Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil

RAMOS, Ana Maria de Oliveira et al. Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil. Pediatric and Developmental Pathology, v.3, n.1, p.29-35, 2000

Sleep and school education

Sleep has emerged in the past decades as a key process for memory consolidation and restructuring. Given the universality of sleep across cultures, the need to reduce educational inequality, the low implementation cost of a sleep-based pedagogy, and its global scalability, it is surprising that the potential of improved sleep as a means of enhancing school education has remained largely unexploited. Students of various socio-economic status often suffer from sleep deficits. In principle, the optimization of sleep schedules both before and after classes should produce large positive benefits for learning. Here we review the biological and psychological phenomena underlying the cognitive role of sleep, present the few published studies on sleep and learning that have been performed in schools, and discuss potential applications of sleep to the school setting. Translational research on sleep and learning has never seemed more appropriate.

Máquina de vetores-suporte intervalar

The Support Vector Machines (SVM) has attracted increasing attention in machine learning area, particularly on classification and patterns recognition. However, in some cases it is not easy to determinate accurately the class which given pattern belongs. This thesis involves the construction of a intervalar pattern classifier using SVM in association with intervalar theory, in order to model the separation of a pattern set between distinct classes with precision, aiming to obtain an optimized separation capable to treat imprecisions contained in the initial data and generated during the computational processing. The SVM is a linear machine. In order to allow it to solve real-world problems (usually nonlinear problems), it is necessary to treat the pattern set, know as input set, transforming from nonlinear nature to linear problem. The kernel machines are responsible to do this mapping. To create the intervalar extension of SVM, both for linear and nonlinear problems, it was necessary define intervalar kernel and the Mercer s theorem (which caracterize a kernel function) to intervalar function

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Apoiando a construção de testes de aceitação automatizados a partir da especificação de requisitos

Automation has become increasingly necessary during the software test process due to the high cost and time associated with such activity. Some tools have been proposed to automate the execution of Acceptance Tests in Web applications. However, many of them have important limitations such as the strong dependence on the structure of the HTML pages and the need of manual valuing of the test cases. In this work, we present a language for specifying acceptance test scenarios for Web applications called IFL4TCG and a tool that allows the generation of test cases from these scenarios. The proposed language supports the criterion of Equivalence Classes Partition and the tool allows the generation of test cases that meet different combination strategies (i.e., Each-Choice, Base-Choice and All Combinations). In order to evaluate the effectiveness of the proposed solution, we used the language and the associated tool for designing and executing Acceptance Tests on a module of Sistema Unificado de Administração Pública (SUAP) of Instituto Federal Rio Grande do Norte (IFRN). Four Systems Analysts and one Computer Technician, which work as developers of the that system, participated in the evaluation. Preliminary results showed that IFL4TCG can actually help to detect defects in Web applications

Coeficientes de incidência do dengue e sua relação com os diferenciais intra-urbanos segundo condições de vida no município do Natal, Rio Grande do Norte

This study sprang from the hypothesis that spatial variations in the morbidity rate for dengue fever within the municipality of Natal are related to intra-city socioeconomic and environmental variations. The objective of the project was to classify the different suburbs of Natal according to their living conditions and establish if there was any correlation between this classification and the incidence rate for dengue fever, with the aim of enabling public health planners to better control this disease. Data on population density, access to safe drinking water, rubbish collection, sewage disposal facilities, income level, education and the incidence of dengue fever during the years 2001 and 2003 was drawn from the Brazilian Demographic Census 2000 and from the Reportable Disease Notification System -SINAN. The study is presented here in the form of two papers, corresponding to the types of analysis performed: a classification of the urban districts into quartiles according to the living conditions which exist there, in the first article; and the incidence of dengue fever in each of these quartiles, in the second. By applying factorial analysis to the chosen socioeconomic and environmental indicators for the year 2000, a compound index of living condition (ICV) was obtained. On the basis of this index, it was possible to classify the urban districts into quartiles. On undertaking this grouping (paper 1), a heterogeneous distribution of living conditions was found across the city. As to the incidence rate for dengue fever (paper 2), it was discovered that the quartile identified as having the best living conditions presented incidence rates of 15.62 and 15.24 per 1000 inhabitants respectively in the years 2001 and 2003; whereas the quartile representing worst living conditions showed incidence rates of 25.10 and 10.32 for the comparable periods. The results suggest that dengue fever occurs in all social classes, and that its incidence is not related in any evident way to the chosen formula for living conditions

Investigando a combinação de técnicas de aprendizado semissupervisionado e classificação hierárquica multirrótulo

Data classification is a task with high applicability in a lot of areas. Most methods for treating classification problems found in the literature dealing with single-label or traditional problems. In recent years has been identified a series of classification tasks in which the samples can be labeled at more than one class simultaneously (multi-label classification). Additionally, these classes can be hierarchically organized (hierarchical classification and hierarchical multi-label classification). On the other hand, we have also studied a new category of learning, called semi-supervised learning, combining labeled data (supervised learning) and non-labeled data (unsupervised learning) during the training phase, thus reducing the need for a large amount of labeled data when only a small set of labeled samples is available. Thus, since both the techniques of multi-label and hierarchical multi-label classification as semi-supervised learning has shown favorable results with its use, this work is proposed and used to apply semi-supervised learning in hierarchical multi-label classication tasks, so eciently take advantage of the main advantages of the two areas. An experimental analysis of the proposed methods found that the use of semi-supervised learning in hierarchical multi-label methods presented satisfactory results, since the two approaches were statistically similar results

Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil

RAMOS, Ana Maria de Oliveira et al. Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil. Pediatric and Developmental Pathology, v.3, n.1, p.29-35, 2000

Sleep and school education

Sleep has emerged in the past decades as a key process for memory consolidation and restructuring. Given the universality of sleep across cultures, the need to reduce educational inequality, the low implementation cost of a sleep-based pedagogy, and its global scalability, it is surprising that the potential of improved sleep as a means of enhancing school education has remained largely unexploited. Students of various socio-economic status often suffer from sleep deficits. In principle, the optimization of sleep schedules both before and after classes should produce large positive benefits for learning. Here we review the biological and psychological phenomena underlying the cognitive role of sleep, present the few published studies on sleep and learning that have been performed in schools, and discuss potential applications of sleep to the school setting. Translational research on sleep and learning has never seemed more appropriate.