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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Anthropization and growth of the electricity grid as variables for the analysis of urban infrastructure

2020 , Ayala-Chauvin, Manuel Ignacio , Huaraca D. , Varela Aldas, José , Ordóñez A. , Riba G.

City growth goes together with the development of infrastructure, and the power network is one of the most relevant towards economic development. The study of urban infrastructure through the analysis of anthropization coupled with power network growth can produce a tool that supports sustainable infrastructure planning, both economic and environmental. The case study focuses on Ambato, Ecuador, in the period from 1950 to 2019, and assesses quantitatively the changes in the city layout and the evolution of its power network. The data are adjusted to a sigmoid-type objective function through a non-linear least squares problem, that is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. Anthropization data show how the urban area grew during the study period: 37% (1950-1960), 53% (1960-1970), 80% (1970-1980), 35% (1980-1990), 39% (1990-2000), 38% (2000-2010), and 11% (2010-2019), mostly at the expense of agricultural land. The forecast for new power network users by 2050 yields a result of 203,630 total users with a population density of 4850 people/km2. The conclusion is that this type of analysis can help city planners and decision makers further understand city and infrastructure growth dynamics and produce policies that bolster sustainable city growth. © 2020 by the authors.

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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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Underwater Power Generator Based on Gravity Vortex Siphon Boost Energy Transition

2021 , Ayala-Chauvin, Manuel Ignacio , Benavides H. , Riba G. , Blanco E.

The need for an energy transition is nowadays undeniable. Climate change, fossil fuel depletion and economic vulnerability are some of the main drivers of the model change. Therefore, it is necessary to promote local energy generation in order to improve a renewable energy transition. This paper presents the design, installation and performance of an Underwater Turbine Generator prototype with a gravitational vortex and siphon. The development of the prototype was done in five stages: contextualization, specifications, conceptualization, detail design and manufacturing. The result of this research is an appropriate, compact and low-cost prototype with a power range of 2 to 10 kW and head of 0.8 to 3 m. According to field measurements, the efficiency of a 7.5 kW generator for heads differences larger than 0.8 m is 37%. This type of design can be reproduced in another context in order to promote the decentralized generation and sustainable growth between the territory and its resources. © 2021, International Centre for Sustainable Development of Energy, Water and Environment Systems SDEWES. All rights reserved.

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Evolution, Collaborations, and Impacts of Big Data Research in Ecuador: Bibliometric Analysis

2024 , Avilés-Castillo, Fátima , Ayala-Chauvin, Manuel Ignacio , Buele J.

Big Data has been gaining significant attention globally due to its potential to drive innovation, guide decision-making, and stimulate economic growth. As part of this global trend, Ecuador has also witnessed a surge in Big Data-related research over the past decade. This study comprehensively analyzes Big Data research evolution, collaborations, and impacts in Ecuador from 2012 to 2023. By examining the patterns of publication, researcher demographics, primary languages, significant publishers, most cited research papers, patterns of author collaboration, and prevalent keywords, we strive to construct a detailed portrayal of the Big Data research landscape in the country. Our investigation reveals a noticeable increase in Big Data research activity post-2015, particularly within major cities like Quito and Guayaquil. Notably, the study also underscores the predominance of English in research publications, with leading publishers such as IEEE and Springer playing significant roles. The diverse themes of the most cited articles illustrate the wide-ranging applications of Big Data research within the country. © 2024, 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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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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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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Lifecycle assessment of electricity generation transition in ecuador

2021 , Ayala-Chauvin, Manuel Ignacio , Samaniego-Ojeda C. , Riba G. , Maldonado-Correa J.

Ecuador’s energy mix has greatly reduced its dependency on fossil fuels the last 15 years, down to a marginal role (5%) in electricity generation in 2017. The development plan for the Ecuadorian power network aims to keep adding hydropower to meet the increasing demand. A prospective lifecycle assessment (LCA) of the future power network (2012–2050) can determine the feasibility of the development plan and its environmental sustainability in the long run. For a quantitative analysis of the energy transition over the entire lifecycle, the simulation software® Global Emission Model of Integrated System (GEMIS) is used. The results show that the current development path of the Ecuadorian energy system reduces the emissions of CO2 per kWh generated by 65% due to the large share of renewable energies, mainly hydropower, which costs 1% of Gross Domestic Product. The obtained LCA footprints are similar to the literature benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

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Data Analysis for Performance Improvement of University Students Using IoT

2024 , Ayala-Chauvin, Manuel Ignacio , Lara-Álvarez P. , Castro R.

Using Internet of Things (IoT) devices and data analysis techniques can potentially transform how universities approach improving student achievement. In this sense, the project is based on implementing a remotely operated pneumatic bank applying IoT for university education. With this technology, it is possible to obtain information about the factors that impact student achievement and design targeted interventions to help students improve their performance. The control system with low-cost technology was developed with Raspberry Pi, AnyDesk, and Canvas LMS for the remote connection. The experiment was carried out with two groups of 7 people, and it was identified that there are correlations of 0.87 and 0.62 between the performance of the students and the time they dedicate to studying and the hours they spend on the platform; this suggests a positive correlation between these variables. Therefore, as students spend more time studying and spending more hours on the platform, they are more likely to achieve better academic results. On the other hand, the study time of the group of students who used the bank remotely increased by 32% compared to those who used the bank in person; therefore, we can infer that with the implementation of the IoT, the use of the system is encouraged. Finally, based on the insights gained from the analysis, targeted interventions can be designed to help students improve their academic performance. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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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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