67 resultados para classifier, pragmatics, information transport, symbolic logic


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The purpose of this paper was to introduce the symbolic formalism based on kneading theory, which allows us to study the renormalization of non-autonomous periodic dynamical systems.

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Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

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In the cell, the correct folding of many proteins depends on the function of preexisting ones known as Molecular Chaperones (for a review see Hartl and Hayer-Hartl 2009). These, were defined as proteins that bind to and stabilize an otherwise unstable conformation of another protein, and by controlling binding and release, facilitate its correct fate in vivo, be it folding, oligomeric assembly, transport to a particular subcellular compartment, or disposal by degradation. Molecular chaperones do not convey steric information specifying correct folding: instead, they prevent incorrect interactions within and between nonnative peptides, thus typically increasing the yield but not the rate of folding reactions. Molecular chaperones are ubiquitous and comprise several protein families that are structurally unrelated (Hartl and Hayer-Hartl 2009). The Hsp70s and the Chaperonin families have been extensively studied.

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Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores

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In distributed video coding, motion estimation is typically performed at the decoder to generate the side information, increasing the decoder complexity while providing low complexity encoding in comparison with predictive video coding. Motion estimation can be performed once to create the side information or several times to refine the side information quality along the decoding process. In this paper, motion estimation is performed at the decoder side to generate multiple side information hypotheses which are adaptively and dynamically combined, whenever additional decoded information is available. The proposed iterative side information creation algorithm is inspired in video denoising filters and requires some statistics of the virtual channel between each side information hypothesis and the original data. With the proposed denoising algorithm for side information creation, a RD performance gain up to 1.2 dB is obtained for the same bitrate.

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In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

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In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

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Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica na Área de Especialização de Energia

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Dissertação de natureza científica realizada para obtenção do grau de Mestre em Engenharia de Redes de Computadores e Multimédia

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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A brincadeira, expressão maior das culturas lúdicas da infância e do saber popular infantil que colora o folclore das crianças e que entre elas constitui prática singular, tem marcos temporais indeléveis que lhe (de)marcaram um tempo e que a memória guardou para sempre. A linearidade que, durante quase todo o tempo antes da chegada da TV, a brincadeira transportou, a revolução das suas práticas que a partir daí se operou e acentuou com a chegada das novas tecnologias da comunicação e informação à vida das crianças e a consequente transformação radical do seu habitus lúdico (da rua para casa e daqui para o quarto) balizam eras distintas de tempos sociais paralelas às que ditaram, consequentemente, a transformação que as artes de e para brincar foram, historicamente, sofrendo. Ao resgatar a brincadeira pela voz das crianças, muitas das vezes expressa pela voz dos adultos que hoje são, faz-se o registo, que neste artigo se guarda, de um pedaço da herança cultural lúdica que foi passando entre as quatro gerações que estudamos qualitativamente a partir de entrevistas grupais feitas em contexto familiar, que serviram de base para o que a seguir fica relatado. A brincadeira e a parafernália que a acompanha fazem parte da história de vida de todos nós e, por isso, a cada um cabe velar para que nunca pereça.