DPTI - Artículos y ponencias con arbitraje
URI permanente para esta colecciónhttps://hdl.handle.net/11117/672
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Ítem Acceso Abierto Data Mart Design to Increase Transactional Flow of Debit and Credit Card in Peruvian Bodegas(Science and Information Organization, 2025) Morales-Arevalo, Juan C.; Aquise-Gonzales, Erick M.; Carpio-Ore, William Y.; Mendoza-Sáenz, Emmanuel V.; Mazzarri-Rodríguez, Carlos J.; Remotti-Becerra, Erick E.; Medina-LaPlata, Edison H.; Luis F. Luque-VegaThe objective of this research is to design a Data Mart to identify tactical actions and increase the use of POS (points of sale) in the bodega business sector of Lima, Peru. A quantitative approach, using transaction history data, is applied using the Kimball methodology. This involves the ETL (Extract, Transform, Load) process to create a dimensional model and to develop a dashboard to visualize key indicators using Power BI. This solution is expected to improve the detection and analysis of transactional errors, categorized by geographic location and business sector while enhancing decision-making processes. This research improves the transactional flow and digital payment adoption in small businesses, fostering greater financial inclusion in the Peruvian market. Therefore, the methodology and tools to be applied in this research offer a framework as a model for similar contexts, especially in emerging markets, which will allow closing gaps in digital payment adoption and financial inclusion.Ítem Acceso Abierto Design, Implementation, and Control of a Linear Electric Actuator for Educational Mechatronics(MDPI, 2023-09) Nava-Pintor, Jesús A.; Carlos-Mancilla, Miriam A.; Guerrero-Osuna, Héctor A.; Luque-Vega, Luis F.; Carrasco-Navarro, Rocío; Castro-Tapia, Salvador; Mata-Romero, Marcela E.; González-Jiménez, Luis E.; Solís-Sánchez, Luis O.Kinematics is a fundamental topic in engineering, robotics, mechatronics, and control systems and significantly resolves some of these fields’ most pressing issues. It is essential to assess the balance between a topic’s theoretical framework and its empirical validation to succeed in engineering. Educational tools have gained significant attention for their ability to enhance the learning experience by providing the hands-on experiences necessary to assess theoretical frameworks and empirical validations. This paper presents a system incorporating state-of-the-art features, including a fuzzy controller enabling precise control of a linear actuator and a USB camera, to provide an interactive experience. The USB camera captures the position of the actuator, providing realtime visual feedback and allowing the students to validate their theoretical understanding through practical experiments. Precision, accuracy, resolution, and the implementation of the fuzzy controller are measured to evaluate the whole system’s performance. The design, implementation, and control of our educational electrical linear actuator for teaching kinematics concepts contribute to a practical educational tool and advance interactive learning approaches in the field.Ítem Acceso Abierto Development and Evaluation of Solar Radiation Sensor Using Cost-Effective Light Sensors and Machine Learning Techniques(MDPI, 2025-05) Nava-Pintor, Jesús A.; Alcalá-Rodríguez, Uriel E.; Guerrero-Osuna, Héctor A.; Mata-Romero, Marcela E.; Lopez-Neri, Emmanuel; García-Vázquez, Fabián; Solís-Sánchez, Luis O.; Carrasco-Navarro, Rocío; Luque-Vega, Luis F.The accurate measurement of solar radiation is essential for applications in agriculture, renewable energy, and environmental monitoring. Traditional pyranometers provide high-precision readings but are often costly and inaccessible for large-scale deployment. This study explores the feasibility of using low-cost ambient light sensors combined with statistical and machine learning models based on linear, random forest, and support vector regressions to estimate solar irradiance. To achieve this, an Internet of Things-based system was developed, integrating the light sensors with cloud storage and processing capabilities. A dedicated solar radiation sensor (Davis 6450) served as a reference, and results were validated against meteorological API data. Experimental validation demonstrated a strong correlation between sensor-measured illuminance and solar irradiance using the random forest model, achieving a coefficient of determination (R2) of 0.9922, a root mean squared error (RMSE) of 44.46 W/m2, and a mean absolute error (MAE) of 27.12 W/m2. These results suggest that low-cost light sensors, when combined with data-driven models, offer a viable and scalable solution for solar radiation monitoring, particularly in resource-limited regions.Ítem Acceso Abierto Design and Implementation of a Robotic Arm for a MoCap System within Extended Educational Mechatronics Framework(MDPI, 2023-09) Lopez-Neri, Emmanuel; Luque-Vega, Luis F.; González-Jiménez, Luis E.; Guerrero-Osuna, Héctor A.Educational mechatronics aims to be the evolution of educational robotics so it can be identified as a part of the educational paradigm of the university, its academic spaces, infrastructure, and practical activities. The fundamental goal of this framework is to develop the knowledge and skills that the new industrial world, inspired by the latest technologies, necessitates. This work proposes the modular design of a robotic arm aligned with the extended educational mechatronics conceptual framework by designing and implementing educational tools to develop the knowledge and skills required for Industry 4.0. The 3D-printed, low-cost robotic arm is designed to be used in a motion capture system for robotics applications to build kinematics concepts for a learning process. In particular, the instructional design to build the mechatronic concept of a robot workspace is carried out considering the three learning levels: concrete, representational, and abstract. The above demonstrates how the proposed pedagogical methodology can impact Industry 4.0 in the small- and medium-sized enterprises’ context.Ítem Acceso Abierto A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature(MDPI, 2024-03) Mata-Romero, Marcela E.; Simental-Martínez, Omar A.; Guerrero-Osuna, Héctor A.; Luque-Vega, Luis F.; Lopez-Neri, Emmanuel; Ornelas-Vargas, Gerardo; Castañeda-Miranda, Rodrigo; Martínez-Blanco, María R.; Nava-Pintor, Jesús A.; García-Vázquez, FabiánThe remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.Ítem Acceso Abierto Long Short-Term Memory Recurrent Neural Network and Extreme Gradient Boosting Algorithms Applied in a Greenhouse’s Internal Temperature Prediction(MDPI, 2023-11) Esparza-Gómez, Juan M.; Luque-Vega, Luis F.; Guerrero-Osuna, Héctor A.; Carrasco-Navarro, Rocío; García-Vázquez, Fabián; Mata-Romero, Marcela E.; Olvera-Olvera, Carlos A.; Carlos-Mancilla, Miriam A.; Solís-Sánchez, Luis O.One of the main challenges agricultural greenhouses face is accurately predicting environmental conditions to ensure optimal crop growth. However, the current prediction methods have limitations in handling large volumes of dynamic and nonlinear temporal data, which makes it difficult to make accurate early predictions. This paper aims to forecast a greenhouse’s internal temperature up to one hour in advance using supervised learning tools like Extreme Gradient Boosting (XGBoost) and Recurrent Neural Networks combined with Long-Short Term Memory (LSTM-RNN). The study uses the many-to-one configuration, with a sequence of three input elements and one output element. Significant improvements in the R2, RMSE, MAE, and MAPE metrics are observed by considering various combinations. In addition, Bayesian optimization is employed to find the best hyperparameters for each algorithm. The research uses a database of internal data such as temperature, humidity, and dew point and external data such as temperature, humidity, and solar radiation, splitting the data into the year’s four seasons and performing eight experiments according to the two algorithms and each season. The LSTM-RNN model produces the best results for the metrics in summer, achieving an R2 = 0.9994, RMSE = 0.2698, MAE = 0.1449, and MAPE = 0.0041, meeting the acceptability criterion of 2 C hysteresis.Ítem Acceso Abierto Prediction of Internal Temperature in Greenhouses Using the Supervised Learning Techniques: Linear and Support Vector Regressions(MDPI, 2023-07) García-Vázquez, Fabián; Ponce-González, Jesús R.; Guerrero-Osuna, Héctor A.; Carrasco-Navarro, Rocío; Luque-Vega, Luis F.; Mata-Romero, Marcela E.; Martínez-Blanco, María R.; Castañeda-Miranda, Celina L.; Díaz-Flórez, GermánAgricultural greenhouses must accurately predict environmental factors to ensure optimal crop growth and energy management efficiency. However, the existing predictors have limitations when dealing with dynamic, non-linear, and massive temporal data. This study proposes four supervised learning techniques focused on linear regression (LR) and Support Vector Regression (SVR) to predict the internal temperature of a greenhouse. A meteorological station is installed in the greenhouse to collect internal data (temperature, humidity, and dew point) and external data (temperature, humidity, and solar radiation). The data comprises a one year, and is divided into seasons for better analysis and modeling of the internal temperature. The study involves sixteen experiments corresponding to the four models and the four seasons and evaluating the models’ performance using R2, RMSE, MAE, and MAPE metrics, considering an acceptability interval of +-2 °C. The results show that LR models had difficulty maintaining the acceptability interval, while the SVR models adapted to temperature outliers, presenting the highest forecast accuracy among the proposed algorithms.Ítem Acceso Abierto Defining Feasible Joint and Geometric Workspaces through Boundary Functions(MDPI, 2025-05) Lizarraga, Jorge A.; Navarro, Dulce M.; Mata-Romero, Marcela E.; Luque-Vega, Luis F.; González-Jiménez, Luis E.; Carrasco-Navarro, Rocío; Castro-Tapia, Salvador; Guerrero-Osuna, Héctor A.; Lopez-Neri, EmmanuelThis work presents an alternative method for defining feasible joint-space boundaries and their corresponding geometric workspace in a planar robotic system. Instead of relying on traditional numerical approaches that require extensive sampling and collision detection, the proposed method constructs a continuous boundary by identifying the key intersection points of boundary functions. The feasibility region is further refined through centroid-based scaling, addressing singularity issues and ensuring a well-defined trajectory. Comparative analyses demonstrate that the final robot pose and reachability depend on the selected traversal path, highlighting the nonlinear nature of the workspace. Additionally, an evaluation of traditional numerical methods reveals their limitations in generating continuous boundary trajectories. The proposed approach provides a structured method for defining feasible workspaces, improving trajectory planning in robotic systems.Ítem Acceso Abierto Workspace definition in parallelogram manipulators: a theoretical framework based on boundary functions(MDPI, 2025-09) Luque-Vega, Luis F.; Lizarraga, Jorge A.; Navarro, Dulce M.; Navarro, José R.; Carrasco-Navarro, Rocío; Lopez-Neri, Emmanuel; Nava-Pintor, Jesús A.; García-Vázquez, Fabián; Guerrero-Osuna, Héctor A.Robots with parallelogram mechanisms are widely employed in industrial applications due to their mechanical rigidity and precise motion control. However, the analytical definition of feasible workspace regions free from self-collisions remains an open challenge, especially considering the nonlinear and composite nature of such regions. This work introduces a mathematical model grounded in a collision theorem that formalizes boundary functions based on joint variables and geometric constraints. These functions explicitly define the envelope of safe configurations by evaluating relative positions between critical structural components. Using the MinervaBotV3 as a case study, the symbolic joint-space boundaries and their corresponding geometric regions in both 2D and 3D are computed and visualized. The feasible region is refined through centroid-based scaling to introduce safety margins and avoid singularities. The results show that this framework enables analytically continuous workspace representations, improving trajectory planning and reliability in constrained environments. Future work will extend this method to spatial mechanisms and real-time implementations in hybrid robotic systems.Ítem Acceso Abierto Mobile App for Air Quality Guadalajara, Mexico.(International Conference on Air Quality Science and Application, 2018-03) González-Figueredo, Carlos; Egurrola-Hernández, E.A.; DeAlba-Martínez, Hugo; Ramírez-Briseño, R.L.; Magaña-Villegas, ElizabethÍtem Acceso Abierto Hybrid Artificial Neural Network Coupled with Kalman Filters for Air Quality Forecasting in Guadalajara, Mexico(2018-03) González-Figueredo, Carlos; Egurrola-Hernández, E.A.; Ramírez-Briseño, R.L.; DeLosReyes-Corona, A.; DeAlba-Martínez, HugoÍtem Acceso Abierto Deforestation in the Kayabi Indigenous Territory: Simulating and Predicting Land Use and Land Cover Change in the Brazilian Amazon(Instituto Panamericano de Geografía e Historia, 2017-06) DeAlba-Martínez, HugoÍtem Acceso Abierto Hacia la creación de un índice de riesgo para diseñar y evaluar un servicio ecosistémico de regulación de inundaciones en microcuencas urbanas(Universidad Distrital Francisco José de Caldas, 2017-12) DeAlba-Martínez, Hugo; Márquez-Azúa, BerthaÍtem Acceso Abierto Karst development of an evaporitic system and its hydrogeological implications inferred from GIS-based analysis and tracing techniques(Union Internationale de Spéléologie, 2017-05) Gil-Márquez, José M.; Barberá-Fornell, Juan A.; Mudarra-Martínez, Matías; Andreo-Navarro, Bartolomé; Prieto-Mera, Jorge; Sánchez-García, Damián; Rizo-Decelis, Luis D.; Argamasilla-Ruiz, Manuel; DeLaTorre, Beatriz; Nieto-Caldera, José M.Ítem Acceso Abierto Clustering approach applied on an artificial neural network model to predict PM10 in mega cities of México(WIT Press, 2016) Magaña-Villegas, Elizabeth; Carrera-Velueta, Jesús M.; Ramos-Herrera, Sergio; Hernández-Barajas, José R.; González-Figueredo, Carlos; Laines-Canepa, José R.; Valdés-Manzanilla, Arturo; Bautista-Margulis, Raúl G.Ítem Acceso Abierto Estudio comparativo de dos secadores solares híbridos tipo charola durante el proceso de secado de piña(Asociación Nacional de Energía Solar, 2014-10) Roldán-Roa, María E.; Gudiño-Ayala, DavidÍtem Acceso Abierto Estudio del desempeño hidrodinámico y energético de una embarcación solar demostrativa(Asociación Nacional de Energía Solar, 2015-10) Gudiño-Ayala, David; Hermosillo-Villalobos, Juan J.Ítem Acceso Abierto Estudio del comportamiento térmico de un secador solar híbrido(Asociación Nacional de Energía Solar, 2016-10) Gudiño-Ayala, DavidÍtem Acceso Abierto Pineapple drying using a new solar hybrid dryer(Elsevier Ltd., 2014) Gudiño-Ayala, David; Calderón-Topete, ÁngelÍtem Acceso Abierto Antagonistic effect of probiotic strains against two pathogens: Salmonella Typhimurium and E. coli O157:H7(Universidad de Guadalajara (UDG), 2013-01) Arias, Berenice; Reyes, María L.; Navarro, Lilia; Solis, Berenice; Márquez, Mayra; Sánchez, Gloria; Snell-Castro, Raúl; Zúñiga-Rojas, Raquel