95 resultados para González Mancebo, José Antonio -- Interviews


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Una versión preliminar de este caso fue presentada como ponencia en el «Second European Conference on Management of Technology» (EUROMOT), celebrado en septiembre de 2006 en Birmingham.

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[EN] The paper analyses a very interesting documentary film about the ancient history of Spain from a franquist, more specifically, falangist point of view (“Nueva Visión de la Historia). It was based on a book about the history of Spain written by a member of Falange, the fascist group in Spain, Antonio Almagro, and was intended as a formative instrument for the youth in the late forties or early fifties. We know only the episodes dealing with Ancient Spain (probably the only ones shot), 25 minutes in all, and it represents an outstanding example of an hyper-nationalistic and hyper-catholic perspective of Spanish history. It also shows a very sympathetic image of José Antonio, the leader of Falange, but, remarkably enough, not of Franco. The film also includes a “theoretical” Introduction about the notion of History.

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In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances that maximize the estimation of distribution algorithm complexity in terms of its success rate. Similarly, instances that minimize the algorithm complexity are evolved. We then identify network measures, computed from the structures of the NK-landscape instances, that have a statistically significant difference between the set of easy and hard instances. The features identified are consistently significant for different values of N and K.

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[ES] El proyecto estudia algoritmos de detección de bordes aplicados a imágenes fotográficas y procedentes de nubes de puntos, posteriormente combina los resultados y analiza las posibilidades de mejora de la solución conjunta.

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Providing on line travel time information to commuters has become an important issue for Advanced Traveler Information Systems and Route Guidance Systems in the past years, due to the increasing traffic volume and congestion in the road networks. Travel time is one of the most useful traffic variables because it is more intuitive than other traffic variables such as flow, occupancy or density, and is useful for travelers in decision making. The aim of this paper is to present a global view of the literature on the modeling of travel time, introducing crucial concepts and giving a thorough classification of the existing tech- niques. Most of the attention will focus on travel time estimation and travel time prediction, which are generally not presented together. The main goals of these models, the study areas and methodologies used to carry out these tasks will be further explored and categorized.

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Tesis leida dentro del Master de "Ingeniería Computacional y Sistemas Inteligentes"

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A partir del análisis del perfil del ingeniero en la sociedad europea, se ha elaborado una encuesta amplia mediante la que se solicitó a las empresas del entorno las competencias y materias que consideraban más importantes en la formación de los ingenieros de las titulaciones ofertadas en la Escuela. A partir de los resultados de dichas encuestas, se establece un perfil requerido a los titulados.

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Duración (en horas): Más de 50 horas. Destinatario: Estudiante y Docente

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Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.