Identidade pessoal em Hume e em Kant

The issue of this dissertation is the problem of personal identity. More specifically, the objective of this work is to investigate and compare how Hume and Kant construct, within their own philosophical systems, their theories of personal identity (of the self), so that these theories can set the grounds for the construction of theoretical knowledge. Hume’s theory of personal identity is closely connected to his empirical model of investigation, according to which no metaphysical conclusion can be accepted. This implies a very specific limitation to the humean description of personal identity. Because he can’t find a safe empirical reference for the self, Hume is obliged to describe it as a mere fiction, which the imagination creates to try to give unity to the set of perceptions that composes the mind. Kant, on the other hand, constructs his theory of the self with the aim of explaining the possibility of the a priori knowledge in Mathematics and in Physics. Kant tries to find which attributes must necessarily belong to the self so that this self can be, at the same time, the a priori transcendental condition of a subjectivity in general and the equally a priori transcendental condition for the construction of objective knowledge. Moreover, Kant shows the impossibility of objectively knowing, as intuition, the self, and limits himself to the description of the self as a mere subjective consciousness of the synthetic capacities of the understanding. Several disparities, thus, can be perceived between the theories of personal identity of these two authors. Based on these differences, the present work also examines the possibility of making an interpretation of the humean theory of the self by using elements of the kantian philosophy. The purpose of this kind of interpretation is to propose a solution to the difficulties faced by Hume in the description of his theory of personal identity.

Efeito do exercício físico na estabilidade de membrana de eritrócitos

CHAPTER II - This study evaluated the effects of two different types of acute aerobic exercise on the osmotic stability of human erythrocyte membrane and on different hematological and biochemical variables that are associated with this membrane property. The study population consisted of 20 healthy and active men. Participants performed single sessions of two types of exercise. The first session consisted of 60 min of moderate-intensity continuous exercise (MICE). The second session, executed a week later, consisted of high-intensity interval exercise (HIIE) until exhaustion. The osmotic stability of the erythrocyte membrane was represented by the inverse of the salt concentration (1/H50) at the midpoint of the sigmoidal curve of dependence between the absorbance of hemoglobin and the NaCl concentration. The values of 1/H50 changed from 2.29 ± 0.1 to 2.33 ± 0.09 after MICE and from 2.30 ± 0.08 to 2.23 ± 0.12 after HIIE. In MICE has occurred an increase in the mean corpuscular volume, probably due to in vivo lysis of older erythrocytes, with preservation of cells that were larger and more resistant to in vitro lysis. The study showed that a single bout of acute exercise affected the erythrocyte osmotic stability, which increased after MICE and decreased after HIIE.

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.

Uma estratégia para otimizar a geração de arranjos em subestações virtuais de energia elétrica

The Virtual Reality techniques applied in Electricity Environments provide a new supervisory control paradigm. The fact of existing a virtual environment (VE), geometrically similar to a real substation, reduces the difference of mental models built by field operators compared with those built by system center operation improving the communication. Beside this, those systems can be used as visualization interfaces for electricity system simulators, training systems for professors and undergraduate students, field operators and maintenance professionals. However, the development process of these systems is quite complex, combining several activities such as implementation, 3D modeling, virtual sceneries construction, usability assessment and management project techniques. In this context, this work present a GUI strategy to build field arrangements based on scene graphs, to reduce time in Virtual Electricity Substations Arrangement development. Through this, mistakes during the VE building can be avoided making this process more reliable. As an concept proof, all toolkits developed in this work were applied in the virtualization of the substations from a Brazilian power concessionary named CEMIG.