A eletrodinâmica escalar generalizada de Duffin-Kemmer-Petiau, uma análise funcional de sua dinâmica quântica covariante e o equilíbrio termodinâmico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Equações diferenciais implícitas com descontinuidade

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo de ciclos limites em uma classe de equações diferenciais descontínuas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sobre a estabilidade estrutural e regularizações de campos de vetores descontínuos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulação de Monte Carlo: de modelos de spin à teoria de campos na rede

Pós-graduação em Física - IFT

Método de integração em dimensão negativa em teoria quântica de campos

This work is a review of the Negative Dimension Integration Method as a powerful tool for the computation of the radiative corrections present in Quantum Field Perturbation Theory. This method is applicable in the context of Dimensional Regularization and it provides exact solutions for Feynman integrals with both dimensional parameter and propagator exponents generalized. These solutions are presentedintheformoflinearcombinationsofhypergeometricfunctionswhosedomains of convergence are related to the analytic structure of the Feynman Integral. Each solution is connected to the others trough analytic continuations. Besides presenting and discussing the general algorithm of the method in a detailed way, we offer concrete applications to scalar one-loop and two-loop integrals as well as to the one-loop renormalizationofQuantumElectrodynamics (QED)

IMPLEMENTATION OF PROTECTED AREAS FORCENTRAL CORRIDOR OF ATLANTIC FORESTIN BAHIA: CHALLENGES AND LIMITS

In Brazil, Protected Areas (PAs) are considered the cornerstone for development of national strategies for biodiversity conservation. Considering this point of view we analyzed thirty protected areas belonging to Atlantic Central Corridor of Atlantic Forest in Bahia, aiming to identify and analyze its current level of implementation. Lemos de Sa and Ferreira (2000) methodology which consist of applying a standard scale, where the variation of the level of implementation conforms to a range of 0 to 5 points was used, with appropriate adaptations. After obtaining the data from the implementation level we use the aggregation method of Ward to help visualize the dissimilarity between the protected areas studied. We used an international classification proposed by IUCN (International Union for Conservation of Nature) for that the UCs to be compared with works done in another countries, the UCs considered are in the groups Ia, II, V and VI da IUCN. As results, 50% of protected areas analyzed are reasonably implemented, 40% inadequately implemented, 6.7% are presented only on paper and only 3.3% can be classified as satisfactorily implemented. These areas presents problems in their regularization; deficiency in infrastructure, human and financial resources. Given the results its clear the recurrent fact that conservation areas under study must be effectively implemented and for this to occur environmental policies should be focused on actions to consolidate the goals of conservation strategy.

STABLE PIECEWISE POLYNOMIAL VECTOR FIELDS

Let N = {y > 0} and S = {y < 0} be the semi-planes of R-2 having as common boundary the line D = {y = 0}. Let X and Y be polynomial vector fields defined in N and S, respectively, leading to a discontinuous piecewise polynomial vector field Z = (X, Y). This work pursues the stability and the transition analysis of solutions of Z between N and S, started by Filippov (1988) and Kozlova (1984) and reformulated by Sotomayor-Teixeira (1995) in terms of the regularization method. This method consists in analyzing a one parameter family of continuous vector fields Z(epsilon), defined by averaging X and Y. This family approaches Z when the parameter goes to zero. The results of Sotomayor-Teixeira and Sotomayor-Machado (2002) providing conditions on (X, Y) for the regularized vector fields to be structurally stable on planar compact connected regions are extended to discontinuous piecewise polynomial vector fields on R-2. Pertinent genericity results for vector fields satisfying the above stability conditions are also extended to the present case. A procedure for the study of discontinuous piecewise vector fields at infinity through a compactification is proposed here.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

The r-matrix of the Alday-Arutyunov-Frolov model

We investigate the classical integrability of the Alday-Arutyunov-Frolov model, and show that the Lax connection can be reduced to a simpler 2 x 2 representation. Based on this result, we calculate the algebra between the L-operators and find that it has a highly non-ultralocal form. We then employ and make a suitable generalization of the regularization technique proposed by Mail let for a simpler class of non-ultralocal models, and find the corresponding r- and s-matrices. We also make a connection between the operator-regularization method proposed earlier for the quantum case, and the Mail let's symmetric limit regularization prescription used for non-ultralocal algebras in the classical theory.

Estimación del movimiento de objetos en secuencias de imágenes de intensidad y profundidad

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Optical flow estimation with consistent spatio-temporal coherence models

[EN] In this work we propose a new variational model for the consistent estimation of motion fields. The aim of this work is to develop appropriate spatio-temporal coherence models. In this sense, we propose two main contributions: a nonlinear flow constancy assumption, similar in spirit to the nonlinear brightness constancy assumption, which conveniently relates flow fields at different time instants; and a nonlinear temporal regularization scheme, which complements the spatial regularization and can cope with piecewise continuous motion fields. These contributions pose a congruent variational model since all the energy terms, except the spatial regularization, are based on nonlinear warpings of the flow field. This model is more general than its spatial counterpart, provides more accurate solutions and preserves the continuity of optical flows in time. In the experimental results, we show that the method attains better results and, in particular, it considerably improves the accuracy in the presence of large displacements.

TV-L1 optical flow estimation

[EN] This article describes an implementation of the optical flow estimation method introduced by Zach, Pock and Bischof. This method is based on the minimization of a functional containing a data term using the L norm and a regularization term using the total variation of the flow. The main feature of this formulation is that it allows discontinuities in the flow field, while being more robust to noise than the classical approach. The algorithm is an efficient numerical scheme, which solves a relaxed version of the problem by alternate minimization.

Temporal constraints in large optical flow estimation

[EN] The aim of this work is to propose a model for computing the optical flow in a sequence of images. We introduce a new temporal regularizer that is suitable for large displacements. We propose to decouple the spatial and temporal regularizations to avoid an incongruous formulation. For the spatial regularization we use the Nagel-Enkelmann operator and a newly designed temporal regularization. Our model is based on an energy functional that yields a partial differential equation (PDE). This PDE is embedded into a multipyramidal strategy to recover large displacements. A gradient descent technique is applied at each scale to reach the minimum.

Robust optical flow estimation

[EN] In this work, we describe an implementation of the variational method proposed by Brox et al. in 2004, which yields accurate optical flows with low running times. It has several benefits with respect to the method of Horn and Schunck: it is more robust to the presence of outliers, produces piecewise-smooth flow fields and can cope with constant brightness changes. This method relies on the brightness and gradient constancy assumptions, using the information of the image intensities and the image gradients to find correspondences. It also generalizes the use of continuous L1 functionals, which help mitigate the efect of outliers and create a Total Variation (TV) regularization. Additionally, it introduces a simple temporal regularization scheme that enforces a continuous temporal coherence of the flow fields.