988 resultados para Chinease characters


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A new procedure for the classification of lower case English language characters is presented in this work . The character image is binarised and the binary image is further grouped into sixteen smaller areas ,called Cells . Each cell is assigned a name depending upon the contour present in the cell and occupancy of the image contour in the cell. A data reduction procedure called Filtering is adopted to eliminate undesirable redundant information for reducing complexity during further processing steps . The filtered data is fed into a primitive extractor where extraction of primitives is done . Syntactic methods are employed for the classification of the character . A decision tree is used for the interaction of the various components in the scheme . 1ike the primitive extraction and character recognition. A character is recognized by the primitive by primitive construction of its description . Openended inventories are used for including variants of the characters and also adding new members to the general class . Computer implementation of the proposal is discussed at the end using handwritten character samples . Results are analyzed and suggestions for future studies are made. The advantages of the proposal are discussed in detail .

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In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets

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Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

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HINDI

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Resumen tomado de la publicaci??n

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Micromorphological characters of the fruiting bodies, such as ascus-type and hymenial amyloidity, and secondary chemistry have been widely employed as key characters in Ascomycota classification. However, the evolution of these characters has yet not been studied using molecular phylogenies. We have used a combined Bayesian and maximum likelihood based approach to trace character evolution on a tree inferred from a combined analysis of nuclear and mitochondrial ribosomal DNA sequences. The maximum likelihood aspect overcomes simplifications inherent in maximum parsimony methods, whereas the Markov chain Monte Carlo aspect renders results independent of any particular phylogenetic tree. The results indicate that the evolution of the two chemical characters is quite different, being stable once developed for the medullary lecanoric acid, whereas the cortical chlorinated xanthones appear to have been lost several times. The current ascus-types and the amyloidity of the hymenial gel in Pertusariaceae appear to have been developed within the family. The basal ascus-type of pertusarialean fungi remains unknown. (c) 2006 The Linnean Society of London, Biological Journal of the Linnean Society, 2006, 89, 615-626.

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We describe a Bayesian method for investigating correlated evolution of discrete binary traits on phylogenetic trees. The method fits a continuous-time Markov model to a pair of traits, seeking the best fitting models that describe their joint evolution on a phylogeny. We employ the methodology of reversible-jump ( RJ) Markov chain Monte Carlo to search among the large number of possible models, some of which conform to independent evolution of the two traits, others to correlated evolution. The RJ Markov chain visits these models in proportion to their posterior probabilities, thereby directly estimating the support for the hypothesis of correlated evolution. In addition, the RJ Markov chain simultaneously estimates the posterior distributions of the rate parameters of the model of trait evolution. These posterior distributions can be used to test among alternative evolutionary scenarios to explain the observed data. All results are integrated over a sample of phylogenetic trees to account for phylogenetic uncertainty. We implement the method in a program called RJ Discrete and illustrate it by analyzing the question of whether mating system and advertisement of estrus by females have coevolved in the Old World monkeys and great apes.

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In attempting to answer the question ‘How is disability represented in plays?’ two approaches are considered, one semiotic and literary and the other concerned with notions of stereotyping drawn from disability studies. The five plays on which the discussion is based are school examination set texts, raising questions about classroom discourse and interpretation. Pilot study data drawn from students’ work in examinations are offered to suggest possible answers to those questions.

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Cladistic analyses begin with an assessment of variation for a group of organisms and the subsequent representation of that variation as a data matrix. The step of converting observed organismal variation into a data matrix has been considered subjective, contentious, under-investigated, imprecise, unquantifiable, intuitive, as a black-box, and at the same time as ultimately the most influential phase of any cladistic analysis (Pimentel and Riggins, 1987; Bryant, 1989; Pogue and Mickevich, 1990; de Pinna, 1991; Stevens, 1991; Bateman et al., 1992; Smith, 1994; Pleijel, 1995; Wilkinson, 1995; Patterson and Johnson, 1997). Despite the concerns of these authors, primary homology assessment is often perceived as reproducible. In a recent paper, Hawkins et al. (1997) reiterated two points made by a number of these authors: that different interpretations of characters and coding are possible and that different workers will perceive and define characters in different ways. One reviewer challenged us: did we really think that two people working on the same group would come up with different data sets? The conflicting views regarding the reproducibility of the cladistic character matrix provoke a number of questions. Do the majority of workers consistently follow the same guidelines? Has the theoretical framework informing primary homology assessment been adequately explored? The objective of this study is to classify approaches to primary homology assessment, and to quantify the extent to which different approaches are found in the literature by examining variation in the way characters are defined and coded in a data matrix.

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Electronic word of mouth (eWoM) has been adopted by Internet users as a way of communicating their consumption preferences and experiences. Consumers are able to reach out to others, unknown to them, and have online conversations that can influence their behaviour. Organisations need to understand how to respond to these brand-related conversations conducted via social media. By looking through the lens of social capital, this paper contributes to social media and social capital research by studying the perceptions that 44 social media users have of companies that interact with them online. The users value social networks and support as part of their online relationships. However, several new value categories are identified when compared to previous research. Further research is required to investigate possible segmentation approaches and alternative methodological choices.

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Traffic Control Signs or destination boards on roadways offer significant information for drivers. Regulation signs tell something like your speed, turns, etc; Warning signs warn drivers of conditions ahead to help them avoid accidents; Destination signs show distances and directions to various locations; Service signs display location of hospitals, gas and rest areas etc. Because the signs are so important and there is always a certain distance from them to drivers, to let the drivers get information clearly and easily even in bad weather or other situations. The idea is to develop software which can collect useful information from a special camera which is mounted in the front of a moving car to extract the important information and finally show it to the drivers. For example, when a frame contains on a destination drive sign board it will be text something like "Linkoping 50",so the software should extract every character of "Linkoping 50", compare them with the already known character data in the database. if there is extracted character match "k" in the database then output the destination name and show to the driver. In this project C++ will be used to write the code for this software.

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This essay presents a portrayal of Heathcliff, Catherine and Isabella from a psychoanalytical perspective with regard to four defense mechanisms; namely, repression, denial, sublimation and projection in order to see how these defense mechanisms have affected the characters’ decisions and behaviour, and led them to their destinations in life. It will include three major sections: repression in characters, denial in characters, and sublimation and projection in characters. These terms will be more clearly defined and explained in the subsequent sections.