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)

High-resolution electrocardiography in the diagnosis of arrhythmogenic right ventricular cardiomyopathy in Boxer dogs

Com o objetivo de avaliar a importância da eletrocardiografia de alta resolução no diagnóstico da cardiomiopatia arritmogênica do ventrículo direito do Boxer, 20 cães sem evidências de doença cardíaca estrutural à avaliação ecodopplercardiográfica foram agrupados de acordo com a frequência de arritmias ventriculares, avaliadas pela eletrocardiografia ambulatorial de 24 horas, e submetidos ao exame eletrocardiográfico de alta resolução. Duração do complexo QRS filtrado, duração dos sinais de baixa amplitude (menor que 40µV) dos últimos 40 milissegundos do complexo QRS e raiz quadrada média da voltagem ao quadrado dos últimos 40 milissegundos do complexo QRS (RMS40) foram as variáveis avaliadas. Não foram observadas diferenças significativas entre os grupos em relação às variáveis estudadas. Sendo assim, os resultados do presente estudo sugerem que a eletrocardiografia de alta resolução não é uma ferramenta útil no auxílio diagnóstico da cardiomiopatia arritmogênica do ventrículo direito dos cães da raça Boxer que não apresentam alterações miocárdicas evidentes ou disfunção sistólica.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Growth curve in Santa Ines sheep

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.

Compressão auto-adaptativa de imagens coloridas

Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

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.

Extração supercrítica do óleo de linhaça: construção do extrator, estudo de parâmetros de processo, avaliação química e antioxidante do produto

The aim of the present study was to extract vegetable oil from brown linseed (Linum usitatissimum L.), determine fatty acid levels, the antioxidant capacity of the extracted oil and perform a rapid economic assessment of the SFE process in the manufacture of oil. The experiments were conducted in a test bench extractor capable of operating with carbon dioxide and co-solvents, obeying 23 factorial planning with central point in triplicate, and having process yield as response variable and pressure, temperature and percentage of cosolvent as independent variables. The yield (mass of extracted oil/mass of raw material used) ranged from 2.2% to 28.8%, with the best results obtained at 250 bar and 50ºC, using 5% (v/v) ethanol co-solvent. The influence of the variables on extraction kinetics and on the composition of the linseed oil obtained was investigated. The extraction kinetic curves obtained were based on different mathematical models available in the literature. The Martínez et al. (2003) model and the Simple Single Plate (SSP) model discussed by Gaspar et al. (2003) represented the experimental data with the lowest mean square errors (MSE). A manufacturing cost of US$17.85/kgoil was estimated for the production of linseed oil using TECANALYSIS software and the Rosa and Meireles method (2005). To establish comparisons with SFE, conventional extraction tests were conducted with a Soxhlet device using petroleum ether. These tests obtained mean yields of 35.2% for an extraction time of 5h. All the oil samples were sterilized and characterized in terms of their composition in fatty acids (FA) using gas chromatography. The main fatty acids detected were: palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2n-6) and α-linolenic (C18:3n-3). The FA contents obtained with Soxhlet dif ered from those obtained with SFE, with higher percentages of saturated and monounsaturated FA with the Soxhlet technique using petroleum ether. With respect to α-linolenic content (main component of linseed oil) in the samples, SFE performed better than Soxhlet extraction, obtaining percentages between 51.18% and 52.71%, whereas with Soxhlet extraction it was 47.84%. The antioxidant activity of the oil was assessed in the β-carotene/linoleic acid system. The percentages of inhibition of the oxidative process reached 22.11% for the SFE oil, but only 6.09% for commercial oil (cold pressing), suggesting that the SFE technique better preserves the phenolic compounds present in the seed, which are likely responsible for the antioxidant nature of the oil. In vitro tests with the sample displaying the best antioxidant response were conducted in rat liver homogenate to investigate the inhibition of spontaneous lipid peroxidation or autooxidation of biological tissue. Linseed oil proved to be more efficient than fish oil (used as standard) in decreasing lipid peroxidation in the liver tissue of Wistar rats, yielding similar results to those obtained with the use of BHT (synthetic antioxidant). Inhibitory capacity may be explained by the presence of phenolic compounds with antioxidant activity in the linseed oil. The results obtained indicate the need for more detailed studies, given the importance of linseed oil as one of the greatest sources of ω3 among vegetable oils

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.

Intercomparison of integrated water vapor estimates from multisensors in the amazonian region

Water vapor is an atmospheric component of major interest in atmospheric science because it affects the energy budget and plays a key role in several atmospheric processes. The Amazonian region is one of the most humid on the planet, and land use change is able to affect the hydrologic cycle in several areas and consequently to generate severe modifications in the global climate. Within this context, accessing the error associated with atmospheric humidity measurement and the validation of the integrated water vapor (IWV) quantification from different techniques is very important in this region. Using data collected during the Radiation, Cloud, and Climate Interactions in Amazonia during the Dry-to-Wet Transition Season (RACCI/DRY-TO-WET), an experiment carried out in southwestern Amazonia in 2002, this paper presents quality analysis of IWV measurements from RS80 radiosondes, a suite of GPS receivers, an Aerosol Robotic Network (AERONET) solar radiometer, and humidity sounding from the Humidity Sounder for Brazil (HSB) aboard the Aqua satellite. When compared to RS80 IWV values, the root-mean-square (RMS) from the AERONET and GPS results are of the order of 2.7 and 3.8 kg m(-2), respectively. The difference generated between IWV from the GPS receiver and RS80 during the daytime was larger than that of the nighttime period because of the combination of the influence of high ionospheric activity during the RACCI experiment and a daytime drier bias from the RS80.

The wavelet method as an alternative for reducing ionospheric effects from single-frequency GPS receivers

The ionospheric effect is one of the major errors in GPS data processing over long baselines. As a dispersive medium, it is possible to compute its influence on the GPS signal with the ionosphere-free linear combination of L1 and L2 observables, requiring dual-frequency receivers. In the case of single-frequency receivers, ionospheric effects are either neglected or reduced by using a model. In this paper, an alternative for single-frequency users is proposed. It involves multiresolution analysis (MRA) using a wavelet analysis of the double-difference observations to remove the short- and medium-scale ionosphere variations and disturbances, as well as some minor tropospheric effects. Experiments were carried out over three baseline lengths from 50 to 450 km, and the results provided by the proposed method were better than those from dual-frequency receivers. The horizontal root mean square was of about 0.28 m (1 sigma).