Buele, Jorge
Thumbnail Image
Preferred name
Buele, Jorge
Main Affiliation
Ambato
Email
jorgebuele@uti.edu.ec
ORCID
Scopus Author ID
57200380202

Research Output

Filters

84
Reset filters

Settings
Now showing 1 - 10 of 84
No Thumbnail Available
Publication

Monitoring System for Physical Water Quality Parameters and Automatic Control for Chlorine Dosing in a Aerator Treatment Plant

2021 , Balarezo J.C. , Buele, Jorge , Naranjo-Avalos H. , Castillo F. , Vargas W.G. , Salazar F.W.

This work proposes the development and creation of an automatic monitoring and control system for the dosage of chlorine in the water treatment plant, purifying the vital liquid and avoiding the distribution and consumption of water contaminated by microorganisms. This is achieved by monitoring the physical parameters through the data sent by wireless sensors, acquiring them in a database, sending the data in real time to a web server, where they can be visible to the public, and generating automatic control in Based on the data obtained, this occurs in a water treatment pools. For this, a Raspberry Pi board is used, it acts as a data store, two Arduino Mega, acting as control nodes, a LAN server, and a PID control for the automatic control of chlorine dosage, thus achieving precautionary that the water is disinfected from any microorganism present. © Published under licence by IOP Publishing Ltd.

View
No Thumbnail Available
Publication

Maintenance Plan Based on TPM for Turbine Recovery Machinery

2021 , Lozada-Cepeda J.A. , Lara-Calle R. , Buele, Jorge

The maintenance and repair of the components of hydroelectric turbines require the use of specialized equipment. To keep these teams operational, it is proposed to design a master plan in order to develop a TPM philosophy for a vertical turning lathe. This project develops five of the twelve steps established by JIPM for the TPM implementation. This paper also provides the necessary documentation for 5S and autonomous maintenance applications. Also, some safety, health and environmental suggestions are provided. PM activities are chosen based on RCM techniques like CA and FMEA. And predictive maintenance activities are established following ISO 3655, 2006. All these activities including automotive maintenance ones are organized and scheduled. Finally, OEE rate is applied to the lathe to identify the principal losses on the machine. After applying this proposal there is an increase of 27.84% and 39.71% in availability and performance respectively. The OEE calculation has increased by 29.97%, thereby motivating readers to implement this methodology in other industries. © Published under licence by IOP Publishing Ltd.

View
No Thumbnail Available
Publication

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.

View
No Thumbnail Available
Publication

Body Composition Evaluation using Bioelectrical Impedance and its Impact on Academic Performance of Nursing Students

2023 , Romero Riaño, Paola , Camaño Carball, Lilian , Yánez-Rueda H. , Buele, Jorge

In the past, nutritional assessment relied on manual measurements that did not allow for the differentiation of body composition components. With technological advancements, the introduction of bioelectrical impedance has provided a more specific approach to obtaining results. This study aims to utilize this innovative method to assess the connection between body composition and academic performance in nursing students. The research focused on a representative sample of 89 participants, utilizing bioelectrical impedance to measure the primary bioelements of the human body. Strong and significant correlations were observed between height and weight, height and muscle mass, and muscle mass and weight. A moderate correlation was found between weight and fat, as well as significant weak correlations between age and fat, and between fat and body mass index. Additionally, a significant weak negative correlation was observed between height and fat. Of the participants, 42.2% of women and 48% of men were classified as overweight. However, the statistical analysis did not reveal significant correlations between academic performance and variables such as weight, muscle mass, fat, and body mass index. Based on this information, it was concluded that most students had a body mass index within the normal range, and no direct relationship between body composition and academic performance was identified. Continuous monitoring of overweight students using this technology is recommended to promote healthy nutritional practices. © 2023 IEEE.

View
No Thumbnail Available
Publication

Virtual reality applications based on instrumental activities of daily living (iADLs) for cognitive intervention in older adults: a systematic review

2023 , Buele, Jorge , Varela-Aldás J.L. , Palacios-Navarro G.

Background: In recent years, the use of virtual reality (VR) as a complementary intervention in treating cognitive impairment has significantly increased. VR applications based on instrumental activities of daily living (iADL-VR) could offer a promising approach with greater ecological validity for intervention in groups with cognitive impairments. However, the effectiveness of this approach is still debated. Objective: This systematic review aims to synthesize the effects of iADL-VR interventions to rehabilitate, train, or stimulate cognitive functions in healthy adults and people with mild cognitive impairment (MCI) and different types of dementia. Methods: A systematic search was performed in the Scopus, PubMed, IEEE Xplore, Web of Science, and APA PsycNet databases until September 2022 and repeated in April 2023. The selected studies met the search terms, were peer-reviewed, included an iADL-VR intervention, and were written in English. Descriptive, qualitative studies, reviews, cognitive assessment, non-intervention studies, those unrelated to VR or iADL, those focused on motor aspects, and non-degenerative disorders were excluded. The PEDro scale was used to assess the methodological quality of the controlled studies. To present and synthesize the results, we organized the extracted data into three tables, including PEDro scores, participant characteristics, and study characteristics. Results: Nineteen studies that met the inclusion and exclusion criteria were included. The total sample reached 590 participants, mostly women (72.67%). Approximately 30% were diagnosed with Alzheimer’s disease or dementia, and 20% had mild cognitive impairment. Variables such as authors and year of publication, study design, type of intervention and VR applied, duration of the intervention, main findings, and conclusions were extracted. Regarding demographic characteristics, the sample size, age, sex, years of education, neurological diagnosis, dropouts, and the city and country where the intervention took place were recorded. Almost all studies showed improvements in some or all the outcomes after the intervention, generally greater in the iADL-VR group than in the control group. Conclusion: iADL-VR interventions could be beneficial in improving the performance of cognitive functions in older adults and people with MCI and different types of dementia. The ecological component of these tasks makes them very suitable for transferring what has been learned to the real world. However, such transfer needs to be confirmed by further studies with larger and more homogeneous samples and longer follow-up periods. This review had no primary funding source and was registered with PROSPERO under registration ID: 375166. © 2023, The Author(s).

View
No Thumbnail Available
Publication

An assessment of a ROS class using an educational mobile robot

2024 , Varela Aldas, José , Junta, Christian , Buele, Jorge , Guillermo Palacios-Navarro

The Robot Operating System (ROS) is a middleware that standardizes robot programming, both in simulation and with real equipment. Despite this open-source tool being available for several years, there's still a need to enhance its utilization in robotics education across all educational levels. In this study, a ROS class is assessed among university students using a commercial educational robot. The primary objective is to measure academic emotions in learning and student performance to determine the impact of the class using the open-access tool from a GitHub repository (https://github.com/joseVarelaAldas/ROS-Crowbot). This tool is based on the rosserial package, compatible with the ESP32 board. For class, CrowBot robots connected to the local wireless network via WiFi are used. TThe participants in this study were eight students from an electronics degree program at a higher education institution, who had no prior experience with ROS and received practical training using the educational mobile robot. For data collection on class performance, three parameters are assessed: execution time, functionality, and motivation, and to measure academic emotions, a validated self-report instrument is used. The results show an overall performance of 82.1%, and in the self-report on academic emotions, a high score in enjoyment (95%) and the lowest score in boredom (24.1 %) were obtained. In conclusion, the repository provides an interesting, practical, and accessible tool for an introduction into the world of robotics using ROS.

View
No Thumbnail Available
Publication

Mobile Manipulator for Hospital Care Using Firebase

2022 , Varela Aldas, José , Buele, Jorge , Guerrero-Núñez S , Andaluz V.H.

The COVID-19 pandemic has shown that the use of the technology in medicine is no longer a luxury, but a necessity. The use of the robotics in the treatment of diseases and physical therapies is limited in Latin America due to the high acquisition and maintenance costs. This document proposes the design, development, and evaluation of a robotic system for the guided monitoring of patients, through remote control using a mobile application. Within the methodology, four phases were proposed: planning, design, development, and evaluation. The 3D design is done using the Tinkercad software, which facilitates the construction of the pieces using 3D printing technology. The ESP32 board is the main element that receives the signals from the sensors and controls the actions of the actuators through the orders received from Firebase. For the development of the application, App inventor is used, building a friendly and easy-to-use interface. To validate this proposal, experimental tests were carried out with two patients in a medical center. In addition, a parameter compliance questionnaire was applied to the robot, obtaining a score of 92.6%, and the mobile application obtained 72.5% in the usability test. All this confirms an efficient care proposal, with a reduced investment. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

View
No Thumbnail Available
Publication

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.

View
No Thumbnail Available
Publication

Ethical Use of Generative Artificial Intelligence Among Ecuadorian University Students

2025 , Buele, Jorge , Ángel Ramón Sabando-García , Bosco Javier Sabando-García , Yánez Rueda, Hugo

Artificial intelligence has transformed educational environments by facilitating processes such as information retrieval, assisted writing, automated feedback, and personalized tutoring. Within university settings, the adoption of technologies capable of autonomously generating content has increased rapidly, becoming a common academic resource for students. However, this accelerated integration poses ethical challenges, particularly when such tools are used without a clear understanding of their implications. This study aimed to examine how students’ emotional attitudes (affective), understanding (cognitive), and practical use (behavioral) of AI relate to their ethical engagement with these technologies. A structured questionnaire was administered to 833 university students in Ecuador. The instrument showed excellent internal consistency (α = 0.992; Ω = 0.992), and the validity analyses confirmed that the dimensions measured distinct but related constructs. ChatGPT was reported as the most used tool (62.2%), followed by Gemini and Siri. The structural model indicated that emotional and cognitive dimensions substantially influenced ethical behavior (β = 0.413 and β = 0.567, respectively), whereas frequent use alone exhibited no significant effect (β = −0.128; p = 0.058). These results suggest that ethical engagement with AI is primarily driven by reflection and knowledge rather than habit. This study contributes to the literature by modeling how different learning dimensions shape ethical behavior in AI use and underscores the relevance of aligning academic practices with socially responsible uses of emerging technologies.

View
No Thumbnail Available
Publication

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.

View