This study presents a predictive model for electricity generation at a petroleum station in Ecuador, using crude oil and diesel as primary energy sources. The objective is to ensure the energy self-sufficiency of the station, which is located in a remote area. To achieve this, tools based on time series and machine learning were employed. Historical data on fuel consumption and electricity generation from 2019 to 2023 were used to train prediction models aimed at anticipating energy demands and optimizing the management of resources involved in this process. To forecast the input variables of the predictive model, ARIMA time series were applied. The predictive models implemented were based on the Decision Tree algorithm and proved successful, as the prediction obtained was compared with actual electric power generation measurements and yielded very low errors. For example, a Mean Square Error of 0.09 MW, a Mean Absolute Error of 0.24 MW, and a coefficient of determination of 0.99 were obtained. As a conclusion, the model developed in this research, which is a combination of ARIMA with decision trees, demonstrates high feasibility for operational implementation at the plant.
Forecast accuracy alone is an incomplete proxy for operational value when load distributions change. This paper presents ARLOS, an auditable forecast–uncertainty–decision framework that combines static and adaptive XGBoost forecasts, rolling performance monitoring, residual-bootstrap uncertainty, and explicit fixed-margin, quantile, and risk-target operating rules. The evaluation uses 2021 for ex ante training and capacity-proxy definition and 2022–2023 for strictly sequential testing on two Ecuadorian distribution substations under a measured baseline, smooth growth, and intraday structural shift. Under the four shifted station–scenario cases, adaptive fixed-margin operation reduced the weighted operational objective by 24.8–46.0% relative to the static fixed-margin baseline; baseline-regime changes ranged from −2.5 to 11.2%, showing that adaptation is valuable primarily when mismatch is present rather than universally. A 2×2 ablation further shows that adaptation and uncertainty are distinct, non-additive sources of operational value: aggregate normalized cost changes from 0.987 for static/fixed operation to 0.650 for adaptive/fixed, 0.515 for static/quantile, and 0.546 for adaptive/quantile. Realized one-sided exceedance, computed from observed load rather than from the bootstrap sample itself, remains within 0.0039–0.0111 of the target across the controlled cases, while nominal 10–90% interval coverage ranges from 78.0% to 78.6%. A nine-substation deployment check corroborates the calibration and identifies a measured drift episode in which adaptation limits, but does not eliminate, forecast degradation. The results support ARLOS as a transparent framework for studying how adaptation and uncertainty propagate into operational consequences under distribution shift.These contributions align with Sustainable Development Goal 7 (Affordable and Clean Energy) and Sustainable Development Goal 9 (Industry, Innovation and Infrastructure) by supporting more reliable, efficient, and intelligent operation of electricity distribution infrastructure.
La presente investigación tuvo como objetivo principal determinar la relación entre el compromiso organizacional y la retención del talento humano en los colaboradores del sector financiero del Cantón Pujilí, Ecuador. Metodológicamente, adoptó un enfoque cuantitativo, no experimental, de corte transversal y alcance descriptivo-correlacional, aplicando un censo poblacional al 100% de la plantilla accesible, conformada por 116 profesionales activos de agencias bancarias y cooperativas de ahorro y crédito locales. La recolección de datos se realizó mediante dos cuestionarios validados en Google Forms que mostraron alta consistencia interna y validez: el de compromiso organizacional (17 ítems) alcanzó un Alfa de Cronbach de 0.920 y un KMO de 0.900, mientras que el de retención (9 ítems) obtuvo un Alfa de 0.902 y un KMO de 0.847. Los resultados descriptivos revelaron un escenario favorable donde predominó el nivel alto tanto en el compromiso organizacional (60.3%) como en la retención del talento (55.2%). Tras aplicar la prueba de Kolmogorov-Smirnov y determinar que los datos no siguen una distribución normal (p = 0.000), se empleó estadística no paramétrica mediante el coeficiente Rho de Spearman, arrojando un valor de Rho = 0.577 (p = 0.000) que evidencia una relación lineal positiva de intensidad moderada, concluyéndose que un mayor compromiso incrementa de manera directa y favorable la retención del personal en la identidad financiera local.
Justificación: El trabajo infantil continúa siendo un problema social que vulnera los derechos de niños, niñas y adolescentes y limita su acceso a la educación, la salud y oportunidades de desarrollo. Si bien se han implementado estrategias de cooperación institucional y acciones de apoyo social para prevenir esta problemática, aún existe escasa evidencia sobre cómo estas intervenciones son percibidas por las familias beneficiarias. Objetivo: Describir la percepción de las familias participantes en el Proyecto de Erradicación del Trabajo Infantil - ETI sobre la cooperación institucional y las acciones de apoyo social desarrolladas en la parroquia Izamba, cantón Ambato. Metodología: Se realizó un estudio con enfoque cuantitativo, de diseño no experimental, transversal y alcance descriptivo-exploratorio. Resultados: Las familias valoraron favorablemente la cooperación institucional, el fortalecimiento económico, la participación comunitaria y el apoyo familiar e institucional para prevenir el trabajo infantil. No obstante, identificaron limitaciones en la articulación entre instituciones, el acceso efectivo a servicios básicos, de salud y educación, y el acompañamiento brindado a los adolescentes para la construcción de su proyecto de vida. Conclusión: La percepción de las familias evidencia que la erradicación del trabajo infantil requiere fortalecer la coordinación interinstitucional y consolidar estrategias integrales de apoyo social, económico y comunitario orientadas a las necesidades de la población beneficiaria.
This study presents a numerical analysis of an agitated vessel with a draft tube through the analysis of dimensionless numbers correlations. The heat transfer and fluid mechanics simulation was conducted using ANSYS Fluent software. The simulation used the Sliding Mesh approach and the SST k- ω turbulence model to capture the vessel’s fluid flow and heat transfer phenomena. A grid independence study was conducted by varying the number of time steps to obtain an appropriate time step size for the simulation. The convective heat transfer coefficient, as indicated by the mean values of the Nusselt number, was calculated. The local values along the radial coordinate of the heat transfer surface were also determined. These results provide insights into the distribution of heat transfer rates within the vessel, which can help optimize process efficiency and equipment design. The simulation results were analyzed by varying the c and m coefficients in the Nusselt correlation presented as Nu= c Re^m Pr^1/3 . Furthermore, correlations describing the mean Nusselt number at the bottom and wall of the vessel are presented and compared with existing literature, contributing to advancing knowledge in this field.
