The power factor in electrical power systems is of paramount importance because of the influence on the economic cost of energy consumption as well as the power quality requested by the grid. Low power factor affects both electrical consumers and suppliers due to an increase in current requirements for the installation, bigger sizing of industrial equipment, bigger conductor wiring that can sustain higher currents, and additional voltage regulators for the equipment. In this work, we present a technique for predicting power factor variations in three phase electrical power systems, using machine learning algorithms. The proposed model was developed and tested in medium voltage installations and was found to be fairly accurate thus representing a cost reduced approach for power quality monitoring. The model can be modified to predict the variation of the power factor, taking into account removable energy sources connected to the grid. This new way of analyzing the behavior of the power factor through prediction has the potential to facilitate decision-making by customers, reduce maintenance costs, reduce the probability of injecting disturbances into the network, and above all affords a reliable model of behavior without the need for real-time monitoring, which represents a potential cost reduction for the consumer.

In this article, a fuzzy logic solar tracker was designed and implemented to increase the efficiency of a photovoltaic system by updating the position of the panel throughout the day for optimal use of solar radiation. In the design and implementation of the solar tracker, different control strategies were analyzed, concluding that the fuzzy control satisfies all the requirements of the photovoltaic system with a solar tracker, the developed prototype underwent different tests in a determined period of time to validate the performance of the solar tracker. system compared to one with a fixed position, achieving an increase of 40% compared to fixed solar systems.

Background: The relationship between selfie addiction and narcissism in students at the Universidad Autónoma de Zacatecas (UAZ, Autonomous University of Zacatecas), Mexico, was analysed. The aim of this study was to identify the narcissistic factors associated with students’ selfie taking addiction. Methods: To identify the relationship between narcissism and selfie addiction, the Narcissistic Personality Inventory (Adapted NPI-40) and the Psychometric Selfie Addiction Scale (PSAS) were used. A structural equation model (SEM) was employed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used for structural validation. EFA and CFA confirmed adequate fit and reliability indicators regarding the robust unidimensional structure of the PSAS. Results: The SEM results indicated significant associations between the latent dimensions of the narcissistic traits of superiority, authority, need for admiration, exhibitionism, and exploitation and selfie addiction. This research provides structural and psychometric evidence for the relationship between narcissism and selfie addiction in the Mexican student population, integrating Adapted NPI-40 and PSAS, as well as a parsimonious explanatory structural equation model that demonstrates the relationship between different narcissistic traits and social media practices. Conclusions: The results provide a basis for developing digital literacy interventions for young people and future cross-validations.

This article analyzes different architectures with which a neural network can be developed using computer vision with the objective of detecting traffic accidents. For the development of the software, the Java Script programming language was used, reaching the conclusion that the best architecture to use is a Convolutional Neural Network since it has the capabilities of detecting features within the images. At the same time, a database was developed with the necessary characteristics for the functioning of the neural network. Este artículo analiza diferentes arquitecturas con las que se puede desarrollar una red neuronal mediante visión por ordenador con el objetivo de detectar accidentes de tráfico. Para el desarrollo del software se utilizó el lenguaje de programación Java Script, llegando a la conclusión que la mejor arquitectura a utilizar es una Red Neural Convolucional ya que tiene la capacidad de detectar características dentro de las imágenes. Paralelamente se desarrolló una base de datos con las características necesarias para el funcionamiento de la red neuronal. Este artigo analisa diferentes arquiteturas com as quais uma rede neural pode ser desenvolvida utilizando visão computacional com o objetivo de detectar acidentes de trânsito. Para o desenvolvimento do software foi utilizada a linguagem de programação Java Script, chegando-se à conclusão de que a melhor arquitetura a ser utilizada é uma Rede Neural Convolucional, pois possui capacidade de detectar características dentro das imagens. Paralelamente, foi desenvolvida uma base de dados com as características necessárias ao funcionamento da rede neural.

In this article, a prototype of a low power wind turbine interconnected to the NETWORK and the controlled electronic converter for the rectification of the generated voltage was designed, which is used for the conditioning of the electrical power generated by low power wind systems for the Connection to the electric grid. Using different electronic components and free hardware development boards, the construction of a controlled three-phase rectifier prototype was carried out, divided into 3 modules, the first one in charge of obtaining a reference signal and synchronization of the voltage to be rectified, the second is the control circuit, which performs the time calculations for the activation of the third module, in charge of rectifying the triphasic voltage using thyristors (SCR), in which the moment of activation of the semiconductors can be controlled. Finally, tests of the prototype connected to a wind turbine built by teachers and students of the Technological University of Campeche were carried out, verifying its correct operation in the rectification of the voltage delivered by this generator. En este artículo se diseñó un prototipo de aerogenerador de baja potencia interconectado a la RED y el convertidor electrónico controlado para la rectificación del voltaje generado, el cual se utiliza para el acondicionamiento de la energía eléctrica generada por sistemas eólicos de baja potencia para la conexión. a la red eléctrica. Utilizando diferentes componentes electrónicos y placas de desarrollo de hardware libre se realizó la construcción de un prototipo de rectificador trifásico controlado, dividido en 3 módulos, el primero encargado de obtener una señal de referencia y sincronización del voltaje a rectificar, el segundo es el circuito de control, que realiza los cálculos de tiempo para la activación del tercer módulo, encargado de rectificar la tensión trifásica mediante tiristores (SCR), en el cual se puede controlar el momento de activación de los semiconductores. Finalmente, se realizaron pruebas del prototipo conectado a un aerogenerador construido por docentes y estudiantes de la Universidad Tecnológica de Campeche, verificando su correcto funcionamiento en la rectificación del voltaje entregado por este generador. Neste artigo foi projetado um protótipo de turbina eólica de baixa potência interligada à REDE e o conversor eletrônico controlado para a retificação da tensão gerada, que é utilizado para o condicionamento da energia elétrica gerada por sistemas eólicos de baixa potência para a Conexão à rede elétrica. Utilizando diferentes componentes eletrônicos e placas de desenvolvimento de hardware livre, foi realizada a construção de um protótipo de retificador trifásico controlado, dividido em 3 módulos, sendo o primeiro responsável pela obtenção do sinal de referência e sincronização da tensão a ser retificada, o segundo é o circuito de controle, que realiza os cálculos de tempo para acionamento do terceiro módulo, encarregado de retificar a tensão trifásica através de tiristores (SCR), nos quais pode ser controlado o momento de acionamento dos semicondutores. Por fim, foram realizados testes do protótipo conectado a um aerogerador construído por professores e alunos da Universidade Tecnológica do Campeche, verificando seu correto funcionamento na retificação da tensão entregue por este gerador.

Background: The aim of this study was to analyse whether narcissistic facets and indicators of the need for social validation predict behaviours related to ‘selfie’ addiction among students at the Autonomous University of Zacatecas (UAZ), Mexico, using a preliminary, adapted version of the NPI-40. Methods: An empirical, cross-sectional, non-experimental, correlational-predictive study was conducted with 255 students aged between 14 and 23, selected via convenience sampling. The adjusted NPI-40, the Psychometric Scale on Selfie Addiction, and six indicators of social validation and Instagram usage were employed. The data were analysed using exploratory factor analysis with a polychoric matrix and hierarchical linear regression. Results: The results revealed a preliminary structure comprising three factors and two observed composites of the adjusted NPI-40: authority, agentic grandiosity, exploitation, vanity, and exhibitionism. Behaviours related to selfie addiction were primarily associated with exhibitionism, exploitation, frequency of posting on Instagram and sensitivity to negative comments. The final model explained 29.5% of the variance. Conclusions: It is concluded that the relationship between narcissism, social validation and selfie addiction is not homogeneous and should therefore be analysed by facets.