Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

The aim of this research is to propose a methodology to build predictive models of academic performance through characteristics of engineering students in our country and to compare the models using different evaluation metrics. In this study, 228 students who are part of a public University in Mexico participated. Data were collected at the beginning of the course and, by means of three machine learning techniques, the predictive models were built. The characteristics of each model were analyzed and a prediction accuracy of around 65% was achieved. The model with the Naïve Bayes technique was the most suitable for most of the metrics used in the study, mainly to identify students in danger of failure. In addition, it was found that the current average was the most significant characteristic for the prediction of the academic performance of the students participating in the study. The methodology developed can be replicated for other courses and the characteristics of the students can be collected at the beginning of the course or before, allowing the possibility of carrying out intervention strategies for students in danger of failure.

In this article we analyze the importance of statistical literacy on citizens, particularizing in the context of the statistical information generated on the COVID-19 disease in Mexico. The theoretical support of the research is provided by the constructs of enculturation, statistical literacy, and representations, to establish relationships between data. We have used a qualitative approach based on document analysis to identify the relationships and types of representations that are used to communicate information in official technical reports, as well as the review of the basic and high school curriculum. Among the main findings, it is highlighted that the information on COVID-19 is provided mainly through graphs, percentages, averages, models, and risks. Statistical contents to understand the information are integrated into the curriculum; however, the absence of the critical and reflective component pointed out by some models for development of statistical culture stands out.

The purpose of this article is to check the main results of the method that allows the construction of a relative projective resolution of an S-module N given in appendix A of the article [1], and to show an application of this method.It is achieve to show the usefulness of the method, and to put in relevance that the relative projective resolution obtained with the method is comparable to the bar resolution of an algebra because it is provided with chain contracting homotopy.

This article analyzes the dynamic of an extended SEIR model for the spread of COVID-19 considering a system of 7 differential equations whose stages are susceptible, exposed, infected, quarantined, recovered, dead and vaccinated. The necessary and sufficient conditions are determined for non-negativity, delimitation, existence and uniqueness of the solution of the model, local stability of the equilibrium points and the next generation matrix method. The simulations made in Python complement the qualitative analysis of the mathematical model to conclude the behavior of the virus spread over time; the information shown in this work could also be useful for the development of new prevention measures.

In the present research, the epidemiological model SIRD was used to study the spreed of the COVID-19 Pandemic in the Tacna Region. To determine the parameters of the model, the information published through social networks by the Regional Health Directorate of the Tacna Region of Peru was used, which was systematized in an EXCEL matrix and then exported to process the information in the System of Scientific Computing Mathematica. As a result, the graphs corresponding to the model referred to the Susceptible, Infected, Recovered and Deceased individuals from the COVID-19 Pandemic in the Tacna Region were obtained and then the graphs were interpreted in the time interval of the study. Keywords: COVID-19, SIRD epidemiologic model.

In this work, a May-Holling-Tanner ratio-dependent predator-prey model is studied with an alternative food source for the predator, described by a two-dimensional system of ordinary differential equations. We study the existence and uniqueness of the solutions of the mentioned above system. In addition, the boundedness and positivity of these solutions are analyzed and we establish conditions for the local stability of a simplified model, through a differentiable equivalence. Likewise, the Python programming language is used to perform the simulations using the Runge-Kutta numerical method of order four with the aim of showing the different cases of qualitative analysis.

The objective of this article is to develop some results on conformable fractional derivatives, specifically the one known as Khalil’s conformable fractional derivative. Its origin, properties, comparisons with other fractional derivatives and some applications on population grow and Newton law of cooling models are studied.

This article presents a rigorous review of the conformable fractional derivative given by J. E. Napoles in [11], studying its classical properties, as a differential operator. Likewise, applications are given to Physics, specifically to the free fall of bodies and Newton’s law of cooling.

A linear rank inequality is a linear inequality that holds by dimensions of vector spaces over any finite field. A characteristic-dependent linear rank inequality is also a linear inequality that involves dimensions of vector spaces but this holds over finite fields of determined characteristics, and does not in general hold over other characteristics. In this paper, using as guide binary matrices whose ranks depend on the finite field where they are defined, we show a theorem which explicitly produces characteristic-dependent linear rank inequalities; this theorem generalizes results previously obtained in the literature.

In this article, we prove the existence and uniqueness of the solution of the homogeneous  generalized Schrödinger equation of order m in the periodic distributional space P0, where m is an even number not a multiple of four. Furthermore, we prove that the solution depends continuously respect to the initial data in P0. Introducing a family of weakly continuous operators, we prove that this family is a group in P0. Then, with this family of operators, we get a fine version of the existence and dependency continuous theorem obtained. Finally, we give the conclusions and remarks derived from this study.