895 resultados para classification and equivalence classes
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La thèse est composée d’un chapitre de préliminaires et de deux articles sur le sujet du déploiement de singularités d’équations différentielles ordinaires analytiques dans le plan complexe. L’article Analytic classification of families of linear differential systems unfolding a resonant irregular singularity traite le problème de l’équivalence analytique de familles paramétriques de systèmes linéaires en dimension 2 qui déploient une singularité résonante générique de rang de Poincaré 1 dont la matrice principale est composée d’un seul bloc de Jordan. La question: quand deux telles familles sontelles équivalentes au moyen d’un changement analytique de coordonnées au voisinage d’une singularité? est complètement résolue et l’espace des modules des classes d’équivalence analytiques est décrit en termes d’un ensemble d’invariants formels et d’un invariant analytique, obtenu à partir de la trace de la monodromie. Des déploiements universels sont donnés pour toutes ces singularités. Dans l’article Confluence of singularities of non-linear differential equations via Borel–Laplace transformations on cherche des solutions bornées de systèmes paramétriques des équations non-linéaires de la variété centre de dimension 1 d’une singularité col-noeud déployée dans une famille de champs vectoriels complexes. En général, un système d’ÉDO analytiques avec une singularité double possède une unique solution formelle divergente au voisinage de la singularité, à laquelle on peut associer des vraies solutions sur certains secteurs dans le plan complexe en utilisant les transformations de Borel–Laplace. L’article montre comment généraliser cette méthode et déployer les solutions sectorielles. On construit des solutions de systèmes paramétriques, avec deux singularités régulières déployant une singularité irrégulière double, qui sont bornées sur des domaines «spirals» attachés aux deux points singuliers, et qui, à la limite, convergent vers une paire de solutions sectorielles couvrant un voisinage de la singularité confluente. La méthode apporte une description unifiée pour toutes les valeurs du paramètre.
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Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.
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Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties.
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Most techniques used for estimating the age of Sotalia guianensis (van B,n,den, 1864) (Cetacea; Delphinidae) are very expensive, and require sophisticated equipment for preparing histological sections of teeth. The objective of this study was to test a more affordable and much simpler method, involving of the manual wear of teeth followed by decalcification and observation under a stereomicroscope. This technique has been employed successfully with larger species of Odontoceti. Twenty-six specimens were selected, and one tooth of each specimen was worn and demineralized for growth layers reading. Growth layers were evidenced in all specimens; however, in 4 of the 26 teeth, not all the layers could be clearly observed. In these teeth, there was a significant decrease of growth layer group thickness, thus hindering the layers count. The juxtaposition of layers hindered the reading of larger numbers of layers by the wear and decalcification technique. Analysis of more than 17 layers in a single tooth proved inconclusive. The method applied here proved to be efficient in estimating the age of Sotalia guianensis individuals younger than 18 years. This method could simplify the study of the age structure of the overall population, and allows the use of the more expensive methodologies to be confined to more specific studies of older specimens. It also enables the classification of the calf, young and adult classes, which is important for general population studies.
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Classical hypothesis testing focuses on testing whether treatments have differential effects on outcome. However, sometimes clinicians may be more interested in determining whether treatments are equivalent or whether one has noninferior outcomes. We review the hypotheses for these noninferiority and equivalence research questions, consider power and sample size issues, and discuss how to perform such a test for both binary and survival outcomes. The methods are illustrated on 2 recent studies in hematopoietic cell transplantation.
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This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the 10 Pillars of Knowledge: Map of Human Knowledge, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.
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ObjectiveTo describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry.MethodsInclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data.ResultsOf the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%.ConclusionEvaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Properties of the Jacobi script v sign3-function and its derivatives under discrete Fourier transforms are investigated, and several interesting results are obtained. The role of modulo N equivalence classes in the theory of script v sign-functions is stressed. An important conjecture is studied. © 2006 American Institute of Physics.
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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.
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Classification and standardization of the sawn wood is a usual activity, developed by countries that come as great consumers of this material. Brazil does not practice the classification of sawn wood. This work had the main objective of evaluating the sensibility of most common non-destructive tests in the classification of dimension lumber from fast grown Eucalyptus plantation. Wood was obtained from genetic material cultivated at Minas Gerais State, Brazil. 296 beams of structural dimensions (6 cm × 12 cm × 280 cm) from 10 different clones of Eucalyptus were sampled. Beams were non-destructively (stress wave, ultrasound and transverse vibration) and destructively (static bending and compression parallel to grain) tested. Non-destructive results showed sensibility in the classification of structural dimension lumber, being possible to establish wave velocity intervals that attend to the main strength classes reported by Wooden Structures Brazilian Code.
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In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.
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Na Análise do Comportamento, vários estudos são realizados a fim de entender como comportamentos podem produtivamente ser controlados por eventos arbitrariamente relacionados, através da formação classes de equivalência. A inclusão de estímulos reforçadores nas classes tem sido apontada como um possível facilitador de sua formação. O presente estudo teve como objetivos avaliar a formação de classes de equivalência mediada por estímulos reforçadores específicos em crianças que apresentam baixo rendimento escolar. Usando crianças com desenvolvimento típico e em maior número, comparado com a literatura, pretendeu-se obter dados com menor variabilidade intersujeitos que é comumente encontrada nesse tipo de pesquisa. Para isso, foram utilizados reforçadores específicos com quatorze crianças (no Experimento I) que apresentam dificuldades de aprendizagem. O procedimento do Experimento 1 foi dividido em 10 fases. Em todas as fases, houve reforçadores específicos (frutas ou brinquedos) para cada uma das classes potenciais que se pretendia verificar. Inicialmente foi realizado um treino de pareamento por identidade com os estímulos dos Conjuntos A (A I e A2), B (B 1 e B2) e C (C I e C2) com reforçamento contínuo, seguido do mesmo treino com Reforçamento Intermitente. Logo após esses treinos foram realizados os testes de relações emergentes AB/BA, ACICA e BCICB. Antes de cada teste foi feito o retorno às discriminações de linha de base. Os dados do Experimento I evidenciam grande variabilidade intersujeitos nos testes de formação de classes. O Experimento 2 pretendeu investigar o efeito de dois tipos de pré-treino sobre o desempenho nos testes de formação de classes. Foi realizado com seis crianças e subdividido em dois grupos. O Grupo I foi submetido a um pré-treino de pareamento por identidade e o Grupo 2 a um pré-treino de pareamento arbitrário. Os resultados confirmam parcialmente a hipótese de que pré-treino de pareamento arbitrário pode reduzir a variabilidade inter-sujeitos nesse tipo estudos, pois altas taxas de variabilidade persistem no presente estudo. .Estudos posteriores deverão explorar essa possibilidade mais sistematicamente.
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O paradigma de equivalência de estímulos tem se mostrado útil na explicação de processos comportamentais complexos, como aqueles envolvidos em comportamentos conceituais numéricos. Vários estudos têm buscado a compreensão de como desempenhos sob controle da função de ordem são estabelecidos e mantidos. O objetivo do presente trabalho foi verificar se classes ordinais poderiam emergir após o ensino por emparelhamento arbitrário e de produção de seqüência. Participaram do estudo três alunos com atraso no desenvolvimento. Os estímulos visuais foram formas abstratas indicando numerosidade (A), numerais cardinais (B)e nomes escritos em letras maiúsculas de numerais (C). As sessões experimentais foram conduzidas em uma sala da APAE-BELÉM e um software controlou e registrou os dados comportamentais. As relações AB/AC foram ensinadas e testou-se a emergência de três classes de equivalência. Em seguida, houve um ensino por encadeamento de respostas com estímulos de um dos conjuntos (A1A2A3) e uma sonda de seqüenciação. Então, foi avaliada a emergência de novas seqüências (B1B2B3 e C1C2C3). Posteriormente, testes de substitutabilidade foram aplicados para verificar a formação de classes ordinais (por exemplo: A1B2C3). Testes de generalização também foram apresentados para verificar se um responder envolvendo numerosidade ocorreria com novos estímulos (por exemplo: E1E2E3). Os resultados demonstraram que os participantes responderam a novas seqüências prontamente ou com emergência gradual. A análise de topografias de controle de estímulos envolvidas nesse tipo de tarefa mostrou-se útil para a compreensão da ordinalidade. Todos os participantes responderam a seqüências com novos estímulos (generalização). O procedimento mostrou-se também eficiente na transferência de funções ordinais em pessoas com atraso no desenvolvimento.