Revista Tecnológica ESPOL - Scientific Publications
Escuela Superior Politécnica del Litoral
Impact of Distributed Generation on Distribution Network in South America: A Techno-Operational Analysis
Over the past decade, the substantial expansion of distributed generation (DG) in South American's Distribution Networks (DN) has represented a paradigmatic shift that both industry and academia must address. Numerous studies have focused on assessing this integration from a technical-operational perspective. In this context, this article presents a literature review on DG integration and its impacts on DNs, focusing on studies that explicitly represent the DN through electrical modeling within the analytical framework. This research has been conducted within a South American context by an exhaustive analysis of scientific articles published between 2013 and 2024, applying the Prisma methodology. The investigation demonstrated that photovoltaic technology constitutes the primary generation source examined, also revealing a marked preference for OpenDSS as the analytical tool and identifying Brazil as the country with the highest research volume in this field. In addition to providing a detailed analysis of key studies, relevant parameters, commonly studied DN cases, and frequently used computational tools, this study also examines the impact of DG across different DN levels. In this regard, it discusses research areas that have received little attention thus far, highlighting the need for further exploration in these areas to fully understand the effects of DG.
Copyright (c) 2026 Diego Cando-Naula, Freddy Chuqui-Cajamarca, Danny Ochoa-Correa, Santiago Torres-Contreras https://creativecommons.org/licenses/by-nc/4.0
STEAM Approach to Traditional Recreational Games and its Impact on Upper Basic Education Students
This article presents a proposal that integrates traditional recreational games with the STEAM approach (Science, Technology, Engineering, Arts, and Mathematics) through an active methodology. The purpose is to reframe these games as interdisciplinary contexts that foster critical thinking and meaningful content learning among Upper Basic Education students. Using a qualitative methodology supported by analytical and digital resources, a six-phase guide was developed and implemented that encompassed playful experiences, scientific inquiry, design and prototyping, mathematical measurement, artistic expression, and social and attitudinal reflection. Through this sequence, traditional games were reinterpreted and transformed into STEAM projects, promoting connections among different subject areas. To evaluate the process, specific rubrics, field logs, and student work were used to assess and adjust levels of participation, creativity, and knowledge mastery. The results show that when traditional games incorporate STEAM experiences, they promote meaningful learning, stimulate curiosity, and strengthen the link between school knowledge and culture. In conclusion, the proposal stands as an important pedagogical and cultural resource within a multidisciplinary framework, offering a meaningful foundation for educational practice.
Copyright (c) 2026 Adrián Esteban Pazan Vásquez https://creativecommons.org/licenses/by-nc/4.0
Flexible Pavement Design Using the AASHTO 93 Methodology and Artificial Intelligence through a Customized GPT Model
This research aimed to determine the feasibility of using artificial intelligence in flexible pavement design through the customization of the OpenAI GPT-5.1 model, which is also applicable to GPT-5.2 and later versions. Five design cases were developed, each applying the design procedure through step-by-step spreadsheet calculations, the DIPAV 3.0 software, and a customized GPT model. Additionally, the adopted pavement thicknesses were evaluated using the rational method via WinDEPAV 2.6 software. For each design case, using both the GPT 5.1 and 5.2 models, five runs of the design prompt were performed with the Instant variant and five with the Thinking variant. For the comparative analysis, the mean error, mean absolute error, mean percentage error, and root mean square error were determined, as well as the coefficient of variation of the Equivalent Single Axle Loads (ESALs) and Structural Numbers (SN) obtained using AI, compared with the results generated by the DIPAV 3.0 software. Likewise, the pavement thicknesses determined by AI for each design case, model, and variant were evaluated in DIPAV 3.0 to determine the percentage of designs meeting the required SN.
Copyright (c) 2026 Fabricio Antonio Oyola Torres, Paul Javier León Torres, Jorge Humberto Maila Paucar https://creativecommons.org/licenses/by-nc/4.0
Effect of AI on the Technical Skills of Software Developers
This article examines the impact of artificial intelligence (AI) on the technical skills of software developers, with a particular focus on problem-solving, coding, and productivity. The study adopts a mixed-methods approach, combining a review of current scientific literature with the administration of structured surveys to programmers with varying levels of experience. The results reveal a frequent use of AI tools in software development, primarily to support learning and perform routine tasks, along with a generally positive perception of increased productivity. However, notable differences were identified across experience levels, with less experienced programmers showing greater trust in and reliance on AI, which influences the use of analytical skills, creativity, and technological autonomy. The study concludes that AI has a significant effect on developers’ technical skills, enhancing operational efficiency in specific contexts, while also transforming how logical reasoning and autonomous problem-solving are practiced, particularly during the early stages of professional training.
Copyright (c) 2026 Angie Jackeline Montes Jácome https://creativecommons.org/licenses/by-nc/4.0
Robotics and ChatGPT: Educational Application
In recent years, the incorporation of Artificial Intelligence (AI), particularly through Large Language Models (LLMs) such as ChatGPT, has enabled the development of new strategies for natural interaction between humans and robots, transforming how robots are controlled, programmed, and manipulated. This work implements a human-robot interface in Python that enables communication via natural-language instructions or queries expressed by the user. OpenAI's ChatGPT was used as an intelligent mediator to translate human natural language into control instructions sent to the robotic system. In addition, the proposal integrated an intelligent vision and data analysis system for the recognition of colour and geometric shapes, expanding the applications of the manipulator. Experimental validation was carried out using a Yahboom DOFBOT educational manipulator robot, an accessible platform for academic and research experiments. This work contributes to the field of Mechatronics by combining AI and robotics and motivates students and researchers towards new emerging, cutting-edge technologies.
Copyright (c) 2026 Jorge Gudiño-Lau, Kevin Andrade-Gudiño, Saida Charre-Ibarra, Miguel Durán-Fonseca, Janeth Alcalá-Rodríguez https://creativecommons.org/licenses/by-nc/4.0
Proposal of a Scrum Model for the ICT Directorate at the Universidad Técnica de Manabí
In the context of the digital transformation affecting higher education institutions, agile methodologies offer alternatives to improve efficiency in the management of technological projects. This study aimed to explore the feasibility of implementing the Scrum framework within the Information and Communication Technologies (ICT) Directorate at the Universidad Técnica de Manabí, based on an analysis of perceptions, barriers, and opportunities, in order to guide the design of an initial implementation proposal adapted to its organizational context. The research was conducted using a mixed-methods approach, through surveys administered to technical and administrative staff and interviews with key officials from the Directorate. The findings show a strong willingness among team members to adopt new practices, along with technical and institutional conditions that enable the initiation of a methodological change process. Based on the diagnosis, an initial proposal is presented that adapts Scrum roles, artifacts, and events to the ICT Directorate’s context, including a progressive pilot implementation and initial training activities to address knowledge gaps. The proposal stands out for its relevance and feasibility, as it integrates agile management tools within a contextualized approach, aimed at strengthening the planning, execution, and monitoring of technological projects at UTM.
Copyright (c) 2026 Andrés Enrique Azúa Arteaga, Gabriel Eduardo Morejón López, Erick Joel Zherdmant Cevallos https://creativecommons.org/licenses/by-nc/4.0
Analysis of Readability and Lexical Complexity in Thesis Abstracts from Early Childhood and Basic Education
The readability of academic texts is a key factor in ensuring reading comprehension, especially in educational contexts where textual clarity directly impacts learning. The main objective of this study is to identify levels of textual complexity and differences in discursive practices between two disciplines. To this end, a mixed-methods, descriptive design was adopted, combining quantitative and qualitative methods. The readability of English-language abstracts was assessed using traditional formulas, including Flesch Reading Ease, Flesch-Kincaid Grade Level, and Gunning Fog Index. Computational tools such as Text Inspector and VocabProfile were also used to analyse lexical diversity and discursive variables. The results revealed a high level of linguistic complexity in both groups of texts. The early childhood education abstracts were more difficult to read, with extreme scores across all the formulas applied. In contrast, the basic education texts showed greater lexical richness and sophistication. The analysis of discourse markers revealed a predominance of interactive resources, especially transitions, while interactional resources were scarce, evidencing an objective and impersonal academic style. In conclusion, writing patterns that hinder comprehension were identified, particularly in early childhood education. This study highlights the need to strengthen academic writing skills to improve the clarity, coherence, and accessibility of university texts.
Copyright (c) 2026 Andrea Ullaguari Piuri, Rodrigo Tovar Viera https://creativecommons.org/licenses/by-nc/4.0
Application of Artificial Intelligence in the Pattern Language for Urban Projects
The integration of artificial intelligence tools with the Building Information Modeling (BIM) software Revit was approached as a support strategy for applying Christopher Alexander’s Pattern Language in urban projects. The study analyzed how generative language models (GPT), combined with visualization and environmental simulation platforms, can contribute to interpreting and reinforcing the coherence, applicability, and sustainability of urban design. The research was carried out in four phases: analysis, modeling, integration, and evaluation. In the first phase, relevant patterns were selected, with an emphasis on Pattern 16, which focused on public transportation networks. Subsequently, an urban environment was modeled in Revit, with a central plaza as a transfer node to enhance accessibility. During the integration phase, three GPT models (My Generative AI Design Assistant, Innovator Architect, and Advanced IFC Editor) were applied to generate qualitative recommendations on accessibility, sustainability, and public space organization, while the LookX.ai platform was used to obtain photorealistic renders of the model, and Autodesk Forma for environmental simulations in two contrasting urban contexts. Finally, the proposals were evaluated in terms of coherence, applicability, and sustainability. The results showed solutions aligned with Alexander’s principles, highlighting the sustainability and functionality of the design. Environmental analyses and visual representations enriched the proposal, though limitations in interoperability and in the dynamic representation of the environment were identified.
Copyright (c) 2026 Ximena Cuenca-Torres https://creativecommons.org/licenses/by-nc/4.0
Community Savings Banks, an Option for Sustainable Socio-economic Development in Indigenous Communities of Loja, Ecuador
This study analyzes the impact of community savings funds as an alternative for sustainable socio-economic development. Information from the Superintendency of Popular and Solidarity Economy (statistics) was considered. Qualitative techniques such as focus groups, individual interviews, and discussions were applied to gather legal, administrative, accounting, and internal control information about the savings funds. A mixed-methods approach, combining qualitative and quantitative data, was used, with a specific focus on indigenous communities in the province of Loja. The aspects considered were the creation, formalization, and management of administrative and financial resources. The results revealed that legal and accounting formalization, along with the implementation of sound administrative and internal controls, are fundamental for their growth. Furthermore, it was determined that most savings funds operate informally, which increases the financial risk for their members. At the national level, there were 17 savings and loan cooperatives in 2021, a number that has grown to 643 in the first four months of 2025. This demonstrates a strengthening of the popular and solidarity-based financial sector nationwide, where these cooperatives play a key role in financial inclusion, especially in rural and low-income areas. In conclusion, community savings and loan cooperatives fulfill a fundamental role in fostering a culture of saving, promoting inclusion, and stimulating the local economy. It is important that these cooperatives become formalized so they can have efficient administrative management that promotes the sustainable socio-economic development of their communities.
Copyright (c) 2026 Dunia Maritza Yaguache Maza, Carlos Nelson Cobos Suarez, Veronica Cecilia Cabrera Gonzalez, Diego Fernando Pineda Arevalo https://creativecommons.org/licenses/by-nc/4.0
Social Responsibility and Profitability in Savings and Credit Cooperatives
Corporate Social Responsibility (CSR) is a fundamental factor for the sustainability and competitiveness of companies, including institutions in the popular and solidarity financial sector. The purpose of this study is to analyze the effects of CSR on the profitability of segment 1 savings and credit cooperatives in Ecuador during the period 2021-2023. The research was based on a mixed-approach design, descriptive and correlational in scope, using analytical-synthetic, inductive, and deductive methods. For the statistical analysis, Pearson's correlation coefficient was applied, complemented by scatter plots that allowed identifying the strength and significance of the links between the variables. The findings show an average correlation coefficient of 0.34, which indicates the existence of a low positive link between CSR and the profitability of the entities. However, certain CSR dimensions showed more significant links: "Member Economic Participation" obtained a coefficient of 0.47, and the "Education, Training, and Information" dimension reached 0.49. These results suggest that the effective use of CSR practices in sectors related to member engagement and community building can contribute to improving profitability indices. In conclusion, it is established that the link between CSR and profitability in cooperatives responds to social and community factors that strengthen trust, institutional cohesion, and positive member perceptions.
Copyright (c) 2026 Ximena Alexandra González Coronel, Siamara Patricia Coello Loaiza, Freddy Andrés Aponte Gómez https://creativecommons.org/licenses/by-nc/4.0
Universal Design for Learning (UDL) as a Core Strategy to Strengthen Inclusive Education in Durán, Ecuador
This study examines the implementation of Universal Design for Learning (UDL) as a strategy to strengthen inclusive education in the canton of Durán, Guayas Province, Ecuador. The research employed a descriptive quantitative approach, using a structured survey administered to 25 teachers from public institutions to identify their knowledge, use, and perceptions of UDL in their teaching practice. The findings reveal that although most teachers recognize the value of UDL and apply some of its strategies, its implementation remains partial due to limited specialized training, lack of accessible teaching resources, and insufficient institutional support. Among the main contributions are improved student participation, greater flexibility in instructional methods, and increased attention to learner diversity in regular classrooms. However, the identified barriers indicate the need to strengthen continuous professional development programs and invest in inclusive resources that enable the systematic application of UDL. The results of this study may inform educational decision-making and be transferable to other Ecuadorian school contexts with similar socio-educational characteristics, contributing to the advancement of a more inclusive and equitable education system.
Copyright (c) 2026 Bernardo Josue Encalada Escobar, Ernesto Isaac Encalada Escobar https://creativecommons.org/licenses/by-nc/4.0
Effect of Humic and Fulvic Acids on Pepper Cultivation (Capsicum annuum L.)
The use of chemical fertilizers generates serious problems such as environmental pollution, pest and disease resistance, and reduced food security. Current trends favor the use of organic products as an alternative for producing healthy foods while increasing productivity. This study aimed to evaluate the effect of applying different doses of humic and fulvic acids on pepper cultivation. The study was conducted in Palestina Canton, Guayas Province, Ecuador, using a completely randomized design with seven treatments and four replications. The results showed that Treatment 5, consisting of a combination of fulvic acid and humic acid (0.25 g + 1.87 cc), produced the best results across the variables evaluated. Plant height in the first evaluation ranged from 16.38 cm to 50.98 cm, stem diameter ranged from 2.94 cm to 3.24 cm, flowering occurred at 27 days, and an average of 5 fruits per plant was obtained. For fruit diameter, Treatment 5 also showed the best performance, reaching 5.12 cm. Fruit length ranged from 12.41 cm to 12.49 cm, fruit weight reached 212.50 g, and productivity reached 1,416.65 kg/ha, with a benefit–cost ratio of $1.28; that is, for every dollar invested, the farmer receives a return of $0.28. Therefore, it is concluded that humic and fulvic acids have positive effects as a supplement to fertilization.
Copyright (c) 2026 Antonio Gonzalo Álava Murillo, Darlyn José Amaya-Márquez, Mariana del Rocío Reyes Bermeo, Anggi Liseth Peñaranda Vásquez, Kleber Manuel Calle-Romero https://creativecommons.org/licenses/by-nc/4.0
Revista Tecnológica ESPOL – RTE: Cincuenta años de historia científica, innovación editorial e internacionalización académica (1976–2026)
En junio de 2026, la Revista Tecnológica ESPOL – RTE conmemora cincuenta años de trayectoria académica y científica, consolidándose como una de las publicaciones universitarias de investigación multidisciplinaria más representativas del Ecuador y alcanzando, precisamente en este año histórico, uno de los logros más trascendentales de toda su existencia: su indexación oficial en Scopus, una de las bases de datos científicas más prestigiosas y exigentes del mundo. Este reconocimiento internacional no solo valida la calidad editorial y científica de la revista, sino que también fortalece la imagen académica de la ESPOL y proyecta a nivel global la producción científica generada en el Ecuador. La indexación en Scopus constituye, además, un hecho especialmente significativo, ya que la RTE logró cumplir, en su primera aplicación, con todos los estándares internacionales exigidos por el comité evaluador, sin atravesar rechazos previos ni procesos de reevaluación, lo cual suele ser habitual incluso en revistas científicas consolidadas. Este resultado representa un motivo de profundo orgullo institucional y evidencia el nivel de madurez editorial alcanzado por la revista en los últimos años. La historia de la RTE refleja también la evolución de la comunicación científica universitaria en el país. A lo largo de cinco décadas, la revista atravesó procesos de consolidación institucional, modernización tecnológica, transformación digital e internacionalización académica, sostenidos por generaciones de directores, editores, revisores y autores comprometidos con la difusión del conocimiento científico.
Copyright (c) 2026 Nayeth Idalid Solórzano Alcivar https://creativecommons.org/licenses/by-nc/4.0
Effective Strategies for Mitigating Voltage and Frequency Fluctuations in Isolated Microgrids: A Literature Review
Territorial expansion has posed new challenges for electrical systems, driving the need to electrify remote rural areas and island territories. This demand has fostered the development of electrical microgrids based on distributed renewable generation, which, due to their low inertia, experience voltage and frequency instability—particularly during overloads or transitions between isolated and grid-connected modes. This article presents a literature review focusing on strategies to mitigate these fluctuations, analyzing 28 recent publications. The findings highlight adaptive controllers, smart inverter compensation, and the integration of energy storage systems as dynamic support tools, showing a preference for solutions based on power electronics and predictive control algorithms.
Copyright (c) 2025 Santiago Arcos-Echeverría, Danny Ochoa-Correa https://creativecommons.org/licenses/by-nc/4.0
Development and Implementation of a Web and Mobile System to Optimize Training and Job Placement Processes at the FUNDET Foundation
The FUNDET Foundation faces inefficiencies in manual processes, including student data errors (35%), loss of graduate traceability (42%), and delays in job placement (an average of 15 days), which increase administrative workload and reduce the social impact of its programs for vulnerable populations in Guayaquil. To address these issues, a web and mobile platform was developed and implemented to automate student registration and psychotechnical assessment using rule-based expert systems (92% accuracy), and course assignment, while enabling real-time bidirectional job matching. The system was designed to comply with usability standards (ISO 9241-11: effectiveness ≥90%, efficiency ≤2 min/task, SUS ≥85) and accessibility requirements (WCAG 2.1 AA: contrast ≥4.5:1, full keyboard navigation). The project applied RUP (web) and Mobile-D (mobile) development methodologies, implemented using PHP, MySQL, HTML5, CSS3, Bootstrap, jQuery, XAMPP (web platform), and Java with Android Studio (mobile app), following an MVC architecture with RESTful API integration. The platform was evaluated with n=52 users (95% confidence level, 5% margin of error). Results show a 67% increase in efficiency (1.8 vs. 5.5 min/task), a SUS score of 87.4/100, a 28% improvement in job placement (from 72 to 92 graduates per month), and a 19% increase in retention. In conclusion, the solution incorporates AI-enhanced psychotechnical testing, predictive language features, and a dropout-tracking dashboard (95% reliability), powered by RUP/Mobile-D, replicable in NGOs ≤$5K, with limitations in rural connectivity and future in machine learning, iOS/PWA for secure data recording.
Copyright (c) 2025 Bryan Orlando Vélez San Martin, Roger Marcelo Freire Avilés, Víctor Hugo Rea Sánchez https://creativecommons.org/licenses/by-nc/4.0
Factors that influence teaching and learning in Police Schools in Colombia
This article describes the factors that influence the teaching-learning process in police education based on three categories of analysis: learning styles, environmental factors, and emotional factors. The communication triangle among instructors, commanders, and students was observed as a resource for examining the pedagogical perspective. The research method was descriptive ethnography and non-participant observation, which analyzed communicative interaction in everyday educational practices in thirteen Police Schools in Colombia, focusing on the training and instructional components. As an emerging variable, the factors that affect learning were identified after processing the observation logs in Atlas.ti. Among the findings, it was noted that instructors use standard strategies that may overlook students’ particularities, due to the difficulty of addressing individual learning styles in large classes. Environmental conditions—such as deficiencies in infrastructure, class size, poor lighting, and educational tools like interactive screens that limit visibility for many students—also impact learning. Regarding emotional factors, the hierarchical relationships and physically exhausting environments were found to influence learning. Persistent cultural traditions and patterns were also evident, including paradigms about what is considered valuable learning. In conclusion, the focus on discipline and obedience is essential in police education and must be integrated with the conceptual and theoretical aspects of the subject matter to achieve comprehensive training. Doctrinal identity is prioritized over educational identity, and greater visibility is needed regarding shared responsibility in curriculum development.
Copyright (c) 2025 Ricardo Pachón Gutiérrez, Jennifer Ortiz Barrios, Martha Lucia Gallego Betancourth https://creativecommons.org/licenses/by-nc/4.0
Step-by-Step Factorization: Didactic Sequence with Symbolab in Tenth Grade of EGB
This article analyzes the impact of the technological tool Symbolab on the teaching of factorization among Tenth-Grade students in Basic General Education (EGB in Spanish). The study was conducted using a didactic sequence structured within a quantitative, quasi-experimental design, with an experimental group using Symbolab as an interactive resource and a control group working with traditional, predominantly expository methods. Diagnostic tests and post-tests were administered to measure students' progress in identifying and solving notable products and trinomial factorization. The data were analyzed using inferential statistics with Student's t-tests for independent samples. A preliminary t-test was conducted to verify equivalence between the groups, followed by a post-intervention t-test to assess differences. The results showed a significant improvement in the academic performance of the experimental group, with a statistically significant difference (t = 3,242; p = 0,002), suggesting a positive impact of Symbolab on the teaching of factorization. Additionally, an increase in motivation, autonomy, conceptual understanding, and a positive attitude toward the use of technologies was observed. It is concluded that the integration of Symbolab into the teaching-learning process supports the acquisition of algebraic content, especially when applied in structured contexts with clear pedagogical objectives. This proposal provides empirical evidence on the effectiveness of Symbolab in teaching factorization, which may guide future pedagogical strategies for integrating digital tools into mathematics instruction.
Copyright (c) 2025 Reinaldo Antonio Guerrero Chirinos, Omar Marcelo Urbina Gálvez, Juan Carlos Jiménez Medina, Carlos Alfredo Ebla Olmedo, Gabriela del Cisne Cuenca Sarango https://creativecommons.org/licenses/by-nc/4.0
Technological Tools for Immersive Reality in the Field of Education
This research analyzes the implementation of immersive reality tools in the educational field, focusing on their potential applications, the challenges that may arise, and the numerous opportunities they offer to enhance the teaching-learning process. Through an extensive literature review of research studies on the use of technological tools in education, the main technical, pedagogical, economic, and social barriers to their adoption across different educational contexts were identified. The results revealed that the studies focused on pedagogical design, technological implementation, accessibility, and teacher-student perceptions. The findings propose an integration model structured around three fundamental pillars: technological infrastructure, teacher training, and institutional sustainability. Inadequate infrastructure and financial constraints were identified as the main barriers to effective implementation. The study concludes that immersive reality has great potential to transform education, particularly in STEM (science, technology, engineering, and mathematics) fields. However, its success depends on overcoming the identified barriers through adaptive, inclusive, and sustainable strategies. Furthermore, the study provides a practical and strategic guide for implementing immersive technologies in education, offering relevant insights that pave the way for future research and strengthen their role in 21st-century educational systems.
Copyright (c) 2025 Keny Jeampier Saltos Sánchez https://creativecommons.org/licenses/by-nc/4.0
The Tax Planning in Decision-Making for Construction Companies
Tax planning is a fundamental element of financial management in construction companies, allowing them to identify fiscal strategies that maximize profitability. Through proper planning, companies can legally reduce their tax burden, improve cash flow, and strengthen their competitiveness in the market. A representative case is Constructora Velsa Bauen, located in the city and province of Loja, which succeeded in applying a comprehensive approach to tax planning, focusing on the analysis of fiscal periods 2018–2022. The research adopted a non-experimental design based on the review, classification, and processing of the company’s financial and tax data. As a result of the analysis, the best tax strategy identified for the construction company was the application of Article 29 of the Internal Tax Regime Law, which establishes that the tax on profits from the purchase and sale of urban properties—paid to municipalities—can be used as a tax credit toward income tax. This measure allowed the company to optimize the use of its resources and significantly reduce its tax burden. The main finding of the study was that, thanks to the implementation of this strategy, the company achieved a 41% savings in the tax incurred. These results demonstrate that strategic tax management not only improves the financial sustainability of construction companies owned by natural persons but also strengthens their growth and permanence in a competitive economic environment.
Copyright (c) 2025 Elizabeth Alexandra López Loján, Irma Abrigo Córdova https://creativecommons.org/licenses/by-nc/4.0
In vitro evaluation of chemical fungicides for the control of Moniliophthora roreri, the causal agent of cacao frosty pod rot (Theobroma cacao L.)
Cacao cultivation represents an important sector for the Ecuadorian economy, as it is one of the country’s main export products; however, diseases such as Moniliophthora roreri cause significant losses, and their control continues to be a challenge for producers. One solution to counteract this disease is the in vitro evaluation of chemical fungicides, as it allows for the characterization of phytopathogenic isolates and the estimation of chemical molecule dosages for phytosanitary management. For this reason, this study consisted of evaluating two fungicides: copper sulfate pentahydrate at 200, 2000, and 20000 mg·L⁻¹ and azoxystrobin at 1.0, 0.1, and 0.01 mg·L⁻¹ using two isolates of M. roreri under in vitro conditions. A completely randomized factorial design with seven replications was used. The radial growth of the fungus was evaluated to estimate the percentage of growth inhibition (PIC). The results showed that azoxystrobin achieved 100% PIC at 1 mg·L⁻¹ and was highly sensitive, regardless of the M. roreri isolate, although statistically the PIC between strains was significant. Copper sulfate pentahydrate reached maximum PIC at a dosage of 20000 mg·L⁻¹ and was classified as insensitive, with no significant differences in PIC between isolates of M. roreri. It is concluded that M. roreri is highly sensitive and insensitive to azoxystrobin and copper sulfate hydrate, respectively. The doses tested provide the basis for analyzing a larger number of isolates and subsequently applying trials under field conditions.
Copyright (c) 2025 Darlyn José Amaya-Márquez, Danny Daniel Avilés Párraga, Angie Lisseth Peñaherrera-Morales, Javier Ulises Mendoza Thompson, Evelyn Elizabeth Sánchez Castro, Antonio Gonzalo Álava Murillo https://creativecommons.org/licenses/by-nc/4.0
Forest Fire Detection and Alert System Based on Image Processing and AI
The objective of this work focuses on the design and implementation of a low-cost intelligent system for the early detection of forest fires, using IoT (Internet of Things) and AI (Artificial Intelligence) technologies. The designed methodology involved the development and comparative evaluation of multiple algorithms, divided into two approaches: techniques based on the analysis of color spaces (RGB, YCbCr, HSI, HSV, and PJF) and AI models (CNN, YOLOv8, and Haar Cascade). From this analysis, a hybrid architecture was selected that integrates the two highest-performing methods: an object detector based on YOLOv8 (Method 9) and a chromatic algorithm that fuses the PJF, RGB, and YCbCr spaces (Method 12). This visual system is complemented by a PM2.5 particle sensor to validate the presence of smoke and GPS/4G modules to issue georeferenced alerts. As a key result, the final prototype validated under controlled conditions achieved outstanding metrics such as 99.82% accuracy, 99.64% sensitivity, and 100.00% specificity under high illumination conditions. It also demonstrated energy efficiency and thermal stability through continuous monitoring of CPU, RAM, and current consumption. The main contribution of this work consists of a validated field solution, whose hybrid architecture proves to be accurate, efficient, and adaptable, confirming its feasibility for implementation in emergency contexts.
Copyright (c) 2025 Erick Alexander Castillo Matamoros, Robert Sebastián Chalco Montalván, Santiago Renán González Martínez https://creativecommons.org/licenses/by-nc/4.0
Development of a Protocol Converter from SMA Data to Modbus TCP for SCADA Integration
The integration of distributed energy resources into smart microgrids frequently necessitates seamless communication between heterogeneous devices and centralized supervisory systems. However, specific power electronics equipment, such as the SMA Sunny Island inverter, relies on proprietary communication protocols that are incompatible with standard SCADA interfaces. The present work delineates the design and implementation of a protocol converter that facilitates transparent translation between SMA Data and Modbus TCP, thereby enabling native integration of the Sunny Island inverter into Modbus-based SCADA environments. The proposed converter was developed using a Raspberry Pi platform and employs a modular architecture that combines the YASDI communication library with a custom Python-based Modbus TCP server. The system retrieves operational data from the inverter, maps it to Modbus input registers, and allows configuration commands to be issued from the SCADA system and applied to the inverter in a controlled manner. The experimental validation was carried out in the Microgrid Laboratory at the University of Cuenca. In this setting, the converter demonstrated reliable performance in two specific tasks: data acquisition and parameter configuration. The response times exhibited a range of 10 to 30 seconds, contingent upon the system's state. Following power cycles and communication interruptions, the converter demonstrated complete recovery capability. The findings substantiate the viability of the proposed method as a cost-effective and resilient solution for integrating proprietary energy devices with industrial monitoring platforms. Its flexibility and resilience render it suitable for broader deployment in smart grid infrastructures and distributed energy management systems.
Copyright (c) 2025 Santiago Ismael Araujo Ochoa, Joe Fernando Tigre Quituizaca, Juan Diego Belesaca, Fabian Astudillo-Salinas https://creativecommons.org/licenses/by-nc/4.0
Methodology for Identifying Good Teaching Practices Through Student Comments Using Sentiment Analysis and Structural Topic Modeling
This study proposes an empirical methodology to identify the most valued dimensions of teaching practices in higher education through a mixed-method approach that integrates qualitative and quantitative analyses. Over 89,000 student comments collected during teacher evaluations at the University of Cuenca (2024–2025) were analyzed. Advanced natural language processing techniques, specifically sentiment analysis and Structural Topic Modeling (STM), were used to process an extensive textual corpus. The analysis focused on positive comments aimed at teachers recognized through a prior comprehensive evaluation, aiming to uncover recurring patterns in student perceptions. Four key dimensions of student evaluation emerged from the analysis: disciplinary knowledge, communication management, socio-emotional skills, and teaching methodology. These dimensions reflect perceived teaching strengths and exhibit significant variability across disciplinary contexts and academic levels. For example, disciplinary knowledge is prioritized in technical areas, while socio-emotional skills are more valued in social sciences and health disciplines. These findings underscore that student evaluations are an essential source of qualitative information, overcoming limitations of traditional numeric metrics by offering deeper, contextual insights. Ultimately, the proposed methodology provides higher education institutions with a practical tool to identify specific faculty strengths and design evidence-based, personalized professional development programs, thus fostering continuous and contextualized improvements in educational quality.
Copyright (c) 2025 Diego Moscoso Lozano, Jorge Maldonado-Mahauad https://creativecommons.org/licenses/by-nc/4.0
Enhancing SCADA System Availability: A Case Study of Microgrid Universidad de Cuenca
Ensuring the uninterrupted operation of Supervisory Control and Data Acquisition (SCADA) systems is critical for industrial environments that rely on continuous monitoring and control of equipment. However, in the Microgrid Laboratory at the University of Cuenca, routine maintenance procedures have revealed a significant vulnerability: the SCADA system temporarily loses communication and control capabilities when some of the devices are powered down, resulting in forced system downtime. This paper investigates practical strategies to enhance SCADA system availability by addressing this critical limitation. Three hypotheses were explored: first, an issue in network redundancy management; second, with disconnecting of a device from the fiber-optic ring network; and third, programming errors within the LabVIEW-developed SCADA application. Experimental results demonstrated that these approaches, particularly the software-level improvements in LabVIEW, successfully maintained system control and communication during maintenance. The proposed solutions offer a scalable and cost-effective pathway to increase the resilience of SCADA systems in microgrid environments.
Copyright (c) 2025 Lourdes Gutierrez-Otavalo, Claudia Padilla-Guaman, Juan Diego Belesaca, Fabian Astudillo-Salinas, Edisson Villa-Ávila https://creativecommons.org/licenses/by-nc/4.0
Rock Fragmentation by Blasting in Open-Pit Mining: an AI Predictive Model
Rock fragmentation by blasting is fundamental in the mining sector. This process seeks to optimize rock size for subsequent extraction, transport, and processing. Predicting this fragmentation becomes a crucial task for improving operational efficiency; however, the application of simplified formulas lacks precision and adaptability to lithological variations. This study proposes the use of artificial intelligence (AI) for the accurate estimation of the average diameter of igneous, sedimentary, and metamorphic rocks. Based on a set of 97 real fragmentation and blasting data from around the world, the Random Forest (RF), Support Vector Regressor (SVR), and Kernel Ridge Regression (KRR) algorithms were evaluated, along with the Kuz-Ram equation, widely used in the industry. The results indicate that AI models significantly outperform the conventional equation. RF offers the highest accuracy with MSE of 0.0017 and R2 of 95.38%. In contrast, SVR achieves values of 0.0064 and 83.13%, while KRR achieves 0.016 and 69.60%. The adequate performance of these algorithms has led to the development of an application that allows users to view drilling grids, set specific dimensions, and compare projections of average rock size. This tool facilitates informed decision-making, improving mining processes and promoting more reliable and sustainable results in different operational contexts.
Copyright (c) 2025 Steven Toapanta-Delgado, Byron Guerrero-Rodriguez, Christian Mejia-Escobar https://creativecommons.org/licenses/by-nc/4.0
Immersive digitization of the Murocomba Forest using image processing techniques
This paper presents the development of a technological solution based on image processing for the immersive digitization of the Murocomba Protected Forest, located in the province of Los Ríos, Ecuador. The proposal integrates the use of a 360° camera to capture high-quality spherical images, which were digitally processed to optimize their sharpness, correct imperfections, and facilitate their integration into an interactive virtual environment. As part of the system, an artificial intelligence model with YOLOv8 architecture was implemented, trained to detect plant species present in the forest trails. These detections were incorporated into a web application that allows users to explore the trail remotely, interact with the content, and identify the flora of the site without the need for physical presence. The project seeks to offer an alternative for the conservation of the ecosystem through digital access to its biodiversity, reducing direct human impact and promoting environmental education. The results demonstrate the effectiveness of combining immersive technologies and sensing models to represent natural environments with high ecological value in an accessible and sustainable way.
Copyright (c) 2025 Diego Intriago-Rodríguez, Mathías Ortega-Rizzo, Carlos Belezaca-Pinargote, Edison Solano-Apuntes https://creativecommons.org/licenses/by-nc/4.0
Recommender System for the Assignment of Professors at the University of Cuenca
The assignment of teachers to courses in higher education represents a critical challenge for academic management, as it directly impacts the quality of the teaching-learning process. Despite their continued use, manual assignment processes face evident challenges, such as subjectivity, lack of standardization, and a high administrative workload. In response to this scenario, this study proposes a recommender system that combines sentiment analysis, using locally adapted transformer-based language models (RoBERTuito), with mathematical optimization techniques, aiming to align teachers' competencies with specific academic requirements. To achieve this, enriched teacher profiles were developed based on historical evaluations, automatically classified student comments, and institutionally defined competencies within the framework of the Competency Pentagon. Additionally, dynamic weights were incorporated to adjust the relevance of pedagogical and technical factors according to the particularities of each academic cycle. The results obtained from the recommender system demonstrate a high correlation between generated recommendations and manual assignments, particularly in technically oriented degree programs. Moreover, program directors who participated in a pilot test positively evaluated the system, noting that it not only significantly reduces the operational workload but also establishes itself as a strategic tool with high potential for scalability and replicability across diverse educational contexts.
Copyright (c) 2025 Pablo Esteban Quito Urgilés, Juan Javier Valdiviezo Armijos, Jorge Maldonado-Mahauad https://creativecommons.org/licenses/by-nc/4.0
Semantic Modeling of ECU911 Emergencies Using NLP and Ontologies
This study proposes a novel hybrid framework for knowledge representation in emergencies, integrating Natural Language Processing (NLP), OWL ontologies, and SWRL rules to process unstructured data from Ecuador's Integrated Security Service (ECU 911). The key contribution lies in the unique combination of advanced NLP models such as BERT for Named Entity Recognition and XLM-RoBERTa for zero-shot semantic classification, with a formally validated ontological model developed in Protégé and a parallel logical implementation in Prolog using the Object-Attribute-Value paradigm. Unlike prior works, this approach specifically addresses the challenge of transforming raw emergency call transcripts into actionable knowledge by (1) automating entity extraction (locations, persons) and semantic categorization of incidents, (2) generating interpretable decision rules via decision trees, and (3) enabling cross-paradigm interoperability through synchronized OWL/SWRL and Prolog inference engines. Experimental validation with SPARQL/SQWRL queries and the Pellet reasoner demonstrated 96.7% accuracy in inferring emergency priorities such as medical emergencies, outperforming standalone NLP or ontology-based methods. This work advances semantic AI for emergency response by bridging unstructured text analysis with formal reasoning, offering a scalable solution for real-time decision support in critical scenarios.
Copyright (c) 2025 Danny Leonardo Paltin Chica, Juan Diego Mejía Mendieta, Marcos Orellana, Jorge Luis Zambrano-Martinez https://creativecommons.org/licenses/by-nc/4.0
Piloting, Validation, and Definition of a Self-Perception Instrument for University Teachers' Digital Competencies in English Language Teaching in Costa Rica
This study aimed to develop, validate, and define a self-perception instrument to assess the digital competencies of university teachers in English language teaching in Costa Rica. Based on previous research hand theoretical frameworks on digital competencies, a questionnaire was constructed, focusing on key dimensions such as digital literacy, ICT integration in teaching, and teacher appropriation and commitment. The methodology employed a quantitative approach with a correlational and cross-sectional design, utilizing statistical techniques, including Confirmatory Factor Analysis (CFA), Classical Test Theory (CTT) and Item Response Theory (IRT), to evaluate the instrument's validity, reliability and objectivity. The results enabled informed decision-making and the definition of the most appropriate instrument for application to university English language teachers at the national level.
Copyright (c) 2025 Mario Esteban Alpizar Rodríguez https://creativecommons.org/licenses/by-nc/4.0
Maximizing agricultural production and economic profit: Simplified application of the quadratic model
Maximizing production and economic profit, as well as minimizing costs, aims to meet food demand, boost food security, and improve farmers' profitability. This study aims to validate the application of three simplified quadratic models for optimizing agricultural yields based on inputs. In quantitative research where the response variable is "higher is better," the law of diminishing returns is verified, and simplified quadratic models prove practical for calculating technical maximums and the economic optimum. For "lower is better" variables such as costs, the simplified quadratic model enables cost minimization with high reliability. Simplified models, applied to maximize production and economic profit, as well as to minimize costs, have proven valid and easily applicable in agricultural experimentation.
Copyright (c) 2025 Luis Alberto Duicela Guambi, Ángel Monserrate Guzmán Cedeño, Osvaldo Fosado Téllez https://creativecommons.org/licenses/by-nc/4.0