A aproximação fisionômica é o método que busca, a partir do crânio, simular a fotografia de um indivíduo quando em vida. Deve ser empregada como último recurso, na busca de desaparecidos, quando não houver possibilidade de aplicação de um método válido de identificação. O objetivo deste estudo foi obter a aproximação fisionômica, a partir de um crânio seco e de tomografia computadorizada multislice de indivíduos vivos, através da função de base radial hermitiana (FBRH). Constituiu-se também em avaliar o resultado da mesma quanto ao reconhecimento. Na primeira etapa do estudo, foi utilizada a imagem escaneada de um crânio seco, de origem desconhecida, com o intuito de avaliar se a quantidade de pontos obtidos seria suficiente para aplicação da FBRH e consequente reconstrução da superfície facial. Na segunda fase, foram utilizadas três tomografias de indivíduos vivos, para análise da semelhança alcançada entre a face escaneada e as aproximações faciais. Nesta etapa, foi aplicada uma associação de diferentes metodologias já publicadas, para reconstrução de uma mesma região da face, a partir de um mesmo crânio. Na última etapa, foram simuladas situações de reconhecimento com familiares e amigos dos indivíduos doadores das tomografias. Observou-se que a metodologia de FBRH pode ser empregada em aproximação fisionômica. Houve reconhecimento positivo nos três sujeitos estudados, sendo que, em dois deles, os resultados foram ainda mais significativos. Desta forma, conclui-se que a metodologia é rápida, objetiva e proporciona o reconhecimento. Esta permite a criação de múltiplas versões de aproximações fisionômicas a partir do mesmo crânio, o que amplia as possibilidades de reconhecimento. Observou-se ainda que a técnica não exige habilidade artística do profissional. / Facial approximation works by building the visual face up from the skull. This method should be performed as last resort, to carry out for missing persons, when there is no other primary identification method avaliable. The purpose of this study was to introduce a new computerized method with hermite radial basis function (HRBF) for facial approximation using dry skull and computed tomography (CT). The same was also evaluated as a result of the recognition. Firstly, a scan of a dry unidentified skull image was used in order to assess if the amount of points would be sufficient for HRBF methodology and subsequent reconstruction of the facial surface. In second, three CT scans of living individuals were used to evaluate the similarity achieved between the real face scanned and facial approximations. An association of different facial structures reconstruction techniques already published for the same region of the face was applied for the same skull. Moreover, some situations from developed facial approximations were simulated, as recognition by a relative or parent, on a face pool-test. Results from the study showed that the purposed methodology can be used for facial approximation. At the three cases a correct approximation identification as one of a few possible matches to the missing person happened. In two of them, the results were consistently better at identifying the correct approximation. In conclusion, the proposed methodology is fast, objective and reaches visual identification. It is possible to perform multiple versions of the same skull, changing the selected data into the system, which maximizes the chances of establishing recognition of the target face. It was also observed that the technique does not need artistic interpretation.

Made available in DSpace on 2014-12-17T14:55:44Z (GMT). No. of bitstreams: 1 AllanDGA_DISSERT.pdf: 1992696 bytes, checksum: 87d8b1dbc6fe4df6df2f85f90481f9be (MD5) Previous issue date: 2010-01-13 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This study aims to seek a more viable alternative for the calculation of differences in images of stereo vision, using a factor that reduces heel the amount of points that are considered on the captured image, and a network neural-based radial basis functions to interpolate the results. The objective to be achieved is to produce an approximate picture of disparities using algorithms with low computational cost, unlike the classical algorithms / O presente trabalho visa buscar uma alternativa mais vi?vel para o c?lculo das disparidades em imagens de vis?o est?reo, utilizando um fator de salto que reduz a quantidade de pontos que s?o considerados da imagem capturada, e uma rede neural baseada em fun??es de base radial para interpolar os resultados obtidos. O objetivo a ser alcan?ado ? produzir uma imagem de disparidades aproximada da real com algoritmos de baixo custo computacional, diferentemente dos algoritmos tradicionais

Made available in DSpace on 2014-12-17T14:55:44Z (GMT). No. of bitstreams: 1 JoilsonBAR_DISSERT.pdf: 5903616 bytes, checksum: bee0d51eb1c54833e1d9a19364c80c76 (MD5) Previous issue date: 2010-07-30 / The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant / O presente trabalho descreve a utiliza??o de uma ferramenta matem?tica na solu??o de problemas decorrentes da teoria de controle, incluindo a identifica??o, a an?lise do retrato de fase e a estabilidade, bem como a evolu??o temporal da planta de corrente do motor de indu??o. A identifica??o de sistemas ? uma ?rea da modelagem matem?tica que tem como objetivo o estudo de t?cnicas que possam determinar um modelo din?mico na representa??o de um sistema real. A ferramenta utilizada na identifica??o e an?lise do sistema din?mico n?o linear ser? as Fun??es de Base Radial (RBF). O processo ou a planta que ser? utilizada possui um modelo matem?tico desconhecido, mas pertence a uma determinada classe que cont?m uma din?mica interna que pode ser modelada. Ser? apresentada como contribui??es a an?lise da estabilidade assint?tica da RBF. A identifica??o utilizando Fun??es de Base Radial ? demonstrada atrav?s de simula??es computacionais a partir de um conjunto de dados reais obtidos da planta de corrente do motor de indu??o

Neste trabalho é proposta uma plataforma robótica móvel, concebida de maneira modular e hierárquica, visando o estudo de diversos aspectos aplicados à navegação, tanto autônoma quanto semi-autônoma, em ambientes internos. O sistema proposto possibilita a implementação de arquiteturas reativas e híbridas com aprendizagem, sendo a importância e limitações desta última discutidas. Utilizando a plataforma desenvolvida, uma aplicação de navegação robótica com aprendizagem supervisionada é realizada, usando sensores de ultra-som e através de tele-operação. O objetivo é fazer com que o agente associe, em tempo real, suas próprias respostas sensoriais com as ações motoras realizadas pelo tele-operador, permitindo que a tarefa seja repetida autonomamente com alguma generalização. Para realizar tal mapeamento, uma rede de função de base radial (RBF), usando um algoritmo de aprendizado seqüencial, é apresentada e utilizada. / This work presents a mobile robotic platform, built as a modular and hierarchical approach, aiming at the study of several aspects of indoor navigation. The proposed system allows the implementation of reactive and hybrid architectures with learning, for autonomous or semi-autonomous navigation. The importance and limitations of the learning characteristics are discussed. An application of robotic navigation with supervised learning is implemented using ultrasonic sensors and teleoperation. The aim is the agent to associate, in real time, its own sensorial perception to the motor actions realized by a teleoperator, allowing the task to be repeated in an autonomous way, with some generalization. To make the corresponding mapping, a radial basis function network (RBF), trained by a sequential learning algorithm, is presented and used.

As a result of the increase in accessibility of computational resources and the increase in the power of the computers during the last two decades, designers are able to create computer models to simulate the behavior of a complex products. To address global competitiveness, companies are forced to optimize their designs and products. Optimizing the design needs several runs of computationally expensive simulation models. Therefore, using metamodels as an efficient and sufficiently accurate approximate of the simulation model is necessary. Radial basis functions (RBF) is one of the several metamodeling methods that can be found in the literature. The established approach is to add a bias to RBF in order to obtain a robust performance. The a posteriori bias is considered to be unknown at the beginning and it is defined by imposing extra orthogonality constraints. In this thesis, a new approach in constructing RBF with the bias to be set a priori by using the normal equation is proposed. The performance of the suggested approach is compared to the classic RBF with a posteriori bias. Another comprehensive comparison study by including several modeling criteria, such as problem dimension, sampling technique and size of samples is conducted. The studies demonstrate that the suggested approach with a priori bias is in general as good as the performance of RBF with a posteriori bias. Using the a priori RBF, it is clear that the global response is modeled with the bias and that the details are captured with radial basis functions. Multi-objective optimization and the approaches used in solving such problems are briefly described in this thesis. One of the methods that proved to be efficient in solving multi-objective optimization problems (MOOP) is the strength Pareto evolutionary algorithm (SPEA2). Multi-objective optimization of a disc brake system of a heavy truck by using SPEA2 and RBF with a priori bias is performed. As a result, the possibility to reduce the weight of the system without extensive compromise in other objectives is found. Multi-objective optimization of material model parameters of an adhesive layer with the aim of improving the results of a previous study is implemented. The result of the original study is improved and a clear insight into the nature of the problem is revealed.

Philosophiae Doctor - PhD / Many problems in financial world are being modeled by means of differential equation. These problems are time dependent, highly nonlinear, stochastic and heavily depend on the previous history of time. A variety of financial products exists in the market, such as forwards, futures, swaps and options. Our main focus in this thesis is to use the numerical analysis tools to solve some option pricing problems. Depending upon the inter-relationship of the financial derivatives, the dimension of the associated problem increases drastically and hence conventional methods (for example, the finite difference methods or finite element methods) for solving them do not provide satisfactory results. To resolve this issue, we use a special class of numerical methods, namely, the mesh free methods. These methods are often better suited to cope with changes in the geometry of the domain of interest than classical discretization techniques. In this thesis, we apply these methods to solve problems that price standard and non-standard options. We then extend the proposed approach to solve Heston' volatility model. The methods in each of these cases are analyzed for stability and thorough comparative numerical results are provided. / South Africa

Au cours de cette thèse, un modèle potentiel résolvant les équations d’Euler-Zakharov a été développé dans le but de simuler la propagation de vagues et d’états de mer irréguliers et multi-directionnels, du large jusqu’à la côte, sur des bathymétries variables. L’objectif est de représenter les effets non-linéaires et dispersifs le plus précisément possible pour des domainescôtiers bidimensionnels (dans le plan horizontal) de l’ordre de quelques kilomètres.La version 1DH initiale du modèle, résolvant le problème aux limites de Laplace à l’aide de schémas aux différences finies d’ordre élevé dans la direction horizontale combinés à une approche spectrale sur la verticale, a été améliorée et validée. L’implémentation de conditions aux limites de type Dirichlet et Neumann pour générer des vagues dans le domaine a été étudiée en détail. Dans la pratique, une zone de relaxation a été utilisée en complément deces conditions pour améliorer la stabilité du modèle.L’expression analytique de la relation de dispersion a été établie dans le cas d’un fond plat. Son analyse a montré que la représentation des effets dispersifs s’améliorait significativement avec l’augmentation de la résolution sur la direction verticale (i.e. avec le degré maximal de la basede polynômes de Tchebyshev utilisée pour projeter le potentiel des vitesses sur la verticale).Une étude de convergence menée pour des ondes solitaires modérément à fortement non-linéaires a confirmé la convergence exponentielle avec la résolution verticale grâce à l’approche spectrale, ainsi que les convergences algébriques en temps et en espace sur l’horizontale avec des ordres d’environ 4 (ou plus) en accord avec les schémas numériques utilisés.La comparaison des résultats du modèle à plusieurs jeux de données expérimentales a démontré les capacités du modèle à représenter les effets non-linéaires induits par les variations de bathymétrie, notamment les transferts d’énergie entre les composantes harmoniques, ainsi que la représentation précise des propriétés dispersives. Une formulation visco-potentielle a également été implémentée afin de prendre en compte les effets visqueux induits par la dissipation interne et le frottement sur le fond. Cette formulation a été validée dans le cas d’une faible viscosité avec un fond plat ou présentant une faible pente.Dans le but de représenter des champs de vagues 2DH, le modèle a été étendu en utilisant une discrétisation non-structurée (par nuage de points) du plan horizontal. Les dérivées horizontales ont été estimées à l’aide de la méthode RBF-FD (Radial Basis Function-Finite Difference), en conservant l’approche spectrale sur la verticale. Une étude numérique de sensibilité a été menée afin d’évaluer la robustesse de la méthode RBF-FD, en comparant différents types de RBFs, avec ou sans paramètre de forme et l’ajout éventuel d’un polynôme. La version 2DH du modèle a été utilisée pour simuler deux expériences en bassin, validant ainsi l’approche choisie et démontrant son applicabilité pour simuler la propagation 3D des vagues faisant intervenir des effets non-linéaires. Dans le but de réduire le temps de calcul et de pouvoir appliquer le code à des simulations sur de grands domaines, le code a été modifié pour utiliser le solveur linéaire direct en mode parallèle / In this work, a potential flow model based on the Euler-Zakharov equations was developed with the objective of simulating the propagation of irregular and multidirectional sea states from deep water conditions to the coast over variable bathymetry. A highly accurate representation of nonlinear and dispersive effects for bidimensional (2DH) nearshore and coastal domains on the order of kilometers is targeted.The preexisting 1DH version of the model, resolving the Laplace Boundary Value problem using a combination of high-order finite difference schemes in the horizontal direction and a spectral approach in the vertical direction, was improved and validated. The generation of incident waves through the implementation of specific Dirichlet and Neumann boundary conditions was studied in detail. In practice, these conditions were used in combination witha relaxation zone to improve the stability of the model.The linear dispersion relation of the model was derived analytically for the flat bottom case. Its analysis showed that the accuracy of the representation of dispersive effects improves significantly by increasing the vertical resolution (i.e. the maximum degree of the Chebyshev polynomial basis used to project the potential in the vertical). A convergence study conducted for moderate to highly nonlinear solitary waves confirmed the exponential convergence in the vertical dimension owing to the spectral approach, and the algebraic convergence in time and in space (horizontal dimension) with orders of about 4 (or higher) in agreement with the numerical schemes used.The capability of the model to represent nonlinear effects induced by variable bathymetry, such as the transfer of energy between harmonic components, as well as the accurate representation of dispersive properties, were demonstrated with comparisons to several experimental data sets. A visco-potential flow formulation was also implemented to take into account viscous effects induced by bulk viscosity and bottom friction. This formulation was validated inthe limit of small viscosity for mild slope bathymetries.To represent 2DH wave fields in complex nearshore domains, the model was extended using an unstructured discretization (scattered nodes) in the horizontal plane. The horizontal derivatives were estimated using the RBF-FD (Radial Basis Function - Finite Difference) method, while the spectral approach in the vertical remained unchanged. A series of sensitivity tests were conducted to evaluate numerically the robustness of the RBF-FD method, including a comparison of a variety of RBFs with or without shape factors and augmented polynomials. The 2DH version of the model was used to simulate two wave basin experiments, validating the approach and demonstrating the applicability of this method for 3D wave propagation, including nonlinear effects. As an initial attempt to improve the computational efficiency ofthe model for running simulations of large spatial domains, the code was adapted to use a parallelized direct linear solver

Radial basis function methods exhibit several very attractive properties such as a high order convergence of the approximated solution and flexibility to the domain geometry. However the method in its classical formulation becomes impractical for problems with relatively large numbers of degrees of freedom due to the ill-conditioning and dense structure of coefficient matrix. To overcome the latter issue we employ a localisation technique, namely a partition of unity method, while the former issue was previously addressed by several authors and was of less concern in this thesis. In this thesis we develop radial basis function partition of unity methods for partial differential equations arising in financial mathematics and glaciology. In the applications of financial mathematics we focus on pricing multi-asset equity and credit derivatives whose models involve several stochastic factors. We demonstrate that localised radial basis function methods are very effective and well-suited for financial applications thanks to the high order approximation properties that allow for the reduction of storage and computational requirements, which is crucial in multi-dimensional problems to cope with the curse of dimensionality. In the glaciology application we in the first place make use of the meshfree nature of the methods and their flexibility with respect to the irregular geometries of ice sheets and glaciers. Also, we exploit the fact that radial basis function methods are stated in strong form, which is advantageous for approximating velocity fields of non-Newtonian viscous liquids such as ice, since it allows to avoid a full coefficient matrix reassembly within the nonlinear iteration. In addition to the applied problems we develop a least squares radial basis function partition of unity method that is robust with respect to the node layout. The method allows for scaling to problem sizes of a few hundred thousand nodes without encountering the issue of large condition numbers of the coefficient matrix. This property is enabled by the possibility to control the coefficient matrix condition number by the rate of oversampling and the mode of refinement.

Em Computação Gráfica, campos vetoriais possuem diversas aplicações desde a síntese e mapeamento de texturas à animações de fluidos, produzindo efeitos amplamente utilizados na indústria do entretenimento. Para produzir tais campos, é preferível o uso de ferramentas de design em vez de simulações numéricas não só devido ao menor custo computacional mas, principalmente, por prover liberdade ao artista ao sintetizar o campo de acordo com a sua necessidade. Atualmente, na literatura, existem bons métodos de design de campos vetoriais em superfícies de objetos tridimensionais porém, o design no interior desses objetos ainda é pouco estudado, principalmente quando o campo de interesse possui propriedades específicas. O objetivo deste trabalho é desenvolver uma técnica para sintetizar campos vetoriais, com características do movimento de fluidos incompressíveis, no interior de domínios. Em uma primeira etapa, o método consiste na interpolação dos vetores de controle, com uma certa propriedade desejada, em todo o domínio. Posteriormente, o campo obtido é modificado para respeitar a geometria do contorno. / Vector fields are important to an wide range of applications on the field of Computer Graphics, from the synthesis and mapping of textures to fluid animation, producing effects widely used on the entertainment industry. To produce such fields, design tools are prefered over numerical simulations not only for its lower computational cost, but mainly by providing freedom to the artist in the creation process. Nowadays, good methods of vector field design over surfaces exist in literature, however there is only a few studies on the synthesis of vector fields of the interior of objects and even fewer when specific properties of the field are required. This work presents a technique to synthesize vector fields with properties of imcompressible fluids motion in the interior of objects. On a first step, the method consists in interpolating control vectors with a certain desired property throughout the whole domain and later the resulting field is modified to properly fit the boundary geometry of the object.

This thesis deals with neural modeling of electromagnetic field inside small aircrafts, witch can contain composite materials in their construction. Introduction to neural networks and its application in EMC of small airplanes is discussed in the first part of the text. In the second part of this thesis we design a simple EM model of small airplane. The airplane is simulated by two parallel dielectric layers (the left-hand side wall and the right hand side wall of the airplane). The layers are put into a rectangular metallic waveguide terminated by the absorber in order to simulate the illumination of the airplane by the external wave (both of the harmonic nature and pulse one). Numerical analyses are performed to search the relations between the distribution of an electromagnetic field inside the aircraft and electric parameters of model walls. The results of numerical analyses are used to train two types of neural network. In this way we can obtain accurate continuous model of electromagnetic field inside the aircraft. For the comparison with neural networks a multi-dimensional cubic spline interpolation is provided also. Neural classifiers are also investigated. We use them for classification of imaginary composite materials in terms of EMC. The nearest neighbour algorithm is applied as a classic approach to problem of classification.