A Virtual Programming Lab for Moodle with automatic assessment and anti-plagiarism features

[EN] This paper describes VPL, a Virtual Programming Lab module for Moodle, developed at the University of Las Palmas of Gran Canaria (ULPGC) and released for free uses under GNU/GPL license. For the students, it is a simple development environment with auto evaluation capabilities. For the instructors, it is a students' work management system, with features to facilitate the preparation of assignments, manage the submissions, check for plagiarism, and do assessments with the aid of powerful and flexible assessment tools based on program testing, all of that being independent of the programming language used for the assignments and taken into account critical security issues.

SED Stroop Effect Detector prototype

[ES] El Detector de Efectos Stroop (SED - Stroop Effect Detector), es una herramienta informática de asistencia, desarrollada a través del programa de investigación de Desarrollo Tecnológico Social de la Universidad de Las Palmas de Gran Canaria, que ayuda a profesionales del sector neuropsicológico a identificar problemas en la corteza orbitofrontal de un individuo, usándose para ello la técnica ideada por Schenker en 1998. Como base metodológica, se han utilizado los conocimientos adquiridos en las diferentes materias de la adaptación al grado en Ingeniería Informática como Gestión del Software, Arquitectura del Software y Desarrollo de Interfaces de Usuario así como conocimiento adquirido con anterioridad en asignaturas de Programación e Ingeniería del Software I y II. Como para realizar este proyecto sólo el conocimiento informático no era suficiente, he realizado una labor de investigación acerca del problema, teniendo que recopilar información de otros documentos científicos que abordan el tema, consultas a profesionales del sector como son el Doctor Don Ayoze Nauzet González Hernández, neurólogo del hospital Doctor Negrín de Las Palmas de Gran Canaria y el psicólogo Don José Manuel Rodríguez Pellejero que habló de este problema en clase del máster de Formación del Profesorado y que actualmente estoy cursando. Este trabajo presenta el test de Stroop con las dos versiones de Schenker: RCN (Reading Color Names) y NCW (Naming Colored Words). Como norma general, ambas pruebas presentan ante los sujetos estudios palabras (nombres de colores) escritas con la tinta de colores diferentes. De esta forma, el RCN consiste en leer la palabra escrita omitiendo la tonalidad de su fuente e intentando que no nos influya. Por el contrario, el NCW requiere enunciar el nombre del color de la tinta con la que está escrita la palabra sin que nos influya que ésta última sea el nombre de un color.

A subpixel edge detector applied to aortic dissection detection

[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.

Caracterización computacional de un detector de germanio hiperpuro de rango extendido (HPGe- XtRa) con simulación Montecarlo y optimización con un algoritmo evolutivo

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Automatic (data-based) learning of expressive indicators for machine failure detection : a proposal

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Automatic clothes segmentation for soft biometrics

[EN]During the last decade, researchers have verified that clothing can provide information for gender recognition. However, before extracting features, it is necessary to segment the clothing region. We introduce a new clothes segmentation method based on the application of the GrabCut technique over a trixel mesh, obtaining very promising results for a close to real time system. Finally, the clothing features are combined with facial and head context information to outperform previous results in gender recognition with a public database.

Automatic initialization for facial analysis in interactive robotics

[EN]This paper focuses on four different initialization methods for determining the initial shape for the AAM algorithm and their particular performance in two different classification tasks with respect to either the facial expression DaFEx database and to the real world data obtained from a robot’s point of view.

The meccano method for automatic 3-d triangulation and volume parametrization of complex solids

[EN]In this paper we review the novel meccano method. We summarize the main stages (subdivision, mapping, optimization) of this automatic tetrahedral mesh generation technique and we concentrate the study to complex genus-zero solids. In this case, our procedure only requires a surface triangulation of the solid. A crucial consequence of our method is the volume parametrization of the solid to a cube. We construct volume T-meshes for isogeometric analysis by using this result. The efficiency of the proposed technique is shown with several examples. A comparison between the meccano method and standard mesh generation techniques is introduced.-1…

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.