Caracterização e classificação dos resíduos de madeira gerados no processo de fabricação de móveis: estudo de caso

O presente estudo apresenta uma caracterização e classificação dos resíduos de madeira gerados no processo de fabricação de móveis de uma das maiores indústrias do pólo moveleiro de Votuporanga-SP, proporcionando um diagnóstico da geração anual dos resíduos de madeira, a participação percentual desses resíduos, a identificação dos resíduos contaminados, realizando uma análise sobre aproveitamento e destinação dos resíduos, além de propor medidas de reciclagem e ações que venham promover a minimização de resíduos na indústria.

Aplicação de mapas auto-organizáveis na classificação de padrões de escoamento bifásico

O escoamento bifásico de gás-líquido é encontrado em muitos circuitos fechados que utilizam circulação natural para fins de resfriamento. O fenômeno da circulação natural é importante nos recentes projetos de centrais nucleares para a remoção de calor. O circuito de circulação natural (Circuito de Circulação Natural - CCN), instalado no Instituto de Pesquisas Energéticas e Nucleares, IPEN / CNEN, é um circuito experimento concebido para fornecer dados termo-hidráulicos relacionados com escoamento monofásico ou bifásico em condições de circulação natural. A estimativa de transferência de calor tem sido melhorada com base em modelos que requerem uma previsão precisa de transições de padrão de escoamento. Este trabalho apresenta testes experimentais desenvolvidos no CCN para a visualização dos fenômenos de instabilidade em ciclos de circulação natural básica e classificar os padrões de escoamento bifásico associados aos transientes e instabilidades estáticas de escoamento. As imagens são comparadas e agrupadas utilizando mapas auto-organizáveis de Kohonen (SOM), aplicados em diferentes características da imagem digital. Coeficientes da Transformada Discreta de Cossenos de Quadro Completo (FFDCT) foram utilizados como entrada para a tarefa de classificação, levando a bons resultados. Os protótipos de FFDCT obtidos podem ser associados a cada padrão de escoamento possibilitando uma melhor compreensão da instabilidade observada. Uma metodologia sistemática foi utilizada para verificar a robustez do método.

Classificação das amostras do ensaio de Baumann através do processamento digital de imagens.

O presente trabalho apresenta uma alternativa ao processo de classificação do defeito da segregação central em amostras de aço, utilizando as imagens digitais que são geradas durante o ensaio de Baumann. O algoritmo proposto tem como objetivo agregar as técnicas de processamento digital de imagens e o conhecimento dos especialistas sobre o defeito da segregação central, visando a classificação do defeito de referência. O algoritmo implementado inclui a identificação e a segmentação da linha segregada por meio da aplicação da transformada de Hough e limiar adaptativo. Adicionalmente, o algoritmo apresenta uma proposta para o mapeamento dos atributos da segregação central nos diferentes graus de severidade do defeito, em função dos critérios de continuidade e intensidade. O mapeamento foi realizado por meio da análise das características individuais, como comprimento, largura e área, dos elementos segmentados que compõem a linha segregada. A avaliação do desempenho do algoritmo foi realizada em dois momentos específicos, de acordo com sua fase de implementação. Para a realização da avaliação, foram analisadas 255 imagens de amostras reais, oriundas de duas usinas siderúrgicas, distribuídas nos diferentes graus de severidade. Os resultados da primeira fase de implementação mostram que a identificação da linha segregada apresenta acurácia de 93%. As classificações oriundas do mapeamento realizado para as classes de criticidade do defeito, na segunda fase de implementação, apresentam acurácia de 92% para o critério de continuidade e 68% para o critério de intensidade.

Dispersión y genes relacionados con la resistencia a insecticidas en Triatoma infestans: su vinculación con el control del vector de la enfermedad de Chagas

Entre las especies transmisoras de la enfermedad de Chagas de mayor importancia a nivel sanitario se destaca Triatoma infestans, considerada el principal vector en América del Sur (entre las latitudes 10° y 46° S). Los programas de control de la transmisión de la enfermedad promueven la eliminación de las poblaciones del vector T. infestans mediante la fumigación con insecticidas en las regiones endémicas. Sin embargo, esta estrategia, presenta dificultades debido en parte a la extensión y variabilidad de las áreas endémicas y por otro lado, al tiempo requerido para prevenir la recuperación de las poblaciones tratadas con insecticidas. La efectividad a largo plazo de las campañas de control es en gran medida dependiente del conocimiento de la estructura de las poblaciones del vector. El análisis de la estructura genética con un enfoque filogeográfico de poblaciones del vector en regiones endémicas de Argentina, mediante secuencias de genes mitocondriales y nucleares descriptas por primera vez para ese fin, permitirá aportar nuevas bases para la comprensión de la dinámica y evolución de las poblaciones del insecto vector y resolver interrogantes sobre procesos como por ejemplo los de dispersión y recolonización de la especie transmisora que afectan en forma directa a la eficiencia de los intentos de control. Los patrones de dispersión de esta especie estarían estrechamente vinculados con la transmisión de la enfermedad de Chagas. Por lo tanto, esta información podría ser de utilidad para la optimización del diseño de las intervenciones de control a implementar en el área endémica que conducirían a una disminución del impacto que esta enfermedad provoca en la población. Por otra parte, se han observado fallas en el control del vector debido a la existencia de resistencia a los insecticidas piretroides. Entre los mecanismos que confieren resistencia a insecticidas se han descripto los que implican cambios en canales de sodio, conocido como resistencia “knockdown” (Kdr), y aquellos que provocan un aumento de la actividad de enzimas responsables de su metabolismo. Con respecto al último mecanismo, las evidencias sugieren que las enzimas mono-oxigenasas citocromo P450 tienen comunmente un rol primario en la resistencia a insecticidas piretroides. Incrementos en la expresión a nivel de la transcripción de genes de citocromos P450 (CYP450) son frecuentemente considerados responsables de aumentar el metabolismo de insecticidas y parece ser un fenómeno común en la evolución del desarrollo de resistencia en insectos. El estudio de la posible relación de genes CYP450, que proponemos caracterizar en T. infestans, con la resistencia a insecticidas podría aportar nuevas bases para el desarrollo del manejo de esa resistencia. Sin embargo, mientras que existen múltiples genes CYP450 en el genoma de insectos, sólo un gen NADPH citocromo P450 reductasa (CPR) existe en el genoma de cada insecto. Por este motivo, se propone también caracterizar en el vector este gen que codifica para una enzima que actúa en la transferencia de electrones desde la forma reducida de NADPH a los citocromos P450, así como investigar el efecto de su silenciamiento en poblaciones de T. infestans resistentes a insecticidas piretroides. Además, con el propósito de analizar si la existencia de resistencia a insecticidas piretroides puede ser el resultado de la acción de los citocromo P450 y/o de otros factores, se investigará en las poblaciones resistentes la posible existencia de una mutación de un gen de canal de sodio relacionada con resistencia a insecticidas (Kdr) que ha sido descripta para T. infestans. Este estudio proveería información de utilidad para el desarrollo de estrategias alternativas de control que serían de suma importancia en regiones en las que las poblaciones de este vector presentan resistencia a los insecticidas y, por lo tanto, tendría claramente implicancias importantes para el manejo de la resistencia en este vector.

Classificação internacional de funcionalidade, incapacidade e saúde : uma revisão

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

Influência dos investimentos sociais na classificação de empresas no Índice de Sustentabilidade Empresarial da BMF&BOVESPA

O mercado global estimula a competitividade para a busca de retornos financeiros. Entretanto, para a obtenção destes retornos financeiros, as empresas não podem atuar sem considerar critérios de sustentabilidade empresarial, condição sem a qual as empresas perderão competitividade. A BM&FBOVESPA trouxe grande contribuição às empresas que operam em seu mercado através do ISE (Índice de Sustentabilidade Empresarial). No entanto é justificado o questionamento se a dimensão que contempla os investimentos relativos à responsabilidade social tem peso suficiente para classificar melhor uma empresa no ISE ou se a concepção de sustentabilidade do ISE é multifocal e cuja ênfase seja distribuída nos conceitos do triple bottom line. Para verificar tal fato, este trabalho procurou comprovar o peso real da dimensão social dentro do ISE por meio de regressão logística, valendo-se de amostragem adequada de empresas participantes ou não na carteira do ISE nos anos 2011 e 2012. Demonstrou-se que não há diferenças significativas entre os grupos que justifiquem a classificação ou não no ISE somente baseando-se nas variáveis da dimensão social, bem como das mesmas com a adição de variáveis financeiras. Nota-se, portanto, que a dimensão social não é suficientemente relevante para diferenciar a participação ou não de uma empresa na carteira do ISE.

Proposição e aplicação de um core set da classificação internacional de funcionalidade, incapacidade e saúde (CIF) para saúde física de idosos

Para aumentar a viabilidade do uso da Classificação Internacional de Funcionalidade, Incapacidade e Saúde (CIF), core sets começaram a ser desenvolvidos, e objetivam estabelecer uma seleção de categorias adaptada para representar os padrões de avaliação multiprofissional de grupos específicos de pacientes. Com o objetivo de propor um core set da CIF para classificar a saúde física de idosos, formou-se uma comissão de especialistas para julgar o instrumento por meio da técnica Delphi, o que mostra a interface multidisciplinar do projeto. Finalizada a participação da comissão, o core set foi proposto contendo 30 categorias. Após aplicação em uma amostra com 340 idosos dos municípios de Natal/RN e Santa Cruz/RN, o core set foi submetido à análise fatorial, tendo ficado com 19 categorias. A análise ainda proporcionou gerar uma pontuação para cada idoso por meio do escore fatorial, tendo provado ser uma forma fidedigna e confiável de se pontuar um core set.

Técnica para segmentação automática de imagens microscópicas de componentes sanguíneos e classificação diferencial de leucócitos baseada em lógica fuzzy

Automatic detection of blood components is an important topic in the field of hematology. The segmentation is an important stage because it allows components to be grouped into common areas and processed separately and leukocyte differential classification enables them to be analyzed separately. With the auto-segmentation and differential classification, this work is contributing to the analysis process of blood components by providing tools that reduce the manual labor and increasing its accuracy and efficiency. Using techniques of digital image processing associated with a generic and automatic fuzzy approach, this work proposes two Fuzzy Inference Systems, defined as I and II, for autosegmentation of blood components and leukocyte differential classification, respectively, in microscopic images smears. Using the Fuzzy Inference System I, the proposed technique performs the segmentation of the image in four regions: the leukocyte’s nucleus and cytoplasm, erythrocyte and plasma area and using the Fuzzy Inference System II and the segmented leukocyte (nucleus and cytoplasm) classify them differentially in five types: basophils, eosinophils, lymphocytes, monocytes and neutrophils. Were used for testing 530 images containing microscopic samples of blood smears with different methods. The images were processed and its accuracy indices and Gold Standards were calculated and compared with the manual results and other results found at literature for the same problems. Regarding segmentation, a technique developed showed percentages of accuracy of 97.31% for leukocytes, 95.39% to erythrocytes and 95.06% for blood plasma. As for the differential classification, the percentage varied between 92.98% and 98.39% for the different leukocyte types. In addition to promoting auto-segmentation and differential classification, the proposed technique also contributes to the definition of new descriptors and the construction of an image database using various processes hematological staining

Classificação de técnicas e auxílio à navegação de busca com base em sua carga cognitiva, precisão e eficiência

Navigation, in both virtual and real environments, is the process of a deliberated movement to a specific place that is usually away from the origin point, and that cannot be perceived from it. Navigation aid techniques (TANs) have as their main objective help finding a path through a virtual environment to a desired location and, are widely used because they ease the navigation on these unknown environments. Tools like maps, GPS (Global Positioning System) or even oral instructions are real world examples of TAN usage. Most of the works which propose new TANs for virtual environments aim to analyze their impact in efficiency gain on navigation tasks from a known place to an unknown place. However, such papers tend to ignore the effect caused by a TAN usage over the route knowledge acquisition process, which is important on virtual to real training transfer, for example. Based on a user study, it was possible to confirm that TANs with different strategies affects the performance of search tasks differently and that the efficiency of the help provided by a TAN is not inversely related to the cognitive load of the technique’s aids. A technique classification formula was created. This formula utilizes three factors instead of only efficiency. The experiment’s data were applied to the formula and we obtained a better refinement of help level provided by TANs.

Classificação de técnicas estendidas no contrabaixo acústico

This work is to identify and classify extended techniques on acoustic bass. The main purpose of this classification is to provide the bass better understanding and practice these techniques. For this, we carried out a literature review, it was noted that, in academia, this topic is new and understanding for some musicians is still complex and nebulous. To assist in the difficulties of the bass player, the extended techniques were divided into two parts, proposing different approaches. The first part proposes the experimentation and exploration of conventional and unconventional techniques from other instruments on acoustic bass. The second seeks to identify and rank the extended techniques, showing excerpts from the solo instrument repertoire compositions. On each, there are still referenced authors and their contributions to the instrumental practice these techniques. In both categories of classification procedures were presented to be adopted by the bass player for the implementation of those techniques, as well as suggestions for their study. Among the main results, it was found that through the proposed classification of these techniques, one can incorporate new resources to technical universe and timbre of the instrument. Lastly, it was found a creation of a composition performed by interaction between composer and performer, containing new extended techniques or extended techniques not found in the instrument's contemporary soloist repertoire.

Classificação de técnicas estendidas no contrabaixo acústico

This work is to identify and classify extended techniques on acoustic bass. The main purpose of this classification is to provide the bass better understanding and practice these techniques. For this, we carried out a literature review, it was noted that, in academia, this topic is new and understanding for some musicians is still complex and nebulous. To assist in the difficulties of the bass player, the extended techniques were divided into two parts, proposing different approaches. The first part proposes the experimentation and exploration of conventional and unconventional techniques from other instruments on acoustic bass. The second seeks to identify and rank the extended techniques, showing excerpts from the solo instrument repertoire compositions. On each, there are still referenced authors and their contributions to the instrumental practice these techniques. In both categories of classification procedures were presented to be adopted by the bass player for the implementation of those techniques, as well as suggestions for their study. Among the main results, it was found that through the proposed classification of these techniques, one can incorporate new resources to technical universe and timbre of the instrument. Lastly, it was found a creation of a composition performed by interaction between composer and performer, containing new extended techniques or extended techniques not found in the instrument's contemporary soloist repertoire.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.