936 resultados para Classificação tipológica


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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.

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No cabe duda que la vivienda excavada constituye, dentro de la arquitectura popular, un fenómeno de incuestionable interés, si bien es cierto que, en muchos casos, ha sido una tipología a menudo menospreciada. Una arquitectura que ha resguardado y protegido al hombre desde hace siglos, gracias a una evolución tipológica perdurable en el tiempo y que se plantea como base formal y constructiva sencilla sin aporte extra de energía para el adecuado acondicionamiento interior en verano o en invierno. Hasta el gran desarrollo tecnológico del siglo XX, hace escasas décadas, la construcción tradicional seguía siendo aplicable a muchas edificaciones de nueva planta. A partir de ese momento, en los últimos años se ha insistido en la utilización de sofisticados planteamientos bioclimáticos para el acondicionamiento eficiente de los espacios habitables, sin poder evitar un excesivo aporte de energía en muchos de los proyectos actuales. Así, gracias al estudio pormenorizado de estas tipologías de viviendas más sencillas, podremos obtener conclusiones interesantes aplicables a los diseños actuales, sin dejar de lado los avances técnicos a nuestra disposición hoy en día. Por tanto, el objetivo de este trabajo es mostrar la evolución tipológica de la vivienda excavada en Crevillente, municipio ubicado en la costa sureste de España, en comparación con otras propuestas o soluciones de arquitectura a nivel mundial, mostrando su nivel de adaptación a la geografía regional. Para ello, se propone una metodología basada en el análisis de las principales tipologías de vivienda excavada existentes a nivel mundial, la identificación y el análisis de las casas-cueva de Crevillente y la evaluación de la influencia de los factores anteriores en las condiciones ambientales de las construcciones subterráneas. El presente trabajo forma parte de la tesis doctoral de la autora.

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

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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.

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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.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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Compararam-se o ganho médio diário (GMD), índice de conversão alimentar (IC) e classificação da carcaça (CC) entre dois tipos de cruzamento comercial (A e B), ambos obtidos pelo cruzamento terminal de varrascos Piétrain com porcas F1 Large White x Landrace. Procurou-se identificar os principais efeitos ambientais que influenciam os referidos carateres. Utilizou-se um total de 200 suínos (machos e fêmeas), de dois cruzamentos comerciais distintos, provenientes de duas unidades de multiplicação comerciais. Determinou-se o GMD e o IC em dois períodos diferentes (63-119 e 120-158 dias de vida). No final do ensaio, efetuou-se a CC, segundo o sistema SEUROP. Procedeu-se a uma análise de variância com o objetivo de identificar os principais efeitos ambientais que influenciam o GMD, IC e CC. Determinou-se o coeficiente de regressão do GMD no peso vivo no início da engorda. Globalmente, observou-se uma superioridade do cruzado B no que concerne ao GMD (+74,6 g) (p<0,01) e ao IC (-0,07) (p<0,05). O GMD dos animais registou um acréscimo médio de 5,8 g por kg de acréscimo do PV no início do ensaio. A superioridade do cruzado B foi ainda evidenciada na classificação de carcaça SEUROP, com um acréscimo significativo (p<0,01) de 2,3% em carne magra.

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Durante o período de funcionamento de uma instalação eléctrica podem ocorrer várias anomalias. Enquanto muitas delas apenas são identificadas tardiamente, outras acabam por nunca serem identificadas como um potencial problema. A identificação atempada dessas anomalias permite a realização de um diagnóstico que leve à correcção das suas causas evitando assim os desperdícios e prejuízos inerentes. A identificação de um consumo anómalo pode ser realizada, de forma automática ou semi automática através de sistemas de apoio que permitam sinalizar falhas ou comportamentos anormais. O trabalho apresentado nesta dissertação pretende possibilitar esta sinalização apenas através da análise dos dados de consumo medidos em tempo real e comparados com dados históricos através de uma abordagem baseada em classificação, recorrendo a métodos de clustering. Foram testadas diferentes abordagens em três casos distintos, dois relativos a consumidores residenciais para os quais existiam registos de consumo durante um período alargado, e um relativo a uma instalação desportiva, para a qual é possível aceder em tempo real ao sistema de gestão de consumos via web. O sistema implementado proporciona vários tipos de informação ao utilizador, permitindo visualizar graficamente a existência de uma potencial anomalia quando a disparidade entre a classificação do consumo no instante e a classe do consumo de referência for significativa.

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Introdução: A complexidade da utilização da CIF devido ao elevado número de categorias levou à necessidade de desenvolver Core Sets de forma a identificar e agrupar os principais problemas dos indivíduos para as diferentes condições de saúde. Contudo, mostra-se necessário comparar estes Core Sets iniciais com a perspetiva dos indivíduos em diferentes países, para uma melhor utilização deste instrumento na prática clínica. Objetivo: Identificar os principais problemas percecionados pelos indivíduos com AR em Portugal e verificar se estes se encontram contemplados nos comprehensive e brief Core Sets da CIF para a mesma condição. Metodologia: Esta investigação consiste num estudo qualitativo com uma amostra de conveniência com indivíduos com AR. Para a recolha de dados foram utilizadas entrevistas individuais gravadas sobre a forma de áudio, sendo o procedimento do estudo baseado no protocolo de Coenen M., (2008). Resultados: O estudo inclui 20 indivíduos com uma média de idade de 61,35 (±10,5) anos, sendo que 95% pertenciam ao género feminino e 5% ao género masculino. Das 99 categorias identificadas, 41 (42,71%) encontram-se presentes nas 96 categorias do comprehensive Core Sets da CIF e 31 (79,49%) nas 39 categorias dos brief Core Sets da CIF. Conclusões: O presente estudo conclui que embora os Core Sets da CIF para a AR sejam específicos para os indivíduos com esta condição, quando comparados com a população portuguesa, estes não apresentam vários problemas identificados por estes indivíduos. Para além disso, estes Core Sets da CIF contêm problemas que não foram relatados por esta população.