42 resultados para modified local binary pattern

em Indian Institute of Science - Bangalore - Índia


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The modified local stability scheme is applied to several two-dimensional problems—blunt body flow, regular reflection of a shock and lambda shock. The resolution of the flow features obtained by the modified local stability scheme is found to be better than that achieved by the other first order schemes and almost identical to that achieved by the second order schemes incorporating artificial viscosity. The scheme is easy for coding, consumes moderate amount of computer storage and time. The scheme can be advantageously used in place of second order schemes.

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Lateral appendages often show allometric growth with a specific growth polarity along the proximo-distal axis. Studies on leaf growth in model plants have identified a basipetal growth direction with the highest growth rate at the proximal end and progressively lower rates toward the distal end. Although the molecular mechanisms governing such a growth pattern have been studied recently, variation in leaf growth polarity and, therefore, its evolutionary origin remain unknown. By surveying 75 eudicot species, here we report that leaf growth polarity is divergent. Leaf growth in the proximo-distal axis is polar, with more growth arising from either the proximal or the distal end; dispersed with no apparent polarity; or bidirectional, with more growth contributed by the central region and less growth at either end. We further demonstrate that the expression gradient of the miR396-GROWTH-REGULATING FACTOR module strongly correlates with the polarity of leaf growth. Altering the endogenous pattern of miR396 expression in transgenic Arabidopsis thaliana leaves only partially modified the spatial pattern of cell expansion, suggesting that the diverse growth polarities might have evolved via concerted changes in multiple gene regulatory networks.

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Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

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An energy landscape view of phase separation and nonideality in binary mixtures is developed by exploring their potential energy landscape (PEL) as functions of temperature and composition. We employ molecular dynamics simulations to study a model that promotes structure breaking in the solute-solvent parent binary liquid, at low temperatures. The PEL of the system captures the potential energy distribution of the inherent structures (IS) of the system and is obtained by removing the kinetic energy (including that of intermolecular vibrations). The broader distribution of the inherent structure energy for structure breaking liquid than that of the structure making liquid demonstrates the larger role of entropy in stabilizing the parent liquid of the structure breaking type of binary mixtures. At high temperature, although the parent structure of the structure breaking binary mixture is homogenous, the corresponding inherent structure is found to be always phase separated, with a density pattern that exhibits marked correlation with the energy of its inherent structure. Over a broad range of intermediate inherent structure energy, bicontinuous phase separation prevails with interpenetrating stripes as signatures of spinodal decomposition. At low inherent structure energy, the structure is largely phase separated with one interface where as at high inherent structure energy we find nucleation type growth. Interestingly, at low temperature, the average inherent structure energy (< EIS >) exhibits a drop with temperature which signals the onset of crystallization in one of the phases while the other remains in the liquid state. The nonideal composition dependence of viscosity is anticorrelated with average inherent structure energy.

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Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

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Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

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There are essentially two different phenomenological models available to describe the interdiffusion process in binary systems in the olid state. The first of these, which is used more frequently, is based on the theory of flux partitioning. The second model, developed much more recently, uses the theory of dissociation and reaction. Although the theory of flux partitioning has been widely used, we found that this theory does not account for the mobility of both species and therefore is not suitable for use in most interdiffusion systems. We have first modified this theory to take into account the mobility of both species and then further extended it to develop relations or the integrated diffusion coefficient and the ratio of diffusivities of the species. The versatility of these two different models is examined in the Co-Si system with respect to different end-member compositions. From our analysis, we found that the applicability of the theory of flux partitioning is rather limited but the theory of dissociation and reaction can be used in any binary system.

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The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

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A new form of L-histidine L-aspartate monohydrate crystallizes in space group P22 witha = 5.131(1),b = 6.881(1),c= 18.277(2) Å,β= 97.26(1)° and Z = 2. The structure has been solved by the direct methods and refined to anR value of 0.044 for 1377 observed reflections. Both the amino acid molecules in the complex assume the energetically least favourable allowed conformation with the side chains staggered between the α-amino and α-scarboxylate groups. This results in characteristic distortions in some bond angles. The unlike molecules aggregate into alternating double layers with water molecules sandwiched between the two layers in the aspartate double layer. The molecules in each layer are arranged in a head-to-tail fashion. The aggregation pattern in the complex is fundamentally similar to that in other binary complexes involving commonly occurring L amino acids, although the molecules aggregate into single layers in them. The distribution of crystallographic (and local) symmetry elements in the old form of the complex is very different from that in the new form. So is the conformation of half the histidine molecules. Yet, the basic features of molecular aggregation, particularly the nature and the orientation of head-to-tail sequences, remain the same in both the forms. This supports the thesis that the characteristic aggregation patterns observed in crystal structures represent an intrinsic property of amino acid aggregation.

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This paper describes the implementation of the modified continuously variable slope delta modulator (MCVSD), in which the basic step size δ0 is made to vary as a function of input signal level. The information needed to carry out this is extracted at the local decoder output so that the coder and the decoder track each other. The result is a significant improvement in the dynamic range (about 15dB) as compared to CVSD coder without degrading the peak signal to noise ratio.

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New dimensionally consistent modified solvate complex models are derived to correlate solubilities of solids in supercritical fluids both in the presence and absence of entrainers (cosolvents). These models are compared against the standard solvate complex models [J.Chrastil, J. Phys. Chem. 86 (1982) 3016-3021; J.C. Gonzalez, M.R.Vieytes, A.M. Botana, J.M. Vieites, L.M. Botana, J. Chromatogr. A 910 (2001) 119-125; Y. Adachi, B.C.Y. Lu, Fluid Phase Equilb. 14 (1983) 47-156; J.M. del Valle, J.M. Aguilera, Ind. Eng. Chem. Res. 27 (1988) 1551-1553] by correlating the solubilities of 13 binary and 12 ternary systems. Though the newly derived models are not significantly better than the standard models in predicting the solubilities, they are dimensionally consistent. (C) 2009 Elsevier B.V. All rights reserved.

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Polyhedral bodies of Bombyx mori nuclear polyhedrosis virus, BmNPV (BGL) isolated from infected silkworms around Bangalore were propagated either in the cultured B. mori cell line, BmN or through infection of larvae. Electron microscopic (EM) observations of the polyhedra revealed an average length of 2 mu m and a height of 0.5 mu m. The purified polyhedra derived virions (PDV) showed several bands in sucrose gradient centrifugation, indicating the multiple nucleocapsid nature of BmNPV. Electron microscopic studies of PDV revealed a cylindrical, rod-shaped nucleocapsid with an average length of 300 nm and a diameter of 35 nm. The genomic DNA from the PDV was characterized by extensive restriction analysis and the genome size was estimated to be 132 kb. The restriction pattern of BmNPV (BGL) resembled that of the prototype strain BmNPV-T3. Distinct differences due to polymorphic sites for restriction enzyme HindIII were apparent between BmNPV (BGL) and the virus isolated from a different part of Karnataka (Dharwad area), BmNPV (DHR).

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The associated model for binary systems has been modified to include volume effects and excess entropy arising from preferential interactions between the associate and the free atoms or between the free atoms. Equations for thermodynamic mixing functions have been derived. An optimization procedure using a modified conjugate gradient method has been used to evaluate the enthalpy and entropy interaction energies, the free energy of dissociation of the complex, its temperature dependance and the size of the associate. An expression for the concentration—concentration structure factor [Scc (0)] has been deduced from the modified associated solution model. The analysis has been applied to the thermodynamic mixing functions of liquid Ga-Te alloys at 1120 K, believed to contain Ga2Te3 associates. It is observed that the modified associated solution model incorporating volume effects and terms for the temperature dependance of interaction energies, describes the thermodynamic properties of Ga-Te system satisfactorily.

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The clusters of binary patterns can be considered as Boolean functions of the (binary) features. Such a relationship between the linearly separable (LS) Boolean functions and LS clusters of binary patterns is examined. An algorithm is presented to answer the questions of the type: “Is the cluster formed by the subsets of the (binary) data set having certain features AND/NOT having certain other features, LS from the remaining set?” The algorithm uses the sequences of Numbered Binary Form (NBF) notation and some elementary (NPN) transformations of the binary data.

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The clusters of binary patterns can be considered as Boolean functions of the (binary) features. Such a relationship between the linearly separable (LS) Boolean functions and LS clusters of binary patterns is examined. An algorithm is presented to answer the questions of the type: “Is the cluster formed by the subsets of the (binary) data set having certain features AND/NOT having certain other features, LS from the remaining set?” The algorithm uses the sequences of Numbered Binary Form (NBF) notation and some elementary (NPN) transformations of the binary data.