8 resultados para Chromatic adaptation transform

em Universitat de Girona, Spain


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Aquest quadern és el primer lliurement de les Orientacions per a l’adaptació a l’espai europeu d’educació superior. Té l’origen en el debat de la Comissió de seguiment del Pla pilot d’adaptació a l’espai europeu d’educació superior de la UdG i del grup de treball que s’ha constituït l’hivern 2005-2006 expressament per tractar el tema de les competències

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Aquest quadern és el quart lliurement de la Guia per a l'adaptació a l'espai europeo superior. Té l'origen en el debat de la Comissió de Seguiment del Pla Pilot d'adaptació a l'Espai Europeu d'Educació Superior de la UdG i del grup de treball que s'ha constituït l'estiu del 2006 expressament per tractar el tema de les activitats d'aprenentatge

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Aquest quadern és el cinquè lliurement de la Guia per a l'adaptació a l'espai europeu d'educació superior. Té l'origen en el debat de la Comissió de Seguiment del Pla pilot d'Adaptació a l'Espai Europeu d'Educació Superior de la UdG i del grup de treball que s'ha constituït expressament per tractar el tema de l'avaluació dels aprenentatges

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Aquest quadern és el sisè lliurament de la Guia per a l'adaptació a l'espai europeu d'educació superior. Té l'origen en el debat de la Comissió de Seguiment del Pla Pilot d'Adaptació a l'Espai Europeu d'Educació Superior de la UdG i del grup de treball que s'ha constituït expressament per tractar el tema de l'avaluació dels aprenentatges

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In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

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Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.