A feasibility analysis was carried out for the implementation of an 824,86 MW photovoltaic plant in the area of the failed “Eloy Alfaro” Pacific Refinery project in El Aromo, Manabí province, Ecuador. It will occupy 91,31% of the 530 ha allocated to the initial project and will cover a demand of 894,68 GWh projected over 10 years. With the RETScreen Expert software, three scenarios were analyzed, in all of them the profitability of the project is established. A simple return on principal payment was estimated ranging from 1,3 to 6,9 years, with projected annual net income from $ 77.023.928 to $ 557.364.599. That would generate a profit of 190,93% if the sale is made at a residential rate and 889,55% if it is marketed according to the sale price established in the regulation of CONELEC 004/11. With a projected cost of electricity generation of 0,045 USD / kWh as a minimum value considering 20% incentives and donations; and a maximum of $ 0,054 / kWh without incentives. An emission reduction of 769.768,7 tCO2 was estimated, equivalent to 70,91% of the emissions of the automotive fleet of the province in 2019 and in barrels of oil represents a reduction of 14,92% in relation to the energy consumption of the sector residential electricity in 2019. The proposal exceeds 4,12 times the minimum installed capacity of a plant to be built in the area in the coming years, requires an additional surface of 45,28% and would present 35,11% less than the cost of production per kWh and if implemented would be the one with the highest power nationwide and the third in Latin America.

This paper addresses the synchronization and operation of a 140kVA inverter system connected to the main grid as part of a decentralized microgeneration system. The considerations for the supply of electrical energy stored in battery banks, mostly of photovoltaic origin, involve a study of the details of a rigid nonlinear system, which parallels the generation and distribution standards typical of hydroelectric and thermoelectric plants. Considering aspects related to power electronics operation, this paper presents both the modeling and the controlling aspects necessary to synchronize and ensure a stable operation of the microgeneration systems when connected to the main grid. Statistical processing was developed to guarantee synchronization between the systems without presenting electric shocks by simulating the magnetic link in asynchronous generators to meet this aim. The proposed model simulates the increase in power by a phase shift by maintaining a constant frequency based on a Chirp wave generator. The proposed process considers a generation power baseband operation. A Mamdani-type fuzzy proportional-integral controller is used to determine the power setpoint, which sets the Chirp generator phase shift setpoint, which includes a Mamdani fuzzy proportional-type controller. Both controllers are connected in a cascade. The applied correlational technique to achieve the synthesis of the sinusoid and the synchronization presented optimal performance when using 17 samples per signal period. The design of the transformer primarily, guaranteed a phase shift of 4.3018, allowed for a THD below 2.75.

Mathematics is one of the areas of knowledge where there are greater difficulties for its learning, due to its complexity, and the little usefulness that is perceived of them in real life, which is why pedagogical alternatives have been developed ( ABP). The usefulness of this tool in learning mathematics, which is sought by solving real problems through the use of mathematics. In this sense, the use of the PBL was evaluated in a group of 60 students of the Software career of the Polytechnic High School of Chimborazo (ESPOCH), 30 before the use of APB and 30 after its use comparing the changes in the academic performance of the students after the implementation of the PBL, as well as the perception of the students in relation to the interest, value, motivation and utilities of mathematics by solving problems using differential equations, The results found show that the students had a greater achievement when understanding and solving the equations adequately using derivation rules and analyzing and adequately interpret the information, which was related to a greater interest (50.85%), assessment (57.36%), satisfaction 57.62 (%) and utility 66.07%, despite the fact that the use of the PBL achieved a significant increase in grades, even the students state that they make a great effort to carry out projects in the area of mathematics, which was expressed by more than half of the students approached, the findings found lead to the conclusion that the use of this learning tool translates into a significant improvement in the acquisition of mathematical skills since a greater understanding and importance of the use of the itself, increases the interest and motivation of students for their study.

El estudio analiza los riesgos eléctricos durante las pruebas de transformadores, un aspecto crítico en ingeniería eléctrica para garantizar la seguridad tanto de equipos como de personal. Se evaluaron modelos predictivos como Árbol de Decisión y Regresión Logística, que mostraron un rendimiento limitado (23% y 29.1% de precisión global, respectivamente). Estos modelos presentaron dificultades significativas para clasificar correctamente clases minoritarias, evidenciando problemas asociados al desequilibrio de datos y la falta de sofisticación para capturar patrones complejos en entornos desafiantes. Además, se observó un sesgo hacia categorías mayoritarias, lo que compromete su aplicabilidad práctica en sistemas críticos como la protección de subestaciones o el análisis de fallas internas mediante técnicas avanzadas como el Análisis de Respuesta en Frecuencia (FRA). La discusión destaca la necesidad de mejorar estos modelos mediante estrategias como sobremuestreo (SMOTE), selección de características más relevantes y la implementación de algoritmos avanzados como XGBoost o redes neuronales artificiales. Desde una perspectiva práctica, se enfatiza la importancia de integrar conocimientos teóricos con herramientas avanzadas de aprendizaje automático para anticipar patrones de riesgo y mitigar fallos operacionales. Las recomendaciones incluyen abordar el desequilibrio de clases, realizar análisis más profundos de las variables y complementar los modelos con técnicas de interpretación como SHAP o LIME. Finalmente, se concluye que es crucial adoptar un enfoque multidisciplinario que combine pruebas físicas con modelos predictivos para optimizar la seguridad en sistemas eléctricos.

Artificial intelligence (AI) is transforming fashion e-commerce through personalized recommendations, virtual try-on, size suggestions, and algorithmic decision support. This study examines AI-driven fit confidence as a fashion-specific mechanism linking AI personalization quality, algorithmic transparency, trust in AI, consumer experience, and purchase intention, while considering privacy concern as a boundary condition. Data from 400 Ecuadorian consumers with prior exposure to AI-enabled recommendation or personalization features in fashion e-commerce were analyzed using partial least squares structural equation modeling. AI personalization quality and trust in AI were positively associated with fit confidence, while algorithmic transparency was associated with trust in AI. Fit confidence was strongly related to consumer experience but showed only a small direct association with purchase intention; its indirect effect through consumer experience was substantially larger, indicating complementary partial mediation. Privacy concern had no significant direct relationship with fit confidence. The interaction between privacy concern and personalization quality was negative, but evidence was mixed and sensitive to the bootstrap confidence-interval method; H7 was not supported under the primary percentile-bootstrap criterion adopted in this study. Predictive analyses showed stronger out-of-sample performance for trust in AI and fit confidence than for purchase intention. The study distinguishes trust in technology from confidence in anticipated product–consumer fit and supports explainable, privacy-sensitive applications in fashion e-commerce.