834 resultados para dissimilarity measures


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Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.

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Dissimilarity measurement plays a crucial role in content-based image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performance, on different feature spaces? In this paper, we summarize fourteen core dissimilarity measures and classify them into three categories. A systematic performance comparison is carried out to test the effectiveness of these dissimilarity measures with six different feature spaces and some of their combinations on the Corel image collection. From our experimental results, we have drawn a number of observations and insights on dissimilarity measurement in content-based image retrieval, which will lay a foundation for developing more effective image search technologies.

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Popular dimension reduction and visualisation algorithms rely on the assumption that input dissimilarities are typically Euclidean, for instance Metric Multidimensional Scaling, t-distributed Stochastic Neighbour Embedding and the Gaussian Process Latent Variable Model. It is well known that this assumption does not hold for most datasets and often high-dimensional data sits upon a manifold of unknown global geometry. We present a method for improving the manifold charting process, coupled with Elastic MDS, such that we no longer assume that the manifold is Euclidean, or of any particular structure. We draw on the benefits of different dissimilarity measures allowing for the relative responsibilities, under a linear combination, to drive the visualisation process.

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The purpose of this research was to examine the influence of cultural dissimilarity on the relationship between multinationality and performance. Both direct and indirect effects were studied. In addition, the form of the multinationality-performance relationship was investigated.^ Five indicators of cultural dissimilarity were developed on the basis of Hofstede's cultural dimensions. Performance was measured along two dimensions--financial and operational. Multinationality was operationalized as the ratio of foreign sales to total sales. Secondary data was used for all variables in the study. The sample of firms comprised multinationals based in the United States from four global industries--chemicals, computers and office equipment, electrical and electrical goods, and drugs and pharmaceuticals.^ Regression analyses using pooled cross-section/time-series data indicated that the relationship between multinationality and performance is curvilinear. No direct effects of cultural dissimilarity on performance were found. However, the results show a moderating effect of cultural dissimilarity on the multinationality-performance relationship. The direction of this effect was positive for four of the five cultural dissimilarity measures. ^

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The aim of this work was to estimate the susceptibility of thirty-six peach cultivars to leaf rust caused by Tranzschelia discolor f. sp. persica. The incidence and severity of the disease as well as defoliation in peach trees of an experimental orchard of Parana Federal University of Technology, Campus Dois Vizinhos were evaluated on the growing seasons 2004/2005 and 2005/2006. Immunity to this disease was not observed in the studied cultivars. There was difference in leaf rust intensity depending on the growing season conditions. Cultivars 'Pilcha', 'Sinuelo', 'Chirua', 'Sulina', 'Eldorado' and 'Pampeano' showed tolerance to leaf rust, whereas cultivars 'Vila Nova', 'Fla 1372', 'Coral 2', 'Chimarrita', 'Della Nona', 'BR-1 ' and 'Guaiaca' showed high susceptibility.

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The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

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Andryala (Asteraceae: Cichorieae) is a little-known Mediterranean-Macaronesian genus whose taxonomy is much in need of revision. The aim of the present biosystematic study was to elucidate species relationships within this genus based on morphological and molecular data. In this study several taxa are recognised: 17 species, 14 subspecies, and 3 hybrids. Among these, 5 species are Macaronesian endemics (A. glandulosa, A. sparsiflora, A. crithmifolia Aiton, A. pinnatifida, and A. perezii), 4 species are Northwest African endemics (A. mogadorensis, A. maroccana, A. chevallieri, and A. nigricans) and one species is endemic to Romania (A. laevitomentosa). Historical background regarding taxonomic delimitation in the genus is addressed from Linnaean to present day concepts, as well as the origin of the name Andryala. The origin of Asteraceae and the systematic position of Andryala is shortly summarised. The morphological study was based on a bibliographic review and the revision of 1066 specimens of 13 herbaria as well as additional material collected during fieldwork. The variability of the morphological characters of the genus, including both vegetative taxonomic characters (root, stem, leaf and indumentum characters) and reproductive ones (inflorescence, floret, fruit and pappus characters), is assessed. Numerical analysis of the morphological data was performed using different similarity or dissimilarity measures and coefficients, as well as ordination and clustering methods. Results support the segregation of the recognised taxa and the congruence of the several analyses in the separation of the recognised taxa (using quantitative, binary or multi-state characters). The proposed taxonomy for Andryala includes a new infra-generic classification, new taxa and new combinations and ranks, typifications and diagnostic keys (one for the species and several for subspecies). For each taxon a list of synonyms, typification comments and a detailed description are provided, just as comments on taxonomy and nomenclature, and a brief discussion on karyology. Additionally, information on ecology and conservation status as well as on distribution and a list of studied material are also presented. Phylogenetic analyses based on different nuclear and chloroplast DNA markers, using Bayesian and maximum parsimony methods of inference, were performed. Results support three main lineages: separate ones for the relict species A. agardhii and A. laevitomentosa and a third including the majority of the Andryala species that underwent a relatively rapid and recent speciation. They also suggest a single colonization event of Madeira and the Canary Islands from the Mediterranean region, followed by insular speciation. Biogeography and speciation within the genus are briefly discussed, including a proposal for the centre of origin of the genus and possible dispersal routes.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Andryala (Asteraceae: Cichorieae) is a little-known Mediterranean-Macaronesian genus whose taxonomy is much in need of revision. The aim of the present biosystematic study was to elucidate species relationships within this genus based on morphological and molecular data. In this study several taxa are recognised: 17 species, 14 subspecies, and 3 hybrids. Among these, 5 species are Macaronesian endemics (A. glandulosa, A. sparsiflora, A. crithmifolia Aiton, A. pinnatifida, and A. perezii), 4 species are Northwest African endemics (A. mogadorensis, A. maroccana, A. chevallieri, and A. nigricans) and one species is endemic to Romania (A. laevitomentosa). Historical background regarding taxonomic delimitation in the genus is addressed from Linnaean to present day concepts, as well as the origin of the name Andryala. The origin of Asteraceae and the systematic position of Andryala is shortly summarised. The morphological study was based on a bibliographic review and the revision of 1066 specimens of 13 herbaria as well as additional material collected during fieldwork. The variability of the morphological characters of the genus, including both vegetative taxonomic characters (root, stem, leaf and indumentum characters) and reproductive ones (inflorescence, floret, fruit and pappus characters), is assessed. Numerical analysis of the morphological data was performed using different similarity or dissimilarity measures and coefficients, as well as ordination and clustering methods. Results support the segregation of the recognised taxa and the congruence of the several analyses in the separation of the recognised taxa (using quantitative, binary or multi-state characters). The proposed taxonomy for Andryala includes a new infra-generic classification, new taxa and new combinations and ranks, typifications and diagnostic keys (one for the species and several for subspecies). For each taxon a list of synonyms, typification comments and a detailed description are provided, just as comments on taxonomy and nomenclature, and a brief discussion on karyology. Additionally, information on ecology and conservation status as well as on distribution and a list of studied material are also presented. Phylogenetic analyses based on different nuclear and chloroplast DNA markers, using Bayesian and maximum parsimony methods of inference, were performed. Results support three main lineages: separate ones for the relict species A. agardhii and A. laevitomentosa and a third including the majority of the Andryala species that underwent a relatively rapid and recent speciation. They also suggest a single colonization event of Madeira and the Canary Islands from the Mediterranean region, followed by insular speciation. Biogeography and speciation within the genus are briefly discussed, including a proposal for the centre of origin of the genus and possible dispersal routes.

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To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

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The objective of this study was to analyze the prevalence of diabetes in older people and the adopted control measures. Data regarding older diabetic individuals who participated in the Health Surveys conducted in the Municipality of Sao Paulo, SP, ISA-Capital, in 2003 and 2008, which were cross-sectional studies, were analyzed. Prevalences and confidence intervals were compared between 2003 and 2008, according to sociodemographic variables. The combination of the databases was performed when the confidence intervals overlapped. The Chi-square (level of significance of 5%) and the Pearson's Chi-square (Rao-Scott) tests were performed. The variables without overlap between the confidence intervals were not tested. The age of the older adults was 60-69 years. The majority were women, Caucasian, with an income of between > 0.5 and 2.5 times the minimum salary and low levels of schooling. The prevalence of diabetes was 17.6% (95%CI 14.9;20.6) in 2003 and 20.1% (95%CI 17.3;23.1) in 2008, which indicates a growth over this period (p at the limit of significance). The most prevalent measure adopted by the older adults to control diabetes was hypoglycemic agents, followed by diet. Physical activity was not frequent, despite the significant differences observed between 2003 and 2008 results. The use of public health services to control diabetes was significantly higher in older individuals with lower income and lower levels of education. Diabetes is a complex and challenging disease for patients and the health systems. Measures that encourage health promotion practices are necessary because they presented a smaller proportion than the use of hypoglycemic agents. Public health policies should be implemented, and aimed mainly at older individuals with low income and schooling levels. These changes are essential to improve the health condition of older diabetic patients.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Dental erosion is defined as the loss of tooth substance by acid exposure not involving bacteria. The etiology of erosion is related to different behavioral, biological and chemical factors. Based on an overview of the current literature, this paper presents a summary of the preventive strategies relevant for patients suffering from dental erosion. Behavioral factors, such as special drinking habits, unhealthy lifestyle factors or occupational acid exposure, might modify the extent of dental erosion. Thus, preventive strategies have to include measures to reduce the frequency and duration of acid exposure as well as adequate oral hygiene measures, as it is known that eroded surfaces are more susceptible to abrasion. Biological factors, such as saliva or acquired pellicle, act protectively against erosive demineralization. Therefore, the production of saliva should be enhanced, especially in patients with hyposalivation or xerostomia. With regard to chemical factors, the modification of acidic solutions with ions, especially calcium, was shown to reduce the demineralization, but the efficacy depends on the other chemical factors, such as the type of acid. To enhance the remineralization of eroded surfaces and to prevent further progression of dental wear, high-concentrated fluoride applications are recommended. Currently, little information is available about the efficacy of other preventive strategies, such as calcium and laser application, as well as the use of matrix metalloproteinase inhibitors. Further studies considering these factors are required. In conclusion, preventive strategies for patients suffering from erosion are mainly obtained from in vitro and in situ studies and include dietary counseling, stimulation of salivary flow, optimization of fluoride regimens, modification of erosive beverages and adequate oral hygiene measures.

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OBJETIVO: Avaliar a validade do peso, estatura e Índice de Massa Corporal (IMC) referidos e sua confiabilidade para o diagnóstico do estado nutricional de adolescentes de Piracicaba. MÉTODOS: Participaram do estudo 360 adolescentes de ambos os sexos, de escolas públicas de Piracicaba, com idade entre 10 e 15 anos. Os adolescentes auto-relataram seu peso e estatura, sendo esses valores obtidos por medidas diretas, logo em seguida, pelos entrevistadores. A validade do IMC referido foi calculada segundo índices de sensibilidade, especificidade e valor preditivo positivo (VPP). Avaliou-se a concordância entre as categorias de IMC obtido por meio das medidas referidas e aferidas a partir do coeficiente kappa ponderado, coeficiente de correlação de Lin. e gráficos de Bland e Altman e Lin. RESULTADOS: Verificou-se que tanto os meninos quanto as meninas subestimaram o peso (-1,0 meninas e meninos) e a estatura (meninas -1,2 e meninos -0,8) (p < 0,001). Os valores de IMC aferidos e referidos apresentaram uma concordância moderada. A sensibilidade do IMC referido para classificar os indivíduos obesos foi maior para os meninos (87,5%), enquanto a especificidade foi maior para as meninas (92,7%). O VPP foi elevado somente para a classificação da eutrofia. CONCLUSÕES: As medidas referidas de peso e estatura de adolescentes não representam medidas válidas e, portanto, não devem ser usadas em substituição aos valores mensurados. Além disso, verificou-se que 10% dos meninos obesos e 40% das meninas obesas poderiam permanecer não identificados utilizando-se as medidas auto-referidas, confirmando a baixa validade das medidas auto-referidas.

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In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.