Agricultura orgânica como processo territorial no município de Chapecó-SC

Pós-graduação em Geografia - FCT

Segmentação de imagens e reconstrução de modelos aplicada a estruturas ósseas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Monitoramento das reações fisiológicas em sujeitos autistas decorrentes da influência dos sons: um estudo em Engenharia biomédica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Suspensões de veículos - Um estudo de caso

Pós-graduação em Engenharia Mecânica - FEG

Estabilidade e adaptabilidade de híbridos de milho utilizando a abordagem AMMI-bayesiano

Biplot graphics are widely employed in the study of the genotypeenvironment interactions, but they are only a graphical tool without a statistical hypothesis test. The singular values and scores (singular vectors) used in biplots correspond to specific estimates of its parameters, and the use of uncertainty measures may lead to different conclusions from those provided by a simple visual evaluation. The aim of this work is to estimate the genotype-environment interactions, using AMMI analysis, through Bayesian approach. Therefore the credibility intervals can be used for decision-making in different situations of analyses. It allows to verify the consistency of the selection and recommendation of cultivars. Two analyses were performed. The first analysis looked into 10 regular commercial hybrids and all possible 45 hybrids obtained from them. They were assessed in 15 locations. The second analysis evaluated 28 hybrids in 35 different environments, with imbalance data. The ellipses were grouped according to the standard of interaction in the biplot. The AMMI analysis with a Bayesian approach proved to be a complete analysis of stability and adaptability, which provides important information that may help the breeder in their decisions. The regions of credibility, built in the biplots, allow to perform an accurate selection and a precise genotype recommendation, with a level of credibility. Genotypes and environments can be grouped according to the existing interaction pattern, which makes possible to formulate specific recommendations. Moreover the environments can be evaluated, in order to find out which ones contribute similarly to the interaction and those to be discarted. The method makes possible to deal with imbalanced data in a natural way, showing efficiency for multienvironment trials. The prediction takes into account instability and the interaction standard of the observed data, in order to establish a direct comparison between genotypes of both 1st and 2nd seasons.

Regressão Simplex aplicada a delineamentos de mistura e utilização do Algoritmo Boosting

In the composition of this work are present two parts. The first part contains the theory used. The second part contains the two articles. The first article examines two models of the class of generalized linear models for analyzing a mixture experiment, which studied the effect of different diets consist of fat, carbohydrate, and fiber on tumor expression in mammary glands of female rats, given by the ratio mice that had tumor expression in a particular diet. Mixture experiments are characterized by having the effect of collinearity and smaller sample size. In this sense, assuming normality for the answer to be maximized or minimized may be inadequate. Given this fact, the main characteristics of logistic regression and simplex models are addressed. The models were compared by the criteria of selection of models AIC, BIC and ICOMP, simulated envelope charts for residuals of adjusted models, odds ratios graphics and their respective confidence intervals for each mixture component. It was concluded that first article that the simplex regression model showed better quality of fit and narrowest confidence intervals for odds ratio. The second article presents the model Boosted Simplex Regression, the boosting version of the simplex regression model, as an alternative to increase the precision of confidence intervals for the odds ratio for each mixture component. For this, we used the Monte Carlo method for the construction of confidence intervals. Moreover, it is presented in an innovative way the envelope simulated chart for residuals of the adjusted model via boosting algorithm. It was concluded that the Boosted Simplex Regression model was adjusted successfully and confidence intervals for the odds ratio were accurate and lightly more precise than the its maximum likelihood version.

Sistema gerador de apoio a um dicionário temático visual-gestual baseado em realidade virtual

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sistema avançado de realidade virtual para visualização de estruturas odontológicas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Conservação de energia em sistemas de iluminação pública e os seus efeitos na rede elétrica de distribuição

Pós-graduação em Engenharia Mecânica - FEG

Analise de desempenho de um sistema híbrido de geração de energia solar-eólico-diesel considerando variações probabilísticas da carga e dos recursos renováveis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Investigação óptica de pontos quânticos de InAs confinados em poços quânticos de In0,15Ga0,85As

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Biodiversidade do gênero Trichoderma (Hypocreales - fungi) mediante técnicas moleculares e análise ecofisiográfica

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

Avaliação do ensino na clínica integrada da Faculdade de Odontologia de Araraquara - UNESP em função do planejamento global de tratamento e sua execução

Pós-graduação em Ciências Odontológicas - FOAR

Construção de signos matemáticos: uma proposta metodológica para séries iniciais do ensino fundamental

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Atlas multimídia sobre movimentos de massa na sera do Mar paulista: município de Cubatão/SP

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)