Keila Mara Cassiano

HYDROELECTRIC ENERGY FORECAST

The aim of this paper is to propose a new methodology for hydroelectric energy forecasting. A new approach for selection of the number of eigenvalues in SSA is also proposed. In this paper it is proposed the hierarchical clustering associated to PCA and integrated to ARIMA models. The proposed approach is applied to forecast the affluent flow in a hydroelectric plant located at Parana River Basin, Brazil. As a matter of fact, modeling such series is quite important for the optimal dispatch of the energy generation in Brazil due to the heavy participation of hydro plants in the country (over 85% of the generated energy comes from hydro plants).

RESIDENTIAL ELECTRICITY CONSUMPTION FORECASTING USING A GEOMETRIC COMBINATION APPROACH

The forecasting of electricity consumption and demand plays a pivotal role in electric power systems planning. This paper proposes the combination of forecasts from two approaches with the aim of improving the forecasting accuracy, in order to make the best use of the installed transmission and generating capacity. In the first approach, the consumption time series is decomposed by wavelet analysis and a Box-Jenkins model is fitted to each wavelet component, following which the individual components forecasts are added to compute the total consumption forecast. The alternative approach, uses the Singular Spectrum Analysis technique to model the consumption time series in order to shrink the noise level. Thereafter, the Box-Jenkins model is used to forecast the filtered time series, producing a second forecast for the consumption series. Eventually, the two forecasts are combined geometrically in order to minimize the mean square error. The proposed methodology is illustrated by a computational experiment with the time series of residential consumption of electricity in Brazil.

Diagnósticos de enfermagem de pacientes hospitalizados com doenças cardiovasculares

Objetivo: Identificar a frequencia dos diagnosticos de enfermagem e caracteristicas definidoras de pacientes com doencas cardiovasculares e caracteriza-los quanto as variaveis sociodemograficas e clinicas. Metodo: Estudo descritivo transversal realizado com 30 pacientes hospitalizados em um hospital de grande porte. Utilizou-se instrumento proprio validado para coleta de dados, que foram analisados por 5 peritos;, havendo concordância de 50%, sofreram analise estatistica descritiva e inferencial. Resultados: Foram encontradas associacoes significativas com fatores Presenca da Insuficiencia Cardiaca, do Infarto Agudo do Miocardio, da Dor, Sexo e Idade. Os diagnosticos mais frequentes foram: Ansiedade (76,7%), Dor Aguda (70,7%), Debito Cardiaco Diminuido (56,7%), Percepcao Sensorial Perturbada - Visual (53,3%), Insonia (46,7%), Intolerância a Atividade (36,7%), Disfuncao Sexual (36,7%) e Eliminacao Urinaria Prejudicada (36,7%). Conclusao: a descricao dos diagnosticos de enfermagem contribui para a analise das respostas a doenca cardiovascular, com foco no objeto de trabalho do enfermeiro, apresentando respostas a doenca cardiovascular por meio de investigacao holistica.

Uma Análise da Dinâmica Inflacionária Brasileira

The chief goal of this paper is to analyze the Brazilian inflationary dynamics, and to measure the degree of inertia in such dynamics. To that end, we start by reporting Monte Carlo simulation results on the finite-sample performance of different variants of the variance ratio, a well know measure of long-run persistence of shocks. The simulations are performed under normal and nonnormal innovations, and also with and without outliers and inliers. Overall, the results favor a robust variant of the variance ratio we propose. The empirical results for Brazil suggest that the degree of inertia in this country is substantially larger than what was found by Campelo and Cribari-Neto (Revista Brasileira de Economia 57, 713-739, 2003); indeed, in several periods of the recent economic history we find full inertia. However, the degree of inertia since the implementation of the Real Plan is small. We also present empirical results for Argentina, Chile and Mexico.

ARTIFICIAL NEURAL NETWORK AND WAVELET DECOMPOSITION IN THE FORECAST OF GLOBAL HORIZONTAL SOLAR RADIATION

This paper proposes a method (denoted by WD-ANN) that combines the Artificial Neural Networks (ANN) and the Wavelet Decomposition (WD) to generate short-term global horizontal solar ra- diation forecasting, which is an essential information for evaluating the electrical power generated from the conversion of solar energy into electrical energy. The WD-ANN method consists of two basic steps: firstly, it is performed the decomposition of level p of the time series of interest, generating p + 1 wavelet orthonormal components; secondly, the p + 1 wavelet orthonormal components (generated in the step 1) are inserted simultaneously into an ANN in order to generate short-term forecasting. The results showed that the proposed method (WD-ANN) improved substantially the performance over the (traditional) ANN method.

Interaction of chemical and structural components providing defences to sea pansies Renilla reniformis and Renilla muelleri

Abstract Chemical and structural defence mechanisms are reported to co-occur in both terrestrial and marine systems. Among benthic marine organisms, the common co-occurrence of secondary metabolites and calcium carbonate (CaCO3) in soft corals provides an opportunity for testing synergistic interactions between these traits. Defensive properties of crude extracts, chemical fractions and CaCO3 sclerites from two sympatric species of soft corals, Renilla reniformis and R. muelleri, from Guanabara Bay, southeastern Brazil, were examined against fishes. To evaluate a potential interaction (secondary metabolites versus sclerites), both crude extracts and sclerites were evaluated as isolated defences and in combination in field assays against generalist fishes during the austral summer of 2007. While neither sclerites nor crude extracts from R. reniformis deterred feeding when offered individually in artificial food, both traits from R. muelleri offered individually provided effective defence. For both species, however, the combination of secondary metabolites and sclerites significantly deterred feeding, indicating that these traits are more effective in combination than in isolation.

Nursing diagnoses for inpatients with cardiovascular diseases

Objetivo: Identificar a frequencia dos diagnosticos de enfermagem e caracteristicas definidoras de pacientes com doencas cardiovasculares e caracteriza-los quanto as variaveis sociodemograficas e clinicas. Metodo: Estudo descritivo transversal realizado com 30 pacientes hospitalizados em um hospital de grande porte. Utilizou-se instrumento proprio validado para coleta de dados, que foram analisados por 5 peritos;, havendo concordância de 50%, sofreram analise estatistica descritiva e inferencial. Resultados: Foram encontradas associacoes significativas com fatores Presenca da Insuficiencia Cardiaca, do Infarto Agudo do Miocardio, da Dor, Sexo e Idade. Os diagnosticos mais frequentes foram: Ansiedade (76,7%), Dor Aguda (70,7%), Debito Cardiaco Diminuido (56,7%), Percepcao Sensorial Perturbada - Visual (53,3%), Insonia (46,7%), Intolerância a Atividade (36,7%), Disfuncao Sexual (36,7%) e Eliminacao Urinaria Prejudicada (36,7%). Conclusao: a descricao dos diagnosticos de enfermagem contribui para a analise das respostas a doenca cardiovascular, com foco no objeto de trabalho do enfermeiro, apresentando respostas a doenca cardiovascular por meio de investigacao holistica.

PERFIL E DESTINO OCUPACIONAL DE EGRESSOS GRADUADOS EM CIÊNCIAS BIOLÓGICAS NAS MODALIDADES A DISTÂNCIA E PRESENCIAL

RESUMO: O presente trabalho tem como objetivo evidenciar o perfil dos egressos de alguns cursos de graduacao em Ciencias Biologicas no Estado do Rio de Janeiro. O instrumento de pesquisa utilizado foi um questionario online, composto por perguntas multiopcionais. Este foi respondido por 241 egressos, sendo 83 do ensino a distância e 158 do ensino presencial, de universidades publicas e uma privada. Os resultados mostraram a predominância de mulheres, de cor branca e idade media de 23 anos, na conclusao do curso dos egressos do ensino presencial, e 33 no ensino a distância. Alem disso, percebeu-se o predominio do cargo de professor, principalmente no Ensino Fundamental II e no Ensino Medio e renda mensal de 3 a 4 salarios minimos. Palavras-chave: Destino ocupacional. Mercado de trabalho. Ciencias Biologicas. PROFILE AND PROFESSIONAL DESTINATION OF GRADUATED STUDENTS IN BIOLOGICAL SCIENCES BOTH IN TRADITIONAL AND DISTANCE EDUCATION MODALITIES

Distribuição espacial dos polos regionais do Cederj: uma análise estatística

O presente trabalho tem como objetivo avaliar a abrangencia geografica da oferta de cursos superiores atraves da educacao a distância pelo Consorcio Cederj no Estado do Rio de Janeiro. Trata-se de um estudo censitario, incluindo todos os alunos ativos dos cursos de graduacao, em abril de 2012. Os dados referentes ao numero de alunos e locais de residencia foram obtidos e, posteriormente, analisados pelo programa SPSS – Statistical Package for the Social Sciences. Foram calculados os Indices do Numero de Alunos para Cada 1.000 Habitantes (IACMH) e de Alunos para Cada 1.000 Domicilios (IACMD), baseados nos dados disponibilizados pelo IBGE – Instituto Brasileiro de Geografia e Estatistica, 2010. As analises foram feitas por municipio e por mesorregiao do Estado. A distância entre residencia e polo, para cada aluno, foi estimada atraves do Google Maps. Os resultados indicam que a missao inicial do Cederj, de oferecer ensino publico e gratuito em regioes nao atendidas, ou pouco atendidas, pelas instituicoes publicas de Ensino Superior, tem sido adequadamente implementada.

Introducing DBSCAN in the singular spectrum analysis procedure

This work proposes using DBSCAN to recognition of noise components of eigentriples in the grouping stage of SSA. The DBSCAN is a modern (revised in 2013) and expert method at to identify noise through regions of lower density. The hierarchical clustering method was the last innovation in noise recognition in SSA approach, implemented on package RSSA. However, it repeated in the literature that the hierarquical clustering method is very sensitive to noise, is unable to separate it correctly, and should not be used in clusters with varying densities and neither works well in clustering time series of different trends. Unlike, the density based clustering methods are effective in separating the noise from the data and dedicated to work well on data from different densities. This work shows better efficiency of DBSCAN over the others methods already used in this stage of SSA, because it allows considerable reduction of noise and provides better forecasting. The result is supported by experimental evaluations realized for simulated stationary and non-stationary series. The proposed combination of methodologies also was applied successfully to forecasting a real series of winds speed.