883 resultados para Word Matching


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Language is typically a function of the left hemisphere but the right hemisphere is also essential in some healthy individuals and patients. This inter-subject variability necessitates the localization of language function, at the individual level, prior to neurosurgical intervention. Such assessments are typically made by comparing left and right hemisphere language function to determine "language lateralization" using clinical tests or fMRI. Here, we show that language function needs to be assessed at the region and hemisphere specific level, because laterality measures can be misleading. Using fMRI data from 82 healthy participants, we investigated the degree to which activation for a semantic word matching task was lateralized in 50 different brain regions and across the entire cortex. This revealed two novel findings. First, the degree to which language is lateralized across brain regions and between subjects was primarily driven by differences in right hemisphere activation rather than differences in left hemisphere activation. Second, we found that healthy subjects who have relatively high left lateralization in the angular gyrus also have relatively low left lateralization in the ventral precentral gyrus. These findings illustrate spatial heterogeneity in language lateralization that is lost when global laterality measures are considered. It is likely that the complex spatial variability we observed in healthy controls is more exaggerated in patients with brain damage. We therefore highlight the importance of investigating within hemisphere regional variations in fMRI activation, prior to neuro-surgical intervention, to determine how each hemisphere and each region contributes to language processing. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.

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This work has been partially supported by Grant No. DO 02-275, 16.12.2008, Bulgarian NSF, Ministry of Education and Science.

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This article introduces EsPal: a Web-accessible repository containing a comprehensive set of properties of Spanish words. EsPal is based on an extensible set of data sources, beginning with a 300 million token written database and a 460 million token subtitle database. Properties available include word frequency, orthographic structure and neighborhoods, phonological structure and neighborhoods, and subjective ratings such as imageability. Subword structure properties are also available in terms of bigrams and trigrams, bi-phones, and bi-syllables. Lemma and part-of-speech information and their corresponding frequencies are also indexed. The website enables users to either upload a set of words to receive their properties, or to receive a set of words matching constraints on the properties. The properties themselves are easily extensible and will be added over time as they become available. It is freely available from the following website: http://www.bcbl.eu/databases/espal

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This article introduces EsPal: a Web-accessible repository containing a comprehensive set of properties of Spanish words. EsPal is based on an extensible set of data sources, beginning with a 300 million token written database and a 460 million token subtitle database. Properties available include word frequency, orthographic structure and neighborhoods, phonological structure and neighborhoods, and subjective ratings such as imageability. Subword structure properties are also available in terms of bigrams and trigrams, bi-phones, and bi-syllables. Lemma and part-of-speech information and their corresponding frequencies are also indexed. The website enables users to either upload a set of words to receive their properties, or to receive a set of words matching constraints on the properties. The properties themselves are easily extensible and will be added over time as they become available. It is freely available from the following website: http://www.bcbl.eu/databases/espal

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This study compared orthographic and semantic aspects of word learning in children who differed in reading comprehension skill. Poor comprehenders and controls matched for age (9-10 years), nonverbal ability and decoding skill were trained to pronounce 20 visually presented nonwords, 10 in a consistent way and 10 in an inconsistent way. They then had an opportunity to infer the meanings of the new words from story context. Orthographic learning was measured in three ways: the number of trials taken to learn to pronounce nonwords correctly, orthographic choice and spelling. Across all measures, consistent items were easier than inconsistent items and poor comprehenders did not differ from control children. Semantic learning was assessed on three occasions, using a nonword-picture matching task. While poor comprehenders showed equivalent semantic learning to controls immediately after exposure to nonword meaning, this knowledge was not well retained over time. Results are discussed in terms of the language and reading skills of poor comprehenders and in relation to current models of reading development.

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Creating non-word lists is a necessary but time consuming exercise often needed when conducting behavioural language tasks involving lexical decision-making or non-word reading. The following article describes the process whereby we created a list of 226 non-words matching 226 of the Snodgrass picture set (Snodgrass & Vanderwart, 1980).The non-words were matched for number of syllables, stress pattern, number of phonemes, bigram count and presence and location of the target sound when relevant.

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Objective: There is convincing evidence that phonological, orthographic and semantic processes influence children’s ability to learn to read and spell words. So far only a few studies investigated the influence of implicit learning in literacy skills. Children are sensitive to the statistics of their learning environment. By frequent reading they acquire implicit knowledge about the frequency of letter patterns in written words, and they use this knowledge during reading and spelling. Additionally, semantic connections facilitate to storing of words in memory. Thus, the aim of the intervention study was to implement a word-picture training which is based on statistical and semantic learning. Furthermore, we aimed at examining the training effects in reading and spelling in comparison to an auditory-visual matching training and a working memory training program. Participants and Methods: One hundred and thirty-two children aged between 8 and 11 years participated in training in three weekly session of 12 minutes over 8 weeks, and completed other assessments of reading, spelling, working memory and intelligence before and after training. Results: Results revealed in general that the word-picture training and the auditory-visual matching training led to substantial gains in reading and spelling performance in comparison to the working-memory training. Although both children with and without learning difficulties profited in their reading and spelling after the word-picture training, the training program led to differential effects for the two groups. After the word-picture training on the one hand, children with learning difficulties profited more in spelling as children without learning difficulties, on the other hand, children without learning difficulties benefit more in word comprehension. Conclusions: These findings highlight the need for frequent reading trainings with semantic connections in order to support the acquisition of literacy skills.

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We propose a novel template matching approach for the discrimination of handwritten and machine-printed text. We first pre-process the scanned document images by performing denoising, circles/lines exclusion and word-block level segmentation. We then align and match characters in a flexible sized gallery with the segmented regions, using parallelised normalised cross-correlation. The experimental results over the Pattern Recognition & Image Analysis Research Lab-Natural History Museum (PRImA-NHM) dataset show remarkably high robustness of the algorithm in classifying cluttered, occluded and noisy samples, in addition to those with significant high missing data. The algorithm, which gives 84.0% classification rate with false positive rate 0.16 over the dataset, does not require training samples and generates compelling results as opposed to the training-based approaches, which have used the same benchmark.

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A expansão da tríplice continência em unidades com quatro ou mais elementos abriu novas perspectivas para a compreensão de comportamentos complexos, como a emergência de respostas que derivam da formação de classes de estímulos equivalentes e que modelam comportamentos simbólicos e conceituais. Na investigação experimental, o procedimento de matching to sample tem sido frequentemente empregado para estabelecer discriminações condicionais. Em particular, a obtenção do matching de identidade generalizado é considerada demonstrativa da aquisição dos conceitos de igualdade e diferença. Segundo argumentamos, o fato de se buscar a compreensão desses conceitos a partir de processos discriminativos condicionais pode ter sido responsável pelos frequentes fracassos em demonstrá-los em sujeitos não humanos. A falta de correspondência entre os processos discriminativos responsáveis por estabelecer a relação de reflexividade entre estímulos que formam classes equivalentes e o matching de identidade generalizado, nesse sentido, é aqui revista ao longo de estudos empíricos e discutida com respeito às suas implicações.

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In this article, we evaluate the use of simple Lee-Goldburg cross-polarization (LG-CP) NMR experiments for obtaining quantitative information of molecular motion in the intermediate regime. In particular, we introduce the measurement of Hartmann-Hahn matching profiles for the assessment of heteronuclear dipolar couplings as well as dynamics as a reliable and robust alternative to the more common analysis of build-up curves. We have carried out dynamic spin dynamics simulations in order to test the method's sensitivity to intermediate motion and address its limitations concerning possible experimental imperfections. We further demonstrate the successful use of simple theoretical concepts, most prominently Anderson-Weiss (AW) theory, to analyze the data. We further propose an alternative way to estimate activation energies of molecular motions, based upon the acquisition of only two LG-CP spectra per temperature at different temperatures. As experimental tests, molecular jumps in imidazole methyl sulfonate, trimethylsulfoxonium iodide, and bisphenol A polycarbonate were investigated with the new method.

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Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

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We consider brightness/contrast-invariant and rotation-discriminating template matching that searches an image to analyze A for a query image Q We propose to use the complex coefficients of the discrete Fourier transform of the radial projections to compute new rotation-invariant local features. These coefficients can be efficiently obtained via FFT. We classify templates in ""stable"" and ""unstable"" ones and argue that any local feature-based template matching may fail to find unstable templates. We extract several stable sub-templates of Q and find them in A by comparing the features. The matchings of the sub-templates are combined using the Hough transform. As the features of A are computed only once, the algorithm can find quickly many different sub-templates in A, and it is Suitable for finding many query images in A, multi-scale searching and partial occlusion-robust template matching. (C) 2009 Elsevier Ltd. All rights reserved.

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Understanding resource capture can help design appropriate species combinations, planting designs and management. Leaf area index (LAI) and its longevity are the most important factors defining dry matter production and thus growth and productivity. The ecophysiological modifications and yield of rubber (Hevea spp.) in an agroforestry system (AFS) with beans (Phaseolus vulgaris L.) were studied. The experiment was established in Southeast-Brazil, with three rubber cultivars: IAN 3087, RRIM 600 and RRIM 527. The AFS comprised double rows of rubber trees along with beans sown in autumn and winter seasons in 1999. There was about 50% higher rubber yield per tree in the AFS than the rubber monoculture. Trees within the AFS responded to higher solar radiation availability with higher LAI and total foliage area, allowing its greater interception. All three cultivars had higher LAI in the AFS than monoculture, reaching maximum values in the AFS between April and May of 3.17 for RRIM 527; 2.83 for RRIM 600 and 2.28 for IAN 3087. The maximum LAI values for monocrop rubber trees were: 2.65, 2.62 and 1.99, respectively, for each cultivar. Rubber production and LAI were positively correlated in both the AFS and monoculture but leaf fall of rubber trees in the AFS was delayed and total phytomass was larger. It is suggested that trees in the AFS were under exploited and could yield more without compromising their life cycle if the tapping system was intensified. This shows how knowledge of LAI can be used to manage tapping intensity in the field, leading to higher rubber yield.

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This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).