Desenvolupament d'un videojoc en 3D

La industria de los videojuegos crece exponencialmente y está ya superando a otras industrias punteras del ocio. En este proyecto, nos hemos planteado la realización de un videojuego con visualización en el espacio real 3D. Para la realización del videojuego se ha usado el siguiente software: Blender para diseñar los modelos 3D, C++ como lenguaje de programación para desarrollar el código y un conjunto de librerías básicas para desarrollar un videojuego llamadas Ogre3d (Motor Gráfico). La lógica del movimiento 3D y los choques entre las partículas del juego ha sido diseñada enteramente en este proyecto acorde con las necesidades del videojuego, y de forma compatible a los ficheros de Blender y a las librerías OGRE3D.

Capa de persistencia en .NET

En aquest projecte s'ha implementat una capa de persistència basada en metadades sota la plataforma .NET, utilitzant el llenguatge de programació C#.

Analitzador Gràfic de Xarxa (sniffer)

El sistema desenvolupat és un 'paquet detector', que vol facilitar la tasca de detecció del d'un trànsit de xarxa fora del normal i aconseguir que els resultats puguin ser vistos amb facilitat des d'altres segments de la xarxa.

World Of Wars Android Game

World Of Wars es un videojuego de acción para plataformas Android basándose en los estilos shoot em¿up arcades antiguos pero adaptándolos a los nuevos tiempos y nuevas formas de juego que existen en la actualidad. Se ha utilizado la librería Cocos2D-x, así como el lenguaje de programación C++ para el desarrollo de el.

World of wars : Desarrollo de aplicaciones Android

World of wars es un videojuego de acción para plataformas Android basándose en los estilos shoot 'em up arcade antiguos pero adaptándolos a los nuevos tiempos y nuevas formas de juego. Se ha utilizado la librería Cocos2d-x, así como el lenguaje de programación C++ para su desarrollo.

VariScan Software

VariScan is a software package for the analysis of DNA sequence polymorphisms at the whole genome scale. Among other features, the software:(1) can conduct many population genetic analyses; (2) incorporates a multiresolution wavelet transform-based method that allows capturing relevant information from DNA polymorphism data; and (3) it facilitates the visualization of the results in the most commonly used genome browsers.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

A programming environment having three levels of complexity for mobile robotics = Entorno de programación con tres niveles de complejidad para robótica móvil

This paper presents a programming environment for supporting learning in STEM, particularly mobile robotic learning. It was designed to maintain progressive learning for people with and without previous knowledge of programming and/or robotics. The environment was multi platform and built with open source tools. Perception, mobility, communication, navigation and collaborative behaviour functionalities can be programmed for different mobile robots. A learner is able to programme robots using different programming languages and editor interfaces: graphic programming interface (basic level), XML-based meta language (intermediate level) or ANSI C language (advanced level). The environment supports programme translation transparently into different languages for learners or explicitly on learners’ demand. Learners can access proposed challenges and learning interfaces by examples. The environment was designed to allow characteristics such as extensibility, adaptive interfaces, persistence and low software/hardware coupling. Functionality tests were performed to prove programming environment specifications. UV BOT mobile robots were used in these tests

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

A logic programming framework for possibilistic argumentation: formalization and logical properties

In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied

Combining Generic Programming and Service-Oriented Architectures for the Effective and Timely Development of Complex e-Learning Systems

Peer-reviewed