Aplicativo Android para aquisição de dados de um baropodômetro via Bluetooth para apoio na análise de escoliose

Pós-graduação em Engenharia Elétrica - FEIS

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

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

Sistema informatizado para dispositivos móveis de coleta dos dados referentes à cesta básica do município de Botucatu/SP

The collection of prices for basic goods supply is very important for the population, based on the collection and processing of these data the CLI (Cost Living Index) is calculated among others, helping consumers to shop more rationally and with a clearer view of each product impact of each product on their household budget, not only food, but also cleaning products and personal hygiene ones. Nowadays, the project of collection of prices for basic goods supply is conducted weekly in Botucatu - SP through a spreadsheet. The aim of this work was to develop a software which utilized mobile devices in the data collection and storage phase, concerning the basic goods supply in Botucatu -SP. This was created in order to eliminate the need of taking notes in paper spreadsheets, increasing efficiency and accelerating the data processing. This work utilized the world of mobile technology and development tools, through the platform".NET" - Compact Framework and programming language Visual Basic".NET" was used in the handheld phase, enabling to develop a system using techniques of object oriented programming, with higher speed and reliability in the codes writing. A HP Pavilion dv3 personal computer and an Eten glofish x500+ handheld computer were used. At the end of the software development, collection, data storing and processing in a report, the phase of in loco paper spreadsheets were eliminated and it was possible to verify that the whole process was faster, more consistent, safer, more efficient and the data were more available.

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

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.

Analysis of the lightning attractive radius of power transmission lines through the use of a physically-oriented model

Models of different degrees of complexity are found in the literature for the estimation of lightning striking distances and attractive radius of objects and structures. However, besides the oversimplifications of the physical nature of the lightning discharge on which most of them are based, till recently the tridimensional structure configuration could not be considered. This is an important limitation, as edges and other details of the object affect the electric field and, consequently, the upward leader initiation. Within this context, the Self-consistent leader initiation and propagation model (SLIM) proposed by Becerra and Cooray is state-of-the-art leader inception and propagation leader model based on the physics of leader discharges which enables the tridimensional geometry of the structure to be taken into account. In this paper, the model is used for estimating the striking distance and attractive radius of power transmission lines. The results are compared with those obtained from the electrogeometric and Eriksson's models. © 2003-2012 IEEE.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Patch-based local histograms and contour estimation for static foreground classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)