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47 results on '"Fabregas, Ernesto"'

3. Comparative Analysis of Deep Learning Methods for Fault Avoidance and Predicting Demand in Electrical Distribution.

Author

Schröder, Karla, Farias, Gonzalo, Dormido-Canto, Sebastián, and Fabregas, Ernesto

Subjects
TRANSFORMER models, POWER transformers, ELECTRICITY markets, QUALITY of service, CURRENT transformers (Instrument transformer), DEEP learning
Abstract

In recent years, the distribution network in Chile has undergone various modifications to meet new demands and integrate new technologies. However, these improvements often do not last as long as expected due to inaccurate forecasting, resulting in frequent equipment changes and service interruptions. These issues affect project investment, unsold energy, and penalties for poor quality of supply. Understanding the electricity market, especially in distribution, is crucial and requires linking technical quality standards with service quality factors, such as the frequency and duration of interruptions, to understand their impact on regulated distribution to customers. In this context, a comparative study will be carried out between Long Short-Term Memory (LSTM) and transformer architectures, with the aim of improving the sizing of distribution transformers and preventing failures when determining the nominal power of the transformer to be installed. Variables such as voltages and operating currents of transformers installed between 2020 and 2021 in the Valparaíso region, Chile, along with the type and number of connected customers, maximum and minimum temperatures of the sectors of interest, and seasonality considerations will be used. The compilation of previous studies and the identification of key variables will help to propose solutions based on error percentages to optimise the accuracy of transformer sizing. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations.

Author

Acevedo, Jaime, Garcia, Gonzalo, Ramirez, Ricardo, Fabregas, Ernesto, Hermosilla, Gabriel, Dormido-Canto, Sebastián, and Farias, Gonzalo

Subjects
DEEP learning, MACHINE learning, SOUND recordings, ORAL communication, INDUSTRIAL workers, QUALITY control
Abstract

The quality of verbal communication, understood as the absence of uncertainty in the message transmitted, is a key factor in mission-critical processes. Several processes are handled by direct voice communication between these endpoints and any miscommunication could have an impact in success of the task. For that reason, the quality control of verbal communication is required to ensure that the instructions issued are effectively understood and adequately executed. In this context, it is expected that instructions from the command center are issued once, and that the acknowledgment from the field are minimal. In the present work, the communication between an electrical company control center and factory workers in the field was chosen for analysis. We developed two complementary approaches by using machine learning and deep learning algorithms to assess, in an automatic way, the quality of information transmission in the voice communications. Preliminary results demonstrate that the automatic uncertainty detection is feasible, despite the small number of samples available at the present time. To support further studies, a repository was created in GitHub with the spectrogram and the tokenized words of all audios. [ABSTRACT FROM AUTHOR]

Published
2024
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9. Development and Control of a Real Spherical Robot

Author

Schröder, Karla, primary, Garcia, Gonzalo, additional, Chacón, Roberto, additional, Montenegro, Guelis, additional, Marroquín, Alberto, additional, Farias, Gonzalo, additional, Dormido-Canto, Sebastián, additional, and Fabregas, Ernesto, additional

Published
2023
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24. Fall Detection using Human Skeleton Features

Author

Ramirez, Heilym, Velastin Carroza, Sergio Alejandro, Fabregas, Ernesto, Meza, Ignacio, Makris, Dimitrios, and Farias, Gonzalo

Subjects
Human skeleton, Informática, Fall detection, Computer vision, computer, Pose estimation
Abstract

Procedings in: 11th International Conference on Pattern Recognition Systems (ICPRS-21), conference paper, 17-19 mar, 2021, Universidad de Talca, Curicó, Chile. Falls is one of the leading causes of death and serious injury in people, especially the elderly. In addition, the falls accidents have a direct financial cost for health systems and, indirectly, for the productivity of society. Among the most important problems in fall detection systems is privacy, limitations of operating devices, and the comparison of machine learn-ing techniques for detection. This article presents a fall detection system by means of a k-Nearest Neighbor (KNN) classifier based on camera-vision using pose detection of the human skeleton for the features extraction. The proposed method is evaluated with UP-FALL dataset, surpassing on the results of other fall detection systems that use the same database. This method achieves a 98.84% accuracy andF1-Score of 97.41%. This work was supported by the Chilean Research and Development Agency (ANID) under the Project FONDECYT 1191188.

Published
2021

30. Comparative Study of Traditional, Simulated and Real Online Remote Laboratory: Student's Perceptions in Technical Training of Electronics.

Author

Taj, Amine Moulay, Fabregas, Ernesto, Abouhilal, Abdelmoula, Taifi, Naima, and Malaoui, Abdessamad

Subjects
STUDENT attitudes, EDUCATIONAL innovations, TELECOMMUNICATION systems, COMPARATIVE studies
Abstract

The developments in technology and communication networks have enabled the possibility of establishing virtual and remote labs, providing new opportunities for students on campus and at a distance overcoming some of the limitations of hands-on labs. The impact of innovations on students' performance can be analyzed statistically by looking at specific skills or indicators, respectively. This paper addresses the lack of empirical evidence supporting electronics education innovations in three practical teaching methods, namely, hands-on, simulation, and online remote real labs. The paper reports on the application of a methodology that takes into account the interaction between students and teachers at different levels of abstraction to evaluate a DC motor laboratory practice, on 150 students at the Polydisciplinary Faculty of Beni Mellal in Morocco. In this work the students' attitudes towards a specific practical method depend on its usefulness, usability, motivation and quality of understanding; these parameters were measured using a questionnaire that considers the relationship between the student, the teacher and the practical work environment. The data collected in each type of experiment environment were was tabulated and analyzed by statistical methods. The results validate the students' satisfaction towards the environments of practical works and identify some aspects that need to be improved in future works. [ABSTRACT FROM AUTHOR]

Published
2021
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42. Platform for Teaching Mobile Robotics

Author

Fabregas, Ernesto, primary, Farias, Gonzalo, additional, Dormido-Canto, Sebastián, additional, Guinaldo, María, additional, Sánchez, José, additional, and Dormido Bencomo, Sebastián, additional

Published
2015
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