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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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.

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Organizational communication in change management: A narrative review

2026 , Taruchaín Pozo, Fernando , Avilés-Castillo, Fátima , Evelyn Cuesta-Andaluz , Buele, Jorge

In an increasingly digital and competitive business landscape, communication practices within organizations are evolving to meet new operational and cultural demands. These shifts have redefined how companies engage with internal and external stakeholders across different levels. Despite the growing importance of communication, many organizations continue to face structural and strategic challenges that hinder effective message delivery and alignment. This review aims to identify key trends, persistent challenges, and the reported benefits of organizational communication, offering a synthesized view of recent academic contributions to the topic. A structured narrative review was conducted using thematic analysis of 52 peer-reviewed studies published in English and Spanish over the last decade. Using thematic analysis, the study identifies prevailing trends, key challenges, and reported benefits within organizational communication in the context of change management. Major trends include the adoption of digital communication tools, personalized messaging, strategic utilization of social media, and the incorporation of storytelling techniques. Challenges highlighted encompass resistance to change, message fragmentation, data security concerns, and information overload. The review also underscores significant benefits such as enhanced decision-making processes, improved stakeholder alignment, innovation facilitation, reputation management, and talent retention. These findings contribute to a comprehensive understanding of the evolving role of communication as a strategic asset in organizational change processes. The study concludes by emphasizing the necessity of integrated, adaptive, and inclusive communication strategies that not only support change initiatives but also foster organizational resilience and competitiveness in dynamic environments. Together, these findings provide a solid foundation for developing more effective communication practices aligned with the current demands of organizational transformation.

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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.

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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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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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Environmental Sustainability in Industrial Operations: A Comprehensive Review

2024 , Espinoza Castro, Froilan , Lara Ramírez, Andy , Buele, Jorge

As industrial activities expand, their significant environmental impact calls for the adoption of sustainable practices to mitigate adverse effects on ecosystems and communities. This comprehensive review synthesizes recent literature from recognized databases such as Scopus, SciELO, IEEE Xplore and Latindex, focusing on articles published within the last five years that emphasize the implementation of sustainable strategies in industrial operations. Our findings highlight a range of implemented strategies across various sectors, including advancements in energy efficiency through technology integration and resource optimization. Despite these improvements, challenges such as high resource consumption and waste production persist, underscoring the ongoing conflict between industrial growth and environmental preservation. The review discusses case studies demonstrating both the environmental and economic benefits of sustainable practices, illustrating the potential for industry-wide improvements. Conclusively, while the industrial sector has made notable progress towards sustainability, substantial efforts are required to address inherent challenges such as the high costs of initial investments and general resistance to change. Future research should explore the development and application of innovative technologies tailored to specific industrial needs, aiming to foster a holistic approach to sustainability that integrates economic, social, and environmental aspects.

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3D Object Reconstruction Using Concatenated Matrices with MS Kinect: A Contribution to Interiors Architecture

2020 , Buele, Jorge , Varela Aldas, José , Castellanos E.X. , Jadán Guerrero, Janio , Barberán J.

Interior architecture is part of the individual, social and business life of the human being; it allows structuring the spaces to inhabit, study or work. This document presents the design and implementation of a system that allows the three-dimensional reconstruction of objects with a reduced economic investment. The image acquisition process and treatment of the information with mathematical support that it entails are described. The system involves an MS Kinect as a tool to create a radar that operates with the structured light principle to capture objects at a distance of less than 2 meters. The development of the scripts is done in the MATLAB software and in the same way the graphical interface that is presented to the user. As part of the initial tests of this prototype, the digitization of geometric shape structures has been performed with an accuracy of over 98%. This validates its efficient operation, which serves as the basis for the development of modeling in interior architecture for future work. © 2020, Springer Nature Switzerland AG.

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Natural lighting performance of vernacular architecture, case study oldtown Pasa, Ecuador

2023 , Bustán-Gaona D. , Ayala-Chauvin M. , Buele, Jorge , Jara-Garzón P. , Riba-Sanmartí G.

Vernacular architecture is an architectural style that reflects the traditions and cultural aspects of a particular region or community. It is characterized by the use of local materials and traditional construction techniques, adapting to the climatic, geographical, and cultural conditions of the place. Despite extensive research on the benefits of natural lighting in modern architecture, there is limited understanding of how vernacular architecture integrates natural lighting principles in various climatic conditions, mainly due to restrictions in intervention and concerns about structural integrity. In today's world, energy efficiency and conservation are crucial aspects of building design. Therefore, this study aims to analyze the effectiveness of natural lighting in the indoor spaces of vernacular architecture. The research includes measurements taken in traditional buildings in the parish of Pasa, Ambato, Ecuador, as well as simulations to evaluate the behavior of sunlight. The findings reveal that, with new construction technologies, lighting levels in the interior spaces of these buildings can be improved. To address this issue, a proposed solution is presented to optimize the use of natural light, resulting in an increase from 30 to 100 lx. This improvement could pave the way for the implementation of policies that enhance the quality of life for users. © 2023

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Factors Influencing University Dropout in Distance Learning: A Case Study

2023 , Núñez Hernández, Corina , Buele, Jorge

In the field of higher education in Ecuador, there is a phenomenon where students abandon the career, they were initially enrolled in. This research article aims to identify the determining factors that influence dropout, analyzing sociodemographic variables and economic, technological, institutional, and academic variables. The methodology used is action research built from educational practice. A survey was used to address several factors applied to 260 students of the second, fourth, and seventh levels of undergraduate study at a private institution. As a result, it was found that the most determining factor for a student to abandon their university career in the distance mode, with 72.31%, is the economic factor. Finally, it is concluded that students' permanence is affected mainly by socioeconomic aspects, which cause economic resources, illness, lack of time, and academic performance to be the most representative factors when deciding whether to remain or abandon a university career. This information increases the bibliography that deals with student behavior to search for alternatives to work on students' permanence. © 2023, North American Business Press. All rights reserved.

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Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial

2024 , Buele, Jorge , Avilés-Castillo, Fátima , Carolina Del-Valle-Soto , Varela Aldas, José , Guillermo Palacios-Navarro

Abstract Background The increase in cases of mild cognitive impairment (MCI) underlines the urgency of finding effective methods to slow its progression. Given the limited effectiveness of current pharmacological options to prevent or treat the early stages of this deterioration, non-pharmacological alternatives are especially relevant. Objective To assess the effectiveness of a cognitive-motor intervention based on immersive virtual reality (VR) that simulates an activity of daily living (ADL) on cognitive functions and its impact on depression and the ability to perform such activities in patients with MCI. Methods Thirty-four older adults (men, women) with MCI were randomized to the experimental group (n = 17; 75.41 ± 5.76) or control (n = 17; 77.35 ± 6.75) group. Both groups received motor training, through aerobic, balance and resistance activities in group. Subsequently, the experimental group received cognitive training based on VR, while the control group received traditional cognitive training. Cognitive functions, depression, and the ability to perform activities of daily living (ADLs) were assessed using the Spanish versions of the Montreal Cognitive Assessment (MoCA-S), the Short Geriatric Depression Scale (SGDS-S), and the of Instrumental Activities of Daily Living (IADL-S) before and after 6-week intervention (a total of twelve 40-minutes sessions). Results Between groups comparison did not reveal significant differences in either cognitive function or geriatric depression. The intragroup effect of cognitive function and geriatric depression was significant in both groups (p < 0.001), with large effect sizes. There was no statistically significant improvement in any of the groups when evaluating their performance in ADLs (control, p = 0.28; experimental, p = 0.46) as expected. The completion rate in the experimental group was higher (82.35%) compared to the control group (70.59%). Likewise, participants in the experimental group reached a higher level of difficulty in the application and needed less time to complete the task at each level. Conclusions The application of a dual intervention, through motor training prior to a cognitive task based on Immersive VR was shown to be a beneficial non-pharmacological strategy to improve cognitive functions and reduce depression in patients with MCI. Similarly, the control group benefited from such dual intervention with statistically significant improvements. Trial registration ClinicalTrials.gov NCT06313931; https://clinicaltrials.gov/study/NCT06313931.

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