Ayala-Chauvin, Manuel Ignacio
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Ayala-Chauvin, Manuel Ignacio
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Ambato
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mayala@uti.edu.ec
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57215428914

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Predicting Academic Performance in Mathematics Using Machine Learning Algorithms

2022 , Espinosa Pinos, Carlos Alberto , Ayala-Chauvin, Manuel Ignacio , Buele, Jorge

Several factors, directly and indirectly, influence students’ performance in their various activities. Children and adolescents in the education process generate enormous data that could be analyzed to promote changes in current educational models. Therefore, this study proposes using machine learning algorithms to evaluate the variables influencing mathematics achievement. Three models were developed to identify behavioral patterns such as passing or failing achievement. On the one hand, numerical variables such as grades in exams of other subjects or entrance to higher education and categorical variables such as institution financing, student’s ethnicity, and gender, among others, are analyzed. The methodology applied was based on CRISP-DM, starting with the debugging of the database with the support of the Python library, Sklearn. The algorithms used are Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF), the last one being the best, with 92% accuracy, 98% recall, and 97% recovery. As mentioned above, the attributes that best contribute to the model are the entrance exam score for higher education, grade exam, and achievement scores in linguistic, scientific, and social studies domains. This confirms the existence of data that help to develop models that can be used to improve curricula and regional education regulations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Automation of an Electro-Hydraulic Test Bench Using a Weitek CMT3092 HMI- PLC

2022 , Altamirano-Haro D. , Sánchez-Díaz P.E. , Buele, Jorge , Ayala-Chauvin, Manuel Ignacio

The industrial environment demands mean that future professionals must acquire more and more technical skills. However, this represents a high investment that many higher education institutions cannot afford. Therefore, the laboratory equipment is updated, and this study begins with the automation of an electro-hydraulic test bench that was manual. For this, a PLC - Weintek was selected, whose programming was carried out in ladder language using CODESYS as a development platform, using an open Modbus programming code through the SFD block language. A human-machine interface (HMI) on a touch screen in the system allows user input (with various hierarchies) and operations control. The operator can also store data for later analysis. Finally, the validation of this proposal is carried out with the respective experimental tests, obtaining a significant reduction in the execution time of the three proposed tasks and improvement of learning conditions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Design and Construction of a Low Cost CNC Milling Machine for Woodworking

2021 , Ayala-Chauvin, Manuel Ignacio , Saá F. , Rodríguez R. , Domènech-Mestres C. , Riba-Sanmartí G.

Computer Numeric Control (CNC) machinery were created to reduce manufacturing times for industry, but this type of machinery is costly and therefore only a few uses can recover the investment. However, the progress of electronics in the last decades has allowed to develop affordable CNC machines. This article explains the design and manufacturing process of a low budget CNC milling machine for woodworking. All the structural elements were designed and simulated using PTC CREO, as well as the manufacturing sequence. The control hardware uses commercially available electronics such as Arduino ONE, and stepper motors to move the machine, while the software uses the free open source codes Vetrica Aspire and Universal G Code. The machine was tested on different materials, obtaining good results. The result is a CNC milling machine for woodworking that costs about 50% the price of an equivalent commercial machine, an can therefore be a suitable solution for craft industries. © 2021, Springer Nature Switzerland AG.

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Preface

2022 , Ayala-Chauvin, Manuel Ignacio , Botto-Tobar M. , Cadena Á.D. , León S.M.

[No abstract available]

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Control System Test Platform for a DC Motor

2022 , Saá-Tapia F. , Mayorga-Miranda L. , Ayala-Chauvin, Manuel Ignacio , Domènech-Mestres C.

Currently, control systems are used to improve the behavior of actuators that are part of an equipment or process. However, to enhance their performance, it is necessary to perform tests to evaluate the responses of its operation depending on the type of controller. In this sense, a test platform was developed to compare and optimize the speed control of a DC motor with three types of controllers: Predictive Model Control (MPC), Proportional Integral Derivative (PID) and Fuzzy Logic. Data acquisition was performed using the Arduino MEGA board and LabVIEW software. The mathematical model of the three controllers was developed, taking into account the electrical and physical properties of the DC motor. Through MATLAB IDENT, the state space (SS) and transfer function F(S) equations were generated for the MPC and PID controller, respectively; on the other hand, input/output ranges for the Fuzzy Logic controller were input/output ranges defined by assigning belonging functions and linguistic variables. Experimental tests were carried out with these models under no-load and load. Tests performed in vacuum show that performance index with the motor at 100 rpm results in a PID of 0.2245, a Fuzzy Logic of 0.3212 and an MPC of 0.3576. On the other hand, with load at 100 rpm, a PID of 0.2343, a Fuzzy Logic of 0.3871 and an MPC of 0.3104 were obtained. It was determined that the Fuzzy Logic controller presents a higher over impulse; the PID and MPC have a faster stabilization time and with negligible over impulses. Finally, the MPC controller presents a better performance index analysis according to the Integral Square Error criterion (ISE). © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Radar system for the reconstruction of 3D Objects: A preliminary study

2020 , Barberán, J. , Moreta, D. , Ayala-Chauvin, Manuel Ignacio , Obregón, J. , Domínguez, R. , Buele, J.L. , Obregón G.

Objects recognition and their reconstruction is a process that involves a significant economic investment. This manuscript presents the basis for the design of a system that detects objects, extracts its main characteristics and digitally reconstructs them in three dimensions considering a reduced economic investment. The popular technological tool Kinect on its version 2.0 and MATLAB software have been linked to develop an efficient algorithm. Next, the process to obtain this prototype is briefly described, as well as the results from the corresponding experimental tests. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

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System for Monitoring and Controlling Industrial Lighting with Amazon Alexa

2021 , Ayala-Chauvin, Manuel Ignacio , Saá F. , Villarroel-Córdova F. , de la Fuente-Morato A.

Intelligent devices, used along with sensors, are becoming more commonplace in industrial contexts. One such device, Amazon Echo (which runs Amazon Alexa), can be used to interact with other industrial systems via voice commands. Taking advantage of this, a skill to control the illumination system of a company has been developed, while also being able to measure power consumption in real time. Besides Echo, the system employs easily obtainable electronic components such as NodeMCU4 and Sonoff Pow, while running open-source software like IDE Arduino and Amazon Developer. Besides the voice commands, the system can be controlled via a cell phone touch app and a manual system. Tests show the skill successfully controls the illumination system and provides accurate power consumption data in real time. This skill can also be replicated in other industrial contexts. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Evaluation of the energy autonomy of urban areas as an instrument to promote the energy transition

2022 , Ayala-Chauvin, Manuel Ignacio , Riba Sanmartí G. , Riba C. , Lara P.

The management of energy systems with a high share of renewables is a challenge for grid planners and operators, as weather and energy demand do not always coincide. Investigating the energy autonomy of cities and their local energy resources can help to overcome this challenge. To this end, real energy demand data from the city of Loja, Ecuador, and wind energy generation from a nearby wind farm were compared. This showed that wind energy provides 53% of the city’s demand. It is exposed that despite the excess energy, the wind farm’s ability to supply the city with electricity is limited to about 74% when the wind farm is expanded to twice its rated capacity. The results show that in order to improve the autonomy, other energy sources, such as photovoltaic, as well as useful size energy storage are needed. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

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Enhancing Sustainability through Accessible Health Platforms: A Scoping Review

2023 , Ramírez-Saltos D. , Acosta-Vargas P. , Acosta-Vargas G. , Santórum M. , Carrion-Toro M. , Ayala-Chauvin, Manuel Ignacio , Ortiz-Prado E. , Maldonado-Garcés V. , González-Rodríguez M.

The digital transformation of healthcare platforms has ushered in a new era of accessibility, making health information and services widely available. This comprehensive scoping review delves into the accessibility landscape of health platforms by analyzing 29 carefully selected research articles. These studies employ automated tools and manual evaluations to evaluate platform accessibility comprehensively. This study revealed that (52%) of these articles are based on automated methods, while 34% combine automated and manual approaches. Most studies show compliance with the latest versions of the Web Content Accessibility Guidelines (WCAG), with a significant focus (70%) on compliance with level A. This study reveals recurring issues within the perceivable operable, understandable, and robust categories, underscoring the pressing need for strict the accessibility testing of health platforms. This study demonstrates substantial agreement between raters, reinforced by a Cohen’s kappa coefficient of 0.613, indicating their reliability in classifying the articles. Future efforts should persist in refining accessibility standards, advocating for compliance with the WCAG, exploring innovative methods to assess the accessibility of healthcare platforms, and conducting user-centered research. This review highlights the paramount importance of ensuring equitable access to health information and services for people, regardless of their abilities or conditions, which resonates significantly with the issue of sustainability in healthcare and its socioeconomic and environmental implications. © 2023 by the authors.

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Prevention of Failures in the Footwear Production Process by Applying Machine Learning

2022 , Tierra-Arévalo M. , Ayala-Chauvin, Manuel Ignacio , Nacevilla C. , de la Fuente-Morato A.

At present, the handcrafted footwear sector is affected by the high competitiveness due to the increasing automation of companies. In this sense, in order to improve its competitiveness, a system was proposed to predict the failures of a production system and to carry out preventive maintenance actions. Samples were taken from 25 productions and 7 activities were established: cutting, stitching, pre fabrication, final preparation, gluing, assembly and finishing. The company produces batches of 90 pairs per day, with a standard time of 274.53 min and a promised productivity of 1.8. A support vector machine model was developed to predict the possible failures of the process taking as a reference the standard time of each stage. Finally, the results allow predicting the faults to optimise the production process by applying Support Vector Machine (SVM). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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