977 resultados para Pattern search
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This paper introduces an encoding of knowledge representation statements as regular languages and proposes a two-phase approach to processing of explicitly declared conceptual information. The idea is presented for the simple conceptual graphs where conceptual pattern search is implemented by the so called projection operation. Projection calculations are organised into off-line preprocessing and run-time computations. This enables fast run-time treatment of NP-complete problems, given that the intermediate results of the off-line phase are kept in suitable data structures. The experiments with randomly-generated, middle-size knowledge bases support the claim that the suggested approach radically improves the run-time conceptual pattern search.
Drying kinetic analysis of municipal solid waste using modified page model and pattern search method
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This work studied the drying kinetics of the organic fractions of municipal solid waste (MSW) samples with different initial moisture contents and presented a new method for determination of drying kinetic parameters. A series of drying experiments at different temperatures were performed by using a thermogravimetric technique. Based on the modified Page drying model and the general pattern search method, a new drying kinetic method was developed using multiple isothermal drying curves simultaneously. The new method fitted the experimental data more accurately than the traditional method. Drying kinetic behaviors under extrapolated conditions were also predicted and validated. The new method indicated that the drying activation energies for the samples with initial moisture contents of 31.1 and 17.2 % on wet basis were 25.97 and 24.73 kJ mol−1. These results are useful for drying process simulation and industrial dryer design. This new method can be also applied to determine the drying parameters of other materials with high reliability.
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The main goal of this paper is to analyze the behavior of nonmono- tone hybrid tabu search approaches when solving systems of nonlinear inequalities and equalities through the global optimization of an appro- priate merit function. The algorithm combines global and local searches and uses a nonmonotone reduction of the merit function to choose the local search. Relaxing the condition aims to call the local search more often and reduces the overall computational e ort. Two variants of a perturbed pattern search method are implemented as local search. An experimental study involving a variety of problems available in the lit- erature is presented.
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Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.
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Locating and identifying points as global minimizers is, in general, a hard and time-consuming task. Difficulties increase in the impossibility of using the derivatives of the functions defining the problem. In this work, we propose a new class of methods suited for global derivative-free constrained optimization. Using direct search of directional type, the algorithm alternates between a search step, where potentially good regions are located, and a poll step where the previously located promising regions are explored. This exploitation is made through the launching of several instances of directional direct searches, one in each of the regions of interest. Differently from a simple multistart strategy, direct searches will merge when sufficiently close. The goal is to end with as many direct searches as the number of local minimizers, which would easily allow locating the global extreme value. We describe the algorithmic structure considered, present the corresponding convergence analysis and report numerical results, showing that the proposed method is competitive with currently commonly used global derivative-free optimization solvers.
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Dissertação para obtenção do Grau de Mestre em Engenharia Civil – Perfil de Construção
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Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.
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The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.
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This article presents a laser tracker position optimization code based on the tracker uncertainty model developed by the National Physical Laboratory (NPL). The code is able to find the optimal tracker positions for generic measurements involving one or a network of many trackers, and an arbitrary set of targets. The optimization is performed using pattern search or optionally, genetic algorithm (GA) or particle swarm optimization (PSO). Different objective function weightings for the uncertainties of individual points, distance uncertainties between point pairs, and the angular uncertainties between three points can be defined. Constraints for tracker position limits and minimum measurement distances have also been implemented. Furthermore, position optimization taking into account of lines-of-sight (LOS) within complex CAD geometry have also been demonstrated. The code is simple to use and can be a valuable measurement planning tool.
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This article presents a laser tracker position optimization code based on the tracker uncertainty model developed by the National Physical Laboratory (NPL). The code is able to find the optimal tracker positions for generic measurements involving one or a network of many trackers, and an arbitrary set of targets. The optimization is performed using pattern search or optionally, genetic algorithm (GA) or particle swarm optimization (PSO). Different objective function weightings for the uncertainties of individual points, distance uncertainties between point pairs, and the angular uncertainties between three points can be defined. Constraints for tracker position limits and minimum measurement distances have also been implemented. Furthermore, position optimization taking into account of lines-of-sight (LOS) within complex CAD geometry have also been demonstrated. The code is simple to use and can be a valuable measurement planning tool.
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Dissertação de Mestrado para a obtenção de grau de Mestre em Engenharia Eletrotécnica Ramo de Automação e Eletrónica Industrial
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Les applications Web en général ont connu d’importantes évolutions technologiques au cours des deux dernières décennies et avec elles les habitudes et les attentes de la génération de femmes et d’hommes dite numérique. Paradoxalement à ces bouleversements technologiques et comportementaux, les logiciels d’enseignement et d’apprentissage (LEA) n’ont pas tout à fait suivi la même courbe d’évolution technologique. En effet, leur modèle de conception est demeuré si statique que leur utilité pédagogique est remise en cause par les experts en pédagogie selon lesquels les LEA actuels ne tiennent pas suffisamment compte des aspects théoriques pédagogiques. Mais comment améliorer la prise en compte de ces aspects dans le processus de conception des LEA? Plusieurs approches permettent de concevoir des LEA robustes. Cependant, un intérêt particulier existe pour l’utilisation du concept patron dans ce processus de conception tant par les experts en pédagogie que par les experts en génie logiciel. En effet, ce concept permet de capitaliser l’expérience des experts et permet aussi de simplifier de belle manière le processus de conception et de ce fait son coût. Une comparaison des travaux utilisant des patrons pour concevoir des LEA a montré qu’il n’existe pas de cadre de synergie entre les différents acteurs de l’équipe de conception, les experts en pédagogie d’un côté et les experts en génie logiciel de l’autre. De plus, les cycles de vie proposés dans ces travaux ne sont pas complets, ni rigoureusement décrits afin de permettre de développer des LEA efficients. Enfin, les travaux comparés ne montrent pas comment faire coexister les exigences pédagogiques avec les exigences logicielles. Le concept patron peut-il aider à construire des LEA robustes satisfaisant aux exigences pédagogiques ? Comme solution, cette thèse propose une approche de conception basée sur des patrons pour concevoir des LEA adaptés aux technologies du Web. Plus spécifiquement, l’approche méthodique proposée montre quelles doivent être les étapes séquentielles à prévoir pour concevoir un LEA répondant aux exigences pédagogiques. De plus, un répertoire est présenté et contient 110 patrons recensés et organisés en paquetages. Ces patrons peuvent être facilement retrouvés à l’aide du guide de recherche décrit pour être utilisés dans le processus de conception. L’approche de conception a été validée avec deux exemples d’application, permettant de conclure d’une part que l’approche de conception des LEA est réaliste et d’autre part que les patrons sont bien valides et fonctionnels. L’approche de conception de LEA proposée est originale et se démarque de celles que l’on trouve dans la littérature car elle est entièrement basée sur le concept patron. L’approche permet également de prendre en compte les exigences pédagogiques. Elle est générique car indépendante de toute plateforme logicielle ou matérielle. Toutefois, le processus de traduction des exigences pédagogiques n’est pas encore très intuitif, ni très linéaire. D’autres travaux doivent être réalisés pour compléter les résultats obtenus afin de pouvoir traduire en artéfacts exploitables par les ingénieurs logiciels les exigences pédagogiques les plus complexes et les plus abstraites. Pour la suite de cette thèse, une instanciation des patrons proposés serait intéressante ainsi que la définition d’un métamodèle basé sur des patrons qui pourrait permettre la spécification d’un langage de modélisation typique des LEA. L’ajout de patrons permettant d’ajouter une couche sémantique au niveau des LEA pourrait être envisagée. Cette couche sémantique permettra non seulement d’adapter les scénarios pédagogiques, mais aussi d’automatiser le processus d’adaptation au besoin d’un apprenant en particulier. Il peut être aussi envisagé la transformation des patrons proposés en ontologies pouvant permettre de faciliter l’évaluation des connaissances de l’apprenant, de lui communiquer des informations structurées et utiles pour son apprentissage et correspondant à son besoin d’apprentissage.
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The present thesis investigates pattern glare susceptibility following stroke and the immediate and prolonged impact of prescribing optimal spectral filters on reading speed, accuracy and visual search performance. Principal observations: A case report has shown that visual stress can occur following stroke. The use of spectral filters and precision tinted lenses proved to be a successful intervention in this case, although the parameters required modification following a further stroke episode. Stroke subjects demonstrate elevated levels of pattern glare compared to normative data values and a control group. Initial use of an optimal spectral filter in a stroke cohort increased reading speed by ~6% and almost halved error scores, findings not replicated in a control group. With the removal of migraine subjects reading speed increased by ~8% with an optimal filter and error scores almost halved. Prolonged use of an optimal spectral filter for stroke subjects, increased reading speed by >9% and error scores more than halved. When the same subjects switched to prolonged use of a grey filter, reading speed reduced by ~4% and error scores increased marginally. When a second group of stroke subjects used a grey filter first, reading speed decreased by ~3% but increased by ~3% with prolonged use of an optimal filter, with error scores almost halving; these findings persisted with migraine subjects excluded. Initial use of an optimal spectral filter improved visual search response time but not error scores in a stroke cohort with migraine subjects excluded. Neither prolonged use of an optimal nor grey filter improved response time or reduced error scores in a stroke group; these findings persisted with the exclusion of migraine subjects.
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We develop a life-cycle model of the labor market in which different worker-firm matches have different quality and the assignment of the right workers to the right firms is time consuming because of search and learning frictions. The rate at which workers move between unemployment, employment and across different firms is endogenous because search is directed and, hence, workers can choose whether to seek low-wage jobs that are easy to find or high-wage jobs that are hard to find. We calibrate our theory using data on labor market transitions aggregated across workers of different ages. We validate our theory by showing that it predicts quite well the pattern of labor market transitions for workers of different ages. Finally, we use our theory to decompose the age profiles of transition rates, wages and productivity into the effects of age variation in work-life expectancy, human capital and match quality.