Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Comparison of non-linear growth models to describe the growth curve in West African Dwarf sheep

The objectives of this study were to compare the goodness of fit of four non-linear growth models, i.e. Brody, Gompertz, Logistic and Von Bertalanffy, in West African Dwarf (WAD) sheep. A total of 5274 monthly weight records from birth up to 180 days of age from 889 lambs, collected during 2001 to 2004 in Betecoucou breeding farm in Benin were used. In the preliminary analysis, the General Linear Model Procedure of the Statistical Analysis Systems Institute was applied to the dataset to identify the significant effects of the sex of lamb (male and female), type of birth (single and twin), season of birth (rainy season and dry season), parity of dam (1, 2 and 3) and year of birth (2001, 2002, 2003 and 2004) on the observed birth weight and monthly weight up to 6 months of age. The models parameters (A, B and k), coefficient of determination (112), mean square error (MSE) were calculated using language of technical computing package Matlab(R), 2006. The mean values of A, B and k were substituted into each model to calculate the corresponding Akaike's Information Criterion (AIC). Among the four growth functions, the Brody model has been selected for its accuracy of fit according to the higher R(2), lower MSE and A/C Finally, the parameters A, B and k were adjusted in Matlab(R) 2006 for the sex of lamb, year of birth, season of birth, birth type and the parity of ewe, providing a specific slope of the Brody growth curve. The results of this study suggest that Brody model can be useful for WAD sheep breeding in Betecoucou farm conditions through growth monitoring.

Estimativas das componentes da radiação solar incidente em superfícies inclinadas baseadas na radiação global horizontal

Statistics equations and validations with groups of annual and monthly data were evaluated for global, direct and diffuse solar radiation components incident on the tilted surface to 12.85, 22.85 and 32.85 degrees with the face North, in climate and geographical conditions of Botucatu, SP. It was employed the fractions of three components of extraterrestrial radiation in correlation with the coefficient clearness index horizontal plane, in a database of April/1998 to December/2007, whose measures at different periods in three inclinations, however concomitant to the horizontal plane. Increasing the angle of the surface led to increased scattering of the daily values of clearness index for inclined and horizontal surfaces. In annual groups, the lower performances were observed in the estimation of inclined daily diffuse radiation, with maximum Root Mean Square Error to 3.89 MJ m(-2) d(-1) (43.65%) and adjustments around 62%. In estimates of global and direct components of solar radiation on inclined planes, both annual and monthly equations can be applied, with performance dependents to climatic conditions.

Estimativa da radiação global incidente em superfícies inclinadas por modelos isotrópicos e índice de claridade

O objetivo deste trabalho foi avaliar o desempenho de modelos isotrópicos de estimativa do total de radiação incidente em superfícies inclinadas e propor estimativas com base nas correlações entre os índices de claridade horizontais e inclinados, em diferentes condições de cobertura de céu, em Botucatu, SP. Foram avaliadas superfícies com inclinação de 12,85º, 22,85º e 32,85º, pelos modelos isotrópicos propostos por Liu & Jordan, Revfeim, Jimenez & Castro, Koronakis, a teoria Circunsolar, e a correlação entre os índices de claridade horizontais e inclinados, para diferentes condições de cobertura de céu. O banco de dados de radiação global utilizado corresponde ao período de 1998 a 2007, com intervalos de 4/1998 a 8/2001 para a inclinação de 22,85º, de 9/2001 a 2/2003 para 12,85º e de 1/2004 a 12/2007 para 32,85º. O desempenho dos modelos foi avaliado pelos indicadores estatísticos erro absoluto médio, raiz quadrada do quadrado médio do erro e índice d de Wilmott. Os modelos de Liu & Jordan, Koronakis e de Revfeim apresentaram os melhores desempenhos em dias nublados, em todas as inclinações. As coberturas de céu parcialmente difuso e parcialmente aberto, nos maiores ângulos de inclinação, apresentaram as maiores dispersões entre valores estimados e medidos, independentemente do modelo. As equações estatísticas apresentaram bons resultados em aplicações com agrupamentos de dados mensais.

Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

Adaptação transcultural Portugal-Brasil do Inventário de Burnout de Maslach para estudantes

OBJETIVO: Realizar a adaptação transcultural da versão em português do Inventário de Burnout de Maslach para estudantes e investigar sua confiabilidade, validade e invariância transcultural. MÉTODOS: A validação de face envolveu participação de equipe multidisciplinar. Foi realizada validação de conteúdo. A versão em português foi preenchida em 2009, pela internet, por 958 estudantes universitários brasileiros e 556 portugueses da zona urbana. Realizou-se análise fatorial confirmatória utilizando-se como índices de ajustamento o χ²/df, o comparative fit index (CFI), goodness of fit index (GFI) e o root mean square error of approximation (RMSEA). Para verificação da estabilidade da solução fatorial conforme a versão original em inglês, realizou-se validação cruzada em 2/3 da amostra total e replicada no 1/3 restante. A validade convergente foi estimada pela variância extraída média e confiabilidade composta. Avaliou-se a validade discriminante e a consistência interna foi estimada pelo coeficiente alfa de Cronbach. A validade concorrente foi estimada por análise correlacional da versão em português e dos escores médios do Inventário de Burnout de Copenhague; a divergente foi comparada à Escala de Depressão de Beck. Foi avaliada a invariância do modelo entre a amostra brasileira e a portuguesa. RESULTADOS: O modelo trifatorial de Exaustão, Descrença e Eficácia apresentou ajustamento adequado (χ²/df = 8,498; CFI = 0,916; GFI = 0,902; RMSEA = 0,086). A estrutura fatorial foi estável (λ: χ²dif = 11,383, p = 0,50; Cov: χ²dif = 6,479, p = 0,372; Resíduos: χ²dif = 21,514, p = 0,121). Observou-se adequada validade convergente (VEM = 0,45;0,64, CC = 0,82;0,88), discriminante (ρ² = 0,06;0,33) e consistência interna (α = 0,83;0,88). A validade concorrente da versão em português com o Inventário de Copenhague foi adequada (r = 0,21;0,74). A avaliação da validade divergente do instrumento foi prejudicada pela aproximação do conceito teórico das dimensões Exaustão e Descrença da versão em português com a Escala de Beck. Não se observou invariância do instrumento entre as amostras brasileiras e portuguesas (λ:χ²dif = 84,768, p < 0,001; Cov: χ²dif = 129,206, p < 0,001; Resíduos: χ²dif = 518,760, p < 0,001). CONCLUSÕES: A versão em português do Inventário de Burnout de Maslach para estudantes apresentou adequada confiabilidade e validade, mas sua estrutura fatorial não foi invariante entre os países, apontando ausência de estabilidade transcultural.

Likelihood approximations and discrete models for tied survival data

Ties among event times are often recorded in survival studies. For example, in a two week laboratory study where event times are measured in days, ties are very likely to occur. The proportional hazards model might be used in this setting using an approximated partial likelihood function. This approximation works well when the number of ties is small. on the other hand, discrete regression models are suggested when the data are heavily tied. However, in many situations it is not clear which approach should be used in practice. In this work, empirical guidelines based on Monte Carlo simulations are provided. These recommendations are based on a measure of the amount of tied data present and the mean square error. An example illustrates the proposed criterion.

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Uma experiência com modelo estatístico (MOS) para a previsão da temperatura mínima diária do ar

Uma equação de regressão múltipla MOS (da sigla em inglês para Model Output Statistics), para previsão da temperatura mínima diária do ar na cidade de Bauru, estado de São Paulo, é desenvolvida. A equação de regressão múltipla, obtida usando análise de regressão stepwise, tem quatro preditores, três do modelo numérico global do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC) e um observacional da estação meteorológica do Instituto de Pesquisas Meteorológicas (IPMet), Bauru. Os preditores são prognósticos para 24 horas do modelo global, válidos para 00:00GMT, da temperatura em 1000hPa, vento meridional em 850hPa e umidade relativa em 1000hPa, e temperatura observada às 18:00GMT. Esses quatro preditores explicam, aproximadamente, 80% da variância total do preditando, com erro quadrático médio de 1,4°C, que é aproximadamente metade do desvio padrão da temperatura mínima diária do ar observada na estação do IPMet. Uma verificação da equação MOS com uma amostra independente de 47 casos mostra que a previsão não se deteriora significativamente quando o preditor observacional for desconsiderado. A equação MOS, com ou sem esse preditor, produz previsões com erro absoluto menor do que 1,5°C em 70% dos casos examinados. Este resultado encoraja a utilização da técnica MOS para previsão operacional da temperatura mínima e seu desenvolvimento para outros elementos do tempo e outras localidades.

Validity and reliability of the Portuguese version of Mandibular Function Impairment Questionnaire

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

Neural networks training using the constructivism paradigms

The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constructivism, an alphabetization method proposed by Emilia Ferreiro based on Piaget philosophy. Simulation results show that the proposed configuration usually obtains a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.