The proposed framework consists of six core components: 1) Atlas merging for ROI annotation and hemisphere separation. 2) Image preprocessing to extract informative slices. 3) Dataset construction to prevent data leakage, select subjects, and split data. 4) Data generation for memory-efficient batches. 5) Model construction for diverse classification training and testing. 6) Weighted ensemble for combining predictions from multiple models with a single learning algorithm. Our instanc e selection framework was applied to construct Transformer-based classification models, demonstrating an overall accuracy of approximately 98.33% in distinguishing between Cognitively Normal and Alzheimer’s cases at the subject level. It exhibited enhancements of 3.68%, 3.01%, 3.62% for sagittal, coronal, and axial planes respectively in comparison with the percentile technique.},\n bibtype = {inproceedings},\n author = {Castro-Silva., Juan A. and Moreno-García., Maria and Guachi-Guachi., Lorena and Peluffo-Ordóñez., Diego H.},\n doi = {10.5220/0012469600003654},\n booktitle = {Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM}\n}\n\n Optimal selection of informative instances from a dataset is critical for constructing accurate predictive models. As databases expand, leveraging instance selection techniques becomes imperative to condense data into a more manageable size. This research unveils a novel framework designed to strategically identify and choose the most informative 2D brain image slices for Alzheimer’s disease classification. Such a framework integrates annotations from multiple regions of interest across multiple atlases. The proposed framework consists of six core components: 1) Atlas merging for ROI annotation and hemisphere separation. 2) Image preprocessing to extract informative slices. 3) Dataset construction to prevent data leakage, select subjects, and split data. 4) Data generation for memory-efficient batches. 5) Model construction for diverse classification training and testing. 6) Weighted ensemble for combining predictions from multiple models with a single learning algorithm. Our instanc e selection framework was applied to construct Transformer-based classification models, demonstrating an overall accuracy of approximately 98.33% in distinguishing between Cognitively Normal and Alzheimer’s cases at the subject level. It exhibited enhancements of 3.68%, 3.01%, 3.62% for sagittal, coronal, and axial planes respectively in comparison with the percentile technique.\n
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\n\n \n \n 2023\n \n \n (21)\n \n \n
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\n \n \n\n \n \n \n \n \n \n A hybrid genetic algorithm for optimizing urban distribution of auto-parts by a vertex routing problem.\n \n \n \n \n\n\n \n Herrera-granda, I., D.; Martín-barreiro, C.; Herrera-granda, E., P.; and Peluffo-ordoñez, D., H.\n\n\n \n\n\n\n REVISTA INVESTIGACION OPERACIONAL. 2023.\n \n\n\n\n
\n\n\n\n \n \n![\"A](\"//bibbase.org/img/filetypes/pdf.svg\"\n\t "\\"Website\\"\n\t")
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\n\n\n@article{\n title = {A hybrid genetic algorithm for optimizing urban distribution of auto-parts by a vertex routing problem},\n type = {article},\n year = {2023},\n keywords = {distribution of auto parts,genetic algorithms,heuristic,urban logistics,vrp},\n websites = {https://rev-inv-ope.pantheonsorbonne.fr/sites/default/files/inline-files/44123-12_author.pdf},\n id = {d387fc78-1cc7-3de4-8eea-a8cae937daa0},\n created = {2021-06-13T01:35:05.137Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-04-30T04:46:54.113Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In the present work, a hybrid algorithm is designed and implemented, by combining genetic-algorithm meta-heuristics, and the nearest neighbor heuristics, aimed at solving the capacited vehicle routing problem with time windows (CVRPTW). The proposed implementation optimizes the distribution for an auto-parts trading company, within the urban perimeter of the city of Quito-Ecuador. By design, a script coded in C# language is developed. Besides, in order to evaluate the quality of the solutions generated by the proposed hybrid algorithm, different instances of the problem are built, by taking small samples from the whole customers’ information. For comparison purposes, the mathematical model of the CVRPTW available in the GAMS optimization software is considered. As well, real instances of the problem are considered, on which the generated routes reaches an improvement up to 20% of the distances traveled by the routes traditionally used in by the case-study company.},\n bibtype = {article},\n author = {Herrera-granda, Israel D and Martín-barreiro, Carlos and Herrera-granda, Erick P and Peluffo-ordoñez, Diego H},\n journal = {REVISTA INVESTIGACION OPERACIONAL}\n}\n\n In the present work, a hybrid algorithm is designed and implemented, by combining genetic-algorithm meta-heuristics, and the nearest neighbor heuristics, aimed at solving the capacited vehicle routing problem with time windows (CVRPTW). The proposed implementation optimizes the distribution for an auto-parts trading company, within the urban perimeter of the city of Quito-Ecuador. By design, a script coded in C# language is developed. Besides, in order to evaluate the quality of the solutions generated by the proposed hybrid algorithm, different instances of the problem are built, by taking small samples from the whole customers’ information. For comparison purposes, the mathematical model of the CVRPTW available in the GAMS optimization software is considered. As well, real instances of the problem are considered, on which the generated routes reaches an improvement up to 20% of the distances traveled by the routes traditionally used in by the case-study company.\n
\n\n\n\n \n\n \n \n \n \n \n \n Positive invariant regions for a modified Van Der Pol equation modeling heart action.\n \n \n \n \n\n\n \n Acosta, A.; Gallo, R.; García, P.; and Peluffo-Ordóñez, D.\n\n\n \n\n\n\n Applied Mathematics and Computation, 442: 127732. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Positive invariant regions for a modified Van Der Pol equation modeling heart action},\n type = {article},\n year = {2023},\n keywords = {Approximate invariant regions,Electrocardiographic signal,Heart action,Van der Pol equation},\n pages = {127732},\n volume = {442},\n websites = {https://www.sciencedirect.com/science/article/pii/S0096300322008001},\n id = {7892f284-45a9-3984-9fb2-b033f955a8f7},\n created = {2022-12-11T12:37:00.580Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-12-11T12:37:00.580Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {ACOSTA2023127732},\n source_type = {article},\n private_publication = {false},\n abstract = {The dynamical characterization of the heart rate is definitely a problem of vital importance. The selection, construction and adjustment of models that reproduce the dynamic behavior of the cardiac muscle, brings us closer to the solution of the usual classification problem in medicine, i.e. decide whether or not a patient belongs to the healthy class of patients. An usual model for this dynamic is often given by a modified Van der Pol model (vdPM), whose parameters are currently optimized with machine learning techniques or evolutionary algorithms. In any of these cases, the proper selection of the initial condition of the parameters drastically reduces the computational cost of the optimization method used. In this work, a strategy to estimate a positively invariant region that contains the periodic orbit, associated with a set of particular parameters of the vdPM considered, is presented. An algorithm is proposed to build the positively invariant region, the numerical results confirm that the vdPM solutions starting within the positively invariant region converge to the periodic orbit. This kind of result allows to reduce the cost of searching for the optimal parameters that represent a real electrocardiographic signal, which in turn, let us reduce the dimensionality of the system allowing the design of more efficient classifiers for these signals.},\n bibtype = {article},\n author = {Acosta, A and Gallo, R and García, P and Peluffo-Ordóñez, D},\n doi = {https://doi.org/10.1016/j.amc.2022.127732},\n journal = {Applied Mathematics and Computation}\n}\n\n The dynamical characterization of the heart rate is definitely a problem of vital importance. The selection, construction and adjustment of models that reproduce the dynamic behavior of the cardiac muscle, brings us closer to the solution of the usual classification problem in medicine, i.e. decide whether or not a patient belongs to the healthy class of patients. An usual model for this dynamic is often given by a modified Van der Pol model (vdPM), whose parameters are currently optimized with machine learning techniques or evolutionary algorithms. In any of these cases, the proper selection of the initial condition of the parameters drastically reduces the computational cost of the optimization method used. In this work, a strategy to estimate a positively invariant region that contains the periodic orbit, associated with a set of particular parameters of the vdPM considered, is presented. An algorithm is proposed to build the positively invariant region, the numerical results confirm that the vdPM solutions starting within the positively invariant region converge to the periodic orbit. This kind of result allows to reduce the cost of searching for the optimal parameters that represent a real electrocardiographic signal, which in turn, let us reduce the dimensionality of the system allowing the design of more efficient classifiers for these signals.\n
\n\n\n\n \n\n \n \n \n \n \n \n Effort Estimation in Agile Software Development: A Systematic Map Study.\n \n \n \n \n\n\n \n Piñeros Rodríguez, C., A.; Sierra Martinez, L., M.; Peluffo Ordoñez, D., H.; and Timana Peña, J., A.\n\n\n \n\n\n\n INGE CUC, 19(1). 1 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Effort Estimation in Agile Software Development: A Systematic Map Study},\n type = {article},\n year = {2023},\n volume = {19},\n websites = {https://revistascientificas.cuc.edu.co/ingecuc/article/view/4420},\n month = {1},\n id = {23e8a854-fd06-3e48-ae4a-62de74c74a0c},\n created = {2023-01-30T19:27:40.141Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-01-30T19:57:52.492Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {pineros2023effortestimation},\n source_type = {article},\n private_publication = {false},\n abstract = {Introduction−Making effort estimation as accurate and suitable for software development projects becomes a fundamental stage to favor its success, which is a difficult task, since the application of these techniques in constant changing agile development projects raises the need to evaluate different methods frequently. Objectives−The objective of this study is to provide a state of the art on techniques of effort estimation in agile software development (ASD), performance evaluation and the drawbacks that arise in its application. Method−A systematic mapping was developed involving the creation of research questions to provide a layout of this study, analysis of related words for the implementation of a search query to obtain related studies, application of exclusion, inclusion, and quality criteria to filter nonrelated studies and finally the organization and extraction of the necessary information from each study. Results−25 studies were selected; the main findings are: the most applied estimation techniques in agile contexts are: Estimation of Story Points (SP) followed by Planning Poker (PP) and Expert Judgment (EJ). The most frequent solutions supported in computational techniques such as: Naive Bayes, Regression Algorithms and Hybrid System; also,the performance evaluation measures Mean Magnitude of Relative Error (MMRE), Prediction Assessment (PRED) and Mean Absolute Error (MAE) have been found to be the most commonly used. Additionally, parameters such as feasibility, experience, and the delivery of expert knowledge, as well as the constant particularity and lack of data in the process of creating models to be applied to a limited number of environments are the challenges that arise the most when estimating software in agile software development (ASD) Conclusions−It has been found there is an increase in the number of articles that address effort estimation in agile development, however, it becomes evident the needto improve the accuracy of the estimation by using estimation techniques supported in machine learning that have been shown to facilitate and improve the performance of this.},\n bibtype = {article},\n author = {Piñeros Rodríguez, Camilo Andrés and Sierra Martinez, Luz Marina and Peluffo Ordoñez, Diego Hernán and Timana Peña, Jimena Andrea},\n doi = {10.17981/ingecuc.19.1.2023.03},\n journal = {INGE CUC},\n number = {1}\n}\n\n Introduction−Making effort estimation as accurate and suitable for software development projects becomes a fundamental stage to favor its success, which is a difficult task, since the application of these techniques in constant changing agile development projects raises the need to evaluate different methods frequently. Objectives−The objective of this study is to provide a state of the art on techniques of effort estimation in agile software development (ASD), performance evaluation and the drawbacks that arise in its application. Method−A systematic mapping was developed involving the creation of research questions to provide a layout of this study, analysis of related words for the implementation of a search query to obtain related studies, application of exclusion, inclusion, and quality criteria to filter nonrelated studies and finally the organization and extraction of the necessary information from each study. Results−25 studies were selected; the main findings are: the most applied estimation techniques in agile contexts are: Estimation of Story Points (SP) followed by Planning Poker (PP) and Expert Judgment (EJ). The most frequent solutions supported in computational techniques such as: Naive Bayes, Regression Algorithms and Hybrid System; also,the performance evaluation measures Mean Magnitude of Relative Error (MMRE), Prediction Assessment (PRED) and Mean Absolute Error (MAE) have been found to be the most commonly used. Additionally, parameters such as feasibility, experience, and the delivery of expert knowledge, as well as the constant particularity and lack of data in the process of creating models to be applied to a limited number of environments are the challenges that arise the most when estimating software in agile software development (ASD) Conclusions−It has been found there is an increase in the number of articles that address effort estimation in agile development, however, it becomes evident the needto improve the accuracy of the estimation by using estimation techniques supported in machine learning that have been shown to facilitate and improve the performance of this.\n
\n\n\n\n \n\n \n \n \n \n \n \n GHG Global Emission Prediction of Synthetic N Fertilizers Using Expectile Regression Techniques.\n \n \n \n \n\n\n \n Benghzial, K.; Raki, H.; Bamansour, S.; Elhamdi, M.; Aalaila, Y.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Atmosphere, 14(2). 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {GHG Global Emission Prediction of Synthetic N Fertilizers Using Expectile Regression Techniques},\n type = {article},\n year = {2023},\n volume = {14},\n websites = {https://www.mdpi.com/2073-4433/14/2/283},\n id = {f1e09260-52ae-3bac-8ad4-7da7e7857381},\n created = {2023-01-31T21:35:14.355Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-01-31T21:35:14.355Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {atmos14020283},\n source_type = {article},\n private_publication = {false},\n abstract = {Agriculture accounts for a large percentage of nitrous oxide (N2O) emissions, mainly due to the misapplication of nitrogen-based fertilizers, leading to an increase in the greenhouse gas (GHG) footprint. These emissions are of a direct nature, released straight into the atmosphere through nitrification and denitrification, or of an indirect nature, mainly through nitrate leaching, runoff, and N2O volatilization processes. N2O emissions are largely ascribed to the agricultural sector, which represents a threat to sustainability and food production, subsequent to the radical contribution to climate change. In this connection, it is crucial to unveil the relationship between synthetic N fertilizer global use and N2O emissions. To this end, we worked on a dataset drawn from a recent study, which estimates direct and indirect N2O emissions according to each country, by the Intergovernmental Panel on Climate Change (IPCC) guidelines. Machine learning tools are considered great explainable techniques when dealing with air quality problems. Hence, our work focuses on expectile regression (ER) based-approaches to predict N2O emissions based on N fertilizer use. In contrast to classical linear regression (LR), this method allows for heteroscedasticity and omits a parametric specification of the underlying distribution. ER provides a complete picture of the target variable’s distribution, especially when the tails are of interest, or in dealing with heavy-tailed distributions. In this work, we applied expectile regression and the kernel expectile regression estimator (KERE) to predict direct and indirect N2O emissions. The results outline both the flexibility and competitiveness of ER-based techniques in regard to the state-of-the-art regression approaches.},\n bibtype = {article},\n author = {Benghzial, Kaoutar and Raki, Hind and Bamansour, Sami and Elhamdi, Mouad and Aalaila, Yahya and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/atmos14020283},\n journal = {Atmosphere},\n number = {2}\n}\n\n Agriculture accounts for a large percentage of nitrous oxide (N2O) emissions, mainly due to the misapplication of nitrogen-based fertilizers, leading to an increase in the greenhouse gas (GHG) footprint. These emissions are of a direct nature, released straight into the atmosphere through nitrification and denitrification, or of an indirect nature, mainly through nitrate leaching, runoff, and N2O volatilization processes. N2O emissions are largely ascribed to the agricultural sector, which represents a threat to sustainability and food production, subsequent to the radical contribution to climate change. In this connection, it is crucial to unveil the relationship between synthetic N fertilizer global use and N2O emissions. To this end, we worked on a dataset drawn from a recent study, which estimates direct and indirect N2O emissions according to each country, by the Intergovernmental Panel on Climate Change (IPCC) guidelines. Machine learning tools are considered great explainable techniques when dealing with air quality problems. Hence, our work focuses on expectile regression (ER) based-approaches to predict N2O emissions based on N fertilizer use. In contrast to classical linear regression (LR), this method allows for heteroscedasticity and omits a parametric specification of the underlying distribution. ER provides a complete picture of the target variable’s distribution, especially when the tails are of interest, or in dealing with heavy-tailed distributions. In this work, we applied expectile regression and the kernel expectile regression estimator (KERE) to predict direct and indirect N2O emissions. The results outline both the flexibility and competitiveness of ER-based techniques in regard to the state-of-the-art regression approaches.\n
\n\n\n\n \n\n \n \n \n \n \n \n Recognition and Classification of Cardiac Arrhythmias Using Discrete Wavelet Transform (DWT) and Machine Learning Techniques.\n \n \n \n \n\n\n \n Ayala-Cucas, H., A.; Mora-Piscal, E., A.; Mayorca-Torres, D.; León-Salas, A., J.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n In Botto-Tobar, M.; Gómez, O., S.; Rosero Miranda, R.; Díaz Cadena, A.; and Luna-Encalada, W., editor(s), Trends in Artificial Intelligence and Computer Engineering, pages 3-15, 2023. Springer Nature Switzerland\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Recognition and Classification of Cardiac Arrhythmias Using Discrete Wavelet Transform (DWT) and Machine Learning Techniques},\n type = {inproceedings},\n year = {2023},\n pages = {3-15},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-25942-5_1},\n publisher = {Springer Nature Switzerland},\n city = {Cham},\n id = {bd0a8d1b-80d2-36dd-900e-28052e660de3},\n created = {2023-02-13T23:10:55.672Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-02-13T23:10:55.672Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-25942-5_1},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Cardiac arrhythmias are heart rhythm problems that usually occur when the electrical impulses coordinated with the heartbeat do not work correctly. For this reason, detecting abnormalities in an electrocardiogram (ECG) plays a vital role in patient follow-up. Due to the presence of noise, the irregularity of the heartbeat, and the nonstationary nature of ECG signals, their interpretation can be difficult, requiring the use of advanced computer systems to support the diagnosis of cardiac disorders. Therefore, the development of assisted ECG analysis systems is a current topic of study, and the main challenge is to achieve adequate accuracy for application in the clinical setting. Therefore, this article describes a software tool for classifying ECG samples into the main classes of cardiac arrhythmias by removing noise from the ECG signal at the preprocessing stage using conventional digital filters; the location of the QRS complex is essential for the identification of the ECG signal. Therefore, the position and amplitude of the R peaks are determined in the segmentation stage. Then the selection of the most relevant features of the ECG signal is performed using the discrete wavelet transform (DWT). The ability of the extracted features to differentiate between different classes of data is tested using machine learning techniques such as k-Nearest Neighbors, Neural Networks, and Decision Trees with 10-fold cross-validation. These methods are evaluated and tested with the MIT-BIH arrhythmia database, achieving the best accuracy of 98.54\\% using the k-Nearest Neighbors classifier.},\n bibtype = {inproceedings},\n author = {Ayala-Cucas, Hermes Andrés and Mora-Piscal, Edison Alexander and Mayorca-Torres, Dagoberto and León-Salas, Alejandro José and Peluffo-Ordoñez, Diego Hernán},\n editor = {Botto-Tobar, Miguel and Gómez, Omar S and Rosero Miranda, Raul and Díaz Cadena, Angela and Luna-Encalada, Washington},\n booktitle = {Trends in Artificial Intelligence and Computer Engineering}\n}\n\n Cardiac arrhythmias are heart rhythm problems that usually occur when the electrical impulses coordinated with the heartbeat do not work correctly. For this reason, detecting abnormalities in an electrocardiogram (ECG) plays a vital role in patient follow-up. Due to the presence of noise, the irregularity of the heartbeat, and the nonstationary nature of ECG signals, their interpretation can be difficult, requiring the use of advanced computer systems to support the diagnosis of cardiac disorders. Therefore, the development of assisted ECG analysis systems is a current topic of study, and the main challenge is to achieve adequate accuracy for application in the clinical setting. Therefore, this article describes a software tool for classifying ECG samples into the main classes of cardiac arrhythmias by removing noise from the ECG signal at the preprocessing stage using conventional digital filters; the location of the QRS complex is essential for the identification of the ECG signal. Therefore, the position and amplitude of the R peaks are determined in the segmentation stage. Then the selection of the most relevant features of the ECG signal is performed using the discrete wavelet transform (DWT). The ability of the extracted features to differentiate between different classes of data is tested using machine learning techniques such as k-Nearest Neighbors, Neural Networks, and Decision Trees with 10-fold cross-validation. These methods are evaluated and tested with the MIT-BIH arrhythmia database, achieving the best accuracy of 98.54\\% using the k-Nearest Neighbors classifier.\n
\n\n\n\n \n\n \n \n \n \n \n \n Neural Networks on Noninvasive Electrocardiographic Imaging Reconstructions: Preliminary Results.\n \n \n \n \n\n\n \n Mayorca-Torres, D.; León-Salas, A., J.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n In Botto-Tobar, M.; Gómez, O., S.; Rosero Miranda, R.; Díaz Cadena, A.; and Luna-Encalada, W., editor(s), Trends in Artificial Intelligence and Computer Engineering, pages 55-63, 2023. Springer Nature Switzerland\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Neural Networks on Noninvasive Electrocardiographic Imaging Reconstructions: Preliminary Results},\n type = {inproceedings},\n year = {2023},\n pages = {55-63},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-25942-5_5},\n publisher = {Springer Nature Switzerland},\n city = {Cham},\n id = {50cc1110-4118-3f46-a3d8-d0189d74521e},\n created = {2023-02-13T23:39:19.516Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-02-13T23:39:19.516Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-25942-5_5},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {In the reverse electrocardiography (ECG) problem, the objective is to reconstruct the heart's electrical activity from a set of body surface potentials by solving the direct model and the geometry of the torso. Over the years, researchers have used various approaches to solve this problem, from direct, iterative, probabilistic, and those based on deep learning. The interest of the latter, among the wide range of techniques, is because the complexity of the problem can be significantly reduced while increasing the precision of the estimation. In this article, we evaluate the performance of a deep learning-based neural network compared to the Tikhonov method of zero order (ZOT), first (FOT), and second (SOT). Preliminary results show an improvement in performance over real data when Pearson's correlation coefficient (CC) and (RMSE) are calculated. The CC's mean value and standard deviation for the proposed method were 0.960 (0.065), well above ZOT, which was 0.864 (0.047).},\n bibtype = {inproceedings},\n author = {Mayorca-Torres, Dagoberto and León-Salas, Alejandro José and Peluffo-Ordoñez, Diego Hernán},\n editor = {Botto-Tobar, Miguel and Gómez, Omar S and Rosero Miranda, Raul and Díaz Cadena, Angela and Luna-Encalada, Washington},\n booktitle = {Trends in Artificial Intelligence and Computer Engineering}\n}\n\n In the reverse electrocardiography (ECG) problem, the objective is to reconstruct the heart's electrical activity from a set of body surface potentials by solving the direct model and the geometry of the torso. Over the years, researchers have used various approaches to solve this problem, from direct, iterative, probabilistic, and those based on deep learning. The interest of the latter, among the wide range of techniques, is because the complexity of the problem can be significantly reduced while increasing the precision of the estimation. In this article, we evaluate the performance of a deep learning-based neural network compared to the Tikhonov method of zero order (ZOT), first (FOT), and second (SOT). Preliminary results show an improvement in performance over real data when Pearson's correlation coefficient (CC) and (RMSE) are calculated. The CC's mean value and standard deviation for the proposed method were 0.960 (0.065), well above ZOT, which was 0.864 (0.047).\n
\n\n\n\n \n\n \n \n \n \n \n \n IoT-ATL : Prototype of a Digital Twin to Simulate Educational Scenarios in the Art and Technology Laboratories at the Departmental Institute of Fine Arts in Cali , Colombia.\n \n \n \n \n\n\n \n Ordóñez-Bolaños, O., A.; Sierra-Martínez, L., M.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Revista de Facultad de Ingeniería UPTC, 32(March): 0-2. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {IoT-ATL : Prototype of a Digital Twin to Simulate Educational Scenarios in the Art and Technology Laboratories at the Departmental Institute of Fine Arts in Cali , Colombia},\n type = {article},\n year = {2023},\n keywords = {Internet of Things,Scrum,agile methodologies,digital twins,virtual simulation},\n pages = {0-2},\n volume = {32},\n websites = {https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15254},\n id = {0a72b9c6-ff16-3ae7-9165-55c156310c0a},\n created = {2023-02-23T09:38:18.843Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-02-23T09:38:35.568Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Digital Twins (DTs) have the potential to revolutionize the manufacturing, construction, maintenance, and control of industrial processes due to their ability to bridge the physical and digital realms. However, creating complex digital concepts requires carefully implementing appropriate methodologies and processes. This study presents a prototype digital twin of the art and technology laboratories at the Departmental Institute of Fine Arts in Cali, Colombia. We employ the Scrum agile development methodology to streamline the design and development process of the IoT-ATL prototype. A three-layer IoT architecture is established; it facilitates mapping the components of the digital twin and the physical elements to be simulated. The IoT-ATL prototype allows students and teachers to interact and learn about the physical state of the laboratory in a digital environment, thus increasing visibility of the availability and use of technological elements in the space. Keywords:},\n bibtype = {article},\n author = {Ordóñez-Bolaños, Oswaldo Andrés and Sierra-Martínez, Luz Marina and Peluffo-Ordóñez, Diego Hernán},\n journal = {Revista de Facultad de Ingeniería UPTC},\n number = {March}\n}\n\n Digital Twins (DTs) have the potential to revolutionize the manufacturing, construction, maintenance, and control of industrial processes due to their ability to bridge the physical and digital realms. However, creating complex digital concepts requires carefully implementing appropriate methodologies and processes. This study presents a prototype digital twin of the art and technology laboratories at the Departmental Institute of Fine Arts in Cali, Colombia. We employ the Scrum agile development methodology to streamline the design and development process of the IoT-ATL prototype. A three-layer IoT architecture is established; it facilitates mapping the components of the digital twin and the physical elements to be simulated. The IoT-ATL prototype allows students and teachers to interact and learn about the physical state of the laboratory in a digital environment, thus increasing visibility of the availability and use of technological elements in the space. Keywords:\n
\n\n\n\n \n\n \n \n \n \n \n \n Condition Monitoring of Wind Turbines : A Case Study of the Gibara II Wind Farm.\n \n \n \n \n\n\n \n Automatisés, S.; Arbella-Feliciano, Y.; Trinchet-Varela, C., A.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Journal Européen des Systèmes Automatisés, 56(2): 329-335. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Condition Monitoring of Wind Turbines : A Case Study of the Gibara II Wind Farm},\n type = {article},\n year = {2023},\n keywords = {condition monitoring,wind turbines,working},\n pages = {329-335},\n volume = {56},\n websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560218},\n id = {edd10552-0fda-3d4c-bb39-aafa5a9bc393},\n created = {2023-06-07T19:47:44.345Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-06-07T19:47:44.345Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The main objective of this study is to investigate the adaptation of wind turbines at the Gibara II Wind Farm in Cuba, which operates in a tropical climate that differs from the typical conditions in which these turbines are designed and manufactured in the northern hemisphere. The study utilizes condition monitoring techniques supported by Big Data acquired through a supervisory control and data acquisition (SCADA) system. By statistically processing normalized databases using multiple linear regression equations, the study establishes mathematical models that characterize the behavior of critical variables such as bearing, oil and winding temperatures, electrical generation, and specific climatic conditions unique to the wind farm under analysis. These models are essential for advancing condition-based maintenance (CBM) practices and developing preventive measures to mitigate functional failures. The significance of this research lies in the historical technical performance of the equipment under investigation, highlighting the importance of addressing the challenges posed by different environmental conditions. The study was conducted using the relevant regulatory technical documentation pertaining to the design of the wind turbines at the Gibara II Wind Farm.},\n bibtype = {article},\n author = {Automatisés, Systèmes and Arbella-Feliciano, Yorley and Trinchet-Varela, Carlos A and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n journal = {Journal Européen des Systèmes Automatisés},\n number = {2}\n}\n\n The main objective of this study is to investigate the adaptation of wind turbines at the Gibara II Wind Farm in Cuba, which operates in a tropical climate that differs from the typical conditions in which these turbines are designed and manufactured in the northern hemisphere. The study utilizes condition monitoring techniques supported by Big Data acquired through a supervisory control and data acquisition (SCADA) system. By statistically processing normalized databases using multiple linear regression equations, the study establishes mathematical models that characterize the behavior of critical variables such as bearing, oil and winding temperatures, electrical generation, and specific climatic conditions unique to the wind farm under analysis. These models are essential for advancing condition-based maintenance (CBM) practices and developing preventive measures to mitigate functional failures. The significance of this research lies in the historical technical performance of the equipment under investigation, highlighting the importance of addressing the challenges posed by different environmental conditions. The study was conducted using the relevant regulatory technical documentation pertaining to the design of the wind turbines at the Gibara II Wind Farm.\n
\n\n\n\n \n\n \n \n \n \n \n \n A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network.\n \n \n \n \n\n\n \n Avilés-Mendoza, K.; Gaibor-León, N., G.; Asanza, V.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Biomimetics, 8(2). 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network},\n type = {article},\n year = {2023},\n volume = {8},\n websites = {https://www.mdpi.com/2313-7673/8/2/255},\n id = {67c065a5-9405-3be2-b975-fa1e24c15789},\n created = {2023-06-17T22:39:24.464Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-06-17T22:39:24.464Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {biomimetics8020255},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Avilés-Mendoza, Karla and Gaibor-León, Neil George and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/biomimetics8020255},\n journal = {Biomimetics},\n number = {2}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Interactive Information Visualization Models: A Systematic Literature Review.\n \n \n \n \n\n\n \n Ortega-Bustamante, M.; Hasperué, W.; Peluffo-Ordóñez, D., H.; Imbaquingo, D.; Raki, H.; Aalaila, Y.; Elhamdi, M.; and Guachi-Guachi, L.\n\n\n \n\n\n\n In Gervasi, O.; Murgante, B.; Taniar, D.; Apduhan, B., O.; Braga, A., C.; Garau, C.; and Stratigea, A., editor(s), Computational Science and Its Applications -- ICCSA 2023, pages 661-676, 2023. Springer Nature Switzerland\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Interactive Information Visualization Models: A Systematic Literature Review},\n type = {inproceedings},\n year = {2023},\n pages = {661-676},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-36805-9_43},\n publisher = {Springer Nature Switzerland},\n city = {Cham},\n id = {aaece7ba-e3f5-355e-b2b8-fd84536daf95},\n created = {2023-07-05T03:17:25.427Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-07-05T03:17:25.427Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-36805-9_43},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Interactive information visualization models aim to make dimensionality reduction (DR) accessible to non-expert users through interactive visualization frameworks. This systematic literature review explores the role of DR and information visualization (IV) techniques in interactive models (IM). We search relevant bibliographic databases, including IEEE Xplore, Springer Link, and Web of Science, for publications from the last five years. We identify 1448 scientific articles, which we then narrow down to 52 after screening and selection. This study addresses three research questions, revealing that the number of articles focused on interactive DR-oriented models has been in the minority in the last five years. However, related topics such as IV techniques or RD methods have increased. Trends are identified in the development of interactive models, as well as in IV techniques and RD methods. For example, researchers are increasingly proposing new DR methods or modifying existing ones rather than relying solely on established techniques. Furthermore, scatter plots have emerged as the predominant option for IV in interactive models, with limited options for customizing the display of raw data and details in application windows. Overall, this review provides insights into the current state of interactive IV models for DR and highlights areas for further research.},\n bibtype = {inproceedings},\n author = {Ortega-Bustamante, MacArthur and Hasperué, Waldo and Peluffo-Ordóñez, Diego H and Imbaquingo, Daisy and Raki, Hind and Aalaila, Yahya and Elhamdi, Mouad and Guachi-Guachi, Lorena},\n editor = {Gervasi, Osvaldo and Murgante, Beniamino and Taniar, David and Apduhan, Bernady O and Braga, Ana Cristina and Garau, Chiara and Stratigea, Anastasia},\n booktitle = {Computational Science and Its Applications -- ICCSA 2023}\n}\n\n Interactive information visualization models aim to make dimensionality reduction (DR) accessible to non-expert users through interactive visualization frameworks. This systematic literature review explores the role of DR and information visualization (IV) techniques in interactive models (IM). We search relevant bibliographic databases, including IEEE Xplore, Springer Link, and Web of Science, for publications from the last five years. We identify 1448 scientific articles, which we then narrow down to 52 after screening and selection. This study addresses three research questions, revealing that the number of articles focused on interactive DR-oriented models has been in the minority in the last five years. However, related topics such as IV techniques or RD methods have increased. Trends are identified in the development of interactive models, as well as in IV techniques and RD methods. For example, researchers are increasingly proposing new DR methods or modifying existing ones rather than relying solely on established techniques. Furthermore, scatter plots have emerged as the predominant option for IV in interactive models, with limited options for customizing the display of raw data and details in application windows. Overall, this review provides insights into the current state of interactive IV models for DR and highlights areas for further research.\n
\n\n\n\n \n\n \n \n \n \n \n \n Construcción de una base de datos no estructurada para procesar datos espirométricos [Building an unstructured database to process spirometric data].\n \n \n \n \n\n\n \n Sierra-Martínez, Luz Marina; Tunubalá-Ramírez, Jorge Alfredo; Ordóñez, D., H., P.\n\n\n \n\n\n\n Revista Ibérica de Sistemas e Tecnologias de Informação, E57: 508 - 521. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Construcción de una base de datos no estructurada para procesar datos espirométricos [Building an unstructured database to process spirometric data]},\n type = {article},\n year = {2023},\n pages = {508 - 521},\n volume = {E57},\n websites = {https://www.proquest.com/openview/e4c408ebe531be18eb89b8e5b66e734b/},\n id = {0e3854ac-e071-3911-83a1-61df054e1f6a},\n created = {2023-07-05T03:34:33.905Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-07-05T03:34:33.905Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Non-SQL databases are becoming an option for information storage, and many healthcare applications are currently relying on this type of storage, given their ease of horizontal growth with low-cost hardware. Spirometric records are a useful tool for monitoring and diagnosing patients with respiratory conditions. Having these records in an easily accessible and easy to grow storage, such as No SQL DBs, favors both the loading and extraction of information for further processing. with machine learning tools that allow the identification, classification or prediction of situations associated with patients. Additionally, this study includes a brief literature review that involves a comparison between RDBs and Non-SQL databases, the most used engines, their performance, and some cases in the health sector, since no similar works for spirometric records to the best knowledge of the authors.},\n bibtype = {article},\n author = {Sierra-Martínez, Luz Marina; Tunubalá-Ramírez, Jorge Alfredo; Ordóñez, Diego H Peluffo.},\n journal = {Revista Ibérica de Sistemas e Tecnologias de Informação}\n}\n\n Non-SQL databases are becoming an option for information storage, and many healthcare applications are currently relying on this type of storage, given their ease of horizontal growth with low-cost hardware. Spirometric records are a useful tool for monitoring and diagnosing patients with respiratory conditions. Having these records in an easily accessible and easy to grow storage, such as No SQL DBs, favors both the loading and extraction of information for further processing. with machine learning tools that allow the identification, classification or prediction of situations associated with patients. Additionally, this study includes a brief literature review that involves a comparison between RDBs and Non-SQL databases, the most used engines, their performance, and some cases in the health sector, since no similar works for spirometric records to the best knowledge of the authors.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Novel Linear-Model-Based Methodology for Predicting the Directional Movement of the Euro-Dollar Exchange Rate.\n \n \n \n \n\n\n \n Argotty-Erazo, M.; Blázquez-Zaballos, A.; Argoty-Eraso, C., A.; Lorente-Leyva, L., L.; Sánchez-Pozo, N., N.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n IEEE Access, 11: 67249-67284. 2023.\n \n\n\n\n
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\n\n\n\n@article{\n title = {A Novel Linear-Model-Based Methodology for Predicting the Directional Movement of the Euro-Dollar Exchange Rate},\n type = {article},\n year = {2023},\n pages = {67249-67284},\n volume = {11},\n websites = {https://ieeexplore.ieee.org/document/10147811},\n id = {0cd92175-c8c7-3b53-a57f-c190956ca69d},\n created = {2023-07-20T23:39:05.243Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-07-20T23:39:05.243Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10147811},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n 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},\n doi = {10.1109/ACCESS.2023.3285082},\n journal = {IEEE Access}\n}\n\n \n\n \n \n \n \n \n \n Edge Artificial Intelligence for Internet of Things Devices: Open Challenges.\n \n \n \n \n\n\n \n Alvear-Puertas, V.; Rosero-Montalvo, P., D.; Félix-López, V.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In de la Iglesia, D., H.; de Paz Santana, J., F.; and López Rivero, A., J., editor(s), New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence, pages 312-319, 2023. Springer Nature Switzerland\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Edge Artificial Intelligence for Internet of Things Devices: Open Challenges},\n type = {inproceedings},\n year = {2023},\n pages = {312-319},\n websites = {https://rd.springer.com/chapter/10.1007/978-3-031-38344-1_30},\n publisher = {Springer Nature Switzerland},\n city = {Cham},\n id = {94374bec-cb66-3c53-a7b3-9ac689d779ae},\n created = {2023-07-23T04:39:48.470Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-07-23T04:39:48.470Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-38344-1_30},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The advent of the Internet of Things (IoT) has witnessed a rapid proliferation of interconnected devices capable of sensing, collecting, and exchanging vast amounts of data. This data deluge has created a pressing need for efficient processing and analysis at the edge of the network, leading to the emergence of Edge Artificial Intelligence (AI) as a promising solution. Edge AI enables intelligent decision-making and real-time analytics on IoT devices, reducing the latency and bandwidth requirements associated with cloud-based processing. This paper aims to provide a comprehensive overview of the open challenges in deploying Edge AI for IoT devices. We identify and discuss key technical and practical challenges that hinder the widespread adoption and optimal utilization of Edge AI in the IoT ecosystem.},\n bibtype = {inproceedings},\n author = {Alvear-Puertas, Vanessa and Rosero-Montalvo, Paul D and Félix-López, Vivian and Peluffo-Ordóñez, Diego H},\n editor = {de la Iglesia, Daniel H and de Paz Santana, Juan F and López Rivero, Alfonso J},\n booktitle = {New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence}\n}\n\n The advent of the Internet of Things (IoT) has witnessed a rapid proliferation of interconnected devices capable of sensing, collecting, and exchanging vast amounts of data. This data deluge has created a pressing need for efficient processing and analysis at the edge of the network, leading to the emergence of Edge Artificial Intelligence (AI) as a promising solution. Edge AI enables intelligent decision-making and real-time analytics on IoT devices, reducing the latency and bandwidth requirements associated with cloud-based processing. This paper aims to provide a comprehensive overview of the open challenges in deploying Edge AI for IoT devices. We identify and discuss key technical and practical challenges that hinder the widespread adoption and optimal utilization of Edge AI in the IoT ecosystem.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Comparison of Monocular Visual SLAM and Visual Odometry Methods Applied to 3D Reconstruction.\n \n \n \n \n\n\n \n Herrera-Granda, E., P.; Torres-Cantero, J., C.; Rosales, A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Applied Sciences, 13(15). 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {A Comparison of Monocular Visual SLAM and Visual Odometry Methods Applied to 3D Reconstruction},\n type = {article},\n year = {2023},\n volume = {13},\n websites = {https://www.mdpi.com/2076-3417/13/15/8837},\n id = {cf231a45-aff7-3e70-a6d6-f4adb7570c5e},\n created = {2023-08-02T21:31:38.340Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-08-02T21:31:38.340Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {app13158837},\n source_type = {article},\n private_publication = {false},\n abstract = {Pure monocular 3D reconstruction is a complex problem that has attracted the research community’s interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion; so, many methods have been proposed. However, most of these methods have not been evaluated on large datasets and under various motion patterns, have not been tested under the same metrics, and most of them have not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine-learning-based methods, and two updates of the best methods to identify the advantages and limitations of each category of the taxonomy and test whether the addition of machine learning or updates on those methods improved them significantly. Thus, we evaluated each algorithm using the TUM-Mono dataset and benchmark, and we performed an inferential statistical analysis to identify the significant differences through its metrics. The results determined that the sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly enhanced the geometric-based methods’ performance from different perspectives.},\n bibtype = {article},\n author = {Herrera-Granda, Erick P and Torres-Cantero, Juan C and Rosales, Andrés and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/app13158837},\n journal = {Applied Sciences},\n number = {15}\n}\n\n Pure monocular 3D reconstruction is a complex problem that has attracted the research community’s interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion; so, many methods have been proposed. However, most of these methods have not been evaluated on large datasets and under various motion patterns, have not been tested under the same metrics, and most of them have not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine-learning-based methods, and two updates of the best methods to identify the advantages and limitations of each category of the taxonomy and test whether the addition of machine learning or updates on those methods improved them significantly. Thus, we evaluated each algorithm using the TUM-Mono dataset and benchmark, and we performed an inferential statistical analysis to identify the significant differences through its metrics. The results determined that the sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly enhanced the geometric-based methods’ performance from different perspectives.\n
\n\n\n\n \n\n \n \n \n \n \n \n Analysis of Oversampling Techniques and Machine Learning Models on Unbalanced Spirometry Data.\n \n \n \n \n\n\n \n Izurieta, R., C.; Sánchez-Pozo, N., N.; Mejía-Ordóñez, J., S.; González-Vergara, J.; Sierra, L., M.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Rocha, Á.; Ferrás, C.; and Ibarra, W., editor(s), Information Technology and Systems, pages 497-506, 2023. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Analysis of Oversampling Techniques and Machine Learning Models on Unbalanced Spirometry Data},\n type = {inproceedings},\n year = {2023},\n pages = {497-506},\n websites = {https://rd.springer.com/chapter/10.1007/978-3-031-33261-6_42},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {b77b87b3-0f6a-3068-b318-facb40ea90bc},\n created = {2023-08-19T20:53:42.473Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-08-19T20:53:42.473Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-33261-6_42},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The use of artificial intelligence in the quest to contribute to human longevity is becoming increasingly common in medical settings, one of these being spirometry. Given the different factors that can deteriorate the pulmonary status, several works aim to establish ways to alert future patients of their potential pulmonary complications. Thus, we carry out a lung age prediction task from spirometry data extracted using a previously developed mobile application. Regarding the imbalanced classes, SMOTE, ADASYN, and Random Oversampling algorithms were compared with different classifier models. The SMOTE and Quadratic Discriminant Analysis combination achieves a 99.12\\% accuracy, 99.09\\% specificity, and 99.91\\% sensitivity. Additionally, we performed an exploratory analysis of deep learning models, demonstrating that multilayer perceptron models, along with feature fusion techniques, achieve higher performances than classical models such as K-Nearest Neighbors or Decision Trees.},\n bibtype = {inproceedings},\n author = {Izurieta, Roberto Castro and Sánchez-Pozo, Nadia N and Mejía-Ordóñez, Juan S and González-Vergara, Juan and Sierra, Luz Marina and Peluffo-Ordóñez, Diego H},\n editor = {Rocha, Álvaro and Ferrás, Carlos and Ibarra, Waldo},\n booktitle = {Information Technology and Systems}\n}\n\n The use of artificial intelligence in the quest to contribute to human longevity is becoming increasingly common in medical settings, one of these being spirometry. Given the different factors that can deteriorate the pulmonary status, several works aim to establish ways to alert future patients of their potential pulmonary complications. Thus, we carry out a lung age prediction task from spirometry data extracted using a previously developed mobile application. Regarding the imbalanced classes, SMOTE, ADASYN, and Random Oversampling algorithms were compared with different classifier models. The SMOTE and Quadratic Discriminant Analysis combination achieves a 99.12\\% accuracy, 99.09\\% specificity, and 99.91\\% sensitivity. Additionally, we performed an exploratory analysis of deep learning models, demonstrating that multilayer perceptron models, along with feature fusion techniques, achieve higher performances than classical models such as K-Nearest Neighbors or Decision Trees.\n
\n\n\n\n \n\n \n \n \n \n \n \n Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology.\n \n \n \n \n\n\n \n Pontón, J., M., P.; Ojeda, V.; Asanza, V.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n International Journal of Advanced Computer Science and Applications, 14(8). 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology},\n type = {article},\n year = {2023},\n volume = {14},\n websites = {http://dx.doi.org/10.14569/IJACSA.2023.0140829},\n publisher = {The Science and Information Organization},\n id = {86dcd3f2-bcec-3964-8bfb-d92b650768c1},\n created = {2023-08-30T20:22:57.931Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-08-30T20:22:57.931Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Pontón2023},\n source_type = {article},\n private_publication = {false},\n abstract = {The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.},\n bibtype = {article},\n author = {Pontón, José M Pereira and Ojeda, Verónica and Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.14569/IJACSA.2023.0140829},\n journal = {International Journal of Advanced Computer Science and Applications},\n number = {8}\n}\n\n The shrimp farming industry in Ecuador, renowned for its shrimp breeding and exportation, faces challenges due to diseases related to variations in abiotic factors during the maturation stage. This is partly attributed to the traditional methods employed in shrimp farms. Consequently, a prototype has been developed for monitoring and controlling abiotic factors using IoT technology. The proposed system consists of three nodes communicating through the LoRa interface. For control purposes, a fuzzy logic system has been implemented that evaluates temperature and dissolved oxygen abiotic factors to determine the state of the aerator, updating the information in the ThingSpeak application. A detailed analysis of equipment energy consumption and the maximum communication range for message transmission and reception was conducted. Subsequently, the monitoring and control system underwent comprehensive testing, including communication with the visualization platform. The results demonstrated significant improvements in system performance. By modifying parameters in the microcontroller, a 2.55-fold increase in battery durability was achieved. The implemented fuzzy logic system enabled effective on/off control of the aerators, showing a corrective trend in response to variations in the analyzed abiotic parameters. The robustness of the LoRa communication interface was evident in urban environments, achieving a distance of up to 1 km without line of sight.\n
\n\n\n\n \n\n \n \n \n \n \n \n Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor.\n \n \n \n \n\n\n \n Alejandro-Sanjines, U.; Maisincho-Jivaja, A.; Asanza, V.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Biomimetics, 8(5). 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor},\n type = {article},\n year = {2023},\n volume = {8},\n websites = {https://www.mdpi.com/2313-7673/8/5/434},\n id = {66aa6072-774d-3a9c-8c16-c027c4659169},\n created = {2023-09-22T18:07:53.553Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-09-22T18:07:53.553Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {biomimetics8050434},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Alejandro-Sanjines, Ulbio and Maisincho-Jivaja, Anthony and Asanza, Victor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/biomimetics8050434},\n journal = {Biomimetics},\n number = {5}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n MILimbEEG: A dataset of EEG signals related to upper and lower limb execution of motor and motor imagery tasks.\n \n \n \n \n\n\n \n Asanza, V.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; Montoya, D.; and Gonzalez, K.\n\n\n \n\n\n\n Data in Brief, 50: 109540. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {MILimbEEG: A dataset of EEG signals related to upper and lower limb execution of motor and motor imagery tasks},\n type = {article},\n year = {2023},\n keywords = {Brain–computer interface,Electroencephalography,Experimental methodology,Motor imagery task,Motor task,OpenBCI},\n pages = {109540},\n volume = {50},\n websites = {https://www.sciencedirect.com/science/article/pii/S2352340923006406},\n id = {96d9c028-3fbb-3e8a-841f-6044063786bd},\n created = {2023-09-22T18:07:53.557Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-09-22T18:07:53.557Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {ASANZA2023109540},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Asanza, Víctor and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Montoya, Daniel and Gonzalez, Kleber},\n doi = {https://doi.org/10.1016/j.dib.2023.109540},\n journal = {Data in Brief}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals.\n \n \n \n \n\n\n \n Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.\n\n\n \n\n\n\n Journal Européen des Systèmes Automatisés, 56(4): 641-649. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals},\n type = {article},\n year = {2023},\n keywords = {artificial,bioelectric signal,electromyography,intelligence,myoelectric prosthesis,neural network,sensor fusion},\n pages = {641-649},\n volume = {56},\n websites = {https://www.iieta.org/journals/jesa/paper/10.18280/jesa.560413},\n id = {f4bf6055-f188-3281-ba6c-a16a7f59d836},\n created = {2023-10-02T16:15:27.725Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-10-02T16:39:16.191Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {TorresK.EspinozaJ.AsanzaV.Lorente-LeyvaL.L.Peluffo-Ordonez2023},\n private_publication = {false},\n abstract = {Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.},\n bibtype = {article},\n author = {Torres, K., Espinoza, J., Asanza, V., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H.},\n journal = {Journal Européen des Systèmes Automatisés},\n number = {4}\n}\n\n Approximately 215,156 people in Ecuador grapple with physical disabilities, of whom nearly half fall within the 30 to 49% disability range, and a considerable number lack limbs. Moreover, there's been a surge in amputation cases, a trend linked to the increasing diabetes prevalence estimated at around 537 million cases by 2021 as per the International Diabetes Federation (IDF). While prosthetic solutions exist, they might incur high costs or offer constrained movement, even when more affordable. Thus, an alternative is proposed: a myoelectric upper limb prosthesis. This prosthesis would be maneuvered through electromyography and pulse oximetry signals, leveraging artificial intelligence methods. Employing a multi-layer neural network model, a structure comprising an input layer, four hidden layers, and an output layer, yields an impressive 93% prediction accuracy for user movement intentions. For AI model training, data from EMG and PPG sensors were recorded and scrutinized, leading to the condensation of classes from four to three. The model was embedded within an ESP32 C3 DevKit-M1 development board, and open-source blueprints facilitated the prosthesis's creation, complemented by supplementary components for electronics integration. The model attains a 93% precision in predicting classes, while the prosthesis's endurance spans approximately three hours and costs $295, equipped to handle diverse lightweight objects.\n
\n\n\n\n \n\n \n \n \n \n \n \n Metodología para la identificación biométrica a partir de señales EEG en múltiples estados emocionales.\n \n \n \n \n\n\n \n Duque-Mejía, C.; Castro, A.; Duque, E.; Serna-Guarín, L.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D.; and Becerra, M., A.\n\n\n \n\n\n\n Revista Ibérica de Sistemas e Tecnologias de Informação, (E62): 281-288. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {Metodología para la identificación biométrica a partir de señales EEG en múltiples estados emocionales},\n type = {article},\n year = {2023},\n pages = {281-288},\n websites = {https://www.proquest.com/docview/2880949468?fromopenview=true&pq-origsite=gscholar},\n publisher = {Associação Ibérica de Sistemas e Tecnologias de Informacao},\n id = {36e530e7-5bd7-31f2-93b3-c88947b50afa},\n created = {2023-11-02T20:55:17.935Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-11-02T20:55:17.935Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {duque2023metodologia},\n source_type = {article},\n private_publication = {false},\n abstract = {Biometric identification is in constant development as well as the systems that violate it, so it is an open field of research that requires new analysis and application of techniques to identify its vulnerabilities and improve its reliability levels. In this work we propose a biometric identification system based on EEG signals in multiple emotional states considering that the underlying dynamics of EEG signals vary according to the emotional state, which may affect the accuracy of classification models. El algoritmo de bosques aleatorios demostró la mayor exactitud (94%) superando los demás algoritmos. 2. Diferentes medidas fueron obtenidas para cada cada una de las señales EEG, a partir usando características derivadas de moving average, linear dynamic systems (LDS), rational asymmetry (RASM), computed differential symmetry (DASM), differential entropy (DE), differential caudality (DCAU), power spectral density (PSD), asymmetry (ASM).},\n bibtype = {article},\n 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},\n journal = {Revista Ibérica de Sistemas e Tecnologias de Informação},\n number = {E62}\n}\n\n Biometric identification is in constant development as well as the systems that violate it, so it is an open field of research that requires new analysis and application of techniques to identify its vulnerabilities and improve its reliability levels. In this work we propose a biometric identification system based on EEG signals in multiple emotional states considering that the underlying dynamics of EEG signals vary according to the emotional state, which may affect the accuracy of classification models. El algoritmo de bosques aleatorios demostró la mayor exactitud (94%) superando los demás algoritmos. 2. Diferentes medidas fueron obtenidas para cada cada una de las señales EEG, a partir usando características derivadas de moving average, linear dynamic systems (LDS), rational asymmetry (RASM), computed differential symmetry (DASM), differential entropy (DE), differential caudality (DCAU), power spectral density (PSD), asymmetry (ASM).\n
\n\n\n\n \n\n \n \n \n \n \n \n A comparative study of Machine Learning-based classification of Tomato fungal diseases: Application of GLCM texture features.\n \n \n \n \n\n\n \n Nyasulu, C.; Diattara, A.; Traore, A.; Ba, C.; Diedhiou, P., M.; Sy, Y.; Raki, H.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Heliyon. 2023.\n \n\n\n\n
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\n\n\n@article{\n title = {A comparative study of Machine Learning-based classification of Tomato fungal diseases: Application of GLCM texture features},\n type = {article},\n year = {2023},\n websites = {https://www.sciencedirect.com/science/article/pii/S2405844023089053},\n publisher = {Elsevier},\n id = {96b04b3f-2f85-3aed-a772-05bdc9925232},\n created = {2023-11-11T22:15:24.543Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-11-11T22:15:24.543Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {nyasulu2023comparative},\n source_type = {article},\n private_publication = {false},\n abstract = {Globally, agriculture remains an important source of food and economic development. Due to various plant diseases, farmers continue to suffer huge yield losses in both quality and quantity. In this study, we explored the potential of using Artificial Neural Networks, K-Nearest Neighbors, Random Forest, and Support Vector Machine to classify tomato fungal leaf diseases: Alternaria, Curvularia, Helminthosporium, and Lasiodiplodi based on Gray Level Co-occurrence Matrix texture features. Small differences between symptoms of these diseases make it difficult to use the naked eye to obtain better results in detecting and distinguishing these diseases. The Artificial Neural Network outperformed other classifiers with an overall accuracy of 94% and average scores of 93.6% for Precision, 93.8% for Recall, and 93.8% for F1-score. Generally, the models confused samples originally belonging to Helminthosporium with Curvularia. The extracted texture features show great potential to classify the different tomato leaf fungal diseases. The results of this study show that texture characteristics of the Gray Level Co-occurrence Matrix play a critical role in the establishment of tomato leaf disease classification systems and can facilitate the implementation of preventive measures by farmers, resulting in enhanced yield quality and quantity.},\n bibtype = {article},\n author = {Nyasulu, Chimango and Diattara, Awa and Traore, Assitan and Ba, Cheikh and Diedhiou, Papa Madiallacké and Sy, Yakhya and Raki, Hind and Peluffo-Ordóñez, Diego Hernán},\n journal = {Heliyon}\n}\n\n Globally, agriculture remains an important source of food and economic development. Due to various plant diseases, farmers continue to suffer huge yield losses in both quality and quantity. In this study, we explored the potential of using Artificial Neural Networks, K-Nearest Neighbors, Random Forest, and Support Vector Machine to classify tomato fungal leaf diseases: Alternaria, Curvularia, Helminthosporium, and Lasiodiplodi based on Gray Level Co-occurrence Matrix texture features. Small differences between symptoms of these diseases make it difficult to use the naked eye to obtain better results in detecting and distinguishing these diseases. The Artificial Neural Network outperformed other classifiers with an overall accuracy of 94% and average scores of 93.6% for Precision, 93.8% for Recall, and 93.8% for F1-score. Generally, the models confused samples originally belonging to Helminthosporium with Curvularia. The extracted texture features show great potential to classify the different tomato leaf fungal diseases. The results of this study show that texture characteristics of the Gray Level Co-occurrence Matrix play a critical role in the establishment of tomato leaf disease classification systems and can facilitate the implementation of preventive measures by farmers, resulting in enhanced yield quality and quantity.\n
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\n \n \n\n \n \n \n \n \n \n Instance Selection on CNNs for Alzheimer’s Disease Classification from MRI.\n \n \n \n \n\n\n \n Castro-Silva., J.; Moreno-García., M.; Guachi-Guachi., L.; and Peluffo-Ordóñez., D.\n\n\n \n\n\n\n In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM,, pages 330-337, 2022. SciTePress\n \n\n\n\n
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\n\n\n\n@inproceedings{\n title = {Instance Selection on CNNs for Alzheimer’s Disease Classification from MRI},\n type = {inproceedings},\n year = {2022},\n pages = {330-337},\n websites = {https://www.scitepress.org/Link.aspx?doi=10.5220/0010900100003122},\n publisher = {SciTePress},\n institution = {INSTICC},\n id = {f807a514-2c97-377a-beae-800b301d4941},\n created = {2022-02-23T01:20:30.603Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-02-23T01:20:30.603Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {icpram22},\n source_type = {conference},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Castro-Silva., J and Moreno-García., M and Guachi-Guachi., Lorena and Peluffo-Ordóñez., D},\n doi = {10.5220/0010900100003122},\n booktitle = {Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM,}\n}\n\n \n\n \n \n \n \n \n \n Parkinson's Disease Diagnosis Through Electroencephalographic Signal Processing and Sub-optimal Feature Extraction.\n \n \n \n \n\n\n \n Pozo-Ruiz, S.; Morocho-Cayamcela, M., E.; Mayorca-Torres, D.; and H. Peluffo-Ordóñez, D.\n\n\n \n\n\n\n In Rocha, Á.; Ferrás, C.; Méndez Porras, A.; and Jimenez Delgado, E., editor(s), Information Technology and Systems, pages 118-127, 2022. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Parkinson's Disease Diagnosis Through Electroencephalographic Signal Processing and Sub-optimal Feature Extraction},\n type = {inproceedings},\n year = {2022},\n pages = {118-127},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-96293-7_12},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {3f5abf4f-8025-3655-a1aa-0ba51ce427d5},\n created = {2022-03-03T22:54:45.784Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-03-03T22:54:45.784Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-96293-7_12},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Parkinson's disease is the second most common neurological disorder after Alzheimer. Several limitations and challenges have arisen when aiming to diagnose this disease. In this regard, a computer-aided diagnosis system is enforced for the early detection of any abnormalities. Prominent research efforts have been developed based on speech and gait analysis; nonetheless, electroencephalographic (EEG)-signal-driven approaches have acquired some interest recently to diagnose an early Parkinson's disease. According to recent studies, the angles and sharpness of brain waves may hold key hints to detect Parkinson's disease. In the present work, an exploratory study over digital signal processing, and machine learning techniques for characterizing and classifying Parkinson-diagnosed EEG signals is conducted; waveform shape, spectral, statistical and non-linear features are taken into account for the present study. The results, without being definitive, propose a suitable set of processing techniques to increase the performance, estimation accuracy, and interpretation of this physiological phenomenon. At the end, it was found that with the characterization performed, k-NN is the classifier which performs better, obtaining a mean accuracy of 86\\% when differentiating Parkinson's disease patients and healthy control subjects.},\n bibtype = {inproceedings},\n author = {Pozo-Ruiz, Santiago and Morocho-Cayamcela, Manuel Eugenio and Mayorca-Torres, Dagoberto and H. Peluffo-Ordóñez, Diego},\n editor = {Rocha, Álvaro and Ferrás, Carlos and Méndez Porras, Abel and Jimenez Delgado, Efren},\n booktitle = {Information Technology and Systems}\n}\n\n Parkinson's disease is the second most common neurological disorder after Alzheimer. Several limitations and challenges have arisen when aiming to diagnose this disease. In this regard, a computer-aided diagnosis system is enforced for the early detection of any abnormalities. Prominent research efforts have been developed based on speech and gait analysis; nonetheless, electroencephalographic (EEG)-signal-driven approaches have acquired some interest recently to diagnose an early Parkinson's disease. According to recent studies, the angles and sharpness of brain waves may hold key hints to detect Parkinson's disease. In the present work, an exploratory study over digital signal processing, and machine learning techniques for characterizing and classifying Parkinson-diagnosed EEG signals is conducted; waveform shape, spectral, statistical and non-linear features are taken into account for the present study. The results, without being definitive, propose a suitable set of processing techniques to increase the performance, estimation accuracy, and interpretation of this physiological phenomenon. At the end, it was found that with the characterization performed, k-NN is the classifier which performs better, obtaining a mean accuracy of 86\\% when differentiating Parkinson's disease patients and healthy control subjects.\n
\n\n\n\n \n\n \n \n \n \n \n \n Identification of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview.\n \n \n \n \n\n\n \n Asanza, V.; Peláez, E.; Loayza, F.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Sensors, 22(5). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {Identification of Lower-Limb Motor Tasks via Brain-Computer Interfaces: A Topical Overview},\n type = {article},\n year = {2022},\n volume = {22},\n websites = {https://www.mdpi.com/1424-8220/22/5/2028},\n id = {cd4aa39b-07c2-304a-91b3-39e35290863e},\n created = {2022-03-05T01:24:01.053Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-03-05T01:24:01.053Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {s22052028},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Asanza, Víctor and Peláez, Enrique and Loayza, Francis and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/s22052028},\n journal = {Sensors},\n number = {5}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; López-Batista, V., F.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Information, 13(5). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications},\n type = {article},\n year = {2022},\n volume = {13},\n websites = {https://www.mdpi.com/2078-2489/13/5/241},\n id = {23ad8fc8-dc19-305c-add3-637d7272d91b},\n created = {2022-05-09T15:28:56.362Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-05-09T15:28:56.362Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {info13050241},\n source_type = {article},\n private_publication = {false},\n abstract = {IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi–Golay and medium filters are appropriate choices for variable sampling rates.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/info13050241},\n journal = {Information},\n number = {5}\n}\n\n IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi–Golay and medium filters are appropriate choices for variable sampling rates.\n
\n\n\n\n \n\n \n \n \n \n \n \n Smart Factory Using Virtual Reality and Online Multi-User: Towards a Metaverse for Experimental Frameworks.\n \n \n \n \n\n\n \n Alpala, L., O.; Quiroga-Parra, D., J.; Torres, J., C.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Applied Sciences, 12(12). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {Smart Factory Using Virtual Reality and Online Multi-User: Towards a Metaverse for Experimental Frameworks},\n type = {article},\n year = {2022},\n volume = {12},\n websites = {https://www.mdpi.com/2076-3417/12/12/6258},\n id = {cf67d7de-c77f-3dad-a366-05b036fc3342},\n created = {2022-06-22T00:22:09.064Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-06-22T00:22:09.064Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {app12126258},\n source_type = {article},\n private_publication = {false},\n abstract = {Virtual reality (VR) has been brought closer to the general public over the past decade as it has become increasingly available for desktop and mobile platforms. As a result, consumer-grade VR may redefine how people learn by creating an engaging “hands-on” training experience. Today, VR applications leverage rich interactivity in a virtual environment without real-world consequences to optimize training programs in companies and educational institutions. Therefore, the main objective of this article was to improve the collaboration and communication practices in 3D virtual worlds with VR and metaverse focused on the educational and productive sector in smart factory. A key premise of our work is that the characteristics of the real environment can be replicated in a virtual world through digital twins, wherein new, configurable, innovative, and valuable ways of working and learning collaboratively can be created using avatar models. To do so, we present a proposal for the development of an experimental framework that constitutes a crucial first step in the process of formalizing collaboration in virtual environments through VR-powered metaverses. The VR system includes functional components, object-oriented configurations, advanced core, interfaces, and an online multi-user system. We present the study of the first application case of the framework with VR in a metaverse, focused on the smart factory, that shows the most relevant technologies of Industry 4.0. Functionality tests were carried out and evaluated with users through usability metrics that showed the satisfactory results of its potential educational and commercial use. Finally, the experimental results show that a commercial software framework for VR games can accelerate the development of experiments in the metaverse to connect users from different parts of the world in real time.},\n bibtype = {article},\n author = {Alpala, Luis Omar and Quiroga-Parra, Darío J and Torres, Juan Carlos and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/app12126258},\n journal = {Applied Sciences},\n number = {12}\n}\n\n Virtual reality (VR) has been brought closer to the general public over the past decade as it has become increasingly available for desktop and mobile platforms. As a result, consumer-grade VR may redefine how people learn by creating an engaging “hands-on” training experience. Today, VR applications leverage rich interactivity in a virtual environment without real-world consequences to optimize training programs in companies and educational institutions. Therefore, the main objective of this article was to improve the collaboration and communication practices in 3D virtual worlds with VR and metaverse focused on the educational and productive sector in smart factory. A key premise of our work is that the characteristics of the real environment can be replicated in a virtual world through digital twins, wherein new, configurable, innovative, and valuable ways of working and learning collaboratively can be created using avatar models. To do so, we present a proposal for the development of an experimental framework that constitutes a crucial first step in the process of formalizing collaboration in virtual environments through VR-powered metaverses. The VR system includes functional components, object-oriented configurations, advanced core, interfaces, and an online multi-user system. We present the study of the first application case of the framework with VR in a metaverse, focused on the smart factory, that shows the most relevant technologies of Industry 4.0. Functionality tests were carried out and evaluated with users through usability metrics that showed the satisfactory results of its potential educational and commercial use. Finally, the experimental results show that a commercial software framework for VR games can accelerate the development of experiments in the metaverse to connect users from different parts of the world in real time.\n
\n\n\n\n \n\n \n \n \n \n \n \n ECG-Based Heartbeat Classification for Arrhythmia Detection Using Artificial Neural Networks.\n \n \n \n \n\n\n \n Cepeda, E.; Sánchez-Pozo, N., N.; Peluffo-Ordóñez, D., H.; González-Vergara, J.; and Almeida-Galárraga, D.\n\n\n \n\n\n\n In Gervasi, O.; Murgante, B.; Hendrix, E., M., T.; Taniar, D.; and Apduhan, B., O., editor(s), Computational Science and Its Applications -- ICCSA 2022, pages 247-259, 2022. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {ECG-Based Heartbeat Classification for Arrhythmia Detection Using Artificial Neural Networks},\n type = {inproceedings},\n year = {2022},\n pages = {247-259},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-10450-3_20},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {6f7eedf2-f5e4-3613-a62e-dbb7ab4d9e12},\n created = {2022-07-16T03:44:07.739Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-07-16T03:44:07.739Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-10450-3_20},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Cardiovascular disease (CVD) has quickly grown in prevalence over the previous decade, becoming the major cause of human morbidity on a global scale. Due to the massive number of ECG data, manual analysis is regarded as a time-consuming, costly and prone to human error task. In the other hand, computational systems based on biomedical signal processing and machine learning techniques might be suited for supporting arrhythmia diagnostic processes, while solving some of those issues. In general, such systems involve five stages: acquisition, preprocessing, segmentation, characterization, and classification. Yet numerous fundamental aspects remain unresolved, including sensitivity to signal fluctuation, accuracy, computing cost, generalizability, and interpretability. In this context, the present study offers a comparative analysis of ECG signal classification using two artificial neural networks created by different machine learning frameworks. The neural nets were built into a pipeline that aims to strike an appropriate balance among signal robustness, variability, and accuracy. The proposed approach reaches up to 99\\% of overall accuracy for each register while keeping the computational cost low.},\n bibtype = {inproceedings},\n author = {Cepeda, Eduardo and Sánchez-Pozo, Nadia N and Peluffo-Ordóñez, Diego H and González-Vergara, Juan and Almeida-Galárraga, Diego},\n editor = {Gervasi, Osvaldo and Murgante, Beniamino and Hendrix, Eligius M T and Taniar, David and Apduhan, Bernady O},\n booktitle = {Computational Science and Its Applications -- ICCSA 2022}\n}\n\n Cardiovascular disease (CVD) has quickly grown in prevalence over the previous decade, becoming the major cause of human morbidity on a global scale. Due to the massive number of ECG data, manual analysis is regarded as a time-consuming, costly and prone to human error task. In the other hand, computational systems based on biomedical signal processing and machine learning techniques might be suited for supporting arrhythmia diagnostic processes, while solving some of those issues. In general, such systems involve five stages: acquisition, preprocessing, segmentation, characterization, and classification. Yet numerous fundamental aspects remain unresolved, including sensitivity to signal fluctuation, accuracy, computing cost, generalizability, and interpretability. In this context, the present study offers a comparative analysis of ECG signal classification using two artificial neural networks created by different machine learning frameworks. The neural nets were built into a pipeline that aims to strike an appropriate balance among signal robustness, variability, and accuracy. The proposed approach reaches up to 99\\% of overall accuracy for each register while keeping the computational cost low.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Computer Vision Model to Identify the Incorrect Use of Face Masks for COVID-19 Awareness.\n \n \n \n \n\n\n \n Crespo, F.; Crespo, A.; Sierra-Martínez, L., M.; Peluffo-Ordóñez, D., H.; and Morocho-Cayamcela, M., E.\n\n\n \n\n\n\n Applied Sciences, 12(14). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {A Computer Vision Model to Identify the Incorrect Use of Face Masks for COVID-19 Awareness},\n type = {article},\n year = {2022},\n volume = {12},\n websites = {https://www.mdpi.com/2076-3417/12/14/6924},\n id = {ce6dafb0-0edd-3bb9-befc-477c66b73aa7},\n created = {2022-07-24T01:29:08.434Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-07-24T01:29:08.434Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {app12146924},\n source_type = {article},\n private_publication = {false},\n abstract = {Face mask detection has become a great challenge in computer vision, demanding the coalition of technology with COVID-19 awareness. Researchers have proposed deep learning models to detect the use of face masks. However, the incorrect use of a face mask can be as harmful as not wearing any protection at all. In this paper, we propose a compound convolutional neural network (CNN) architecture based on two computer vision tasks: object localization to discover faces in images/videos, followed by an image classification CNN to categorize the faces and show if someone is using a face mask correctly, incorrectly, or not at all. The first CNN is built upon RetinaFace, a model to detect faces in images, whereas the second CNN uses a ResNet-18 architecture as a classification backbone. Our model enables an accurate identification of people who are not correctly following the COVID-19 healthcare recommendations on face mask use. To enable further global use of our technology, we have released both the dataset used to train the classification model and our proposed computer vision pipeline to the public, and optimized it for embedded systems deployment.},\n bibtype = {article},\n author = {Crespo, Fabricio and Crespo, Anthony and Sierra-Martínez, Luz Marina and Peluffo-Ordóñez, Diego Hernán and Morocho-Cayamcela, Manuel Eugenio},\n doi = {10.3390/app12146924},\n journal = {Applied Sciences},\n number = {14}\n}\n\n Face mask detection has become a great challenge in computer vision, demanding the coalition of technology with COVID-19 awareness. Researchers have proposed deep learning models to detect the use of face masks. However, the incorrect use of a face mask can be as harmful as not wearing any protection at all. In this paper, we propose a compound convolutional neural network (CNN) architecture based on two computer vision tasks: object localization to discover faces in images/videos, followed by an image classification CNN to categorize the faces and show if someone is using a face mask correctly, incorrectly, or not at all. The first CNN is built upon RetinaFace, a model to detect faces in images, whereas the second CNN uses a ResNet-18 architecture as a classification backbone. Our model enables an accurate identification of people who are not correctly following the COVID-19 healthcare recommendations on face mask use. To enable further global use of our technology, we have released both the dataset used to train the classification model and our proposed computer vision pipeline to the public, and optimized it for embedded systems deployment.\n
\n\n\n\n \n\n \n \n \n \n \n \n Heart Rate Detection using a Piezoelectric Ceramic Sensor: Preliminary results.\n \n \n \n \n\n\n \n E Cepeda; Peluffo-Ordóñez, D., H.; Rosero-Montalvo, P.; Becerra, M., A.; Umaquinga-Criollo, A., C.; and Ramírez., L.\n\n\n \n\n\n\n Bionatura, 7(30). 2022.\n \n\n\n\n
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\n\n\n\n@article{\n title = {Heart Rate Detection using a Piezoelectric Ceramic Sensor: Preliminary results},\n type = {article},\n year = {2022},\n volume = {7},\n websites = {http://revistabionatura.com/2022.07.03.30.html},\n id = {991f2269-76dd-316f-99c7-450837ad576e},\n created = {2022-08-25T05:37:07.776Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-08-25T05:37:07.776Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {bionatura2022},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {E Cepeda, undefined and Peluffo-Ordóñez, D H and Rosero-Montalvo, P and Becerra, M A and Umaquinga-Criollo, A C and Ramírez., L},\n doi = {10.21931/RB/2022.07.03.30},\n journal = {Bionatura},\n number = {30}\n}\n\n \n\n \n \n \n \n \n \n Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach.\n \n \n \n \n\n\n \n Proaño-Guevara, D.; Blanco-Valencia, X.; Rosero-Montalvo, P., D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n International Journal of Interactive Multimedia and Artificial Intelligence, 7(5). 2022.\n \n\n\n\n
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\n\n\n\n@article{\n title = {Electromiographic Signal Processing Using Embedded Artificial Intelligence: An Adaptive Filtering Approach},\n type = {article},\n year = {2022},\n volume = {7},\n websites = {https://www.ijimai.org/journal/bibcite/reference/3162},\n id = {a0c0b007-bf8c-3505-aae8-7f4ebb68e507},\n created = {2022-08-27T03:33:14.839Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-08-27T03:33:14.839Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {ijmai2022},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Proaño-Guevara, Daniel and Blanco-Valencia, Xiomara and Rosero-Montalvo, Paul D and Peluffo-Ordóñez, Diego H},\n doi = {10.9781/ijimai.2022.08.009},\n journal = {International Journal of Interactive Multimedia and Artificial Intelligence},\n number = {5}\n}\n\n \n\n \n \n \n \n \n \n Analysis of OM-Based Literature Reviews on Facility Layout Planning.\n \n \n \n \n\n\n \n Herrera-Granda Israel D.; Alemany, M., M., E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Journal of Scientific & Industrial Research, 81. 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {Analysis of OM-Based Literature Reviews on Facility Layout Planning},\n type = {article},\n year = {2022},\n volume = {81},\n websites = {http://nopr.niscpr.res.in/handle/123456789/60487},\n id = {9676a2a4-d813-38c2-af61-d5c21538d7f3},\n created = {2022-09-08T02:35:51.623Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-09-08T02:40:39.888Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {Article},\n private_publication = {false},\n abstract = {This work consists of a systematized review of the state of the art of reviews for the problem of Facility Layout Planning (FLP) within the Operations Management (OM) field to support the decisions taken for the improvement of the manufacturing and logistics in a factory environment. The first phase begins by defining the search strategies for obtaining the scientific literature, for which we used ten databases. With these, a base of 112 articles was obtained, but after the systematized process was reduced to 32 directly related articles. In the second phase, we executed a Dimensional analysis of these literature review articles employing a quantitative analysis of the sections and subsections of the selected articles. The third phase comprises the identification of gaps and future research lines. Finally, the conclusions obtained from the systematized review process are presented.},\n bibtype = {article},\n author = {Herrera-Granda Israel D., undefined and Alemany, M. M. E. and Peluffo-Ordóñez, Diego H.},\n doi = {10.56042/jsir.v81i09.57607},\n journal = {Journal of Scientific & Industrial Research}\n}\n\n This work consists of a systematized review of the state of the art of reviews for the problem of Facility Layout Planning (FLP) within the Operations Management (OM) field to support the decisions taken for the improvement of the manufacturing and logistics in a factory environment. The first phase begins by defining the search strategies for obtaining the scientific literature, for which we used ten databases. With these, a base of 112 articles was obtained, but after the systematized process was reduced to 32 directly related articles. In the second phase, we executed a Dimensional analysis of these literature review articles employing a quantitative analysis of the sections and subsections of the selected articles. The third phase comprises the identification of gaps and future research lines. Finally, the conclusions obtained from the systematized review process are presented.\n
\n\n\n\n \n\n \n \n \n \n \n \n Intensity-Duration-Frequency Curve for Extreme Rainfall Event Characterization, in the High Tropical Andes.\n \n \n \n \n\n\n \n Escobar-González, D.; S., S., M.; Juan, G.; Bolívar, E.; Zambrano, M.; Darwin, A.; Marcos, V.; Mario, G.; Lahuatte, B.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Water, 14(19). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {Intensity-Duration-Frequency Curve for Extreme Rainfall Event Characterization, in the High Tropical Andes},\n type = {article},\n year = {2022},\n volume = {14},\n websites = {https://www.mdpi.com/2073-4441/14/19/2998},\n id = {3ac0291d-ef7a-31fc-a0bd-60b6456e3fbf},\n created = {2022-09-28T04:37:06.963Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-09-28T04:37:06.963Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {w14192998},\n source_type = {article},\n private_publication = {false},\n abstract = {In fields such as hydrology, meteorology, and civil engineering, the study of extreme precipitation events is useful to prevent rainfall related disasters. A widely-used practice to address such a problem is by using statistical inferences about precipitation intensity, duration and frequency (IDF). Despite of its great usefulness, the selection of the adequate data and methodology to characterize precipitation’s IDF in the urban area of high-altitude Andean cities remains an open issue for practitioners and decision makers. In this sense, the present paper develops an approach to schematically build the IDF curves for a sub-basin of the study case Andean city, Quito–Ecuador. The here-used data holds information from 12 meteorological stations. Then, the IDF curves are obtained by using both a parametrization followed by a Gamma distribution and a 3-parameter cumulative distribution function, also called mnp. Finally, the curve-fitting process is estimated numerically by adjusting the Sherman equation. Results (average R2=0.9) demonstrated that the framework is well-suited for the high-altitude regime. As a noticeable outcome, a novel spatial interpolation-based analysis is introduced, which enabled the identification of extreme rainfall events according to its duration.},\n bibtype = {article},\n author = {Escobar-González, Diego and S., Singaña-Chasi Mélany and Juan, González-Vergara and Bolívar, Erazo and Zambrano, Miguel and Darwin, Acosta and Marcos, Villacís and Mario, Guallpa and Lahuatte, Braulio and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/w14192998},\n journal = {Water},\n number = {19}\n}\n\n In fields such as hydrology, meteorology, and civil engineering, the study of extreme precipitation events is useful to prevent rainfall related disasters. A widely-used practice to address such a problem is by using statistical inferences about precipitation intensity, duration and frequency (IDF). Despite of its great usefulness, the selection of the adequate data and methodology to characterize precipitation’s IDF in the urban area of high-altitude Andean cities remains an open issue for practitioners and decision makers. In this sense, the present paper develops an approach to schematically build the IDF curves for a sub-basin of the study case Andean city, Quito–Ecuador. The here-used data holds information from 12 meteorological stations. Then, the IDF curves are obtained by using both a parametrization followed by a Gamma distribution and a 3-parameter cumulative distribution function, also called mnp. Finally, the curve-fitting process is estimated numerically by adjusting the Sherman equation. Results (average R2=0.9) demonstrated that the framework is well-suited for the high-altitude regime. As a noticeable outcome, a novel spatial interpolation-based analysis is introduced, which enabled the identification of extreme rainfall events according to its duration.\n
\n\n\n\n \n\n \n \n \n \n \n \n Crop Classification Using Deep Learning: A Quick Comparative Study of Modern Approaches.\n \n \n \n \n\n\n \n Raki, H.; González-Vergara, J.; Aalaila, Y.; Elhamdi, M.; Bamansour, S.; Guachi-Guachi, L.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n In Florez, H.; and Gomez, H., editor(s), Applied Informatics, pages 31-44, 2022. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Crop Classification Using Deep Learning: A Quick Comparative Study of Modern Approaches},\n type = {inproceedings},\n year = {2022},\n pages = {31-44},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-19647-8_3},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {26fc8471-8d58-394d-89de-34b3149cc292},\n created = {2022-10-15T21:45:01.937Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-10-15T21:45:01.937Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-19647-8_3},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Automatic crop classification using new technologies is recognized as one of the most important assets in today's smart farming improvement. Investments in technology and innovation are key issues for shaping agricultural productivity as well as the inclusiveness and sustainability of the global agricultural transformation. Digital image processing (DIP) has been widely adopted in this field, by merging Unmanned Aerial Vehicle (UAV) based remote sensing and deep learning (DL) as a powerful tool for crop classification. Despite the wide range of alternatives, the proper selection of a DL approach is still an open and challenging issue. In this work, we carry out an exhaustive performance evaluation of three remarkable and lightweight DL approaches, namely: Visual Geometry Group (VGG), Residual Neural Network (ResNet) and Inception V3, tested on high resolution agriculture crop images dataset. Experimental results show that InceptionV3 outperforms VGG and ResNet in terms of precision (0,92), accuracy (0,97), recall (0,91), AUC (0,98), PCR (0,97), and F1 (0,91).},\n bibtype = {inproceedings},\n author = {Raki, Hind and González-Vergara, Juan and Aalaila, Yahya and Elhamdi, Mouad and Bamansour, Sami and Guachi-Guachi, Lorena and Peluffo-Ordoñez, Diego H},\n editor = {Florez, Hector and Gomez, Henry},\n booktitle = {Applied Informatics}\n}\n\n Automatic crop classification using new technologies is recognized as one of the most important assets in today's smart farming improvement. Investments in technology and innovation are key issues for shaping agricultural productivity as well as the inclusiveness and sustainability of the global agricultural transformation. Digital image processing (DIP) has been widely adopted in this field, by merging Unmanned Aerial Vehicle (UAV) based remote sensing and deep learning (DL) as a powerful tool for crop classification. Despite the wide range of alternatives, the proper selection of a DL approach is still an open and challenging issue. In this work, we carry out an exhaustive performance evaluation of three remarkable and lightweight DL approaches, namely: Visual Geometry Group (VGG), Residual Neural Network (ResNet) and Inception V3, tested on high resolution agriculture crop images dataset. Experimental results show that InceptionV3 outperforms VGG and ResNet in terms of precision (0,92), accuracy (0,97), recall (0,91), AUC (0,98), PCR (0,97), and F1 (0,91).\n
\n\n\n\n \n\n \n \n \n \n \n \n A Genetic Algorithm for Scheduling Laboratory Rooms: A Case Study.\n \n \n \n \n\n\n \n Fuenmayor, R.; Larrea, M.; Moncayo, M.; Moya, E.; Trujillo, S.; Terneus, J.; Guachi, R.; Peluffo-Ordoñez, D., H.; and Guachi-Guachi, L.\n\n\n \n\n\n\n In Florez, H.; and Gomez, H., editor(s), Applied Informatics, pages 3-14, 2022. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A Genetic Algorithm for Scheduling Laboratory Rooms: A Case Study},\n type = {inproceedings},\n year = {2022},\n pages = {3-14},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-19647-8_1},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {17c9fd19-9704-3a2a-a8a8-48d3017305c3},\n created = {2022-10-15T21:50:35.310Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-10-15T21:50:35.310Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-19647-8_1},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Genetic algorithms (GAs) are a great tool for solving optimization problems. Their characteristics and different components based on the principles of biological evolution make these algorithms very robust and efficient in this type of problem. Many research works have presented dedicated solutions to schedule or resource optimization problems in different areas and project types; most of them have adopted GA implementation to find an individual that represents the best solution. Under this conception, in this work, we present a GA with a controlled mutation operator aiming at maintaining a trade-off between diversity and survival of the best individuals of each generation. This modification is supported by an improvement in terms of convergence time, efficiency of the results and the fulfillment of the constraints (of 29\\%, 14.98\\% and 23.33\\% respectively, compared with state-of-the-art GA with a single random mutation operator) to solve the problem of schedule optimization in the use of three laboratory rooms of the Mechatronics Engineering Career of the International University of Ecuador.},\n bibtype = {inproceedings},\n author = {Fuenmayor, Rafael and Larrea, Martín and Moncayo, Mario and Moya, Esteban and Trujillo, Sebastián and Terneus, Juan-Diego and Guachi, Robinson and Peluffo-Ordoñez, Diego H and Guachi-Guachi, Lorena},\n editor = {Florez, Hector and Gomez, Henry},\n booktitle = {Applied Informatics}\n}\n\n Genetic algorithms (GAs) are a great tool for solving optimization problems. Their characteristics and different components based on the principles of biological evolution make these algorithms very robust and efficient in this type of problem. Many research works have presented dedicated solutions to schedule or resource optimization problems in different areas and project types; most of them have adopted GA implementation to find an individual that represents the best solution. Under this conception, in this work, we present a GA with a controlled mutation operator aiming at maintaining a trade-off between diversity and survival of the best individuals of each generation. This modification is supported by an improvement in terms of convergence time, efficiency of the results and the fulfillment of the constraints (of 29\\%, 14.98\\% and 23.33\\% respectively, compared with state-of-the-art GA with a single random mutation operator) to solve the problem of schedule optimization in the use of three laboratory rooms of the Mechatronics Engineering Career of the International University of Ecuador.\n
\n\n\n\n \n\n \n \n \n \n \n \n Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA.\n \n \n \n \n\n\n \n Montesdeoca, G.; Asanza, V.; Chica, K.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In 2022 International Conference on Applied Electronics (AE), pages 1-4, 2022. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Analysis of Sorting Algorithms Using a WSN and Environmental Pollution Data based on FPGA},\n type = {inproceedings},\n year = {2022},\n pages = {1-4},\n websites = {https://ieeexplore.ieee.org/document/9920090},\n id = {1684577b-1b22-322d-82f5-a4a2f1660b4e},\n created = {2022-10-20T14:01:48.425Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-10-20T14:01:48.425Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9920090},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.},\n bibtype = {inproceedings},\n author = {Montesdeoca, Guillermo and Asanza, Víctor and Chica, Kevin and Peluffo-Ordóñez, Diego H.},\n doi = {10.1109/AE54730.2022.9920090},\n booktitle = {2022 International Conference on Applied Electronics (AE)}\n}\n\n Wireless Snesor Network (WSN) based systems with a focus on Internet of Things (IoT) applications generate a large amount of data. Many applications that need to process data in real time make use of microcontroller-based architectures with sequential programming. Systems based on sequential programming can emulate parallelism up to a certain number of instructions, which is not the case with Field Programmable Gate Array (FPGA). The main objective of this work is to monitor a network of 40 CO2 sensors and to perform real-time sorting of all data. In addition, the run time analysis of two sorting algorithms is performed: bubble sort and insertion sort. For this purpose, an FPGA-based architecture is implemented, controlled by a finite state machine(FSM), which executes each of the sorting algorithms. The results show that the insertion sort algorithm is faster than the burbble sort, but consumes more hardware resources in the FPGA.\n
\n\n\n\n \n\n \n \n \n \n \n \n Trilateration-based Indoor Location using Supervised Learning Algorithms.\n \n \n \n \n\n\n \n Landívar, J.; Ormaza, C.; Asanza, V.; Ojeda, V.; Avilés, J., C.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In 2022 International Conference on Applied Electronics (AE), pages 1-6, 2022. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Trilateration-based Indoor Location using Supervised Learning Algorithms},\n type = {inproceedings},\n year = {2022},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9920073},\n id = {424c1095-034f-37a8-8183-1500630ffe47},\n created = {2022-10-20T14:03:23.688Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-10-20T14:07:03.057Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9920073},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The indoor positioning system (IPS) has a wide range of applications, due to the advantages it has over Global Positioning Systems (GPS) in indoor environments. Due to the biosecurity measures established by the World Health Organization (WHO), where the social distancing is provided, being stricter in indoor environments. This work proposes the design of a positioning system based on trilateration. The main objective is to predict the positioning in both the ‘x’ and ‘y’ axis in an area of 8 square meters. For this purpose, 3 Access Points (AP) and a Mobile Device (DM), which works as a raster, have been used. The Received Signal Strength Indication (RSSI) values measured at each AP are the variables used in regression algorithms that predict the x and y position. In this work, 24 regression algorithms have been evaluated, of which the lowest errors obtained are 70.322 [cm] and 30.1508 [cm], for the x and y axes, respectively.},\n bibtype = {inproceedings},\n author = {Landívar, Jerry and Ormaza, Carolina and Asanza, Víctor and Ojeda, Verónica and Avilés, Juan Carlos and Peluffo-Ordóñez, Diego H},\n doi = {10.1109/AE54730.2022.9920073},\n booktitle = {2022 International Conference on Applied Electronics (AE)}\n}\n\n The indoor positioning system (IPS) has a wide range of applications, due to the advantages it has over Global Positioning Systems (GPS) in indoor environments. Due to the biosecurity measures established by the World Health Organization (WHO), where the social distancing is provided, being stricter in indoor environments. This work proposes the design of a positioning system based on trilateration. The main objective is to predict the positioning in both the ‘x’ and ‘y’ axis in an area of 8 square meters. For this purpose, 3 Access Points (AP) and a Mobile Device (DM), which works as a raster, have been used. The Received Signal Strength Indication (RSSI) values measured at each AP are the variables used in regression algorithms that predict the x and y position. In this work, 24 regression algorithms have been evaluated, of which the lowest errors obtained are 70.322 [cm] and 30.1508 [cm], for the x and y axes, respectively.\n
\n\n\n\n \n\n \n \n \n \n \n \n Modelling of Proton Exchange Membrane Fuel Cells with Sinusoidal Approach.\n \n \n \n \n\n\n \n González-Castaño, C.; Aalaila, Y.; Restrepo, C.; Revelo-Fuelagán, J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Membranes, 12(11). 2022.\n \n\n\n\n
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\n\n\n@article{\n title = {Modelling of Proton Exchange Membrane Fuel Cells with Sinusoidal Approach},\n type = {article},\n year = {2022},\n volume = {12},\n websites = {https://www.mdpi.com/2077-0375/12/11/1056},\n id = {970a0c4a-beb2-348a-a6f7-31b57734e947},\n created = {2022-10-31T13:38:07.787Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-10-31T13:38:07.787Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {membranes12111056},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper validates a sinusoidal approach for the proton-exchange membrane fuel cell (PEMFC) model as a supplement to experimental studies. An FC simulation or hardware emulation is necessary for prototype design, testing, and fault diagnosis to reduce the overall cost. For this objective, a sinusoidal model that is capable of accurately estimating the voltage behavior from the operating current value of the DC was developed. The model was 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 study was carried out to evaluate the effectiveness and superiority of the proposed FC Sinusoidal model compared with the Diffusive Global model and the Evolution Strategy.},\n bibtype = {article},\n author = {González-Castaño, Catalina and Aalaila, Yahya and Restrepo, Carlos and Revelo-Fuelagán, Javier and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.3390/membranes12111056},\n journal = {Membranes},\n number = {11}\n}\n\n This paper validates a sinusoidal approach for the proton-exchange membrane fuel cell (PEMFC) model as a supplement to experimental studies. An FC simulation or hardware emulation is necessary for prototype design, testing, and fault diagnosis to reduce the overall cost. For this objective, a sinusoidal model that is capable of accurately estimating the voltage behavior from the operating current value of the DC was developed. The model was 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 study was carried out to evaluate the effectiveness and superiority of the proposed FC Sinusoidal model compared with the Diffusive Global model and the Evolution Strategy.\n
\n\n\n\n \n\n \n \n \n \n \n \n Electrooculography Signals Classification for FPGA-based Human-Computer Interaction.\n \n \n \n \n\n\n \n Asanza, V.; Miranda, J.; Miranda, J.; Rivas, L.; Hernan Peluffo-Ordóñez, D.; Pelaez, E.; Loayza, F.; and Alejandro, O.\n\n\n \n\n\n\n In 2022 IEEE ANDESCON, pages 1-7, 2022. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Electrooculography Signals Classification for FPGA-based Human-Computer Interaction},\n type = {inproceedings},\n year = {2022},\n pages = {1-7},\n websites = {https://ieeexplore.ieee.org/document/9989664},\n id = {95ffdb23-f38c-3c35-a2fe-bc252ecebbb7},\n created = {2022-12-28T22:59:59.641Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-12-28T22:59:59.641Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9989664},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.},\n bibtype = {inproceedings},\n author = {Asanza, Víctor and Miranda, Jesús and Miranda, Jocelyn and Rivas, Leiber and Hernan Peluffo-Ordóñez, Diego and Pelaez, Enrique and Loayza, Francis and Alejandro, Otilia},\n doi = {10.1109/ANDESCON56260.2022.9989664},\n booktitle = {2022 IEEE ANDESCON}\n}\n\n Electrooculographic techniques are applied in the development of new technologies that compensate for the limitations of people with motor disabilities. The algorithms in charge of classifying these signals play a fundamental role, mainly for Human Computer Interfaces (HCI), specially when the machine learning algorithms are implemented in customized hardware like FPGA. In this work, electrooculography data were collected from 10 healthy subjects during six eye movement tasks. Then, the data were filtered and introduced into supervised and unsupervised learning algorithms with six classification labels. The results obtained showed that the SVM algorithm had 93.5% of accuracy, thus being considered the most efficient of the classification algorithms proposed in this work. Then, we develop a custom hardware architecture for real-time implementation of EOG classification model in al FPGA card. We demonstrate the effectiveness of the proposed framework for EOG data classification.\n
\n\n\n\n \n\n \n \n \n \n \n \n Impact of ECG Signal Preprocessing and Filtering on Arrhythmia Classification Using Machine Learning Techniques.\n \n \n \n \n\n\n \n Andrés Ayala-Cucas, H.; Mora-Piscal, E., A.; Mayorca-Torres, D.; Peluffo-Ordoñez, D., H.; and León-Salas, A., J.\n\n\n \n\n\n\n In Bicharra Garcia, A., C.; Ferro, M.; and Rodríguez Ribón, J., C., editor(s), Advances in Artificial Intelligence -- IBERAMIA 2022, pages 27-40, 2022. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Impact of ECG Signal Preprocessing and Filtering on Arrhythmia Classification Using Machine Learning Techniques},\n type = {inproceedings},\n year = {2022},\n pages = {27-40},\n websites = {https://link.springer.com/chapter/10.1007/978-3-031-22419-5_3},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {58ee6029-be62-36b2-a17b-58c09d879c27},\n created = {2023-01-04T00:03:18.949Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2023-01-04T00:03:18.949Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-031-22419-5_3},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Cardiac arrhythmias are heartbeat disorders in which the electrical impulses that coordinate the cardiac cycle malfunction. The heart's electrical activity is recorded using electrocardiography (ECG), a non-invasive method that helps diagnose several cardiovascular diseases. However, interpretation of ECG signals can be difficult due to the presence of noise, the irregularity of the heartbeat, and their nonstationary nature. Hence, the use of computational systems is required to support the diagnosis of cardiac arrhythmias. The main challenge in developing AI-assisted ECG systems is achieving accuracies suitable for application in clinical settings. Therefore, this paper introduces a software tool for classifying cardiac arrhythmias in ECG recordings that uses filtering, segmentation, and feature extraction of the QRS interval. We use the MIT-BIH Arrhythmia Database, which has 48 records of five different types of arrhythmias. We evaluate the data using supervised machine learning techniques such as k-Nearest Neighbors (KNN), Random Forest (RF), Multilayer Perceptron (MLP), and the Naive Bayesian classifier. This paper shows the impact of selecting and employing filtering and feature extraction methods on the performance of supervised machine learning algorithms compared with benchmark approaches.},\n bibtype = {inproceedings},\n author = {Andrés Ayala-Cucas, Hermes and Mora-Piscal, Edison Alexander and Mayorca-Torres, Dagoberto and Peluffo-Ordoñez, Diego Hernán and León-Salas, Alejandro J},\n editor = {Bicharra Garcia, Ana Cristina and Ferro, Mariza and Rodríguez Ribón, Julio Cesar},\n booktitle = {Advances in Artificial Intelligence -- IBERAMIA 2022}\n}\n\n Cardiac arrhythmias are heartbeat disorders in which the electrical impulses that coordinate the cardiac cycle malfunction. The heart's electrical activity is recorded using electrocardiography (ECG), a non-invasive method that helps diagnose several cardiovascular diseases. However, interpretation of ECG signals can be difficult due to the presence of noise, the irregularity of the heartbeat, and their nonstationary nature. Hence, the use of computational systems is required to support the diagnosis of cardiac arrhythmias. The main challenge in developing AI-assisted ECG systems is achieving accuracies suitable for application in clinical settings. Therefore, this paper introduces a software tool for classifying cardiac arrhythmias in ECG recordings that uses filtering, segmentation, and feature extraction of the QRS interval. We use the MIT-BIH Arrhythmia Database, which has 48 records of five different types of arrhythmias. We evaluate the data using supervised machine learning techniques such as k-Nearest Neighbors (KNN), Random Forest (RF), Multilayer Perceptron (MLP), and the Naive Bayesian classifier. This paper shows the impact of selecting and employing filtering and feature extraction methods on the performance of supervised machine learning algorithms compared with benchmark approaches.\n
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\n \n \n\n \n \n \n \n \n \n Enhanced Convolutional-Neural-Network Architecture for Crop Classification.\n \n \n \n \n\n\n \n Moreno-revelo, M., Y.; Guachi-guachi, L.; Gómez-mendoza, J., B.; Revelo-fuelagán, J.; and Peluffo-ordóñez, D., H.\n\n\n \n\n\n\n Applied Sciences,1-23. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Enhanced Convolutional-Neural-Network Architecture for Crop Classification},\n type = {article},\n year = {2021},\n pages = {1-23},\n websites = {https://www.mdpi.com/2076-3417/11/9/4292},\n id = {81e44ece-1c1b-3fa2-a5ea-ce619122cb98},\n created = {2021-05-10T23:31:45.506Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-11T19:59:24.988Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Automatic crop identification and monitoring is a key element in enhancing food production processes as well as diminishing the related environmental impact. Although several efficient deep learning techniques have emerged in the field of multispectral imagery analysis, the crop classification problem still needs more accurate solutions. This work introduces a competitive methodology for crop classification from multispectral satellite imagery mainly using an enhanced 2D convolutional neural network (2D-CNN) designed at a smaller-scale architecture, as well as a novel post-processing step. The proposed methodology contains four steps: image stacking, patch extraction, classification model design (based on a 2D-CNN architecture), and post-processing. First, the images are stacked to increase the number of features. Second, the input images are split into patches and fed into the 2D-CNN model. Then, the 2D-CNN model is constructed within a small-scale framework, and properly trained to recognize 10 different types of crops. Finally, a post-processing step is performed in order to reduce the classification error caused by lower-spatial-resolution images. Experiments were carried over the so-named Campo Verde database, which consists of a set of satellite images captured by Landsat and Sentinel satellites from the municipality of Campo Verde, Brazil. In contrast to the maximum accuracy values reached by remarkable works reported in the literature (amounting to an overall accuracy of about 81%, a f1 score of 75.89%, and average accuracy of 73.35%), the proposed methodology achieves a competitive overall accuracy of 81.20%, a f1 score of 75.89%, and an average accuracy of 88.72% when classifying 10 different crops, while ensuring an adequate trade-off between the number of multiply-accumulate operations (MACs) and accuracy. Furthermore, given its ability to effectively classify patches from two image sequences, this methodology may result appealing for other real-world applications, such as the classification of urban materials.},\n bibtype = {article},\n author = {Moreno-revelo, Mónica Y and Guachi-guachi, Lorena and Gómez-mendoza, Juan Bernardo and Revelo-fuelagán, Javier and Peluffo-ordóñez, Diego H},\n journal = {Applied Sciences}\n}\n\n Automatic crop identification and monitoring is a key element in enhancing food production processes as well as diminishing the related environmental impact. Although several efficient deep learning techniques have emerged in the field of multispectral imagery analysis, the crop classification problem still needs more accurate solutions. This work introduces a competitive methodology for crop classification from multispectral satellite imagery mainly using an enhanced 2D convolutional neural network (2D-CNN) designed at a smaller-scale architecture, as well as a novel post-processing step. The proposed methodology contains four steps: image stacking, patch extraction, classification model design (based on a 2D-CNN architecture), and post-processing. First, the images are stacked to increase the number of features. Second, the input images are split into patches and fed into the 2D-CNN model. Then, the 2D-CNN model is constructed within a small-scale framework, and properly trained to recognize 10 different types of crops. Finally, a post-processing step is performed in order to reduce the classification error caused by lower-spatial-resolution images. Experiments were carried over the so-named Campo Verde database, which consists of a set of satellite images captured by Landsat and Sentinel satellites from the municipality of Campo Verde, Brazil. In contrast to the maximum accuracy values reached by remarkable works reported in the literature (amounting to an overall accuracy of about 81%, a f1 score of 75.89%, and average accuracy of 73.35%), the proposed methodology achieves a competitive overall accuracy of 81.20%, a f1 score of 75.89%, and an average accuracy of 88.72% when classifying 10 different crops, while ensuring an adequate trade-off between the number of multiply-accumulate operations (MACs) and accuracy. Furthermore, given its ability to effectively classify patches from two image sequences, this methodology may result appealing for other real-world applications, such as the classification of urban materials.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Brief Review on Instance Selection Based on Condensed Nearest Neighbors for Data Classification Tasks.\n \n \n \n \n\n\n \n Fernández-Fernández, Y.; Peluffo-Ordóñez, D., H.; Umaquinga-Criollo, A., C.; Lorente-Leyva, L., L.; and Cabrera-Alvarez, E., N.\n\n\n \n\n\n\n In Bindhu, V.; Tavares, J., M., R., S.; Boulogeorgos, A., A.; and Vuppalapati, C., editor(s), International Conference on Communication, Computing and Electronics Systems, pages 313-324, 2021. Springer Singapore\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A Brief Review on Instance Selection Based on Condensed Nearest Neighbors for Data Classification Tasks},\n type = {inproceedings},\n year = {2021},\n pages = {313-324},\n websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_23},\n publisher = {Springer Singapore},\n city = {Singapore},\n id = {5dbf5acc-279b-3744-843c-c05d86dcce9e},\n created = {2021-05-10T23:31:45.938Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.938Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-981-33-4909-4_23},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n author = {Fernández-Fernández, Yasmany and Peluffo-Ordóñez, Diego H and Umaquinga-Criollo, Ana C and Lorente-Leyva, Leandro L and Cabrera-Alvarez, Elia N},\n editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},\n booktitle = {International Conference on Communication, Computing and Electronics Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Evaluation of Working Temperature in Wind Turbine Bearings by Simulation of Lubricant Level.\n \n \n \n \n\n\n \n Feliciano, Y., A.; Varela, C., A., T.; Guativas, J., A., V.; Lorente-leyva, L., L.; and Peluffo-ordóñez, D., H.\n\n\n \n\n\n\n IIETA, 16(1): 99-104. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Evaluation of Working Temperature in Wind Turbine Bearings by Simulation of Lubricant Level},\n type = {article},\n year = {2021},\n keywords = {bearing,cfd,heat,lubricant,simulation,wind turbines,working temperature},\n pages = {99-104},\n volume = {16},\n websites = {http://www.iieta.org/journals/ijdne/paper/10.18280/ijdne.160113},\n id = {f8c53a90-bd0e-3969-a272-7d19afb25a79},\n created = {2021-05-10T23:31:46.271Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.271Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Feliciano, Yorley Arbella and Varela, Carlos A Trinchet and Guativas, Javier A Vargas and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego H},\n journal = {IIETA},\n number = {1}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; López-Batista, V., F.; Arciniega-Rocha, R.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Logic Journal of the IGPL. 2 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study},\n type = {article},\n year = {2021},\n websites = {https://academic.oup.com/jigpal/advance-article/doi/10.1093/jigpal/jzab005/6133990},\n month = {2},\n day = {13},\n id = {1542fff9-c769-35ee-9c4f-15f08b5835e5},\n created = {2021-05-10T23:31:46.701Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.701Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2021},\n private_publication = {false},\n abstract = {Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D and López-Batista, Vivian F and Arciniega-Rocha, Ricardo and Peluffo-Ordóñez, Diego H},\n doi = {10.1093/jigpal/jzab005},\n journal = {Logic Journal of the IGPL}\n}\n\n Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.\n
\n\n\n\n \n\n \n \n \n \n \n \n An Interactive Framework to Compare Multi-criteria Optimization Algorithms: Preliminary Results on NSGA-II and MOPSO.\n \n \n \n \n\n\n \n Dorado-Sevilla, D., F.; Peluffo-Ordóñez, D., H.; Lorente-Leyva, L., L.; Herrera-Granda, E., P.; and Herrera-Granda, I., D.\n\n\n \n\n\n\n In Bindhu, V.; Tavares, J., M., R., S.; Boulogeorgos, A., A.; and Vuppalapati, C., editor(s), International Conference on Communication, Computing and Electronics Systems, pages 61-76, 2021. Springer Singapore\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {An Interactive Framework to Compare Multi-criteria Optimization Algorithms: Preliminary Results on NSGA-II and MOPSO},\n type = {inproceedings},\n year = {2021},\n pages = {61-76},\n websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_5},\n publisher = {Springer Singapore},\n city = {Singapore},\n id = {49621a2a-4aaa-30b2-a1b6-76b4166efefb},\n created = {2021-05-10T23:31:47.064Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.064Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-981-33-4909-4_5},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n 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},\n editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},\n booktitle = {International Conference on Communication, Computing and Electronics Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Overview on kernels for least-squares support-vector-macihine-based clustering: explaining kernel expectral clustering.\n \n \n \n \n\n\n \n Fernández, Y.; Marrufo, I.; Paez, M., A.; Umaquinga-Criollo, A., C.; Rosero, P., D.; and Peluffo-Ordóñez, H., D.\n\n\n \n\n\n\n REVISTA INVESTIGACION OPERACIONAL. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Overview on kernels for least-squares support-vector-macihine-based clustering: explaining kernel expectral clustering.},\n type = {article},\n year = {2021},\n keywords = {clustering,kernel principal component,kernel spectral clustering ksc,support vector machine,svm},\n websites = {https://rev-inv-ope.pantheonsorbonne.fr/sites/default/files/inline-files/42121-10.pdf},\n id = {78aa5cc8-f9aa-33a0-a835-d36779bcbb13},\n created = {2021-05-10T23:31:47.066Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.066Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Fernandez2021},\n private_publication = {false},\n abstract = {This letter presents an overview on some remarkable basics on kernels as well as the formulation of a clustering approach based on least-squares support vector machines. Specifically, the method known as kernel spectral clustering (KSC) is of interest. We explore the links between KSC and a weighted version of kernel principal component analysis (WKPCA). Also, we study the solution of the KSC problem by means of a primal-dual scheme. All mathematical developments are carried out following an entirely matrix formulation. As a result, in addition to the elegant KSC formulation, important insights and hints about the use and design of kernel-based approaches for clustering are provided.},\n bibtype = {article},\n author = {Fernández, Y. and Marrufo, I. and Paez, M. A. and Umaquinga-Criollo, A. C. and Rosero, P. D. and Peluffo-Ordóñez, H. D.},\n journal = {REVISTA INVESTIGACION OPERACIONAL}\n}\n\n This letter presents an overview on some remarkable basics on kernels as well as the formulation of a clustering approach based on least-squares support vector machines. Specifically, the method known as kernel spectral clustering (KSC) is of interest. We explore the links between KSC and a weighted version of kernel principal component analysis (WKPCA). Also, we study the solution of the KSC problem by means of a primal-dual scheme. All mathematical developments are carried out following an entirely matrix formulation. As a result, in addition to the elegant KSC formulation, important insights and hints about the use and design of kernel-based approaches for clustering are provided.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Dynamic Programming Approach for Power Curtailment Decision Making on PV Systems.\n \n \n \n \n\n\n \n Fernández-Fernández, Y.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; and Álvarez, E., N., C.\n\n\n \n\n\n\n In Bindhu, V.; Tavares, J., M., R., S.; Boulogeorgos, A., A.; and Vuppalapati, C., editor(s), International Conference on Communication, Computing and Electronics Systems, pages 77-86, 2021. Springer Singapore\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A Dynamic Programming Approach for Power Curtailment Decision Making on PV Systems},\n type = {inproceedings},\n year = {2021},\n pages = {77-86},\n websites = {https://link.springer.com/chapter/10.1007/978-981-33-4909-4_6},\n publisher = {Springer Singapore},\n city = {Singapore},\n id = {5b848e4e-c592-3f10-8e3f-e06c15969819},\n created = {2021-05-10T23:31:47.151Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.151Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-981-33-4909-4_6},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n author = {Fernández-Fernández, Yasmany and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Álvarez, Elia N Cabrera},\n editor = {Bindhu, V and Tavares, João Manuel R S and Boulogeorgos, Alexandros-Apostolos A and Vuppalapati, Chandrasekar},\n booktitle = {International Conference on Communication, Computing and Electronics Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas].\n \n \n \n \n\n\n \n Vargas-Muñoz, A., M.; Chamorro-Sangoquiza, D., C.; Umaquinga-Criollo, A., C.; Rosero-Montalvo, P., D.; Becerra, M., A.; Peluffo-Ordóñez, D., H.; and Revelo-Fuelagán, E., J.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2021(E40): 470-479. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Design of a low computational cost prototype for cardiac arrhythmia detection [Diseño de un prototipo de bajo coste computacional para detección de arritmias cardiacas]},\n type = {article},\n year = {2021},\n pages = {470-479},\n volume = {2021},\n websites = {https://search.proquest.com/openview/d9dffd8a726c99f54a47adaf372e13b8/1?pq-origsite=gscholar&cbl=1006393},\n id = {8916a7b5-6e57-3c2d-9b8e-9b41005e76c4},\n created = {2021-05-10T23:31:47.572Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.572Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Vargas-Muñoz2021470},\n source_type = {article},\n notes = {cited By 0},\n private_publication = {false},\n abstract = {This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.},\n bibtype = {article},\n author = {Vargas-Muñoz, A M and Chamorro-Sangoquiza, D C and Umaquinga-Criollo, A C and Rosero-Montalvo, P D and Becerra, M A and Peluffo-Ordóñez, D H and Revelo-Fuelagán, E J},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},\n number = {E40}\n}\n\n This research presents the design of a prototype for the detection of cardiac arrhythmias that incorporates an embedded low-cost computational system in an environment of limited computational resources capable of analyzing characteristics of the QRS complexes. To do this, a strategy for classifying normal and pathological heart beats is developed in long-term electrocardiographic recordings (Holter), which are representative waves of the beat and their analysis allows identifying ventricular arrhythmias. For the development of this initial prototype, it is found that the use of the k nearest neighbors (k-NN) algorithm together with a stage of selection of variables from the training set is a good alternative and represents an important contribution of this work to experimental level. The experiments were carried out on the basis of cardiac arrhythmia data from the Massachusetts Institute of Technology (MIT). The results are satisfactory and promising. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.\n
\n\n\n\n \n\n \n \n \n \n \n \n Demand Forecasting for Textile Products Using Statistical Analysis and Machine Learning Algorithms.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Alemany, M., M., E.; Peluffo-Ordóñez, D., H.; and Araujo, R., A.\n\n\n \n\n\n\n In Nguyen, N., T.; Chittayasothorn, S.; Niyato, D.; and Trawiński, B., editor(s), Intelligent Information and Database Systems, pages 181-194, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Demand Forecasting for Textile Products Using Statistical Analysis and Machine Learning Algorithms},\n type = {inproceedings},\n year = {2021},\n pages = {181-194},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-73280-6_15},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {3adbd4fc-40d1-39b7-b75c-cc617553c7a2},\n created = {2021-05-10T23:31:47.640Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.640Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {leyva2021demandforecasting},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n author = {Lorente-Leyva, Leandro L and Alemany, M M E and Peluffo-Ordóñez, Diego H and Araujo, Roberth A},\n editor = {Nguyen, Ngoc Thanh and Chittayasothorn, Suphamit and Niyato, Dusit and Trawiński, Bogdan},\n booktitle = {Intelligent Information and Database Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n An MPPT Strategy Based on a Surface-Based Polynomial Fitting for Solar Photovoltaic Systems Using Real-Time Hardware.\n \n \n \n \n\n\n \n González-Castaño, C.; Lorente-Leyva, L., L.; Muñoz, J.; Restrepo, C.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Electronics, 10(2): 206. 1 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {An MPPT Strategy Based on a Surface-Based Polynomial Fitting for Solar Photovoltaic Systems Using Real-Time Hardware},\n type = {article},\n year = {2021},\n pages = {206},\n volume = {10},\n websites = {https://www.mdpi.com/2079-9292/10/2/206},\n month = {1},\n day = {17},\n id = {8463aee6-3d46-3462-b127-fc40f029b83c},\n created = {2021-05-10T23:31:47.668Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.668Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Gonzalez-Castano2021},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {González-Castaño, Catalina and Lorente-Leyva, Leandro L. and Muñoz, Javier and Restrepo, Carlos and Peluffo-Ordóñez, Diego H.},\n doi = {10.3390/electronics10020206},\n journal = {Electronics},\n number = {2}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Unsupervised Barter Model Based on Natural Human Interaction.\n \n \n \n \n\n\n \n Fernández-Fernández, Y.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; Pérez, R., M.; and Álvarez, E., N., C.\n\n\n \n\n\n\n In Hong, T.; Wojtkiewicz, K.; Chawuthai, R.; and Sitek, P., editor(s), Recent Challenges in Intelligent Information and Database Systems, pages 387-400, 2021. Springer Singapore\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Unsupervised Barter Model Based on Natural Human Interaction},\n type = {inproceedings},\n year = {2021},\n pages = {387-400},\n websites = {https://link.springer.com/chapter/10.1007/978-981-16-1685-3_32},\n publisher = {Springer Singapore},\n city = {Singapore},\n id = {3e7f5aae-00c8-34e2-9146-4651c1780cd9},\n created = {2021-05-10T23:31:47.919Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.919Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {fernandez2021unsupervisedbarter},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n author = {Fernández-Fernández, Yasmany and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H and Pérez, Ridelio Miranda and Álvarez, Elia N Cabrera},\n editor = {Hong, Tzung-Pei and Wojtkiewicz, Krystian and Chawuthai, Rathachai and Sitek, Pawel},\n booktitle = {Recent Challenges in Intelligent Information and Database Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Analysis of Business Behavior in the Australian Market Under an Approach of Statistical Techniques and Economic Dimensions for Sustainable Business: A Case Study.\n \n \n \n \n\n\n \n Patiño-Alarcón, D., R.; Patiño-Alarcón, F., A.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Proceedings of International Conference on Sustainable Expert Systems, pages 595-605, 2021. Springer Singapore\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Analysis of Business Behavior in the Australian Market Under an Approach of Statistical Techniques and Economic Dimensions for Sustainable Business: A Case Study},\n type = {inproceedings},\n year = {2021},\n pages = {595-605},\n websites = {https://link.springer.com/chapter/10.1007/978-981-33-4355-9_44},\n publisher = {Springer Singapore},\n city = {Singapore},\n id = {51f02335-d770-3c77-bf0f-c81fd997836b},\n created = {2021-05-10T23:31:47.945Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.945Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-981-33-4355-9_44},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n author = {Patiño-Alarcón, Delio R and Patiño-Alarcón, Fernando A and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n booktitle = {Proceedings of International Conference on Sustainable Expert Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Information Quality Assessment in Fusion Systems.\n \n \n \n \n\n\n \n Becerra, M.A.; Tobón, C.; Castro-Ospina, A.E.; Peluffo-Ordóñez, D.\n\n\n \n\n\n\n DATA,1-30. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Information Quality Assessment in Fusion Systems},\n type = {article},\n year = {2021},\n keywords = {completeness,figure 1 illustrates a,information quality,it shows the components,multi-source fusion,operational fusion process,relevance,reliability,simplified model of an,system,uncertainty,which},\n pages = {1-30},\n websites = {https://www.mdpi.com/2306-5729/6/6/60},\n id = {a5022293-36c4-3a17-ab02-9a3087b97c6a},\n created = {2021-06-08T21:27:21.545Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-06-08T21:27:32.687Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This paper provides a comprehensive description of the current literature on data fusion, with an emphasis on Information Quality (IQ) and performance evaluation. This literature review highlights recent studies that reveal existing gaps, the need to find a synergy between data fusion and IQ, several research issues, and the challenges and pitfalls in this field. First, the main models, frameworks, architectures, algorithms, solutions, problems, and requirements are analyzed. Second, a general data fusion engineering process is presented to show how complex it is to design a framework for a specific application. Third, an IQ approach, as well as the different methodologies and frameworks used to assess IQ in information systems are addressed; in addition, data fusion systems are presented along with their related criteria. Furthermore, information on the context in data fusion systems and its IQ assessment are discussed. Subsequently, the issue of data fusion systems’ performance is reviewed. Finally, some key aspects and concluding remarks are outlined, and some future lines of work are gathered.},\n bibtype = {article},\n author = {Becerra, M.A.; Tobón, C.; Castro-Ospina, A.E.; Peluffo-Ordóñez, D.H.},\n journal = {DATA}\n}\n\n This paper provides a comprehensive description of the current literature on data fusion, with an emphasis on Information Quality (IQ) and performance evaluation. This literature review highlights recent studies that reveal existing gaps, the need to find a synergy between data fusion and IQ, several research issues, and the challenges and pitfalls in this field. First, the main models, frameworks, architectures, algorithms, solutions, problems, and requirements are analyzed. Second, a general data fusion engineering process is presented to show how complex it is to design a framework for a specific application. Third, an IQ approach, as well as the different methodologies and frameworks used to assess IQ in information systems are addressed; in addition, data fusion systems are presented along with their related criteria. Furthermore, information on the context in data fusion systems and its IQ assessment are discussed. Subsequently, the issue of data fusion systems’ performance is reviewed. Finally, some key aspects and concluding remarks are outlined, and some future lines of work are gathered.\n
\n\n\n\n \n\n \n \n \n \n \n \n Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities.\n \n \n \n \n\n\n \n Rosero-montalvo, P., D.; Fuentes-hernández, E., A.; and Morocho-cayamcela, M., E.\n\n\n \n\n\n\n Sensors,1-17. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Addressing the Data Acquisition Paradigm in the Early Detection of Pediatric Foot Deformities},\n type = {article},\n year = {2021},\n keywords = {academic editor,children,data analysis,embedded systems,emmanouil,machine learning,plantar pressure},\n pages = {1-17},\n websites = {https://www.mdpi.com/1424-8220/21/13/4422},\n id = {929ceb5e-262b-3907-8ea2-14728f604515},\n created = {2021-07-03T23:43:10.721Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-07-03T23:43:16.522Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.},\n bibtype = {article},\n author = {Rosero-montalvo, Paul D and Fuentes-hernández, Edison A and Morocho-cayamcela, Manuel E},\n journal = {Sensors}\n}\n\n The analysis of plantar pressure through podometry has allowed analyzing and detecting different types of disorders and treatments in child patients. Early detection of an inadequate distribution of the patient’s weight can prevent serious injuries to the knees and lower spine. In this paper, an embedded system capable of detecting the presence of normal, flat, or arched footprints using resistive pressure sensors was proposed. For this purpose, both hardware- and software-related criteria were studied for an improved data acquisition through signal coupling and filtering processes. Subsequently, learning algorithms allowed us to estimate the type of footprint biomechanics in preschool and school children volunteers. As a result, the proposed algorithm achieved an overall classification accuracy of 97.2%. A flat feet share of 60% was encountered in a sample of 1000 preschool children. Similarly, flat feet were observed in 52% of a sample of 600 school children.\n
\n\n\n\n \n\n \n \n \n \n \n \n The Impact of Technological Advancements on Educational Innovation (VSI-tei).\n \n \n \n \n\n\n \n Hosseini, S.; Peluffo, D.; Okoye, K.; and Nganji, J., T.\n\n\n \n\n\n\n Computers & Electrical Engineering, 93: 107333. 2021.\n \n\n\n\n
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\n\n\n\n@article{\n title = {The Impact of Technological Advancements on Educational Innovation (VSI-tei)},\n type = {article},\n year = {2021},\n keywords = {Educational innovation,Educational technologies,Future of education,Higher education},\n pages = {107333},\n volume = {93},\n websites = {https://www.sciencedirect.com/science/article/pii/S0045790621003050},\n id = {91d45431-12a2-3f0f-99b7-8f50a07fafe5},\n created = {2021-08-03T17:46:31.179Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-08-03T17:46:31.179Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {HOSSEINI2021107333},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hosseini, Samira and Peluffo, Diego and Okoye, Kingsley and Nganji, Julius Tanyu},\n doi = {https://doi.org/10.1016/j.compeleceng.2021.107333},\n journal = {Computers & Electrical Engineering}\n}\n\n \n\n \n \n \n \n \n \n Integrating Information Visualization and Dimensionality Reduction: A pathway to Bridge the Gap between Natural and Artificial Intelligence.\n \n \n \n \n\n\n \n Peluffo-ordóñez, D., H.\n\n\n \n\n\n\n TecnoLógicas, 24. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Integrating Information Visualization and Dimensionality Reduction: A pathway to Bridge the Gap between Natural and Artificial Intelligence},\n type = {article},\n year = {2021},\n keywords = {Dimensionality Reduction,Information Visualization},\n volume = {24},\n websites = {https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2108},\n id = {55be4cd3-3015-3c0a-a3f6-f3296c127b58},\n created = {2021-08-10T02:43:40.485Z},\n file_attached = {true},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-08-10T02:50:04.632Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {By importing some natural abilities from human thinking into the design of computerized decision support systems, a cross-cutting trend of intelligent systems has emerged, namely, the synergetic integration between natural and artificial intelligence [1]. While natural intelligence provides creative, parallel, and holistic thinking, its artificial counterpart is logical, accurate, able to perform complex and extensive calculations, and tireless. In the light of such integration, two concepts are important: controllability and interpretability. The former is defined as the ability of computerized systems to receive feedback and follow users’ instructions, while the latter refers to human-machine communication. A suitable alternative to simultaneously involve these two concepts—and then bridging the gap between natural and artificial intelligence—is bringing together the fields of dimensionality reduction (DimRed) and information visualization (InfoVis).},\n bibtype = {article},\n author = {Peluffo-ordóñez, Diego H.},\n journal = {TecnoLógicas}\n}\n\n By importing some natural abilities from human thinking into the design of computerized decision support systems, a cross-cutting trend of intelligent systems has emerged, namely, the synergetic integration between natural and artificial intelligence [1]. While natural intelligence provides creative, parallel, and holistic thinking, its artificial counterpart is logical, accurate, able to perform complex and extensive calculations, and tireless. In the light of such integration, two concepts are important: controllability and interpretability. The former is defined as the ability of computerized systems to receive feedback and follow users’ instructions, while the latter refers to human-machine communication. A suitable alternative to simultaneously involve these two concepts—and then bridging the gap between natural and artificial intelligence—is bringing together the fields of dimensionality reduction (DimRed) and information visualization (InfoVis).\n
\n\n\n\n \n\n \n \n \n \n \n \n Information fusion and information quality assessment for environmental forecasting.\n \n \n \n \n\n\n \n Becerra, M., A.; Uribe, Y.; and Peluffo-ord, D., H.\n\n\n \n\n\n\n Urban Climate, 39(August). 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Information fusion and information quality assessment for environmental forecasting},\n type = {article},\n year = {2021},\n volume = {39},\n websites = {https://www.sciencedirect.com/science/article/pii/S2212095521001905},\n id = {49f34caf-cf59-3d29-b88a-5add2c2d00bf},\n created = {2021-08-25T20:04:24.999Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-09-14T03:13:16.624Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Air pollution is a major environmental threat to human health. Therefore, multiple systems have been developed for early prediction of air pollution levels in large cities. However, deterministic models produce uncertainties due to the complexity of the physical and chemical processes of individual systems and transport. In turn, statistical and machine learning techniques require a large amount of historical data to predict the behavior of a variable. In this paper, we propose a data fusion model to spatially and temporally predict air quality and assess its situation and risk for public health. Our model is based on the Joint Directors of Laboratories (JDL) model and focused on Information Quality (IQ), which allows us to fine tune hyper-parameters in different processes and trace information from raw data to knowledge. Expert systems use the information assessment to select and process data, information, and knowledge. The functionality of our model is tested using an environmental database of the Air Quality Monitoring Network of Área Metropolitana del Valle de Aburrá (AMVA in Spanish) in Colombia. Different levels of noise are added to the data to analyze the effects of information quality on the systems' performance throughout the process. Finally, our system is compared with two conventional machine learning-based models: Deep Learning and Support Vector Regression (SVR). The results show that our proposed model exhibits better performance, in terms of air quality forecasting, than conventional models. Furthermore, its capability as a mechanism to support decision making is clearly demonstrated.},\n bibtype = {article},\n author = {Becerra, M A and Uribe, Y and Peluffo-ord, D H},\n doi = {10.1016/j.uclim.2021.100960},\n journal = {Urban Climate},\n number = {August}\n}\n\n Air pollution is a major environmental threat to human health. Therefore, multiple systems have been developed for early prediction of air pollution levels in large cities. However, deterministic models produce uncertainties due to the complexity of the physical and chemical processes of individual systems and transport. In turn, statistical and machine learning techniques require a large amount of historical data to predict the behavior of a variable. In this paper, we propose a data fusion model to spatially and temporally predict air quality and assess its situation and risk for public health. Our model is based on the Joint Directors of Laboratories (JDL) model and focused on Information Quality (IQ), which allows us to fine tune hyper-parameters in different processes and trace information from raw data to knowledge. Expert systems use the information assessment to select and process data, information, and knowledge. The functionality of our model is tested using an environmental database of the Air Quality Monitoring Network of Área Metropolitana del Valle de Aburrá (AMVA in Spanish) in Colombia. Different levels of noise are added to the data to analyze the effects of information quality on the systems' performance throughout the process. Finally, our system is compared with two conventional machine learning-based models: Deep Learning and Support Vector Regression (SVR). The results show that our proposed model exhibits better performance, in terms of air quality forecasting, than conventional models. Furthermore, its capability as a mechanism to support decision making is clearly demonstrated.\n
\n\n\n\n \n\n \n \n \n \n \n \n Generalized Spectral Dimensionality Reduction Based on Kernel Representations and Principal Component Analysis.\n \n \n \n \n\n\n \n Ortega-Bustamante, M., C.; Hasperué, W.; Peluffo-Ordóñez, D., H.; González-Vergara, J.; Marín-Gaviño, J.; and Velez-Falconi, M.\n\n\n \n\n\n\n In Gervasi, O.; Murgante, B.; Misra, S.; Garau, C.; Blečić, I.; Taniar, D.; Apduhan, B., O.; Rocha, A., M., A., C.; Tarantino, E.; and Torre, C., M., editor(s), Computational Science and Its Applications -- ICCSA 2021, pages 512-523, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Generalized Spectral Dimensionality Reduction Based on Kernel Representations and Principal Component Analysis},\n type = {inproceedings},\n year = {2021},\n pages = {512-523},\n websites = {https://link.springer.com/chapter/10.1007%2F978-3-030-86973-1_36},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {5262b832-cee7-3378-bc02-08095254a76f},\n created = {2021-09-14T03:14:54.660Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-09-14T03:14:54.660Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-86973-1_36},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Very often, multivariate data analysis problems require dimensionality reduction (DR) stages to either improve analysis performance or represent the data in an intelligible fashion. Traditionally DR techniques are developed under different frameworks and settings what makes their comparison a non-trivial task. In this sense, generalized DR approaches are of great interest as they enable both to power and compare the DR techniques in a proper and fair manner. This work introduces a generalized spectral dimensionality reduction (GSDR) approach able to represent DR spectral techniques and enhance their representation ability. To do so, GSDR exploits the use of kernel-based representations as an initial nonlinear transformation to obtain a new space. Then, such a new space is used as an input for a feature extraction process based on principal component analysis. As remarkable experimental results, GSDR shows to be able to outperform the conventional implementation of well-known spectral DR techniques (namely, classical multidimensional scaling and Laplacian eigenmaps) in terms of the scaled version of the average agreement rate. Additionally, relevant insights and theoretical developments to understand the effect of data structure preservation at local and global levels are provided.},\n bibtype = {inproceedings},\n author = {Ortega-Bustamante, MacArthur C and Hasperué, Waldo and Peluffo-Ordóñez, Diego H and González-Vergara, Juan and Marín-Gaviño, Josué and Velez-Falconi, Martín},\n editor = {Gervasi, Osvaldo and Murgante, Beniamino and Misra, Sanjay and Garau, Chiara and Blečić, Ivan and Taniar, David and Apduhan, Bernady O and Rocha, Ana Maria A C and Tarantino, Eufemia and Torre, Carmelo Maria},\n booktitle = {Computational Science and Its Applications -- ICCSA 2021}\n}\n\n Very often, multivariate data analysis problems require dimensionality reduction (DR) stages to either improve analysis performance or represent the data in an intelligible fashion. Traditionally DR techniques are developed under different frameworks and settings what makes their comparison a non-trivial task. In this sense, generalized DR approaches are of great interest as they enable both to power and compare the DR techniques in a proper and fair manner. This work introduces a generalized spectral dimensionality reduction (GSDR) approach able to represent DR spectral techniques and enhance their representation ability. To do so, GSDR exploits the use of kernel-based representations as an initial nonlinear transformation to obtain a new space. Then, such a new space is used as an input for a feature extraction process based on principal component analysis. As remarkable experimental results, GSDR shows to be able to outperform the conventional implementation of well-known spectral DR techniques (namely, classical multidimensional scaling and Laplacian eigenmaps) in terms of the scaled version of the average agreement rate. Additionally, relevant insights and theoretical developments to understand the effect of data structure preservation at local and global levels are provided.\n
\n\n\n\n \n\n \n \n \n \n \n \n Algorithms Air Quality Estimation: A Comparative Study of Stochastic and Heuristic Predictive Models.\n \n \n \n \n\n\n \n Sánchez-Pozo, N., N.; Trilles-Oliver, S.; Solé-Ribalta, A.; Lorente-Leyva, L., L.; Mayorca-Torres, D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Sanjurjo González, H.; Pastor López, I.; García Bringas, P.; Quintián, H.; and Corchado, E., editor(s), Hybrid Artificial Intelligent Systems, pages 293-304, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Algorithms Air Quality Estimation: A Comparative Study of Stochastic and Heuristic Predictive Models},\n type = {inproceedings},\n year = {2021},\n pages = {293-304},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-86271-8_25},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {8d3061ab-4492-3fb0-bca1-67ee4580abd1},\n created = {2021-09-15T02:10:09.174Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-09-15T02:10:09.174Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-86271-8_25},\n source_type = {inproceedings},\n private_publication = {false},\n 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.},\n bibtype = {inproceedings},\n 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},\n editor = {Sanjurjo González, Hugo and Pastor López, Iker and García Bringas, Pablo and Quintián, Héctor and Corchado, Emilio},\n booktitle = {Hybrid Artificial Intelligent Systems}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Monitoring a turkey hatchery based on a cyber-physical system.\n \n \n \n \n\n\n \n Maisincho-Jivaja, A.; Alejandro-Sanjines, U.; Asanza, V.; Toscano-Quiroga, T.; Sánchez-Pozo, N., N.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In 2021 International Conference on Applied Electronics, AE, 2021. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Monitoring a turkey hatchery based on a cyber-physical system},\n type = {inproceedings},\n year = {2021},\n keywords = {internet of things,meleagriculture,pid tunner toolbox,sensor,system identification toolbox},\n websites = {https://ieeexplore.ieee.org/document/9542899},\n id = {3e04b53a-0f31-3ac5-be80-21ab7ea1db70},\n created = {2021-10-01T19:08:52.147Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-10-01T19:08:52.147Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.},\n bibtype = {inproceedings},\n author = {Maisincho-Jivaja, Anthony and Alejandro-Sanjines, Ulbio and Asanza, Víctor and Toscano-Quiroga, Tonny and Sánchez-Pozo, Nadia N. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego Hernan},\n booktitle = {2021 International Conference on Applied Electronics, AE}\n}\n\n The implementation of a turkey farm brings with it severe environmental problems due to the deficient study of the physical space where the animals are placed. To counteract this situation and improve the quality of life in the hatchery, it is necessary to monitor and control the following variables: Temperature, Humidity, Ammonia Emission and Lux. The solution is based on a cyber-physical system which is composed of a network of sensors, controller and actuator. The sensors will provide information from the physical environment, the con- troller evaluates these parameters to execute an action to the actuator. Proportional, Integral and Derivative (PID) control defines the setpoint for temperature while Pulse- Width Modulation (PWM) adjusts the light intensity in a spotlight. The End Device executes these actions and its parameters will be sent to ThingSpeak which monitors system behavior the Internet of Things.\n
\n\n\n\n \n\n \n \n \n \n \n \n Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system.\n \n \n \n \n\n\n \n Capelo, J.; Ruiz, E.; Asanza, V.; Toscano-quiroga, T.; Sánchez-pozo, N., N.; Lorente-leyva, L., L.; and Peluffo-ordóñez, D., H.\n\n\n \n\n\n\n In 2021 International Conference on Applied Electronics, AE, pages 7-10, 2021. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Raspberry Pi-based IoT for shrimp farms Real-time remote monitoring with automated system},\n type = {inproceedings},\n year = {2021},\n keywords = {atmega328p,cyberphysical system,dissolved oxygen,ecuador,salinity,shrimp farming,temperature,xbee},\n pages = {7-10},\n websites = {https://ieeexplore.ieee.org/document/9542907},\n id = {d136a56e-bbf9-317f-9c9b-58ce7d9e2fbc},\n created = {2021-10-01T19:08:52.148Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-10-01T19:08:52.148Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.},\n bibtype = {inproceedings},\n author = {Capelo, Jesús and Ruiz, Erick and Asanza, Víctor and Toscano-quiroga, Tonny and Sánchez-pozo, Nadia N and Lorente-leyva, Leandro L and Peluffo-ordóñez, Diego Hernan},\n booktitle = {2021 International Conference on Applied Electronics, AE}\n}\n\n This project analyses the optimal parameters for the shrimp farming, trying to help the aquaculture of Ecuador, using a cyberphysical system, which includes temperature, salinity, dissolved oxygen, and pH sensors to monitor the water conditions and an embedded system to control it using an XBee andATMega328p microcontrollers to remotely activate and deactivate aerators to maintain the quality of each pool in neat conditions.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Chatterbot Based on Genetic Algorithm: Preliminary Results.\n \n \n \n \n\n\n \n Orellana, C.; Tobar, M.; Yazán, J.; Peluffo-Ordóñez, D.; and Guachi-Guachi, L.\n\n\n \n\n\n\n In Florez, H.; and Pollo-Cattaneo, M., F., editor(s), Applied Informatics, pages 3-12, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A Chatterbot Based on Genetic Algorithm: Preliminary Results},\n type = {inproceedings},\n year = {2021},\n pages = {3-12},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-89654-6_1},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {a6a31205-4ede-3a93-9e34-77c133be63af},\n created = {2021-10-23T00:23:22.030Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-10-23T00:23:22.030Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-89654-6_1},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Chatterbots are programs that simulate an intelligent conversation with people. They are commonly used in customer service, product suggestions, e-commerce, travel and vacations, queries, and complaints. Although some works have presented valuable studies by using several technologies including evolutionary computing, artificial intelligence, machine learning, and natural language processing, creating chatterbots with a low rate of grammatical errors and good user satisfaction is still a challenging task. Therefore, this work introduces a preliminary study for the development of a GA-based chatterbot that generates intelligent dialogues with a low rate of grammatical errors and a strong sense of responsiveness, so boosting the personals satisfaction of individuals who interact with it. Preliminary results show that the proposed GA-based chatterbot yields 69\\% of ``Good'' responses for typical conversations regarding orders and receipts in a cafeteria.},\n bibtype = {inproceedings},\n author = {Orellana, Cristian and Tobar, Martín and Yazán, Jeremy and Peluffo-Ordóñez, D and Guachi-Guachi, Lorena},\n editor = {Florez, Hector and Pollo-Cattaneo, Ma Florencia},\n booktitle = {Applied Informatics}\n}\n\n Chatterbots are programs that simulate an intelligent conversation with people. They are commonly used in customer service, product suggestions, e-commerce, travel and vacations, queries, and complaints. Although some works have presented valuable studies by using several technologies including evolutionary computing, artificial intelligence, machine learning, and natural language processing, creating chatterbots with a low rate of grammatical errors and good user satisfaction is still a challenging task. Therefore, this work introduces a preliminary study for the development of a GA-based chatterbot that generates intelligent dialogues with a low rate of grammatical errors and a strong sense of responsiveness, so boosting the personals satisfaction of individuals who interact with it. Preliminary results show that the proposed GA-based chatterbot yields 69\\% of ``Good'' responses for typical conversations regarding orders and receipts in a cafeteria.\n
\n\n\n\n \n\n \n \n \n \n \n \n Sign Language Recognition Using Leap Motion Based on Time-Frequency Characterization and Conventional Machine Learning Techniques.\n \n \n \n \n\n\n \n López-Albán, D.; López-Barrera, A.; Mayorca-Torres, D.; and Peluffo-Ordóñez, D.\n\n\n \n\n\n\n In Florez, H.; and Pollo-Cattaneo, M., F., editor(s), Applied Informatics, pages 55-67, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Sign Language Recognition Using Leap Motion Based on Time-Frequency Characterization and Conventional Machine Learning Techniques},\n type = {inproceedings},\n year = {2021},\n pages = {55-67},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-89654-6_5},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {4317f039-bd45-365f-9dc1-03ce2b3f1e14},\n created = {2021-10-23T00:26:10.704Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-10-23T00:26:10.704Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-89654-6_5},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The abstract should briefly summarize the contents of the paper in Sign language is the form of communication between the deaf and hearing population, which uses the gesture-spatial configuration of the hands as a communication channel with their social environment. This work proposes the development of a gesture recognition method associated with sign language from the processing of time series from the spatial position of hand reference points granted by a Leap Motion optical sensor. A methodology applied to a validated American Sign Language (ASL) Dataset which involves the following sections: (i) preprocessing for filtering null frames, (ii) segmentation of relevant information, (iii) time-frequency characterization from the Discrete Wavelet Transform (DWT). Subsequently, the classification is carried out with Machine Learning algorithms (iv). It is graded by a 97.96\\% rating yield using the proposed methodology with the Fast Tree algorithm.},\n bibtype = {inproceedings},\n author = {López-Albán, D and López-Barrera, A and Mayorca-Torres, D and Peluffo-Ordóñez, D},\n editor = {Florez, Hector and Pollo-Cattaneo, Ma Florencia},\n booktitle = {Applied Informatics}\n}\n\n The abstract should briefly summarize the contents of the paper in Sign language is the form of communication between the deaf and hearing population, which uses the gesture-spatial configuration of the hands as a communication channel with their social environment. This work proposes the development of a gesture recognition method associated with sign language from the processing of time series from the spatial position of hand reference points granted by a Leap Motion optical sensor. A methodology applied to a validated American Sign Language (ASL) Dataset which involves the following sections: (i) preprocessing for filtering null frames, (ii) segmentation of relevant information, (iii) time-frequency characterization from the Discrete Wavelet Transform (DWT). Subsequently, the classification is carried out with Machine Learning algorithms (iv). It is graded by a 97.96\\% rating yield using the proposed methodology with the Fast Tree algorithm.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Fast-Tracking Hybrid MPPT Based on Surface-Based Polynomial Fitting and P&O Methods for Solar PV under Partial Shaded Conditions.\n \n \n \n \n\n\n \n González-Castaño, C.; Restrepo, C.; Revelo-Fuelagán, J.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Mathematics, 9(21). 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {A Fast-Tracking Hybrid MPPT Based on Surface-Based Polynomial Fitting and P&O Methods for Solar PV under Partial Shaded Conditions},\n type = {article},\n year = {2021},\n volume = {9},\n websites = {https://www.mdpi.com/2227-7390/9/21/2732},\n id = {29021801-5ce6-3370-b19b-841255fdfd2b},\n created = {2021-10-28T19:12:14.132Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-10-28T19:12:14.132Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {math9212732},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {González-Castaño, Catalina and Restrepo, Carlos and Revelo-Fuelagán, Javier and Lorente-Leyva, Leandro L and Peluffo-Ordóñez, Diego H},\n doi = {10.3390/math9212732},\n journal = {Mathematics},\n number = {21}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n BCI System using a Novel Processing Technique Based on Electrodes Selection for Hand Prosthesis Control.\n \n \n \n \n\n\n \n Constantine, A.; Asanza, V.; Loayza, F., R.; Peláez, E.; and Peluffo-Ordóñez, D.\n\n\n \n\n\n\n IFAC-PapersOnLine, 54(15): 364-369. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {BCI System using a Novel Processing Technique Based on Electrodes Selection for Hand Prosthesis Control},\n type = {article},\n year = {2021},\n keywords = {Bio-signals analysis,Brain Computer Interface,Embedded Systems,FPGA,Neural Networks},\n pages = {364-369},\n volume = {54},\n websites = {https://www.sciencedirect.com/science/article/pii/S2405896321016876},\n id = {e71c5fe9-1885-31d3-8297-8aa5241d1051},\n created = {2021-11-03T19:21:30.443Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-11-03T19:21:30.443Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {CONSTANTINE2021364},\n source_type = {article},\n notes = {11th IFAC Symposium on Biological and Medical Systems BMS 2021},\n private_publication = {false},\n abstract = {This work proposes an end-to-end model architecture, from feature extraction to classification using an Artificial Neural Network. The feature extraction process starts from an initial set of signals acquired by electrodes of a Brain-Computer Interface (BCI). The proposed architecture includes the design and implementation of a functional six Degree-of-Freedom (DOF) prosthetic hand. A Field Programmable Gate Array (FPGA) translates electroencephalography (EEG) signals into movements in the prosthesis. We also propose a new technique for selecting and grouping electrodes, which is related to the motor intentions of the subject. We analyzed and predicted two imaginary motor-intention tasks: opening and closing both fists and flexing and extending both feet. The model implemented with the proposed architecture showed an accuracy of 93.7% and a classification time of 8.8y«s for the FPGA. These results present the feasibility to carry out BCI using machine learning techniques implemented in a FPGA card.},\n bibtype = {article},\n author = {Constantine, Alisson and Asanza, Víctor and Loayza, Francis R and Peláez, Enrique and Peluffo-Ordóñez, Diego},\n doi = {https://doi.org/10.1016/j.ifacol.2021.10.283},\n journal = {IFAC-PapersOnLine},\n number = {15}\n}\n\n This work proposes an end-to-end model architecture, from feature extraction to classification using an Artificial Neural Network. The feature extraction process starts from an initial set of signals acquired by electrodes of a Brain-Computer Interface (BCI). The proposed architecture includes the design and implementation of a functional six Degree-of-Freedom (DOF) prosthetic hand. A Field Programmable Gate Array (FPGA) translates electroencephalography (EEG) signals into movements in the prosthesis. We also propose a new technique for selecting and grouping electrodes, which is related to the motor intentions of the subject. We analyzed and predicted two imaginary motor-intention tasks: opening and closing both fists and flexing and extending both feet. The model implemented with the proposed architecture showed an accuracy of 93.7% and a classification time of 8.8y«s for the FPGA. These results present the feasibility to carry out BCI using machine learning techniques implemented in a FPGA card.\n
\n\n\n\n \n\n \n \n \n \n \n \n Classification of Subjects with Parkinson’s Disease using Finger Tapping Dataset.\n \n \n \n \n\n\n \n Asanza, V.; Sánchez-Pozo, N., N.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; Loayza, F., R.; and Peláez, E.\n\n\n \n\n\n\n IFAC-PapersOnLine, 54(15): 376-381. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Classification of Subjects with Parkinson’s Disease using Finger Tapping Dataset},\n type = {article},\n year = {2021},\n keywords = {Classification,Finger Tapping,Machine Learning,Parkinson’s disease},\n pages = {376-381},\n volume = {54},\n websites = {https://www.sciencedirect.com/science/article/pii/S2405896321016906},\n id = {ef69df98-9ea1-3302-a2b9-9f8a2cb74985},\n created = {2021-11-03T19:29:59.950Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-11-03T19:29:59.950Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {ASANZA2021376},\n source_type = {article},\n notes = {11th IFAC Symposium on Biological and Medical Systems BMS 2021},\n private_publication = {false},\n 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%.},\n bibtype = {article},\n 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},\n doi = {https://doi.org/10.1016/j.ifacol.2021.10.285},\n journal = {IFAC-PapersOnLine},\n number = {15}\n}\n\n 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%.\n
\n\n\n\n \n\n \n \n \n \n \n \n Comparison of current deep convolutional neural networks for the segmentation of breast masses in mammograms.\n \n \n \n \n\n\n \n Anaya-Isaza, A.; Mera-Jiménez, L.; Cabrera-Chavarro, J.; Guachi-Guachi, L.; Peluffo-Ordóñez, D.; and Rios-Patiño, J.\n\n\n \n\n\n\n IEEE Access. 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Comparison of current deep convolutional neural networks for the segmentation of breast masses in mammograms},\n type = {article},\n year = {2021},\n websites = {https://ieeexplore.ieee.org/document/9614200},\n id = {7505ba31-fcfc-35de-9211-2296994f198d},\n created = {2021-11-14T02:18:51.666Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-11-14T02:18:51.666Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9614200},\n source_type = {article},\n private_publication = {false},\n abstract = {Breast cancer causes approximately 684,996 deaths worldwide, making it the leading cause of female cancer mortality. However, these figures can be reduced with early diagnosis through mammographic imaging, allowing for the timely and effective treatment of this disease. To establish the best tools for contributing to the automatic diagnosis of breast cancer, different deep learning (DL) architectures were compared in terms of breast lesion segmentation, lesion type classification, and degree of suspicion of malignancy tests. The tasks were completed with state-of-the-art architectures and backbones. Initially, during segmentation, the base UNet, Visual Geometry Group 19 (VGG19), InceptionResNetV2, EfficientNet, MobileNetv2, ResNet, ResNeXt, MultiResUNet, linkNet-VGG19, DenseNet, SEResNet and SeResNeXt architectures were compared, where “Res” denotes a residual network. In addition, training was performed with 5 of the most advanced loss functions and validated by the Dice coefficient, sensitivity, and specificity. The proposed models achieved Dice values above 90%, with the EfficientNet architecture achieving 94.75% and 99% accuracy on the two tasks. Subsequently, classification was addressed with the ResNet50V2, VGG19, InceptionResNetV2, DenseNet121, InceptionV3, Xception and EfficientNetB7 networks. The proposed models achieved 96.97% and 97.73% accuracy through the VGG19 and ResNet50V2 networks on the lesion classification and degree of suspicion tasks, respectively. All three tasks were addressed with open-access databases, including the Digital Database for Screening Mammography (DDSM), the Mammographic Image Analysis Society (MIAS) database, and INbreast.},\n bibtype = {article},\n author = {Anaya-Isaza, Andrés and Mera-Jiménez, Leonel and Cabrera-Chavarro, Johan and Guachi-Guachi, Lorena and Peluffo-Ordóñez, Diego and Rios-Patiño, Jorge},\n doi = {10.1109/ACCESS.2021.3127862},\n journal = {IEEE Access}\n}\n\n Breast cancer causes approximately 684,996 deaths worldwide, making it the leading cause of female cancer mortality. However, these figures can be reduced with early diagnosis through mammographic imaging, allowing for the timely and effective treatment of this disease. To establish the best tools for contributing to the automatic diagnosis of breast cancer, different deep learning (DL) architectures were compared in terms of breast lesion segmentation, lesion type classification, and degree of suspicion of malignancy tests. The tasks were completed with state-of-the-art architectures and backbones. Initially, during segmentation, the base UNet, Visual Geometry Group 19 (VGG19), InceptionResNetV2, EfficientNet, MobileNetv2, ResNet, ResNeXt, MultiResUNet, linkNet-VGG19, DenseNet, SEResNet and SeResNeXt architectures were compared, where “Res” denotes a residual network. In addition, training was performed with 5 of the most advanced loss functions and validated by the Dice coefficient, sensitivity, and specificity. The proposed models achieved Dice values above 90%, with the EfficientNet architecture achieving 94.75% and 99% accuracy on the two tasks. Subsequently, classification was addressed with the ResNet50V2, VGG19, InceptionResNetV2, DenseNet121, InceptionV3, Xception and EfficientNetB7 networks. The proposed models achieved 96.97% and 97.73% accuracy through the VGG19 and ResNet50V2 networks on the lesion classification and degree of suspicion tasks, respectively. All three tasks were addressed with open-access databases, including the Digital Database for Screening Mammography (DDSM), the Mammographic Image Analysis Society (MIAS) database, and INbreast.\n
\n\n\n\n \n\n \n \n \n \n \n \n Developments on Support Vector Machines for Multiple-Expert Learning.\n \n \n \n \n\n\n \n Umaquinga-Criollo, A., C.; Tamayo-Quintero, J., D.; Moreno-García, M., N.; Aalaila, Y.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Intelligent Data Engineering and Automated Learning -- IDEAL 2021, pages 587-598, 2021. Springer International Publishing\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Developments on Support Vector Machines for Multiple-Expert Learning},\n type = {inproceedings},\n year = {2021},\n pages = {587-598},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-91608-4_57},\n publisher = {Springer International Publishing},\n city = {Cham},\n id = {bddf49c7-6a92-3d8c-aacf-877eddfa18a8},\n created = {2021-11-24T10:24:48.945Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-11-24T10:24:48.945Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {10.1007/978-3-030-91608-4_57},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {In supervised learning scenarios, some applications require solve a classification problem wherein labels are not given as a single ground truth. Instead, the criteria of a set of experts is used to provide labels aimed at compensating for the erroneous influence with respect to a single labeler as well as the error bias (excellent or lousy) due to the level of perception and experience of each expert. This paper aims to briefly outline mathematical developments on support vector machines (SVM), and overview SVM-based approaches for multiple expert learning (MEL). Such MEL approaches are posed by modifying the formulation of a least-squares SVM, which enables to obtain a set of reliable, objective labels while penalizing the evaluation quality of each expert. Particularly, this work studies both two-class (binary) MEL classifier (BMLC) and its extension to multiclass through one-against all (OaA-MLC) including penalization of each expert's influence. Formal mathematical developments are stated, as well as remarkable discussion on key aspects about the least-squares SVM formulation and penalty factors are provided.},\n bibtype = {inproceedings},\n author = {Umaquinga-Criollo, Ana C and Tamayo-Quintero, Juan D and Moreno-García, María N and Aalaila, Yahya and Peluffo-Ordóñez, Diego H},\n booktitle = {Intelligent Data Engineering and Automated Learning -- IDEAL 2021}\n}\n\n In supervised learning scenarios, some applications require solve a classification problem wherein labels are not given as a single ground truth. Instead, the criteria of a set of experts is used to provide labels aimed at compensating for the erroneous influence with respect to a single labeler as well as the error bias (excellent or lousy) due to the level of perception and experience of each expert. This paper aims to briefly outline mathematical developments on support vector machines (SVM), and overview SVM-based approaches for multiple expert learning (MEL). Such MEL approaches are posed by modifying the formulation of a least-squares SVM, which enables to obtain a set of reliable, objective labels while penalizing the evaluation quality of each expert. Particularly, this work studies both two-class (binary) MEL classifier (BMLC) and its extension to multiclass through one-against all (OaA-MLC) including penalization of each expert's influence. Formal mathematical developments are stated, as well as remarkable discussion on key aspects about the least-squares SVM formulation and penalty factors are provided.\n
\n\n\n\n \n\n \n \n \n \n \n \n Dynamic Modeling of a Proton-Exchange Membrane Fuel Cell Using a Gaussian Approach.\n \n \n \n \n\n\n \n González-Castaño, C.; Lorente-Leyva, L., L.; Alpala, J.; Revelo-Fuelagán, J.; Peluffo-Ordóñez, D., H.; and Restrepo, C.\n\n\n \n\n\n\n Membranes, 11(12). 2021.\n \n\n\n\n
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\n\n\n@article{\n title = {Dynamic Modeling of a Proton-Exchange Membrane Fuel Cell Using a Gaussian Approach},\n type = {article},\n year = {2021},\n volume = {11},\n websites = {https://www.mdpi.com/2077-0375/11/12/953},\n id = {f899dbdf-6f15-349f-830f-13d624b6d425},\n created = {2021-12-02T14:56:55.819Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-12-02T14:56:55.819Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {membranes11120953},\n source_type = {article},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {González-Castaño, Catalina and Lorente-Leyva, Leandro L and Alpala, Janeth and Revelo-Fuelagán, Javier and Peluffo-Ordóñez, Diego H and Restrepo, Carlos},\n doi = {10.3390/membranes11120953},\n journal = {Membranes},\n number = {12}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Implementation of a two-loop digital control for high voltage DC-DC buck-boost converter with coupled inductor.\n \n \n \n \n\n\n \n González-Castaño, C.; Madrid, E.; Naranajo, W.; Restrepo, C.; Revelo-Fuelagán, J.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n In 2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL), pages 1-6, 2021. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Implementation of a two-loop digital control for high voltage DC-DC buck-boost converter with coupled inductor},\n type = {inproceedings},\n year = {2021},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9645983},\n id = {ce5590bf-7476-3a69-a0d5-5bc30bdb8c7d},\n created = {2021-12-27T16:26:05.692Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-12-27T16:26:05.692Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9645983},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {This paper presents a digital control for a DC-DC buck-boost converter with coupled inductors, using averaged current mode control as inner loop controller, in order to regulate the output DC voltage for high voltage application. The controller has been implemented using a digital signal controller (DSC); reference voltage variations experiments were performed for the different operating modes of the converter. The experimental results are in good agreement with the simulated results.},\n bibtype = {inproceedings},\n author = {González-Castaño, Catalina and Madrid, Emerson and Naranajo, Walter and Restrepo, Carlos and Revelo-Fuelagán, Javier and Peluffo-Ordoñez, Diego H},\n doi = {10.1109/COMPEL52922.2021.9645983},\n booktitle = {2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL)}\n}\n\n This paper presents a digital control for a DC-DC buck-boost converter with coupled inductors, using averaged current mode control as inner loop controller, in order to regulate the output DC voltage for high voltage application. The controller has been implemented using a digital signal controller (DSC); reference voltage variations experiments were performed for the different operating modes of the converter. The experimental results are in good agreement with the simulated results.\n
\n\n\n\n \n\n \n \n \n \n \n \n Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques.\n \n \n \n \n\n\n \n Sánchez-Pozo, N., N.; Mejía-Ordóñez, J., S.; Chamorro, D., C.; Mayorca-Torres, D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In 2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop, pages 1-6, 2021. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques},\n type = {inproceedings},\n year = {2021},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9733756},\n id = {1bed7b30-fa81-3dc6-9bd4-f43264eeb6cb},\n created = {2022-03-20T02:14:46.579Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-03-20T02:14:46.579Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9733756},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The proliferation of mobile devices and the rapid development of information and communication technologies have revolutionized education. Educational data has evolved to be voluminously massive, broadly various, and produced at high velocity. Therefore, computerized techniques for integrating, processing, and transforming data into valuable knowledge have become necessary to improve internal academic processes. Specifically, educational data mining is an emerging discipline concerned with analyzing the massive amounts of academic data generated and stored by educational institutions. In this sense, machine learning algorithms aid decision-makers who are establishing strategies to improve students' learning experience and institutional effectiveness by revealing hidden patterns in academic performance. Thus, this paper describes our comparative study of machine learning techniques to predict academic performance. We selected the features that best fit the discovery of patterns in the academic performance of high school students, resulting in a balance between accuracy and interpretability. We implemented six supervised learning algorithms for pattern recognition: Light Gradient Boosting Machine, Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and K-nearest Neighbors. The experimental results showed that the Gradient Boosting (Gbc) algorithm achieved the highest accuracy (96.77%), superior to other classification techniques considered.},\n bibtype = {inproceedings},\n author = {Sánchez-Pozo, Nadia N and Mejía-Ordóñez, Juan S and Chamorro, Diana C and Mayorca-Torres, Dagoberto and Peluffo-Ordóñez, Diego H},\n doi = {10.1109/IEEECONF53024.2021.9733756},\n booktitle = {2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop}\n}\n\n The proliferation of mobile devices and the rapid development of information and communication technologies have revolutionized education. Educational data has evolved to be voluminously massive, broadly various, and produced at high velocity. Therefore, computerized techniques for integrating, processing, and transforming data into valuable knowledge have become necessary to improve internal academic processes. Specifically, educational data mining is an emerging discipline concerned with analyzing the massive amounts of academic data generated and stored by educational institutions. In this sense, machine learning algorithms aid decision-makers who are establishing strategies to improve students' learning experience and institutional effectiveness by revealing hidden patterns in academic performance. Thus, this paper describes our comparative study of machine learning techniques to predict academic performance. We selected the features that best fit the discovery of patterns in the academic performance of high school students, resulting in a balance between accuracy and interpretability. We implemented six supervised learning algorithms for pattern recognition: Light Gradient Boosting Machine, Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and K-nearest Neighbors. The experimental results showed that the Gradient Boosting (Gbc) algorithm achieved the highest accuracy (96.77%), superior to other classification techniques considered.\n
\n\n\n\n \n\n \n \n \n \n \n \n Effect of simulated height on people exposed to different scenarios by means of virtual reality: Preliminary study [Efecto de la altura simulada en personas expuestas a distintos escenarios por medio de realidad virtual: Estudio preliminar].\n \n \n \n \n\n\n \n Moncayo, D., S., M.; Santa Muñoz, J., A.; Torres, D., M.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Revista Ibérica de Sistemas e Tecnologias de Informação, (E46): 440-451. 2021.\n \n\n\n\n
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\n\n\n\n@article{\n title = {Effect of simulated height on people exposed to different scenarios by means of virtual reality: Preliminary study [Efecto de la altura simulada en personas expuestas a distintos escenarios por medio de realidad virtual: Estudio preliminar]},\n type = {article},\n year = {2021},\n pages = {440-451},\n websites = {https://www.proquest.com/openview/bd031100f0a1e828c8ccd7d32790f87f/1?pq-origsite=gscholar&cbl=1006393},\n publisher = {Associação Ibérica de Sistemas e Tecnologias de Informacao},\n id = {5751bbfc-cf98-33a2-a285-d35f2f5252b5},\n created = {2022-05-09T16:19:24.209Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-05-09T16:19:24.209Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {moncayo2021efecto},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Moncayo, Dario Sebastian Muñoz and Santa Muñoz, Jesús Alejandro and Torres, Dagoberto Mayorca and Peluffo-Ordóñez, Diego Hernán},\n journal = {Revista Ibérica de Sistemas e Tecnologias de Informação},\n number = {E46}\n}\n\n \n\n \n \n \n \n \n \n Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques.\n \n \n \n \n\n\n \n Sánchez-Pozo, N., N.; Mejía-Ordóñez, J., S.; Chamorro, D., C.; Mayorca-Torres, D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In 2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop, pages 1-6, 2021. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques},\n type = {inproceedings},\n year = {2021},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/9733756},\n id = {7bf00cb6-24e2-3997-b0bd-304d86c181c8},\n created = {2022-08-25T04:35:23.040Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2022-08-25T04:35:23.040Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {9733756},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The proliferation of mobile devices and the rapid development of information and communication technologies have revolutionized education. Educational data has evolved to be voluminously massive, broadly various, and produced at high velocity. Therefore, computerized techniques for integrating, processing, and transforming data into valuable knowledge have become necessary to improve internal academic processes. Specifically, educational data mining is an emerging discipline concerned with analyzing the massive amounts of academic data generated and stored by educational institutions. In this sense, machine learning algorithms aid decision-makers who are establishing strategies to improve students' learning experience and institutional effectiveness by revealing hidden patterns in academic performance. Thus, this paper describes our comparative study of machine learning techniques to predict academic performance. We selected the features that best fit the discovery of patterns in the academic performance of high school students, resulting in a balance between accuracy and interpretability. We implemented six supervised learning algorithms for pattern recognition: Light Gradient Boosting Machine, Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and K-nearest Neighbors. The experimental results showed that the Gradient Boosting (Gbc) algorithm achieved the highest accuracy (96.77%), superior to other classification techniques considered.},\n bibtype = {inproceedings},\n author = {Sánchez-Pozo, Nadia N and Mejía-Ordóñez, Juan S and Chamorro, Diana C and Mayorca-Torres, Dagoberto and Peluffo-Ordóñez, Diego H},\n doi = {10.1109/IEEECONF53024.2021.9733756},\n booktitle = {2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop}\n}\n\n The proliferation of mobile devices and the rapid development of information and communication technologies have revolutionized education. Educational data has evolved to be voluminously massive, broadly various, and produced at high velocity. Therefore, computerized techniques for integrating, processing, and transforming data into valuable knowledge have become necessary to improve internal academic processes. Specifically, educational data mining is an emerging discipline concerned with analyzing the massive amounts of academic data generated and stored by educational institutions. In this sense, machine learning algorithms aid decision-makers who are establishing strategies to improve students' learning experience and institutional effectiveness by revealing hidden patterns in academic performance. Thus, this paper describes our comparative study of machine learning techniques to predict academic performance. We selected the features that best fit the discovery of patterns in the academic performance of high school students, resulting in a balance between accuracy and interpretability. We implemented six supervised learning algorithms for pattern recognition: Light Gradient Boosting Machine, Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and K-nearest Neighbors. The experimental results showed that the Gradient Boosting (Gbc) algorithm achieved the highest accuracy (96.77%), superior to other classification techniques considered.\n
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\n \n \n\n \n \n \n \n \n \n Data fusion and information quality for biometric identification from multimodal signals.\n \n \n \n \n\n\n \n Becerra, M., A.; Lasso-Arciniegas, L.; Viveros, A.; Serna-Guarín, L.; Peluffo-Ordóñez, D.; and Tobón, C.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Data fusion and information quality for biometric identification from multimodal signals},\n type = {article},\n year = {2020},\n keywords = {Biometry,Data fusion,Information quality,Signal processing},\n websites = {https://search.proquest.com/docview/2385757504?pq-origsite=gscholar&fromopenview=true},\n id = {6763ae7a-7a2a-3258-abf4-098da06ce585},\n created = {2021-05-10T23:31:45.097Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.097Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2020a},\n private_publication = {false},\n abstract = {Biometric identification is carried out by processing physiological traits and signals. Biometrics systems are an open field of research and development, since they are permanently susceptible to attacks demanding permanent development to maintain their confidence. The main objective of this study is to analyze the effects of the quality of information on biometric identification and consider it in access control systems. This paper proposes a data fusion model for the development of biometrics systems considering the assessment of information quality. This proposal is based on the JDL (Joint Directors of Laboratories) data fusion model, which includes raw data processing, pattern detection, situation assessment and risk or impact. The results demonstrated the functionality of the proposed model and its potential compared to other traditional identification models.},\n bibtype = {article},\n author = {Becerra, Miguel A. and Lasso-Arciniegas, Laura and Viveros, Andrés and Serna-Guarín, Leonardo and Peluffo-Ordóñez, Diego and Tobón, Catalina},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Biometric identification is carried out by processing physiological traits and signals. Biometrics systems are an open field of research and development, since they are permanently susceptible to attacks demanding permanent development to maintain their confidence. The main objective of this study is to analyze the effects of the quality of information on biometric identification and consider it in access control systems. This paper proposes a data fusion model for the development of biometrics systems considering the assessment of information quality. This proposal is based on the JDL (Joint Directors of Laboratories) data fusion model, which includes raw data processing, pattern detection, situation assessment and risk or impact. The results demonstrated the functionality of the proposed model and its potential compared to other traditional identification models.\n
\n\n\n\n \n\n \n \n \n \n \n \n Structural capital model for universities based on JDL data fusion model and information quality.\n \n \n \n \n\n\n \n Becerra, M., A.; Londoño-Montoya, E.; Serna-Guarín, L.; Peluffo-Ordóñez, D.; Tobón, C.; and Giraldo, L.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Structural capital model for universities based on JDL data fusion model and information quality},\n type = {article},\n year = {2020},\n keywords = {Data fusion,Information quality,Intelectual capital,JDL model,Structural capital},\n websites = {https://search.proquest.com/docview/2394535766},\n id = {b3b17407-6b20-3b6d-85a7-770f74effa52},\n created = {2021-05-10T23:31:45.518Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.518Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2020b},\n private_publication = {false},\n abstract = {Intellectual capital is one of the most critical intangible active assets for universities, and there are multiple models to value it through the human, structural, and relational components. However, this is an open field of research that still demands new solutions to assess it effectively from each of its components. For the assessment of the structural component in higher education institutions, this study proposes a model that combines the assessment of the quality of information and the JDL data fusion model (joint directors of laboratories), which has been used in applications military. The proposed model is original in the methods used and their association, distributed in six levels that execute the pre-processing of the information, valuation of objects, valuation of the situation and the risk, and the refinement of the process. Besides, it evaluates the quality of the information, its traceability, and context to refine the process and obtain a more objective assessment taking into account the imperfection of the information for decision-making in the management of impact and risk. The model not only allows the assessment of structural capital, but also supports decision-making based on the quality of information and its impact. The functionality of the model is described by levels.},\n bibtype = {article},\n author = {Becerra, Miguel A. and Londoño-Montoya, Erika and Serna-Guarín, Leonardo and Peluffo-Ordóñez, Diego and Tobón, Catalina and Giraldo, Lillyana},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Intellectual capital is one of the most critical intangible active assets for universities, and there are multiple models to value it through the human, structural, and relational components. However, this is an open field of research that still demands new solutions to assess it effectively from each of its components. For the assessment of the structural component in higher education institutions, this study proposes a model that combines the assessment of the quality of information and the JDL data fusion model (joint directors of laboratories), which has been used in applications military. The proposed model is original in the methods used and their association, distributed in six levels that execute the pre-processing of the information, valuation of objects, valuation of the situation and the risk, and the refinement of the process. Besides, it evaluates the quality of the information, its traceability, and context to refine the process and obtain a more objective assessment taking into account the imperfection of the information for decision-making in the management of impact and risk. The model not only allows the assessment of structural capital, but also supports decision-making based on the quality of information and its impact. The functionality of the model is described by levels.\n
\n\n\n\n \n\n \n \n \n \n \n \n Knee joint angle measuring portable embedded system based on inertial measurement units for gait analysis.\n \n \n \n \n\n\n \n Mayorca-Torres, D.; Caicedo-Eraso, J., C.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n International Journal on Advanced Science, Engineering and Information Technology. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Knee joint angle measuring portable embedded system based on inertial measurement units for gait analysis},\n type = {article},\n year = {2020},\n keywords = {Gait analysis,IMU,Kalman filter,Knee-joint angle,Motion analysis},\n websites = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10814},\n id = {8d210419-b3ca-32bc-ad7a-7380614f0787},\n created = {2021-05-10T23:31:45.631Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.631Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Mayorca-Torres2020},\n private_publication = {false},\n abstract = {Inside clinical research, gait analysis is a fundamental part of the functional evaluation of the human body's movement. Its evaluation has been carried out through different methods and tools, which allow early diagnosis of diseases, and monitoring and assessing the effectiveness of therapeutic plans applied to patients for rehabilitation. The observational method is one of the most used in specialized centers in Colombia; however, to avoid any possible errors associated with the subjectivity observation, technological tools that provide quantitative data can support this method. This paper deals with the methodological process for developing a computational tool and hardware device for the analysis of gait, specifically on articular kinematics of the knee. This work develops a prototype based on the fusion of inertial measurement units (IMU) data as an alternative for the attenuation of errors associated with each of these technologies. A videogrammetry technique measured the same human gait patterns to validate the proposed system, in terms of accuracy and repeatability of the recorded data. Results showed that the developed prototype successfully captured the kneejoint angles of the flexion-extension motions with high consistency and accuracy in with the measurements obtained from the videogrammetry technique. Statistical analysis (ICC and RMSE) exhibited a high correlation between the two systems for the measures of the joint angles. These results suggest the possibility of using an IMU-based prototype in realistic scenarios for accurately tracking a patient's knee-joint kinematics during a human gait.},\n bibtype = {article},\n author = {Mayorca-Torres, Dagoberto and Caicedo-Eraso, Julio C. and Peluffo-Ordóñez, Diego H.},\n doi = {10.18517/ijaseit.10.2.10814},\n journal = {International Journal on Advanced Science, Engineering and Information Technology}\n}\n\n Inside clinical research, gait analysis is a fundamental part of the functional evaluation of the human body's movement. Its evaluation has been carried out through different methods and tools, which allow early diagnosis of diseases, and monitoring and assessing the effectiveness of therapeutic plans applied to patients for rehabilitation. The observational method is one of the most used in specialized centers in Colombia; however, to avoid any possible errors associated with the subjectivity observation, technological tools that provide quantitative data can support this method. This paper deals with the methodological process for developing a computational tool and hardware device for the analysis of gait, specifically on articular kinematics of the knee. This work develops a prototype based on the fusion of inertial measurement units (IMU) data as an alternative for the attenuation of errors associated with each of these technologies. A videogrammetry technique measured the same human gait patterns to validate the proposed system, in terms of accuracy and repeatability of the recorded data. Results showed that the developed prototype successfully captured the kneejoint angles of the flexion-extension motions with high consistency and accuracy in with the measurements obtained from the videogrammetry technique. Statistical analysis (ICC and RMSE) exhibited a high correlation between the two systems for the measures of the joint angles. These results suggest the possibility of using an IMU-based prototype in realistic scenarios for accurately tracking a patient's knee-joint kinematics during a human gait.\n
\n\n\n\n \n\n \n \n \n \n \n \n Comparison of kernel functions for the prediction of the photovoltaic energy supply [Comparación de funciones kernel para la predicción de la oferta energética fotovoltaica].\n \n \n \n \n\n\n \n Mora-Paz, H.; Riascos, J., A.; Salazar-Castro, J., A.; Mora, G.; Pantoja, A.; Revelo-Fuelagán, J.; Mancera-Valetts, L.; and Peluffo-Ordoñez, D.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2020(E38): 310-324. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Comparison of kernel functions for the prediction of the photovoltaic energy supply [Comparación de funciones kernel para la predicción de la oferta energética fotovoltaica]},\n type = {article},\n year = {2020},\n pages = {310-324},\n volume = {2020},\n websites = {https://search.proquest.com/docview/2474915437/fulltextPDF/D88B81E498D44759PQ/1},\n publisher = {Associacao Iberica de Sistemas e Tecnologias de Informacao},\n id = {6391e573-a20b-3200-a0a8-0a382168fc99},\n created = {2021-05-10T23:31:45.680Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.680Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Mora-Paz2020310},\n source_type = {article},\n notes = {cited By 0},\n private_publication = {false},\n abstract = {Recently, at the fields of climate change and energy demand have turned their attention to the study and discovery of patterns in renewable energies, such as the photovoltaic-type. Such patterns can be obtained by extrapolating radiation based on the electromagnetic spectrum bands captured by NASA’s Landsat and MODIS satellites, where artificial neural network (ANN) and support vector machine (SVM) algorithms have produced the best models. Nonetheless, the acquisition of training data from those sources is expensive, as well as it lacks the exploration of kernel functions for this application. Therefore, in this study, adjustments were made in the above aspects, mainly through: coupling of new kernels to ANN and SVM in the scikit-learn library, contributing to the reuse and robustness of these algorithms; and implementing an experimental framework to tune hyper-parameters, thus generating results comparable to those reported in the state of the art. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.},\n bibtype = {article},\n author = {Mora-Paz, H and Riascos, J A and Salazar-Castro, J A and Mora, G and Pantoja, A and Revelo-Fuelagán, J and Mancera-Valetts, L and Peluffo-Ordoñez, D},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao},\n number = {E38}\n}\n\n Recently, at the fields of climate change and energy demand have turned their attention to the study and discovery of patterns in renewable energies, such as the photovoltaic-type. Such patterns can be obtained by extrapolating radiation based on the electromagnetic spectrum bands captured by NASA’s Landsat and MODIS satellites, where artificial neural network (ANN) and support vector machine (SVM) algorithms have produced the best models. Nonetheless, the acquisition of training data from those sources is expensive, as well as it lacks the exploration of kernel functions for this application. Therefore, in this study, adjustments were made in the above aspects, mainly through: coupling of new kernels to ANN and SVM in the scikit-learn library, contributing to the reuse and robustness of these algorithms; and implementing an experimental framework to tune hyper-parameters, thus generating results comparable to those reported in the state of the art. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.\n
\n\n\n\n \n\n \n \n \n \n \n \n Clustering of Reading Ability Performance Variables in the English Language Based on TBL Methodology and Behavior in the Left Hemisphere of the Brain.\n \n \n \n \n\n\n \n Patiño-Alarcón, D., R.; Patiño-Alarcón, F., A.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science. 2020.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2020},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-62833-8_7},\n id = {313e4162-2bbd-3d95-b770-51e851970791},\n created = {2021-05-10T23:31:45.774Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.774Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Patino-Alarcon2020},\n private_publication = {false},\n abstract = {This research presents an application of the clustering based on Thinking Based - Learning methodology (TBL), which offers guidelines to promote students’ reflective thinking. Within this methodology, the Intelligence Execution Theory (IET) tool will be used to encourage this kind of thinking in the classroom. Having in mind that, in any educational process, methodologies and pedagogical tools have a pivotal role as they are one of the bases for optimizing cognitive intelligence. In this case, it was given a priority to the potential development of a specific linguistic skill. This study presented a mixed methodology with an exploratory and descriptive scope. The main objective of this research was the clustering of the variables of functioning of the reading ability in the English language based on the TBL methodology and its behavior in the left hemisphere of the brain, specifically to analyze the improvement of the reading ability in the English language of the participants of this case study. With the expectation of generating sustainability of adequate levels of performance, instruction and learning of the English language of students at all levels.},\n bibtype = {inbook},\n author = {Patiño-Alarcón, Delio R. and Patiño-Alarcón, Fernando A. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-62833-8_7},\n chapter = {Clustering of Reading Ability Performance Variables in the English Language Based on TBL Methodology and Behavior in the Left Hemisphere of the Brain},\n title = {Communications in Computer and Information Science}\n}\n\n This research presents an application of the clustering based on Thinking Based - Learning methodology (TBL), which offers guidelines to promote students’ reflective thinking. Within this methodology, the Intelligence Execution Theory (IET) tool will be used to encourage this kind of thinking in the classroom. Having in mind that, in any educational process, methodologies and pedagogical tools have a pivotal role as they are one of the bases for optimizing cognitive intelligence. In this case, it was given a priority to the potential development of a specific linguistic skill. This study presented a mixed methodology with an exploratory and descriptive scope. The main objective of this research was the clustering of the variables of functioning of the reading ability in the English language based on the TBL methodology and its behavior in the left hemisphere of the brain, specifically to analyze the improvement of the reading ability in the English language of the participants of this case study. With the expectation of generating sustainability of adequate levels of performance, instruction and learning of the English language of students at all levels.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Alemany, M., M., E.; Peluffo-Ordóñez, D., H.; and Herrera-Granda, I., D.\n\n\n \n\n\n\n pages 131-142. Lecture Notes in Computer Science, 2020.\n \n\n\n\n
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\n\n\n\n@inbook{\n type = {inbook},\n year = {2020},\n pages = {131-142},\n websites = {http://link.springer.com/10.1007/978-3-030-64580-9_11},\n publisher = {Lecture Notes in Computer Science},\n id = {8eb31ab0-bb79-3e72-87fa-0c099cc3dce0},\n created = {2021-05-10T23:31:45.890Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.890Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n bibtype = {inbook},\n author = {Lorente-Leyva, Leandro L. and Alemany, M. M. E. and Peluffo-Ordóñez, Diego H. and Herrera-Granda, Israel D.},\n doi = {10.1007/978-3-030-64580-9_11},\n chapter = {A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry}\n}\n\n \n\n \n \n \n \n \n \n Evaluation of characterization techniques for classification of seismic-volcanic signals of the nevado del ruiz.\n \n \n \n \n\n\n \n Bravo, Y., E.; Narváez, E., R.; Cabrera, P., C.; Bonilla, J., L.; and Ordoñez, D., P.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Evaluation of characterization techniques for classification of seismic-volcanic signals of the nevado del ruiz},\n type = {article},\n year = {2020},\n keywords = {Cepstral,Characterization,Classification,Machine Learning,Seismic-volcanic},\n websites = {https://search.proquest.com/docview/2350120798},\n id = {c3b59614-8b4f-3942-ae06-81311f731571},\n created = {2021-05-10T23:31:46.134Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.134Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Bravo2020},\n private_publication = {false},\n abstract = {Currently, researches have been carried out on automatic classification of seismic-volcanic events-mainly based on machine learning techniques-aimed at identifying the nature of the recorded event. In this sense, several approaches have been introduced. Nonetheless, due to these signals’ variability, there is no still a conclusive method of characterization, and it is in fact an open and challenging research problem. In this work, a methodology for comparing features extraction techniques is developed aimed at the discrimination of seismic events of volcanic origin. Representation of the signals in the domain of time, frequency, time-frequency and Cepstral is used. The set of attributes is optimized by selecting characteristics by assigning weights. A supervised classification is executed using known records. Finally, classification performance measures were obtained to determine the subset of characteristics that best represent and discriminate the signals.},\n bibtype = {article},\n author = {Bravo, Yoiner Erazo and Narváez, Edison Rosero and Cabrera, Paola Castro and Bonilla, John Londoño and Ordoñez, Diego Peluffo},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Currently, researches have been carried out on automatic classification of seismic-volcanic events-mainly based on machine learning techniques-aimed at identifying the nature of the recorded event. In this sense, several approaches have been introduced. Nonetheless, due to these signals’ variability, there is no still a conclusive method of characterization, and it is in fact an open and challenging research problem. In this work, a methodology for comparing features extraction techniques is developed aimed at the discrimination of seismic events of volcanic origin. Representation of the signals in the domain of time, frequency, time-frequency and Cepstral is used. The set of attributes is optimized by selecting characteristics by assigning weights. A supervised classification is executed using known records. Finally, classification performance measures were obtained to determine the subset of characteristics that best represent and discriminate the signals.\n
\n\n\n\n \n\n \n \n \n \n \n \n Comparative study of data mining techniques to reveal patterns of academic performance in secondary education.\n \n \n \n \n\n\n \n Chamorro-Sangoquiza, D., C.; Vargas-Muñoz, A., M.; Umaquinga-Criollo, A., C.; Becerra, M., A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Comparative study of data mining techniques to reveal patterns of academic performance in secondary education},\n type = {article},\n year = {2020},\n keywords = {Academic performance patterns,Classifiers,Feature selection,Matlab,Multiple classifier},\n websites = {https://search.proquest.com/docview/2452331372/fulltextPDF/64A2741CD0B646EAPQ/1},\n id = {614838e8-a8fb-3f79-908c-5c94ddff9fb0},\n created = {2021-05-10T23:31:46.266Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.266Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Chamorro-Sangoquiza2020},\n private_publication = {false},\n abstract = {The data mining techniques allow for unveiling knowledge from large volumes of information, which have recently been explored in information analysis by educational institutions but already with an increasing demand for this sector to support decision-making. In this research, a methodology for comparing data mining techniques is proposed, which is to be applied to the analysis of academic patrons in students of media education. Multiple methods of selecting attributes are applied to reduce the dimensionality and compare three classifiers and multi-classifiers. The experiments are carried out in a dataset of 285 instances and 36 attributes obtained from an educational survey applied to the students of the School of Education of the University of Barcelona 2017-2018. The best results of classification achieved by the multi-splitter Boosted Tree and Bagged Tree with 93.24% accuracy using the data selected using the BestFirst algorithm.},\n bibtype = {article},\n author = {Chamorro-Sangoquiza, Diana C. and Vargas-Muñoz, Andrés M. and Umaquinga-Criollo, Ana C. and Becerra, Miguel A. and Peluffo-Ordóñez, Diego H.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n The data mining techniques allow for unveiling knowledge from large volumes of information, which have recently been explored in information analysis by educational institutions but already with an increasing demand for this sector to support decision-making. In this research, a methodology for comparing data mining techniques is proposed, which is to be applied to the analysis of academic patrons in students of media education. Multiple methods of selecting attributes are applied to reduce the dimensionality and compare three classifiers and multi-classifiers. The experiments are carried out in a dataset of 285 instances and 36 attributes obtained from an educational survey applied to the students of the School of Education of the University of Barcelona 2017-2018. The best results of classification achieved by the multi-splitter Boosted Tree and Bagged Tree with 93.24% accuracy using the data selected using the BestFirst algorithm.\n
\n\n\n\n \n\n \n \n \n \n \n \n Analytic study on the performance of multi-classification approaches in case-based reasoning systems: Medical data exploration.\n \n \n \n \n\n\n \n Bastidas, D.; Piñeros, C.; Peluffo-Ordóñez, D., H.; Sierra, L., M.; Becerra, M., A.; and Umaquinga-Criollo, A., C.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Analytic study on the performance of multi-classification approaches in case-based reasoning systems: Medical data exploration},\n type = {article},\n year = {2020},\n keywords = {Case based reasoning,Classifiers fusion,Dermatology disease,Heart disease},\n websites = {https://search.proquest.com/docview/2451420129/fulltextPDF/F4AF5E590BD14D5EPQ/9},\n id = {110b6f27-3135-3732-a220-25368f4c99bb},\n created = {2021-05-10T23:31:46.313Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.313Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Bastidas2020},\n private_publication = {false},\n abstract = {This paper compares the main combinations of classifiers (Sequential, Parallel and Stacking) over two remarkable medical data collections: Cleveland and Dermatology. The principal rationale underlying the use of multiple classifiers is that together the methods may be powered rather than their individual behavior. Such a premise is validated through the identification of the best the combination reaching the lowest error rate within a case-based reasoning system (CBR). The different combinations are essentially formed by five different classifiers greatly different regarding their nature and inception: SVM (Support Vector Machines), Parzen, Random Forest, K-NN (k-nearest neighbors) and Naive Bayes. From experimental results, it can be inferred that the combination of techniques is greatly useful. Also, in this work, some key aspects and hints are discussed about the relationship between the nature of the input data and the classification (either individual or mixture of classifiers) stage building within a CBR framework.},\n bibtype = {article},\n author = {Bastidas, David and Piñeros, Camilo and Peluffo-Ordóñez, Diego H. and Sierra, Luz Marina and Becerra, Miguel A. and Umaquinga-Criollo, Ana C.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n This paper compares the main combinations of classifiers (Sequential, Parallel and Stacking) over two remarkable medical data collections: Cleveland and Dermatology. The principal rationale underlying the use of multiple classifiers is that together the methods may be powered rather than their individual behavior. Such a premise is validated through the identification of the best the combination reaching the lowest error rate within a case-based reasoning system (CBR). The different combinations are essentially formed by five different classifiers greatly different regarding their nature and inception: SVM (Support Vector Machines), Parzen, Random Forest, K-NN (k-nearest neighbors) and Naive Bayes. From experimental results, it can be inferred that the combination of techniques is greatly useful. Also, in this work, some key aspects and hints are discussed about the relationship between the nature of the input data and the classification (either individual or mixture of classifiers) stage building within a CBR framework.\n
\n\n\n\n \n\n \n \n \n \n \n \n Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Lopez-Batista, V., F.; and Peluffo-Ordonez, D., H.\n\n\n \n\n\n\n IEEE Sensors Journal. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Hybrid Embedded-Systems-based Approach to in-Driver Drunk Status Detection using Image Processing and Sensor Networks},\n type = {article},\n year = {2020},\n websites = {https://ieeexplore.ieee.org/document/9258992},\n id = {8a1bb9c6-29c9-3ebd-9ded-0b18534584c7},\n created = {2021-05-10T23:31:46.484Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.484Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020a},\n private_publication = {false},\n abstract = {Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Lopez-Batista, Vivian F. and Peluffo-Ordonez, Diego H.},\n doi = {10.1109/jsen.2020.3038143},\n journal = {IEEE Sensors Journal}\n}\n\n Car drivers under the influence of alcohol is one of the most common causes of road traffic accidents. To tackle this issue, an emerging, suitable alternative is the use of intelligent systems -traditionally based on either sensor networks or artificial vision- that are aimed to prevent starting the car when drunk status on the car driver is detected. In such vein, this paper introduces a system whose main objective is identifying a person having alcohol in the blood through supervised classification of sensor-generated and computer-vision-based data. To do so, some drunk-status criteria are considered, namely: the concentration of alcohol in the car environment, the facial temperature of the driver and the pupil width. Specifically, for data acquisition purposes, the proposed system incorporates a gas sensor, temperature sensor and a digital camera. Acquired data are analyzed into a two-stages machine learning system consisting of feature selection and supervised classification algorithms. Both acquisition and analysis stages are to be performed into a embedded system, and therefore all procedures and algorithms are designed to work at low-computational resources. As a remarkable outcome, due mainly to the incorporation of feature selection and relevance analysis stages, proposed approach reaches a classification performance of 98% while ensures adequate operation conditions for the embedded system.\n
\n\n\n\n \n\n \n \n \n \n \n \n Multi-expert Methods Evaluation on Financial and Economic Data: Introducing Bag of Experts.\n \n \n \n \n\n\n \n Umaquinga-Criollo, A., C.; Tamayo-Quintero, J., D.; Moreno-García, M., N.; Riascos, J., A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science. 2020.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2020},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-61705-9_36},\n id = {b1eb4f00-2930-37ee-96fa-72eae84e4cbb},\n created = {2021-05-10T23:31:46.548Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.548Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Umaquinga-Criollo2020},\n private_publication = {false},\n abstract = {The use of machine learning into economics scenarios results appealing since it allows for automatically testing economic models and predict consumer/client behavior to support decision-making processes. The finance market typically uses a set of expert labelers or Bureau credit scores given by governmental or private agencies such as Experian, Equifax, and Creditinfo, among others. This work focuses on introducing a so-named Bag of Expert (BoE): a novel approach for creating multi-expert Learning (MEL) frameworks aimed to emulate real experts labeling (human-given labels) using neural networks. The MEL systems “learn” to perform decision-making tasks by considering a uniform number of labels per sample or individuals along with respective descriptive variables. The BoE is created similarly to Generative Adversarial Network (GANs), but rather than using noise or perturbation by a generator, we trained a feed-forward neural network to randomize sampling data, and either add or decrease hidden neurons. Additionally, this paper aims to investigate the performance on economics-related datasets of several state-of-the-art MEL methods, such as GPC, GPC-PLAT, KAAR, MA-LFC, MA-DGRL, and MA-MAE. To do so, we develop an experimental framework composed of four tests: the first one using novice experts; the second with proficient experts; the third is a mix of novices, intermediate and proficient experts, and the last one uses crowd-sourcing. Our BoE method presents promising results and can be suitable as an alternative to properly assess the reliability of both MEL methods and conventional labeler generators (i.e., virtual expert labelers).},\n bibtype = {inbook},\n author = {Umaquinga-Criollo, A. C. and Tamayo-Quintero, J. D. and Moreno-García, M. N. and Riascos, J. A. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-61705-9_36},\n chapter = {Multi-expert Methods Evaluation on Financial and Economic Data: Introducing Bag of Experts},\n title = {Lecture Notes in Computer Science}\n}\n\n The use of machine learning into economics scenarios results appealing since it allows for automatically testing economic models and predict consumer/client behavior to support decision-making processes. The finance market typically uses a set of expert labelers or Bureau credit scores given by governmental or private agencies such as Experian, Equifax, and Creditinfo, among others. This work focuses on introducing a so-named Bag of Expert (BoE): a novel approach for creating multi-expert Learning (MEL) frameworks aimed to emulate real experts labeling (human-given labels) using neural networks. The MEL systems “learn” to perform decision-making tasks by considering a uniform number of labels per sample or individuals along with respective descriptive variables. The BoE is created similarly to Generative Adversarial Network (GANs), but rather than using noise or perturbation by a generator, we trained a feed-forward neural network to randomize sampling data, and either add or decrease hidden neurons. Additionally, this paper aims to investigate the performance on economics-related datasets of several state-of-the-art MEL methods, such as GPC, GPC-PLAT, KAAR, MA-LFC, MA-DGRL, and MA-MAE. To do so, we develop an experimental framework composed of four tests: the first one using novice experts; the second with proficient experts; the third is a mix of novices, intermediate and proficient experts, and the last one uses crowd-sourcing. Our BoE method presents promising results and can be suitable as an alternative to properly assess the reliability of both MEL methods and conventional labeler generators (i.e., virtual expert labelers).\n
\n\n\n\n \n\n \n \n \n \n \n \n Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador).\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; López-Batista, V., F.; Riascos, J., A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Remote Sensing. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando river from Ecuador)},\n type = {article},\n year = {2020},\n keywords = {Prototype selection,River pollution,Supervised classification,WSN},\n websites = {https://www.mdpi.com/2072-4292/12/12/1988},\n id = {cc652dfc-0db6-35a2-baef-6511a3ecafa8},\n created = {2021-05-10T23:31:46.635Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.635Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020b},\n private_publication = {false},\n abstract = {This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Riascos, Jaime A. and Peluffo-Ordóñez, Diego H.},\n doi = {10.3390/rs12121988},\n journal = {Remote Sensing}\n}\n\n This work presents a wireless sensor network (WSN) system able to determine the water quality of rivers. Particularly, we consider the Tahuando River from Ibarra, Ecuador, as a case study. The main goal of this research is to determine the river's status throughout its route, by generating data reports into an interactive user interface. To this end, we use an array of sensors collecting several measures such as: turbidity, temperature, water quality, pH, and temperature. Subsequently, from the information collected on an Internet-of-Things (IoT) server, we develop a data analysis scheme with both data representation and supervised classification. As an important result, our system outputs a map that shows the contamination levels of the river at different regions. Furthermore, in terms of data analysis performance, the proposed system reduces the data matrix by 97% from its original size, while it reaches a classification performance over 90%. Furthermore, as an additional remarkable result, we here introduce the so-called quantitative metric of balance (QMB), which measures the balance or ratio between performance and power consumption.\n
\n\n\n\n \n\n \n \n \n \n \n \n A new approach of service platform for water optimization in lettuce crops using wireless sensor network.\n \n \n \n \n\n\n \n Maya-Olalla, E.; Domínguez-Limaico, H.; Vásquez-Ayala, C.; Jaramillo-Vinueza, E.; Zambrano V, M.; Jácome-Ortega, A.; Rosero-Montalvo, P., D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Advances in Intelligent Systems and Computing, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A new approach of service platform for water optimization in lettuce crops using wireless sensor network},\n type = {inproceedings},\n year = {2020},\n keywords = {Cloud Computing,Irrigation,Precision agriculture,WSN},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29},\n id = {032f0462-20ce-36dc-bd6c-e66b90dbed68},\n created = {2021-05-10T23:31:46.669Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.669Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Maya-Olalla2020},\n private_publication = {false},\n abstract = {Wireless sensor network is implemented and communicated with the cloud through IPv6. The entire system is applied to precision irrigation systems for lettuce crops in Ecuador. The main objective is to provide optimization system for irrigation water for productive purposes and providing crops with the adequate amount of water needed for surviving and producing. To do that the system has a data acquisition system by sensors and this data is stored in web services. By improving the irrigation system crops can be planted throughout the year including summer, the system has a remarkable result for efficient water savings and lettuce crops.},\n bibtype = {inproceedings},\n author = {Maya-Olalla, Edgar and Domínguez-Limaico, Hernán and Vásquez-Ayala, Carlos and Jaramillo-Vinueza, Edgar and Zambrano V, Marcelo and Jácome-Ortega, Alexandra and Rosero-Montalvo, Paul D. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-29513-4_1},\n booktitle = {Advances in Intelligent Systems and Computing}\n}\n\n Wireless sensor network is implemented and communicated with the cloud through IPv6. The entire system is applied to precision irrigation systems for lettuce crops in Ecuador. The main objective is to provide optimization system for irrigation water for productive purposes and providing crops with the adequate amount of water needed for surviving and producing. To do that the system has a data acquisition system by sensors and this data is stored in web services. By improving the irrigation system crops can be planted throughout the year including summer, the system has a remarkable result for efficient water savings and lettuce crops.\n
\n\n\n\n \n\n \n \n \n \n \n \n Forecasting the Consumer Price Index (CPI) of Ecuador: A comparative study of predictive models.\n \n \n \n \n\n\n \n Riofrío, J.; Chang, O.; Revelo-Fuelagán, E., J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n International Journal on Advanced Science, Engineering and Information Technology. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Forecasting the Consumer Price Index (CPI) of Ecuador: A comparative study of predictive models},\n type = {article},\n year = {2020},\n keywords = {Consumer Price Index (CPI),Ecuador,Forecasting,Predictive models},\n websites = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10813},\n id = {207d2308-9f53-3970-8b33-315b015634b1},\n created = {2021-05-10T23:31:46.707Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.707Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Riofrio2020},\n private_publication = {false},\n abstract = {The Consumer Price Index (CPI) is one of the most important economic indicators for countries' characterization and is typically considered an official measure of inflation. The CPI considers the monthly price variation of a determined set of goods and services in a specific region, and it is key in the economic and social planning of a given country, hence the great importance of CPI forecasting. In this paper, we outline a comparative study of state-of-the-art predictive models over an Ecuadorian CPI dataset with 174 monthly registers, from 2005 to 2019. This small available dataset makes forecasting a challenging time-series-prediction task. Another difficulty is last years trend variation, which since mid-2016, has changed from an upward average of 3.5 points to a stable trend of ±0.8 points. This paper explores the performance of relevant predictive models when tackling the Ecuadorian CPI forecasting problem accurately for the next 12 months. For this, a comparative study considering a variety of predictive models is carried out, including the Neural networks approach using a Sequential Model with Long Short-Term Memory layers machine learning using Support Vector Regression, as well as classical approaches like SARIMA and Exponential Smoothing. We also consider big corporations tools like Facebook Prophet. As a result, the paper presents the best predictive models, and parameters found, along with Ecuadors CPI forecasting for the next 12 months (part of 2020). This information could be used for decisionmaking in several important topics related to social and economic activities.},\n bibtype = {article},\n author = {Riofrío, Juan and Chang, Oscar and Revelo-Fuelagán, E. J. and Peluffo-Ordóñez, Diego H.},\n doi = {10.18517/ijaseit.10.3.10813},\n journal = {International Journal on Advanced Science, Engineering and Information Technology}\n}\n\n The Consumer Price Index (CPI) is one of the most important economic indicators for countries' characterization and is typically considered an official measure of inflation. The CPI considers the monthly price variation of a determined set of goods and services in a specific region, and it is key in the economic and social planning of a given country, hence the great importance of CPI forecasting. In this paper, we outline a comparative study of state-of-the-art predictive models over an Ecuadorian CPI dataset with 174 monthly registers, from 2005 to 2019. This small available dataset makes forecasting a challenging time-series-prediction task. Another difficulty is last years trend variation, which since mid-2016, has changed from an upward average of 3.5 points to a stable trend of ±0.8 points. This paper explores the performance of relevant predictive models when tackling the Ecuadorian CPI forecasting problem accurately for the next 12 months. For this, a comparative study considering a variety of predictive models is carried out, including the Neural networks approach using a Sequential Model with Long Short-Term Memory layers machine learning using Support Vector Regression, as well as classical approaches like SARIMA and Exponential Smoothing. We also consider big corporations tools like Facebook Prophet. As a result, the paper presents the best predictive models, and parameters found, along with Ecuadors CPI forecasting for the next 12 months (part of 2020). This information could be used for decisionmaking in several important topics related to social and economic activities.\n
\n\n\n\n \n\n \n \n \n \n \n \n A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study.\n \n \n \n \n\n\n \n Godoy-Trujillo, P., E.; Rosero-Montalvo, P., D.; Suárez-Zambrano, L., E.; Peluffo-Ordoñez, D., H.; and Revelo-Fuelagán, E., J.\n\n\n \n\n\n\n In Advances in Intelligent Systems and Computing, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study},\n type = {inproceedings},\n year = {2020},\n keywords = {Data analysis,Embedded systems,Sensor data},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-52249-0_29},\n id = {7b1b5742-e20f-386e-bffa-ffc2786e940c},\n created = {2021-05-10T23:31:46.848Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.848Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Godoy-Trujillo2020},\n private_publication = {false},\n abstract = {Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).},\n bibtype = {inproceedings},\n author = {Godoy-Trujillo, Pamela E. and Rosero-Montalvo, Paul D. and Suárez-Zambrano, Luis E. and Peluffo-Ordoñez, Diego H. and Revelo-Fuelagán, E. J.},\n doi = {10.1007/978-3-030-52249-0_29},\n booktitle = {Advances in Intelligent Systems and Computing}\n}\n\n Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).\n
\n\n\n\n \n\n \n \n \n \n \n \n Comparison of controllers and mathematical modeling of a magnetic levitator.\n \n \n \n \n\n\n \n Herrera-Granda, E., P.; Herrera-Mayorga, K., A.; Herrera-Granda, I., D.; Martínez, L., M., S.; and H.peluffo-Ordoñez, D.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Comparison of controllers and mathematical modeling of a magnetic levitator},\n type = {article},\n year = {2020},\n keywords = {Comparison,Feedback Controller,Magnetic Levitator,Modeling,NARMA},\n websites = {https://search.proquest.com/docview/2350120753},\n id = {97db2766-d010-30fb-8d84-0e3167174f46},\n created = {2021-05-10T23:31:46.855Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.855Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Herrera-Granda2020},\n private_publication = {false},\n abstract = {This work presents the mathematical modeling and simulation of a magnetic levitator, and a comparison of different control techniques, applied on the system, in order to visualize which technique better stabilizes the magnetic levitator. The dynamical modeling was done applying the Newton Euler’s formulation, and the obtained equations were represented on the space state. Then the system was linearized applying Taylor’s approximation, and the obtained matrixes were used for the controller’s design. The employed controllers for the comparison were: Feedback Controller, Linear–quadratic regulator (LQR), and the neural-network based nonlinear autoregressive moving average controller (NARMA). Finally, the designed controllers and the plant were tested under several simulations using MATLAB and Symulink. The results proved that the three techniques were capable of stabilizing this particular system, and some significant advantages were found applying the NARMA and LQR techniques.},\n bibtype = {article},\n author = {Herrera-Granda, Erick P. and Herrera-Mayorga, Karla A. and Herrera-Granda, Israel D. and Martínez, Luz Marina Sierra and H.peluffo-Ordoñez, Diego},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n This work presents the mathematical modeling and simulation of a magnetic levitator, and a comparison of different control techniques, applied on the system, in order to visualize which technique better stabilizes the magnetic levitator. The dynamical modeling was done applying the Newton Euler’s formulation, and the obtained equations were represented on the space state. Then the system was linearized applying Taylor’s approximation, and the obtained matrixes were used for the controller’s design. The employed controllers for the comparison were: Feedback Controller, Linear–quadratic regulator (LQR), and the neural-network based nonlinear autoregressive moving average controller (NARMA). Finally, the designed controllers and the plant were tested under several simulations using MATLAB and Symulink. The results proved that the three techniques were capable of stabilizing this particular system, and some significant advantages were found applying the NARMA and LQR techniques.\n
\n\n\n\n \n\n \n \n \n \n \n \n Stochastic-and neuro-fuzzy-analysis-based characterization and classification of 4-channel phonocardiograms for cardiac murmur detection.\n \n \n \n \n\n\n \n Becerra, M., A.; Delgado-Trejos, E.; Mejía-Arboleda, C.; Peluffo-Ordóñez, D., H.; and Umaquinga-Criollo, A., C.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Stochastic-and neuro-fuzzy-analysis-based characterization and classification of 4-channel phonocardiograms for cardiac murmur detection},\n type = {article},\n year = {2020},\n keywords = {ANFIS,Cardiac murmur,Empirical mode decomposition,Hidden markov models,Phonocardiogram},\n websites = {https://search.proquest.com/docview/2451419849/fulltextPDF/F4AF5E590BD14D5EPQ/8},\n id = {1c57e2ee-b717-3f7b-be19-59ea17d57a00},\n created = {2021-05-10T23:31:46.884Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-08-25T21:58:34.448Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2020},\n private_publication = {false},\n abstract = {Cardiac murmurs (CMs) are the most common heart’s diseases that are typically diagnosed from phonocardiogram (PCG) and echocardiogram tests-often supported by computerized systems. Research works have traditionally addressed the automatic CM diagnosis with no distinctively use of the four auscultation areas (one of each cardiac valve), resulting-most probably-in a constrained, nonimpartial diagnostic procedure. This study presents a comparison among four different CM detection systems from a 4-channel PCG. We first evaluate the acoustic characteristics derived from Mel-Frequency Cepstral Coefficients, Empirical Mode Decomposition (EMD), and statistical measures. Secondly, a relevance analysis is carried out using Fuzzy Rough Feature Selection. Thirdly, Hidden Markov Models (HMM), Adaptative Neuro-Fuzzy Inference System (ANFIS), Naïve Bayes, and Gaussian Mixture Model were applied for classification and validated using a 50fold cross-validation procedure with a 70/30 split demonstrating the functionality and capability of EMD, Hidden Markov Model and ANFIS for CM classification.},\n bibtype = {article},\n author = {Becerra, Miguel A. and Delgado-Trejos, Edilson and Mejía-Arboleda, Cristian and Peluffo-Ordóñez, Diego H. and Umaquinga-Criollo, Ana C.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Cardiac murmurs (CMs) are the most common heart’s diseases that are typically diagnosed from phonocardiogram (PCG) and echocardiogram tests-often supported by computerized systems. Research works have traditionally addressed the automatic CM diagnosis with no distinctively use of the four auscultation areas (one of each cardiac valve), resulting-most probably-in a constrained, nonimpartial diagnostic procedure. This study presents a comparison among four different CM detection systems from a 4-channel PCG. We first evaluate the acoustic characteristics derived from Mel-Frequency Cepstral Coefficients, Empirical Mode Decomposition (EMD), and statistical measures. Secondly, a relevance analysis is carried out using Fuzzy Rough Feature Selection. Thirdly, Hidden Markov Models (HMM), Adaptative Neuro-Fuzzy Inference System (ANFIS), Naïve Bayes, and Gaussian Mixture Model were applied for classification and validated using a 50fold cross-validation procedure with a 70/30 split demonstrating the functionality and capability of EMD, Hidden Markov Model and ANFIS for CM classification.\n
\n\n\n\n \n\n \n \n \n \n \n \n Interactive Visualization Interfaces for Big Data Analysis Using Combination of Dimensionality Reduction Methods: A Brief Review.\n \n \n \n \n\n\n \n Umaquinga-Criollo, A., C.; Peluffo-Ordóñez, D., H.; Rosero-Montalvo, P., D.; Godoy-Trujillo, P., E.; and Benítez-Pereira, H.\n\n\n \n\n\n\n In Advances in Intelligent Systems and Computing, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Interactive Visualization Interfaces for Big Data Analysis Using Combination of Dimensionality Reduction Methods: A Brief Review},\n type = {inproceedings},\n year = {2020},\n keywords = {Big data,Business intelligence,Data mining,Dimensionality reduction,Interactive interface},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-37221-7_17},\n id = {45d9262a-0ed1-3bb3-902b-3470b62d2bfc},\n created = {2021-05-10T23:31:47.023Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.023Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Umaquinga-Criollo2020a},\n private_publication = {false},\n abstract = {The Big Data analysis allows to generate knowledge based on mathematical models that surpass human capabilities, and therefore it is necessary to have robust computer systems. In this connection, the dimensionality reduction (DR) allows to perform approximations to make data perceptible in a simple and compact way while also the computational cost is reduced. Additionally, interactive interfaces enable the user to work with algorithms involving complex mathematical and statistical processes typically aimed at providing weighting factors to each RD algorithm to find the best way to represent data at a low dimension. In this study, a bibliographic re-view of the different models of interactive interfaces for the analysis of Big Data using RD is presented, by considering different, existing proposals and approaches on how to display the information. Particularly, those approaches based on mental processes and uses of color along with an intuitive handling are of special interest.},\n bibtype = {inproceedings},\n author = {Umaquinga-Criollo, Ana C. and Peluffo-Ordóñez, Diego H. and Rosero-Montalvo, Paúl D. and Godoy-Trujillo, Pamela E. and Benítez-Pereira, Henry},\n doi = {10.1007/978-3-030-37221-7_17},\n booktitle = {Advances in Intelligent Systems and Computing}\n}\n\n The Big Data analysis allows to generate knowledge based on mathematical models that surpass human capabilities, and therefore it is necessary to have robust computer systems. In this connection, the dimensionality reduction (DR) allows to perform approximations to make data perceptible in a simple and compact way while also the computational cost is reduced. Additionally, interactive interfaces enable the user to work with algorithms involving complex mathematical and statistical processes typically aimed at providing weighting factors to each RD algorithm to find the best way to represent data at a low dimension. In this study, a bibliographic re-view of the different models of interactive interfaces for the analysis of Big Data using RD is presented, by considering different, existing proposals and approaches on how to display the information. Particularly, those approaches based on mental processes and uses of color along with an intuitive handling are of special interest.\n
\n\n\n\n \n\n \n \n \n \n \n \n Design and Tests to Implement Hyperconvergence into a DataCenter: Preliminary Results.\n \n \n \n \n\n\n \n Maya-Olalla, E.; Dominguez-Limaico, M.; Meneses-Narvaez, S.; Rosero-Montalvo, P., D.; Narvaez-Pupiales, S.; Zambrano Vizuete, M.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Advances in Intelligent Systems and Computing, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Design and Tests to Implement Hyperconvergence into a DataCenter: Preliminary Results},\n type = {inproceedings},\n year = {2020},\n keywords = {Availability,Data Center,Hyperconvergence,Proxmox},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-32022-5_6},\n id = {e8a22fc4-820c-3138-9e0e-38c122f53eba},\n created = {2021-05-10T23:31:47.024Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.024Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Maya-Olalla2020a},\n private_publication = {false},\n abstract = {Hyperconvergence is a new technological trend that integrates and centralizes the functions of network, storage and computing in a single infrastructure, facilitating the administration, operability and scalability of a Data Center as a whole, benets that do not provide an architecture of traditional network or virtualization-specic technologies. This research based on qualitative and experimental methods suggests a model of Implementation of a HyperConvergent Architecture for the management of the Data Center of the Universidad Técnica del Norte, as a competitive and high-performance Open Source alternative for the integration of physical and virtual components. The suggested deployment model is based on the virtualization platform Proxmox VE, CEPH (Storage Software Platform), vSwitch (network scheme) and KVM (equipment virtualization). It includes a centralized domain and it provides a 99.88% availability rate making it in total harmony with functionalities requiring high availability. The results show the simplicity of the system: efficient execution of all applications, migrations of virtual machines from node to node, inactivity times between 50.3 ms and 53 ms, processing acceleration providing agility to IT operations without forgetting that its implementation and its start-up times are relatively low.},\n bibtype = {inproceedings},\n author = {Maya-Olalla, Edgar and Dominguez-Limaico, Mauricio and Meneses-Narvaez, Santiago and Rosero-Montalvo, Paul D. and Narvaez-Pupiales, Sandra and Zambrano Vizuete, Marcelo and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-32022-5_6},\n booktitle = {Advances in Intelligent Systems and Computing}\n}\n\n Hyperconvergence is a new technological trend that integrates and centralizes the functions of network, storage and computing in a single infrastructure, facilitating the administration, operability and scalability of a Data Center as a whole, benets that do not provide an architecture of traditional network or virtualization-specic technologies. This research based on qualitative and experimental methods suggests a model of Implementation of a HyperConvergent Architecture for the management of the Data Center of the Universidad Técnica del Norte, as a competitive and high-performance Open Source alternative for the integration of physical and virtual components. The suggested deployment model is based on the virtualization platform Proxmox VE, CEPH (Storage Software Platform), vSwitch (network scheme) and KVM (equipment virtualization). It includes a centralized domain and it provides a 99.88% availability rate making it in total harmony with functionalities requiring high availability. The results show the simplicity of the system: efficient execution of all applications, migrations of virtual machines from node to node, inactivity times between 50.3 ms and 53 ms, processing acceleration providing agility to IT operations without forgetting that its implementation and its start-up times are relatively low.\n
\n\n\n\n \n\n \n \n \n \n \n \n Inverse Data Visualization Framework (IDVF): Towards a Prior-Knowledge-Driven Data Visualization.\n \n \n \n \n\n\n \n Vélez-Falconí, M.; González-Vergara, J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Communications in Computer and Information Science, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Inverse Data Visualization Framework (IDVF): Towards a Prior-Knowledge-Driven Data Visualization},\n type = {inproceedings},\n year = {2020},\n keywords = {Data visualization,Dimensionality reduction,Interaction model,Kernel functions},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-61702-8_19},\n id = {8e568fd5-9733-3182-881a-5d1e0f217a8d},\n created = {2021-05-10T23:31:47.281Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.281Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Velez-Falconi2020},\n private_publication = {false},\n abstract = {Broadly, the area of dimensionality reduction (DR) is aimed at providing ways to harness high dimensional (HD) information through the generation of lower dimensional (LD) representations, by following a certain data-structure-preservation criterion. In literature there have been reported dozens of DR techniques, which are commonly used as a pre-processing stage withing exploratory data analyses for either machine learning or information visualization (IV) purposes. Nonetheless, the selection of a proper method is a nontrivial and -very often- toilsome task. In this sense, a readily and natural way to incorporate an expert’s criterion into the analysis process, while making this task more tractable is the use of interactive IV approaches. Regarding the incorporation of experts’ prior knowledge there still exists a range of open issues. In this work, we introduce a here-named Inverse Data Visualization Framework (IDVF), which is an initial approach to make the input prior knowledge directly interpretable. Our framework is based on 2D-scatter-plots visuals and spectral kernel-driven DR techniques. To capture either the user’s knowledge or requirements, users are requested to provide changes or movements of data points in such a manner that resulting points are located where best convenient according to the user’s criterion. Next, following a Kernel Principal Component Analysis approach and a mixture of kernel matrices, our framework accordingly estimates an approximate LD space. Then, the rationale behind the proposed IDVF is to adjust as accurate as possible the resulting LD space to the representation fulfilling users’ knowledge and requirements. Results are greatly promising and open the possibility to novel DR-based visualizations approaches.},\n bibtype = {inproceedings},\n author = {Vélez-Falconí, M. and González-Vergara, J. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-61702-8_19},\n booktitle = {Communications in Computer and Information Science}\n}\n\n Broadly, the area of dimensionality reduction (DR) is aimed at providing ways to harness high dimensional (HD) information through the generation of lower dimensional (LD) representations, by following a certain data-structure-preservation criterion. In literature there have been reported dozens of DR techniques, which are commonly used as a pre-processing stage withing exploratory data analyses for either machine learning or information visualization (IV) purposes. Nonetheless, the selection of a proper method is a nontrivial and -very often- toilsome task. In this sense, a readily and natural way to incorporate an expert’s criterion into the analysis process, while making this task more tractable is the use of interactive IV approaches. Regarding the incorporation of experts’ prior knowledge there still exists a range of open issues. In this work, we introduce a here-named Inverse Data Visualization Framework (IDVF), which is an initial approach to make the input prior knowledge directly interpretable. Our framework is based on 2D-scatter-plots visuals and spectral kernel-driven DR techniques. To capture either the user’s knowledge or requirements, users are requested to provide changes or movements of data points in such a manner that resulting points are located where best convenient according to the user’s criterion. Next, following a Kernel Principal Component Analysis approach and a mixture of kernel matrices, our framework accordingly estimates an approximate LD space. Then, the rationale behind the proposed IDVF is to adjust as accurate as possible the resulting LD space to the representation fulfilling users’ knowledge and requirements. Results are greatly promising and open the possibility to novel DR-based visualizations approaches.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Data-Driven Approach for Automatic Classification of Extreme Precipitation Events: Preliminary Results.\n \n \n \n \n\n\n \n González-Vergara, J.; Escobar-González, D.; Chaglla-Aguagallo, D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Communications in Computer and Information Science, 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {A Data-Driven Approach for Automatic Classification of Extreme Precipitation Events: Preliminary Results},\n type = {inproceedings},\n year = {2020},\n keywords = {Data driven,Extreme precipitation,Feature selection,Forecasting,PCA,Relief,SVM},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-61702-8_14},\n id = {09b5f99f-6dc1-35b6-b2e2-586b16642d98},\n created = {2021-05-10T23:31:47.333Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.333Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Gonzalez-Vergara2020},\n private_publication = {false},\n abstract = {Even though there exists no universal definition, in the South America Andean Region, extreme precipitation events can be referred to the period of time in which standard thresholds of precipitation are abruptly exceeded. Therefore, their timely forecasting is of great interest for decision makers from many fields, such as: urban planning entities, water researchers and in general, climate related institutions. In this paper, a data-driven study is performed to classify and anticipate extreme precipitation events through hydroclimate features. Since the analysis of precipitation-events-related time series involves complex patterns, input data requires undergoing both pre-processing steps and feature selection methods, in order to achieve a high performance at the data classification stage itself. In this sense, in this study, both individual Principal Component Analysis (PCA) and Regresional Relief (RR) as well as a cascade approach mixing both are considered. Subsequently, the classification is performed by a Support-Vector-Machine-based classifier (SVM). Results reflect the suitability of an approach involving feature selection and classification for precipitation events detection purposes. A remarkable result is the fact that a reduced dataset obtained by applying RR mixed with PCA discriminates better than RR alone but does not significantly hence the SVM rate at two- and three-class problems as done by PCA itself.},\n bibtype = {inproceedings},\n author = {González-Vergara, J. and Escobar-González, D. and Chaglla-Aguagallo, D. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-61702-8_14},\n booktitle = {Communications in Computer and Information Science}\n}\n\n Even though there exists no universal definition, in the South America Andean Region, extreme precipitation events can be referred to the period of time in which standard thresholds of precipitation are abruptly exceeded. Therefore, their timely forecasting is of great interest for decision makers from many fields, such as: urban planning entities, water researchers and in general, climate related institutions. In this paper, a data-driven study is performed to classify and anticipate extreme precipitation events through hydroclimate features. Since the analysis of precipitation-events-related time series involves complex patterns, input data requires undergoing both pre-processing steps and feature selection methods, in order to achieve a high performance at the data classification stage itself. In this sense, in this study, both individual Principal Component Analysis (PCA) and Regresional Relief (RR) as well as a cascade approach mixing both are considered. Subsequently, the classification is performed by a Support-Vector-Machine-based classifier (SVM). Results reflect the suitability of an approach involving feature selection and classification for precipitation events detection purposes. A remarkable result is the fact that a reduced dataset obtained by applying RR mixed with PCA discriminates better than RR alone but does not significantly hence the SVM rate at two- and three-class problems as done by PCA itself.\n
\n\n\n\n \n\n \n \n \n \n \n \n Introducing the Concept of Interaction Model for Interactive Dimensionality Reduction and Data Visualization.\n \n \n \n \n\n\n \n Ortega-Bustamante, M., C.; Hasperué, W.; Peluffo-Ordóñez, D., H.; Paéz-Jaime, M.; Marrufo-Rodríguez, I.; Rosero-Montalvo, P.; Umaquinga-Criollo, A., C.; and Vélez-Falconi, M.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Introducing the Concept of Interaction Model for Interactive Dimensionality Reduction and Data Visualization},\n type = {inproceedings},\n year = {2020},\n keywords = {Data visualization,Dimensionality reduction,Interaction model,Kernel functions},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-58802-1_14},\n id = {5a39e753-fcd0-30eb-ad3f-40cb819d1590},\n created = {2021-05-10T23:31:47.432Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.432Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Ortega-Bustamante2020},\n private_publication = {false},\n abstract = {This letter formally introduces the concept of interaction model (IM), which has been used either directly or tangentially in previous works but never defined. Broadly speaking, an IM consists of the use of a mixture of dimensionality reduction (DR) techniques within an interactive data visualization framework. The rationale of creating an IM is the need for simultaneously harnessing the benefit of several DR approaches to reach a data representation being intelligible and/or fitted to any user’s criterion. As a remarkable advantage, an IM naturally provides a generalized framework for designing both interactive DR approaches as well as readily-to-use data visualization interfaces. In addition to a comprehensive overview on basics of data representation and dimensionality reduction, the main contribution of this manuscript is the elegant definition of the concept of IM in mathematical terms.},\n bibtype = {inproceedings},\n author = {Ortega-Bustamante, M. C. and Hasperué, W. and Peluffo-Ordóñez, D. H. and Paéz-Jaime, M. and Marrufo-Rodríguez, I. and Rosero-Montalvo, P. and Umaquinga-Criollo, A. C. and Vélez-Falconi, M.},\n doi = {10.1007/978-3-030-58802-1_14},\n booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n This letter formally introduces the concept of interaction model (IM), which has been used either directly or tangentially in previous works but never defined. Broadly speaking, an IM consists of the use of a mixture of dimensionality reduction (DR) techniques within an interactive data visualization framework. The rationale of creating an IM is the need for simultaneously harnessing the benefit of several DR approaches to reach a data representation being intelligible and/or fitted to any user’s criterion. As a remarkable advantage, an IM naturally provides a generalized framework for designing both interactive DR approaches as well as readily-to-use data visualization interfaces. In addition to a comprehensive overview on basics of data representation and dimensionality reduction, the main contribution of this manuscript is the elegant definition of the concept of IM in mathematical terms.\n
\n\n\n\n \n\n \n \n \n \n \n \n Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Erazo-Chamorro, V., C.; López-Batista, V., F.; Moreno-García, M., N.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Sensors (Switzerland). 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Environment monitoring of rose crops greenhouse based on autonomous vehicles with a wsn and data analysis},\n type = {article},\n year = {2020},\n keywords = {Ambient intelligence,Autonomous vehicles,Monitoring systems,Roses crops,Wireless sensor networks},\n websites = {https://www.mdpi.com/1424-8220/20/20/5905},\n id = {86695b64-b1b5-3ffe-abef-b3c4303a356f},\n created = {2021-05-10T23:31:47.482Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.482Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2020},\n private_publication = {false},\n abstract = {This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Erazo-Chamorro, Vanessa C. and López-Batista, Vivian F. and Moreno-García, María N. and Peluffo-Ordóñez, Diego H.},\n doi = {10.3390/s20205905},\n journal = {Sensors (Switzerland)}\n}\n\n This work presents a monitoring system for the environmental conditions of rose flower-cultivation in greenhouses. Its main objective is to improve the quality of the crops while regulating the production time. To this end, a system consisting of autonomous quadruped vehicles connected with a wireless sensor network (WSN) is developed, which supports the decision-making on type of action to be carried out in a greenhouse to maintain the appropriate environmental conditions for rose cultivation. A data analysis process was carried out, aimed at designing an in-situ intelligent system able to make proper decisions regarding the cultivation process. This process involves stages for balancing data, prototype selection, and supervised classification. The proposed system produces a significant reduction of data in the training set obtained by the WSN while reaching a high classification performance in real conditions—amounting to 90 % and 97.5%, respectively. As a remarkable outcome, it is also provided an approach to ensure correct planning and selection of routes for the autonomous vehicle through the global positioning system.\n
\n\n\n\n \n\n \n \n \n \n \n \n A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of southern Colombia.\n \n \n \n \n\n\n \n Parraga-Alava, J.; Moncayo-Nacaza, J., D.; Revelo-Fuelagán, J.; Rosero-Montalvo, P., D.; Anaya-Isaza, A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Data in Brief. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of southern Colombia},\n type = {article},\n year = {2020},\n keywords = {Electric power consumption,Forecasting,Machine learning,Smart grid,Socio-demographic data},\n websites = {https://www.sciencedirect.com/science/article/pii/S2352340920301402},\n id = {9174c5e6-c4ee-32e6-961e-486d2c37452c},\n created = {2021-05-10T23:31:47.914Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.914Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Parraga-Alava2020},\n private_publication = {false},\n abstract = {In this article, we introduce a data set concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The data set consists of 4427 socio-demographic characteristics, and 7 power-consumption-referred measured values. Data were fully collected by the company Centrales Eléctricas de Nariño (CEDENAR) according to the client consumption records. Power consumption data collection was carried following a manual procedure wherein company workers are in charge of manually registering the readings (measured in kWh) reported by the electric energy meters installed at each housing/building. Released data set is aimed at providing researchers a suitable input for designing and assessing the performance of forecasting, modelling, simulation and optimization approaches applied to electric power consumption prediction and characterization problems. The data set, so-named in shorthand PCSTCOL, is freely and publicly available at https://doi.org/10.17632/xbt7scz5ny.3.},\n bibtype = {article},\n author = {Parraga-Alava, Jorge and Moncayo-Nacaza, Jorge Dario and Revelo-Fuelagán, Javier and Rosero-Montalvo, Paul D. and Anaya-Isaza, Andrés and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.1016/j.dib.2020.105246},\n journal = {Data in Brief}\n}\n\n In this article, we introduce a data set concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The data set consists of 4427 socio-demographic characteristics, and 7 power-consumption-referred measured values. Data were fully collected by the company Centrales Eléctricas de Nariño (CEDENAR) according to the client consumption records. Power consumption data collection was carried following a manual procedure wherein company workers are in charge of manually registering the readings (measured in kWh) reported by the electric energy meters installed at each housing/building. Released data set is aimed at providing researchers a suitable input for designing and assessing the performance of forecasting, modelling, simulation and optimization approaches applied to electric power consumption prediction and characterization problems. The data set, so-named in shorthand PCSTCOL, is freely and publicly available at https://doi.org/10.17632/xbt7scz5ny.3.\n
\n\n\n\n \n\n \n \n \n \n \n \n Analysis of the thermal behavior in the goldwind S50/750 wind turbines installed in the wind farm gibara ii using cad-cae tools.\n \n \n \n \n\n\n \n Feliciano, Y., A.; Trinchet, C., A.; Meléndez, E.; Lorente-Leyva, L., L.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n International Journal of Mechanical and Production Engineering Research and Development. 2020.\n \n\n\n\n
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\n\n\n@article{\n title = {Analysis of the thermal behavior in the goldwind S50/750 wind turbines installed in the wind farm gibara ii using cad-cae tools},\n type = {article},\n year = {2020},\n keywords = {Goldwind Wind Turbines,Temperatures & CAD/CAE Tools,Thermal Behavior,Wind Farm},\n websites = {http://www.tjprc.org/view_paper.php?id=12471},\n id = {2d2a2a2b-c0ee-3ed4-8c04-75d4c01067b5},\n created = {2021-05-10T23:31:47.918Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.918Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Feliciano2020},\n private_publication = {false},\n abstract = {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.},\n bibtype = {article},\n author = {Feliciano, Yorley Arbella and Trinchet, Carlos A. and Meléndez, Ernesto and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H.},\n doi = {10.24247/ijmperdapr202032},\n journal = {International Journal of Mechanical and Production Engineering Research and Development}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios.\n \n \n \n \n\n\n \n Herrera-Granda, I., D.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; and Alemany, M., M., E.\n\n\n \n\n\n\n pages 245-258. Lecture Notes in Computer Science, 2020.\n \n\n\n\n
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\n\n\n\n@inbook{\n type = {inbook},\n year = {2020},\n pages = {245-258},\n websites = {http://link.springer.com/10.1007/978-3-030-64580-9_21},\n publisher = {Lecture Notes in Computer Science},\n id = {df4949de-a6d3-3a55-ab48-7dd67a63f43b},\n created = {2021-05-10T23:31:48.061Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:48.061Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n bibtype = {inbook},\n author = {Herrera-Granda, Israel D. and Lorente-Leyva, Leandro L. and Peluffo-Ordóñez, Diego H. and Alemany, M. M. E.},\n doi = {10.1007/978-3-030-64580-9_21},\n chapter = {A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios}\n}\n\n
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\n \n \n\n \n \n \n \n \n \n Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; López-Batista, V., F.; Peluffo-Ordóñez, D., H.; Lorente-Leyva, L., L.; and Blanco-Valencia, X., P.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 686-696. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Data analysis,Environmental monitoring,Environmental science computing,Intelligent system},\n pages = {686-696},\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_58},\n id = {9c581990-70ce-35a5-a2f5-5b860da79bd4},\n created = {2021-05-10T23:31:44.865Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:44.865Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019b},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-030-29859-3_58},\n chapter = {Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Medical dispenser of control and monitoring services for the elderly health care institute hogar del anciano “san vicente de paúl” from atuntaqui (Ecuador).\n \n \n \n \n\n\n \n Encalada-Grijalva, M., T.; Narváez-Pupiales, S., K.; Umaquinga-Criollo, A., C.; Suárez-Zambrano, L., E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Medical dispenser of control and monitoring services for the elderly health care institute hogar del anciano “san vicente de paúl” from atuntaqui (Ecuador)},\n type = {article},\n year = {2019},\n keywords = {Arduino,Database,Elderly,Electronic Dispenser,MySQL},\n websites = {https://search.proquest.com/openview/ca355d43bc1ac0d2c3428cf5f1030ce1/1?pq-origsite=gscholar&cbl=1006393},\n id = {3875c471-ebe9-32ca-bfa8-174190d05f50},\n created = {2021-05-10T23:31:44.869Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:44.869Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Encalada-Grijalva2019},\n private_publication = {false},\n abstract = {Aging is a stage of life of the human being that presents psychological, social, physiological changes, as well as the deterioration of their physical capacities. Elderly Home “San Vicente de Paúl” of the city of Atuntaqui (Ecuador), older adults take medicines to treat diseases such as high blood pressure, osteoarthritis, osteoporosis, cognitive deterioration, depression, hypothyroidism, gastritis, anemia, among others. The medical staff, because they do not keep a record of the dosage of medications in the pre-established hours, has caused delays, omissions in the same and a decline in their health status. The present research designs and develops an embedded system to control and monitor the supply of medicines through two types of notifications to the medical department: In the first instance, by sending text messages via GSM; in the absence of a response, the second notification is issued by means of a voice call to the nurse on duty in order to safeguard the adequate intake of medicine and comply fully with the treatments prescribed by the doctor and improve the quality of life of the adult higher.},\n bibtype = {article},\n author = {Encalada-Grijalva, María T. and Narváez-Pupiales, Sandra K. and Umaquinga-Criollo, Ana C. and Suárez-Zambrano, Luis E. and Peluffo-Ordóñez, Diego H.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Aging is a stage of life of the human being that presents psychological, social, physiological changes, as well as the deterioration of their physical capacities. Elderly Home “San Vicente de Paúl” of the city of Atuntaqui (Ecuador), older adults take medicines to treat diseases such as high blood pressure, osteoarthritis, osteoporosis, cognitive deterioration, depression, hypothyroidism, gastritis, anemia, among others. The medical staff, because they do not keep a record of the dosage of medications in the pre-established hours, has caused delays, omissions in the same and a decline in their health status. The present research designs and develops an embedded system to control and monitor the supply of medicines through two types of notifications to the medical department: In the first instance, by sending text messages via GSM; in the absence of a response, the second notification is issued by means of a voice call to the nurse on duty in order to safeguard the adequate intake of medicine and comply fully with the treatments prescribed by the doctor and improve the quality of life of the adult higher.\n
\n\n\n\n \n\n \n \n \n \n \n \n Satellite-image-based crop identification using unsupervised machine learning techniques: Preliminary results.\n \n \n \n \n\n\n \n Revelo, M., Y., M.; Gómez Menoza, J., B.; and Peluffo Ordoñez, D., H.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Satellite-image-based crop identification using unsupervised machine learning techniques: Preliminary results},\n type = {article},\n year = {2019},\n keywords = {Landsat satellite,Max-min algorithm,Parzen’s probability density function,Satellite image},\n websites = {https://search.proquest.com/openview/07a5294795bdf4c5423a32a23b32a228},\n id = {21ee2e0e-d7fb-3e28-841d-ddf952e53a0a},\n created = {2021-05-10T23:31:45.268Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.268Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Revelo2019},\n private_publication = {false},\n abstract = {Artificial vision and image processing have been widely used in the field of scientific research related to satellite landscapes with purposes, like soil classification, detection of changes in urban and rural areas, among others. The existing prototypes have reported meaningful results, notwithstanding, the implementation of a system more properly fitting the nature of the images by taking into account factors such as lighting control, noise reduction and presence of clouds is still an open and of-great-interest problem. This paper presents an initial satellite image processing methodology for clustering crops. The proposed methodology is as follows: Firstly, data pre-processing is carried out, followed by a feature extraction stage. Secondly, image clustering is performed by means of a probabilistic algorithm. This methodology is validated with the Campo Verde database built over crops from a Brazil’s area. Our approach reaches a classification percentage 87.97%, sensitivity 87.1%, specificity 97.22 and f1_score 71.78 %.},\n bibtype = {article},\n author = {Revelo, Mónica Yolanda Moreno and Gómez Menoza, Juan Bernardo and Peluffo Ordoñez, Diego Hernán},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Artificial vision and image processing have been widely used in the field of scientific research related to satellite landscapes with purposes, like soil classification, detection of changes in urban and rural areas, among others. The existing prototypes have reported meaningful results, notwithstanding, the implementation of a system more properly fitting the nature of the images by taking into account factors such as lighting control, noise reduction and presence of clouds is still an open and of-great-interest problem. This paper presents an initial satellite image processing methodology for clustering crops. The proposed methodology is as follows: Firstly, data pre-processing is carried out, followed by a feature extraction stage. Secondly, image clustering is performed by means of a probabilistic algorithm. This methodology is validated with the Campo Verde database built over crops from a Brazil’s area. Our approach reaches a classification percentage 87.97%, sensitivity 87.1%, specificity 97.22 and f1_score 71.78 %.\n
\n\n\n\n \n\n \n \n \n \n \n \n Optimization of the Network of Urban Solid Waste Containers: A Case Study.\n \n \n \n \n\n\n \n Herrera-Granda, I., D.; Imbaquingo-Usiña, W., G.; Lorente-Leyva, L., L.; Herrera-Granda, E., P.; Peluffo-Ordóñez, D., H.; and Rossit, D., G.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 578-589. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Collection network,Facility Location Problem,NP-hard,Optimization,Reverse logistics,Urban solid waste},\n pages = {578-589},\n websites = {http://link.springer.com/10.1007/978-3-030-05532-5_44},\n id = {e56e94f8-b34e-3a1e-990e-2c2e19a4a9a4},\n created = {2021-05-10T23:31:45.411Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.411Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Herrera-Granda2019b},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-030-05532-5_44},\n chapter = {Optimization of the Network of Urban Solid Waste Containers: A Case Study},\n title = {Communications in Computer and Information Science}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Public urban transport optimization by means of tabu search and pso algorithms: Medellín, colombia.\n \n \n \n \n\n\n \n Betancur-Delgado, L.; Becerra, M., A.; Duque-Mejía, C.; Peluffo-Ordóñez, D.; and Álvarez-Uribe, K., C.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Public urban transport optimization by means of tabu search and pso algorithms: Medellín, colombia},\n type = {article},\n year = {2019},\n keywords = {Bus scheduling problem,Particle swarm optimization,Tabu search optimization,Urban public transport: Route optimization},\n websites = {https://search.proquest.com/openview/ec8601c82489c20f58286629e316c348},\n id = {a1f32a30-f873-39a8-8410-248661929432},\n created = {2021-05-10T23:31:45.604Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.604Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Betancur-Delgado2019},\n private_publication = {false},\n abstract = {Urban public transport in the city of Medellín (Col) has had a positive development, however insufficient due to the increase in population density. This paper presents a comparative analysis of the Tabu Search algorithm (TS) and the Particle Swarm Optimization algorithm (PSO). It proposes an optimization of the urban public transport service in the northern area of the city, using variables from different organizational units (vehicle mechanics, human resources management, environmental and operational management). The algorithms achieved convergence with the objective of maximizing profitability regarding the use of buses during the operating day. A route planning proposal was obtained that allows a user’s increment of 25%, improve service times, generating sustainable development for the environment and the transport company.},\n bibtype = {article},\n author = {Betancur-Delgado, Laura and Becerra, Miguel A. and Duque-Mejía, Carolina and Peluffo-Ordóñez, Diego and Álvarez-Uribe, Karla C.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Urban public transport in the city of Medellín (Col) has had a positive development, however insufficient due to the increase in population density. This paper presents a comparative analysis of the Tabu Search algorithm (TS) and the Particle Swarm Optimization algorithm (PSO). It proposes an optimization of the urban public transport service in the northern area of the city, using variables from different organizational units (vehicle mechanics, human resources management, environmental and operational management). The algorithms achieved convergence with the objective of maximizing profitability regarding the use of buses during the operating day. A route planning proposal was obtained that allows a user’s increment of 25%, improve service times, generating sustainable development for the environment and the transport company.\n
\n\n\n\n \n\n \n \n \n \n \n \n Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; López-Batista, V., F.; Peluffo-Ordóñez, D., H.; Erazo-Chamorro, V., C.; and Arciniega-Rocha, R., P.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 234-243. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Alcohol detection,Drunk detection,Prototype selection,Sensors,Supervised classification},\n pages = {234-243},\n websites = {http://link.springer.com/10.1007/978-3-030-19651-6_23},\n id = {cf27fda4-0ac6-380e-a71b-632a230686a3},\n created = {2021-05-10T23:31:45.897Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.897Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019a},\n private_publication = {false},\n abstract = {This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and López-Batista, Vivian F. and Peluffo-Ordóñez, Diego H. and Erazo-Chamorro, Vanessa C. and Arciniega-Rocha, Ricardo P.},\n doi = {10.1007/978-3-030-19651-6_23},\n chapter = {Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n This work presents a system for detecting excess alcohol in drivers to reduce road traffic accidents. To do so, criteria such as alcohol concentration the environment, a facial temperature of the driver and width of the pupil are considered. To measure the corresponding variables, the data acquisition procedure uses sensors and artificial vision. Subsequently, data analysis is performed into stages for prototype selection and supervised classification algorithms. Accordingly, the acquired data can be stored and processed in a system with low-computational resources. As a remarkable result, the amount of training samples is significantly reduced, while an admissible classification performance is achieved - reaching then suitable settings regarding the given device’s conditions.\n
\n\n\n\n \n\n \n \n \n \n \n \n Optimization-based algorithms applied in photovoltaic systems.\n \n \n \n \n\n\n \n Fernández, Y., F.; Tobar, A., C.; Peluffo-Ordóñez, D., H.; Manosalvas, T., S.; and Miranda, R.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Optimization-based algorithms applied in photovoltaic systems},\n type = {article},\n year = {2019},\n keywords = {Algorithms,Dynamic programming,Photovoltaic energy},\n websites = {https://search.proquest.com/openview/33e52f4b710e1368bead8eda6346684a},\n id = {9ed2099f-6db4-3899-ae30-4eebebe666c4},\n created = {2021-05-10T23:31:46.047Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.047Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Fernandez2019},\n private_publication = {false},\n abstract = {Network codes have been developed to facilitate the integration of power plants into the electrical system; a specific case is that concerning the performance of large scale photovoltaic power plants, which represents a drawback for operators of transmission systems due to the way in which solar irradiance varies during the day. The present study is focused on a group of models that are based on dynamic programming with recursive algorithms. Broadly, such algorithms may significantly benefit to the decision making in the field of the optimization of the photovoltaic systems. The main contribution of this work lies on the the compilation of a group of models whose recursive algorithms allow evaluating each stage of a given process and related to a group of parameters that can be controlled within a dynamic model whose nuances vary depending on other submodels associated with some families of classic models of linear and nonlinear programming.},\n bibtype = {article},\n author = {Fernández, Yasmany Fernández and Tobar, Ana Cabrera and Peluffo-Ordóñez, Diego H. and Manosalvas, Teresa Sánchez and Miranda, Ridelio},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n Network codes have been developed to facilitate the integration of power plants into the electrical system; a specific case is that concerning the performance of large scale photovoltaic power plants, which represents a drawback for operators of transmission systems due to the way in which solar irradiance varies during the day. The present study is focused on a group of models that are based on dynamic programming with recursive algorithms. Broadly, such algorithms may significantly benefit to the decision making in the field of the optimization of the photovoltaic systems. The main contribution of this work lies on the the compilation of a group of models whose recursive algorithms allow evaluating each stage of a given process and related to a group of parameters that can be controlled within a dynamic model whose nuances vary depending on other submodels associated with some families of classic models of linear and nonlinear programming.\n
\n\n\n\n \n\n \n \n \n \n \n \n Artificial Neural Networks for Urban Water Demand Forecasting: A Case Study.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Pavón-Valencia, J., F.; Montero-Santos, Y.; Herrera-Granda, I., D.; Herrera-Granda, E., P.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Journal of Physics: Conference Series, 1284: 012004. 8 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Artificial Neural Networks for Urban Water Demand Forecasting: A Case Study},\n type = {article},\n year = {2019},\n pages = {012004},\n volume = {1284},\n websites = {https://iopscience.iop.org/article/10.1088/1742-6596/1284/1/012004},\n month = {8},\n id = {5ccfc039-4e0b-3bee-a9f6-0fd37d8e1ad2},\n created = {2021-05-10T23:31:46.057Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.057Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lorente-Leyva2019a},\n private_publication = {false},\n abstract = {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.},\n bibtype = {article},\n 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.},\n doi = {10.1088/1742-6596/1284/1/012004},\n journal = {Journal of Physics: Conference Series}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Exploring the Characterization and Classification of EEG Signals for a Computer-Aided Epilepsy Diagnosis System.\n \n \n \n \n\n\n \n Vega-Gualán, E.; Vargas, A.; Becerra, M.; Umaquinga, A.; Riascos, J., A.; and Peluffo, D.\n\n\n \n\n\n\n Volume 11976 LNAI . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 189-198. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Electroencephalogram (EEG),Epilepsy diagnosis,K-Nearest Neighbors (KNN),Linear Discriminant Analysis (LDA),Quadratic Discriminant Analysis (QDA),Support Vector Machine (SVM)},\n pages = {189-198},\n volume = {11976 LNAI},\n websites = {http://link.springer.com/10.1007/978-3-030-37078-7_19},\n id = {14e2c5d0-580c-3a22-afd6-f31821153ae9},\n created = {2021-05-10T23:31:46.106Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.106Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2019, Springer Nature Switzerland AG. Epilepsy occurs when localized electrical activity of neurons suffer from an imbalance. One of the most adequate methods for diagnosing and monitoring is via the analysis of electroencephalographic (EEG) signals. Despite there is a wide range of alternatives to characterize and classify EEG signals for epilepsy analysis purposes, many key aspects related to accuracy and physiological interpretation are still considered as open issues. In this paper, this work performs an exploratory study in order to identify the most adequate frequently-used methods for characterizing and classifying epileptic seizures. In this regard, a comparative study is carried out on several subsets of features using four representative classifiers: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The framework uses a well-known epilepsy dataset and runs several experiments for two and three classification problems. The results suggest that DWT decomposition with SVM is the most suitable combination.},\n bibtype = {inbook},\n author = {Vega-Gualán, Emil and Vargas, Andrés and Becerra, Miguel and Umaquinga, Ana and Riascos, Jaime A. and Peluffo, Diego},\n doi = {10.1007/978-3-030-37078-7_19},\n chapter = {Exploring the Characterization and Classification of EEG Signals for a Computer-Aided Epilepsy Diagnosis System},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n © 2019, Springer Nature Switzerland AG. Epilepsy occurs when localized electrical activity of neurons suffer from an imbalance. One of the most adequate methods for diagnosing and monitoring is via the analysis of electroencephalographic (EEG) signals. Despite there is a wide range of alternatives to characterize and classify EEG signals for epilepsy analysis purposes, many key aspects related to accuracy and physiological interpretation are still considered as open issues. In this paper, this work performs an exploratory study in order to identify the most adequate frequently-used methods for characterizing and classifying epileptic seizures. In this regard, a comparative study is carried out on several subsets of features using four representative classifiers: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The framework uses a well-known epilepsy dataset and runs several experiments for two and three classification problems. The results suggest that DWT decomposition with SVM is the most suitable combination.\n
\n\n\n\n \n\n \n \n \n \n \n \n Low Resolution Electroencephalographic-Signals-Driven Semantic Retrieval: Preliminary Results.\n \n \n \n \n\n\n \n Becerra, M., A.; Londoño-Delgado, E.; Botero-Henao, O., I.; Marín-Castrillón, D.; Mejia-Arboleda, C.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Volume 11466 LNBI . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 333-342. Springer Verlag, 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Electroencephalographic signal,Machine learning,Semantic category,Semantic retrieval,Signal processing},\n pages = {333-342},\n volume = {11466 LNBI},\n websites = {http://link.springer.com/10.1007/978-3-030-17935-9_30},\n publisher = {Springer Verlag},\n id = {6ce257cb-f31a-3589-a5fd-c2d8dfac2afc},\n created = {2021-05-10T23:31:46.269Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.269Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2019},\n private_publication = {false},\n abstract = {Nowadays, there exist high interest in the brain-computer interface (BCI) systems, and there are multiple approaches to developing them. Lexico-semantic (LS) classification from Electroencephalographic (EEG) signals is one of them, which is an open and few explored research field. The LS depends on the creation of the concepts of each person and its context. Therefore, it has not been demonstrated a universal fingerprint of the LS either the spatial location in the brain, which depends on the variability the brain plasticity and other changes throughout the time. In this study, an analysis of LS from EEG signals was carried out. The Emotiv Epoc+ was used for the EEG acquisition from three participants reading 36 different words. The subjects were characterized throughout two surveys (Becks depression, and emotion test) for establishing their emotional state, depression, and anxiety levels. The signals were processed to demonstrate semantic category and for decoding individual words (4 pairs of words were selected for this study). The methodology was executed as follows: first, the signals were pre-processed, decomposed by sub-bands (δ, θ, α, β, and γ ) and standardized. Then, feature extraction was applied using linear and non-linear statistical measures, and the Discrete Wavelet Transform calculated from EEG signals, generating the feature space termed set-1. Also, the principal component analysis was applied to reduce the dimensionality, generating the feature space termed set-2. Finally, both sets were tested independently by multiple classifiers based on the support vector machine and k- nearest neighbor. These were validated using 10-fold cross-validation achieving results upper to 95% of accuracy which demonstrated the capability of the proposed mechanism for decoding LS from a reduced number of EEG signals acquired using a portable system of acquisition.},\n bibtype = {inbook},\n author = {Becerra, Miguel Alberto and Londoño-Delgado, Edwin and Botero-Henao, Oscar I. and Marín-Castrillón, Diana and Mejia-Arboleda, Cristian and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.1007/978-3-030-17935-9_30},\n chapter = {Low Resolution Electroencephalographic-Signals-Driven Semantic Retrieval: Preliminary Results},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Nowadays, there exist high interest in the brain-computer interface (BCI) systems, and there are multiple approaches to developing them. Lexico-semantic (LS) classification from Electroencephalographic (EEG) signals is one of them, which is an open and few explored research field. The LS depends on the creation of the concepts of each person and its context. Therefore, it has not been demonstrated a universal fingerprint of the LS either the spatial location in the brain, which depends on the variability the brain plasticity and other changes throughout the time. In this study, an analysis of LS from EEG signals was carried out. The Emotiv Epoc+ was used for the EEG acquisition from three participants reading 36 different words. The subjects were characterized throughout two surveys (Becks depression, and emotion test) for establishing their emotional state, depression, and anxiety levels. The signals were processed to demonstrate semantic category and for decoding individual words (4 pairs of words were selected for this study). The methodology was executed as follows: first, the signals were pre-processed, decomposed by sub-bands (δ, θ, α, β, and γ ) and standardized. Then, feature extraction was applied using linear and non-linear statistical measures, and the Discrete Wavelet Transform calculated from EEG signals, generating the feature space termed set-1. Also, the principal component analysis was applied to reduce the dimensionality, generating the feature space termed set-2. Finally, both sets were tested independently by multiple classifiers based on the support vector machine and k- nearest neighbor. These were validated using 10-fold cross-validation achieving results upper to 95% of accuracy which demonstrated the capability of the proposed mechanism for decoding LS from a reduced number of EEG signals acquired using a portable system of acquisition.\n
\n\n\n\n \n\n \n \n \n \n \n \n Feature Extraction Analysis for Emotion Recognition from ICEEMD of Multimodal Physiological Signals.\n \n \n \n \n\n\n \n Gómez-Lara, J., F.; Ordóñez-Bolaños, O., A.; Becerra, M., A.; Castro-Ospina, A., E.; Mejía-Arboleda, C.; Duque-Mejía, C.; Rodriguez, J.; Revelo-Fuelagán, J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 351-362. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Emotion recognition,Improved complementary ensemble empirical mode dec,Multimodal,Physiological signals,Signal processing},\n pages = {351-362},\n websites = {http://link.springer.com/10.1007/978-3-030-14799-0_30},\n id = {fb6ced10-7df0-3951-a6ad-994ee2a1a465},\n created = {2021-05-10T23:31:46.541Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.541Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Gomez-Lara2019},\n private_publication = {false},\n abstract = {The emotions identification is a very complex task due to depending on multiple variables individually and as a group. They are evaluated by different criteria such as arousal, valence, and dominance mainly. Several investigations have been focused on building prediction systems. Nevertheless, this is still an open research field. The main objective of this paper is the analysis of the Improved Complementary Ensemble Empirical Mode Decomposition (ICEEMD) for feature extraction from physiological signals for emotions prediction. Physiological signals and metadata of the DEAP database were used. First, the signals were preprocessed, then three decompositions were carried out using ICEEMD, Discrete Wavelet Transform (DWT), and Maximal overlap DWT. Feature extraction was carried out using Hermite coefficients, and multiple statistic measures from IMFs, coefficients DWT, and MODWT, and signals. Then, Relief F selection algorithms were applied to reducing the dimensionality of the feature space. Finally, Linear Discriminant Classifier (LDC) and K-NN cascade, and Random Forest classifiers were tested. The different decomposition techniques were compared, and the relevant signals and measures were established. The results demonstrated the capability of ICEEMD decomposition for emotions analysis from physiological signals.},\n bibtype = {inbook},\n author = {Gómez-Lara, J. F. and Ordóñez-Bolaños, O. A. and Becerra, M. A. and Castro-Ospina, A. E. and Mejía-Arboleda, C. and Duque-Mejía, C. and Rodriguez, J. and Revelo-Fuelagán, Javier and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-14799-0_30},\n chapter = {Feature Extraction Analysis for Emotion Recognition from ICEEMD of Multimodal Physiological Signals},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n The emotions identification is a very complex task due to depending on multiple variables individually and as a group. They are evaluated by different criteria such as arousal, valence, and dominance mainly. Several investigations have been focused on building prediction systems. Nevertheless, this is still an open research field. The main objective of this paper is the analysis of the Improved Complementary Ensemble Empirical Mode Decomposition (ICEEMD) for feature extraction from physiological signals for emotions prediction. Physiological signals and metadata of the DEAP database were used. First, the signals were preprocessed, then three decompositions were carried out using ICEEMD, Discrete Wavelet Transform (DWT), and Maximal overlap DWT. Feature extraction was carried out using Hermite coefficients, and multiple statistic measures from IMFs, coefficients DWT, and MODWT, and signals. Then, Relief F selection algorithms were applied to reducing the dimensionality of the feature space. Finally, Linear Discriminant Classifier (LDC) and K-NN cascade, and Random Forest classifiers were tested. The different decomposition techniques were compared, and the relevant signals and measures were established. The results demonstrated the capability of ICEEMD decomposition for emotions analysis from physiological signals.\n
\n\n\n\n \n\n \n \n \n \n \n \n Intelligence in Embedded Systems: Overview and Applications.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Batista, V., F., L.; Rosero, E., A.; Jaramillo, E., D.; Caraguay, J., A.; Pijal-Rojas, J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Advances in Intelligent Systems and Computing, pages 874-883. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Decision making,Embedded systems,Internet of things,Machine learning},\n pages = {874-883},\n websites = {http://link.springer.com/10.1007/978-3-030-02686-8_65},\n id = {f042e54c-cae0-3774-84ee-576df50f4079},\n created = {2021-05-10T23:31:46.548Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.548Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019},\n private_publication = {false},\n abstract = {The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.},\n bibtype = {inbook},\n author = {Rosero-Montalvo, Paul D. and Batista, Vivian F. López and Rosero, Edwin A. and Jaramillo, Edgar D. and Caraguay, Jorge A. and Pijal-Rojas, José and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-02686-8_65},\n chapter = {Intelligence in Embedded Systems: Overview and Applications},\n title = {Advances in Intelligent Systems and Computing}\n}\n\n The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.\n
\n\n\n\n \n\n \n \n \n \n \n \n Intelligent system for identification of wheelchair user's posture using machine learning techniques.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Peluffo-Ordonez, D., H.; Lopez Batista, V., F.; Serrano, J.; and Rosero, E., A.\n\n\n \n\n\n\n IEEE Sensors Journal. 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Intelligent system for identification of wheelchair user's posture using machine learning techniques},\n type = {article},\n year = {2019},\n keywords = {Embedded system,K-nearest neighbors,Kennard-stone,posture detection,principal component analysis},\n websites = {https://ieeexplore.ieee.org/document/8565996},\n id = {60fe12fa-6957-3dc7-b29c-01ecc6364ed2},\n created = {2021-05-10T23:31:46.885Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.885Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2019c},\n private_publication = {false},\n abstract = {This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.},\n bibtype = {article},\n author = {Rosero-Montalvo, Paul D. and Peluffo-Ordonez, Diego Hernn and Lopez Batista, Vivian Felix and Serrano, Jorge and Rosero, Edwin A.},\n doi = {10.1109/JSEN.2018.2885323},\n journal = {IEEE Sensors Journal}\n}\n\n This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: Selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for training is significantly reduced while an admissible classification performance is achieved being a suitable trade given the device conditions.\n
\n\n\n\n \n\n \n \n \n \n \n \n Artificial Neural Networks in the Demand Forecasting of a Metal-Mechanical Industry.\n \n \n \n \n\n\n \n L. Lorente-Leyva, L.; R. Patino-Alarcon, D.; Montero-Santos, Y.; D. Herrera-Granda, I.; H. Peluffo-Ordonez, D.; M. Lastre-Aleaga, A.; and Cordoves-Garcia, A.\n\n\n \n\n\n\n Journal of Engineering and Applied Sciences, 15(1): 81-87. 10 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Artificial Neural Networks in the Demand Forecasting of a Metal-Mechanical Industry},\n type = {article},\n year = {2019},\n pages = {81-87},\n volume = {15},\n websites = {http://www.medwelljournals.com/abstract/?doi=jeasci.2020.81.87},\n month = {10},\n day = {25},\n id = {3effcaaf-d34c-30ec-95c9-6bf005414117},\n created = {2021-05-10T23:31:46.920Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.920Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {L.Lorente-Leyva2019},\n private_publication = {false},\n abstract = {This research presents an application of artificial neural networks in demand forecasting by using MATLAB Software. Keeping in mind that in any planning process forecasts play a fundamental role, being one of the bases for; planning, organizing and controlling production. It gives priority to the most critical nodes and their key activities, so that, the decisions made about them will generate the greatest possible positive impact. The methodology applied demonstrates the quality of the solutions found which are compared with traditional statistical methods to demonstrate the value of the solution proposed. When the results show that the minimum quadratic error is reached with the application of artificial neural networks, a better performance is obtained. Therefore, a suitable horizon is established for the planification and decision making in the metal-mechanical industry for the use of artificial intelligence in the production processes.},\n bibtype = {article},\n author = {L. Lorente-Leyva, Leandro and R. Patino-Alarcon, Delio and Montero-Santos, Yakcleem and D. Herrera-Granda, Israel and H. Peluffo-Ordonez, Diego and M. Lastre-Aleaga, Arlys and Cordoves-Garcia, Alexis},\n doi = {10.36478/jeasci.2020.81.87},\n journal = {Journal of Engineering and Applied Sciences},\n number = {1}\n}\n\n This research presents an application of artificial neural networks in demand forecasting by using MATLAB Software. Keeping in mind that in any planning process forecasts play a fundamental role, being one of the bases for; planning, organizing and controlling production. It gives priority to the most critical nodes and their key activities, so that, the decisions made about them will generate the greatest possible positive impact. The methodology applied demonstrates the quality of the solutions found which are compared with traditional statistical methods to demonstrate the value of the solution proposed. When the results show that the minimum quadratic error is reached with the application of artificial neural networks, a better performance is obtained. Therefore, a suitable horizon is established for the planification and decision making in the metal-mechanical industry for the use of artificial intelligence in the production processes.\n
\n\n\n\n \n\n \n \n \n \n \n \n Method for the Improvement of Knee Angle Accuracy Based on Kinect and IMU: Preliminary Results.\n \n \n \n \n\n\n \n Mayorca-Torres, D.; Caicedo-Eraso, J., C.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 184-199. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Knee flexion,Motion analysis,Multisensor fusion,Orientation estimation},\n pages = {184-199},\n websites = {http://link.springer.com/10.1007/978-3-030-36636-0_14},\n id = {325a743a-ffb4-343a-a027-ba515f60a4e5},\n created = {2021-05-10T23:31:47.027Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.027Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Mayorca-Torres2019},\n private_publication = {false},\n abstract = {One way to identify musculoskeletal disorders in the lower limb is through the functional examination where the ranges of normality of the joints are evaluated. Currently, this test can be performed with technological support, with optical sensors and inertial measurement sensors (IMU) being the most used. Kinect has been widely used for the functional evaluation of the human body, however, there are some limits to the movements made in the depth plane and when there is occlusion of the limbs. Inertial measurement sensors (IMU) allow orientation and acceleration measurements to be obtained with a high sampling rate, with some restrictions associated with drift. This article proposes a methodology that combines the acceleration measures of the IMU and kinect sensors in two planes of movement (Frontal and sagittal). These measurements are filtered in the preprocessing stage according to a Kalman filter and are obtained from a mathematical equation that allows them to be merged. The fusion system data obtains acceptable RMS error values of 5.5 and an average consistency of 92.5% for the sagittal plane with respect to the goniometer technique. The data is shown through an interface that allows the visualization of knee joint kinematic data, as well as tools for the analysis of signals by the health professional.},\n bibtype = {inbook},\n author = {Mayorca-Torres, D. and Caicedo-Eraso, Julio C. and Peluffo-Ordoñez, Diego H.},\n doi = {10.1007/978-3-030-36636-0_14},\n chapter = {Method for the Improvement of Knee Angle Accuracy Based on Kinect and IMU: Preliminary Results},\n title = {Communications in Computer and Information Science}\n}\n\n One way to identify musculoskeletal disorders in the lower limb is through the functional examination where the ranges of normality of the joints are evaluated. Currently, this test can be performed with technological support, with optical sensors and inertial measurement sensors (IMU) being the most used. Kinect has been widely used for the functional evaluation of the human body, however, there are some limits to the movements made in the depth plane and when there is occlusion of the limbs. Inertial measurement sensors (IMU) allow orientation and acceleration measurements to be obtained with a high sampling rate, with some restrictions associated with drift. This article proposes a methodology that combines the acceleration measures of the IMU and kinect sensors in two planes of movement (Frontal and sagittal). These measurements are filtered in the preprocessing stage according to a Kalman filter and are obtained from a mathematical equation that allows them to be merged. The fusion system data obtains acceptable RMS error values of 5.5 and an average consistency of 92.5% for the sagittal plane with respect to the goniometer technique. The data is shown through an interface that allows the visualization of knee joint kinematic data, as well as tools for the analysis of signals by the health professional.\n
\n\n\n\n \n\n \n \n \n \n \n \n Recognition of emotions using ICEEMD-based characterization of multimodal physiological signals.\n \n \n \n \n\n\n \n Ordonez-Bolanos, O., A.; Gomez-Lara, J., F.; Becerra, M., A.; Peluffo-Ordonez, D., H.; Duque-Mejia, C., M.; Medrano-David, D.; and Mejia-Arboleda, C.\n\n\n \n\n\n\n In 2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS), pages 113-116, 2 2019. IEEE\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Recognition of emotions using ICEEMD-based characterization of multimodal physiological signals},\n type = {inproceedings},\n year = {2019},\n pages = {113-116},\n websites = {https://ieeexplore.ieee.org/document/8667585/},\n month = {2},\n publisher = {IEEE},\n id = {671d8d21-e0ac-3638-a873-a1582d8ca547},\n created = {2021-05-10T23:31:47.179Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.179Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Ordonez-Bolanos2019},\n private_publication = {false},\n abstract = {Physiological-signal-Analysis-based approaches are typically used for automatic emotion identification. Given the complex nature of signals-related emotions, their right identification often results in a non-Trivial and exhaustive process-especially because such signals suffer from high dependence upon multiple external variables. Some emotional criteria of interest are arousal, valence, and dominance. Several research works have addressed this issue, mainly through creating prediction systems, notwithstanding, due to aspects such as accuracy, in-context interpretation and computational cost, it is still considered a great-of-interest, open research eld. This paper is aimed at verifying the usefulness of the so-called improved complete empirical mode decomposition (ICEEMD) as a physiological-signal-characterization building block within an emotion-predicting system. To this purpose, some physiological signals along with patients' metadata from the DEAP database are considered. The experiments are set-up as follows: Signals are pre-processed by amplitude adjusting and simple filtering. Then, a feature set is built using HC, and multiple statistic measures from information given by the three considered decompositions, namely: ICEEMD, discrete wavelet transform (DWT),and Maximal overlap DWT. Subsequently, Relief F selection algorithm was applied for reducing the dimensionality of the feature space. Finally, classifiers (LDC and K-NN cascade architectures) are used to assess the class-separability given by the feature set. The different decomposition techniques were compared, and the relevant signals and measures were established. Experimental results evidence the suitability of ICEEMD decomposition for physiological-signal-driven emotions analysis.},\n bibtype = {inproceedings},\n author = {Ordonez-Bolanos, O. A. and Gomez-Lara, J. F. and Becerra, M. A. and Peluffo-Ordonez, D. H. and Duque-Mejia, C. M. and Medrano-David, D. and Mejia-Arboleda, C.},\n doi = {10.1109/LASCAS.2019.8667585},\n booktitle = {2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS)}\n}\n\n Physiological-signal-Analysis-based approaches are typically used for automatic emotion identification. Given the complex nature of signals-related emotions, their right identification often results in a non-Trivial and exhaustive process-especially because such signals suffer from high dependence upon multiple external variables. Some emotional criteria of interest are arousal, valence, and dominance. Several research works have addressed this issue, mainly through creating prediction systems, notwithstanding, due to aspects such as accuracy, in-context interpretation and computational cost, it is still considered a great-of-interest, open research eld. This paper is aimed at verifying the usefulness of the so-called improved complete empirical mode decomposition (ICEEMD) as a physiological-signal-characterization building block within an emotion-predicting system. To this purpose, some physiological signals along with patients' metadata from the DEAP database are considered. The experiments are set-up as follows: Signals are pre-processed by amplitude adjusting and simple filtering. Then, a feature set is built using HC, and multiple statistic measures from information given by the three considered decompositions, namely: ICEEMD, discrete wavelet transform (DWT),and Maximal overlap DWT. Subsequently, Relief F selection algorithm was applied for reducing the dimensionality of the feature space. Finally, classifiers (LDC and K-NN cascade architectures) are used to assess the class-separability given by the feature set. The different decomposition techniques were compared, and the relevant signals and measures were established. Experimental results evidence the suitability of ICEEMD decomposition for physiological-signal-driven emotions analysis.\n
\n\n\n\n \n\n \n \n \n \n \n \n Multi-target tracking for sperm motility measurement using the kalman filter and JPDAF: Preliminary results.\n \n \n \n \n\n\n \n Mayorca-Torres, D.; Guerrero-Chapal, H.; Mejía-Manzano, J.; Lopez-Mesa, D.; Peluffo-Ordoñez, D., H.; and Salazar-Castro, J., A.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
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\n\n\n@article{\n title = {Multi-target tracking for sperm motility measurement using the kalman filter and JPDAF: Preliminary results},\n type = {article},\n year = {2019},\n keywords = {JPDAF,Kalman filter,Morphology,Motility,Spermatozoa},\n websites = {https://search.proquest.com/openview/69fcef4b61d6ec863099124a9c2fe66f},\n id = {fc1e5eda-e10d-31be-a861-4d35a0e9fcab},\n created = {2021-05-10T23:31:47.246Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.246Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Mayorca-Torres2019a},\n private_publication = {false},\n abstract = {The determination of sperm motility characteristics is of great importance for the specification of fertility in men. The semengram is the main diagnostic test to confirm semen quality. Currently, many fertility laboratories use visual assistance techniques to evaluate by using the Makler counting chamber, where motility and sperm count analysis can be performed. This research project proposes a method that allows the quantification of motility through the use of the probabilistic filter (JPDAF) based on the Kalman filter. This research requires the stages of segmentation, feature extraction and development of tracking algorithms for the association of sperm trajectories when there are multiple objectives. A total of 200 individual sperm were selected and the effectiveness for sperm classification was determined according to the mobility categories established by the WHO, obtaining an average value of 93.5% for the categories (A, B, C and D).},\n bibtype = {article},\n author = {Mayorca-Torres, Dagoberto and Guerrero-Chapal, H. and Mejía-Manzano, Julio and Lopez-Mesa, Diana and Peluffo-Ordoñez, Diego H. and Salazar-Castro, José A.},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n The determination of sperm motility characteristics is of great importance for the specification of fertility in men. The semengram is the main diagnostic test to confirm semen quality. Currently, many fertility laboratories use visual assistance techniques to evaluate by using the Makler counting chamber, where motility and sperm count analysis can be performed. This research project proposes a method that allows the quantification of motility through the use of the probabilistic filter (JPDAF) based on the Kalman filter. This research requires the stages of segmentation, feature extraction and development of tracking algorithms for the association of sperm trajectories when there are multiple objectives. A total of 200 individual sperm were selected and the effectiveness for sperm classification was determined according to the mobility categories established by the WHO, obtaining an average value of 93.5% for the categories (A, B, C and D).\n
\n\n\n\n \n\n \n \n \n \n \n \n Kernel-Spectral-Clustering-Driven Motion Segmentation: Rotating-Objects First Trials.\n \n \n \n \n\n\n \n Oña-Rocha, O.; Riascos-Salas, J., A.; Marrufo-Rodríguez, I., C.; Páez-Jaime, M., A.; Mayorca-Torres, D.; Ponce-Guevara, K., L.; Salazar-Castro, J., A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 30-40. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Kernels,Motion tracking,Spectral clustering},\n pages = {30-40},\n websites = {http://link.springer.com/10.1007/978-3-030-36636-0_3},\n id = {1ea33f46-62bb-3ebe-a0de-361c51b667d9},\n created = {2021-05-10T23:31:47.415Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.415Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Ona-Rocha2019},\n private_publication = {false},\n abstract = {Time-varying data characterization and classification is a field of great interest in both scientific and technology communities. There exists a wide range of applications and challenging open issues such as: automatic motion segmentation, moving-object tracking, and movement forecasting, among others. In this paper, we study the use of the so-called kernel spectral clustering (KSC) approach to capture the dynamic behavior of frames - representing rotating objects - by means of kernel functions and feature relevance values. On the basis of previous research works, we formally derive a here-called tracking vector able to unveil sequential behavior patterns. As a remarkable outcome, we alternatively introduce an encoded version of the tracking vector by converting into decimal numbers the resulting clustering indicators. To evaluate our approach, we test the studied KSC-based tracking over a rotating object from the COIL 20 database. Preliminary results produce clear evidence about the relationship between the clustering indicators and the starting/ending time instance of a specific dynamic sequence.},\n bibtype = {inbook},\n author = {Oña-Rocha, O. and Riascos-Salas, J. A. and Marrufo-Rodríguez, I. C. and Páez-Jaime, M. A. and Mayorca-Torres, D. and Ponce-Guevara, K. L. and Salazar-Castro, J. A. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-36636-0_3},\n chapter = {Kernel-Spectral-Clustering-Driven Motion Segmentation: Rotating-Objects First Trials},\n title = {Communications in Computer and Information Science}\n}\n\n Time-varying data characterization and classification is a field of great interest in both scientific and technology communities. There exists a wide range of applications and challenging open issues such as: automatic motion segmentation, moving-object tracking, and movement forecasting, among others. In this paper, we study the use of the so-called kernel spectral clustering (KSC) approach to capture the dynamic behavior of frames - representing rotating objects - by means of kernel functions and feature relevance values. On the basis of previous research works, we formally derive a here-called tracking vector able to unveil sequential behavior patterns. As a remarkable outcome, we alternatively introduce an encoded version of the tracking vector by converting into decimal numbers the resulting clustering indicators. To evaluate our approach, we test the studied KSC-based tracking over a rotating object from the COIL 20 database. Preliminary results produce clear evidence about the relationship between the clustering indicators and the starting/ending time instance of a specific dynamic sequence.\n
\n\n\n\n \n\n \n \n \n \n \n \n Cardiac Murmur Effects on Automatic Segmentation of ECG Signals for Biometric Identification: Preliminary Study.\n \n \n \n \n\n\n \n Duque-Mejía, C.; Becerra, M., A.; Zapata-Hernández, C.; Mejia-Arboleda, C.; Castro-Ospina, A., E.; Delgado-Trejos, E.; Peluffo-Ordóñez, D., H.; Rosero-Montalvo, P.; and Revelo-Fuelagán, J.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 269-279, 2019. \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Cardiac Murmur Effects on Automatic Segmentation of ECG Signals for Biometric Identification: Preliminary Study},\n type = {inproceedings},\n year = {2019},\n keywords = {Automatic segmentation,Biometric,Electrocardiographic signal,Heart murmur,Pattern recognition},\n pages = {269-279},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-14799-0_23,http://link.springer.com/10.1007/978-3-030-14799-0_23},\n id = {a26a9397-6d18-3873-bf4a-aaec00abc746},\n created = {2021-05-10T23:31:47.457Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.457Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Duque-Mejia2019},\n private_publication = {false},\n abstract = {Biometric identification or authentication is a pattern recognition process, which is carried out acquiring different measures of human beings to distinguish them. Fingerprint and eye iris are the most known and used biometric techniques; nevertheless, also they are the most vulnerable to counterfeiting. Consequently, nowadays research has been focused on physiological signals and behavioral traits for biometric identification because these allow not only the authentication but also determine that the subject is alive. Electrocardiographic signals (ECG-S) have been studied for biometric identification demonstrating their capability. Taking into account that some pathologies are detected using ECG-S, these can affect the results of biometric identification; nonetheless, some diseases such as cardiac murmurs are not detected by ECG-S, but they can distort their morphology. Therefore, these signals must be analyzed considering different pathologies. In this paper, a biometric study was carried out from 40 subjects (20 with cardiac murmurs and 20 without cardiac affections). First, the ECG-S were preprocessed and segmented using the fast method for detecting T waves with annotation of P and T waves, then feature extraction was carried out using discrete wavelet transform (DWT), maximal overlap DWT, cepstral coefficients, and statistical measures. Then, rough set and relief F algorithms were applied to datasets (pathological and normal signals) for attribute reduction. Finally, multiple classifiers and combinations of them were tested. The results of the segmentation were analyzed achieving low results for signals affected by cardiac murmurs. On the other hand, according to the cardiac murmur effects analyzed, the performance of the classifiers in cascade shown the best accuracy for human identification from ECG-S, minimizing the impact of variability generated on ECG-S by cardiac murmurs diseases.},\n bibtype = {inproceedings},\n author = {Duque-Mejía, C. and Becerra, M. A. and Zapata-Hernández, C. and Mejia-Arboleda, C. and Castro-Ospina, A. E. and Delgado-Trejos, E. and Peluffo-Ordóñez, Diego H. and Rosero-Montalvo, P. and Revelo-Fuelagán, Javier},\n doi = {10.1007/978-3-030-14799-0_23},\n booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Biometric identification or authentication is a pattern recognition process, which is carried out acquiring different measures of human beings to distinguish them. Fingerprint and eye iris are the most known and used biometric techniques; nevertheless, also they are the most vulnerable to counterfeiting. Consequently, nowadays research has been focused on physiological signals and behavioral traits for biometric identification because these allow not only the authentication but also determine that the subject is alive. Electrocardiographic signals (ECG-S) have been studied for biometric identification demonstrating their capability. Taking into account that some pathologies are detected using ECG-S, these can affect the results of biometric identification; nonetheless, some diseases such as cardiac murmurs are not detected by ECG-S, but they can distort their morphology. Therefore, these signals must be analyzed considering different pathologies. In this paper, a biometric study was carried out from 40 subjects (20 with cardiac murmurs and 20 without cardiac affections). First, the ECG-S were preprocessed and segmented using the fast method for detecting T waves with annotation of P and T waves, then feature extraction was carried out using discrete wavelet transform (DWT), maximal overlap DWT, cepstral coefficients, and statistical measures. Then, rough set and relief F algorithms were applied to datasets (pathological and normal signals) for attribute reduction. Finally, multiple classifiers and combinations of them were tested. The results of the segmentation were analyzed achieving low results for signals affected by cardiac murmurs. On the other hand, according to the cardiac murmur effects analyzed, the performance of the classifiers in cascade shown the best accuracy for human identification from ECG-S, minimizing the impact of variability generated on ECG-S by cardiac murmurs diseases.\n
\n\n\n\n \n\n \n \n \n \n \n \n Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors.\n \n \n \n \n\n\n \n Bastidas Torres, D.; Piñeros Rodriguez, C.; Peluffo-Ordóñez, D., H.; Blanco Valencia, X.; Revelo-Fuelagán, J.; Becerra, M., A.; Castro-Ospina, A., E.; and Lorente-Leyva, L., L.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 339-350. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Bayes,Case-based reasoning,Classification,Parametric,Probability},\n pages = {339-350},\n websites = {http://link.springer.com/10.1007/978-3-030-14799-0_29},\n id = {bbb1a0bb-3ef4-3aca-a34a-e1da045b92c5},\n created = {2021-05-10T23:31:47.498Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.498Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {BastidasTorres2019},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-030-14799-0_29},\n chapter = {Adaptation and Recovery Stages for Case-Based Reasoning Systems Using Bayesian Estimation and Density Estimation with Nearest Neighbors},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Classification system for corporate reputation based on financial variables.\n \n \n \n \n\n\n \n Londoño-Montoya, E.; Becerra, M., A.; Murillo-Escobar, J.; Gómez-Bayona, L.; Moreno-López, G.; and Peluffo-Ordoñez, D.\n\n\n \n\n\n\n RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Classification system for corporate reputation based on financial variables},\n type = {article},\n year = {2019},\n keywords = {Adaptive diffuse inference system,Corporate reputation,Optimization by particle swarm,Reputational index,Vector support machines},\n websites = {https://search.proquest.com/openview/fc081b269b3464d65f6211b07c6ca1e5/},\n id = {86483c27-5de7-3500-92e5-9b48ca520ca1},\n created = {2021-05-10T23:31:47.643Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.643Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Londono-Montoya2019},\n private_publication = {false},\n abstract = {The most important external assessment for companies is reputation, which is very difficult to calculate since its characterization may require a large number of qualitative and quantitative data. This study presents a comparison of different corporate reputation classification systems based on financial variables. Initially, a database was constructed using data from the Corporate Reputation Business Monitor and the Business Information and Reporting System of the Colombian Superintendence of Companies. The records were labeled as high and low. Then, a relevance analysis was carried out, using linear discriminant analysis. Four classifiers (ANFIS, K-NN, F-NN, and SVM-PSO) were compared to categorize the reputation, achieving a performance of 94% accuracy, which allowed to demonstrate the discriminant capacity of the financial variables to classify the reputation.},\n bibtype = {article},\n author = {Londoño-Montoya, Erika and Becerra, Miguel A. and Murillo-Escobar, Juan and Gómez-Bayona, Ledy and Moreno-López, Gustavo and Peluffo-Ordoñez, Diego},\n journal = {RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao}\n}\n\n The most important external assessment for companies is reputation, which is very difficult to calculate since its characterization may require a large number of qualitative and quantitative data. This study presents a comparison of different corporate reputation classification systems based on financial variables. Initially, a database was constructed using data from the Corporate Reputation Business Monitor and the Business Information and Reporting System of the Colombian Superintendence of Companies. The records were labeled as high and low. Then, a relevance analysis was carried out, using linear discriminant analysis. Four classifiers (ANFIS, K-NN, F-NN, and SVM-PSO) were compared to categorize the reputation, achieving a performance of 94% accuracy, which allowed to demonstrate the discriminant capacity of the financial variables to classify the reputation.\n
\n\n\n\n \n\n \n \n \n \n \n \n Drowsiness Detection in Drivers Through Real-Time Image Processing of the Human Eye.\n \n \n \n \n\n\n \n Herrera-Granda, E., P.; Caraguay-Procel, J., A.; Granda-Gudiño, P., D.; Herrera-Granda, I., D.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; and Revelo-Fuelagán, J.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019. \n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Drowsiness Detection in Drivers Through Real-Time Image Processing of the Human Eye},\n type = {inproceedings},\n year = {2019},\n keywords = {Alarm,Artificial intelligence,Drowsiness detection,Human eye,Image processing},\n websites = {https://link.springer.com/chapter/10.1007/978-3-030-14799-0_54},\n id = {f7dc79e5-ff6b-3e40-9bd9-c900c367aba9},\n created = {2021-05-10T23:31:47.664Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.664Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Herrera-Granda2019},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inproceedings},\n 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},\n doi = {10.1007/978-3-030-14799-0_54},\n booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Artificial Neural Networks for Bottled Water Demand Forecasting: A Small Business Case Study.\n \n \n \n \n\n\n \n Herrera-Granda, I., D.; Chicaiza-Ipiales, J., A.; Herrera-Granda, E., P.; Lorente-Leyva, L., L.; Caraguay-Procel, J., A.; García-Santillán, I., D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 362-373. 2019.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Artificial neural networks,Long-term demand forecasting,Small business},\n pages = {362-373},\n websites = {http://link.springer.com/10.1007/978-3-030-20518-8_31},\n id = {5023e781-e264-3613-a71c-ed7fc4badc3e},\n created = {2021-05-10T23:31:47.921Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.921Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Herrera-Granda2019a},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-030-20518-8_31},\n chapter = {Artificial Neural Networks for Bottled Water Demand Forecasting: A Small Business Case Study},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Murillo-Valle, J., R.; Montero-Santos, Y.; Herrera-Granda, I., D.; Herrera-Granda, E., P.; Rosero-Montalvo, P., D.; Peluffo-Ordóñez, D., H.; and Blanco-Valencia, X., P.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 674-685. 2019.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2019},\n keywords = {Forecasting,Genetic algorithm,Master Production Scheduling,Optimization,Production planning,Textile industry},\n pages = {674-685},\n websites = {http://link.springer.com/10.1007/978-3-030-29859-3_57},\n id = {470f3bf4-97a2-31d5-9431-917e81c3b05f},\n created = {2021-05-10T23:31:47.946Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.946Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lorente-Leyva2019},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-030-29859-3_57},\n chapter = {Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Non-generalized Analysis of the Multimodal Signals for Emotion Recognition: Preliminary Results.\n \n \n \n \n\n\n \n Londoño-Delgado, E.; Becerra, M., A.; Duque-Mejía, C., M.; Zapata, J., C.; Mejía-Arboleda, C.; Castro-Ospina, A., E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11466 LNBI, pages 363-373, 2019. Springer Verlag\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Non-generalized Analysis of the Multimodal Signals for Emotion Recognition: Preliminary Results},\n type = {inproceedings},\n year = {2019},\n keywords = {Emotion recognition,Physiological signals,Signal processing},\n pages = {363-373},\n volume = {11466 LNBI},\n websites = {https://link.springer.com/chapter/10.1007%2F978-3-030-17935-9_33},\n publisher = {Springer Verlag},\n id = {a5b4427b-9c92-364f-9cea-d3abac5fb2cb},\n created = {2021-11-10T17:31:52.935Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-11-10T17:31:52.935Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Emotions are mental states associated with some stimuli, and they have a relevant impact on the people living and are correlated with their physical and mental health. Different studies have been carried out focused on emotion identification considering that there is a universal fingerprint of the emotions. However, this is an open field yet, and some authors had refused such proposal which is contrasted with many results which can be considered as no conclusive despite some of them have achieved high results of performances for identifying some emotions. In this work an analysis of identification of emotions per individual based on physiological signals using the known MAHNOB-HCI-TAGGING database is carried out, considering that there is not a universal fingerprint based on the results achieved by a previous meta-analytic investigation of emotion categories. The methodology applied is depicted as follows: first the signals were filtered and normalized and decomposed in five bands (δ, θ, α, β, γ ), then a features extraction stage was carried out using multiple statistical measures calculated of results achieved after applied discrete wavelet transform, Cepstral coefficients, among others. A feature space dimensional reduction was applied using the selection algorithm relief F. Finally, the classification was carried out using support vector machine, and k-nearest neighbors and its performance analysis was measured using 10 folds cross-validation achieving high performance uppon to 99%.},\n bibtype = {inproceedings},\n author = {Londoño-Delgado, Edwin and Becerra, Miguel Alberto and Duque-Mejía, Carolina M. and Zapata, Juan Camilo and Mejía-Arboleda, Cristian and Castro-Ospina, Andrés Eduardo and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.1007/978-3-030-17935-9_33},\n booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Emotions are mental states associated with some stimuli, and they have a relevant impact on the people living and are correlated with their physical and mental health. Different studies have been carried out focused on emotion identification considering that there is a universal fingerprint of the emotions. However, this is an open field yet, and some authors had refused such proposal which is contrasted with many results which can be considered as no conclusive despite some of them have achieved high results of performances for identifying some emotions. In this work an analysis of identification of emotions per individual based on physiological signals using the known MAHNOB-HCI-TAGGING database is carried out, considering that there is not a universal fingerprint based on the results achieved by a previous meta-analytic investigation of emotion categories. The methodology applied is depicted as follows: first the signals were filtered and normalized and decomposed in five bands (δ, θ, α, β, γ ), then a features extraction stage was carried out using multiple statistical measures calculated of results achieved after applied discrete wavelet transform, Cepstral coefficients, among others. A feature space dimensional reduction was applied using the selection algorithm relief F. Finally, the classification was carried out using support vector machine, and k-nearest neighbors and its performance analysis was measured using 10 folds cross-validation achieving high performance uppon to 99%.\n
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\n \n \n\n \n \n \n \n \n \n Movement Identification in EMG Signals Using Machine Learning: A Comparative Study.\n \n \n \n \n\n\n \n Lasso-Arciniegas, L.; Viveros-Melo, A.; Salazar-Castro, J., A.; Becerra, M., A.; Castro-Ospina, A., E.; Revelo-Fuelagán, E., J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 368-375. 2018.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {ANN,EMG signals,Feature extraction,KNN,Parzen},\n pages = {368-375},\n websites = {http://link.springer.com/10.1007/978-3-030-01132-1_42},\n id = {a9425c81-e43a-3c0e-8058-cc4d8bac53fc},\n created = {2021-05-10T23:31:45.103Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.103Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lasso-Arciniegas2018},\n private_publication = {false},\n abstract = {The analysis of electromyographic (EMG) signals enables the development of important technologies for industry and medical environments, due mainly to the design of EMG-based human-computer interfaces. There exists a wide range of applications encompassing: Wireless-computer controlling, rehabilitation, wheelchair guiding, and among others. The semantic interpretation of EMG analysis is typically conducted by machine learning algorithms, and mainly involves stages for signal characterization and classification. This work presents a methodology for comparing a set of state-of-the-art approaches of EMG signal characterization and classification within a movement identification framework. We compare the performance of three classifiers (KNN, Parzen-density-based classifier and ANN) using spectral (Wavelets) and time-domain-based (statistical and morphological descriptors) features. Also, a methodology for movement selection is proposed. Results are comparable with those reported in literature, reaching classification performance of (90.89 ± 1.12)% (KNN), (93.92 ± 0.34)% (ANN) and 91.09 ± 0.93 (Parzen-density-based classifier) with 12 movements.},\n bibtype = {inbook},\n author = {Lasso-Arciniegas, Laura and Viveros-Melo, Andres and Salazar-Castro, José A. and Becerra, Miguel A. and Castro-Ospina, Andrés Eduardo and Revelo-Fuelagán, E. Javier and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-01132-1_42},\n chapter = {Movement Identification in EMG Signals Using Machine Learning: A Comparative Study},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n The analysis of electromyographic (EMG) signals enables the development of important technologies for industry and medical environments, due mainly to the design of EMG-based human-computer interfaces. There exists a wide range of applications encompassing: Wireless-computer controlling, rehabilitation, wheelchair guiding, and among others. The semantic interpretation of EMG analysis is typically conducted by machine learning algorithms, and mainly involves stages for signal characterization and classification. This work presents a methodology for comparing a set of state-of-the-art approaches of EMG signal characterization and classification within a movement identification framework. We compare the performance of three classifiers (KNN, Parzen-density-based classifier and ANN) using spectral (Wavelets) and time-domain-based (statistical and morphological descriptors) features. Also, a methodology for movement selection is proposed. Results are comparable with those reported in literature, reaching classification performance of (90.89 ± 1.12)% (KNN), (93.92 ± 0.34)% (ANN) and 91.09 ± 0.93 (Parzen-density-based classifier) with 12 movements.\n
\n\n\n\n \n\n \n \n \n \n \n \n Mejoramiento de las Capacidades Tecnológicas en los Sectores Rurales de la Provincia de Imbabura.\n \n \n \n \n\n\n \n Armas, S., F.; Montalvo, P., R.; Olalla, E., M.; and Ordoñez, D., P.\n\n\n \n\n\n\n Ciencia. 2018.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Mejoramiento de las Capacidades Tecnológicas en los Sectores Rurales de la Provincia de Imbabura},\n type = {article},\n year = {2018},\n websites = {https://ia601608.us.archive.org/0/items/Articulo11_201705/Artículo 11.pdf},\n id = {65376318-f550-3280-a420-b276c473d53b},\n created = {2021-05-10T23:31:45.255Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.255Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Armas2018},\n private_publication = {false},\n abstract = {La Universidad Técnica del Norte a través de la carrera de ingeniería en Electrónica y Redes de Comunicación, fortaleciendo al proceso de vinculación con la sociedad, crea un proyecto que beneficia a la población de las zonas rurales de la provincia de Imbabura, y que, particularmente, tiene el objetivo de disminuir la brecha digital en colegios, brindado acceso a las tecnologías de información y comunicación. Para poner en acción el proyecto de mejoramiento de las capacidades tecnológicas, se consideró como población de interés a los individuos mayores de 12 años, hombres y mujeres, de diferentes niveles sociales, culturales y étnicos. Metodológicamente, se plantea una planificación de programas de capacitación en base a un diagnóstico de las necesidades, que posteriormente fueron evaluados con el propósito de reducir las deficiencias tecnológicas de las personas y así mejorar la calidad de vida con miras a reducir el analfabetismo digital. Dentro de la ejecución del proyecto, se toma como estrategia los Infocentros Comunitarios y propios laboratorios de computación de las instituciones educativas, los mismos que son punto de referencia para llegar a las comunidades, logrando capacitar en herramientas de ofimática básica, asistencias de redes de comunicación, Internet, mantenimiento de computadoras, y administración de páginas web. Posteriormente a la capacitación, claramente se pudo observar que, en los sectores de acción, satisficieron sus expectativas, adquirieron habilidades y destrezas de temas tecnológicos. En este artículo se presenta los aspectos metodológicos y resultados más importantes del proyecto.},\n bibtype = {article},\n author = {Armas, Stefany Flores and Montalvo, Paul Rosero and Olalla, Edgar Maya and Ordoñez, Diego Peluffo},\n journal = {Ciencia}\n}\n\n La Universidad Técnica del Norte a través de la carrera de ingeniería en Electrónica y Redes de Comunicación, fortaleciendo al proceso de vinculación con la sociedad, crea un proyecto que beneficia a la población de las zonas rurales de la provincia de Imbabura, y que, particularmente, tiene el objetivo de disminuir la brecha digital en colegios, brindado acceso a las tecnologías de información y comunicación. Para poner en acción el proyecto de mejoramiento de las capacidades tecnológicas, se consideró como población de interés a los individuos mayores de 12 años, hombres y mujeres, de diferentes niveles sociales, culturales y étnicos. Metodológicamente, se plantea una planificación de programas de capacitación en base a un diagnóstico de las necesidades, que posteriormente fueron evaluados con el propósito de reducir las deficiencias tecnológicas de las personas y así mejorar la calidad de vida con miras a reducir el analfabetismo digital. Dentro de la ejecución del proyecto, se toma como estrategia los Infocentros Comunitarios y propios laboratorios de computación de las instituciones educativas, los mismos que son punto de referencia para llegar a las comunidades, logrando capacitar en herramientas de ofimática básica, asistencias de redes de comunicación, Internet, mantenimiento de computadoras, y administración de páginas web. Posteriormente a la capacitación, claramente se pudo observar que, en los sectores de acción, satisficieron sus expectativas, adquirieron habilidades y destrezas de temas tecnológicos. En este artículo se presenta los aspectos metodológicos y resultados más importantes del proyecto.\n
\n\n\n\n \n\n \n \n \n \n \n \n Building a Nasa Yuwe Language Corpus and Tagging with a Metaheuristic Approach.\n \n \n \n \n\n\n \n Sierra Martínez, L., M.; Cobos, C., A.; Corrales Muñoz, J., C.; Rojas Curieux, T.; Herrera-Viedma, E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Computación y Sistemas, 22(3). 9 2018.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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\n\n\n@article{\n title = {Building a Nasa Yuwe Language Corpus and Tagging with a Metaheuristic Approach},\n type = {article},\n year = {2018},\n keywords = {Global-best harmony search,Harmony search,Hill climbing,Nasa Yuwe language,Part of speech tagger,Tabu memory,Tagged corpus},\n volume = {22},\n websites = {http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3018},\n month = {9},\n day = {30},\n id = {9b5e991a-5c41-36be-9c7b-7e968adab18c},\n created = {2021-05-10T23:31:45.629Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.629Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {SierraMartinez2018},\n private_publication = {false},\n abstract = {Nasa Yuwe is the language of the Nasa indigenous community in Colombia. It is currently threatened with extinction. In this regard, a range of computer science solutions have been developed to the teaching and revitalization of the language. One of the most suitable approaches is the construction of a Part- Of-Speech Tagging (POST), which encourages the analysis and advanced processing of the language. Nevertheless, for Nasa Yuwe no tagged corpus exists, neither is there a POS Tagger and no related works have been reported. This paper therefore concentrates on building a linguistic corpus tagged for the Nasa Yuwe language and generating the first tagging application for Nasa Yuwe. The main results and findings are 1) the process of building the Nasa Yuwe corpus, 2) the tagsets and tagged sentences, as well as the statistics associated with the corpus, 3) results of two experiments to evaluate several POS Taggers (a Random tagger, three versions of HSTAGger, a tagger based on the harmony search metaheuristic, and three versions of a memetic algorithm GBHS Tagger, based on Global-Best Harmony Search (GBHS), Hill Climbing and an explicit Tabu memory, which obtained the best results in contrast with the other methods considered over the Nasa Yuwe language corpus.},\n bibtype = {article},\n author = {Sierra Martínez, Luz Marina and Cobos, Carlos Alberto and Corrales Muñoz, Juan Carlos and Rojas Curieux, Tulio and Herrera-Viedma, Enrique and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.13053/cys-22-3-3018},\n journal = {Computación y Sistemas},\n number = {3}\n}\n\n Nasa Yuwe is the language of the Nasa indigenous community in Colombia. It is currently threatened with extinction. In this regard, a range of computer science solutions have been developed to the teaching and revitalization of the language. One of the most suitable approaches is the construction of a Part- Of-Speech Tagging (POST), which encourages the analysis and advanced processing of the language. Nevertheless, for Nasa Yuwe no tagged corpus exists, neither is there a POS Tagger and no related works have been reported. This paper therefore concentrates on building a linguistic corpus tagged for the Nasa Yuwe language and generating the first tagging application for Nasa Yuwe. The main results and findings are 1) the process of building the Nasa Yuwe corpus, 2) the tagsets and tagged sentences, as well as the statistics associated with the corpus, 3) results of two experiments to evaluate several POS Taggers (a Random tagger, three versions of HSTAGger, a tagger based on the harmony search metaheuristic, and three versions of a memetic algorithm GBHS Tagger, based on Global-Best Harmony Search (GBHS), Hill Climbing and an explicit Tabu memory, which obtained the best results in contrast with the other methods considered over the Nasa Yuwe language corpus.\n
\n\n\n\n \n\n \n \n \n \n \n \n Cardiac Pulse Modeling Using a Modified van der Pol Oscillator and Genetic Algorithms.\n \n \n \n \n\n\n \n Lopez-Chamorro, F., M.; Arciniegas-Mejia, A., F.; Imbajoa-Ruiz, D., E.; Rosero-Montalvo, P., D.; García, P.; Castro-Ospina, A., E.; Acosta, A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 96-106. 2018.\n \n\n\n\n
\n\n\n\n \n \nWebsite\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n pages = {96-106},\n websites = {http://link.springer.com/10.1007/978-3-319-78723-7_8},\n id = {7845a0e7-96c6-3c02-849b-ef31efb1cd17},\n created = {2021-05-10T23:31:45.632Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.632Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lopez-Chamorro2018},\n private_publication = {false},\n abstract = {This paper proposes an approach for modeling cardiac pulses from electrocardiographic signals (ECG). A modified van der Pol oscillator model (mvP) is analyzed, which, under a proper configuration, is capable of describing action potentials, and, therefore, it can be adapted for modeling a normal cardiac pulse. Adequate parameters of the mvP system response are estimated using non-linear dynamics methods, like dynamic time warping (DTW). In order to represent an adaptive response for each individual heartbeat, a parameter tuning optimization method is applied which is based on a genetic algorithm that generates responses that morphologically resemble real ECG. This feature is particularly relevant since heartbeats have intrinsically strong variability in terms of both shape and length. Experiments are performed over real ECG from MIT-BIH arrhythmias database. The application of the optimization process shows that the mvP oscillator can be used properly to model the ideal cardiac rate pulse.},\n bibtype = {inbook},\n author = {Lopez-Chamorro, Fabián M. and Arciniegas-Mejia, Andrés F. and Imbajoa-Ruiz, David Esteban and Rosero-Montalvo, Paul D. and García, Pedro and Castro-Ospina, Andrés Eduardo and Acosta, Antonio and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.1007/978-3-319-78723-7_8},\n chapter = {Cardiac Pulse Modeling Using a Modified van der Pol Oscillator and Genetic Algorithms},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n This paper proposes an approach for modeling cardiac pulses from electrocardiographic signals (ECG). A modified van der Pol oscillator model (mvP) is analyzed, which, under a proper configuration, is capable of describing action potentials, and, therefore, it can be adapted for modeling a normal cardiac pulse. Adequate parameters of the mvP system response are estimated using non-linear dynamics methods, like dynamic time warping (DTW). In order to represent an adaptive response for each individual heartbeat, a parameter tuning optimization method is applied which is based on a genetic algorithm that generates responses that morphologically resemble real ECG. This feature is particularly relevant since heartbeats have intrinsically strong variability in terms of both shape and length. Experiments are performed over real ECG from MIT-BIH arrhythmias database. The application of the optimization process shows that the mvP oscillator can be used properly to model the ideal cardiac rate pulse.\n
\n\n\n\n \n\n \n \n \n \n \n \n Air Quality Monitoring Intelligent System Using Machine Learning Techniques.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Caraguay-Procel, J., A.; Jaramillo, E., D.; Michilena-Calderon, J., M.; Umaquinga-Criollo, A., C.; Mediavilla-Valverde, M.; Ruiz, M., A.; Beltran, L., A.; and Peluffo, D., H.\n\n\n \n\n\n\n In 2018 International Conference on Information Systems and Computer Science (INCISCOS), pages 75-80, 11 2018. IEEE\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Air Quality Monitoring Intelligent System Using Machine Learning Techniques},\n type = {inproceedings},\n year = {2018},\n keywords = {Air quality,Intelligent system,Monitoring system},\n pages = {75-80},\n websites = {https://ieeexplore.ieee.org/document/8564511/},\n month = {11},\n publisher = {IEEE},\n id = {7c87f54b-ce25-312f-b6ff-037e9977a8df},\n created = {2021-05-10T23:31:45.695Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.695Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018},\n private_publication = {false},\n abstract = {Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Caraguay-Procel, Jorge A. and Jaramillo, Edgar D. and Michilena-Calderon, Jaime M. and Umaquinga-Criollo, Ana C. and Mediavilla-Valverde, Mario and Ruiz, Miguel A. and Beltran, Luis A. and Peluffo, Diego H.},\n doi = {10.1109/INCISCOS.2018.00019},\n booktitle = {2018 International Conference on Information Systems and Computer Science (INCISCOS)}\n}\n\n Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.\n
\n\n\n\n \n\n \n \n \n \n \n \n Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages.\n \n \n \n \n\n\n \n Blanco Valencia, X.; Bastidas Torres, D.; Piñeros Rodriguez, C.; Peluffo-Ordóñez, D., H.; Becerra, M., A.; and Castro-Ospina, A., E.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 26-38. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Cascade classification,Case-based reasoning,Preprocessing,Probability},\n pages = {26-38},\n websites = {http://link.springer.com/10.1007/978-3-319-78723-7_3},\n id = {bc34246f-2b5c-3e9f-a0af-dd726c640450},\n created = {2021-05-10T23:31:45.895Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.895Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {BlancoValencia2018},\n private_publication = {false},\n abstract = {Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.},\n bibtype = {inbook},\n author = {Blanco Valencia, X. and Bastidas Torres, D. and Piñeros Rodriguez, C. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E.},\n doi = {10.1007/978-3-319-78723-7_3},\n chapter = {Case-Based Reasoning Systems for Medical Applications with Improved Adaptation and Recovery Stages},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Case-Based Reasoning Systems (CBR) are in constant evolution, as a result, this article proposes improving the retrieve and adaption stages through a different approach. A series of experiments were made, divided in three sections: a proper pre-processing technique, a cascade classification, and a probability estimation procedure. Every stage offers an improvement, a better data representation, a more efficient classification, and a more precise probability estimation provided by a Support Vector Machine (SVM) estimator regarding more common approaches. Concluding, more complex techniques for classification and probability estimation are possible, improving CBR systems performance due to lower classification error in general cases.\n
\n\n\n\n \n\n \n \n \n \n \n \n Methodology for the design and simulation of industrial facilities and production systems based on a modular approach in an \"industry 4.0\" context.\n \n \n \n \n\n\n \n Alpala, L., O.; Alemany, M., d., M., E.; Peluffo, D., H.; Bolaños, F., A.; Rosero, A., M.; and Torres, J., C.\n\n\n \n\n\n\n DYNA, 85(207): 243-252. 10 2018.\n \n\n\n\n
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\n\n\n@article{\n title = {Methodology for the design and simulation of industrial facilities and production systems based on a modular approach in an "industry 4.0" context},\n type = {article},\n year = {2018},\n keywords = {Coffee processing plant,Industrial facilities,Industry 4.0,Layout,Production system,Simulation},\n pages = {243-252},\n volume = {85},\n websites = {https://revistas.unal.edu.co/index.php/dyna/article/view/68545},\n month = {10},\n day = {1},\n id = {cb7258ac-6d3b-3ff0-8243-0811a80690c7},\n created = {2021-05-10T23:31:45.904Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.904Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Alpala2018},\n private_publication = {false},\n abstract = {The design of the industrial facilities distribution is one of the most important decisions to be made, as it will condition the operation thereof. The concept of industrial installation as it is known today has evolved to the point that it integrates automation and information systems. Indeed, such evolution has given rise to the so-called intelligent factory. At present, in order to produce customized mass products according to customers' requirements, it is become an important issue the distribution of facilities with the generation of successful layout designs, based on the flexibility, modularity and easy configuration of production systems.This paper proposes a methodology to solve the problem of plant distribution design and redesign based upon a novel modular approach within an industry 4.0 context. Proposed methodology is an adaptation of the "SLP" Methodology (Systematic Layout Planning-Simulation) so-called SLP Modulary 4.0 (systematic planning of the Layout based on a modular vision under a context of Industry 4.0); this methodology incorporates in its structure an integrated design system (IDS) into its structure, which allows collaborative work with different CAD design and simulation tools. For the validation of the proposed methodology, a case study of a coffee processing plant is considered. The distribution design results obtained from the case study prove the benefit and usefulness of the proposed methodology.},\n bibtype = {article},\n author = {Alpala, Luis Omar and Alemany, Maria del Mar Eva and Peluffo, DIego Hernán and Bolaños, Fabio Andres and Rosero, Aura Maria and Torres, Juan Carlos},\n doi = {10.15446/dyna.v85n207.68545},\n journal = {DYNA},\n number = {207}\n}\n\n The design of the industrial facilities distribution is one of the most important decisions to be made, as it will condition the operation thereof. The concept of industrial installation as it is known today has evolved to the point that it integrates automation and information systems. Indeed, such evolution has given rise to the so-called intelligent factory. At present, in order to produce customized mass products according to customers' requirements, it is become an important issue the distribution of facilities with the generation of successful layout designs, based on the flexibility, modularity and easy configuration of production systems.This paper proposes a methodology to solve the problem of plant distribution design and redesign based upon a novel modular approach within an industry 4.0 context. Proposed methodology is an adaptation of the \"SLP\" Methodology (Systematic Layout Planning-Simulation) so-called SLP Modulary 4.0 (systematic planning of the Layout based on a modular vision under a context of Industry 4.0); this methodology incorporates in its structure an integrated design system (IDS) into its structure, which allows collaborative work with different CAD design and simulation tools. For the validation of the proposed methodology, a case study of a coffee processing plant is considered. The distribution design results obtained from the case study prove the benefit and usefulness of the proposed methodology.\n
\n\n\n\n \n\n \n \n \n \n \n \n Comparative Analysis Between Embedded-Spaces-Based and Kernel-Based Approaches for Interactive Data Representation.\n \n \n \n \n\n\n \n Basante-Villota, C., K.; Ortega-Castillo, C., M.; Peña-Unigarro, D., F.; Revelo-Fuelagán, J., E.; Salazar-Castro, J., A.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 28-38. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Artificial intelligence,CMDS,Dimensionality reduction methods,Kernel,Kernel PCA,LE,LLE},\n pages = {28-38},\n websites = {http://link.springer.com/10.1007/978-3-319-98998-3_3},\n id = {ec4a3c4e-c584-34f5-9e1d-37368281329e},\n created = {2021-05-10T23:31:45.904Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:45.904Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Basante-Villota2018},\n private_publication = {false},\n abstract = {This work presents a comparative analysis between the linear combination of em-bedded spaces resulting from two approaches: (1) The application of dimensional reduction methods (DR) in their standard implementations, and (2) Their corresponding kernel-based approximations. Namely, considered DR methods are: CMDS (Classical Multi- Dimensional Scaling), LE (Laplacian Eigenmaps) and LLE (Locally Linear Embedding). This study aims at determining -through objective criteria- what approach obtains the best performance of DR task for data visualization. The experimental validation was performed using four databases from the UC Irvine Machine Learning Repository. The quality of the obtained embedded spaces is evaluated regarding the RNX(K) criterion. The RNX(K) allows for evaluating the area under the curve, which indicates the performance of the technique in a global or local topology. Additionally, we measure the computational cost for every comparing experiment. A main contribution of this work is the provided discussion on the selection of an interactivity model when mixturing DR methods, which is a crucial aspect for information visualization purposes.},\n bibtype = {inbook},\n author = {Basante-Villota, C. K. and Ortega-Castillo, C. M. and Peña-Unigarro, D. F. and Revelo-Fuelagán, J. E. and Salazar-Castro, J. A. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-319-98998-3_3},\n chapter = {Comparative Analysis Between Embedded-Spaces-Based and Kernel-Based Approaches for Interactive Data Representation},\n title = {Communications in Computer and Information Science}\n}\n\n This work presents a comparative analysis between the linear combination of em-bedded spaces resulting from two approaches: (1) The application of dimensional reduction methods (DR) in their standard implementations, and (2) Their corresponding kernel-based approximations. Namely, considered DR methods are: CMDS (Classical Multi- Dimensional Scaling), LE (Laplacian Eigenmaps) and LLE (Locally Linear Embedding). This study aims at determining -through objective criteria- what approach obtains the best performance of DR task for data visualization. The experimental validation was performed using four databases from the UC Irvine Machine Learning Repository. The quality of the obtained embedded spaces is evaluated regarding the RNX(K) criterion. The RNX(K) allows for evaluating the area under the curve, which indicates the performance of the technique in a global or local topology. Additionally, we measure the computational cost for every comparing experiment. A main contribution of this work is the provided discussion on the selection of an interactivity model when mixturing DR methods, which is a crucial aspect for information visualization purposes.\n
\n\n\n\n \n\n \n \n \n \n \n \n Exploration of Characterization and Classification Techniques for Movement Identification from EMG Signals: Preliminary Results.\n \n \n \n \n\n\n \n Viveros-Melo, A.; Lasso-Arciniegas, L.; Salazar-Castro, J., A.; Peluffo-Ordóñez, D., H.; Becerra, M., A.; Castro-Ospina, A., E.; and Revelo-Fuelagán, E., J.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 139-149. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Classification,EMG signals,Movements selection,Wavelet},\n pages = {139-149},\n websites = {http://link.springer.com/10.1007/978-3-319-98998-3_11},\n id = {a4c2357f-c314-30d8-b6d2-265eb1c7df87},\n created = {2021-05-10T23:31:46.133Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.133Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Viveros-Melo2018},\n private_publication = {false},\n abstract = {Today, human-computer interfaces are increasingly more often used and become necessary for human daily activities. Among some remarkable applications, we find: Wireless-computer controlling through hand movement, wheelchair directing/guiding with finger motions, and rehabilitation. Such applications are possible from the analysis of electromyographic (EMG) signals. Despite some research works have addressed this issue, the movement classification through EMG signals is still an open challenging issue to the scientific community -especially, because the controller performance depends not only on classifier but other aspects, namely: used features, movements to be classified, the considered feature-selection methods, and collected data. In this work, we propose an exploratory work on the characterization and classification techniques to identifying movements through EMG signals. We compare the performance of three classifiers (KNN, Parzen-density-based classifier and ANN) using spectral (Wavelets) and time-domain-based (statistical and morphological descriptors) features. Also, a methodology for movement selection is proposed. Results are comparable with those reported in literature, reaching classification errors of 5.18% (KNN), 14.7407% (ANN) and 5.17% (Parzen-density-based classifier).},\n bibtype = {inbook},\n author = {Viveros-Melo, A. and Lasso-Arciniegas, L. and Salazar-Castro, J. A. and Peluffo-Ordóñez, D. H. and Becerra, M. A. and Castro-Ospina, A. E. and Revelo-Fuelagán, E. J.},\n doi = {10.1007/978-3-319-98998-3_11},\n chapter = {Exploration of Characterization and Classification Techniques for Movement Identification from EMG Signals: Preliminary Results},\n title = {Communications in Computer and Information Science}\n}\n\n Today, human-computer interfaces are increasingly more often used and become necessary for human daily activities. Among some remarkable applications, we find: Wireless-computer controlling through hand movement, wheelchair directing/guiding with finger motions, and rehabilitation. Such applications are possible from the analysis of electromyographic (EMG) signals. Despite some research works have addressed this issue, the movement classification through EMG signals is still an open challenging issue to the scientific community -especially, because the controller performance depends not only on classifier but other aspects, namely: used features, movements to be classified, the considered feature-selection methods, and collected data. In this work, we propose an exploratory work on the characterization and classification techniques to identifying movements through EMG signals. We compare the performance of three classifiers (KNN, Parzen-density-based classifier and ANN) using spectral (Wavelets) and time-domain-based (statistical and morphological descriptors) features. Also, a methodology for movement selection is proposed. Results are comparable with those reported in literature, reaching classification errors of 5.18% (KNN), 14.7407% (ANN) and 5.17% (Parzen-density-based classifier).\n
\n\n\n\n \n\n \n \n \n \n \n \n Advances in Homotopy Applied to Object Deformation.\n \n \n \n \n\n\n \n Salazar-Castro, J., A.; Umaquinga-Criollo, A., C.; Cruz-Cruz, L., D.; Alpala-Alpala, L., O.; González-Castaño, C.; Becerra-Botero, M., A.; Peluffo-Ordóñez, D., H.; and Castellanos-Domínguez, C., G.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 231-242. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Homotopy,Object deformation,Smooth transitions,Transcendental functions},\n pages = {231-242},\n websites = {http://link.springer.com/10.1007/978-3-319-78759-6_22},\n id = {305cb5ee-fcf9-3c31-92e8-591b613e7245},\n created = {2021-05-10T23:31:46.139Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.139Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Salazar-Castro2018b},\n private_publication = {false},\n abstract = {This work explores novel alternatives to conventional linear homotopy to enhance the quality of resulting transitions from object deformation applications. Studied/introduced approaches extend the linear mapping to other representations that provides smooth transitions when deforming objects while homotopy conditions are fulfilled. Such homotopy approaches are based on transcendental functions (TFH) in both simple and parametric versions. As well, we propose a variant of an existing quality indicator based on the ratio between the coefficients curve of resultant homotopy and that of a less-realistic, reference homotopy. Experimental results depict the effect of proposed TFH approaches regarding its usability and benefit for interpolating images formed by homotopic objects with smooth changes.},\n bibtype = {inbook},\n author = {Salazar-Castro, Jose Alejandro and Umaquinga-Criollo, Ana Cristina and Cruz-Cruz, Lilian Dayana and Alpala-Alpala, Luis Omar and González-Castaño, Catalina and Becerra-Botero, Miguel A. and Peluffo-Ordóñez, Diego Hernán and Castellanos-Domínguez, Cesar Germán},\n doi = {10.1007/978-3-319-78759-6_22},\n chapter = {Advances in Homotopy Applied to Object Deformation},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n This work explores novel alternatives to conventional linear homotopy to enhance the quality of resulting transitions from object deformation applications. Studied/introduced approaches extend the linear mapping to other representations that provides smooth transitions when deforming objects while homotopy conditions are fulfilled. Such homotopy approaches are based on transcendental functions (TFH) in both simple and parametric versions. As well, we propose a variant of an existing quality indicator based on the ratio between the coefficients curve of resultant homotopy and that of a less-realistic, reference homotopy. Experimental results depict the effect of proposed TFH approaches regarding its usability and benefit for interpolating images formed by homotopic objects with smooth changes.\n
\n\n\n\n \n\n \n \n \n \n \n \n Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorithms.\n \n \n \n \n\n\n \n Herrera-Granda, I., D.; Lorente-Leyva, L., L.; Peluffo-Ordóñez, D., H.; Valencia-Chapi, R., M.; Montero-Santos, Y.; Chicaiza-Vaca, J., L.; and Castro-Ospina, A., E.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 95-107. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Clustering algorithms,Contraction hierarchies,Free software,K-means,Optimization,University transportation,Vehicle routing},\n pages = {95-107},\n websites = {http://link.springer.com/10.1007/978-3-319-92639-1_9},\n id = {a44ba06e-6359-3597-997c-296e3cefd1a8},\n created = {2021-05-10T23:31:46.274Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.274Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Herrera-Granda2018},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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.},\n doi = {10.1007/978-3-319-92639-1_9},\n chapter = {Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorithms},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Electroencephalographic Signals and Emotional States for Tactile Pleasantness Classification.\n \n \n \n \n\n\n \n Becerra, M., A.; Londoño-Delgado, E.; Pelaez-Becerra, S., M.; Castro-Ospina, A., E.; Mejia-Arboleda, C.; Durango, J.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 309-316. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Electroencephalographic signal,Sensorial stimulus,Signal processing,Tactile pleasantness},\n pages = {309-316},\n websites = {http://link.springer.com/10.1007/978-3-030-01132-1_35},\n id = {990b571c-f546-3b1f-bbb5-ea0c1147117f},\n created = {2021-05-10T23:31:46.314Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.314Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2018b},\n private_publication = {false},\n abstract = {Haptic textures are alterations of any surface that are perceived and identified using the sense of touch, and such perception affects individuals. Therefore, it has high interest in different applications such as multimedia, medicine, marketing, systems based on human-computer interface among others. Some studies have been carried out using electroencephalographic signals; nevertheless, this can be considered few. Therefore this is an open research field. In this study, an analysis of tactile stimuli and emotion effects was performed from EEG signals to identify pleasantness and unpleasantness sensations using classifier systems. The EEG signals were acquired using Emotiv Epoc+ of 14 channels following a protocol for presenting ten different tactile stimuli two times. Besides, three surveys (Becks depression, emotion test, and tactile stimuli pleasant level) were applied to three volunteers for establishing their emotional state, depression, anxiety and the pleasantness level to characterize each subject. Then, the results of the surveys were computed and the signals preprocessed. Besides, the registers were labeled as pleasant and unpleasant. Feature extraction was applied from Short Time Fourier Transform and discrete wavelet transform calculated to each sub-bands (ƍ, θ, α, β, and γ) of EEG signals. Then, Rough Set algorithm was applied to identify the most relevant features. Also, this technique was employed to establish relations among stimuli and emotional states. Finally, five classifiers based on the support vector machine were tested using 10-fold cross-validation achieving results upper to 99% of accuracy. Also, dependences among emotions and pleasant and unpleasant tactile stimuli were identified.},\n bibtype = {inbook},\n author = {Becerra, Miguel A. and Londoño-Delgado, Edwin and Pelaez-Becerra, Sonia M. and Castro-Ospina, Andrés Eduardo and Mejia-Arboleda, Cristian and Durango, Julián and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-01132-1_35},\n chapter = {Electroencephalographic Signals and Emotional States for Tactile Pleasantness Classification},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Haptic textures are alterations of any surface that are perceived and identified using the sense of touch, and such perception affects individuals. Therefore, it has high interest in different applications such as multimedia, medicine, marketing, systems based on human-computer interface among others. Some studies have been carried out using electroencephalographic signals; nevertheless, this can be considered few. Therefore this is an open research field. In this study, an analysis of tactile stimuli and emotion effects was performed from EEG signals to identify pleasantness and unpleasantness sensations using classifier systems. The EEG signals were acquired using Emotiv Epoc+ of 14 channels following a protocol for presenting ten different tactile stimuli two times. Besides, three surveys (Becks depression, emotion test, and tactile stimuli pleasant level) were applied to three volunteers for establishing their emotional state, depression, anxiety and the pleasantness level to characterize each subject. Then, the results of the surveys were computed and the signals preprocessed. Besides, the registers were labeled as pleasant and unpleasant. Feature extraction was applied from Short Time Fourier Transform and discrete wavelet transform calculated to each sub-bands (ƍ, θ, α, β, and γ) of EEG signals. Then, Rough Set algorithm was applied to identify the most relevant features. Also, this technique was employed to establish relations among stimuli and emotional states. Finally, five classifiers based on the support vector machine were tested using 10-fold cross-validation achieving results upper to 99% of accuracy. Also, dependences among emotions and pleasant and unpleasant tactile stimuli were identified.\n
\n\n\n\n \n\n \n \n \n \n \n \n Physiological Signals Fusion Oriented to Diagnosis - A Review.\n \n \n \n \n\n\n \n Uribe, Y., F.; Alvarez-Uribe, K., C.; Peluffo-Ordoñez, D., H.; and Becerra, M., A.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 1-15. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Data fusion,Diagnostic decision support,Multimodal fusion,Physiological signal,Signal processing},\n pages = {1-15},\n websites = {http://link.springer.com/10.1007/978-3-319-98998-3_1},\n id = {32a0a39c-b8a6-3443-9385-2b39d1db654b},\n created = {2021-05-10T23:31:46.538Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.538Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Uribe2018},\n private_publication = {false},\n abstract = {The analysis of physiological signals is widely used for the development of diagnosis support tools in medicine, and it is currently an open research field. The use of multiple signals or physiological measures as a whole has been carried out using data fusion techniques commonly known as multimodal fusion, which has demonstrated its ability to improve the accuracy of diagnostic care systems. This paper presents a review of state of the art, putting in relief the main techniques, challenges, gaps, advantages, disadvantages, and practical considerations of data fusion applied to the analysis of physiological signals oriented to diagnosis decision support. Also, physiological signals data fusion architecture oriented to diagnosis is proposed.},\n bibtype = {inbook},\n author = {Uribe, Y. F. and Alvarez-Uribe, K. C. and Peluffo-Ordoñez, D. H. and Becerra, M. A.},\n doi = {10.1007/978-3-319-98998-3_1},\n chapter = {Physiological Signals Fusion Oriented to Diagnosis - A Review},\n title = {Communications in Computer and Information Science}\n}\n\n The analysis of physiological signals is widely used for the development of diagnosis support tools in medicine, and it is currently an open research field. The use of multiple signals or physiological measures as a whole has been carried out using data fusion techniques commonly known as multimodal fusion, which has demonstrated its ability to improve the accuracy of diagnostic care systems. This paper presents a review of state of the art, putting in relief the main techniques, challenges, gaps, advantages, disadvantages, and practical considerations of data fusion applied to the analysis of physiological signals oriented to diagnosis decision support. Also, physiological signals data fusion architecture oriented to diagnosis is proposed.\n
\n\n\n\n \n\n \n \n \n \n \n \n Fingertips Segmentation of Thermal Images and Its Potential Use in Hand Thermoregulation Analysis.\n \n \n \n \n\n\n \n Castro-Ospina, A., E.; Correa-Mira, A., M.; Herrera-Granda, I., D.; Peluffo-Ordóñez, D., H.; and Fandiño-Toro, H., A.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 455-463. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Fingertip segmentation,NPR measurement,Thermal hand images,Thermorregulation},\n pages = {455-463},\n websites = {http://link.springer.com/10.1007/978-3-319-92639-1_38},\n id = {da8e81f4-2517-3a9f-a30c-2e2c16581ceb},\n created = {2021-05-10T23:31:46.544Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.544Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Castro-Ospina2018},\n private_publication = {false},\n abstract = {Thermoregulation refers to the physiological processes that maintain stable the body temperatures. Infrared thermography is a non-invasive technique useful for visualizing these temperatures. Previous works suggest it is important to analyze thermoregulation in peripheral regions, such as the fingertips, because some disabling pathologies affect particularly the thermoregulation of these regions. This work proposes an algorithm for fingertip segmentation in thermal images of the hand. By using a supervised index, the results are compared against segmentations provided by humans. The results are outstanding even when the analyzed images are highly resized.},\n bibtype = {inbook},\n author = {Castro-Ospina, A. E. and Correa-Mira, A. M. and Herrera-Granda, I. D. and Peluffo-Ordóñez, D. H. and Fandiño-Toro, H. A.},\n doi = {10.1007/978-3-319-92639-1_38},\n chapter = {Fingertips Segmentation of Thermal Images and Its Potential Use in Hand Thermoregulation Analysis},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Thermoregulation refers to the physiological processes that maintain stable the body temperatures. Infrared thermography is a non-invasive technique useful for visualizing these temperatures. Previous works suggest it is important to analyze thermoregulation in peripheral regions, such as the fingertips, because some disabling pathologies affect particularly the thermoregulation of these regions. This work proposes an algorithm for fingertip segmentation in thermal images of the hand. By using a supervised index, the results are compared against segmentations provided by humans. The results are outstanding even when the analyzed images are highly resized.\n
\n\n\n\n \n\n \n \n \n \n \n \n Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Godoy-Trujillo, P.; Flores-Bosmediano, E.; Carrascal-Garcia, J.; Otero-Potosi, S.; Benitez-Pereira, H.; and Peluffo-Ordonez, D., H.\n\n\n \n\n\n\n In 2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM), pages 1-5, 10 2018. IEEE\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Sign Language Recognition Based on Intelligent Glove Using Machine Learning Techniques},\n type = {inproceedings},\n year = {2018},\n keywords = {intelligent glove,knn,prototype selection,sign language},\n pages = {1-5},\n websites = {https://ieeexplore.ieee.org/document/8580268/},\n month = {10},\n publisher = {IEEE},\n id = {48b45fe2-cd74-3e71-9368-b9f67c99698b},\n created = {2021-05-10T23:31:46.707Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.707Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018a},\n private_publication = {false},\n abstract = {We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Godoy-Trujillo, Pamela and Flores-Bosmediano, Edison and Carrascal-Garcia, Jorge and Otero-Potosi, Santiago and Benitez-Pereira, Henry and Peluffo-Ordonez, Diego H.},\n doi = {10.1109/ETCM.2018.8580268},\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\n}\n\n We present an intelligent electronic glove system able to detect numbers of sign language in order to automate the process of communication between a deaf-mute person and others. This is done by translating the hands move sign language into an oral language. The system is inside to a glove with flex sensors in each finger that we are used to collect data that are analyzed through a methodology involving the following stages: (i) Data balancing with the Kennard-Stone (KS), (ii) Comparison of prototypes selection between CHC evolutionary Algorithm and Decremental Reduction Optimization Procedure 3 (DROP3) to define the best one. Subsequently, the K-Nearest Neighbors (kNN) as classifier (iii) is implemented. As a result, the amount of data reduced from stage (i) from storage within the system is 98%. Also, a classification performance of 85% is achieved with CHC evolutionary algorithm.\n
\n\n\n\n \n\n \n \n \n \n \n \n Generalized Low-Computational Cost Laplacian Eigenmaps.\n \n \n \n \n\n\n \n Salazar-Castro, J., A.; Peña, D., F.; Basante, C.; Ortega, C.; Cruz-Cruz, L.; Revelo-Fuelagán, J.; Blanco-Valencia, X., P.; Castellanos-Domínguez, G.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 661-669. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Dimensionality reduction,Generalized methodology,Kernel approximations,Low-computational cost,Multiple kernel learning,Spectral methods},\n pages = {661-669},\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_69},\n id = {a6319236-f058-3954-8733-030eb4b01271},\n created = {2021-05-10T23:31:46.723Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.723Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Salazar-Castro2018},\n private_publication = {false},\n abstract = {Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.},\n bibtype = {inbook},\n author = {Salazar-Castro, J. A. and Peña, D. F. and Basante, C. and Ortega, C. and Cruz-Cruz, L. and Revelo-Fuelagán, J. and Blanco-Valencia, X. P. and Castellanos-Domínguez, G. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-030-03493-1_69},\n chapter = {Generalized Low-Computational Cost Laplacian Eigenmaps},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and may represent a preprocessing stage or be an essential element for the representation and classification of data. The main objective of DR is to obtain a new representation of the original data in a space of smaller dimension, such that more refined information is produced, as well as the time of the subsequent processing is decreased and/or visual representations more intelligible for human beings are generated. The spectral DR methods involve the calculation of an eigenvalue and eigenvector decomposition, which is usually high-computational-cost demanding, and, therefore, the task of obtaining a more dynamic and interactive user-machine integration is difficult. Therefore, for the design of an interactive IV system based on DR spectral methods, it is necessary to propose a strategy to reduce the computational cost required in the calculation of eigenvectors and eigenvalues. For this purpose, it is proposed to use locally linear submatrices and spectral embedding. This allows integrating natural intelligence with computational intelligence for the representation of data interactively, dynamically and at low computational cost. Additionally, an interactive model is proposed that allows the user to dynamically visualize the data through a weighted mixture.\n
\n\n\n\n \n\n \n \n \n \n \n \n Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models.\n \n \n \n \n\n\n \n Rosero-Montalvo, P., D.; Pijal-Rojas, J.; Vasquez-Ayala, C.; Maya, E.; Pupiales, C.; Suarez, L.; Benitez-Pereira, H.; and Peluffo-Ordonez, D.\n\n\n \n\n\n\n In 2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM), pages 1-6, 10 2018. IEEE\n \n\n\n\n
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\n\n\n@inproceedings{\n title = {Wireless Sensor Networks for Irrigation in Crops Using Multivariate Regression Models},\n type = {inproceedings},\n year = {2018},\n keywords = {WSN,crops analysis,regression model},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/8580322/},\n month = {10},\n publisher = {IEEE},\n id = {1c6f9e13-9824-3159-945e-3b36ccada7d7},\n created = {2021-05-10T23:31:46.839Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:46.839Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rosero-Montalvo2018b},\n private_publication = {false},\n abstract = {The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.},\n bibtype = {inproceedings},\n author = {Rosero-Montalvo, Paul D. and Pijal-Rojas, Jose and Vasquez-Ayala, Carlos and Maya, Edgar and Pupiales, Carlos and Suarez, Luis and Benitez-Pereira, Henry and Peluffo-Ordonez, D.H.},\n doi = {10.1109/ETCM.2018.8580322},\n booktitle = {2018 IEEE Third Ecuador Technical Chapters Meeting (ETCM)}\n}\n\n The present wireless sensor network system shows a data analysis approach within greenhouses in short cycle crops. This research, on the one hand, is carried out to reduce water consumption and improve the product by predicting the right moment of the irrigation cycle through the evapotranspiration criterion. On the other hand, an efficient electronic system is designed under the electronic standard. To define the best model to define the next irrigation in the crops in base to ground humidity, the algorithms are compared for continuous and discontinuous multivariate regressions. The results are evaluated with different criteria of prediction errors. As a result, the linear regression with Support Vector Machine model is chosen for counting an average deviation error of 7.89% and an error variability of 4.48%. In addition, water consumption is reduced by 20%, achieving better quality products.\n
\n\n\n\n \n\n \n \n \n \n \n \n Computer Vision-Based Method for Automatic Detection of Crop Rows in Potato Fields.\n \n \n \n \n\n\n \n García-Santillán, I.; Peluffo-Ordoñez, D.; Caranqui, V.; Pusdá, M.; Garrido, F.; and Granda, P.\n\n\n \n\n\n\n Advances in Intelligent Systems and Computing, pages 355-366. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Autonomous guidance,Computer vision,Crop row detection,Image segmentation},\n pages = {355-366},\n websites = {http://link.springer.com/10.1007/978-3-319-73450-7_34},\n id = {18bc712c-8b07-34d7-a98f-e478750169d2},\n created = {2021-05-10T23:31:47.061Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.061Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Garcia-Santillan2018},\n private_publication = {false},\n abstract = {This work presents an adaptation and validation of a method for automatic crop row detection from images captured in potato fields (Solanum tuberosum) for initial growth stages based on the micro-ROI concept. The crop row detection is a crucial aspect for autonomous guidance of agricultural vehicles and site-specific treatments application. The images were obtained using a color camera installed in the front of a tractor under perspective projection. There are some issues that can affect the quality of the images and the detection procedure, among them: uncontrolled illumination in outdoor agricultural environments, different plant densities, presence of weeds and gaps in the crop rows. The adapted approach was designed to address these adverse situations and it consists of three linked phases. The main contribution is the ability to detect straight and curved crop rows in potato crops. The performance was quantitatively compared against two existing methods, achieving acceptable results in terms of accuracy and processing time.},\n bibtype = {inbook},\n author = {García-Santillán, Iván and Peluffo-Ordoñez, Diego and Caranqui, Víctor and Pusdá, Marco and Garrido, Fernando and Granda, Pedro},\n doi = {10.1007/978-3-319-73450-7_34},\n chapter = {Computer Vision-Based Method for Automatic Detection of Crop Rows in Potato Fields},\n title = {Advances in Intelligent Systems and Computing}\n}\n\n This work presents an adaptation and validation of a method for automatic crop row detection from images captured in potato fields (Solanum tuberosum) for initial growth stages based on the micro-ROI concept. The crop row detection is a crucial aspect for autonomous guidance of agricultural vehicles and site-specific treatments application. The images were obtained using a color camera installed in the front of a tractor under perspective projection. There are some issues that can affect the quality of the images and the detection procedure, among them: uncontrolled illumination in outdoor agricultural environments, different plant densities, presence of weeds and gaps in the crop rows. The adapted approach was designed to address these adverse situations and it consists of three linked phases. The main contribution is the ability to detect straight and curved crop rows in potato crops. The performance was quantitatively compared against two existing methods, achieving acceptable results in terms of accuracy and processing time.\n
\n\n\n\n \n\n \n \n \n \n \n \n Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems.\n \n \n \n \n\n\n \n Becerra, M., A.; Duque-Mejía, C.; Zapata-Hernández, C.; Peluffo-Ordóñez, D., H.; Serna-Guarín, L.; Delgado-Trejos, E.; Revelo-Fuelagán, E., J.; and Blanco Valencia, X., P.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 410-418. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Biometric identification,Cardiac murmur,Electrocardiographic signal,Signal processing},\n pages = {410-418},\n websites = {http://link.springer.com/10.1007/978-3-030-03493-1_43},\n id = {4b191a37-1c7f-3e93-a3ae-34ae6fbb8efd},\n created = {2021-05-10T23:31:47.230Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.230Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2018},\n private_publication = {false},\n abstract = {The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.},\n bibtype = {inbook},\n author = {Becerra, M. A. and Duque-Mejía, C. and Zapata-Hernández, C. and Peluffo-Ordóñez, D. H. and Serna-Guarín, L. and Delgado-Trejos, Edilson and Revelo-Fuelagán, E. J. and Blanco Valencia, X. P.},\n doi = {10.1007/978-3-030-03493-1_43},\n chapter = {Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.\n
\n\n\n\n \n\n \n \n \n \n \n \n Low Data Fusion Framework Oriented to Information Quality for BCI Systems.\n \n \n \n \n\n\n \n Becerra, M., A.; Alvarez-Uribe, K., C.; and Peluffo-Ordoñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 289-300. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Brain-computer interface,Data fusion,Evaluation system,Information quality},\n pages = {289-300},\n websites = {http://link.springer.com/10.1007/978-3-319-78759-6_27},\n id = {6f24fb3e-ff0e-3b93-8277-9db808971969},\n created = {2021-05-10T23:31:47.237Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.237Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2018c},\n private_publication = {false},\n abstract = {The evaluation of the data/information fusion systems does not have standard quality criteria making the reuse and optimization of these systems a complex task. In this work, we propose a complete low data fusion (DF) framework based on the Joint Director of Laboratories (JDL) model, which considers contextual information alongside information quality (IQ) and performance evaluation system to optimize the DF process according to the user requirements. A set of IQ criteria was proposed by level. The model was tested with a brain-computer interface (BCI) system multi-environment to prove its functionality. The first level makes the selection and preprocessing of electroencephalographic signals. In level one feature extraction is carried out using discrete wavelet transform (DWT), nonlinear and linear statistical measures, and Fuzzy Rough Set – FRS algorithm for selecting the relevant features; finally, in the same level a classification process was conducted using support vector machine – SVM. A Fuzzy Inference system is used for controlling different processes based on the results given by an IQ evaluation system, which applies quality measures that can be weighted by the users of the system according to their requirements. Besides, the system is optimized based on the results given by the cuckoo search algorithm, which uses the IQ traceability for maximizing the IQ criteria according to user requirements. The test was carried out with different type and levels of noise applied to the signals. The results showed the capability and functionality of the model.},\n bibtype = {inbook},\n author = {Becerra, Miguel Alberto and Alvarez-Uribe, Karla C. and Peluffo-Ordoñez, Diego Hernán},\n doi = {10.1007/978-3-319-78759-6_27},\n chapter = {Low Data Fusion Framework Oriented to Information Quality for BCI Systems},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n The evaluation of the data/information fusion systems does not have standard quality criteria making the reuse and optimization of these systems a complex task. In this work, we propose a complete low data fusion (DF) framework based on the Joint Director of Laboratories (JDL) model, which considers contextual information alongside information quality (IQ) and performance evaluation system to optimize the DF process according to the user requirements. A set of IQ criteria was proposed by level. The model was tested with a brain-computer interface (BCI) system multi-environment to prove its functionality. The first level makes the selection and preprocessing of electroencephalographic signals. In level one feature extraction is carried out using discrete wavelet transform (DWT), nonlinear and linear statistical measures, and Fuzzy Rough Set – FRS algorithm for selecting the relevant features; finally, in the same level a classification process was conducted using support vector machine – SVM. A Fuzzy Inference system is used for controlling different processes based on the results given by an IQ evaluation system, which applies quality measures that can be weighted by the users of the system according to their requirements. Besides, the system is optimized based on the results given by the cuckoo search algorithm, which uses the IQ traceability for maximizing the IQ criteria according to user requirements. The test was carried out with different type and levels of noise applied to the signals. The results showed the capability and functionality of the model.\n
\n\n\n\n \n\n \n \n \n \n \n \n A Novel Color-Based Data Visualization Approach Using a Circular Interaction Model and Dimensionality Reduction.\n \n \n \n \n\n\n \n Salazar-Castro, J., A.; Rosero-Montalvo, P., D.; Peña-Unigarro, D., F.; Umaquinga-Criollo, A., C.; Castillo-Marrero, Z.; Revelo-Fuelagán, E., J.; Peluffo-Ordóñez, D., H.; and Castellanos-Domínguez, C., G.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 557-567. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Data visualization,Dimensionality reduction,Interactive interface,Pairwise similarity},\n pages = {557-567},\n websites = {http://link.springer.com/10.1007/978-3-319-92537-0_64},\n id = {80a3c048-876b-371c-ac85-ef182388e408},\n created = {2021-05-10T23:31:47.295Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.295Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Salazar-Castro2018a},\n private_publication = {false},\n abstract = {Dimensionality reduction (DR) methods are able to produce low-dimensional representations of an input data sets which may become intelligible for human perception. Nonetheless, most existing DR approaches lack the ability to naturally provide the users with the faculty of controlability and interactivity. In this connection, data visualization (DataVis) results in an ideal complement. This work presents an integration of DR and DataVis through a new approach for data visualization based on a mixture of DR resultant representations while using visualization principle. Particularly, the mixture is done through a weighted sum, whose weighting factors are defined by the user through a novel interface. The interface’s concept relies on the combination of the color-based and geometrical perception in a circular framework so that the users may have a at hand several indicators (shape, color, surface size) to make a decision on a specific data representation. Besides, pairwise similarities are plotted as a non-weighted graph to include a graphic notion of the structure of input data. Therefore, the proposed visualization approach enables the user to interactively combine DR methods, while providing information about the structure of original data, making then the selection of a DR scheme more intuitive.},\n bibtype = {inbook},\n author = {Salazar-Castro, Jose Alejandro and Rosero-Montalvo, Paul D. and Peña-Unigarro, Diego Fernando and Umaquinga-Criollo, Ana Cristina and Castillo-Marrero, Zenaida and Revelo-Fuelagán, Edgardo Javier and Peluffo-Ordóñez, Diego Hernán and Castellanos-Domínguez, César Germán},\n doi = {10.1007/978-3-319-92537-0_64},\n chapter = {A Novel Color-Based Data Visualization Approach Using a Circular Interaction Model and Dimensionality Reduction},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n Dimensionality reduction (DR) methods are able to produce low-dimensional representations of an input data sets which may become intelligible for human perception. Nonetheless, most existing DR approaches lack the ability to naturally provide the users with the faculty of controlability and interactivity. In this connection, data visualization (DataVis) results in an ideal complement. This work presents an integration of DR and DataVis through a new approach for data visualization based on a mixture of DR resultant representations while using visualization principle. Particularly, the mixture is done through a weighted sum, whose weighting factors are defined by the user through a novel interface. The interface’s concept relies on the combination of the color-based and geometrical perception in a circular framework so that the users may have a at hand several indicators (shape, color, surface size) to make a decision on a specific data representation. Besides, pairwise similarities are plotted as a non-weighted graph to include a graphic notion of the structure of input data. Therefore, the proposed visualization approach enables the user to interactively combine DR methods, while providing information about the structure of original data, making then the selection of a DR scheme more intuitive.\n
\n\n\n\n \n\n \n \n \n \n \n \n Developments on Solutions of the Normalized-Cut-Clustering Problem Without Eigenvectors.\n \n \n \n \n\n\n \n Lorente-Leyva, L., L.; Herrera-Granda, I., D.; Rosero-Montalvo, P., D.; Ponce-Guevara, K., L.; Castro-Ospina, A., E.; Becerra, M., A.; Peluffo-Ordóñez, D., H.; and Rodríguez-Sotelo, J., L.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 318-328. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Eigenvectors,Graph-based clustering,Normalized cut clustering,Quadratic forms},\n pages = {318-328},\n websites = {http://link.springer.com/10.1007/978-3-319-92537-0_37},\n id = {3eacd037-4e24-3228-b858-2ce5af9a024b},\n created = {2021-05-10T23:31:47.383Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.383Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Lorente-Leyva2018},\n private_publication = {false},\n abstract = {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.},\n bibtype = {inbook},\n 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},\n doi = {10.1007/978-3-319-92537-0_37},\n chapter = {Developments on Solutions of the Normalized-Cut-Clustering Problem Without Eigenvectors},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n 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.\n
\n\n\n\n \n\n \n \n \n \n \n \n Voice Pathology Detection Using Artificial Neural Networks and Support Vector Machines Powered by a Multicriteria Optimization Algorithm.\n \n \n \n \n\n\n \n Areiza-Laverde, H., J.; Castro-Ospina, A., E.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 148-159. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Classification,Computer-aided diagnosis,Optimization,Voice pathology},\n pages = {148-159},\n websites = {http://link.springer.com/10.1007/978-3-030-00350-0_13},\n id = {f74ac284-876a-3bcf-abef-dc49b52f344b},\n created = {2021-05-10T23:31:47.649Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.649Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Areiza-Laverde2018},\n private_publication = {false},\n abstract = {Computer-aided diagnosis (CAD) systems have allowed to enhance the performance of conventional, medical diagnosis procedures in different scenarios. Particularly, in the context of voice pathology detection, the use of machine learning algorithms has proved to be a promising and suitable alternative. This work proposes the implementation of two well known classification algorithms, namely artificial neural networks (ANN) and support vector machines (SVM), optimized by particle swarm optimization (PSO) algorithm, aimed at classifying voice signals between healthy and pathologic ones. Three different configurations of the Saarbrucken voice database (SVD) are used. The effect of using balanced and unbalanced versions of this dataset is proved as well as the usefulness of the considered optimization algorithm to improve the final performance outcomes. Also, proposed approach is comparable with state-of-the-art methods.},\n bibtype = {inbook},\n author = {Areiza-Laverde, Henry Jhoán and Castro-Ospina, Andrés Eduardo and Peluffo-Ordóñez, Diego Hernán},\n doi = {10.1007/978-3-030-00350-0_13},\n chapter = {Voice Pathology Detection Using Artificial Neural Networks and Support Vector Machines Powered by a Multicriteria Optimization Algorithm},\n title = {Communications in Computer and Information Science}\n}\n\n Computer-aided diagnosis (CAD) systems have allowed to enhance the performance of conventional, medical diagnosis procedures in different scenarios. Particularly, in the context of voice pathology detection, the use of machine learning algorithms has proved to be a promising and suitable alternative. This work proposes the implementation of two well known classification algorithms, namely artificial neural networks (ANN) and support vector machines (SVM), optimized by particle swarm optimization (PSO) algorithm, aimed at classifying voice signals between healthy and pathologic ones. Three different configurations of the Saarbrucken voice database (SVD) are used. The effect of using balanced and unbalanced versions of this dataset is proved as well as the usefulness of the considered optimization algorithm to improve the final performance outcomes. Also, proposed approach is comparable with state-of-the-art methods.\n
\n\n\n\n \n\n \n \n \n \n \n \n Angle-Based Model for Interactive Dimensionality Reduction and Data Visualization.\n \n \n \n \n\n\n \n Basante-Villota, C., K.; Ortega-Castillo, C., M.; Peña-Unigarro, D., F.; Revelo-Fuelagán, E., J.; Salazar-Castro, J., A.; Ortega-Bustamante, M.; Rosero-Montalvo, P.; Vega-Escobar, L., S.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 149-157. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Data visualization,Dimensionality reduction,Kernel PCA,Pairwise similarity},\n pages = {149-157},\n websites = {http://link.springer.com/10.1007/978-3-030-01132-1_17},\n id = {a9f23a45-f742-3a7c-ad32-ad4c283fa7d1},\n created = {2021-05-10T23:31:47.715Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:47.715Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Basante-Villota2018a},\n private_publication = {false},\n abstract = {In recent times, an undeniable fact is that the amount of data available has increased dramatically due mainly to the advance of new technologies allowing for storage and communication of enormous volumes of information. In consequence, there is an important need for finding the relevant information within the raw data through the application of novel data visualization techniques that permit the correct manipulation of data. This issue has motivated the development of graphic forms for visually representing and analyzing high-dimensional data. Particularly, in this work, we propose a graphical approach, which, allows the combination of dimensionality reduction (DR) methods using an angle-based model, making the data visualization more intelligible. Such approach is designed for a readily use, so that the input parameters are interactively given by the user within a user-friendly environment. The proposed approach enables users (even those being non-experts) to intuitively select a particular DR method or perform a mixture of methods. The experimental results prove that the interactive manipulation enabled by the here-proposed model-due to its ability of displaying a variety of embedded spaces-makes the task of selecting a embedded space simpler and more adequately fitted for a specific need.},\n bibtype = {inbook},\n author = {Basante-Villota, Cielo K. and Ortega-Castillo, Carlos M. and Peña-Unigarro, Diego F. and Revelo-Fuelagán, E. Javier and Salazar-Castro, Jose A. and Ortega-Bustamante, MacArthur and Rosero-Montalvo, Paul and Vega-Escobar, Laura Stella and Peluffo-Ordóñez, Diego H.},\n doi = {10.1007/978-3-030-01132-1_17},\n chapter = {Angle-Based Model for Interactive Dimensionality Reduction and Data Visualization},\n title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}\n}\n\n In recent times, an undeniable fact is that the amount of data available has increased dramatically due mainly to the advance of new technologies allowing for storage and communication of enormous volumes of information. In consequence, there is an important need for finding the relevant information within the raw data through the application of novel data visualization techniques that permit the correct manipulation of data. This issue has motivated the development of graphic forms for visually representing and analyzing high-dimensional data. Particularly, in this work, we propose a graphical approach, which, allows the combination of dimensionality reduction (DR) methods using an angle-based model, making the data visualization more intelligible. Such approach is designed for a readily use, so that the input parameters are interactively given by the user within a user-friendly environment. The proposed approach enables users (even those being non-experts) to intuitively select a particular DR method or perform a mixture of methods. The experimental results prove that the interactive manipulation enabled by the here-proposed model-due to its ability of displaying a variety of embedded spaces-makes the task of selecting a embedded space simpler and more adequately fitted for a specific need.\n
\n\n\n\n \n\n \n \n \n \n \n \n Odor Pleasantness Classification from Electroencephalographic Signals and Emotional States.\n \n \n \n \n\n\n \n Becerra, M., A.; Londoño-Delgado, E.; Pelaez-Becerra, S., M.; Serna-Guarín, L.; Castro-Ospina, A., E.; Marin-Castrillón, D.; and Peluffo-Ordóñez, D., H.\n\n\n \n\n\n\n Communications in Computer and Information Science, pages 128-138. 2018.\n \n\n\n\n
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\n\n\n@inbook{\n type = {inbook},\n year = {2018},\n keywords = {Electroencephalographic signal,Emotion,Odor pleasantness,Sensorial stimuli,Signal processing},\n pages = {128-138},\n websites = {http://link.springer.com/10.1007/978-3-319-98998-3_10},\n id = {533da51e-5559-35a6-ae9b-75a3a0e61a03},\n created = {2021-05-10T23:31:48.044Z},\n file_attached = {false},\n profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},\n group_id = {b8c873a2-ed58-396e-b124-8a273665874f},\n last_modified = {2021-05-10T23:31:48.044Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Becerra2018a},\n private_publication = {false},\n abstract = {Odor identification refers to the capability of the olfactory sense for discerning odors. The interest in this sense has grown over multiple fields and applications such as multimedia, virtual reality, marketing, among others. Therefore, objective identification of pleasant and unpleasant odors is an open research field. Some studies have been carried out based on electroencephalographic signals (EEG). Nevertheless, these can be considered insufficient due to the levels of accuracy achieved so far. The main objective of this study was to investigate the capability of the classifiers systems for identification pleasant and unpleasant odors from EEG signals. The methodology applied was carried out in three stages. First, an odor database was collected using the signals recorded with an Emotiv Epoc+ with 14 channels of electroencephalography (EEG) and using a survey for establishing the emotion levels based on valence and arousal considering that the odor induces emotions. The registers were acquired from three subjects, each was subjected to 10 different odor stimuli two times. The second stage was the feature extraction which was carried out on 5 sub-bands δ, θ, α, β, γ of EEG signals using discrete wavelet transform, statistical measures, and other measures such as area, energy, and entropy. Then, feature selection was applied based on Rough Set algorithms. Finally, in the third stage was applied a Support vector machine (SVM) classifier, which was tested with five different kernels. The performance of classifiers was compared using k-fold cross-validation. The best result of 99.9% was achieved using the linear kernel. The more relevant features were obtained from sub-bands β and α. Finally, relations among emotion, EEG, and odors were demonstrated.},\n bibtype = {inbook},\n author = {Becerra, M. A. and Londoño-Delgado, E. and Pelaez-Becerra, S. M. and Serna-Guarín, L. and Castro-Ospina, A. E. and Marin-Castrillón, D. and Peluffo-Ordóñez, D. H.},\n doi = {10.1007/978-3-319-98998-3_10},\n chapter = {Odor Pleasantness Classification from Electroencephalographic Signals and Emotional States},\n title = {Communications in Computer and Information Science}\n}\n\n Odor identification refers to the capability of the olfactory sense for discerning odors. The interest in this sense has grown over multiple fields and applications such as multimedia, virtual reality, marketing, among others. Therefore, objective identification of pleasant and unpleasant odors is an open research field. Some studies have been carried out based on electroencephalographic signals (EEG). Nevertheless, these can be considered insufficient due to the levels of accuracy achieved so far. The main objective of this study was to investigate the capability of the classifiers systems for identification pleasant and unpleasant odors from EEG signals. The methodology applied was carried out in three stages. First, an odor database was collected using the signals recorded with an Emotiv Epoc+ with 14 channels of electroencephalography (EEG) and using a survey for establishing the emotion levels based on valence and arousal considering that the odor induces emotions. The registers were acquired from three subjects, each was subjected to 10 different odor stimuli two times. The second stage was the feature extraction which was carried out on 5 sub-bands δ, θ, α, β, γ of EEG signals using discrete wavelet transform, statistical measures, and other measures such as area, energy, and entropy. Then, feature selection was applied based on Rough Set algorithms. Finally, in the third stage was applied a Support vector machine (SVM) classifier, which was tested with five different kernels. The performance of classifiers was compared using k-fold cross-validation. The best result of 99.9% was achieved using the linear kernel. The more relevant features were obtained from sub-bands β and α. Finally, relations among emotion, EEG, and odors were demonstrated.\n
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