Clima organizacional y desempeño laboral en los trabajadores de empresas del sector automotriz de la ciudad de Huancayo, 2022

La investigación que tiene el tituló de: “Clima organizacional y desempeño laboral en los trabajadores de empresas del sector automotriz de la ciudad de Huancayo, 2022”. Esta tesis tuvo como intención principal el determinar la relación entre el clima organizacional como primera variable y el desempeño laboral como segunda variable en los trabajadores de empresas del sector automotriz. Se utilizaron como bases teóricas los modelos de clima organizacional y desempeño laboral según el autor consultado (Chiavenato, 2012). Como método general o universal se empleó el método científico y como métodos específicos el descriptivo correlacional, se trata de una investigación de tipo básica, con un alcance descriptivo – correlacional, el tipo de diseño es correlacional con corte transversal. Referente a la población se constituyó por la totalidad de personas que laboran en empresas del sector automotriz en venta y posventa de la ciudad de Huancayo, siendo que la muestra de estudio fue no probabilística dirigida conformada por 95 casos a los cuales se usó la técnica de la encuesta con dos escalas valorativas una para medir la percepción del clima organizacional como primera variable con 17 ítems y para medir la segunda variable contó con 17 ítems, ambas utilizando una escala de tipo Likert. En base a la utilización del estadístico no paramétrico inferencial Rho de Spearman de logró determinar a un nivel significativo que, la primera variable se relaciona en forma directa y moderada con el desempeño laboral de los trabajadores del sector automotriz de la ciudad de Huancayo en el año 2022, siendo que Rho = 0.518 y el nivel de significancia fue de 0.000

Pruning dominated policies in multiobjective Pareto Q-learning

The solution for a Multi-Objetive Reinforcement Learning problem is a set of Pareto optimal policies. MPQ-learning is a recent algorithm that approximates the whole set of all Pareto-optimal deterministic policies by directly generalizing Q-learning to the multiobjective setting. In this paper we present a modification of MPQ-learning that avoids useless cyclical policies and thus improves the number of training steps required for convergence.Supported by: the Spanish Government, Agencia Estatal de Investigaci´on (AEI) and European Union, Fondo Europeo de Desarrollo Regional (FEDER), grant TIN2016-80774-R (AEI/FEDER, UE); and Plan Propio de Investigación de la Universidad de Málaga - Campus de Excelencia Internacional Andalucía Tech

Learning Bayesian Networks for Student Modeling

In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. This increased interest is probably due to the fact that BNs provide a sound methodology for this difficult task. In order to develop a Bayesian student model, it is necessary to define the structure (nodes and links) and the parameters. Usually the structure can be elicited with the help of human experts (teachers), but the difficulty of the problem of parameter specification is widely recognized in this and other domains. In the work presented here we have performed a set of experiments to compare the performance of two Bayesian Student Models, whose parameters have been specified by experts and learnt from data respectively. Results show that both models are able to provide reasonable estimations for knowledge variables in the student model, in spite of the small size of the dataset available for learning the parametersUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Context-aware Assessment Using QR-codes

In this paper we present the implementation of a general mechanism to deliver tests based on mobile devices and matrix codes. The system is an extension of Siette, and has not been specifically developed for any subject matter. To evaluate the performance of the system and show some of its capabilities, we have developed a test for a second-year college course on Botany at the School of Forestry Engineering. Students were equipped with iPads and took an outdoor test on plant species identification. All students were able to take and complete the test in a reasonable time. Opinions expressed anonymously by the students in a survey about the usability of the system and the usefulness of the test were very favorable. We think that the application presented in this paper can broaden the applicability of automatic assessment techniques.The presentation of this work has been co-founded by the Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A temporal difference method for multi-objective reinforcement learning

This work describes MPQ-learning, an temporal-difference method that approximates the set of all non-dominated policies in multi-objective Markov decision problems, where rewards are vectors and each component stands for an objective to maximize. Unlike other approximations to Multi-objective Reinforcement Learning, MPQ-learning does not require additional parameters or preference information, and can be applied to non-convex Pareto frontiers. We also present the results of the application of MPQ-learning to some benchmark problems and compare it to a linearization procedure.This work is partially funded by grants TIN2009-14179 (Spanish Government, Plan Nacional de I+D+i) and TIN2016-80774-R (AEI/FEDER, UE) (Spanish Government, Agencia Estatal de Investigación; and European Union, Fondo Europeo de Desarrollo Regional). Manuela Ruiz-Montiel is funded by the Spanish Ministry of Education through the National F.P.U. Program

PQ-learning: aprendizaje por refuerzo multiobjetivo

En este artí culo describimos y analizamos PQ-learning, un algoritmo para problemas de aprendizaje por refuerzo multiobjetivo. El algoritmo es una extensi ón de Q-learning, un algoritmo para problemas de aprendizaje por refuerzo escalares. Al contrario que otros algoritmos, PQ-learning no requiere informaci ón de preferencias sobre los objetivos, es aplicable a problemas con fronteras de Pareto no convexas y permite recuperar a partir de los Q-valores las secuencias de acci ón correspondientes a diferentes polí ticas Pareto- óptimas. PQ-learning ha sido aplicado a dos problemas pertenecientes a un banco de pruebas propuesto en la literatura de aprendizaje por refuerzo multiobjetivoEste trabajo está parcialmente fi nanciado por el Plan Nacional de I+D+I, proyecto TIN2009-14179 (Gobierno de España, Ministerio de Ciencia e Innovaci ón) y por la Universidad de M álaga, Campus de Excelencia Internacional Andaluc ía Tech. Manuela Ruiz-Montiel disfruta de una beca FPU (Gobierno de España, Ministerio de Educación

Multi-objective dynamic programming with limited precision

This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or even infinite. In order to overcome this difficulty we propose to approximate the set of all solutions by means of a limited precision approach based on White’s multi-objective value-iteration dynamic programming algorithm. We prove that the number of calculated solutions is tractable and show experimentally that the solutions obtained are a good approximation of the true Pareto front.Funding for open access charge: Universidad de Málaga / CBUA. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funded by the Spanish Government, Agencia Estatal de Investigación (AEI) and European Union, Fondo Europeo de Desarrollo Regional (FEDER), Grant TIN2016-80774-R (AEI/FEDER, UE)

Using machine learning techniques for architectural design tracking: An experimental study of the design of a shelter

In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on the quality of the final project and to find and assess common solution pathways in problem-solving behaviour. In this sense, we propose a new methodology for design tracking, based on the application of data analysis and machine learning techniques to data obtained in snapshots of selected design instants. This methodology has been applied in an experimental study, in which fifty-two novice designers were required to design a shelter with the help of a specifically developed computer tool that allowed collecting snapshots of the project at six selected design instants. The snapshots were described according to nine variables. Data analysis and machine learning techniques were then used to extract the knowledge contained in the data. More concretely, supervised learning techniques (decision trees) were used to find strategies employed in higher-quality designs, while unsupervised learning techniques (clustering) were used to find common solution pathways. Results provide evidence that supervised learning techniques allow elucidating the class of the best projects by considering the order of some of the decisions taken. Also, unsupervised learning techniques can find several common problem-solving pathways by grouping projects into clusters that use similar strategies. In this way, our work suggests a novel approach to design tracking, using quantitative analysis methods that can complement and enrich the traditional qualitative approachThis work has been partially funded by the Spanish Government, Agencia Estatal de Investigación (AEI), and the European Union, Fondo Europeo de Desarrollo Regional (FEDER), grant TIN2016-80774-R (AEI/FEDER, UE). Funding for open access charge: Universidad de Málaga/CBUA

Using machine learning techniques for architectural design tracking: an experimental study of the design of a shelter

In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on the quality of the final project and to find and assess common solution pathways in problem-solving behaviour. In this sense, we propose a new methodology for design tracking, based on the application of data analysis and machine learning techniques to data obtained in snapshots of selected design instants. This methodology has been applied in an experimental study, in which fifty-two novice designers were required to design a shelter with the help of a specifically developed computer tool that allowed collecting snapshots of the project at six selected design instants. The snapshots were described according to nine variables. Data analysis and machine learning techniques were then used to extract the knowledge contained in the data. More concretely, supervised learning techniques (decision trees) were used to find strategies employed in higher-quality designs, while unsupervised learning techniques (clustering) were used to find common solution pathways. Results provide evidence that supervised learning techniques allow elucidating the class of the best projects by considering the order of some of the decisions taken. Also, unsupervised learning techniques can find several common problem-solving pathways by grouping projects into clusters that use similar strategies. In this way, our work suggests a novel approach to design tracking, using quantitative analysis methods that can complement and enrich the traditional qualitative approach.This work has been partially funded by the Spanish Government, Agencia Estatal de Investigaci ́on (AEI), and the European Union, Fondo Europeo de Desarrollo Regional (FEDER), grant TIN2016-80774-R (AEI/FEDER, UE). Funding for open access charge: Universidad de Málaga/CBUA

Follow-up of gone away in the accreditation of Master in Infirmary of the BUAP

[EN] Introduction: The follow-up of gone away is an indicator of the relevancy of the Study plan, in case of the Master in Infirmary it is a source of information for the modification of the programs of the subjects as well as the identification of the needs of education continues of the gone away ones. Aims To identify the opinion of the gone away ones from the study plan, that course, requirements of the labor market, professional performance and needs of update. Methodology: Type of study: descriptive, longitudinal. Results: They met 1120egresados, 65 % of the gone away ones obtained employment to six months of concluding the career, the principal activity that they realize is the care of patients, 59 % thinks that the labor coincidence is total with his studies, the economic sector at which they are employed is that of services of health. He thinks that the content of the programs of the subjects as well as the knowledge of the teachers as good, 86. % would return to study the master in infirmary. Conclusion: the opinion of the gone away ones has allowed the extension of the practices, the implementation of the programs of the specialities of infirmary and that the program of the master continues being an educational program of quality when assessors are accredited by the organisms as COMACE CIEES[ES] Introducción: El seguimiento de egresados es un indicador de la pertinencia del Plan de Estudios, en el caso de la Licenciatura en Enfermería es fuente de información para la modificación de los programas de las asignaturas así como la identificación de las necesidades de educación continua de los egresados.Objetivos: Identificar la opinión de los egresados del plan de estudios, que curso, exigencias del mercado laboral, desempeño profesional y necesidades de actualización.Metodología: Tipos de estudio: descriptivo, longitudinal.Resultados: Se entrevistaron 1120egresados, el 65% de los egresados obtuvieron empleo a los seis meses de concluir la carrera, la principal actividad que realizan es el cuidado de pacientes, el 59% opina que es total la coincidencia laboral con sus estudios, el sector económico en el que trabajan es el de servicios de salud. Opina que el contenido de los programas de las asignaturas así como los conocimientos de los docentes como buenos, el 86 % volvería estudiar la licenciatura en enfermería.Conclusión: la opinión de los egresados ha permitido la ampliación de las practicas, la implementación de los programas de las especialidades de enfermería y que el programa de la licenciatura siga siendo un programa educativo de calidad al ser acreditado por los organismos evaluadores como COMACE CIFRUS.Salazar Peña, MTL.; Trujillo De La Cruz, C.; Perez Noriega, E.; Bonilla Luis, MDLL.; Rios Palacios, N.; Morales Espinoza, MDL.; Huesca Gil, JLA. (2014). Seguimiento de egresados en la acreditación de Licenciatura en Enfermeria de la BUAP. En CONFERENCIA INTERNACIONAL INFOACES. UN SISTEMA DE INFORMACIÓN PARA LAS UNIVERSIDADES LATINOAMERICANAS. LIBRO DE ACTAS. Editorial Universitat Politècnica de València. 83-86. http://hdl.handle.net/10251/85894OCS838