A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Improving the accuracy of the optimum-path forest supervised classifier for large datasets

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the training set. Identification of outliers is based on a penalty computed for each sample in the training set from the corresponding number of imputable false positive and false negative classification of samples. This approach enhances the accuracy of OPF while still gaining in classification time, at the expense of a slight increase in training time. © 2010 Springer-Verlag.

Improving Parkinson's disease identification through evolutionary-based feature selection

Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Território, legislação e monarquia no reinado de Alfonso X, o Sábio (1252-1284)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ideologia industrial x cultura rural: o método SESI de ensino em uma escola rural

This study compares two educational practices: the Rural School method (Escola do Campo) and the SESI teaching method, suggesting that the latter one is inefficient when applied to rural schools, as illustrated with a case study of a rural school that was obliged to adopt this method in 2012. The epistemological basis of a dialogical pedagogy for rural education has been used in order to criticize the practices of a method whose origins in the industrial ideology and in consumerism promotes a true cultural invasion, according to Paulo Freire, hindering the students' dialogues with respect to the ways of life in rural areas and in towns – an interaction that assured school performance in the previous educational system, which has been arbitrarily discontinued by the political power. Different surveys were used in this study for both compared cases, specially dissertations that have evaluated the Rural School project (Projeto Escola do Campo), adopted in Araraquara in 2004, a dissertation about the SESI teaching method that has discussed its new didactic material and, also, an evaluation of the contents of a representative sample of textbooks of History, Geography, Sciences and Mathematics for the 6th grade of elementary school. It is a theoretical text, not an essay, considering that it is based on concrete situations, which were explained using researches on the implicit themes and summarizes the analytical procedures that have allowed to unveil, in the textbooks prepared by SESI, the stimulus and the valorization of consumerism, without any criticism and environment concerns.

Directed search for gravitational waves from Scorpius X-1 with initial LIGO data

We present results of a search for continuously emitted gravitational radiation, directed at the brightest low-mass x-ray binary, Scorpius X-1. Our semicoherent analysis covers 10 days of LIGO S5 data ranging from 50-550 Hz, and performs an incoherent sum of coherent F-statistic power distributed amongst frequency-modulated orbital sidebands. All candidates not removed at the veto stage were found to be consistent with noise at a 1% false alarm rate. We present Bayesian 95% confidence upper limits on gravitational-wave strain amplitude using two different prior distributions: a standard one, with no a priori assumptions about the orientation of Scorpius X-1; and an angle-restricted one, using a prior derived from electromagnetic observations. Median strain upper limits of 1.3 x 10(-24) and 8 x 10(-25) are reported at 150 Hz for the standard and angle-restricted searches respectively. This proof-of-principle analysis was limited to a short observation time by unknown effects of accretion on the intrinsic spin frequency of the neutron star, but improves upon previous upper limits by factors of similar to 1.4 for the standard, and 2.3 for the angle-restricted search at the sensitive region of the detector.