Neural Network Configurations Analysis for Multilevel Speech Pattern Recognition System with Mixture of Experts

This chapter proposes to analyze two configurations of neural networks to compose the expert set in the development of a multilevel speech signal pattern recognition system of 30 commands in the Brazilian Portuguese language. Then, multilayer perceptron (MLP) and learning vector quantization (LVQ) networks have their performances verified during the training, validation and test stages in the speech signal recognition, whose patterns are given by two-dimensional time matrices, result from mel-cepstral coefficients coding by the discrete cosine transform (DCT). In order to avoid the pattern separability problem, the patterns are modified by a nonlinear transformation to a high-dimensional space through a suitable set of Gaussian radial base functions (GRBF). The performance of MLP and LVQ experts is improved and configurations are trained with few examples of each modified pattern. Several combinations were performed for the neural network topologies and algorithms previously established to determine the network structures with the best hit and generalization results

Computer models for disease prediction

With the increased computational power and ease of gathering medical information, Artificial Intelligence has helped all areas of health in developing algorithms and techniques for disease diagnosis and staging. The technology has been applied in several areas, due to its wide range of features, some activities become simpler with your help. Thus, this study aimed to identify the main computational models for disease prediction. Data collection was performed in the virtual databases present in the Health Library Research Portal (VHL): LILACS: Latin American and Caribbean Health Sciences Literature, Scielo - ScientificElectronic Library Online and Literature Analysis and Retrieval System Medical Online (MEDLINE). We found 52 articles and 10 of these in the review. From the reading and evaluation of the included articles, which can be aided by computer vision techniques, machine learning through neural networks and pattern recognition can be developed algorithms capable of identifying diseases. Thus, from this diagnosis provided by the algorithm, the health professional will have conditions for early prevention, diagnosis and treatment of diseases

Epidemiological, Sociodemographic And Clinical Profile of Men With Cancer in Rondônia, Brazilian Amazon

Objective: to analyze the epidemiological, sociodemographic and clinical profile of men in Rondônia, Western Amazonia (Brazil), diagnosed with the main types of cancer, during a period of 2 (two) years. Materials and Methods: it is an epidemiological, descriptive, cross-sectional and quantitative study, with the systematization of primary data according to the methodological model recommended by Paraguassu-Chaves et al [6]. We used an instrument developed by Paraguassu-Chaves et al [5], semi-structured composed of a series of epidemiological, clinical and sociodemographic variables. The research project is in compliance with Resolution 196/96 of the National Health Council of Brazil, taking into account the ethical aspects of research in Brazil. Main results: the 10 (ten) main types of cancer diagnosed by the location of the primary tumor in men were analyzed, corresponding to 1,163 (74.9%) cases of cancer in men, over a period of 2 (two) years. The 10 (ten) most common types of cancer in men were: prostate (30.9%), non-melanoma skin (22.9%), stomach (11.7%), bronchi and lungs (6.7%), colon (5.8%), leukemia (5.8%), esophagus (4.4%), central nervous system (4.2%), rectum (3.9%) and bladder (3.6%). The age group of 50 to 79 years old reaches 76.4% of the 10 main types of cancer in men. They are more frequent in brown (64.6%) and white (28%) men and with low education. 73.2% of men with cancer are married. 44.9% of men with cancer work in agriculture. 45.6% of men with cancer have a family history of cancer. The sum of smokers and ex-smokers reaches a relative frequency of 43.7%. 19.5% consume alcoholic beverages and 17.2% are ex-consumers. In 40.1%, "other isolated therapeutic procedures" were applied in the first treatment. 14.2% of diagnosed patients died from the disease. Conclusions: The scenario of cancer projection in men in Rondônia is worrying and requires an urgent redirection of actions and strategies for cancer prevention, control, assistance and treatment

Epidemiological and sociodemographic characterization of women and men with cancer in a State in the Brazilian Amazon

Objective: Objective: Analyzes the epidemiological and sociodemographic characterization of women and men with cancer in the State of Rondônia, Western Amazon (Brazil), diagnosed over a period of 2 (two) years. Materials and Methods: It is a documentary, cross-sectional and descriptive study, with the systematization of primary data, according to the methodological model recommended by Paraguassú-Chaves et al [25]. We used an instrument developde by Paraguassu-Chaves et al [26], semi-structured, divided into two blocks: (a) Block I – sociodemographic profile and (b) Block II – epidemiological profile. The Ethics Committee on Human Research at the reference hospital was asked to waive the Informed Consent Form. The research project is in accordance with Resolution 196/96 of the National Health Council of Brazil. Results: Of the 3.333 new cases of cancer, 53.4% ​​were female and 46.5% male. The 10 (ten) most common types of cancer among men and women in Rondônia over a 2-year period were non-melanoma skin (C44), breast (C50), prostate (C61), cervix (C53), stomach (C16), thyroid gland (C73), bronchi and lungs (C33-C34), colon (C18), reticuloendothelial hematopoietic system (C42) and rectal cancer (C20). An age range of 50 to 69 years was predominant in both sexes and patients with low educational level. The highest frequency was for married patients. There was a predominance of brown skin, patients born in the State of Rondônia (22.6%) and agricultural workers. The Unified Health System - SUS was responsible for the entry for treatment of 99.5% of patients. Most patients underwent “other isolated therapeutic procedures” and with the disease in advanced stages. Conclusions: The estimate of new cancer cases in Rondônia follows an increasing trend. The scenarios selected from the variables of the sociodemographic and epidemiological indicators of the research require the public health authorities of Rondônia, urgent redirection of actions and strategies for the prevention, control, assistance and treatment of cancer in women and men in Rondônia

Quantitative methods and analysis of health performance and environmental conditions in the city of Porto Velho: 6 years after the hydroelectric dams of Jirau and Santo Antônio, on the Madeira River

Objective: to analyze the IQVU of the city of Porto Velho, Rondônia, Brazil, in a perspective of quality of life from the construction of the UHEs on the Madeira River. Methods: the model developed by Paraguassú-Chaves et al [3] was used to analyze the performance index in health and environmental conditions. 552 forms and interviews were applied, which contributed to the collection of primary data in the sample survey in the 69 neighborhoods grouped by the four urban areas of Porto Velho, involving 8 households per neighborhood. The data were submitted to Factor Analysis to calculate the quality of life indexes. In the analysis phase, the IQVU model of the Hair et al classification index scale [4] was used. Results: After 6 years, the quality of life indexes found in this research are similar to those found previously. Central Zone IQVU (0.456) Regular, East Zone IQVU (0.406), North Zone IQVU (0.428) and South Zone IQVU (0.393), with the average IQVU (0.420) of the city of Porto Velho. Conclusions: there was a significant drop in the quality of life index with the construction of the Jirau and Santo Antônio hydroelectric dams on the Madeira River, in Porto Velho. The city\u27s quality of urban life index, which had already suffered a negative impact during the construction of the dams and 1 year later, worsened six years later

Middle Childhood Adverse Psychomotor Outcomes from Malaria in Pregnancy: A Study using the Denver Developmental Screening Test-II

Objective: to evaluate changes in the development of premature children aged 5 to 6 years, born to mothers with malaria during pregnancy and to compare them to a control group of premature children born to mothers who did not have malaria during pregnancy. Methods: cross-sectional and analytical study. The Denver test-II was applied to 20 children in the study group and 20 children in the control group. Results: in the group of premature children of mothers with malaria during pregnancy, the vast majority showed abnormal performance with more significant changes in the activities of the language sector "define seven words", "say two compound words", "understand four prepositions" and "account five blocks”, “knows three adjectives”. In the fine-adaptive motor sector, the activities "draw people with six parts", "copy disassembled square", "copy +" and in the gross motor sector "swing your foot for six seconds", "swing your foot for five seconds", "swing the foot for four seconds", "rocks the foot for three seconds", were the most important developmental changes. In the control group, the performance of suspected delay or possible abnormality was more concentrated in the gross motor sector. Conclusions: children from 5 to 6 years of age, born prematurely to mothers with malaria during pregnancy, 80% had suspected abnormal performance, a result much higher than the group of children born prematurely to mothers without malaria. These results strongly suggest that malaria disease during pregnancy alters fetal development, producing developmental sequelae that can be detected even at 5 to 6 years of age. In addition, the results support the use of the Denver test-II as a simple screening method for the assessment of delays in child development, covering broad motor coordination (coarse), fine motor coordination (adaptive), language and personal-social adaptation. This test has been used to identify children who are at risk of developing problems and to monitor the child longitudinally

AVALIAÇÃO DE MÉTODOS DE CONVERGÊNCIA NO TREINAMENTO DE REDES NEURAIS ARTIFICIAIS APLICADAS À PREDIÇÃO DE ÍNDICE DE IODO, VISCOSIDADE E DENSIDADE EM BIODIESEL

Algumas propriedades do biodiesel, como índice de iodo, viscosidade e densidade, podem sofrer variações conforme as estruturas moleculares dos seus ésteres constituintes. O objetivo do pre-sente estudo é avaliar e comparar três métodos de convergência no treinamento supervisionado de redes neurais com arquitetura MLP na predição de propriedades de biodiesel. Os métodos aplicados foram os de BFGS, Gradiente Descendente e Gradiente Conjugado. Dados do LAPQAP e da literatura foram padronizados, organizados e armazenados no Sistema Oleodata, sendo divididos em três partes: 70% para o treinamento da rede, 15% para a fase de validação e 15% para a de teste. As variáveis de entrada foram os percentuais de cada éster de ácido graxo que compõe as amostras de biodiesel, e as variáveis de saída foram o índice de iodo, a viscosidade e a densidade. As seguintes funções de ativação foram previamente testadas: tangente hiperbólica, seno, identidade, exponencial e logística. Além disso, foram fixadas a quantidade de 1000 redes treinadas para cada variação do estudo e 1000 ciclos de treinamento para cada rede. Em seguida, foram variados os métodos de convergência: BFGS, Gradiente Descenden-te e Gradiente Conjugado. Após a obtenção do método de convergência, um novo treinamento foi feito para a otimização da quantidade de neurônios, variando-se de 5 a 15. Ao final de todos os treinamentos a rede com melhores desempenhos foi treinada pelo método de BFGS e apresentava 10 neurônios ocul-tos, função logística em ambas as camadas oculta e de saída, com um coeficiente médio superior a 0,88.Palavras-chave: Parâmetros de Qualidade. Método de BFGS. Método de Gradiente Descendente. Mé-todo de Gradiente Conjugado.EVALUATION OF CONVERGENCE METHODS IN TRAINING OF ARTIFICIAL NEURAL NETWORKS APPLIED TO PREDICTION OF IODINE INDEX, VISCOSITY AND DENSITY IN BIODIESELABSTRACT: Some properties of biodiesel, like iodine index, viscosity and density, can vary with the mo-lecular structures of its esters. The present study evaluates and compares three convergence methods of supervised training of neural networks with MLP architecture on prediction of biodiesel properties. The methods applied were BFGS, Descent Gradient and Conjugate Gradient. Data from LAPQAP and from literature were standardized, organized and stored into the Oleodata System, being divided in three parts: 70% for networks training, 15% for validation phase and 15% for test. The input variables were the per-cent of each fatty ester which compose the biodiesel samples, and the output variables were iodine index, viscosity and density. The following activation functions were previously tested: hyperbolic tangent, sine, identity, exponential and logistic. Moreover, it was fixed the quantity of 1000 networks trained for each va-riation of the study and 1000 cycles of training for each network. Then, convergence methods were varied: BFGS, Descent Gradient and Conjugate Gradient. After selected the best convergence method, a new training was carried out for optimization of neurons quantity, ranging from 5 to 15. At the end of training, the network with best performances was trained by BFGS method and presented 10 hidden neurons, logistic function in both hidden and output layers, with a mean coefficient higher than 0,88.KEYWORDS: Quality Parameters. BFGS Method. Descent Gradient Method. Conjugate Gradient Method.EVALUACIÓN DE MÉTODOS DE CONVERGENCIA EN EL ENTRENAMIENTO DE REDES NEURONALES ARTIFICIALES APLICADAS A LA PREDICCIÓN DEL ÍNDICE DE YODO, LA VISCOSIDAD Y LA DENSIDAD DE BIODIESELRESUMEN: Algunas propiedades del biodiesel, como índice de yodo, viscosidad y densidad, pueden va-riar con las estructuras moleculares de sus ésteres. El presente estudio evalúa y compara tres métodos de convergencia de entrenamiento supervisado de las redes neuronales con la arquitectura MLP en la predicción de las propiedades del biodiesel. Los métodos aplicados fueron BFGS, Gradiente de Descen-so y Gradiente Conjugado. Los datos de LAPQAP y de la literatura fueron estandarizados, organizado y almacenado en el Sistema de Oleodata, siendo divididos en tres partes: 70% para el entrenamiento de redes, 15% para la fase de validación y 15% para el test. Las variables de entrada fueron el porcentaje de cada éster de grasa que componen las muestras de biodiesel, y las variables de salida fueron el índice de yodo, la viscosidad y la densidad. Las siguientes funciones de activación fueron probadas previamente: tangente hiperbólica, seno, identidad, exponencial y logística. Además, se determinó la cantidad de 1.000 redes entrenadas para cada variación del estudio y 1000 ciclos de formación para cada red. Entonces, los métodos de convergencia fueron variados: BFGS, Gradiente de Descenso y Gradiente Conjugado. Después de seleccionar el mejor método de convergencia, un nuevo entrenamiento fue realizado para la optimización de la cantidad de neuronas, que van de 5 a 15. Al final de la formación, la red con las mejores actuaciones fue entrenada por el método BFGS y presentó 10 neuronas ocultas, la función logística en capas encubiertas y de salida, con un coeficiente medio superior a 0,88.PALABRAS CLAVE: Parámetros de Calidad. Método de BFGS. Método del Gradiente de Descenso. Método del Gradiente Conjugado

Quantitative methods and study of the parth dependence effect of Douglass North from the cocoa production index (CPI) in Rondônia, Brazil

Objective: to analyze the path dependence effect of Douglass North from the construction of the cocoa production index (IPC) using quantitative methods, aiming to contribute to the discussions on the "conservation and development" trade-off in the Amazon. Methods: this is a hypothetical-deductive study. The CPI was calculated following the factorial analysis techniques presented by Hair et al [11], Santana [12,13) and Cavalcante [14] and the SPSS (Statistical Package for Social Sciences) was used. Results: in Brazil the level of performance of cocoa production, when considering the number of cocoa producing municipalities and the indicators, area destined to harvest (hectares), quantity produced (ton), average production yield (kilograms per hectare) and value production (thousand reais) is very low, almost inefficient. Rondônia follows the logic found in Brazil. Conclusions: despite the importance of cocoa production, there are still no regional development centers for cocoa cultivation in Rondônia. All cocoa producing municipalities had low levels of PCI performance. The fact that CEPLAC develops its actions exclusively in the East Rondoniense portion of the State only reinforces the analysis in this direction, which helps to understand the path dependence character of the cocoa policy in Rondônia