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.

Automatic Indexing and Information Visualization: A Study Based on Paraconsistent Logic

This paper reports a research to evaluate the potential and the effects of use of annotated Paraconsistent logic in automatic indexing. This logic attempts to deal with contradictions, concerned with studying and developing inconsistency-tolerant systems of logic. This logic, being flexible and containing logical states that go beyond the dichotomies yes and no, permits to advance the hypothesis that the results of indexing could be better than those obtained by traditional methods. Interactions between different disciplines, as information retrieval, automatic indexing, information visualization, and nonclassical logics were considered in this research. From the methodological point of view, an algorithm for treatment of uncertainty and imprecision, developed under the Paraconsistent logic, was used to modify the values of the weights assigned to indexing terms of the text collections. The tests were performed on an information visualization system named Projection Explorer (PEx), created at Institute of Mathematics and Computer Science (ICMC - USP Sao Carlos), with available source code. PEx uses traditional vector space model to represent documents of a collection. The results were evaluated by criteria built in the information visualization system itself, and demonstrated measurable gains in the quality of the displays, confirming the hypothesis that the use of the para-analyser under the conditions of the experiment has the ability to generate more effective clusters of similar documents. This is a point that draws attention, since the constitution of more significant clusters can be used to enhance information indexing and retrieval. It can be argued that the adoption of non-dichotomous (non-exclusive) parameters provides new possibilities to relate similar information.

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

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

Recycling of silicon carbide and corn starch as binder originating from commercial starch consolidation

The main goal of this work is to demonstrate that the use of recycled material originated from SiC ceramics is viable. These ceramics were produced by commercial starch consolidation process. Before calcination stage, surplus of these materials always appears. This surplus is rich in SiC and starch. Samples were made by material previously milled in automatic mortar and sieved (100 Tyler). Later, 10% of distilled water was added to the material and the mixture was pressed at 40 MPa. In order to characterize the ceramic, three point flexural test were made, according to the ASTM C1161/94 norm. The results were analyzed by Weibull statistical method. Apparent density and porosity measures also were made, according to ASTM C20/87 norm. A verification of the surface was made in the fracture area by the depth from focus method and SEM image analysis. The results showed that the recycling process is fully viable, being a good economic option and reduce possible pollutant effect to the environment.

Fault identification in distribution lines using intelligent systems and statistical methods

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Prevalence and etiology of buffalo mastitis and milk somatic cell countin dry and rainy seasons in a buffalo herd from Analândia, São Paulo State,Brazil

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

Weather variables, water balance, growth, and agro industrial yield of sugarcane

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Indexação automatizada de artigos de periódicos científicos: análise da aplicação do software SISA com uso da terminologia DeCS na área de Odontologia

The indexing automation has been discussed by researches in the area of Information Science however the discussions have not been so clear on the use of indexing software. Thus, it is necessary to know the indexing software, as well as its application in the analysis of documentary contents. To do so, it is proposed, here, to investigate both the consistency of indexing and the exhaustiveness and precision of the information retrieval, by means of comparative analysis between SISA (Sistema de Indizacion Semi-Automatico) automatic index and BIREME ( Centro Latino-Americano e do Caribe de Informação em Ciencias da Saude) manual indexing. The aim of this paper is to contribute to the theoretical development of the indexing automation and the improvement of SISA. Thus, SISA application and evaluation was used based on the calculation of the consistency indexes between the two types of indexing, and the calculation of the exhaustiveness and precision indexes in information retrieval, by means of searching into BDSISA and BIREME databases, composed by descriptors taken from SISA and manual indexing respectively. The differences among the terms used in scientific papers comparing to the DeCS ones were the main difficult factor to achieve higher consistency indexes in the indexing. These differences influenced the exhaustiveness and precision indexes in the information retrieval, showing that it is necessary to improve the documentary language used by SISA software and to incorporate linguistic methods.

Structural abnormalities of the thalamus in juvenile myoclonic epilepsy

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

Measurement of the differential cross section for the production of an isolated photon with associated jet in p(p)over-bar collisions at root s=1.96 TeV

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

Adaptative techniques for the human faces detection

This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

The embodied embedded character of system 1 processing

In the last thirty years, a relatively large group of cognitive scientists have begun characterising the mind in terms of two distinct, relatively autonomous systems. To account for paradoxes in empirical results of studies mainly on reasoning, Dual Process Theories were developed. Such Dual Process Theories generally agree that System 1 is rapid, automatic, parallel, and heuristic-based and System 2 is slow, capacity-demanding, sequential, and related to consciousness. While System 2 can still be decently understood from a traditional cognitivist approach, I will argue that it is essential for System 1 processing to be comprehended in an Embodied Embedded approach to Cognition.© MSM 2013.

Avaliação leucocitária de cães com linfoma submetidos ao protocolo de Madison-Wisconsin pela técnica convencional e citometria de fluxo

Lymphoma is the most common hematopoietic tumor in dogs and one of the malignant tumors with higher occurrence in this species. It is a great experimental model due to its resemblance with the non-Hodgkin lymphoma in humans. Considering the importance of the overall changes that result from to this kind of neoplastic tumor and those due to polichemotherapy this study aimed to evaluate the absolute leukon count and the total count of CD45+ cells in the blood of 25 dogs with lymphoma. Findings were crosschecked since diagnose and then once weekly during the first eight sessions of the Madison-Wisconsin chemotherapic protocol. Total granulocyte, lymphocyte and monocyte counts obtained from a conventional automatic counter and by flow cytometry were compared. Results did not reveal statistically significant changes between the two techniques.