https://repositorio.uide.edu.ec/handle/37000/7601 2026-05-11T19:57:02Z https://repositorio.uide.edu.ec/handle/37000/9247 Title: Diseño de un escape room en realidad virtual para preservar las tradiciones y cultura de la comunidad shuar Authors: Carrión Campoverde, Leonardo Andrés; Cardenas, Charlie (tutor) Abstract: This article presents the design and implementation of a escape room called “Arutam: The Call of the Spirit,” which is a virtual reality game developed with Unreal Engine 5 for implementation on the Meta Quest 3 platform. The main objective is to contribute to the preservation and dissemination of the Shuar people's worldview through an immersive experience based on symbolic narrative and interactive mechanics. The development followed an iterative approach, integrating narrative design, human-computer interaction, and programming using Blueprints and C++. Qualitative results suggest that virtual reality promotes immersion and cultural understanding, positioning the video game as a viable technological tool for the preservation of intangible cultural heritage. 2026-01-01T00:00:00Z https://repositorio.uide.edu.ec/handle/37000/9246 Title: Implementación de Modelos Predictivos para la Gestión del Proceso de Polinización y Germinación de Semillas en la Empresa Ecuagenera Authors: Portilla Cartuche, Arlette Stefanny; Palacios Morocho, Milton Ricardo (tutor) Abstract: The study develops and implements a predictive system based on machine learning techniques for managing orchid pollination and germination processes at the Ecuadorian company Ecuagenera. These processes exhibit high biological and seasonal variability, which has historically forced the company to rely on manual records and empirical experience, generating operational uncertainty and production losses. The research adopts a quantitative and experimental approach, using historical data collected in the laboratory and applying feature engineering techniques to incorporate temporal, biological, and operational variables. Different supervised learning algorithms were evaluated, including Random Forest, XGBoost, and LightGBM, selecting the models with the best predictive performance according to metrics such as MAE, RMSE, and coefficient of determination (R²). The results show that Random Forest offers a high level of accuracy in predicting germination time, while XGBoost performs better in predicting the times associated with the pollination and germination process. 2026-01-01T00:00:00Z https://repositorio.uide.edu.ec/handle/37000/8725 Title: Desarrollo e implementación de un Chatbot basado en LLM para brindar información a la comunidad universitaria de la Universidad Internacional del Ecuador, campus Loja Authors: Jiménez Orellana, Santiago Michael; Palacios Morocho, Milton Ricardo (tutor) 2025-01-01T00:00:00Z https://repositorio.uide.edu.ec/handle/37000/8724 Title: Optimización de las rutas de recolección de residuos y tiempos de flota de recolección en la zona urbana de la ciudad de Yantzaza mediante inteligencia artificial Authors: Torres Pineda, Nelson Eduardo; Palacios Morocho, Milton Ricardo (tutor) Abstract: Este trabajo presenta el desarrollo de un sistema de optimización de rutas de recolección de residuos sólidos en la ciudad de Yantzaza mediante algoritmos de búsqueda y sistemas de información geográfica. El sistema implementa un algoritmo de optimización basado en colonias de hormigas (ACO) que, combinado con herramientas de visualización geoespacial, permite mejorar significativamente la eficiencia operativa del servicio de recolección.La investigación aborda la problemática actual de la gestión de residuos en Yantzaza, donde el crecimiento poblacional del 2,24% anual ha generado mayor producción de desechos, provocando contenedores desbordados, vertederos ilegales y un servicio de recolección ineficiente. El sistema desarrollado optimiza las rutas de recolección considerando variables como capacidad de vehículos, restricciones de tiempo, condiciones de tráfico y variabilidad en la generación de residuos...This work presents the development of an optimization system for solid waste collection routes in the city of Yantzaza using search algorithms and geographic information systems. The system implements an Ant Colony Optimization (ACO) algorithm that, combined with geospatial visualization tools, significantly improves the operational efficiency of the collection service.The research addresses the current waste management problems in Yantzaza, where population growth of 2.24% annually has generated increased waste production, causing overflowing containers, illegal dumps, and inefficient collection service. The developed system optimizes collection routes considering variables such as vehicle capacity, time constraints, traffic conditions, and variability in waste generation... 2025-01-01T00:00:00Z