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3. Machine Learning Modeling in Industrial Processes for Visual Analysis

Author

Morán, Antonio, Alonso, Serafín, Fuertes, Juan J., Prada, Miguel A., Roca, Lidia, Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Papaleonidas, Antonios, editor, Pimenidis, Elias, editor, and Jayne, Chrisina, editor

Published
2024
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4. Deep Echo State Networks for Modelling of Industrial Systems

Author

Rodríguez-Ossorio, José Ramón, Gallicchio, Claudio, Morán, Antonio, Díaz, Ignacio, Fuertes, Juan J., Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Papaleonidas, Antonios, editor, Pimenidis, Elias, editor, and Jayne, Chrisina, editor

Published
2024
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5. Integrating microbial electrochemical technologies with anaerobic digestion to accelerate propionate degradation

Author

Alonso, Raul M., Escapa, Adrian, Sotres, Ana, and Moran, Antonio

Subjects
Quantitative Biology - Quantitative Methods
Abstract

The aim of this study is to evaluate the integration of microbial electrochemical technologies (MET) with anaerobic digestion (AD) to overcome AD limitations caused by propionate accumulation. The study focuses on understanding to what extent the inoculum impacts on the behaviour of the integrated systems (AD-MET) from the perspective of propionate degradation, methane production and microbial population dynamics. Three different inocula were used: two from environmental sources (anaerobic sludge and river sediment) and another one from a pre-enriched electroactive consortium adapted to propionate degradation. Contrary to expectations, the reactor inoculated with the pre-enriched consortium was not able to maintain its initial good performance in the long run, and the bioelectrochemical activity collapsed after three months of operation. In contrast, the reactor inoculated with anaerobic sludge, although it required a relatively longer time to produce any observable current, was able to maintain the electrogenic activity operation (0.8 A.m-2) as well as the positive contribution of AD-MET integration to tackle propionate accumulation and to enhance methane yield (338 mL.gCOD-1). However, it must also be highlighted that from a purely energetic point of view the AD-MET was not favorable.

Published
2020

6. Degradation of 2-mercaptobenzothizaole in microbial electrolysis cells: intermediates, toxicity, and microbial communities

Author

San-Martin, M. Isabel, Escapaa, Adrian, Alonso, Raul M., Canle, Moises, and Moran, Antonio

Subjects
Quantitative Biology - Genomics, Quantitative Biology - Populations and Evolution
Abstract

The compound 2-mercaptobenzothizaole (MBT) has been frequently detected in wastewater and surface water and is a potential threat to both aquatic organisms and human health (its mutagenic potential has been demonstrated). This study investigated the degradation routes of MBT in the anode of a microbial electrolysis cell (MEC) and the involved microbial communities. The results indicated that graphene-modified anodes promoted the presence of more enriched, developed, and specific communities compared to bare anodes. Moreover, consecutive additions of the OH substituent to the benzene ring of MBT were only detected in the reactor equipped with the graphene-treated electrode. Both phenomena, together with the application of an external voltage, may be related to the larger reduction of biotoxicity observed in the MEC equipped with graphene-modified anodes (46.2 eqtox/m3 to 27.9 eqtox/m3).

Published
2020
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8. Adaptive Model for Industrial Systems Using Echo State Networks

Author

Rodríguez-Ossorio, José Ramón, Morán, Antonio, Fuertes, Juan J., Prada, Miguel A., Díaz, Ignacio, Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Chen, Phoebe, Editorial Board Member, Cuzzocrea, Alfredo, Editorial Board Member, Du, Xiaoyong, Editorial Board Member, Kara, Orhun, Editorial Board Member, Liu, Ting, Editorial Board Member, Sivalingam, Krishna M., Editorial Board Member, Slezak, Dominik, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yang, Xiaokang, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Alonso, Serafin, editor, Jayne, Chrisina, editor, and Pimenidis, Elias, editor

Published
2023
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9. Virtual Flow Meter for an Industrial Process

Author

González-Herbón, Raúl, González-Mateos, Guzmán, Alonso, Serafín, Prada, Miguel A., Fuertes, Juan J., Morán, Antonio, Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Chen, Phoebe, Editorial Board Member, Cuzzocrea, Alfredo, Editorial Board Member, Du, Xiaoyong, Editorial Board Member, Kara, Orhun, Editorial Board Member, Liu, Ting, Editorial Board Member, Sivalingam, Krishna M., Editorial Board Member, Slezak, Dominik, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yang, Xiaokang, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Alonso, Serafin, editor, Jayne, Chrisina, editor, and Pimenidis, Elias, editor

Published
2023
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10. Hierarchical Prediction in Incomplete Submetering Systems Using a CNN

Author

Alonso, Serafín, Morán, Antonio, Pérez, Daniel, Prada, Miguel A., Fuertes, Juan J., Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Chen, Phoebe, Editorial Board Member, Cuzzocrea, Alfredo, Editorial Board Member, Du, Xiaoyong, Editorial Board Member, Kara, Orhun, Editorial Board Member, Liu, Ting, Editorial Board Member, Sivalingam, Krishna M., Editorial Board Member, Slezak, Dominik, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yang, Xiaokang, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, Alonso, Serafin, editor, Jayne, Chrisina, editor, and Pimenidis, Elias, editor

Published
2023
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14. Reconstructing Electricity Profiles in Submetering Systems Using a GRU-AE Network

Author

Alonso, Serafín, Morán, Antonio, Pérez, Daniel, Prada, Miguel A., Fuertes, Juan J., Domínguez, Manuel, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Iliadis, Lazaros, editor, Jayne, Chrisina, editor, Tefas, Anastasios, editor, and Pimenidis, Elias, editor

Published
2022
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19. Virtual Flow Meter for an Industrial Process

Author

González-Herbón, Raúl, primary, González-Mateos, Guzmán, additional, Alonso, Serafín, additional, Prada, Miguel A., additional, Fuertes, Juan J., additional, Morán, Antonio, additional, and Domínguez, Manuel, additional

Published
2023
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22. Influence of Adding Conductive Materials and Integrating Bio Electrochemical Systems on the Efficiency of Anaerobic Digestion.

Author

Mur-Gorgas, Alberto, García-Triviño, Antonio V., Mateos, Raúl, Escapa, Adrián, and Morán, Antonio

Subjects
SEWAGE purification, SEWAGE sludge, CHARGE exchange, CARBON-black, RENEWABLE energy sources, POLYLACTIC acid, BIOGAS production
Abstract

This study explores the impact of incorporating conductive materials and bioelectrochemical systems (BES) on the efficiency of anaerobic digestion (AD) of sewage sludge. The research consists of two phases: biodegradability tests using 3D-printed polylactic acid-based conductive fillers (PLA/Carbon Black and PLA/Graphene) and semi-continuous assays integrating an external BES into the AD process. Results from biodegradability tests indicate that conductive fillers enhance around 50% methane production during the start-up phase, with microbial communities adapting over time to reduce variability in methane yields. Moreover, as the experiment progressed, the methane yields of the digesters with and without fillers became equal. Semi-continuous experiments demonstrate that BES integration improves process stability and methane production by achieving a 5–10% improvement in the amount of methane in the biogas throughout the entire operation, even under high organic loads, by facilitating diverse electron transfer pathways. The challenges of BES operation highlight the need for optimized designs to ensure scalability. Microbial analyses reveal that BES application shifts methanogenic pathways, favouring acetoclastic methanogenesis. Overall, the findings underscore the potential of conductive materials and BES to improve biogas quality and production, contributing to sustainable wastewater management and renewable energy generation. [ABSTRACT FROM AUTHOR]

Published
2025
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28. Chronic Pain Estimation Through Deep Facial Descriptors Analysis

Author

Mauricio, Antoni, Peña, Jonathan, Dianderas, Erwin, Mauricio, Leonidas, Díaz, Jose, Morán, Antonio, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Founding Editor, Lossio-Ventura, Juan Antonio, editor, Condori-Fernandez, Nelly, editor, and Valverde-Rebaza, Jorge Carlos, editor

Published
2020
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29. Analysis of the Thermal Distribution Generated by a Thermal Patch to Evaluate Its Feasibility to Treat Patient’s Pain Relief

Author

Castellanos-Rivera, Luis A., Mandujano-García, Edgar A., Ruiz-Morán, Antonio, Barrón-Salazar, Melany, Morales-Ruiz, Benjamín A., Trujillo-Romero, Citlalli J., Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, González Díaz, César A., editor, Chapa González, Christian, editor, Laciar Leber, Eric, editor, Vélez, Hugo A., editor, Puente, Norma P., editor, Flores, Dora-Luz, editor, Andrade, Adriano O., editor, Galván, Héctor A., editor, Martínez, Fabiola, editor, García, Renato, editor, Trujillo, Citlalli J., editor, and Mejía, Aldo R., editor

Published
2020
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34. Virtual Sensor Based on a Deep Learning Approach for Estimating Efficiency in Chillers

Author

Alonso, Serafín, Morán, Antonio, Pérez, Daniel, Reguera, Perfecto, Díaz, Ignacio, Domínguez, Manuel, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Macintyre, John, editor, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, and Jayne, Chrisina, editor

Published
2019
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35. Comparison of Network Intrusion Detection Performance Using Feature Representation

Author

Pérez, Daniel, Alonso, Serafín, Morán, Antonio, Prada, Miguel A., Fuertes, Juan José, Domínguez, Manuel, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Macintyre, John, editor, Iliadis, Lazaros, editor, Maglogiannis, Ilias, editor, and Jayne, Chrisina, editor

Published
2019
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39. Analysis of Parallel Process in HVAC Systems Using Deep Autoencoders

Author

Morán, Antonio, Alonso, Serafín, Prada, Miguel A., Fuertes, Juan J., Díaz, Ignacio, Domínguez, Manuel, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Boracchi, Giacomo, editor, Iliadis, Lazaros, editor, Jayne, Chrisina, editor, and Likas, Aristidis, editor

Published
2017
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45. Gap imputation in related multivariate time series through recurrent neural network-based denoising autoencoder.

Author

Alonso, Serafín, Morán, Antonio, Pérez, Daniel, Prada, Miguel A., Fuertes, Juan J., and Domínguez, Manuel

Subjects
*RECURRENT neural networks, *TIME series analysis, *MISSING data (Statistics)
Abstract

Technological advances in industry have made it possible to install many connected sensors, generating a great amount of observations at high rate. The advent of Industry 4.0 requires analysis capabilities of heterogeneous data in form of related multivariate time series. However, missing data can degrade processing and lead to bias and misunderstandings or even wrong decision-making. In this paper, a recurrent neural network-based denoising autoencoder is proposed for gap imputation in related multivariate time series, i.e., series that exhibit spatio-temporal correlations. The denoising autoencoder (DAE) is able to reproduce input missing data by learning to remove intentionally added gaps, while the recurrent neural network (RNN) captures temporal patterns and relationships among variables. For that reason, different unidirectional (simple RNN, GRU, LSTM) and bidirectional (BiSRNN, BiGRU, BiLSTM) architectures are compared with each other and to state-of-the-art methods using three different datasets in the experiments. The implementation with BiGRU layers outperforms the others, effectively filling gaps with a low reconstruction error. The use of this approach is appropriate for complex scenarios where several variables contain long gaps. However, extreme scenarios with very short gaps in one variable or no available data should be avoided. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Experiencias en la organización de un taller práctico usando Raspberry Pi para fomentar el interés entre los alumnos en la materia de Ingeniería de Computadores

Author

Escudero-Sahuquillo, Jesús, Martínez Iniesta, Miguel, Sánchez, José Luis, García, Pedro J., Alfaro, Francisco J., Quiles, Francisco J., Garrido-Hidalgo, Celia, Roda-Sanchez, Luis, Morán, Antonio, Olmedilla, Cristina, Gómez, Gabriel, Sánchez de la Rosa, Miguel, Escudero-Sahuquillo, Jesús, Martínez Iniesta, Miguel, Sánchez, José Luis, García, Pedro J., Alfaro, Francisco J., Quiles, Francisco J., Garrido-Hidalgo, Celia, Roda-Sanchez, Luis, Morán, Antonio, Olmedilla, Cristina, Gómez, Gabriel, and Sánchez de la Rosa, Miguel

Abstract

El grado en Ingeniería Informática de nuestra Escuela oferta cuatro perfiles de intensificación, entre los que se incluye Ingeniería de Computadores (IC). En el año 2015 el número de alumnos matriculados en las asignaturas de esta tecnología rondaba los 5 estudiantes, muy lejos de los 25 que establece la dirección de la Escuela. Con el objetivo de despertar el interés en los alumnos por las asignaturas de la tecnología de IC, algunos profesores que imparten docencia en estas y otras asignaturas relacionadas propusieron la organización de un taller práctico fuera de las horas lectivas. El objetivo principal del taller es la introducción a los contenidos de la materia de ingeniería de computadores utilizando como herramienta el ordenador mono-placa Raspberry Pi, que ha despertado un gran interés en la docencia en la última década, gracias a su bajo coste y facilidad de adquisición. Como se refleja en este artículo, después de cinco ediciones (y con la sexta en marcha en el momento del envío de este artículo), el número de alumnos matriculados en las asignaturas de la tecnología de IC ha aumentado significativamente, y el taller propuesto ha contribuido objetivamente a ello., The Computer Science degree in our Faculty offers four specialization profiles, including Computer Engineering (CE). In 2015, the number of students enrolled in subjects related to CE was around 5, far from the maximum of 25 established in the degree normative. To awaken students’ interest in CE subjects, some professors proposed the organization of a practical workshop, outside of lecture hours. The proposed workshop focuses on using single board computers (SBC), specifically on the Raspberry Pi ecosystem, which has aroused great interest in teaching in the last decade, thanks to its low cost and ease of acquisition. This article reflects that, after five editions and with the 6th edition underway at the time of sending this article, the number of students enrolled in the CE specialization subjects has increased significantly, and the proposed workshop has objectively contributed to this.

Published
2023

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