20 años de Programa Erasmus

El trabajo recopila y analiza los intercambios de estudiantes que la Escuela Politécnica Superior (EPS) ha realizado en el marco del programa Erasmus durante el período comprendido entre los cursos 2000-2001 y 2007-2008. El análisis de dichos intercambios se realiza desde distintas perspectivas: número y reciprocidad de los intercambios, instituciones, países, titulaciones y actividades que realizan en las instituciones de destino. El objetivo del trabajo era evidenciar las instituciones con las cuales se han venido realizando intercambios y más colaboraciones docentes para poder contactar con los responsables de las mismas con el fin de incrementar la cantidad y la calidad de los intercambios y estudiar la posible colaboración en el desarrollo de títulos de grado y de master con doble titulación. Los resultados del estudio ponen de manifiesto que marchan más estudiantes de los que vienen; que los países con los cuales se han realizado más intercambios son Bélgica y Alemania, que la mayoría de los intercambios corresponden a estudiantes de Ingeniería Industrial y que mayoritariamente la actividad que los estudiantes realizan en la institución de destino es la realización del proyecto final de carrera (PFC). Un análisis más profundo de los resultados obtenidos en cuanto países, instituciones y titulaciones con más intercambios tienen su justificación en la política que se llevó a cabo justo al inicio del programa Erasmus cuando la Escuela Politécnica Superior entró a formar parte de dos redes formadas por instituciones de distintos países dentro del Programa de Cooperación Interuniversitaria (PCI) en el marco del Programa Erasmus. Se constata que las instituciones y las titulaciones con más intercambios coinciden en su mayoría con las instituciones integrantes de dichos PCIs y las titulaciones se imparten en dichas instituciones. El hecho que tanto los estudiantes que vienen a la EPS como los que marchan utilicen su estancia para realizar mayoritariamente su proyecto final de carrera obedece al hecho de que la organización de los planes de estudio y la lengua en la que se imparte la docencia no favorece que los estudiantes cursen créditos de asignaturas en instituciones extranjeras. La conclusión final es que si el análisis realizado en este estudio se hubiese llevado a cabo en algún momento de estos casi 20 años de Programa Erasmus, seguramente se habrían propuesto estrategias para aprovechar al máximo la sinergia creada por el Programa Erasmus y nuestra escuela entraría ahora en una mejor posición en el Espacio Europeo de Educación Superior

Diseñar la internacionalización: perspectivas desde los programas de movilidad de estudiantes

La labor de internacionalización de las universidades españolas en el nuevo marco propiciado por Bolonia supone un gran reto al que debemos enfrentarnos. Las particularidades de los diversos estudios que se imparten en una universidad son un factor relevante que debería ser tomado en consideración en el diseño de los planes de internacionalización de estas universidades, acogiendo las peculiaridades de estos estudios en los instrumentos que definen la estrategia de internacionalización, en la cual los programas de movilidad de estudiantes asumen un papel clave. En este sentido la presente comunicación quiere exponer el planteamiento que se lleva a cabo en los estudios de Derecho en la Facultat de Ciències Jurídiques de la URV, en un programa de movilidad en especial, el Sócrates-Erasmus. Para ello, se ha reflexionado detenidamente sobre cuestiones referidas a las estrategias diseñadas hacia la futura mediata implementación de los nuevos grados y la movilidad de estudiantes

La Participació d'estudiants i professors en una network d'infermeria

El 17th Annual Meeting of the Florence Network (FN) va tenir lloc del 21 al 25 d’abril de 2009 a The Hague University of Applied Sciences (THU) Academy of Health-School of Nursing, sota el lema: “Patient/client centred healthcare”. The Ducht perspective with an international touch”, i es va centrar en l’actual situació dels drets dels pacients a Holanda aplicat en diferents camps de les cures infermeres. L’Escola d’Infermeria de la Universitat de Girona hi va participar amb l’assistència de dues professores i quatre estudiants. E nombre total d’estudiants que varen assistir a la FN es de 47. La procedència dels mateixos en total de 9 països diferents. De tots ells assistien per primer cop 18 persones 4 ho feien per segona vegada i 1 per tercera . Els objectius del treball que es presenta son els següents: 1, Conèixer l’opinió dels estudiants respecte a la seva participació a la Florence Network. 2, Saber quin perfil tenen els universitaris que hi assisteixen 3, Detectar els punts forts i els punts febles que destaquen els estudiants després de participar a la Florence Network

Una Aproximación a la mentoría de alumnos extranjeros en la Universidad de Burgos

El movimiento internacional de estudiantes es en la actualidad, el mayor de la historia contemporánea. España no ha dejado de incrementar la cifra de alumnos tanto comunitarios como extracomunitarios que llegan hasta sus aulas, por lo que los responsables universitarios deben contemplar la acogida humana y académica de estos nuevos integrantes de la comunidad. Una de las maneras con las que se pretende hacer más fácil y amena la integración es a través de otro estudiante que lo acompañe en este proceso. La presente comunicación tiene como objetivo realizar una aproximación a la mentoría de estos alumnos extranjeros, advirtiendo las características diferenciadoras que presenta tanto este tipo de alumno que llega a la Universidad como el mentor que le acompañará en su integración. Se realiza también unan proyección de la posible aplicación del Programa Mentor en la Universidad de Burgos, con especial atención a los alumnos extranjeros

Colour image processing

In the context of the round table the following topics related to image colour processing will be discussed: historical point of view. Studies of Aguilonius, Gerritsen, Newton and Maxwell. CIE standard (Commission International de lpsilaEclaraige). Colour models. RGB, HIS, etc. Colour segmentation based on HSI model. Industrial applications. Summary and discussion. At the end, video images showing the robustness of colour in front of B/W images will be presented

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Laser stripe peak detector for 3D scanners: a FIR filter approach

The accuracy of a 3D reconstruction using laser scanners is significantly determined by the detection of the laser stripe. Since the energy pattern of such a stripe corresponds to a Gaussian profile, it makes sense to detect the point of maximum light intensity (or peak) by computing the zero-crossing point of the first derivative of such Gaussian profile. However, because noise is present in every physical process, such as electronic image formation, it is not sensitive to perform the derivative of the image of the stripe in almost any situation, unless a previous filtering stage is done. Considering that stripe scanning is an inherently row-parallel process, every row of a given image must be processed independently in order to compute its corresponding peak position in the row. This paper reports on the use of digital filtering techniques in order to cope with the scanning of different surfaces with different optical properties and different noise levels, leading to the proposal of a more accurate numerical peak detector, even at very low signal-to-noise ratios

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach