POSIBILIDADES DE DESARROLLO PROFESIONAL EN INFORMÁTICA EDUCATIVA USANDO COURSERA

Los cursos masivos en línea (MOOC, por sus siglas en inglés) han impactado notablemente en el contexto educativo mundial en los últimos 5 años. Para los profesionales que trabajan en el mundo de la Informática Educativa, este fenómeno tiene un doble interés. Por una parte, como sujetos del proceso educativo, el estudio de las experiencias y buenas prácticas acumuladas respecto a estos cursos en estos años, puede ser útil para mejorar su práctica educativa. Por otra parte, debido a la constante necesidad de superación, este tipo de cursos puede convertirse en una vía efectiva de estar en la avanzada de la práctica educativa mundial y de intercambiar con profesionales de la educación de otros países. A pesar de esto, no se cuenta con estudios que analicen las posibilidades reales que brindan los MOOC para el desarrollo profesional de especialistas en Informática Educativa. En este trabajo se analizan y clasifican los cursos disponibles en la renombrada plataforma de cursos Coursera, y se han identificado un grupo de ellos que pueden ser muy valiosos para la formación y desarrollo de profesionales en el mundo de la Informática Educativa. Igualmente, se detectan temas importantes que no están suficientemente cubiertos. Con el trabajo, se avanza un paso importante hacia el empleo efectivo de las posibilidades de este tipo de curso en la mejoría de las prácticas educativas mediadas por la informática

Los Cursos Masivos en Línea en Coursera y su Empleo Potencial en los Programas de Ingeniería en América Latina

Massive Open Online Courses have changed the way in which education is conceived, especially in certain subjects and countries. The authors present a quantitative and qualitative analysis of the languages and topics covered by the courses of Coursera, a leader in this field. We demonstrate that there are many courses with potential impact in the engineering careers in Latin-America. The topics are not restricted to Information and Computer Engineering, but they also include Mechanical, Civil, Hydraulic, Electric and Electronic Engineering. We show that several hundreds of courses are relevant for engineering. This number is growing and this is also the case of number of courses in the languages with more importance to our region.Los cursos masivos abierto en línea son un fenómeno reciente que ha revolucionado la forma en que se enfoca la educación superior a nivel mundial, fundamentalmente en ciertas temáticas y para los países más desarrollados. En este trabajo se realiza un análisis cuantitativo y cualitativo de los idiomas y temáticas de los cursos que se ofertan en la plataforma Coursera, que es hoy una de las más importantes. Los resultados demuestra que son grandes las potencialidades de la actual oferta educativa de este tipo de cursos para ser empleado en las carreras de ingeniería en América Latina, no solo en el área de la Ingeniería en Informática o Computación, sino en otras ingenierías como son los casos de las Ingeniería Mecánica, Civil, Hidráulica, Eléctrica y Electrónica

Experiences in Operations Research course in Software Engineering degree

El trabajo muestra las principales experiencias de los profesores de la asignatura Investigación de Operaciones en la Facultad de Ingeniería Informática de la CUJAE entre los cursos 2015-16 y 2018-19. La asignatura en estos cursos fue concebida hacia la búsqueda de un aprendizaje desarrollador por parte del estudiante, su formación como un profesional capaz de aprender por sí mismo, así como hacia su desarrollo integral como profesional de la Informática. Se muestran los resultados de los análisis realizados en cursos previos y los resultados docentes alcanzados por los estudiantes, así como algunas observaciones correspondientes a los cursos en cuestión. Para realizar los análisis mencionados, fueron aplicadas múltiples encuestas, tanto a estudiantes de cursos anteriores (para determinar las principales dificultades), como a los estudiantes que han recibido el nuevo diseño (con el fin de valorar su calidad y cumplimiento de los objetivos deseados). Con este mismo fin, se comparan la calidad de ambos diseños de la asignatura a partir de los resultados de los Exámenes Finales. Tanto las encuestas de opinión como los resultados docentes muestran como el nuevo diseño logra mayor motivación e interés en los estudiantes, así como aumentar la calidad de las calificaciones sin disminuir las exigencias.This work presents the main experiences of the professors of Operations Research in the Faculty of Informatics Engineering of CUJAE between the courses 2015-16 and 2018-19. This subject in these courses was conceived towards the search of a developer learning on the part of the student, the training as a professional capable of learning by themselves, as well as towards their integral development as a computer professional. The results of the analysis carried out in previous courses and the teaching results achieved by the students are shown, as well as some observations corresponding to the courses in question. To carry out the aforementioned analyzes, multiple surveys were applied, both to students from previous courses (to determine the main difficulties), and to students who have received the new design (in order to assess its quality and compliance with the desired objectives). For the same purpose, the quality of both designs of the subject are compared in terms of the results of the Final Exams. Both, opinion and teaching results show how the new design achieves greater motivation and interest in students, as well as an increasing quality of grades without reducing demands.Facultad de Informátic

Extensión del concepto de utopía para el problema de la agregación de rankings sin empates

The use of rankings and how to aggregate or summarize them has received increasing attention in various fields: bibliometrics, web search, data mining, statistics, educational quality, and computational biology. For the Optimal Bucket Order Problem, the concept of Utopian Matrix was recently introduced: an ideal and not necessarily feasible solution with an unsurpassed quality for the feasible solutions of the problem. This work proposes an extension of the notion of Utopian Matrix to the Rank Aggregation Problem in which ties are not allowed between elements in the output ranking. Beyond the extension that is direct, the work focuses on studying its usefulness as an idealization or super optimal solution. As the Rank Aggregation Problem can be solved exactly based on its definition as an Integer Linear Programming Problem, an experimental study is presented where it is analyzed the relationship that exists between utopian (and anti utopian) values and the optimal solution in several instances solved by using the open source software SCIP. Among the 47 instances analyzed, in 19 the Utopian Value turned out to be equal to the optimal value (40.43 % feasibility) and in 18 the Anti Utopian Value also turned out to be feasible (38.00 %). This experimental study demonstrates the usefulness of utopian and anti utopian values to be considered as extreme values in the Rank Aggregation Problem, thus being able to find higher and lower bounds for optimization very quickly.El uso de los rankings y la forma de agregarlos o resumirlos ha recibido una atención creciente en diversos campos: bibliometría, búsquedas web, minería de datos, estadística, calidad educativa y biología computacional. Para el Problema de Ordenamiento Óptimo con empates fue introducido recientemente el concepto de Matriz Utópica: una solución ideal y no necesariamente factible con una calidad insuperable para las soluciones factibles del problema. Este trabajo propone una extensión de la noción de Matriz Utópica para el Problema de Agregación de Rankings en que no se permiten empates entre elementos en el ranking de salida. Más allá de la extensión que es directa, el trabajo se centra en estudiar su valor como idealización o solución súper óptima. Como el Problema de Agregación de Rankings puede resolverse de forma exacta a partir de su definición como Problema de Programación Lineal Entera, se presenta un estudio experimental donde se analiza la relación que existe entre los valores utópicos (y anti utópicos) y la solución óptima en instancias resueltas con la ayuda del software de código abierto SCIP. Entre las 47 instancias analizadas, en 19 el Valor Utópico resultó ser igual al valor óptimo (40,43 % de factibilidad) y en 18 el Valor Anti Utópico también resultó ser factible (38,00 %). Este estudio experimental demuestra la utilidad de los valores utópicos y anti utópicos para ser considerados como valores extremos en el Problema de Agregación de Rankings, pudiendo así encontrase muy rápidamente cotas superiores e inferiores para la optimización

Sign Languague Recognition without frame-sequencing constraints: A proof of concept on the Argentinian Sign Language

Automatic sign language recognition (SLR) is an important topic within the areas of human-computer interaction and machine learning. On the one hand, it poses a complex challenge that requires the intervention of various knowledge areas, such as video processing, image processing, intelligent systems and linguistics. On the other hand, robust recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of sign language for the hearing population. SLR systems usually employ Hidden Markov Models, Dynamic Time Warping or similar models to recognize signs. Such techniques exploit the sequential ordering of frames to reduce the number of hypothesis. This paper presents a general probabilistic model for sign classification that combines sub-classifiers based on different types of features such as position, movement and handshape. The model employs a bag-of-words approach in all classification steps, to explore the hypothesis that ordering is not essential for recognition. The proposed model achieved an accuracy rate of 97% on an Argentinian Sign Language dataset containing 64 classes of signs and 3200 samples, providing some evidence that indeed recognition without ordering is possible.Comment: IBERAMIA 201

LSA64: An Argentinian Sign Language Dataset

Automatic sign language recognition is a research area that encompasses human-computer interaction, computer vision and machine learning. Robust automatic recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of sign language to the hearing population. Sign languages differ significantly in different countries and even regions, and their syntax and semantics are different as well from those of written languages. While the techniques for automatic sign language recognition are mostly the same for different languages, training a recognition system for a new language requires having an entire dataset for that language. This paper presents a dataset of 64 signs from the Argentinian Sign Language (LSA). The dataset, called LSA64, contains 3200 videos of 64 different LSA signs recorded by 10 subjects, and is a first step towards building a comprehensive research-level dataset of Argentinian signs, specifically tailored to sign language recognition or other machine learning tasks. The subjects that performed the signs wore colored gloves to ease the hand tracking and segmentation steps, allowing experiments on the dataset to focus specifically on the recognition of signs. We also present a pre-processed version of the dataset, from which we computed statistics of movement, position and handshape of the signs.Comment: Published in CACIC XXI

Proactive local search based on fdc

This paper introduces a proactive version of Hill Climbing (or Local Search). It is based on the identification of the best neighborhood through the repeated application of mutations and the evaluation of theses neighborhood by using FDC (Fitness Distance Correlation). The best neighborhood is used during a time window, and then the analysis is repeated. An experimental study was conducted in 28 functions on binary strings. The proposed algorithm achieves good performance compared to other metaheuristics (Evolutionary Algorithms, Great Deluge Algorithm, Threshold Accepting, and RRT)

LSA64: An Argentinian Sign Language Dataset

Automatic sign language recognition is a research area that encompasses human-computer interaction, computer vision and machine learning. Robust automatic recognition of sign language could assist in the translation process and the integration of hearing-impaired people, as well as the teaching of sign language to the hearing population. Sign languages differ significantly in different countries and even regions, and their syntax and semantics are different as well from those of written languages. While the techniques for automatic sign language recognition are mostly the same for different languages, training a recognition system for a new language requires having an entire dataset for that language. This paper presents a dataset of 64 signs from the Argentinian Sign Language (LSA). The dataset, called LSA64, contains 3200 videos of 64 different LSA signs recorded by 10 subjects, and is a first step towards building a comprehensive research-level dataset of Argentinian signs, specifically tailored to sign language recognition or other machine learning tasks. The subjects that performed the signs wore colored gloves to ease the hand tracking and segmentation steps, allowing experiments on the dataset to focus specifically on the recognition of signs.XIII Workshop Bases de datos y Minería de Datos (WBDMD).Red de Universidades con Carreras en Informática (RedUNCI

JPEG encoder hardware software partitioning using stochastic hill climbing optimization technique

La partición hardware/software es una etapa clave dentro del proceso de co-diseño de los sistemas embebidos. En esta etapa se decide qué componentes serán implementados como co-procesadores de hardware y qué componentes serán implementados en un procesador de propósito general. La decisión es tomada a partir de la exploración del espacio de diseño, evaluando un conjunto de posibles soluciones para establecer cuál de estas es la que mejor balance logra entre todas las métricas de diseño. Para explorar el espacio de soluciones, la mayoría de las propuestas, utilizan algoritmos metaheurísticos; destacándose los Algoritmos Genéticos, Recocido Simulado. Esta decisión, en muchos casos, no es tomada a partir de análisis comparativos que involucren a varios algoritmos sobre un mismo problema. En este trabajo se presenta la aplicación de los algoritmos: Escalador de Colinas Estocástico y Escalador de Colinas Estocástico con Reinicio, para resolver el problema de la partición hardware/software. Para validar el empleo de estos algoritmos se presenta la aplicación de este algoritmo sobre un caso de estudio, en particular la partición hardware/software de un codificador JPEG. En todos los experimentos es posible apreciar que ambos algoritmos alcanzan soluciones comparables con las obtenidas por los algoritmos utilizados con más frecuencia.Hardware/software partitioning is a key task for embedded system co-design. The goal of this task is to decide which components of an application will be executed in a general purpose processor (software) and which ones on a specific hardware. To support this decision a design space exploration is executed, by the evaluation of several solutions to establish the best trade-off reached. To accomplish this task, metaheuristics algorithms are used by the most proposals; highlighting Genetic Algorithms and Simulated Annealing. Many times this decision is not taken by a comparative study over several algorithms. In this article the application of Stochastic Hill Climbing and Restart Stochastic Hill Climbing for solving the hardware/software partitioning problem is presented. A case study of JPEG encoder is presented. The results show that comparable solutions are reached by those algorithms

Lexicographic Methods for Fuzzy Linear Programming

Fuzzy Linear Programming (FLP) has addressed the increasing complexity of real-world decision-making problems that arise in uncertain and ever-changing environments since its introduction in the 1970s. Built upon the Fuzzy Sets theory and classical Linear Programming (LP) theory, FLP encompasses an extensive area of theoretical research and algorithmic development. Unlike classical LP, there is not a unique model for the FLP problem, since fuzziness can appear in the model components in different ways. Hence, despite fifty years of research, new formulations of FLP problems and solution methods are still being proposed. Among the existing formulations, those using fuzzy numbers (FNs) as parameters and/or decision variables for handling inexactness and vagueness in data have experienced a remarkable development in recent years. Here, a long-standing issue has been how to deal with FN-valued objective functions and with constraints whose left- and right-hand sides are FNs. The main objective of this paper is to present an updated review of advances in this particular area. Consequently, the paper briefly examines well-known models and methods for FLP, and expands on methods for fuzzy single- and multi-objective LP that use lexicographic criteria for ranking FNs. A lexicographic approach to the fuzzy linear assignment (FLA) problem is discussed in detail due to the theoretical and practical relevance. For this case, computer codes are provided that can be used to reproduce results presented in the paper and for practical applications. The paper demonstrates that FLP that is focused on lexicographic methods is an active area with promising research lines and practical implications.Spanish Ministry of Economy and CompetitivenessEuropean Union (EU) TIN2017-86647-