69 resultados para Graph Decomposition


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This work presents a novel algorithm for decomposing NFA automata into one-state-active modules for parallel execution on Multiprocessor Systems on Chip (MP-SoC). Furthermore, performance related studies based on a 16-PE system for Snort, Bro and Linux-L7 regular expressions are presented. ©2009 IEEE.

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We address the presence of bound entanglement in strongly interacting spin systems at thermal equilibrium. In particular, we consider thermal graph states composed of an arbitrary number of particles. We show that for a certain range of temperatures no entanglement can be extracted by means of local operations and classical communication, even though the system is still entangled. This is found by harnessing the independence of the entanglement in some bipartitions of such states with the system's size. Specific examples for one- and two-dimensional systems are given. Our results thus prove the existence of thermal bound entanglement in an arbitrary large spin system with finite-range local interactions.

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Demand Side Management (DSM) programmes are designed to shift electrical loads from peak times. Demand Response (DR) algorithms automate this process for controllable loads. DR can be implemented explicitly in terms of Peak to Average Ratio Reduction (PARR), in which case the maximum peak load is minimised over a prediction horizon by manipulating the amount of energy given to controllable loads at different times. A hierarchical predictive PARR algorithm is presented here based on Dantzig-Wolfe decomposition. © 2013 IEEE.

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Levoglucosan (1,6-anhydro-β-d-glucopyranose) decomposition is an important step during cellulose pyrolysis and for secondary tar reactions. The mechanism of levoglucosan thermal decomposition was studied in this paper using density functional theory methods. The decomposition included direct CO bond breaking, direct CC bond breaking, and dehydration. In total, 9 different pathways, including 16 elementary reactions, were studied, in which levoglucosan serves as a reactant. The properties of the reactants, transition states, intermediates, and products for every elementary reaction were obtained. It was found that 1-pentene-3,4-dione, acetaldehyde, 2,3-dihydroxypropanal, and propanedialdehyde can be formed from the CO bond breaking decomposition reactions. 1,2-Dihydroxyethene and hydroxyacetic acid vinyl ester can be formed from the CC bond breaking decomposition reactions. It was concluded that CO bond breaking is easier than CC bond breaking due to a lower activation energy and a higher released energy. During the 6 levoglucosan dehydration pathways, one water molecule which composed of a hydrogen atom from C3 and a hydroxyl group from C2 is the preferred pathway due to a lower activation energy and higher product stability. © 2012 Elsevier B.V. All rights reserved.

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A systematic theoretical study on the adsorption of steam and its thermal decomposition products on carbon both zigzag and armchair surface was performed to provide molecular-level understanding of the reaction activity of all these reactants in biomass steam gasification process. All the calculations were carried out using density functional theory (DFT) at the B3LYP/6-31+g(d,p) level. The structures of carbonaceous surfaces, all reactants and surface complexes were optimized and characterized. Based on the value of adsorption heat been obtained from the calculation, the activity of all reactants can be ordered as: O > O2 >H2 >H >OH >H2O for both zigzag and armchair surface, and the adsorption style is physisorption to water molecule and chemisorption to the other dissociated components.

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Microcystins (cyclic heptapeptides) produced by a number of freshwater cyanobacteria are a potential cause for concern in potable water supplies due to their acute and chronic toxicity. TiO2 photocatalysis is a promising technology for removal of these toxins from drinking water. It is, however, necessary to have a sufficient knowledge of how the catalyst materials cause the degradation of the toxins through the photocatalytic process. The present study reports microcystin degradation products of the photocatalytic oxidation by using a number of commercial TiO2 powder (P25, PC50, PC500 and UV100) and granular (KO1, KO3, TiCat-C, TiCat-S) materials, so aiding the mechanistic understanding of this process. Liquid chromatography-mass spectrometry analysis demonstrated that the major destruction pathway of microcystin for all the catalysts tested followed almost the same pathway, indicating the physical properties of the catalysts had little effects on the degradation pathway of microcystin-LR. 

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Microcystins (cyclic heptapeptides) are produced by a number of freshwater cyanobacteria and cause concern in potable water supplies due to their acute and chronic toxicity. The present study reports the structural characterization of the degradation products of the photocatalytic oxidation of microcystin-LR, so aiding the mechanistic understanding of this process. TiO2 photocatalysis is a promising technology for removal of these toxins from drinking water. However, before it can be adopted in any practical application it is necessary to have a sufficient knowledge of degradation byproducts and their potential toxicity. Liquid chromatography-mass spectrometry analysis demonstrated that the major destruction pathway of microcystin appears to be initiated via three mechanisms: UV irradiation, hydroxyl radical attack, and oxidation. UV irradiation caused geometrical isomerization of microcystin converting the (4E), (6E) of the Adda configuration to (4E), 6(Z) or 4(Z), 6(E). Hydroxyl radical attack on the conjugated diene structure of Adda moiety produced dihyroxylated products. Further oxidation cleaved the hydroxylated 4-5 and/or 6-7 bond of Adda to form aldehyde or ketone peptide residues, which then were oxidized into the corresponding carboxylic acids. Photocatalysis also hydrolyzed the peptide bond on the ring structure of microcystin to form linear structures although this appeared to be a minor pathway.

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In this paper we propose a graph stream clustering algorithm with a unied similarity measure on both structural and attribute properties of vertices, with each attribute being treated as a vertex. Unlike others, our approach does not require an input parameter for the number of clusters, instead, it dynamically creates new sketch-based clusters and periodically merges existing similar clusters. Experiments on two publicly available datasets reveal the advantages of our approach in detecting vertex clusters in the graph stream. We provide a detailed investigation into how parameters affect the algorithm performance. We also provide a quantitative evaluation and comparison with a well-known offline community detection algorithm which shows that our streaming algorithm can achieve comparable or better average cluster purity.