A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

Refraction corrected transmission ultrasound computed tomography for application in breast imaging

Purpose: We present an iterative framework for CT reconstruction from transmission ultrasound data which accurately and efficiently models the strong refraction effects that occur in our target application: Imaging the female breast. Methods: Our refractive ray tracing framework has its foundation in the fast marching method (FNMM) and it allows an accurate as well as efficient modeling of curved rays. We also describe a novel regularization scheme that yields further significant reconstruction quality improvements. A final contribution is the development of a realistic anthropomorphic digital breast phantom based on the NIH Visible Female data set. Results: Our system is able to resolve very fine details even in the presence of significant noise, and it reconstructs both sound speed and attenuation data. Excellent correspondence with a traditional, but significantly more computationally expensive wave equation solver is achieved. Conclusions: Apart from the accurate modeling of curved rays, decisive factors have also been our regularization scheme and the high-quality interpolation filter we have used. An added benefit of our framework is that it accelerates well on GPUs where we have shown that clinical 3D reconstruction speeds on the order of minutes are possible.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

As políticas públicas de urbanização e regularização fundiária no processo de inclusão social: o PROAP Rio de Janeiro

This work objectives to investigate how the public policies of urbanization and land regularization of the Program of Urbanization of Informal Settlements - PROAP, in Rio de Janeiro allow the social inclusion and the rescue of the citizenship of the poor populations. To reach this objective the two programs of PROAP were analyzed into two communities both beneficed by each one of these programs. First, the social exclusion and how it reflects itself in the form of appropriation of the territory and in the type of housing was deeply analyzed. It leads the analysis of the public policies. As a next step, a brief historical analysis was made to include the PROAP in the historical context, and this was analyzed in each one of its stages. Finally, through a qualitative approaching, the slum of Vigário Geral and the irregular settlement of Ana Gonzaga have been researched, both were chose by their singular characteristics and, according to speech of the inhabitants, it was evaluated how the Program contributes in the social inclusion in these communities.

Uso da análise discriminante regularizada (RDA) no reconhecimento de padrões em imagens digitais hiperespectral de sensoriamento remoto

Em cenas naturais, ocorrem com certa freqüência classes espectralmente muito similares, isto é, os vetores média são muito próximos. Em situações como esta, dados de baixa dimensionalidade (LandSat-TM, Spot) não permitem uma classificação acurada da cena. Por outro lado, sabe-se que dados em alta dimensionalidade [FUK 90] tornam possível a separação destas classes, desde que as matrizes covariância sejam suficientemente distintas. Neste caso, o problema de natureza prática que surge é o da estimação dos parâmetros que caracterizam a distribuição de cada classe. Na medida em que a dimensionalidade dos dados cresce, aumenta o número de parâmetros a serem estimados, especialmente na matriz covariância. Contudo, é sabido que, no mundo real, a quantidade de amostras de treinamento disponíveis, é freqüentemente muito limitada, ocasionando problemas na estimação dos parâmetros necessários ao classificador, degradando portanto a acurácia do processo de classificação, na medida em que a dimensionalidade dos dados aumenta. O Efeito de Hughes, como é chamado este fenômeno, já é bem conhecido no meio científico, e estudos vêm sendo realizados com o objetivo de mitigar este efeito. Entre as alternativas propostas com a finalidade de mitigar o Efeito de Hughes, encontram-se as técnicas de regularização da matriz covariância. Deste modo, técnicas de regularização para a estimação da matriz covariância das classes, tornam-se um tópico interessante de estudo, bem como o comportamento destas técnicas em ambientes de dados de imagens digitais de alta dimensionalidade em sensoriamento remoto, como por exemplo, os dados fornecidos pelo sensor AVIRIS. Neste estudo, é feita uma contextualização em sensoriamento remoto, descrito o sistema sensor AVIRIS, os princípios da análise discriminante linear (LDA), quadrática (QDA) e regularizada (RDA) são apresentados, bem como os experimentos práticos dos métodos, usando dados reais do sensor. Os resultados mostram que, com um número limitado de amostras de treinamento, as técnicas de regularização da matriz covariância foram eficientes em reduzir o Efeito de Hughes. Quanto à acurácia, em alguns casos o modelo quadrático continua sendo o melhor, apesar do Efeito de Hughes, e em outros casos o método de regularização é superior, além de suavizar este efeito. Esta dissertação está organizada da seguinte maneira: No primeiro capítulo é feita uma introdução aos temas: sensoriamento remoto (radiação eletromagnética, espectro eletromagnético, bandas espectrais, assinatura espectral), são também descritos os conceitos, funcionamento do sensor hiperespectral AVIRIS, e os conceitos básicos de reconhecimento de padrões e da abordagem estatística. No segundo capítulo, é feita uma revisão bibliográfica sobre os problemas associados à dimensionalidade dos dados, à descrição das técnicas paramétricas citadas anteriormente, aos métodos de QDA, LDA e RDA, e testes realizados com outros tipos de dados e seus resultados.O terceiro capítulo versa sobre a metodologia que será utilizada nos dados hiperespectrais disponíveis. O quarto capítulo apresenta os testes e experimentos da Análise Discriminante Regularizada (RDA) em imagens hiperespectrais obtidos pelo sensor AVIRIS. No quinto capítulo são apresentados as conclusões e análise final. A contribuição científica deste estudo, relaciona-se à utilização de métodos de regularização da matriz covariância, originalmente propostos por Friedman [FRI 89] para classificação de dados em alta dimensionalidade (dados sintéticos, dados de enologia), para o caso especifico de dados de sensoriamento remoto em alta dimensionalidade (imagens hiperespectrais). A conclusão principal desta dissertação é que o método RDA é útil no processo de classificação de imagens com dados em alta dimensionalidade e classes com características espectrais muito próximas.

Do acesso clássico à comercialização: especificidades do mercado imobiliário informal na área especial de interesse social de Mãe Luiza, Natal/ RN.

This study presents research regarding affordable housing and their effects on the spatial reconfiguration of Natal/ RN, aiming to identify the specificities of the informality of urban land. This study aims to understand how informal housing market operates housing provision for the population located in popular informal settlements, through buying and selling market and rental market of residential properties irregular / illegal. This understanding will be through the neighborhood of Mãe Luisa, Special Area of Social Interest (SASI), located between neighborhoods with a population of high purchasing power and inserted into the tourist shaft of seaside of town. The characterization of informal housing market in Mãe Luiza, from buyers, sellers and renters, will help to understand how these informal transactions operate on SASI and housing provision for public policy development and implementation of housing programs and land regularization for low-income population, adequate to dynamic and reality of housing of informal areas

O descompasso de uma experiência: avaliação do Programa Habitar Brasil na Comunidade África-Natal/RN

This research deals with the evaluation of the Programa do Governo Federal para Urbanização de Favelas Habitar Brasil(1993) carried out in the Africa slum - Redinha neighbourhood in Natal-Rn. This study carried out in period from 2005 to 2006 searches to identify the effects of the actions proposed by Program in 1993-1994 about the current urbanistic configuration of the Africa community. It analyzes the effectiveness in the process of achievement of the considered objectives to habitation, communitity equipments, infrastructure and agrarian regularization. On the evaluation process, it has been as reference the works developed by Adauto Cardoso (2004), Blaine Worthen (2004), Ronaldo Garcia (2001) and Rosângela Paz (2006). About the Habitational Policy with approach to the Urbanistic Right and the right to the housing, the reflections by Raquel Rolnik, Nabil Bonduki, Ermínia Maricato, Saule Júnior, Betânia de Moraes Alfonsin and Edésio Fernandes are main references. To gauge the execution of the objectives proposed by Habitar Brasil in 1993, it has searched in the documentary data of the time and in information gotten in interviews with technicians that had participated of the program, consistent references on what was considered, what was executed and the process of the intervention of Habitar Brasil in the Africa community. The area analysis in 2005-2006 has developed on the base of the urbanistic survey of the current situation from the four performance lines of the Program: habitation, infrastructure, community equipments and agrarian regularization, with a current urbanistic evaluation of Africa considering the intervention carried out in 1993 and 1994. The study points out the context of Brazilian Habitational Policy where the Programa Habitar Brasil was launched, explaining the main principles of the Program. In terms of local, it empahsizes the administrative-political factors that had contributed so that Natal-Rn city has been pioneering in the resources captation of Habitar Brazil (1993). Considering Habitar Brazil in Africa, the work argues and presents the intervention diagnosis and the proposal, developed by Program in 1993 evidencing the local problem of the time. After that, it makes a current reading of the area, identifying in 2006 representative elements of Habitar Brasil (1993-1994) for the Africa community. It identifies significant advances in the constitution of the institucional apparatus of the plaining system of Habitation of Social Interest for the city of Natal and points the fragilities in the implementation of the urban infrastructure actions and above all in the achievement of the objectives of the agrarian regularization

Habitabilidade na cidade sobre as águas: desafios da implantação de infra-estrutura de saneamento nas palafitas do Igarapé do Quarenta bairro Japiim Manaus/AM

The present research if inserts in the subject of the habitation of social interest and its relation with the sanitation infra-structure questions (sewer, water, draining and garbage). Having as study universe the narrow river of the Forty , situated one in the city of Manaus, capital of Amazon, approaches questions that if present between the necessities of housing and the especificidades of the natural environment, whose characteristics evidence limits for the implantation of adequate habitations. The objective is to analyze the possibilities and the limits of the urbanística regularization in the palafitas of the narrow rivers of Manaus, in view of the factors of habitability and ambient protection, expresses for the sanitation system - sanitary exhaustion, water supply, urban draining and garbage collection. The work approaches initially relative the conceptual aspects to the subject of social habitation in the country and its relation with the habitability factors, also focusing the question of the housing and the processes of urban informality in the city of Manaus. It deals with the process of constitution of the palafitas in the space of the city and its relation with the habitacionais politics, presenting the analysis of the implantation of the palafitas in relation to the sanitation infra-structure conditions (sewer, water, draining and garbage). As conclusion, it identifies to the possibilities and limits of urbanística regularization of the palafitas implanted to the long one of the narrow river of the Forty , taking in consideration the systems of the sanitation infrastructure

Cultura, Comunicação e cidadania: o caso do Centro Cultural do Banco do Brasil de São Paulo

O artigo analisa as atuais políticas culturais e analisa empiricamente as ações da unidade paulistana do Centro Cultural Banco do Brasil (CCBB). O objetivo é interpretar como esta instituição opera o fomento à cultura no contexto da normatização cultural no Brasil. A articulação institucional entre Banco do Brasil e seu Centro Cultural enseja algumas particularidades no campo da difusão cultural, pois o status institucional do CCBB condiciona de maneira decisiva as formas como transcorrem as relações com produtores culturais, público consumidor e com seu respectivo mantenedor. Trata-se de estudo baseado em pesquisa bibliográfica, levantamento de campo e na abordagem dialética de análise. Conclui-se que, ao consentir um laissez-faire cultural, o Estado admite que o mercado imponha sua lógica à cultura, de modo que o objeto empírico pode ser caracterizado como um exemplo dessa dinâmica.

A gestão da qualidade nos cursos de graduação a distância da UFRN/SEDIS : a percepção dos discentes

The management of water resources in the river basin level, as it defines the Law nº 9433/97, requires the effective knowledge of the processes of hydrological basin, resulting from studies based on consistent series of hydrological data that reflect the characteristics of the basin. In this context, the objective of this work was to develop the modeling of catchment basin of the river Jundiaí - RN and carry out the study of attenuation of a flood of the dam Tabatinga, by means of a monitoring project of hydrological data and climatology of the basin, with a view to promoting the development of research activities by applying methodologies unified and appropriate for the assessment of hydrological studies in the transition region of the semiarid and the forest zone on the coast of Rio Grande do Norte. For the study of the hydrological characteristics of the basin was conducted the automatic design of the basin of the river Jundiaí, with the aid of programs of geoprocessing, was adopted a hydrological model daily, the NRCS, which is a model determined and concentrated. For the use of this model was necessary to determine some parameters that are used in this model, as the Curve Number. Having in mind that this is the first study that is being conducted in the basin with the employment of this model, it was made sensitivity analysis of the results of this model from the adoption of different values of CN, situated within a range appropriate to the conditions of use, occupation and the nature of the soil of this basin. As the objective of this study was also developing a simulation model of the operation of the Tabatinga dam and with this flood control caused in the city of Macaíba, it was developed a mathematical model of fluid balance, developed to be used in Microsoft Excel. The simulation was conducted in two phases: the first step was promoted the water balance daily that allowed the analysis of the sensitivity of the model in relation to the volume of waiting, as well as the determination of the period of greatest discharges daily averages. From this point, it was assumed for the second stage, which was in the determination of the hydrograph of discharges effluent slots, that was determined by means of the fluid balance time, on the basis of the discharges effluents generated by a mathematical equation whose parameters were adjusted according to the hydrograph daily. Through the analyzes it was realized that the dam Tabatinga only has how to carry out the attenuation of floods through the regularization of the volume of waiting, with this there is a loss of approximately 56.5% on storage capacity of this dam, because for causing the attenuation effect of filled the shell of this dam has to remain more than 5m below the level of the sill, representing at least 50.582.927m3. The results obtained with the modeling represents a first step in the direction of improving the level of hydrological information about the behavior of the basins of the semiarid. In order to monitor quantitatively the hydrographic basin of the river Jundiaí will be necessary to install a rain gauge register, next to the Tabatinga dam and a pressure transducer, for regular measurements of flow in the reservoir of the dam. The climatological data will be collected in full automatic weather station installed in Agricultural School Jundiaí

Extração automática de contornos de telhados usando dados de varredura a laser e campos randômicos de Markov

This paper proposes a methodology for automatic extraction of building roof contours from a Digital Elevation Model (DEM), which is generated through the regularization of an available laser point cloud. The methodology is based on two steps. First, in order to detect high objects (buildings, trees etc.), the DEM is segmented through a recursive splitting technique and a Bayesian merging technique. The recursive splitting technique uses the quadtree structure for subdividing the DEM into homogeneous regions. In order to minimize the fragmentation, which is commonly observed in the results of the recursive splitting segmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. The high object polygons are extracted by using vectorization and polygonization techniques. Second, the building roof contours are identified among all high objects extracted previously. Taking into account some roof properties and some feature measurements (e. g., area, rectangularity, and angles between principal axes of the roofs), an energy function was developed based on the Markov Random Field (MRF) model. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing (SA) algorithm. Experiments carried out with laser scanning DEM's showed that the methodology works properly, as it delivered roof contours with approximately 90% shape accuracy and no false positive was verified.

Generic Bifurcations of Planar Filippov Systems via Geometric Singular Perturbations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Vacuum effects on massive spinor fields: S-1 x R-3 topology

The aim of this work was to investigate the role played by an external field on the Casimir energy density for massive fermions under S-1 x R-3 topology. Both twisted- and untwisted-spin connections are considered and the calculation in a closed form is performed using an alternative approach based on the combination of the analytic regularization method and the Euler-Maclaurin summation formula. It is shown that no mass scale appears in the final result and, therefore, Casimir effect arises only from the boundary conditions and vacuum fluctuations induced by the coupling with the external field.

Parâmetro de regularização em problemas inversos: estudo numérico com a transformada de Radon

In general, an inverse problem corresponds to find a value of an element x in a suitable vector space, given a vector y measuring it, in some sense. When we discretize the problem, it usually boils down to solve an equation system f(x) = y, where f : U Rm ! Rn represents the step function in any domain U of the appropriate Rm. As a general rule, we arrive to an ill-posed problem. The resolution of inverse problems has been widely researched along the last decades, because many problems in science and industry consist in determining unknowns that we try to know, by observing its effects under certain indirect measures. Our general subject of this dissertation is the choice of Tykhonov´s regulaziration parameter of a poorly conditioned linear problem, as we are going to discuss on chapter 1 of this dissertation, focusing on the three most popular methods in nowadays literature of the area. Our more specific focus in this dissertation consists in the simulations reported on chapter 2, aiming to compare the performance of the three methods in the recuperation of images measured with the Radon transform, perturbed by the addition of gaussian i.i.d. noise. We choosed a difference operator as regularizer of the problem. The contribution we try to make, in this dissertation, mainly consists on the discussion of numerical simulations we execute, as is exposed in Chapter 2. We understand that the meaning of this dissertation lays much more on the questions which it raises than on saying something definitive about the subject. Partly, for beeing based on numerical experiments with no new mathematical results associated to it, partly for being about numerical experiments made with a single operator. On the other hand, we got some observations which seemed to us interesting on the simulations performed, considered the literature of the area. In special, we highlight observations we resume, at the conclusion of this work, about the different vocations of methods like GCV and L-curve and, also, about the optimal parameters tendency observed in the L-curve method of grouping themselves in a small gap, strongly correlated with the behavior of the generalized singular value decomposition curve of the involved operators, under reasonably broad regularity conditions in the images to be recovered

Incorporação do vínculo de suavidade no ajuste de histórico de reservatórios de petróleo

The history match procedure in an oil reservoir is of paramount importance in order to obtain a characterization of the reservoir parameters (statics and dynamics) that implicates in a predict production more perfected. Throughout this process one can find reservoir model parameters which are able to reproduce the behaviour of a real reservoir.Thus, this reservoir model may be used to predict production and can aid the oil file management. During the history match procedure the reservoir model parameters are modified and for every new set of reservoir model parameters found, a fluid flow simulation is performed so that it is possible to evaluate weather or not this new set of parameters reproduces the observations in the actual reservoir. The reservoir is said to be matched when the discrepancies between the model predictions and the observations of the real reservoir are below a certain tolerance. The determination of the model parameters via history matching requires the minimisation of an objective function (difference between the observed and simulated productions according to a chosen norm) in a parameter space populated by many local minima. In other words, more than one set of reservoir model parameters fits the observation. With respect to the non-uniqueness of the solution, the inverse problem associated to history match is ill-posed. In order to reduce this ambiguity, it is necessary to incorporate a priori information and constraints in the model reservoir parameters to be determined. In this dissertation, the regularization of the inverse problem associated to the history match was performed via the introduction of a smoothness constraint in the following parameter: permeability and porosity. This constraint has geological bias of asserting that these two properties smoothly vary in space. In this sense, it is necessary to find the right relative weight of this constrain in the objective function that stabilizes the inversion and yet, introduces minimum bias. A sequential search method called COMPLEX was used to find the reservoir model parameters that best reproduce the observations of a semi-synthetic model. This method does not require the usage of derivatives when searching for the minimum of the objective function. Here, it is shown that the judicious introduction of the smoothness constraint in the objective function formulation reduces the associated ambiguity and introduces minimum bias in the estimates of permeability and porosity of the semi-synthetic reservoir model