In the last few years, many routing protocols have been proposed for vehicular ad hoc networks (VANETs) because of their specific characteristics. Protocols that use several metrics have been shown to be the most adequate to VANETs due to their effectiveness in dealing with dynamic environment changes due to vehicle mobility. Metrics such as distance, density, link stability, speed, and position were selected by the authors for the best proposal. Several surveys of routing proposals have been generated to categorize contributions and their application scenarios, but none of them focused on multimetric approaches. In this paper, we present a review of the routing protocols based on more than one metric to select the best route in a VANET. The main objective of this research was to present the contemporary most frequently used metrics in the different proposals and their application scenarios. This review helps in the selection protocols or the creation of metrics when a new protocol is designed.This survey of multimetric VANET routing protocols employed systematic literature-review (SLR) methodology in four well-knownown databases that allowed to analyze current state-of-the-art proposals. In addition, this paper provides a description of these multimetric routing protocols. Our findings indicate that distance and speed are the most popular and versatile metrics. Finally, we define some possible directions for future research related to the use of this class of protocols.

The Internet of Things (IoT) paradigm is growing, affecting human life and aiming to solve problems in the real world, i.e., in education, healthcare, smart homes, intelligent transportation, and other areas. However, it is a fact that the development of IoT systems is complicated compared to that of traditional software systems, especially in relation to requirements engineering (RE). The RE of IoT systems is not implemented frequently due to their broad aspects, such as the variety of user needs, making these systems difficult to construct. In this sense, the use of loT-based systems has not been well explored by the research community in order to provide well-planned proposals to improve the quality of their performance. In this work, we present a comprehensive and inclusive review of the RE of loT-based systems. To accomplish this, a systematic mapping study (SMS) is presented to evaluate the use of parameters based on the existing literature. SMS is a methodology used for research in the medical field and has recently been implemented in software engineering (SE) to sort and organize research publications to gain knowledge on progress and identify research gaps. In this article, we aim to classify the existing research publications in the current scientific literature regarding RE proposals for IoT software systems and review their implications for future research. This will make it possible to establish lines of research in order to improve the quality of the development of future IoT systems.

La educación es la base de la sociedad. Aun así, es frecuentemente confundida con adiestrar y adoctrinar; aunado a que sufre el desinterés de la familia, lo que facilita el fracaso escolar y provoca una creciente problemática en el rendimiento de los estudiantes desde hace años en México. Principalmente conformada por el triángulo maestro-alumno-padre de familia, requiere que estos elementos se desempeñen de manera adecuada para lograr el éxito académico. En el contexto mexicano, no obstante, la armonía entre las tres partes frecuentemente está corrompida y es ahí dónde surge el problema. Este artículo revisa la literatura de investigación sobre la relación entre la participación de los padres y el rendimiento académico en estudiantes de educación primaria. Se trata de una revisión de 41 estudios publicados entre 2011 y 2019. Los resultados se clasifican en una tabla que incluye lugar y fecha de publicación, autor y principal contribución al área de estudio. Se discuten las coincidencias y divergencias de las publicaciones incluidas en este artículo; así como las tendencias futuras en esta línea de investigación.

The use of educational software offers many advantages but may also become a frustrating experience for teachers and students that lack experience of its use. We presented an evaluation of the use of Maths educational software to support the learning of first-year primary students in the city of Mazatlan, Mexico. One of our reasons was to determine whether the use of Information and Communication Technologies (ICTs) would motivate students and make learning easier, more interesting and even fun. Three surveys were conducted wherein the following people participated: teachers who teach Maths in the first-year of primary school; managers of the computing facilities used in this study; and first-year primary students. Due to time constraints, the three surveys were only applied in three schools, in two shifts in each school. Overall, our study suggests three key aspects for learning to be improved through ICTs, namely: (1) learning activities should be designed considering the use of educational software; (2) learning materials and activities should include guiding material to facilitate learning; and (3) promote learning through play. We propose a few design principles for educational software to support learning better and more effectively.

The effective administration of lithium-ion batteries is key to the performance and durability of electric vehicles (EVs). This systematic mapping study (SMS) thoroughly examines optimization methodologies for battery management, concentrating on the estimation of state of health (SoH), remaining useful life (RUL), and state of charge (SoC). The findings disclose various methods that boost the accuracy and reliability of SoC, including enhanced variants of the Kalman filter, machine learning models like long short-term memory (LSTM) and convolutional neural networks (CNNs), as well as hybrid optimization frameworks that combine Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). For estimating SoH, prevalent data-driven techniques include support vector regression (SVR) and Gaussian process regression (GPR), alongside hybrid models merging machine learning with conventional estimation techniques to heighten predictive accuracy. RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). This study underscores the critical role of integrating advanced filtering techniques, machine learning, and optimization algorithms in developing battery management systems (BMSs) that enhance battery reliability, extend lifespan, and optimize energy management for EVs. Moreover, innovations like hybrid models and synthetic data generation using generative adversarial networks (GANs) further augment the robustness and precision of battery management strategies. This review lays out a thorough framework for future exploration and development in the optimization of EV batteries.

Conversational agents are a piece of software widely used nowadays in several domains, such as e-commerce, customer support, education, among others. To build one, proficiency in distinct areas of knowledge is necessary. Moreover, its development demands the availability of frameworks, tools, and proposals to facilitate its application in several domain areas. Recently, the adoption of models in a software development process has increased through the application of Model-Driven Development in several areas to improve and increase productivity in software development. This work aims to provide state of the art through a Systematic Mapping Study regarding to Model-Driven Development approaches to automate or semi-automate the development of Chatbots. For this study, 429 scientific articles were analyzed, of which, after the inclusion and exclusion criteria, only 20 were considered primary studies.