Metodologia projetual para produtos de moda e a sua interface com as tabelas de medidas do vestuário

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação de forças manuais em atividades simuladas com indivíduos adultos brasileiros de diferentes gêneros e faixas etárias: aspectos do design ergonômico. -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de sistema computacional para pré-dimensionamento de turbinas para micro, mini e pequenas centrais hidrelétricas

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Desenvolvimento de um sistema computacional para monitoramento de parâmetros físicos na área de irrigação, com base na plataforma labVIEW

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A interface da urgência em saúde bucal no SUS: o caso de um Pronto Socorro, no município de São Paulo, 2006

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Implementação de uma plataforma HW/SW para automação industrial, utilizando hardware reconfigurável com processador NIOS II em conformidade com o padrão IEEE 1451

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

O desenvolvimento moral em aulas de Ciências: explorando uma interface de contribuições

Pós-graduação em Educação para a Ciência - FC

A interface música e linguística como instrumental metodológico para o estudo da prosódia do português arcaico

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Embalagens de medicamentos: diretrizes para o desenvolvimento

Pós-graduação em Design - FAAC

Projeto e desenvolvimento de robô cartesiano de baixo custo para manipulação de produtos em linhas de média cadência

Pós-graduação em Engenharia Elétrica - FEB

Cellular behavior as a dynamic field for exploring bone bioengineering: A closer look at cell-biomaterial interface

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

DEVELOPMENT OF AN ALGORITHM TO ANALYZE CARTOGRAPHIC FEATURES EXTRACTION METHODS IN DIGITAL IMAGES

The algorithm creates a buffer area around the cartographic features of interest in one of the images and compare it with the other one. During the comparison, the algorithm calculates the number of equals and different points and uses it to calculate the statistical values of the analysis. One calculated statistical value is the correctness, which shows the user the percentage of points that were correctly extracted. Another one is the completeness that shows the percentage of points that really belong to the interest feature. And the third value shows the idea of quality obtained by the extraction method, since that in order to calculate the quality the algorithm uses the correctness and completeness previously calculated. All the performed tests using this algorithm were possible to use the statistical values calculated to represent quantitatively the quality obtained by the extraction method executed. So, it is possible to say that the developed algorithm can be used to analyze extraction methods of cartographic features of interest, since that the results obtained were promising.

Interface com o AEDROMO (Ambiente experimental e didático com robôs móveis) utilizando sistema Android

The AEDROMO (Experimental and Didactic Environment with Mobile Robots) is a versatile, user friendly and scalable environment that supports a wide range of experiments. In it there is an area that is similar to a desk where objects can interact with each other, including robots and other objects, and thus can perform numerous activities. In it's current state, AEDROMO has client computers that interact with the system through an interface, and thus realize the communication between the user and AEDROMO. This project offer support to create a new form of interface for AEDROMO and can therefore be used for devices running Android, the app developed in this project will serve as a basis for future work on this new interface

Interface para classificação de dados por máquinas de vetores de suporte

In this project the Pattern Recognition Problem is approached with the Support Vector Machines (SVM) technique, a binary method of classification that provides the best solution separating the data in the better way with a hiperplan and an extension of the input space dimension, as a Machine Learning solution. The system aims to classify two classes of pixels chosen by the user in the interface in the interest selection phase and in the background selection phase, generating all the data to be used in the LibSVM library, a library that implements the SVM, illustrating the library operation in a casual way. The data provided by the interface is organized in three types, RGB (Red, Green and Blue color system), texture (calculated) or RGB + texture. At last the project showed successful results, where the classification of the image pixels was showed as been from one of the two classes, from the interest selection area or from the background selection area. The simplest user view of results classification is the RGB type of data arrange, because it’s the most concrete way of data acquisition

Use, development and improvements in the protocol of whole-sediment toxicity identification evaluation using benthic copepods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)