No / New representations and efficient calculation methods are derived for the problem of propagation from an infinite regularly spaced array of coherent line sources above a homogeneous impedance plane, and for the Green's function for sound propagation in the canyon formed by two infinitely high, parallel rigid or sound soft walls and an impedance ground surface. The infinite sum of source contributions is replaced by a finite sum and the remainder is expressed as a Laplace-type integral. A pole subtraction technique is used to remove poles in the integrand which lie near the path of integration, obtaining a smooth integrand, more suitable for numerical integration, and a specific numerical integration method is proposed. Numerical experiments show highly accurate results across the frequency spectrum for a range of ground surface types. It is expected that the methods proposed will prove useful in boundary element modeling of noise propagation in canyon streets and in ducts, and for problems of scattering by periodic surfaces.

Yes / PICARD is a space-based observatory hosting the Solar Diameter Imager and Surface Mapper (SODISM) telescope, which has continuously observed the Sun from July 2010 and up to March 2014. In order to study the fine structure of the solar surface, it is helpful to apply techniques that enhance the images so as to improve the visibility of solar features such as sunspots or faculae. The objective of this work is to develop an innovative technique to enhance the quality of the SODISM images in the five wavelengths monitored by the telescope at 215.0 nm, 393.37 nm, 535.7 nm, 607.1 nm and 782.2 nm. An enhancement technique using interpolation of the high-frequency sub-bands obtained by Discrete Wavelet Transforms (DWT) and the input image is applied to the SODISM images. The input images are decomposed by the DWT as well as Stationary Wavelet Transform (SWT) into four separate sub-bands in horizontal and vertical directions namely, low-low (LL), low-high (LH), high-low (HL) and high–high (HH) frequencies. The DWT high frequency sub-bands are interpolated by a factor 2. The estimated high frequency sub-bands (edges) are enhanced by introducing an intermediate stage using a stationary Wavelet Transform (SWT), and then all these sub-bands and input image are combined and interpolated with half of the interpolation factor α/2, used to interpolate the high-frequency sub-bands, in order to reach the required size for IDWT processing. Quantitative and visual results show the superiority of the proposed technique over a bicubic image resolution enhancement technique. In addition, filling factors for sunspots are calculated from SODISM images and results are presented in this work.

The thesis consists of four main chapters. The first chapter includes an introduction to inhomogeneous self-similar sets and measures. In particular, we show that these sets and measures are natural generalizations of the well known self-similar sets and measures. We then investigate the structure of these sets and measures. In the second chapter we study various fractal dimensions (Hausdorff, packing and box dimensions) of inhomogeneous self-similar sets and compare our results with the well-known results for (ordinary) self-similar sets. In the third chapter we investigate the L {q} spectra and the Renyi dimensions of inhomogeneous self-similar measures and prove that new multifractal phenomena, not exhibited by (ordinary) self-similar measures, appear in the inhomogeneous case. Namely, we show that inhomogeneous self-similar measures may have phase transitions which is in sharp contrast to the behaviour of the L {q} spectra of (ordinary) self-similar measures satisfying the Open Set Condition. Then we study the significantly more difficult problem of computing the multifractal spectra of inhomogeneous self-similar measures. We show that the multifractal spectra of inhomogeneous self-similar measures may be non-concave which is again in sharp contrast to the behaviour of the multifractal spectra of (ordinary) self-similar measures satisfying the Open Set Condition. Then we present a number of applications of our results. Many of them are related to the notoriously difficult problem of computing (or simply obtaining non-trivial bounds) for the multifractal spectra of self-similar measures not satisfying the Open Set Condition. More precisely, we will show that our results provide a systematic approach to obtain non-trivial bounds (and in some cases even exact values) for the multifractal spectra of several large and interesting classes of self-similar measures not satisfying the Open Set Condition. In the fourth chapter we investigate the asymptotic behaviour of the Fourier transforms of inhomogeneous self-similar measures and again we present a number of applications of our results, in particular to non-linear self-similar measures.

Cette thèse s'intéresse à l'étude des propriétés et applications de quatre familles des fonctions spéciales associées aux groupes de Weyl et dénotées $C$, $S$, $S^s$ et $S^l$. Ces fonctions peuvent être vues comme des généralisations des polynômes de Tchebyshev. Elles sont en lien avec des polynômes orthogonaux à plusieurs variables associés aux algèbres de Lie simples, par exemple les polynômes de Jacobi et de Macdonald. Elles ont plusieurs propriétés remarquables, dont l'orthogonalité continue et discrète. En particulier, il est prouvé dans la présente thèse que les fonctions $S^s$ et $S^l$ caractérisées par certains paramètres sont mutuellement orthogonales par rapport à une mesure discrète. Leur orthogonalité discrète permet de déduire deux types de transformées discrètes analogues aux transformées de Fourier pour chaque algèbre de Lie simple avec racines des longueurs différentes. Comme les polynômes de Tchebyshev, ces quatre familles des fonctions ont des applications en analyse numérique. On obtient dans cette thèse quelques formules de <<cubature>>, pour des fonctions de plusieurs variables, en liaison avec les fonctions $C$, $S^s$ et $S^l$. On fournit également une description complète des transformées en cosinus discrètes de types V--VIII à $n$ dimensions en employant les fonctions spéciales associées aux algèbres de Lie simples $B_n$ et $C_n$, appelées cosinus antisymétriques et symétriques. Enfin, on étudie quatre familles de polynômes orthogonaux à plusieurs variables, analogues aux polynômes de Tchebyshev, introduits en utilisant les cosinus (anti)symétriques. / This thesis presents several properties and applications of four families of Weyl group orbit functions called $C$-, $S$-, $S^s$- and $S^l$-functions. These functions may be viewed as generalizations of the well-known Chebyshev polynomials. They are related to orthogonal polynomials associated with simple Lie algebras, e.g. the multivariate Jacobi and Macdonald polynomials. They have numerous remarkable properties such as continuous and discrete orthogonality. In particular, it is shown that the $S^s$- and $S^l$-functions characterized by certain parameters are mutually orthogonal with respect to a discrete measure. Their discrete orthogonality allows to deduce two types of Fourier-like discrete transforms for each simple Lie algebra with two different lengths of roots. Similarly to the Chebyshev polynomials, these four families of functions have applications in numerical integration. We obtain in this thesis various cubature formulas, for functions of several variables, arising from $C$-, $S^s$- and $S^l$-functions. We also provide a~complete description of discrete multivariate cosine transforms of types V--VIII involving the Weyl group orbit functions arising from simple Lie algebras $C_n$ and $B_n$, called antisymmetric and symmetric cosine functions. Furthermore, we study four families of multivariate Chebyshev-like orthogonal polynomials introduced via (anti)symmetric cosine functions.

[pt] Ao mesmo tempo em que a autonomia de robôs pessoais e domésticos aumenta, cresce a necessidade de interação dos mesmos com o ambiente. A interação mais básica de um robô com o ambiente é feita pela percepção deste e sua navegação. Para uma série de aplicações não é prático prover modelos geométricos válidos do ambiente a um robô antes de seu uso. O robô necessita, então, criar estes modelos enquanto se movimenta e percebe o meio em que está inserido através de sensores. Ao mesmo tempo é necessário minimizar a complexidade requerida quanto a hardware e sensores utilizados. No presente trabalho, um algoritmo iterativo baseado em entropia é proposto para planejar uma estratégia de exploração visual, permitindo a construção eficaz de um modelo em grafo do ambiente. O algoritmo se baseia na determinação da informação presente em sub-regiões de uma imagem panorâmica 2-D da localização atual do robô obtida com uma câmera fixa sobre o mesmo. Utilizando a métrica de entropia baseada na Teoria da Informação de Shannon, o algoritmo determina nós potenciais para os quais deve se prosseguir a exploração. Através de procedimento de Visual Tracking, em conjunto com a técnica SIFT (Scale Invariant Feature Transform), o algoritmo auxilia a navegação do robô para cada nó novo, onde o processo é repetido. Um procedimento baseado em transformações invariáveis a determinadas variações espaciais (desenvolvidas a partir de Fourier e Mellin) é utilizado para auxiliar o processo de guiar o robô para nós já conhecidos. Também é proposto um método baseado na técnica SIFT. Os processos relativos à obtenção de imagens, avaliação, criação do grafo, e prosseguimento dos passos citados continua até que o robô tenha mapeado o ambiente com nível pré-especificado de detalhes. O conjunto de nós e imagens obtidos são combinados de modo a se criar um modelo em grafo do ambiente. Seguindo os caminhos, nó a nó, um robô pode navegar pelo ambiente já explorado. O método é particularmente adequado para ambientes planos. As componentes do algoritmo proposto foram desenvolvidas e testadas no presente trabalho. Resultados experimentais mostrando a eficácia dos métodos propostos são apresentados. / [en] As the autonomy of personal service robotic systems increases so has their need to interact with their environment. The most basic interaction a robotic agent may have with its environment is to sense and navigate through it. For many applications it is not usually practical to provide robots in advance with valid geometric models of their environment. The robot will need to create these models by moving around and sensing the environment, while minimizing the complexity of the required sensing hardware. This work proposes an entropy-based iterative algorithm to plan the robot´s visual exploration strategy, enabling it to most efficiently build a graph model of its environment. The algorithm is based on determining the information present in sub-regions of a 2- D panoramic image of the environment from the robot´s current location using a single camera fixed on the mobile robot. Using a metric based on Shannon s information theory, the algorithm determines potential locations of nodes from which to further image the environment. Using a Visual Tracking process based on SIFT (Scale Invariant Feature Transform), the algorithm helps navigate the robot to each new node, where the imaging process is repeated. An invariant transform (based on Fourier and Mellin) and tracking process is used to guide the robot back to a previous node. Also, an SIFT based method is proposed to accomplish such task. This imaging, evaluation, branching and retracing its steps continues until the robot has mapped the environment to a pre-specified level of detail. The set of nodes and the images taken at each node are combined into a graph to model the environment. By tracing its path from node to node, a service robot can navigate around its environment. This method is particularly well suited for flat-floored environments. The components of the proposed algorithm were developed and tested. Experimental results show the effectiveness of the proposed methods.

O hipocampo é uma estrutura cerebral que possui importância primordial para o sistema de memória humana. Alterações no seus tecidos levam a doenças neurodegenerativas, tais como: epilepsia, esclerose múltipla e demência, entre outras. Para medir a atrofia do hipocampo é necessário isolá-lo do restante do cérebro. A separação do hipocampo das demais partes do cérebro ajuda aos especialistas na análise e o entendimento da redução de seu volume e detecção de qualquer anomalia presente. A extração do hipocampo é principalmente realizada de modo manual, a qual é demorada, pois depende da interação do usuário. A segmentação automática do hipocampo é investigada como uma alternativa para contornar tais limitações. Esta dissertação de mestrado apresenta um novo método de segmentação automático, denominado Modelo de Nuvem de Similaridade (Similarity Cloud Model - SimCM). O processo de segmentação é dividido em duas etapas principais: i) localização por similaridade e ii) ajuste de nuvem. A primeira operação utiliza a nuvem para localizar a posição mais provável do hipocampo no volume destino. A segunda etapa utiliza a nuvem para corrigir o delineamento final baseada em um novo método de cálculo de readequação dos pesos das arestas. Nosso método foi testado em um conjunto de 235 MRI combinando imagens de controle e de pacientes com epilepsia. Os resultados alcançados indicam um rendimento superior tanto em efetividade (qualidade da segmentação) e eficiência (tempo de processamento), comparado com modelos baseados em grafos e com modelos Bayesianos. Como trabalho futuro, pretendemos utilizar seleção de características para melhorar a construção da nuvem e o delineamento dos tecidos / The hippocampus is a particular structure that plays a main role in human memory systems. Tissue modifications of the hippocampus lead to neurodegenerative diseases as epilepsy, multiple sclerosis, and dementia, among others. To measure hippocampus atrophy, it is crucial to get its isolated representation from the whole brain volume. Separating the hippocampus from the brain helps physicians in better analyzing and understanding its volume reduction, and detecting any abnormal behavior. The extraction of the hippocampus is dominated by manual segmentation, which is time consuming mainly because it depends on user interaction. Therefore, automatic segmentation of the hippocampus has being investigated as an alternative solution to overcome such limitations. This master dissertation presents a new automatic segmentation method called Similarity Cloud Model (SimCM) based on hippocampus feature extraction. The segmentation process consists of two main operations: i) localization by similarity, and ii) cloud adjustment. The first operation uses the cloud to localize the most probable position of the hippocampus in a target volume. The second process invokes the cloud to correct the final labeling, based on a new method for arc-weight re-adjustment. Our method has been tested in a dataset of 235 MRIs combining healthy and epileptic patients. Results indicate superior performance, in terms of effectiveness (segmentation quality) and efficiency (processing time), in comparison with similar graph-based and Bayesian-based models. As future work, we intend to use feature selection to improve cloud construction and tissue delineation

Made available in DSpace on 2016-03-22T17:26:22Z (GMT). No. of bitstreams: 1 DMII_AndreMarcel.pdf: 2907967 bytes, checksum: 5f3911468dd5affdd2020316f31ee238 (MD5) Previous issue date: 2009-12-11 / The increasing use of digital video on the Internet, devices and also in mobile digital TV has lead to an increasing interest for research in this area, from both industry and academia. This work follows this trend by proposing the investigation of the main aspects of digital video, video compression and also of the H.264/AVC video compression for the implementation of performance efficient dedicated architectures for some modules of the H.264/AVC encoder. In particular, this work presents some architectural alternatives for the increase of performance of two modules of the H.264/AVC, which are: T Module (composed by the Forward Hadamard and Discrete Cosine Transforms) and Motion Estimation (ME). For the implementation of these modules the use of techniques to the increase of performance has been considered, such as the use of efficient adders and pipeline. This efficient adders presents high use of hardware features. Thus, the implemented architectures in this work presented these characteristics too. The main aspect presented by the implemented modules is a large number of arithmetic operations of addition and subtraction for their processing. Thus, the motivation of this work is the increase of performance of these modules, from the use of efficient adder/subtractor circuits that are present in literature. In particular, 4:2, 8:2 and 16:2 adder compressors that perform the simultaneous addition of 4, 8 and 16 operands, respectively, with no penalties in area and the critical path are used. The architectures were described in VHDL and targeted to ASIC technology. The validation of the circuits and the obtained results were performed by using Leonardo Spectrum tool from Mentor Graphics. Comparisons against the solutions of the literature were done and the main results show that the architectures proposed in this work are more efficient. Significant gains in performance are achievable using our solutions for both Forward Transforms and Motion Estimation architectures / A crescente utilização de vídeos digitais na Internet, em dispositivos móveis e também na TV digital faz com que haja um interesse crescente em pesquisas nesta área, tanto na indústria quanto no meio acadêmico. Este trabalho segue esta tendência e tem como proposta estudar aspectos de vídeo digital, compressão de vídeo e também do padrão H.264/AVC de compressão de vídeo para a implementação de arquiteturas dedicadas eficientes em desempenho, isto é, com elevada frequência de operação, dos módulos do codificador do padrão H.264/AVC. Em particular, este trabalho apresenta algumas alternativas arquiteturais para aumento de desempenho de dois módulos do padrão H.264/AVC, que são: Módulo T (composto pelas Transformadas Diretas Transformadas Hadamard e Transformada Discreta do Coseno) e Estimação de Movimento (ME). A implementação destes módulos foi realizada utilizando técnicas para o aumento de desempenho, tais como o uso de somadores eficientes e pipeline. Uma característica dos somadores eficientes utilizados neste trabalho é o uso elevado de recursos de hardware. Assim, as arquiteturas implementadas neste trabalho também apresentaram esta característica. Os módulos implementados apresentam como principal característica um elevado número de operações aritméticas de soma e subtração para o seu processamento. Desta forma, a motivação deste trabalho consiste em aumentar o desempenho destes módulos, a partir da utilização de circuitos somadores/subtratores eficientes presentes na literatura. Em particular, são utilizados circuitos somadores compressores 4:2, 8:2 e 16:2, pois estes realizam a soma simultânea de 4, 8 e 16 operandos, respectivamente, sem penalidades em área e no caminho crítico. As arquiteturas foram descritas em VHDL e direcionadas para tecnologia ASIC, a validação e resultados foram obtidos através da ferramenta Leonardo Spectrum da Mentor Graphics. Para os estudos de caso utilizados neste trabalho (Transformadas Diretas e Estimação de Movimento), foram feitas comparações com soluções apresentadas na literatura e os resultados mostram que as arquiteturas implementadas neste trabalho obtiveram significativos ganhos em desempenho, quando comparadas com soluções apresentadas na literatura

Cette thèse s'inscrit dans le domaine de l'analyse harmonique et plus exactement, des estimations à poids. Un intérêt particulier est porté aux estimations Lp à poids des transformées de Riesz sur des variétés Riemanniennes complètes ainsi qu'à l'optimalité des résultats en terme de la puissance de la caractéristique des poids. On obtient un premier résultat (en terme de la linéarité et de la non dépendance de la dimension) sur des espaces pas nécessairement de type homogène, lorsque p = 2 et la courbure de Bakry-Emery est positive. On utilise pour cela une approche analytique en exhibant une fonction de Bellman concrète. Puis, en utilisant des techniques stochastiques et une domination éparse, on démontre que les transformées de Riesz sont bornées sur Lp, pour p ∈ (1, +∞) et on déduit également le résultat précèdent. Enfin, on utilise un changement élégant dans la preuve précèdente pour affaiblir l'hypothèse sur la courbure et la supposer minorée. / The topics addressed in this thesis lie in the field of harmonic analysis and more pre- cisely, weighted inequalities. Our main interests are the weighted Lp-bounds of the Riesz transforms on complete Riemannian manifolds and the sharpness of the bounds in terms of the power of the characteristic of the weights. We first obtain a linear and dimensionless result on non necessarily homogeneous spaces, when p = 2 and the Bakry-Emery curvature is non-negative. We use here an analytical approach by exhibiting a concrete Bellman function. Next, using stochastic techniques and sparse domination, we prove that the Riesz transforms are Lp-bounded for p ∈ (1, +∞) and obtain the previous result for free. Finally, we use an elegant change in the precedent proof to weaken the condition on the curvature and assume it is bounded from below.

Power and Generator Transformers are important and expensive elements of a power system. Inadvertent failure of Power Transformers would cause long interruption in power supply with consequent loss of reliability and revenue to the supply utilities. The mineral oil impregnated paper, OIP, is an insulation of choice in large power transformers in view of its excellent dielectric and other properties, besides being relatively inexpensive. During the normal working regime of the transformer, the insulation thereof is subjected to various stresses, the more important among them are, electrical, thermal, mechanical and chemical. Each of these stresses, appearing singly, or in combination, would lead to a time variant deterioration in the properties of insulation, called Ageing. This normal and inevitable process of degradation in the several essential properties of the insulation is irreversible, is a non-Markov physico-chemical reaction kinetic process. The speed or the rapidity of insulation deterioration is a very strong function of the magnitude of the stresses and the duration over which they acted. This is further compounded, if the stresses are in synergy. During the processes of ageing, some, or all the vital properties undergo subtle changes, more often, not in step with the duration of time over which the damage has been accumulated. Often, these changes are non monotonic, thus presenting a random or a chaotic picture and understanding the processes leading to eventual failure becomes difficult. But, there is some order in this chaos, in that, the time average of the changes over short intervals of time, seems to indicate some degree of predictability. The status of insulation at any given point in time is assessed by measuring such of those properties as are sensitive to the amount of ageing and comparing it with earlier measurements. This procedure, called the Diagnostic or nondestructive Testing, has been in vogue for some time now. Of the many parameters used as sensitive indices of the dynamics of insulation degradation, temporal changes in temperatures at different locations in the body of the transformer, more precisely, the winding hot spots (HST) and top oil temperature (TOT) are believed to give a fairly accurate indication of the rate of degradation. Further, an accurate estimation of the temperatures would enable to determine the loading limit (loadability) of power transformer. To estimate the temperature rise reasonably accurately, one has to resort to classical mathematical techniques involving formulation and solution of boundary value problem of heat conduction under carefully prescribed boundary conditions. Several complications are encountered in the development of the governing equations for the emergent heat transfer problems. The more important among them are, the inhomogeneous composition of the insulation structure and of the conductor, divergent flow patterns of the oil phase and inordinately varying thermal properties of conductor and insulation. Validation and reconfirmation of the findings of the thermal models can be made using state of the art methods, such as, Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Genetic Algorithm (GA). Over the years, different criteria have been prescribed for the prediction of terminal or end of life (EOL) of equipment from the standpoint of its insulation. But, thus far, no straightforward and unequivocal criterion is forth coming. Calculation of elapsed life in line with the existing methodology, given by IEEE, IEC, introduces unacceptable degrees of uncertainty. It is needless to say that, any conformal procedure proposed in the accurate prediction of EOL, has to be based on a technically feasible and economically viable consideration. A systematic study for understanding the dynamical nature of ageing in transformers in actual service is precluded for reasons very well known. Laboratory experiments on prototypes or pro-rated units fabricated based on similarity studies, are performed under controlled conditions and at accelerated stress levels to reduce experimental time. The results thereof can then be judiciously extrapolated to normal operating conditions and for full size equipment. The terms of reference of the present work are as follows; 1. Computation of TOT and HST Theoretical model based on Boundary Value Problem of Heat Conduction Application of AI Techniques 2. Experimental Investigation for estimating the Elapsed Life of transformers Based on the experimental investigation a semi-empirical expression has been developed to estimate the loss of life of power and station transformer by analyzing gas content and furfural dissolved in oil without performing off-line and destructive tests.

Imagine your local creamery administers a survey asking their patrons to choose their five favorite ice cream flavors. Any data collected by this survey would be an example of partially ranked data, as the set of all possible flavors is only ranked into subsets of the chosen flavors and the non-chosen flavors. If the creamery asks you to help analyze this data, what approaches could you take? One approach is to use the natural symmetries of the underlying data space to decompose any data set into smaller parts that can be more easily understood. In this work, I describe how to use permutation representations of the symmetric group to create and study efficient algorithms that yield such decompositions.