Rendimiento del sector bancario en Colombia conforme a la divulgación on-line de las políticas de gobierno corporativo

Bogotá (Colombia) : Universidad de La Salle. Facultad de Ciencias Administrativas y Contables. Programa de Contaduría Pública

Moodle plataforma, teknologia berria eredu zaharrekin. Esperientzia bat “Hiznet” on-line graduondokoan

Lan honen egilea Eusko Ikaskuntzaren Asmoz Fundazioaren eta UPV/EHUko Sociología II Sailaren artean antolatzen duten eta Moodle plataforma erabiltzen duen HIZNET on-line graduondokoaren modulu baten irakaslea da. Esperientzia hori abiapuntu, komunikazio honetan hausnarketaren beharra planteatu nahi dugu bereziki bi punturen inguruan: Batetik, unibertsitate alorreko formazioan komunikazio sistema gisa Moodle plataforma bezalako IKT teknologiak erabiltzeak berez hezkuntza praktikaren berrikuntza edota eraldaketa suposatzen ote duen hausnarketa. Bestetik, IKT teknologietan oinarritutako formazio proiektuen eraikuntza sustengatzen dituzten eredu edota paradigmei buruzko hausnarketa.

Rendición de cuentas on-line de los partidos y movimientos políticos en Colombia

Bogotá (Colombia) : Universidad de La Salle. Facultad de Ciencias Administrativas y Contables. Programa de Contaduría Pública

Evaluación de Nutrire®: una herramienta on-line para realizar estudios de evaluación del estado nutricional

Introducción: Nutrire® es un programa informático, fruto de tres proyectos de innovación docente de la Universidad de Granada (España), que permite la valoración del estado nutricional mediante a partir de parámetros antropométricos, dietéticos y bioquímicos. Objetivo: El objetivo de este trabajo es presentar los resultados obtenidos de la evaluación global del programa por alumnos y egresados para poder analizar sus puntos fuertes y débiles que sirvan con posterioridad para realizar las modificaciones oportunas. Material y Métodos: Se ha realizado una encuesta anónima a 128 alumnos de 3 titulaciones de grado y 1 de postgrado de la Universidad de Granada. Se incluye 6 preguntas sobre navegabilidad y diseño y 5 sobre contenidos académicos del programa. Asimismo, se han entrevistado a 20 egresados que lo han utilizado en su actividad profesional. Resultados: La puntuación media obtenida en los alumnos fue de 4,1 sobre 5. Como aspectos positivos destacan: facilidad de uso, incorporación de fotografías de alimentos para elegir el tamaño de ración/porción. Como aspectos de mejora señalan: incorporar más fotos de alimentos, el poder instalar el programa para su uso en un ordenador. Según los egresados, el principal punto fuerte es tener reunido en un solo programa los tres aspectos de la evaluación del estado nutricional. Como puntos débiles señalan la falta de algún nutriente, como los azucares, en la base de datos nutricional. Conclusión: Nutrire® es un programa de fácil utilización, muy bien valorada por los alumnos y por los egresados para realizar estudios de evaluación del estado nutricional.

Issues in On-Line Legal Translation Teaching

A description is given of the structure of, theoretical background of, and experiences gained from, a course in legal English-Spanish translation taught at the University of Alicante.

Radiotórax.es: una herramienta para la evaluación on-line de las capacidades interpretativas en radiografía de tórax.

Introducción La radiografía de tórax es una de las técnicas diagnósticas más importantes ya que aporta gran cantidad de información para el diagnóstico de enfermedades respiratorias y cardíacas. Es la prueba radiológica más usada en urgencias, ampliamente utilizada por especialistas de radiología, por médicos de familia y otras especialidades (intensivistas, neumólogos, anestesistas, internistas, pediatras y cardiólogos). Su correcta interpretación es fundamental, pues con frecuencia influye en la toma de decisión para el manejo del paciente. La autoevaluación, metodología poco explorada en nuestro entorno, es una parte del proceso educativo que fomenta la reflexión sobre las competencias adquiridas del individuo en formación, donde el alumno se evalúa para progresar en su formación y no para superar una nota, eliminar una materia o establecer un orden de prelación con sus compañeros. Justificación y objetivos Los objetivos de este trabajo son: 1) desarrollar una aplicación informática que permita autoevaluar las habilidades interpretativas de la radiografía de tórax emulando una sesión de trabajo de 20 casos; 2) evaluar el funcionamiento e introducir mejoras en fases preliminares, y 3) analizar los hábitos de uso y las posibilidades formativas de la misma. Material y métodos Radiotórax.es es una herramienta Web de libre acceso por toda la comunidad, ubicada en la URL www.radiotorax.es. El sistema pretende emular una sesión de trabajo, informando 20 casos radiológicos , seleccionados aleatoriamente de una base de datos de 400, con una o dos proyecciones de tórax que debe informar disponiendo de una hora. Los informes y resultados se archivan en una base de datos y el usuario dispone de un documento pdf detallado de cada ronda de evaluación que realice. Resultados Se analizan los resultados del global de usuarios registrados en la fase beta de desarrollo de la aplicación ( 30/05/2011 - 31/08/2011) y durante el período comprendido entre el 01/09/2011 hasta el 31/12/2013 de la fase definitiva de la aplicación, que sigue vigente en la actualidad. La autoevaluación en Radiotorax.es guarda correlación con el grado de experiencia y nivel de aprendizaje del usuario, obteniéndose mejores resultados los grupos con mayor experiencia y formación. Además el 75.7% de los usuarios mejoró en evaluaciones sucesivas. Conclusiones Radiotorax.es es un proyecto educativo de interés en pregrado y en la formación continuada de postgrado que persigue como objetivo facilitar la autoevaluación en habilidades interpretativas de radiología de tórax. Es una aplicación gratuita, de acceso libre, que se puede utilizar con cualquier sistema operativo y cualquier navegador Web y permite realizar autoevaluaciones sucesivas, modificando los casos y manteniendo la misma proporción de dificultad. Proporciona un documento pdf con toda la información de cada evaluación completada accesible por el usuario, lo que le permite controlar su evolución en el aprendizaje. Los estudios sobre la interpretación de radiografías de tórax por diferentes colectivos subrayan que la formación es esencial para disminuir el número de errores en la interpretación de radiografías de tórax y resaltan la necesidad de disponer de herramientas formativas de tipo práctico para mejorar la habilidad interpretando radiografías torácicas, como Radiotorax.es.

2 D game ediror on-line : A edição de videojogos em contexto web

Descreve-se, no presente trabalho, os esforços envidados no sentido de criar uma solução informática generalista, para os problemas mais recorrentes do processo de produção de videojogos 20, baseados em sprites, a correr em plataformas móveis. O sistema desenvolvido é uma aplicação web que está inserida no paradigma cloud­computing, usufruindo, portanto, de todas as vantagens em termos de acessibilidade, segurança da informação e manutenção que este paradigma oferece actualmente. Além das questões funcionais, a aplicação é ainda explorada do ponto de vista da arquitetura da implementação, com vista a garantir um sistema com implementação escalável, adaptável e de fácil manutenção. Propõe-se ainda um algoritmo que foi desenvolvido para resolver o problema de obter uma distribuição espacial otimizada de várias áreas retangulares, sem sobreposições nem restrições a nível das dimensões, quer do arranjo final, quer das áreas arranjadas. ABSTRACT: This document describes the efforts taken to create a generic computing solution for the most recurrent problems found in the production of two dimensional, sprite­based videogames, running on mobile platforms. The developed system is a web application that fits within the scope of the recent cloud-computing paradigm and, therefore, enjoys all of its advantages in terms of data safety, accessibility and application maintainability. In addition, to the functional issues, the system is also studied in terms of its internal software architecture, since it was planned and implemented in the perspective of attaining an easy to maintain application, that is both scalable and adaptable. Furthermore, it is also proposed an algorithm that aims to find an optimized solution to the space distribution problem of several rectangular areas, with no overlapping and no dimensinal restrictions, neither on the final arrangement nor on the arranged areas.

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

Integración del alumnado con discapacidad en la formación on-line: una propuesta de accesibilidad universal

El proyecto trata de dar solución de accesibilidad a un curso previamente diseñado de formación oficial on-line. El proyecto pretende dotar de altas condiciones de accesibilidad para todas las personas. En concreto se implantará sobre una plataforma moodle ya establecida al objeto de dotarla del mayor grado de accesibilidad técnica y conceptual en atención al alumnado con discapacidades físicas, psíquicas y sensoriales.

A experiência da ESEV TV - televisão académica on-line

The study focuses on the analysis of the academic experience entitled Television of the Superior School of Education from Viseu (ESEV TV). This academic project has been an online experience since 2011 and comprises a space of experimentation and broadcasting for audiovisual contents. The significance of the digital sphere embodied mostly through the internet places this medium as the ideal platform to the exchange of contents created by the academic community and favors its dissemination to a heterogeneous audience. The implementation of this audiovisual project encourages the collaboration and the creative initiative of those involved in it and, at the same time, intents to improve the capabilities of expression and communication skills of the participants. It is also an objective of this creative initiative to build an historical archive of audiovisual produced material as also as to promote the integration of students, strengthening ethical and moral values and increasing communication strategies. ESEV TV is available to all study cycles from the institution where it is allocated and represents a workshop camp where it is possible to practice techniques and develop knowledge in the television production area. The accomplishment of the project purpose is inextricably dependent on the existence of a working group constantly updated, also multidisciplinary, that aggregates students from different areas. This complex interdependent mission is guided by teachers with knowledge and experience in the audiovisual field. The team work expects to produce an interesting online schedule that reunites, at the same time, information, culture, education and entertainment.

Worst-case bounds for the logarithmic loss of predictors

We investigate on-line prediction of individual sequences. Given a class of predictors, the goal is to predict as well as the best predictor in the class, where the loss is measured by the self information (logarithmic) loss function. The excess loss (regret) is closely related to the redundancy of the associated lossless universal code. Using Shtarkov's theorem and tools from empirical process theory, we prove a general upper bound on the best possible (minimax) regret. The bound depends on certain metric properties of the class of predictors. We apply the bound to both parametric and nonparametric classes ofpredictors. Finally, we point out a suboptimal behavior of the popular Bayesian weighted average algorithm.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Secondary structure prediction with support vector machines

Motivation: A new method that uses support vector machines (SVMs) to predict protein secondary structure is described and evaluated. The study is designed to develop a reliable prediction method using an alternative technique and to investigate the applicability of SVMs to this type of bioinformatics problem. Methods: Binary SVMs are trained to discriminate between two structural classes. The binary classifiers are combined in several ways to predict multi-class secondary structure. Results: The average three-state prediction accuracy per protein (Q3) is estimated by cross-validation to be 77.07 ± 0.26% with a segment overlap (Sov) score of 73.32 ± 0.39%. The SVM performs similarly to the 'state-of-the-art' PSIPRED prediction method on a non-homologous test set of 121 proteins despite being trained on substantially fewer examples. A simple consensus of the SVM, PSIPRED and PROFsec achieves significantly higher prediction accuracy than the individual methods. Availability: The SVM classifier is available from the authors. Work is in progress to make the method available on-line and to integrate the SVM predictions into the PSIPRED server.