Submitted by Kamila Costa (kamilavasconceloscosta@gmail.com) on 2015-06-18T20:16:38Z No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-06T15:29:34Z (GMT) No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-06T15:27:26Z (GMT) No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-06T15:33:36Z (GMT) No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5) / Made available in DSpace on 2015-07-06T15:33:36Z (GMT). No. of bitstreams: 1 Dissertação-Carina Figueiredo Coelho.pdf: 3096964 bytes, checksum: 57c06ccd1fdc732a7cf9a50381d3806b (MD5) Previous issue date: 2013-06-28 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / We investigated use of finite mixture models with skew normal independent distributions to model the conditional distributions in discriminat analysis, particularly the skew normal and skew t. To evaluate this model, we developed a simulation study and applications with real data sets, analyzing error rates associated with the classifiers obtained with these mixture models. Problems were simulated with different structures and separations for the classes distributions employing different training set sizes. The results of the study suggest that the models evaluated are able to adjust to different problems studied, from the simplest to the most complex in terms of modeling the observations for classification purposes. With real data, where then shapes distributions of the class is unknown, the models showed reasonable error rates when compared to other classifiers. As a limitation for the analized sets of data was observed that modeling by finite mixtures requires large samples per class when the dimension of the feature vector is relatively high. / Investigamos o emprego de misturas finitas de densidades na família normal assimétrica independente, em particular a normal assimétrica e a t assimétrica, para modelar as distribuições condicionais do vetor de características em Análise Discriminante (AD). O objetivo é obter modelos capazes de modelar dados com estruturas mais complexas onde, por exemplo, temos assimetria e multimodalidade, o quemuitas vezes ocorrem em problemas reais de AD. Para avaliar esta modelagem, desenvolvemos um estudo de simulação e aplicações em dados reais, analisando a taxa de erro (TE) associadas aos classificadores obtidos com estes modelos de misturas. Foram simulados problemas com diferentes estruturas, relativas à separação e distribuição das classes e o tamanho do conjunto de treinamento. Os resultados do estudo sugerem que os modelos avaliados são capazes de se ajustar aos diferentes problemas estudados, desde os mais simples aos mais complexos, em termos de modelagem das observações para fins de classificação. Com os dados reais, situações onde desconhecemos as formas das distribuições nas classes, os modelos apresentaram TE’s razoáveis quando comparados a outros classificadores. Como uma limitação, para os conjuntos de dados analisados, foi observado que a modelagem por misturas finitas necessita de amostras grandes por classe em situações onde a dimensão do vetor de características é relativamente alta.

In 2007, Domínguez-Molina et al. obtained the moment generating function (mgf) of the matrix variate closed skew normal distribution. In this paper, we use their mgf to obtain the first two moments and some additional properties of quadratic forms for the matrix variate skew normal distributions. The quadratic forms are particularly interesting because they are essentially correlation tests that introduce a new type of orthogonality condition.

The clock is the important synchronizing element in all synchronous digital systems. The difference in the clock arrival time between sink points is called the clock skew. This uncertainty in arrival times will limit operating frequency and might cause functional errors. Various clock routing techniques can be broadly categorized into 'balanced tree' and 'fixed mesh' methods. The skew and delay using the balanced tree method is higher compared to the fixed mesh method. Although fixed mesh inherently uses more wire length, the redundancy created by loops in a mesh structure reduces undesired delay variations. The fixed mesh method uses a single mesh over the entire chip but it is hard to introduce clock gating in a single clock mesh. This thesis deals with the introduction of 'reconfigurability' by using control structures like transmission gates between sub-clock meshes, thus enabling clock gating in clock mesh. By using the optimum value of size for PMOS and NMOS of transmission gate (SZF) and optimum number of transmission gates between sub-clock meshes (NTG) for 4x4 reconfigurable mesh, the average of the maximum skew for all benchmarks is reduced by 18.12 percent compared to clock mesh structure when no transmission gates are used between the sub-clock meshes (reconfigurable mesh with NTG =0). Further, the research deals with a ‘modified zero skew method' to connect synchronous flip-flops or sink points in the circuit to the clock grids of clock mesh. The wire length reduction algorithms can be applied to reduce the wire length used for a local clock distribution network. The modified version of ‘zero skew method’ of local clock routing which is based on Elmore delay balancing aims at minimizing wire length for the given bounded skew of CDN using clock mesh and H-tree. The results of ‘modified zero skew method' (HC_MZSK) show average local wire length reduction of 17.75 percent for all ISPD benchmarks compared to direct connection method. The maximum skew is small for HC_MZSK in most of the test cases compared to other methods of connections like direct connections and modified AHHK. Thus, HC_MZSK for local routing reduces the wire length and maximum skew.

Made available in DSpace on 2015-03-03T15:47:48Z (GMT). No. of bitstreams: 1 HelioAS_DISSERT.pdf: 11850754 bytes, checksum: c0dc4577693acf33bf104d52950511e6 (MD5) Previous issue date: 2013-11-08 / Universidade Federal do Rio Grande do Norte / Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness. / A Segmenta??o de imagens ? o processo de rotulagem de pixels em diferentes objetos, um passo importante em diversos sistemas de processamento de imagens. Este trabalho prop?e um m?todo de agrupamento para a segmenta??o de imagens digitais coloridas com propriedades texturais. Isto ? feito atrav?s da redu??o de dimensionalidade dos histogramas das imagens coloridas e do uso da Diverg?ncia Skew no c?lculo das fun??es de a nidade fuzzy. Esse tipo de abordagem ? adequada ? segmenta??o de imagens coloridas que possuam caracter?sticas texturais, como imagens geol?gicas, dermatosc?picas e outras imagens naturais, como imagens que contenham montanhas, grama ou orestas. Al?m disso, resultados experimentais do agrupamento de texturas coloridas usando imagens de rochas sedimentares porosas s?o apresentados e analisados em termos de precis?o para comprovar sua efetividade

To investigate the passive force-displacement relationships provided by a transitional zoned backfill consisting of cement treated aggregate (CTA) and compacted gravel, a series of full-scale lateral abutment load tests were performed. The transitional zoned backfill was designed to minimize differential settlement adjacent to bridge abutments for the California High Speed Rail project. Tests were performed with a 2-D or plane strain backfill geometry to simulate a wide abutment. To investigate the effect of skew angle on the passive force, lateral abutment load tests were also performed with a simulated abutment with skew angles of 30º and 45º. The peak passive force developed was about 2.5 times higher than that predicted with the California HSR design method for granular backfill material with a comparable backwall height and width. The displacement required to develop the peak passive force decreased with skew angle and was somewhat less than for conventional granular backfills. Peak passive force developed with displacements of 3 to 1.8% of the wall height, H in comparison to 3 to 5% of H for conventional granular backfills.The skew angle had less effect on the peak passive force for the transitional backfill than for conventional granular backfills. For example, the passive force reduction factor, Rskew, was only 0.83 and 0.51 for the 30º and 45º skew abutments in comparison to 0.51 and 0.37 for conventional granular backfills. Field measurements suggest that the CTA backfill largely moves with the abutment and does not experience significant heave while shear failure and heaving largely occurs in the granular backfill behind the CTA backfill zone.

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Conjuntos de dados com respostas multivariadas aparecem frequentemente em pesquisas em que os dados são provenientes de questionários. Exemplos mais comuns são pesquisas de opinião, mais especificamente, pesquisas de marketing em que a preferência do consumidor em potencial é avaliado: pelo produto, marca, preço, praça, promoção e etc. Um tipo pesquisa de opinião que ganha grande destaque no Brasil de dois em dois anos são as pesquisas eleitorais de intenção de votos. Nós introduzimos nesta tese uma classe de modelos de regressão multivariados com funções de ligação assimétricas para o ajuste de conjuntos de dados com respostas multivariadas binárias. As funções de ligação consideradas são bastante flexíveis e robustas, contemplando funções de ligação simétricas como casos particulares. Devido a complexidade do modelo, nós discutimos a sua identificabilidade. A abordagem Bayesiana foi considerada e alguns algoritmos de Monte Carlo via Cadeia de Markov (MCMC) foram desenvolvidos. Nós descrevemos algumas ferramentas de seleção de modelos, os quais incluem o Critério de Informação da Deviance (DIC), a Pseudo-Verossimilhança Marginal e o Pseudo-Fator de Bayes. Adicionalmente, um estudo de simulação foi desenvolvido com dois objetivos; i) verificar a qualidade dos algoritmos desenvolvidos e ii) verificar a importância da escolha da função de ligação . No final da tese uma aplicação em um conjunto de dados real é considerada com o objetivo de ilustrar as metodologias e técnicas apresentadas. / Data sets with multivariate responses often appear in surveys where the data came from questionnaires. Opinion poll, sometimes simply referred to as a poll, are common examples of studies in which the responses are multivariate. One type poll that gain great prominence in Brazil in election years, is the survey of vote intent. However, despite the higher visibility of prognostic studies of election, opnion polls is a tool widely used to detect trends and positions of different social segments on various topics, be they political, social or governmental. We introduce in this work a class of multivariate regression models with asymmetric link functions to fit data sets with multivariate binary responses. The link functions here considered are quite flexible and robust, contemplating symmetrical link functions as special cases. Due to the complexity of the model, we discuss its identifiability. The Bayesian approach was considered and some Monte Carlo Markov Chain (MCMC) algorithms have been developed. Simulation studies have been developed with two objectives: i) verify the quality of the algorithms developed and ii) to verify the importance of choosing the link function. At the end of this work an application in a real data set is considered in order to illustrate the methodologies and techniques presented.

Prefabricated concrete elements are widely used in the construction industry today. With advantages such as time savings, increased safety at the construction site and minimized material usage, prefab becomes a major challenger to the traditional on-site casting construction method. However, constructing a bridge in concrete still presents challenges when using prefab as a construction method. Hence, more research in the area is needed. This master thesis has been studying the behavior of a prefabricated skew angle slab and the connection between the slab and wall elements of a bridge. The study was conducted using a finite element software, where three 3D-models of skew angle slabs were created. The three models had different skew angles (0, 15 and 30 degrees) and crossed the same path. The models could represent both the slab and the slab-wall connection. The finite element analysis showed that slabs with angles up to 15 degrees could be designed as a straight bridge. However, when the skew angle increases to 30 degrees, the behavior of the slab and connection changes significantly. Furthermore, the results show that a stress concentration occurs in the obtuse corner and that the stress increases when the skew angle increases. Moreover, there is a slight uplift in the acute corner when the skew angle increases to 30 degrees.

Conjuntos de dados com respostas multivariadas aparecem frequentemente em pesquisas em que os dados são provenientes de questionários. Exemplos mais comuns são pesquisas de opinião, mais especificamente, pesquisas de marketing em que a preferência do consumidor em potencial é avaliado: pelo produto, marca, preço, praça, promoção e etc. Um tipo pesquisa de opinião que ganha grande destaque no Brasil de dois em dois anos são as pesquisas eleitorais de intenção de votos. Nós introduzimos nesta tese uma classe de modelos de regressão multivariados com funções de ligação assimétricas para o ajuste de conjuntos de dados com respostas multivariadas binárias. As funções de ligação consideradas são bastante flexíveis e robustas, contemplando funções de ligação simétricas como casos particulares. Devido a complexidade do modelo, nós discutimos a sua identificabilidade. A abordagem Bayesiana foi considerada e alguns algoritmos de Monte Carlo via Cadeia de Markov (MCMC) foram desenvolvidos. Nós descrevemos algumas ferramentas de seleção de modelos, os quais incluem o Critério de Informação da Deviance (DIC), a Pseudo-Verossimilhança Marginal e o Pseudo-Fator de Bayes. Adicionalmente, um estudo de simulação foi desenvolvido com dois objetivos; i) verificar a qualidade dos algoritmos desenvolvidos e ii) verificar a importância da escolha da função de ligação . No final da tese uma aplicação em um conjunto de dados real é considerada com o objetivo de ilustrar as metodologias e técnicas apresentadas. / Data sets with multivariate responses often appear in surveys where the data came from questionnaires. Opinion poll, sometimes simply referred to as a poll, are common examples of studies in which the responses are multivariate. One type poll that gain great prominence in Brazil in election years, is the survey of vote intent. However, despite the higher visibility of prognostic studies of election, opnion polls is a tool widely used to detect trends and positions of different social segments on various topics, be they political, social or governmental. We introduce in this work a class of multivariate regression models with asymmetric link functions to fit data sets with multivariate binary responses. The link functions here considered are quite flexible and robust, contemplating symmetrical link functions as special cases. Due to the complexity of the model, we discuss its identifiability. The Bayesian approach was considered and some Monte Carlo Markov Chain (MCMC) algorithms have been developed. Simulation studies have been developed with two objectives: i) verify the quality of the algorithms developed and ii) to verify the importance of choosing the link function. At the end of this work an application in a real data set is considered in order to illustrate the methodologies and techniques presented.