Repositorio Universidad Europea del Atlántico
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Plataforma virtual de educación Moodle para mejorar el proceso de enseñanza aprendizaje virtual en el modelo educativo por competencias. Estudio de caso: educación secundaria en Perú
No full textEste proyecto se enfoca en la implementación de Moodle en Amazon EC2 para mejorar el aprendizaje basado en competencias en una institución educativa en Cusco, Perú. Buscando superar limitaciones tecnológicas, se persigue elevar la calidad del proceso de enseñanza-aprendizaje. La investigación cuantitativa comprendió un estudio exploratorio para entender las necesidades de la institución, seguido del diseño e implementación de Moodle en Amazon EC2. Resultados clave incluyen el acceso a materiales didácticos y educativos, áreas curriculares, boletas de notas, y planes educativos alineados al Currículo Nacional de la Educación Básica. La plataforma facilitó la interacción dinámica entre estudiantes y profesores, mejorando la participación y colaboración. Se observó una mejora en el desarrollo y desempeño estudiantil, evidenciado por análisis de evaluaciones y seguimiento de progreso. La integración eficiente de Moodle en la nube de Amazon EC2 garantiza accesibilidad y disponibilidad para la comunidad educativa. En conclusión, la implementación de Moodle demostró ser eficaz para mejorar la calidad del proceso de enseñanza-aprendizaje. La interacción dinámica y colaborativa entre estudiantes y profesores mejoró la participación y el compromiso. La integración de Moodle en la nube de Amazon EC2 proporciona una solución tecnológica escalable y eficiente, brindando educación de calidad y fortaleciendo las capacidades de los estudiantes
Control Interno y su incidencia en la gestión administrativa de la empresa TURBONET S.A. Propuesta alternativa, Manual de Control Interno año 2024. Del Cantón Vinces, Provincia Los Ríos – Ecuador.
No full textEsta tesis analiza el impacto del Control Interno en la Gestión Administrativa de TURBONET S.A. del Cantón Vinces, Ecuador. Se identifican las áreas de mejora en los sistemas actuales y se propone un Manual de Control Interno para el 2024. Las recomendaciones están elaboradas con el fin de poder contribuir a la mejora y crecimiento constante de la empresa
Obstacle Detection and Warning System for Visually Impaired Using IoT Sensors
No full textEnsuring safe and independent mobility for visually impaired individuals requires efficient obstacle detection systems. This study introduces an innovative smart knee glove, integrating machine learning technologies for real-time obstacle detection and alerting. The system is equipped with ultrasonic sensor, PIR sensor and a buzzer, with data processing managed by an Arduino Uno microcontroller. To enhance detection accuracy, multiple machine learning algorithms including Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest (RF) and Gaussian Naïve Bayes (GNB) are utilized. A novel Voting Classifier ensemble method is proposed, effectively combining the strengths of these classifiers to maximize performance. Rigorous cross-fold validation ensures robust evaluation under varying conditions. Experimental results demonstrates that the system achieves an impressive 98.34% detection accuracy within a 4-meter range, with high precision, recall and F1 scores. These findings underscore the system’s reliability and potential to empower visually impaired users with safer, more autonomous navigation, marking a significant advancement in obstacle detection technologies
Novel hybrid transfer neural network for wheat crop growth stages recognition using field images
No full textWheat is one of the world’s most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential for precision farming. Determining wheat growth stages accurately is crucial for increasing the efficiency of agricultural yield in wheat farming. Preliminary research identified obstacles in distinguishing between these stages, negatively impacting crop yields. To address this, this study introduces an innovative approach, MobDenNet, based on data collection and real-time wheat crop stage recognition. The data collection utilized a diverse image dataset covering seven growth phases ‘Crown Root’, ‘Tillering’, ‘Mid Vegetative’, ‘Booting’, ‘Heading’, ‘Anthesis’, and ‘Milking’, comprising 4496 images. The collected image dataset underwent rigorous preprocessing and advanced data augmentation to refine and minimize biases. This study employed deep and transfer learning models, including MobileNetV2, DenseNet-121, NASNet-Large, InceptionV3, and a convolutional neural network (CNN) for performance comparison. Experimental evaluations demonstrated that the transfer model MobileNetV2 achieved 95% accuracy, DenseNet-121 achieved 94% accuracy, NASNet-Large achieved 76% accuracy, InceptionV3 achieved 74% accuracy, and the CNN achieved 68% accuracy. The proposed novel hybrid approach, MobDenNet, that synergistically merges the architectures of MobileNetV2 and DenseNet-121 neural networks, yields highly accurate results with precision, recall, and an F1 score of 99%. We validated the robustness of the proposed approach using the k-fold cross-validation. The proposed research ensures the detection of growth stages with great promise for boosting agricultural productivity and management practices, empowering farmers to optimize resource distribution and make informed decisions
Health Benefits and Uses of Beeswax in Medicine
No full textBeeswax (BW) is the substance that forms the structure of a honeycomb, made by bees to store honey. Compared with honey and propolis, beeswax as a by-product possesses several favorable therapeutic properties and is of great interest to the scientific community. In this chapter, the various health benefits of beeswax and its applications are systematically introduced, including mainly the protection of skin disease, wound healing, oxidative damage, antimicrobial activities, and other health applications, with the aim to make more common the use of this by-product for human health. Beeswax, due to its beneficial components and special structural properties, could even assist in preventing and treating some types of cancers or some metabolic diseases, such as nonalcoholic fatty liver disease. Therefore, this chapter aims to update the major scientific works that have highlighted the various health benefits exerted by beeswax in different types of pathological conditions
El Derecho Internacional y la Inviolabilidad Diplomática: Un Estudio de la Crisis Diplomática entre Ecuador y México en 2024
No full textLa tesis examina la crisis diplomática entre Ecuador y México
(2024), como un caso emblemático de transgresión a la
inviolabilidad de sedes diplomáticas. Analiza la responsabilidad internacional estatal, la calificación del asilo diplomático y la naturaleza común de los delitos atribuidos a Jorge Glas. Concluye que Ecuador vulneró obligaciones internacionales, configurando un hecho internacionalmente ilícito según el derecho internacional vigente
The Road to Re-Use of Spice By-Products: Exploring Their Bioactive Compounds and Significance in Active Packaging
Full text linkSpice by-products, often discarded as waste, represent an untapped resource for sustainable packaging solutions due to their unique, multifunctional, and bioactive profiles. Unlike typical plant residues, these materials retain diverse phytochemicals—including phenolics, polysaccharides, and other compounds, such as essential oils and vitamins—that exhibit controlled release antimicrobial and antioxidant effects with environmental responsiveness to pH, humidity, and temperature changes. Their distinctive advantage is in preserving volatile bioactives, demonstrating enzyme-inhibiting properties, and maintaining thermal stability during processing. This review encompasses a comprehensive characterization of phytochemicals, an assessment of the re-utilization pathway from waste to active materials, and an investigation of processing methods for transforming by-products into films, coatings, and nanoemulsions through green extraction and packaging film development technologies. It also involves the evaluation of their mechanical strength, barrier performance, controlled release mechanism behavior, and effectiveness of food preservation. Key findings demonstrate that ginger and onion residues significantly enhance antioxidant and antimicrobial properties due to high phenolic acid and sulfur-containing compound concentrations, while cinnamon and garlic waste effectively improve mechanical strength and barrier attributes owing to their dense fiber matrix and bioactive aldehyde content. However, re-using these residues faces challenges, including the long-term storage stability of certain bioactive compounds, mechanical durability during scale-up, natural variability that affects standardization, and cost competitiveness with conventional packaging. Innovative solutions, including encapsulation, nano-reinforcement strategies, intelligent polymeric systems, and agro-biorefinery approaches, show promise for overcoming these barriers. By utilizing these spice by-products, the packaging industry can advance toward a circular bio-economy, depending less on traditional plastics and promoting environmental sustainability in light of growing global population and urbanization trends
Edge-Based Autonomous Fire and Smoke Detection Using MobileNetV2
Full text linkForest fires pose significant threats to ecosystems, human life, and the global climate, necessitating rapid and reliable detection systems. Traditional fire detection approaches, including sensor networks, satellite monitoring, and centralized image analysis, often suffer from delayed response, high false positives, and limited deployment in remote areas. Recent deep learning-based methods offer high classification accuracy but are typically computationally intensive and unsuitable for low-power, real-time edge devices. This study presents an autonomous, edge-based forest fire and smoke detection system using a lightweight MobileNetV2 convolutional neural network. The model is trained on a balanced dataset of fire, smoke, and non-fire images and optimized for deployment on resource-constrained edge devices. The system performs near real-time inference, achieving a test accuracy of 97.98% with an average end-to-end prediction latency of 0.77 s per frame (approximately 1.3 FPS) on the Raspberry Pi 5 edge device. Predictions include the class label, confidence score, and timestamp, all generated locally without reliance on cloud connectivity, thereby enhancing security and robustness against potential cyber threats. Experimental results demonstrate that the proposed solution maintains high predictive performance comparable to state-of-the-art methods while providing efficient, offline operation suitable for real-world environmental monitoring and early wildfire mitigation. This approach enables cost-effective, scalable deployment in remote forest regions, combining accuracy, speed, and autonomous edge processing for timely fire and smoke detection
The effect of anthocyanins and anthocyanin-rich foods on cognitive function: a meta-analysis of randomized controlled trials
No full textThe rising prevalence of cognitive disorders highlights the urgent need for effective prevention strategies and therapeutic interventions. While adherence to a balanced diet has been associated with a reduced risk of cognitive decline, emerging evidence underscores the potential role of plant-derived bioactive compounds, such as (poly)phenols, with anthocyanins receiving increasing attention. This meta-analysis aimed to evaluate the effect of anthocyanin-rich interventions on cognitive performance. A systematic search of randomized controlled trials (RCTs) assessing the effects of anthocyanin supplementation and cognitive outcomes identified 59 eligible studies. Overall, anthocyanin intervention significantly improved global cognition (standardized mean difference (SMD) = 0.46, 95% CI = 0.30 to 0.63, I2 = 0.0%) compared with controls. Domain-specific analyses further revealed significant benefits for visuospatial processing/reasoning and attention (SMD = 0.37, 95% CI = 0.18 to 0.55, I2 = 76.3%), processing and psychomotor speed (SMD = 0.19, 95% CI = 0.05 to 0.34, I2 = 64.0%), verbal speed and fluency (SMD = 0.21, 95% CI = 0.03 to 0.39, I2 = 30.5%), episodic memory (SMD = 0.30, 95% CI = 0.10 to 0.50, I2 = 75.9%), and working memory (SMD = 0.24, 95% CI = 0.12 to 0.36, I2 = 46.5%). Collectively, these findings suggest that anthocyanin supplementation may improve multiple cognitive domains. Although these results are promising, further well-designed RCTs are needed to validate these outcomes and consolidate the current evidence base
Strawberry as a health promoter: an evidence-based review. Where are we 10 years later?
No full textStrawberries are commonly consumed berries in the Mediterranean area. The fruits present a high concentration of micronutrients and bioactive compounds that confer a plethora of biological activities, including antioxidant and anti-inflammatory properties. This review discusses and updates the recent results of in vivo studies, in animals and humans, focusing on the impact that strawberry consumption has on many common human diseases, such as obesity, cancer, cardiovascular diseases and metabolic disorders; particular attention has been given to the biological effects and molecular mechanisms involved in the beneficial effects exerted by this berry. Evidence suggests these fruits can contribute to preventing or slowing down the progression of many diseases, even though further research is necessary to confirm their long-term effectiveness, to improve patients’ quality of life or prognosis