Buele, Jorge
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Buele, Jorge
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Ambato
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jorgebuele@uti.edu.ec
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57200380202

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Sustainable Development in Higher Education Curricula for Software Engineering Chairs

2023 , León Toro, Jenny Marcela , Buele, Jorge , Camino-Morejón V.M. , Ayala-Chauvin, Manuel Ignacio

Nowadays, society demands that high quality teaching practices must be part of the curriculum in higher education institutions. The interdisciplinarity view of the contents taught has made the technical aspects of engineering merge with social, cultural, and economic nuances. In this sense, the new generations of students show their interest in learning and carrying out activities that contribute to sustainability, for this reason, the inclusion of ecological themes in the subjects of computer science and software career is required. A bibliographical analysis was carried out that allowed recognition of main concepts and methodologies applied to the subject. As a result of them, an adjustment of chairs is presented allowing integrating conventional teaching with the new trends of green technology. Reforms were implemented from introductory courses to theoretical knowledge of green software, to the development of web applications with the same approach. In the same way, it involves the management of computer projects, modeling, monitoring, and optimization of resources, and green evaluation. According to the socio-educational model, the articulation between technology and sustainability will allow managing software projects that provide real solutions to problems in context. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Electric Monitoring System for Residential Customers Using Wireless Technology

2022 , Buele, Jorge , Morales-Sánchez J.C. , Varela Aldas, José , Palacios-Navarro G. , Ayala-Chauvin, Manuel Ignacio

Power grids continue to develop and it is increasingly difficult to guarantee the quality of service offered to the user. In several developing countries, consumption is calculated on the basis of visual inspection, which is prone to errors. Consequently, this document outlines the construction of electrical consumption telemetering equipment. This is designed to reduce human error through manual measures and have a web backup that can be accessed from anywhere. To develop the prototype voltage and current sensors are used, and the signal is conditioned for the control stage. The processing unit is the Arduino Mega embedded board, which incorporates a GPRS Shield (General Packet Radio Services) that handles communication with a LAMP server (Linux, Apache, MySQL, PHP) connected to the Internet. It also incorporates a block of connection and disconnection of the electrical service that would leave the whole house without service. Two functionalities are used to present the data, one is local on the LCD display of the equipment installed in the home (user) and the second is remote access to a website (server). The results show that in comparison with a standard voltage device it presents an error of 0.28% and 4.12% in current. In this way, the use of this prototype for real-time monitoring of electricity consumption is validated, since it works similarly to a conventional one. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Low-Cost Energy Consumption Monitoring System Using NodeMCU

2022 , Ayala-Chauvin, Manuel Ignacio , Acurio-Pérez J.A. , Sanmartí G.R. , Buele, Jorge

Energy consumption in urban areas has experienced unprecedented growth. This shows the need to know the consumption in real-time to make efficient use. Therefore, this paper describes the development of a low-cost prototype for the acquisition of energy consumption data. A simple design has been proposed, using electronic components readily available in the local market. Measurements are made with an SCT013 electrical sensor placed around a conductor in the distribution box. The NodeMCU development board is a processing unit connecting several devices through data buses and WiFi. The script programming was done in c++ language using the Arduino IDE, while the mobile application for visualization was developed in Blynk. As a case study, real-time measurements and tests were carried out in a higher education center. A standard ammeter and multimeter were used for system calibration to ensure reliable and accurate results. During the experimental tests, an error of 2,839% was obtained compared to commercial equipment, which validates the use of this proposal. Linear regression is performed to propose an approximation model based on monthly consumption data for one year. With this average measurement, abnormal variations in monthly consumption can be identified, which could mean an electrical failure in the building. This type of proposal allows for better decision-making, proposes structural improvements, and is a basis for developing smarter cities. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Exploring the Landscape of Data Analysis: A Review of Its Application and Impact in Ecuador

2023 , Ayala-Chauvin, Manuel Ignacio , Avilés-Castillo F. , Buele, Jorge

Latin America has shown increased big data adoption since 2012; Ecuador is now entering this transformative field. Science and engineering in Ecuador have benefited most from data analysis, with untapped potential in health and services sectors. Big data is shaping sectors in Ecuador, including disaster prediction, agriculture, smart city development, and electoral data analysis. Despite public sector inefficiencies, residential ICT adoption provides opportunities for Ecuador’s smart city advancements. Despite some data underutilization, big data’s transformative potential is evident in Ecuador’s healthcare and education advancements. Highlights: Data analysis is increasingly critical in aiding decision-making within public and private institutions. This paper scrutinizes the status quo of big data and data analysis and its applications within Ecuador, focusing on its societal, educational, and industrial impact. A detailed literature review was conducted from academic databases such as SpringerLink, Scopus, IEEE Xplore, Web of Science, and ACM, incorporating research from inception until May 2023. The search process adhered to the PRISMA statement, employing specific inclusion and exclusion criteria. The analysis revealed that data implementation in Ecuador, while recent, has found noteworthy applications in six principal areas, classified using ISCED: education, science, engineering, health, social, and services. In the scientific and engineering sectors, big data has notably contributed to disaster mitigation and optimizing resource allocation in smart cities. Its application in the social sector has fortified cybersecurity and election data integrity, while in services, it has enhanced residential ICT adoption and urban planning. Health sector applications are emerging, particularly in disease prediction and patient monitoring. Educational applications predominantly involve student performance analysis and curricular evaluation. This review emphasizes that while big data’s potential is being gradually realized in Ecuador, further research, data security measures, and institutional interoperability are required to fully leverage its benefits. © 2023 by the authors.

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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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Static reactive power compensator design, based on three-phase voltage converter

2021 , Ayala-Chauvin, Manuel Ignacio , Kavrakov B.S. , Buele, Jorge , Varela Aldas, José

At present, electrical network stability is of the utmost importance because of the increase in electric demand and the integration of distributed generation deriving from renewable energy. In this paper, we proposed a static reactive power compensator model with common direct current voltage sources. Converter parameters were calculated and designed to fulfill specifications. In order to ascertain the device response for different operating modes as reactive power consumer and generator, we developed the model’s power and control circuits in Matlab Simulink. Simulations were performed for different conditions, and as a result, the current and voltage waveforms and the circular power chart were obtained. This paper has theoretically proven it is possible to achieve the consumption or generation of purely active or reactive power by implementing a static reactive power compensator with common DC voltage sources. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Augmented Reality Application with Multimedia Content to Support Primary Education

2023 , Buele, Jorge , Espinoza J. , Ruales, María Belén , Camino-Morejón V.M. , Ayala-Chauvin, Manuel Ignacio

Education is continually reinventing itself to meet the growing needs of learners. In the context of an emergency, confinement and mobilization difficulties have necessitated the adoption of online education. This new offer brings technological means to conventional processes, but its main disadvantage is the limited access in some places. This has motivated the present study, which proposes the development of a mobile application using augmented reality (AR) to complement primary education. This application aims to disseminate multimedia content without needing a stable internet connection. A high-performance computer is required for the design and a mid-range smartphone for its execution. Four scripts are generated in c# programming language using Visual Studio. The environment and the three-dimensional objects are developed using Unity software and the packages ARFoundation, Unity MARS, and Vuforia. Two groups of 13 children each participated in the experimental testing. The experimental group used the application for two weeks to complement the virtual classes in the subjects of language, natural sciences, and mathematics. The analysis with SPSS software shows a statistically significant increase in the average grades compared to the control group. This research shows that the use of technology can contribute to improving the current teaching-learning processes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Big Data as a Tool for Analyzing Academic Performance in Education

2024 , Ayala-Chauvin, Manuel Ignacio , Chucuri-Real B. , ESCUDERO VILLA, PEDRO FERNANDO , Buele, Jorge

Educational processes are constantly evolving and need upgrading according to the needs of the students. Every day an immense amount of data is generated that could be used to understand children’s behavior. This research proposes using three machine learning algorithms to evaluate academic performance. After debugging and organizing the information, the respective analysis is carried out. Data from eight academic cycles (2014–2021) of an elementary school are used to train the models. The algorithms used were Random Trees, Logistic Regression, and Support Vector Machines, with an accuracy of 93.48%, 96.86%, and 97.1%, respectively. This last algorithm was used to predict the grades of a new group of students, highlighting that most students will have acceptable grades and none with a grade lower than 7/10. Thus, it can be corroborated that the daily stored data of an elementary school is sufficient to predict the academic performance of its students using computational algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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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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Socio-spatial Segregation Using Computational Algorithms: Case Study in Ambato, Ecuador

2023 , Ayala-Chauvin, Manuel Ignacio , Maigua P. , Medina-Enríquez A. , Buele, Jorge

Access to basic services, housing, and social security influence people’s quality of life. Within the cities, it is common for there to be specific sectors where the presence of those groups that have an abundance of resources predominates. The same occurs with the opposite group, motivated by various social and economic conditions. For this reason, this study explicitly considers the population of Ambato, Ecuador, to evaluate the existence of socio-spatial segregation. The data are obtained from the latest census base of 2010, which is publicly accessible by the Institute of Statistics and Census. The socioeconomic characterization of the population consists of the calculation of the condition index. A programming algorithm developed in the statistical software RStudio has been used to process the information. With the calculations obtained, we proceeded to generate geographic maps where the location of the different social groups could be seen. The results show that the values 0.77 and 0.90 predominate in the city’s west. Also, we identify that only the fourth quartile achieves well-being and an abundance of resources, while those in the first quartile are well below the average. The information describes a very low and positive spatial autocorrelation, where most of the population is concentrated in the city’s southwest. Thus, this proposal, which combines computational algorithms for the exposition of social and spatial characteristics of a specific population, is validated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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