Mean square solution of Bessel differential equation with uncertainties

[EN] This paper deals with the study of a Bessel-type differential equation where input parameters (coefficient and initial conditions) are assumed to be random variables. Using the so-called Lp-random calculus and assuming moment conditions on the random variables in the equation, a mean square convergent generalized power series solution is constructed. As a result of this convergence, the sequences of the mean and standard deviation obtained from the truncated power series solution are convergent as well. The results obtained in the random framework extend their deterministic counterpart. The theory is illustrated in two examples in which several distributions on the random inputs are assumed. Finally, we show through examples that the proposed method is computationally faster than Monte Carlo method.This work has been partially supported by the Spanish Ministerio de Economía y Competitividad grant MTM2013-41765-P and by the European Union in the FP7-PEOPLE-2012-ITN Program under Grant Agreement No. 304617 (FP7 Marie Curie Action, Project Multi-ITN STRIKE-Novel Methods in Computational Finance) and Mexican Conacyt.Cortés, J.; Jódar Sánchez, LA.; Villafuerte, L. (2017). Mean square solution of Bessel differential equation with uncertainties. Journal of Computational and Applied Mathematics. 309:383-395. https://doi.org/10.1016/j.cam.2016.01.034S38339530

Solving Riccati time-dependent models with random quadratic coefficient

This paper deals with the construction of approximate solutions of a random logistic differential equation whose nonlinear coefficient is assumed to be an analytic stochastic process and the initial condition is a random variable. Applying p-mean stochastic calculus, the nonlinear equation is transformed into a random linear equation whose coefficients keep analyticity. Next, an approximate solution of the nonlinear problem is constructed in terms of a random power series solution of the associate linear problem. Approximations of the average and variance of the solution are provided. The proposed technique is illustrated through an example where comparisons with respect to Monte Carlo simulations are shown. © 2011 Elsevier Ltd. All rights reserved.This work has been partially supported by the Spanish M.C.Y.T. grants MTM2009-08587, DPI2010-20891-C02-01, Universitat Politecnica de Valencia grant PAID06-09-2588 and Mexican Conacyt.Cortés López, JC.; Jódar Sánchez, LA.; Company Rossi, R.; Villafuerte Altuzar, L. (2011). Solving Riccati time-dependent models with random quadratic coefficient. Applied Mathematics Letters. 24(12):2193-2196. https://doi.org/10.1016/j.aml.2011.06.024S21932196241

Random differential operational calculus: theory and applications

In this article, we obtain a product rule and a chain rule for mean square derivatives. An application of the chain rule to the mean square solution of random differential equations is shown. However, to achieve such mean square differentiation rules, fourth order properties were needed and, therefore, we first studied a mean fourth order differential and integral calculus. Results are applied to solve random linear variable coefficient differential problems

Random differential operational calculus: Theory and applications

A product rule and a chain rule for mean square derivatives are obtained using fourth order properties. Applications to the mean square solution of random differential equations are shown

Extending the deterministic Riemann-Liouville and Caputo operators to the random framework: A mean square approach with applications to solve random fractional differential equations

[EN] This paper extends both the deterministic fractional Riemann¿Liouville integral and the Caputo fractional derivative to the random framework using the mean square random calculus. Characterizations and sufficient conditions to guarantee the existence of both fractional random operators are given. Assuming mild conditions on the random input parameters (initial condition, forcing term and diffusion coefficient), the solution of the general random fractional linear differential equation, whose fractional order of the derivative is ¿ ¿ [0, 1], is constructed. The approach is based on a mean square chain rule, recently established, together with the random Fröbenius method. Closed formulae to construct reliable approximations for the mean and the covariance of the solution stochastic process are also given. Several examples illustrating the theoretical results are included.This work has been partially supported by the Ministerio de Economia y Competitividad grant MTM2013-41765-P. The co-author Prof. L. Villafuerte acknowledges the support by Mexican Conacyt.Burgos, C.; Cortés, J.; Villafuerte, L.; Villanueva Micó, RJ. (2017). Extending the deterministic Riemann-Liouville and Caputo operators to the random framework: A mean square approach with applications to solve random fractional differential equations. Chaos, Solitons and Fractals. 102:305-318. https://doi.org/10.1016/j.chaos.2017.02.008S30531810

Learning Styles and Motivations for Practicing English as a Foreign Language: A Case Study of Role-play in Two Ecuadorian Universities

This action research studies the Ecuadorian university students’ learning styles and motivations to practice English as a Foreign Language through Role-play. The sample is composed of 158 students from two national universities located in the Coastal region of Ecuador. They took part of Role-play practices in the English as a Foreign Language course during 2016-2017. The instruments applied were the Social Software Survey Used with Undergraduate Students; and a questionnaire designed ad hoc, by the research team named Likert Questionnaire Learners’ Motivations for Practicing English through Role-play. The results show participants' openness to cooperative learning and task-based learning. It is concluded that the learning styles that participants prefer is working in groups; situation that favours the implementation of English as a foreign language practices through role-play

Constructing power series solutions for random differential models

En este artículo se construyen soluciones analítico-numéricas de ecuaciones diferenciales lineales aleatorias a través de métodos basados en series de potencias y se dan condiciones suficientes para garantizar la convergencia en media cuadrática de dichas series. A partir de la truncación de las series construidas se calculan aproximaciones de las funciones media y varianza del proceso solución de los modelos diferenciales estudiados. El artículo concluye mostrando diferentes ejemplos ilustrativos donde se comparan los resultados que se obtienen con la técnica aquí desarrollada con respecto a los proporcionados por métodos tipo Monte Carlo.This paper deals with the construction of analytic-numerical solutions of random linear diferential equations by means of a power series method. Suficient conditions for the mean square convergence of the series solution are established. The mean and variance functions of the approximate solution stochastic process are also computed. Lastly, several illustrative examples where the proposed method is compared with respect to Monte Carlo approximations are included.Peer Reviewe

Academic socialization, parental educational expectations, and academic selfâ efficacy among Latino adolescents

This study examined the direct association between parental educational expectations and adolescentsâ academic selfâ efficacy, as well as the moderating influence of parental academic socialization messages. Participants were 148 Latino parentâ adolescent dyads with the majority of Mexican origin (80.4%). Most of the parent participants were mothers (85.8%). Adolescents were 13 (46%) or 14 (54%) years of age, and 53% identified as female. Adolescents reported their academic selfâ efficacy and perceptions of their parentsâ educational expectations; parents reported on their academic socialization messages of shame/pressure and effort regarding academics. The results suggest that, after accounting for parentsâ level of education and immigrant status, parental educational expectations were positively associated with adolescent academic selfâ efficacy. This association was stronger among adolescents whose parents reported transmitting fewer messages of shame/pressure and academic effort. These results point to the importance of nuances in the content and type of academic socialization messages within Latino families.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148265/1/pits22239_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148265/2/pits22239.pd

Numerical solution of random differential models

This paper deals with the construction of a numerical solution of random initial value problems by means of a random improved Euler method. Conditions for the mean square convergence of the proposed method are established. Finally, an illustrative example is included in which the main statistics properties such as the mean and the variance of the stochastic approximation solution process are given. © 2011 Elsevier Ltd.This work has been partially supported by the Spanish M.C.Y.T. grants MTM2009-08587, DPI2010-20891-C02-01, Universidad Politecnica de Valencia grant PAID06-09-2588 and Mexican Conacyt.Cortés López, JC.; Jódar Sánchez, LA.; Villafuerte Altuzar, L.; Company Rossi, R. (2011). Numerical solution of random differential models. Mathematical and Computer Modelling. 54(7):1846-1851. https://doi.org/10.1016/j.mcm.2010.12.037S1846185154

Random fractional generalized Airy differential equations: A probabilistic analysis using mean square calculus

[EN] The aim of this paper is to study a generalization of fractional Airy differential equations whose input data (coefficient and initial conditions) are random variables. Under appropriate hypotheses assumed upon the input data, we construct a random generalized power series solution of the problem and then we prove its convergence in the mean square stochastic sense. Afterwards, we provide reliable explicit approximations for the main statistical information of the solution process (mean, variance and covariance). Further, we show a set of numerical examples where our obtained theory is illustrated. More precisely, we show that our results for the random fractional Airy equation are in full agreement with the corresponding to classical random Airy differential equation available in the extant literature. Finally, we illustrate how to construct reliable approximations of the probability density function of the solution stochastic process to the random fractional Airy differential equation by combining the knowledge of the mean and the variance and the Principle of Maximum Entropy.This work has been partially supported by the Ministerio de Economia y Competitividad grant MTM2017-89664-P. The authors express their deepest thanks and respect to the editors and reviewers for their valuable comments.Burgos-Simon, C.; Cortés, J.; Debbouche, A.; Villafuerte, L.; Villanueva Micó, RJ. (2019). Random fractional generalized Airy differential equations: A probabilistic analysis using mean square calculus. Applied Mathematics and Computation. 352:15-29. https://doi.org/10.1016/j.amc.2019.01.039S152935