Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

O problema mente-corpo na psicologia fenomenológica de Edith Stein : implicações para uma fundamentação da ciência psicológica

Psychology is a relatively new scientific branch and still lacks consistent methodological foundation to support its investigations. Given its immaturity, this science finds difficulties to delimit its ontological status, which spawnes several epistemological and methodological misconceptions. Given this, Psychology failed to demarcate precisely its object of study, leading, thus, the emergence of numerous conceptions about the psychic, which resulted in the fragmentation of this science. In its constitution, psychological science inherited a complex philosophical problem: the mind-body issue. Therefore, to define their status, Psychology must still face this problem, seeking to elucidate what is the mind, the body and how they relate. In light of the importance of this issue to a strict demarcation of psychological object, it was sought in this research, to investigate the mind-body problem in the Phenomenological Psychology of Edith Stein (1891-1942), phenomenologist philosopher who undertook efforts for a foundation of Psychology. For that, the discussion was subsidized from the contributions of the Philosophy of Mind and the support of the phenomenological method to the mind-body problem. From there, by a qualitative bibliographical methodology, it sought to examine the problem of research through the analysis of some philosophical-psychological philosopher's works, named: "Psychic Causality” (Kausalität Psychische, 1922) and “Introduction to Philosophy" (Einführung in die Philosophie, 1920). For this investigation, it was made, without prejudice to the discussion, a terminological equivalence between the terms mind and psyche, as the philosopher used the latter to refer to the object of Psychology. It sought to examine, therefore, how Stein conceived the psyche, the body and the relationship between them. Although it wasn't the focus of the investigation, it also took into account the spiritual dimension, as the philosopher conceived the human person as consisting of three dimensions: body, psyche and spirit. Given this, Stein highlighted the causal mechanism of the psyche, which is based on the variations of the vital force that emerges from the vital sphere. In relation to the corporeal dimension, the philosopher, following the analysis of Edmund Husserl (1859-1938), highlighted the dual aspect of the body, because it is at the same time something material (Körper) and also a linving body (Leib). On the face of it, it is understood that the psyche and the body are closely connected, so that it constitutes a dual-unit which is manifested in the Leib. This understanding of the problem psyche-mind/body provides a rich analysis of this issue, enabling the overcoming of some inconsistencies of the monistic and dualistic positions. Given this, it allows a strict elucidation of the Psychology object, contributing to the foundation of this science.

Projeto iterativo, simulação, análise e otimização de máquina a relutância variável monofásica

Variable reluctance motors have been increasingly used as an alternative for variable speed and high speed drives in many industrial applications, due to many advantages like the simplicity of construction, robustness, and low cost. The most common applications in recent years are related to aeronautics, electric and hybrid vehicles and wind power generation. This paper explores the theory, operation, design procedures and analysis of a variable reluctance machine. An iterative design methodology is introduced and used to design a 1.25 kW prototype. For the analysis of the machine two methods are used, an analytical method and the finite element simulation. The results obtained by both methods are compared. The results of finite element simulation are used to determine the inductance profiles and torque of the prototype. The magnetic saturation is examined visually and numerically in four critical points of the machine. The data collected in the simulation allow the verification of design and operating limits for the prototype. Moreover, the behavior of the output quantities is analyzed (inductance, torque and magnetic saturation) by variation of physical dimensions of the motor. Finally, a multiobjective optimization using Differential Evolution algorithms and Genetic Algorithms for switched reluctance machine design is proposed. The optimized variables are rotor and stator polar arcs, and the goals are to maximize the average torque, the average torque per copper losses and the average torque per core volume. Finally, the initial design and optimized design are compared.