New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

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

Application of wavelets to the evaluation of phantom images for mammography quality control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Biological shape analysis by digital curvature

This paper reports the novel application of digital curvature as a feature for morphological characterization and classification of landmark shapes. By inheriting several unique features of the continuous curvature, the digital curvature provides invariance to translations, rotations, local shape deformations, and is easily made tolerant to scaling. In addition, the bending energy, a global shape feature, can be directly estimated from the curvature values. The application of these features to analyse patterns of cranial morphological geographic differentiation in the rodent species Thrichomys apereoides has led to encouraging results, indicating a close correspondence between the geographical and morphological distributions. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Conjunctival impression cytology in dogs

Objective Ocular conjunctivas of healthy dogs were studied by conjunctival impression cytology for evaluation of feasibility, protocol standardization, and normal cytologic pattern recognition of this technique.Animals studied Twenty healthy, adult, cross-breed dogs.Procedures Samples of the bulbar conjunctiva were collected after instillation of topical anesthetic drops at the ocular surface. Impression cytology was performed by applying asymmetric strips of Millipore filter on the superior temporal bulbar conjunctiva near the limbus. The filter strip was gently pressed against the conjunctiva for 5 s and removed with a peeling motion. Samples were immediately fixed in 95% ethyl alcohol, stained with periodic acid-Schiff and hematoxylin, and mounted on slides cover-slipped using synthetic resin. The slides were examined by light microscopy.Results Microscopic examination of the impressions revealed superficial, intermediate and basal epithelial cells arranged in sheets. Keratinized epithelial cells, goblet cells and leukocytes, as well as cellular debris and mucus were observed.Conclusions Feasibility of impression cytology for sampling the bulbar conjunctiva of the dog and the standardization the the proposed protocol was shown. The results allowed the recognition the the normal cytologic pattern of healthy conjunctivas in dogs.

A structure-activity relationship study of quinone compounds with trypanocidal activity

A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T-5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi. (c) 2005 Elsevier SAS. All rights reserved.

Optimum-Path Forest Classifier for Large Scale Biometric Applications

This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.

Interactions between TLR2, TLR4, and mannose receptors with gp43 from Paracoccidioides brasiliensis induce cytokine production by human monocytes

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

A Fast Large Scale Iris Database Classification with Optimum-Path Forest Technique: A Case Study

Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.

Anaerobic threshold estimation by statistical modelling.

Anaerobic threshold (AT) is usually estimated as a change point problem by visual analysis of the cardiorespiratory response to incremental dynamic exercise. In this study, two phase linear (TPL) models of the linear-linear and linear-quadratic type were used for the estimation of AT. The correlation coefficient between the classical and statistical approaches was 0.88, and 0.89 after outlier exclusion. The TPL models provide a simple method for estimating AT that can be easily implemented using a digital computer for the automatic pattern recognition of AT.

Rede neural não supervisionada baseada em transformada Karhunen-Loève para processamento, compressão e reconhecimento de imagens

The merit of the Karhunen-Loève transform is well known. Since its basis is the eigenvector set of the covariance matrix, a statistical, not functional, representation of the variance in pattern ensembles is generated. By using the Karhunen-Loève transform coefficients as a natural feature representation of a character image, the eigenvector set can be regarded as an feature extractor for a classifier.

Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning

In this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.

Cross-cultural differences for three visual memory tasks in Brazilian children

Norms for three visual memory tasks, including Corsi's block tapping test and the BEM 144 complex figures and visual recognition, were developed for neuropsychological assessment in Brazilian children. The tasks were measured in 127 children ages 7 to 10 years from rural and urban areas of the States of São Paulo and Minas Gerais. Analysis indicated age-related but not sex-related differences. A cross-cultural effect was observed in relation to copying and recall of Complex pictures. Different performances between rural and urban children were noted. © Perceptual and Motor Skills 2005.

Extração semi-automática de rodovias em um par de imagens aéreas digitais utilizando geometria epipolar e programação dinâmica

The purpose of this paper is to introduce a methodology for semi-automatic road extraction from aerial digital image pairs by using dynamic programming and epipolar geometry. The method uses both images from where each road feature pair is extracted. The operator identifies the corresponding road featuresand s/he selects sparse seed points along them. After all road pairs have been extracted, epipolar geometry is applied to determine the automatic point-to-point correspondence between each correspondent feature. Finally, each correspondent road pair is georeferenced by photogrammetric intersection. Experiments were made with rural aerial images. The results led to the conclusion that the methodology is robust and efficient, even in the presence of shadows of trees and buildings or other irregularities.

Automated extraction of road network from medium-and high-resolution images

This paper presents an automatic methodology for road network extraction from medium-and high-resolution aerial images. It is based on two steps. In the first step, the road seeds (i.e., road segments) are extracted using a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each road seed is composed by a sequence of connected road objects in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. In the second step, two strategies for road completion are applied in order to generate the complete road network. The first strategy is based on two basic perceptual grouping rules, i.e., proximity and collinearity rules, which allow the sequential reconstruction of gaps between every pair of disconnected road segments. This strategy does not allow the reconstruction of road crossings, but it allows the extraction of road centerlines from the contiguous quadrilaterals representing connected road segments. The second strategy for road completion aims at reconstructing road crossings. Firstly, the road centerlines are used to find reference points for road crossings, which are their approximate positions. Then these points are used to extract polygons representing the contours of road crossings. This paper presents the proposed methodology and experimental results. © Pleiades Publishing, Inc. 2006.

Orientação semi-automática de imagens CBERS usando rodovias como controle de campo

In this paper is proposed a methodology for semiautomatic CBERS image orientation using roads as ground control. It is based on an iterative strategy involving three steps. In the first step, an operator identifies on the image the ground control roads and supplies along them a few seed points, which could be sparsely and coarsely distributed. These seed points are used by the dynamic programming algorithm for extracting the ground control roads from the image. In the second step, it is established the correspondences between points describing the ground control roads and the corresponding ones extracted from the image. In the last step, the corresponding points are used to orient the CBERS image by using the DLT (Direct Linear Transformation). The two last steps are iterated until the convergence of the orientation process is verified. Experimental results showed that the proposed methodology was efficient with several test images. In all cases the orientation process converged. Moreover, the estimated orientation parameters allowed the registration of check roads with pixel accuracy or better.