59 resultados para Hybrid constraint methods
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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21th Annual Conference of the International Group for Lean Construction (IGLC 21), July 2013, Fortaleza, Brazil
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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As an introduction to a series of articles focused on the exploration of particular tools and/or methods to bring together digital technology and historical research, the aim of this paper is mainly to highlight and discuss in what measure those methodological approaches can contribute to improve analytical and interpretative capabilities available to historians. In a moment when the digital world present us with an ever-increasing variety of tools to perform extraction, analysis and visualization of large amounts of text, we thought it would be relevant to bring the digital closer to the vast historical academic community. More than repeating an idea of digital revolution introduced in the historical research, something recurring in the literature since the 1980s, the aim was to show the validity and usefulness of using digital tools and methods, as another set of highly relevant tools that the historians should consider. For this several case studies were used, combining the exploration of specific themes of historical knowledge and the development or discussion of digital methodologies, in order to highlight some changes and challenges that, in our opinion, are already affecting the historians' work, such as a greater focus given to interdisciplinarity and collaborative work, and a need for the form of communication of historical knowledge to become more interactive.
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Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de Construção
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Dissertação para obtenção do Grau de Mestre em Logica Computicional
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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Dissertação para obtenção do Grau de Doutor em Ambiente
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Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.
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Mesoamerican cultures had a strong tradition of written and pictorial manuscripts, called the codices. In studies already performed it was found the use of Maya Blue, made from a mixture of indigo and a clay called palygorskite, forming an incredibly stable material where the dye is trapped inside the nanotubes of the clay, after heating. However, a bigger challenge lies in the study of the yellows used, for these civilizations might have used this clay-dye mixture to produce their yellow colorants. As a first step, it was possible to provide identification, by non-invasive methods, of two colorants (a flavonoid and a carotenoid). While the flavonoid absorbed between 368-379 nm, the carotenoid would absorb around 455 nm. A temperature study also conducted allowed to set 140ºC as the desirable temperature to heat the samples without degrading them. FT-IR, conventional Raman and SERS allowed us to understand the existence of a reaction between the dyes and the clays (palygorskite and kaolinite), however it is difficult to understand it in a molecular point of view. As a second step, five species of Mexican dyes were selected on the basis of historical sources. The Maya yellow samples were produced adapting the recipe proposed by Reyes-Valerio, supporting the yellow dyes extracted from the dried plants on the clays, with addition of water, and then heated at 140ºC. It was found that the addition of water in palygorskite would increase the pH, hence deprotonating the molecules having a clear negative effect in the color. A second recipe was developed, without the addition of water; however, it was found that the use of water based binders would still alter the color of the samples with palygorskite. In this case, kaolinite without heating yield better results as a Maya yellow hybrid. It was found that the Maya chemistry might not have been the same for all the colors. The Mesoamericans might have found that different dyes could work better to their desires if matched with different clays. It was noticeable that for a clear distinction between flavonoids and carotenoids the reflectance and emission studies suffice, but when clay is added, Raman techniques will perform better. For this reason, conventional Raman and SERS were employed in order to create a database for the Mesoamerican dyestuffs for a future identification.
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Fundação para a Ciência e a Tecnologia - SFRH/BD/27914/2006
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Hybrid knowledge bases are knowledge bases that combine ontologies with non-monotonic rules, allowing to join the best of both open world ontologies and close world rules. Ontologies shape a good mechanism to share knowledge on theWeb that can be understood by both humans and machines, on the other hand rules can be used, e.g., to encode legal laws or to do a mapping between sources of information. Taking into account the dynamics present today on the Web, it is important for these hybrid knowledge bases to capture all these dynamics and thus adapt themselves. To achieve that, it is necessary to create mechanisms capable of monitoring the information flow present on theWeb. Up to today, there are no such mechanisms that allow for monitoring events and performing modifications of hybrid knowledge bases autonomously. The goal of this thesis is then to create a system that combine these hybrid knowledge bases with reactive rules, aiming to monitor events and perform actions over a knowledge base. To achieve this goal, a reactive system for the SemanticWeb is be developed in a logic-programming based approach accompanied with a language for heterogeneous rule base evolution having as its basis RIF Production Rule Dialect, which is a standard for exchanging rules over theWeb.
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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.