Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN

NASCIMENTO, H. G. ; FERNANDES, L. C. ; SOUSA, M. B. C. . Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN. Publica , v. 2, p. 39-48, 2006.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Um Modelo híbrido para previsão de curvas de produção de petróleo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Potencialidade à degradação na microbacia Riacho Passagem/RN

A degradação dos recursos naturais é talvez o principal problema da região do semiárido brasileiro, e essa degradação é principalmente resultante das perdas de solo, decorrente do processo erosivo. Na busca de melhor conhecer esta problemática vem sendo empregado o processo de modelagem ambiental, cujo objetivo é identificar e propor soluções para a degradação dos solos. Nesse sentido, o trabalho aplica o modelo da Equação Universal de Perda de Solos (EUPS), desenvolvido nos Estados Unidos ao longo da década de 1950, agregado as ferramentas de geoprocessamento, informações de sensoriamento remoto e Sistemas de Informações Geográficas (SIGs). A área de estudo é a Microbacia Riacho Passagem localizada na região oeste do Estado do Rio Grande do Norte, a microbacia tem uma área de 221,7Km² e esta inserida no semiárido, região Nordeste do Brasil. A metodologia utilizada consiste: em agrupar as variáveis da EUPS no ambiente SIG utilizando imagens de satélite, levantamentos bibliográficos e trabalhos de campo. Para determinação das extensões das vertentes foi empregado o Modelo RAMPA, e para adequar a EUPS as condições da área de estudo, foram realizados ajuste através de modelos estatísticos, aperfeiçoando o trabalho e os resultados gerados pelo modelo. Ao fim do processo foi desenvolvida uma pseudo linguagem no aplicativo Linguagem Espacial para Geoprocessamento Algébrico (LEGAL) disponível no software SPRING versão 5.1.2 servindo de suporte para o processamento das informações contidas no banco de dados, base da EUPS. Os resultados demonstram que inicialmente é necessário delimitar com precisão o período seco e chuvoso, informação fundamental para a EUPS, uma vez que o trabalho busca identificar a perda de solo por erosão hídrica. O modelo RAMPA apresentou-se satisfatório e com elevado potencial de aplicação na determinação dos comprimentos de vertentes utilizando imagens de radar. Quanto ao comportamento das extensões de vertentes, na microbacia, o mesmo apresentou uma pequena variação na porção leste, maiores vertentes, área próxima a desembocadura. Após a aplicação do modelo o valor máximo de perda de solo foi 88 ton/ha.ano com núcleos localizados no NEOSSOLOS LITÓLICOS e o mínimo 0,01 ton/ha.ano localizado no domínio dos LATOSSOLOS e NEOSSOLOS FLÚVICOS. A erosão provoca diminuição do perfil de solo, principalmente nos NEOSSOLOS LITÓLICOS, resultando em alteração no balanço hídrico e conseqüentemente aumento da temperatura do solo, podendo desencadear a desertificação. Os resultados e a metodologia do presente trabalho poderão ser aplicados na busca pelo desenvolvimento sustentável, na região do semiárido brasileiro, auxiliando na compreensão do binômio uso do solo e capacidade de suporte do meio natural.

Avaliação térmica e desempenho do processo de secagem de misturas de graviola e leite em secador de leito de jorro

The soursop (A. muricata) is a fruit rich in minerals especially the potassium content. The commercialization of soursop in natura and processed has increased greatly in recent years. Drying fruit pulp in order to obtain the powdered pulp has been studied, seeking alternatives to ensure the quality of dehydrated products at a low cost of production. The high concentration of sugars reducing present in fruits causes problems of agglomeration and retention during fruit pulp drying in spouted bed dryers. On the other hand in relation to drying of milk and fruit pulp with added milk in spouted bed, promising results are reported in the literature. Based on these results was studied in this work drying of the pulp soursop with added milk in spouted bed with inert particles. The tests were based on a 24 factorial design were evaluated for the effects of milk concentration (30 to 50% m/m), drying air temperature (70 to 90 °C), intermittency time (10 to 14 min), and ratio of air velocity in relation to the minimum spout (1.2 to 1.5) on the rate of production, of powder moisture, yield, rate of drying and thermal efficiency of the process. There were physical and chemical analysis of mixtures, of powders and of mixtures reconstituted by rehydration powders. Were adjusted statistical models of first order to data the rate of production, yield and thermal efficiency, that were statistically significant and predictive. An efficiency greater than 40% under the conditions of 50% milk mixture, at 70 ° C the drying air temperature and 1.5 for the ratio between the air velocity and the minimum spout has been reached. The intermittency time showed no significant effect on the analyzed variables. The final product had moisture in the range of 4.18% to 9.99% and water activity between 0.274 to 0.375. The mixtures reconstituted by rehydration powders maintained the same characteristics of natural blends.

Sustentabilidade e gestão da pesca artesanal na costa do Semiárido Potiguar (RN), Brasil

T he socio - economy of the coastal municipalities of Rio Grande do Norte semiarid coast was analyzed th r ou g h by the actors, ant hropogenic implications, fishing environment and composition of its fish fauna, as well as the trend of product ion landed by the artisanal fleet with the aim of identifying the sustainability and management. In this study, were used participatory methodologies, monthly data of rainfall between September 2001 and December 2010; landings of the artisanal fleet during January 2001 to December 2010; and socioeconomic (IBGE, 2002/2010), (IDEMA, 2011/2012), (MPA, 2010; 2012), UNDP and MS (2013). Based on these data, we performed analysis of variance were performed using the method of Analytic Hierarchy Process (HAP) and s tatistical models of multiple regression and time series. It was identified that the occupation of the coastal and marine zone through salt industry, tourism, shrimp farming, oil and gas and wind energy reconfigured the environment and attracted new actors . Rainfall influenced the catches, of which 35% occur in the rainy season, 40% in the dry season and 25% independent. Production increased 55%, in the period analyzed , being landed in 31 ports spread over 11 municipalities, cap tured in environments mangrov e/ estuarine (23%), coastal (46%) and oceanic (31%). Despite market up 41 species, were commercialized in the region production concentrated in eight, mainly landed in Macau and Caiçara North, by vessels of small and medium - sized (motorized and sailboats) . Highlights included three species ( Hirundichthys affins , Coryphaena hippurus and Opisthonema oglinum ), which together accounted for 63.3% of the whole volume. It was found that the motorized vessels tripled in number while sailboats reduced by half. Landin gs by different types of vessels tend to increase over time, while the small sailboats vessels, decrease. The introduction of more new motorized vessels and sailboats also tend to increase production. The study concluded that GDP and HDI of coastal countie s increased however inequality persisted. The potential of artisanal fishing is in the stage “ unfavorable ” of development and the trend in fish production is to grow over time and with the entry of more vessels. However, it is urgent that the state actions to promote and enhance planning to restore fish stocks in a sustainable and profitable fisheries standards. Therefore, it is recommend the strategic use of natural resources in a sustainable development perspective.

Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN

NASCIMENTO, H. G. ; FERNANDES, L. C. ; SOUSA, M. B. C. . Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN. Publica , v. 2, p. 39-48, 2006.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Um Modelo híbrido para previsão de curvas de produção de petróleo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Um estudo sobre a variabilidade do vento no nordeste do Brasil através de métodos estatísticos e via modelos dinâmicos de meso e micro escala

The objective of this study was to determine the seasonal and interannual variability and calculate the trends of wind speed in NEB and then validate the mesoscale numerical model for after engage with the microscale numerical model in order to get the wind resource at some locations in the NEB. For this we use two data sets of wind speed (weather stations and anemometric towers) and two dynamic models; one of mesoscale and another of microscale. We use statistical tools to evaluate and validate the data obtained. The simulations of the dynamic mesoscale model were made using data assimilation methods (Newtonian Relaxation and Kalman filter). The main results show: (i) Five homogeneous groups of wind speed in the NEB with higher values in winter and spring and with lower in summer and fall; (ii) The interannual variability of the wind speed in some groups stood out with higher values; (iii) The large-scale circulation modified by the El Niño and La Niña intensified wind speed for the groups with higher values; (iv) The trend analysis showed more significant negative values for G3, G4 and G5 in all seasons and in the annual average; (v) The performance of dynamic mesoscale model showed smaller errors in the locations Paracuru and São João and major errors were observed in Triunfo; (vi) Application of the Kalman filter significantly reduce the systematic errors shown in the simulations of the dynamic mesoscale model; (vii) The wind resource indicate that Paracuru and Triunfo are favorable areas for the generation of energy, and the coupling technique after validation showed better results for Paracuru. We conclude that the objective was achieved, making it possible to identify trends in homogeneous groups of wind behavior, and to evaluate the quality of both simulations with the dynamic model of mesoscale and microscale to answer questions as necessary before planning research projects in Wind-Energy area in the NEB

Métodos estatísticos recursivos aplicados ao problema de estimação de vazão de gás em plantas de Plunger-lift

This work has as main objective to find mathematical models based on linear parametric estimation techniques applied to the problem of calculating the grow of gas in oil wells. In particular we focus on achieving grow models applied to the case of wells that produce by plunger-lift technique on oil rigs, in which case, there are high peaks in the grow values that hinder their direct measurement by instruments. For this, we have developed estimators based on recursive least squares and make an analysis of statistical measures such as autocorrelation, cross-correlation, variogram and the cumulative periodogram, which are calculated recursively as data are obtained in real time from the plant in operation; the values obtained for these measures tell us how accurate the used model is and how it can be changed to better fit the measured values. The models have been tested in a pilot plant which emulates the process gas production in oil wells