900 resultados para Hierarchy of text classifiers


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We present a mathematical model describing the inward solidification of a slab, a circular cylinder and a sphere of binary melt kept below its equilibrium freezing temperature. The thermal and physical properties of the melt and solid are assumed to be identical. An asymptotic method, valid in the limit of large Stefan number is used to decompose the moving boundary problem for a pure substance into a hierarchy of fixed-domain diffusion problems. Approximate, analytical solutions are derived for the inward solidification of a slab and a sphere of a binary melt which are compared with numerical solutions of the unapproximated system. The solutions are found to agree within the appropriate asymptotic regime of large Stefan number and small time. Numerical solutions are used to demonstrate the dependence of the solidification process upon the level of impurity and other parameters. We conclude with a discussion of the solutions obtained, their stability and possible extensions and refinements of our study.

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Background: Research in aphasia has focused on acquired dyslexias at the single word level, with a paucity of assessment techniques and rehabilitation approaches for individuals with difficulty at the text level. A rich literature from research with paediatric populations and healthy non-brain damaged, skilled adult readers allows the component processes that are important for text reading to be defined and more appropriate assessments to be devised. Aims: To assess the component processes of text reading in a small group of individuals with aphasia who report difficulties reading at the text level. Do assessments of component processes in reading comprehension reveal distinct profiles of text comprehension? To what extent are text comprehension difficulties caused by underlying linguistic and/or cognitive deficits? Methods & Procedures: Four individuals with mild aphasia who reported difficulties reading at the text level took part in a case-series study. Published assessments were used to confirm the presence of text comprehension impairment. Participants completed a range of assessments to provide a profile of their linguistic and cognitive skills, focusing on processes known to be important for text comprehension. We identified the following areas for assessment: reading speed, language skills (single word and sentence), inferencing, working memory and metacognitive skills (monitoring and strategy use). Outcomes & Results: Performance was compared against age-matched adult control data. One participant presented with a trend for impaired abilities in inferencing, with all other assessed skills being within normal limits. The other three had identified linguistic and working memory difficulties. One presented with a residual deficit in accessing single word meaning that affected text comprehension. The other two showed no clear link between sentence processing difficulties and text comprehension impairments. Across these three, data suggested a link between verbal working memory capacity and specific inferencing skills. Conclusions: Successful text reading relies on a number of component processes. In this paper we have made a start in defining those component processes and devising tasks suitable to assess them. From our results, assessment of verbal working memory and inferencing appears to be critical for understanding text comprehension impairments in aphasia. It is possible that rehabilitation input can capitalize on key meta-cognitive skills (monitoring, strategy use) to support functional reading in the face of existing linguistic, text comprehension and memory impairments.

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Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

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Sclera segmentation is shown to be of significant importance for eye and iris biometrics. However, sclera segmentation has not been extensively researched as a separate topic, but mainly summarized as a component of a broader task. This paper proposes a novel sclera segmentation algorithm for colour images which operates at pixel-level. Exploring various colour spaces, the proposed approach is robust to image noise and different gaze directions. The algorithm’s robustness is enhanced by a two-stage classifier. At the first stage, a set of simple classifiers is employed, while at the second stage, a neural network classifier operates on the probabilities’ space generated by the classifiers at stage 1. The proposed method was ranked the 1st in Sclera Segmentation Benchmarking Competition 2015, part of BTAS 2015, with a precision of 95.05% corresponding to a recall of 94.56%.

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Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.

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Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

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We revisit the problem of an otherwise classical particle immersed in the zero-point radiation field, with the purpose of tracing the origin of the nonlocality characteristic of Schrodinger`s equation. The Fokker-Planck-type equation in the particles phase-space leads to an infinite hierarchy of equations in configuration space. In the radiationless limit the first two equations decouple from the rest. The first is the continuity equation: the second one, for the particle flux, contains a nonlocal term due to the momentum fluctuations impressed by the field. These equations are shown to lead to Schrodinger`s equation. Nonlocality (obtained here for the one-particle system) appears thus as a property of the description, not of Nature. (C) 2011 Elsevier B.V. All rights reserved.

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Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features. (c) 2008 Elsevier Inc. All rights reserved.

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We have demonstrated previously that the complex bis[(2-oxindol-3-ylimino)-2-(2-aminoethyl)pyridine-N,N`]copper(II), named [Cu(isaepy)(2)], induces AMPK (AMP-activated protein kinase)-dependent/p53-mediated apoptosis in tumour cells by targeting mitochondria. In the present study, we found that p38(MAPK) (p38 mitogen-activated protein kinase) is the molecular link in the phosphorylation cascade connecting AMPK to p53. Transfection of SH-SY5Y cells with a dominant-negative mutant of AMPK resulted in a decrease in apoptosis and a significant reduction in phospho-active p38(MAPK) and p53. Similarly, reverse genetics of p38(MAPK) yielded a reduction in p53 and a decrease in the extent of apoptosis, confirming an exclusive hierarchy of activation that proceeds via AMPK/p38(MAPK)/p53. Fuel supplies counteracted [Cu(isaepy)(2)]-induced apoptosis and AMPK/p38(MAPK)/p53 activation, with glucose being the most effective, suggesting a role for energetic imbalance in [Cu(isaepy)(2)] toxicity. Co-administration of 3BrPA (3-bromopyruvate), a well-known inhibitor of glycolysis, and succinate dehydrogenase, enhanced apoptosis and AMPK/p38(MAPK)/p53 signalling pathway activation. Under these conditions, no toxic effect was observed in SOD (superoxide dismutase)-overexpressing SH-SY5Y cells or in PCNs (primary cortical neurons), which are, conversely, sensitized to the combined treatment with [Cu(isaepy)(2)] and 3BrPA only if grown in low-glucose medium or incubated with the glucose-6-phosphate dehydrogenase inhibitor dehydroepiandrosterone. Overall, the results suggest that NADPH deriving from the pentose phosphate pathway contributes to PCN resistance to [Cu(isaepy)(2)] toxicity and propose its employment in combination with 3BrPA as possible tool for cancer treatment.

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Though sound symbolic words (onomatopoeia and mimetic words, or giongo and gitaigo in Japanese) exist in other languages, it would not be so easy to compare them to those in Japanese. This is because unlike in Japanese, in many other languages (here we see English and Spanish) sound symbolic words do not have distinctive forms that separate them immediately from the rest of categories of words. In Japanese, a sound symbolic word has a radical (that is based on the elaborated Japanese sound symbolic system), and often a suffix that shows subtle nuance. Together they give the word a distinctive form that differentiates it from other categories of words, though its grammatical functions could vary, especially in the case of mimetic words (gitaigo). Without such an obvious feature, in other languages, it would not be always easy to separate sound symbolic words from the rest. These expressions are extremely common and used in almost all types of text in Japanese, but their elaborated sound symbolic system and possibly their various grammatical functions are making giongo and gitaigo one of the most difficult challenges for the foreign students and translators. Studying the translation of these expressions into other languages might give some indication related to the comparison of Japanese sound symbolic words and those in other languages. Though sound symbolic words are present in many types of texts in Japanese, their functions in traditional forms of text (letters only) and manga (Japanese comics)are different and they should be treated separately. For example, in traditional types of text such as novels, the vast majority of the sound symbolic words used are mimetic words (gitaigo) and most of them are used as adverbs, whereas in manga, the majority of the sound symbolic words used (excluding those appear within the speech bubbles) are onomatopoeias (giongo) and often used on their own (i.e. not as a part of a sentence). Naturally, the techniques used to translate these expressions in the above two types of documents differ greatly. The presentation will focus on i) grammatical functions of Japanese sound symbolic words in traditional types of texts (novels/poems) and in manga works, and ii) whether their features and functions are maintained (i.e. whether they are translated as sound symbolic words) when translated into other languages (English and Spanish). The latter point should be related to a comparison of sound symbolic words in Japanese and other languages, which will be also discussed.

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Optimal location on the transport infrastructure is the preferable requirement for many decision making processes. Most studies have focused on evaluating performances of optimally locate p facilities by minimizing their distances to a geographically distributed demand (n) when p and n vary. The optimal locations are also sensitive to geographical context such as road network, especially when they are asymmetrically distributed in the plane. The influence of alternating road network density is however not a very well-studied problem especially when it is applied in a real world context. This paper aims to investigate how the density level of the road network affects finding optimal location by solving the specific case of p-median location problem. A denser network is found needed when a higher number of facilities are to locate. The best solution will not always be obtained in the most detailed network but in a middle density level. The solutions do not further improve or improve insignificantly as the density exceeds 12,000 nodes, some solutions even deteriorate. The hierarchy of the different densities of network can be used according to location and transportation purposes and increase the efficiency of heuristic methods. The method in this study can be applied to other location-allocation problem in transportation analysis where the road network density can be differentiated. 

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Delineation of commuting regions has always been based on statistical units, often municipalities or wards. However, using these units has certain disadvantages as their land areas differ considerably. Much information is lost in the larger spatial base units and distortions in self-containment values, the main criterion in rule-based delineation procedures, occur. Alternatively, one can start from relatively small standard size units such as hexagons. In this way, much greater detail in spatial patterns is obtained. In this paper, regions are built by means of intrazonal maximization (Intramax) on the basis of hexagons. The use of geoprocessing tools, specifically developed for the processing ofcommuting data, speeds up processing time considerably. The results of the Intramax analysis are evaluated with travel-to-work area constraints, and comparisons are made with commuting fields, accessibility to employment, commuting flow density and network commuting flow size. From selected steps in the regionalization process, a hierarchy of nested commuting regions emerges, revealing the complexity of commuting patterns.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The negative symmetry flows are incorporated into the Riemann-Hilbert problem for the homogeneous A(m)-hierarchy and its (gl) over cap (m + 1, C) extension.A loop group automorphism of order two is used to define a sub-hierarchy of (gl) over cap (m + 1, C) hierarchy containing only the odd symmetry flows. The positive and negative flows of the +/-1 grade coincide with equations of the multidimensional Toda model and of topological-anti-topological fusion. (C) 2002 Elsevier B.V. B.V. All rights reserved.

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Using the coadjoint orbit method we derive a geometric WZWN action based on the extended two-loop Kac-Moody algebra. We show that under a hamiltonian reduction procedure, which respects conformal invariance, we obtain a hierarchy of Toda type field theories, which contain as submodels the Toda molecule and periodic Toda lattice theories. We also discuss the classical r-matrix and integrability properties.