Neuro-fuzzy system for diagnosis of engines, based on oil samples analysis

The present paper describes a neuro-fuzzy. hybrid system applied to the diagnosis of automobile engines, based on the analysis of oil samples. A relevance analysls was done to select the most significant variables among the avallable ones, in order to classify the samples. Such relevance analysls is described in detalls along the paper. Four dlfferent systems were implemented one pure neural system, and three dlfferent neuro-fuzzy systems. A detailed descriptlon of the neural and fuzzy systems is also presented, as well as the performance obtained by each one of them

A degradação ambiental na Amazônia brasileira e os desafios para a inclusão do crime de ecocídio no Estatuto de Roma

O presente artigo busca elucidar quais são os desafios para a ampliação da competência do Tribunal Penal Internacional (TPI) de forma a incluir o ecocídio como o quinto crime previsto no Estatuto de Roma. O texto irá relatar fatos singulares (o ecocídio na Floresta Amazônica) para refletir sobre a necessidade da inclusão de crimes ambientais sob a jurisdição do TPI. Dessa forma, o método de abordagem utilizado será o indutivo, utilizando a pesquisa bibliográfica e documental. Para que tal inclusão ocorra, ela seria limitada aos requisitos de intenção existentes do Estatuto de Roma, ou seja, a exigência do dolo do autor do crime. Por consequência, esse requisito poderia afastar muitos julgamentos que o crime de ecocídio pretende litigar. Ademais, o TPI não tem jurisdição para processar Estados ou pessoas jurídicas, apenas indivíduos. Esse fato dificulta o estabelecimento do nexo de causalidade entre a atividade humana causadora do dano e o próprio dano para efeito de responsabilização penal

Automatic speech recognition: a study and performance evaluation on neural networks and hidden markov models

The main goal in this research is to find out possible ways to built hybrid systems, based on neural network (NN) and hidden M;arkov (HMM) models, for the task of automatic speech recognition. The investigation that has been conducted covers different types of neural network and hidden Markov models, and the combination of them into some hybrid models. The neural networks used were basically MLP and Radial Basis models. The hidden Markov models were basically different combinations of states and mixtures of the Continuous Density type of the Bakis model. A reduced set with ten words spoken in the Portuguese idiom, from Brazil, was carefully chosen to provide some pronounce and phonetic confusion. The results already obtained showed very positive, pointing toward to a high potentiality of such hybrid models

Proposing a customized exokernel library to data mining

The implementation of customized system libraries in an exokernel environment is considered as a promising approach in optimizing data mining processes. Customized libraries in exokernel environments have been successfully used in optimizing other applications, and is potentially suitable to demanding applications such as data mining. A prototype, to test our hypothesis, is under construction. This work introduces data mining, the exokernel environment and describes our prototype's building strategy

Ensino dos números de forma lúdica: Bingo de Decimais

Anais do II Seminário Seminário Estadual PIBID do Paraná: tecendo saberes / organizado por Dulcyene Maria Ribeiro e Catarina Costa Fernandes — Foz do Iguaçu: Unioeste; Unila, 2014Este trabalho tem por objetivo fazer um relato da experiência da aplicação do jogo bingo de decimais com110 estudantes de três turmas do 7° ano do Colégio Estadual Santa Cândida – Ensino Fundamental, Médio e Profissional, através do PIBID (Programa Institucional de Bolsa de Iniciação à Docência). Por meio desta atividade foram desenvolvidas as operações envolvendo os números decimais, de forma a fixar o conteúdo trabalhando em sala de aula, despertando um maior interesse pelos estudantes, pois desta forma o conteúdo tornava-se mais atrativo para os mesmos e assim uma melhor interação entre professor e estudante no processo de ensino e aprendizage

Avaliação de redes neurais aplicadas à previsão de índices de mercados de ações

Artificial neural networks have been utilized in modeling solutions for time series forecasting problems arisen in different financial area segments such as financial statements analysis, macro-economic indicators, currency market, stock quotations and market indexes. When dealing with such problems, the forecasting model quality is usually appraised in terms of the difference between the actual value and the network forecasted value. But financial area applications also require that related financial goals such as profitability and low risk exposure be considered. The commonly used mean square error generally does not grant those needs are met. It seems then to be necessary to establish additional criteria considering specific financial goals. The current paper shows the results obtained in experiments carried on to compare different neural network architectures to forecast the São Paulo Stock Exchange Ibovespa index using different training criteria and performance evaluation strategies based on business and financial goalsAs redes neurais artificiais vêm sendo utilizadas na modelagem da solução de problemas de previsão de séries temporais em diferentes segmentos da área financeira, como por exemplo, análise de balanços, indicadores macroeconômicos, mercado de câmbio, cotação de ações e índices de mercados. Nesses problemas, é usual mensurar a qualidade do modelo de previsão através do uso de alguma medida de erro entre o valor real e o valor previsto pela rede. Contudo, aplicações na área financeira demandam o atendimento a objetivos financeiros subjacentes, tais como nível de lucratividade ou exposição ao risco. A obtenção de medidas de erro com magnitude pouco significativa não é garantia de atendimento a esses objetivos: há necessidade do estabelecimento de critérios adicionais, de forma a possibilitar a aferição da qualidade dos resultados obtidos à luz de objetivos financeiros específicos. Este artigo apresenta resultados de alguns experimentos realizados com vistas a comparar diferentes arquiteturas de redes neurais para a previsão do índice Ibovespa, da Bolsa de Valores de São Paulo, envolvendo diferentes critérios de treinamento e estratégias de avaliação do desempenho com base em objetivos financeiros e de negócio

Automatic speech recognition: a comparative evaluation between neural networks and hidden markov models

In this work we do a comparative evaluation between Artificial Neural Networks (RNA's) and Continuous Hidden Markov Models (CDHMM), in the framework of the recognition of isolated words, under the constrain of using a small number of features extracted from each voice signal. In order to accomplish such comparison we used two models of neural networks: the Multilayer Perceptron (MLP) and a variant of the Radial Basis (RBF), and some HMM models. We evaluated the performance of all models using two different test set and observed that the neural models presented the best results in both cases. Seeking to improve the HMM performance we developed a hybrid system, HMM/MLP, that improved the results previously obtained with all HMMs, and even those obtained with the neural networks for the all previous HMM, and even the neural nets for the hardest test set case

2010 report of the Brazilian dialysis census

INTRODUCTION: National chronic dialysis data are fundamental for treatment planning. OBJECTIVE: To report data of the annual survey of the Brazilian Society of Nephrology about patients with chronic renal failure who were on dialysis in 1 July, 2010. METHODS: A national survey based on data from the country's dialysis centers. Data collection was performed by using a questionnaire filled out online by the dialysis centers. RESULTS: 340 (53.3%) centers answered the questionnaire. National data were estimated for the overall dialysis population. In July 2010, the estimated total number of patients on dialysis was 92,091. The estimated prevalence and incidence rates of end-stage chronic kidney disease patients on maintenance dialysis were 483 and 100/million population, respectively. The estimated number of patients starting a dialysis program in 2010 was 18,972. The annual crude mortality rate was 17.9%. Of those on maintenance dialysis, 30.7% were aged 65 years or older, 90.6% were on hemodialysis and 9.4% on peritoneal dialysis, 35,639 (38.7%) were on a kidney transplant waiting list, 28% were diabetics, 34.5% had serum phosphorus levels > 5.5 mg/dL, and 38.5% had hemoglobin levels 5,5 mg/dL e 38,5%, hemoglobina < 11 g/dL. O cateter venoso era usado como acesso vascular em 13,6% dos pacientes em hemodiálise. CONCLUSÕES: A prevalência de pacientes em diálise tem apresentado aumento progressivo. Os dados dos indicadores da qualidade diálise de manutenção melhoraram em relação a 2009 e destacam a importância do censo anual para o planejamento da assistência dialítica.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de MedicinaUniversidade Federal da Bahia Faculdade de Medicina da Bahia Departamento de MedicinaUniversidade Federal do Rio Grande Faculdade de Medicina Departamento de Medicina InternaUniversidade Federal Fluminense Faculdade de Medicina Departamento de Medicina ClínicaFaculdade de Medicina do ABC Departamento de MedicinaUNIFESP, EPM, Depto. de MedicinaSciEL