Facultad de Ingenierías
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Item type:Publication, Decision-Making and Operational Research Methods: A Theoretical-Cognitive Approach Personal Experience(Springer Nature Switzerland, 2026); ; Guerrero-Aldana, Andy NicolásThis article examines the relationship between decision-making and operations research methods, focusing on their evolution and application in complex environments. The main objective is to analyze how tools such as linear programming, simulation, and queue theory optimize resources and improve efficiency through the incorporation of advanced technologies like artificial intelligence and predictive analytics. These methods have been essential in solving problems across various sectors such as manufacturing, transportation, and services. Interviews with 50 participants, including academics and students, were used to assess the effectiveness of various operational methods in decision-making. The primary criterion was efficiency and improvement in the results obtained, while secondary results included the perception of flexibility and practical applicability of the methods. Simulation emerged as the most efficient approach, with a 22% improvement over other methods. Simulation methods proved to be the most effective, improving results by 22% compared to other approaches like integer and nonlinear programming. Participants highly valued practical and flexible methods, such as simulation, due to their ability to adapt to different contexts and situations. Additionally, the ease of implementation and time savings in decision-making were key factors in their preference. The study confirms that simulation is a key tool in decision-making in complex operational environments, providing superior results in efficiency. This suggests that, for future research, further exploration of the integration of practical and flexible methods like simulation, along with the exploration of their potential in combination with emerging technologies, is needed to optimize real-time decision-making processes. It is also recommended to evaluate their implementation in other sectors beyond those analyzed in this study, such as healthcare and public management. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving Electrical Efficiency at La Roca S.A. Construction Company(Springer Nature Switzerland, 2026); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Effect of replacing mixing water with milk on the compressive strength of concrete at different curing ages(Frontiers Media SA, 2026-07-17); ; Zurita, MarcoIntroduction – The chemical composition of mixing water directly affects cement hydration and the strength development of concrete. Although alternative mixing liquids—such as treated wastewater, leachates, and wash water—have shown moderate strength reductions compatible with structural use, the behavior of concrete exposed to complex organic liquids remains largely uncharacterized. Methods – This study investigates how replacing mixing water with whole bovine milk, a medium rich in lactose, casein, and fat, affects cement hydration and compressive strength in conventional Portland concrete. Three mixtures with increasing replacement levels were produced: 0% (M0, control), 50% (M50), and 100% (M100). Twenty-seven cylindrical specimens (3 mixtures × 3 ages × 3 replicates) were tested under axial compression following ASTM C39/C39M at 15, 28, and 45 days. Peak strength, stress–strain curves, within-condition dispersion, and failure modes were recorded. Results – The control developed strengths of 14.39 ± 0.64, 16.47 ± 0.73, and 20.91 ± 0.81 MPa at 15, 28, and 45 days, whereas M50 and M100 remained below 1 MPa at all ages (M50: 0.61 ± 0.03, 0.67 ± 0.03, 0.90 ± 0.06 MPa; M100: 0.38 ± 0.02, 0.55 ± 0.02, 0.60 ± 0.03 MPa), a strength loss greater than 95% relative to the control. Coefficients of variation ranged from 3.9% to 6.1%, below the 10% threshold of ACI 214R. The modified mixtures also lost the ascending branch of the stress–strain curves and exhibited diffuse failure modes, without the longitudinal cracking typical of sound concrete. Conclusion – The magnitude of the strength loss (>95%) places milk in a category distinct from previously reported alternative mixing liquids. Rather than producing a degraded variant of conventional concrete, it generates a system in which the cementitious reaction is practically inhibited. This behavior, attributable to the combined action of lactose, casein, and fats on C3S hydration, redefines the operational limits of chemical compatibility between organic fluids and cementitious systems and provides a reference calibration point for predictive models of organic inhibition. Copyright © 2026 Pinto, Zambrano, Apraez, Gómez, Zurita and Buele. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Academic Performance and Inequality: Can Generative AI Widen the Digital Divide in Higher Education?Higher educationHigher education has undergone a rapid transformation driven by digitalization and the rise of generative artificial intelligenceGenerative artificial intelligence tools, such as Chat Generative Pre-trained Transformer and Copilot. While these technologies offer significant opportunities to support learning processes, they also risk deepening existing inequalities if not implemented under equitable conditions. Many students, particularly those in rural areas or with limited resources, continue to face barriers related to device availability, Internet connectivity, and digital training, which restricts the effective use of generative AIArtificial intelligence and negatively affects academic performance. To analyze this gap and identify possible solutions, a critical narrative review of eighteen academic and technical sources published between 2022 and 2024 was conducted. The review focused on five key areas: access, digital literacy, academic impact, structural inequality, and inclusive strategies. The findings reveal sharp disparities: only 27% of rural students have access to devices compatible with generative AI, compared to 70% in urban settings, and students with strong digital competencies obtain up to 60% greater academic benefit from these tools. These results underscore the urgent need for targeted interventions to avoid exacerbating the digital divide. In response, the study proposes five strategies: ensuring equitable institutional access, strengthening critical digital literacyCritical digital literacy, adopting hybrid pedagogical models, designing inclusive curricula, and promoting dedicated research lines on public policy. The conclusion is that although generative artificial intelligenceGenerative artificial intelligence holds considerable educational potential, its benefits will only be realized if embedded in inclusive ecosystems that guarantee equal conditions, teacher support, and the ethical development of learning. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Robotics in higher education and its impact on digital learningIn recent years, robotics has transformed various industrial processes but has also influenced teaching methodologies. Although there are literature reviews on its application in professional training, many are outdated or lack a current focus on its impact in higher education. Addressing this gap, the present mini review examines the impact, challenges, and opportunities of this technology in the university setting. To this end, a search was conducted in the PubMed, Scopus, IEEE Xplore, APA PsycNet, and Web of Science databases, selecting 11 studies that addressed diverse applications of robotics, including educational robotics, robotic telepresence, human-robot interaction, and artificial intelligence applications. Their effects on teaching, the factors influencing their adoption, and the strategies used to optimize their implementation were analyzed. The findings show that educational robotics enhances student motivation and engagement, with prediction models reaching an accuracy of 98.78% in assessing academic engagement. Additionally, robotic telepresence emerges as an effective alternative for hybrid education, and social robots and AI-based tutors demonstrated their potential to personalize learning. However, methodological and structural challenges persist, such as the need to develop more accurate evaluation metrics and ensure accessibility and educational equity. Future research should focus on improving these aspects, enabling more efficient integration to enhance teaching processes. This study was registered in the Open Science Framework under the code: 10.17605/OSF.IO/KHDTU.57 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhancing Simulation Accuracy in Radioactive Decay Models: Comparative Analysis of Euler and RK2 Methods for Interactive SystemsThe modeling of radioactive decay processes has long been essential in fields such as nuclear physics, embedded systems, and educational simulations. Traditionally, the Euler method has been used to numerically solve the differential equations governing these phenomena. However, Euler’s method exhibits significant limitations in terms of accuracyAccuracy and stability, particularly in coupled systems or stiff mathematical configurations. To address this issue, this study presents a detailed comparison between the Euler method and the second-order Runge-Kutta method (RK2), aiming to evaluate their performance in terms of error accumulation, temporal fidelity, and the ability to preserve system dynamics. The goal is to determine which method is more suitable for simulations that demand high precision and computational efficiency. Numerical simulations were conducted for dual decay, cyclic decay, and thermistor cooling models using normalized time steps (Δt = 0.01 and 0.05). The results were compared against analytical solutions and analyzed through logarithmic error plots. RK2 consistently outperformed the Euler method, reducing absolute error by up to 80%. For instance, in the dual decay model, Euler’s error reached 3.41 units, while RK2 kept it below 0.62. Moreover, RK2 preserved the oscillatory dynamics in cyclic models and accurately predicted thermal thresholds in thermistor simulations. RK2 proves to be significantly more suitable for dynamic simulations where numerical precision and stability are critical. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.15 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Study of the Influence of Anthropogenic Sources on the Water Quality of the Ambato River, Tungurahua - Ecuador. A Growing Environmental Problem(2022)15 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Perceptions and Dispositions of Parents and Teachers Toward Technological Learning Communities(2023)29 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predicting Academic Performance in Mathematics Using Machine Learning AlgorithmsSeveral 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.39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Design of a Semi-automatic Dough Mixer for the Prevention of Occupational Diseases in Marzipan ArtisansOlder people, due to the natural aging process, are particularly vulnerable to occupational tasks, as they experience a gradual loss of physical capacities, which increases the incidence of occupational diseases in this population. Despite these challenges, their experience and skills acquired over the years make them a valuable resource for society. This study focuses on designing a semi-automatic dough sheeter for the dough making process used by the artisans of Calderón in Ecuador, who currently carry out this work manually, this practice being an integral part of the local culture. The research began with a detailed analysis of modern manual molders, collecting data on shear force, bending moment, and tensile stress, which are fundamental to the design. Subsequently, a simulation of the design was carried out using SolidWorks software. The result was the creation of a prototype kneading machine equipped with AISI 1050 steel rollers, processed by HR. This device was able to significantly reduce repetitive hand movements, reducing the effort during the kneading process by 25,000 TMU, which translates into improved health and work performance for the artisans. The implementation of this technology reduced the risk of occupational diseases such as bursitis, which is caused by inflammation of the bursae in the joints, and carpal tunnel syndrome, which affects the functionality of the hands. In addition to the physical benefits, this project also addresses the psychological aspect, as many older craftsmen and women feel demotivated due to their diminished ability to perform tasks they used to do in their youth. The research aims to provide a better quality of life for these workers, protecting both their physical health and emotional well-being. In short, the semi-automatic laminator not only improves the working conditions of the Calderon artisans but also preserves and promotes an important cultural tradition, ensuring that these valuable knowledge and skills can continue to be practiced in a safe and sustainable manner.11