Formação do educador no curso de pedagogia de Caicó-RN: reprodução ou transformação social

ARAÚJO, Marta Maria de. Formação do educador no curso de pedagogia de Caicó-RN: reprodução ou transformação social. Porto Alegre, 1985. Dissertação (Mestrado) - Curso de Pós-graduação em Educação. Universidade Federal do Rio Grande do Sul, Porto alegre, 1985

Análise da organização da rede de saúde da Paraíba a partir do modelo de regionalização

Este artigo analisa a organização da rede de saúde da Paraíba a partir do modelo de regionalização proposto pelo estado da Paraíba. Material e Métodos: Trata-se de um estudo documental que tomou por base, prioritariamente, o Plano Diretor de Regionalização da Paraíba e os documentos oficiais do Ministério da Saúde que orientam a construção dos mesmos pelos Estados. Resultados: A análise dos dados revelou alguns limites no processo de implantação do PDR/ PB, tais como a ausência de análise das características sociais, econômicas e culturais durante a escolha das sedes das regiões de saúde e a inexistente descrição da organização da assistência à saúde do território estadual. Conclusão: O processo de regionalização e a formulação do PDR da Paraíba não seguiram a Instrução Normativa do Ministério da Saúde em alguns aspectos, desconsiderando as especificidades de cada região de saúde, o que pode resultar em problemas no acesso e na articulação da rede de serviços com vistas à legitimação das regiões de saúde desse Estado

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

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

Análise de métodos para detecção de mudanças estruturais em séries temporais climáticas

The time series analysis has played an increasingly important role in weather and climate studies. The success of these studies depends crucially on the knowledge of the quality of climate data such as, for instance, air temperature and rainfall data. For this reason, one of the main challenges for the researchers in this field is to obtain homogeneous series. A time series of climate data is considered homogeneous when the values of the observed data can change only due to climatic factors, i.e., without any interference from external non-climatic factors. Such non-climatic factors may produce undesirable effects in the time series, as unrealistic homogeneity breaks, trends and jumps. In the present work it was investigated climatic time series for the city of Natal, RN, namely air temperature and rainfall time series, for the period spanning from 1961 to 2012. The main purpose was to carry out an analysis in order to check the occurrence of homogeneity breaks or trends in the series under investigation. To this purpose, it was applied some basic statistical procedures, such as normality and independence tests. The occurrence of trends was investigated by linear regression analysis, as well as by the Spearman and Mann-Kendall tests. The homogeneity was investigated by the SNHT, as well as by the Easterling-Peterson and Mann-Whitney-Pettit tests. Analyzes with respect to normality showed divergence in their results. The von Neumann ratio test showed that in the case of the air temperature series the data are not independent and identically distributed (iid), whereas for the rainfall series the data are iid. According to the applied testings, both series display trends. The mean air temperature series displays an increasing trend, whereas the rainfall series shows an decreasing trend. Finally, the homogeneity tests revealed that all series under investigations present inhomogeneities, although they breaks depend on the applied test. In summary, the results showed that the chosen techniques may be applied in order to verify how well the studied time series are characterized. Therefore, these results should be used as a guide for further investigations about the statistical climatology of Natal or even of any other place.

Levantamentos epidemiológicos em saúde bucal: análise da metodologia proposta pela Organização Mundial da Saúde

Epidemiological surveys are important for obtaining information on the prevalence and etiology of mouth diseases, since the data collected permit health actions to be planned, performed, and assessed. Methodological uniformity is necessary, however, to maintain reproductibility, validity, and reliability, and to allow national and international comparisons. The initiative of the World Health Organization (WHO) as an advisor in ongoing surveys has been extremely useful, stimulating standardization in all countries. In 1991, a Portuguese version of the 1987 third edition of Oral Health Surveys - basic methods, an instruction manual for performing epidemiological surveys, was published and became a reference for many parts of Brazil and the World. The present analysis found conflicting points in relation to the sample size, calibration of the examiners, and criteria for evaluating oral health and treatment needs. In conclusion, due to the dynamic characteristics of scientific knowledge and, considering the regional differences in relation to the development of oral diseases, we recommend that proposals for standardizing surveys be checked periodically. Other important issues may have not been detected in this analysis, urging a thorough discussion within the dentistry community as a whole.

Levantamentos epidemiológicos em saúde bucal: análise da metodologia proposta pela Organização Mundial da Saúde

Epidemiological surveys are important for obtaining information on the prevalence and etiology of mouth diseases, since the data collected permit health actions to be planned, performed, and assessed. Methodological uniformity is necessary, however, to maintain reproductibility, validity, and reliability, and to allow national and international comparisons. The initiative of the World Health Organization (WHO) as an advisor in ongoing surveys has been extremely useful, stimulating standardization in all countries. In 1991, a Portuguese version of the 1987 third edition of Oral Health Surveys - basic methods, an instruction manual for performing epidemiological surveys, was published and became a reference for many parts of Brazil and the World. The present analysis found conflicting points in relation to the sample size, calibration of the examiners, and criteria for evaluating oral health and treatment needs. In conclusion, due to the dynamic characteristics of scientific knowledge and, considering the regional differences in relation to the development of oral diseases, we recommend that proposals for standardizing surveys be checked periodically. Other important issues may have not been detected in this analysis, urging a thorough discussion within the dentistry community as a whole.

Formação do educador no curso de pedagogia de Caicó-RN: reprodução ou transformação social

ARAÚJO, Marta Maria de. Formação do educador no curso de pedagogia de Caicó-RN: reprodução ou transformação social. Porto Alegre, 1985. Dissertação (Mestrado) - Curso de Pós-graduação em Educação. Universidade Federal do Rio Grande do Sul, Porto alegre, 1985

Análise da organização da rede de saúde da Paraíba a partir do modelo de regionalização

Este artigo analisa a organização da rede de saúde da Paraíba a partir do modelo de regionalização proposto pelo estado da Paraíba. Material e Métodos: Trata-se de um estudo documental que tomou por base, prioritariamente, o Plano Diretor de Regionalização da Paraíba e os documentos oficiais do Ministério da Saúde que orientam a construção dos mesmos pelos Estados. Resultados: A análise dos dados revelou alguns limites no processo de implantação do PDR/ PB, tais como a ausência de análise das características sociais, econômicas e culturais durante a escolha das sedes das regiões de saúde e a inexistente descrição da organização da assistência à saúde do território estadual. Conclusão: O processo de regionalização e a formulação do PDR da Paraíba não seguiram a Instrução Normativa do Ministério da Saúde em alguns aspectos, desconsiderando as especificidades de cada região de saúde, o que pode resultar em problemas no acesso e na articulação da rede de serviços com vistas à legitimação das regiões de saúde desse Estado

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