Discontinuous Galerkin methods for the Multi-dimensional Vlasov-Poisson problem

We introduce and analyze two new semi-discrete numerical methods for the multi-dimensional Vlasov-Poisson system. The schemes are constructed by combing a discontinuous Galerkin approximation to the Vlasov equation together with a mixed finite element method for the Poisson problem. We show optimal error estimates in the case of smooth compactly supported initial data. We propose a scheme that preserves the total energy of the system.

Utilització del robot mòbil com a eina d'aprenentatge en ensenyaments tècnics

En aquest Projecte de Millora de la Qualitat Docent es descriu el disseny, la construcció i la utilització d’un robot mòbil com a eina docent en titulacions d’Enginyeria. El robot mòbil té com a element de control un PC portàtil convencional per tal de facilitar el procés d’aprenentatge de l’alumnat estigui centrat en l’objectiu de les pràctiques i no en el funcionament i control del robot. A més a més, el robot disposa d’un elevat nombre de sensors i actuadors per tal d’oferir un elevat grau d’interdisciplinaritat.

Multi-stage oligopoly models with nested logit demand structures: A simplifying approach

Solving multi-stage oligopoly models by backward induction can easily become a com- plex task when rms are multi-product and demands are derived from a nested logit frame- work. This paper shows that under the assumption that within-segment rm shares are equal across segments, the analytical expression for equilibrium pro ts can be substantially simpli ed. The size of the error arising when this condition does not hold perfectly is also computed. Through numerical examples, it is shown that the error is rather small in general. Therefore, using this assumption allows to gain analytical tractability in a class of models that has been used to approach relevant policy questions, such as for example rm entry in an industry or the relation between competition and location. The simplifying approach proposed in this paper is aimed at helping improving these type of models for reaching more accurate recommendations.

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market. Keywords: Product introduction, entry, uncertainty, multiproduct firms, automobile JEL codes: L11, L13

Construcción de un modelo Multi- Regional Input-Output (MRIO) medioambiental para Cataluña y el resto de España: Estudio del balance en CO2 incorporado en el comercio

El objetivo de este estudio es analizar el impacto, en emisiones de CO2, de la demanda final de Cataluña en relación a los vínculos comerciales interregionales con el resto de España y el resto del mundo. Este proceso implica el análisis del balance en CO2 incorporado para Cataluña, lo que permitirá evaluar la responsabilidad de la economía catalana respecto a estas emisiones. Para este propósito se construye, para esta determinada desagregación regional, un modelo Multi-Regional Input-Output (MRIO) extendido al medioambiente con sectores verticalmente integrados. La incorporación de la técnica de la integración vertical nos permite un enfoque alternativo para el Balance Neto y un análisis más detallado de los vínculos interregionales entre los diversos sectores productivos, centrado en la responsabilidad última de la demanda final de cada sector en cada región. Hasta el momento, los estudios previos sobre los impactos medioambientales incorporados al comercio español se han centrado principalmente en el ámbito nacional. No obstante, por un lado el comercio interregional con el resto de España en términos monetarios representa cerca de la mitad del comercio exterior catalán. Por otro lado, los distintos metabolismos energéticos de ambas economías tienen como consecuencia una importante diferencia en la intensidad de emisión en la producción de bienes y servicios. Esta situación genera para Cataluña un déficit en el Balance Neto estimado con el resto de España, aún teniendo un importante superávit monetario. De esto se desprende la importancia de integrar el nivel interregional en los estudios de los impactos medioambientales incorporados en el comercio y, en consecuencia, en la planificación y formalización de políticas económicas y ambientales a nivel nacional.

Optimització d'una aplicacio bioinformàtica d'alineament de seqüències executada en processadors multi-core i many-core (GPUs)

Las aplicaciones de alineamiento de secuencias son una herramienta importante para la comunidad científica. Estas aplicaciones bioinformáticas son usadas en muchos campos distintos como pueden ser la medicina, la biología, la farmacología, la genética, etc. A día de hoy los algoritmos de alineamiento de secuencias tienen una complejidad elevada y cada día tienen que manejar un volumen de datos más grande. Por esta razón se deben buscar alternativas para que estas aplicaciones sean capaces de manejar el aumento de tamaño que los bancos de secuencias están sufriendo día a día. En este proyecto se estudian y se investigan mejoras en este tipo de aplicaciones como puede ser el uso de sistemas paralelos que pueden mejorar el rendimiento notablemente.

Anàlisis, disseny i implementació d'una aplicació de gestió d'històries mèdiques per un sistema multi centres mitjançant tecnologia J2EE, i tecnologia de xarxes de bases de dades

El treball final de carrera 'HISMED', es basa en l'anàlisi, disseny, investigació e implementació d'una aplicació dins l'àmbit assistencial sanitari amb la premissa de voler ser un sistema per oferir un servei sanitari de millor qualitat, i crear un entorn en el qual investigadors, laboratoris, metges i personal docent comparteixen dades amb una rellevància cabdal per les seves professions. Oferint-los una eina de consulta molt potent en quant a l'obtenció de dades clíniques, que els permet explotar la informació segons convingui el cas.

Segmentación interactiva multi-clase de personas

La segmentació de persones es molt difícil a causa de la variabilitat de les diferents condicions, com la postura que aquestes adoptin, color del fons, etc. Per realitzar aquesta segmentació existeixen diferents tècniques, que a partir d'una imatge ens retornen un etiquetat indicant els diferents objectes presents a la imatge. El propòsit d'aquest projecte és realitzar una comparativa de les tècniques recents que permeten fer segmentació multietiqueta i que son semiautomàtiques, en termes de segmentació de persones. A partir d'un etiquetatge inicial idèntic per a tots els mètodes utilitzats, s'ha realitzat una anàlisi d'aquests, avaluant els seus resultats sobre unes dades publiques, analitzant 2 punts: el nivell de interacció i l'eficiència.

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task