67 resultados para graph anonymization
em Chinese Academy of Sciences Institutional Repositories Grid Portal
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Knowledge management is a critical issue for the next-generation web application, because the next-generation web is becoming a semantic web, a knowledge-intensive network. XML Topic Map (XTM), a new standard, is appearing in this field as one of the structures for the semantic web. It organizes information in a way that can be optimized for navigation. In this paper, a new set of hyper-graph operations on XTM (HyO-XTM) is proposed to manage the distributed knowledge resources.HyO-XTM is based on the XTM hyper-graph model. It is well applied upon XTM to simplify the workload of knowledge management.The application of the XTM hyper-graph operations is demonstrated by the knowledge management system of a consulting firm. HyO-XTM shows the potential to lead the knowledge management to the next-generation web.
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ACM SIGIR; ACM SIGWEB
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IN this paper, the engraving process with Q-Switched Nd:YAG laser is investigated. High power density is the pre- requisition to vapor materials, and high repetition rate makes the engraving process highly efficient. An acousto- optic Q-Switch is applied in the cavity of CW 200 W Nd:YAG laser to achieve the high peak power density and the high pulse repetition rate. Different shape craters are formed in a patterned structure on the material surface when the laser beam irradiates on it by controlling power density, pulse repetition rate, pulse quantity and pulse interval. In addition, assisting oxygen gas is used for not only improving combustion to deepen the craters but also removing the plasma that generated on the top of craters. Off-focus length classified as negative and positive has a substantial effect on crater diameters. According to the message of rotating angle positions from material to be engraved and the information of graph pixels from computer, a special graph is imparted to the material by integrating the Q- Switched Nd:YAG laser with the computer graph manipulation and the numerically controlled worktable. The crater diameter depends on laser beam divergence and laser focal length. The crater diameter changes from 50 micrometers to 300 micrometers , and the maximum of crater depth reaches one millimeter.
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Features of homologous relationship of proteins can provide us a general picture of protein universe, assist protein design and analysis, and further our comprehension of the evolution of organisms. Here we carried Out a Study of the evolution Of protein molecules by investigating homologous relationships among residue segments. The motive was to identify detailed topological features of homologous relationships for short residue segments in the whole protein universe. Based on the data of a large number of non-redundant Proteins, the universe of non-membrane polypeptide was analyzed by considering both residue mutations and structural conservation. By connecting homologous segments with edges, we obtained a homologous relationship network of the whole universe of short residue segments, which we named the graph of polypeptide relationships (GPR). Since the network is extremely complicated for topological transitions, to obtain an in-depth understanding, only subgraphs composed of vital nodes of the GPR were analyzed. Such analysis of vital subgraphs of the GPR revealed a donut-shaped fingerprint. Utilization of this topological feature revealed the switch sites (where the beginning of exposure Of previously hidden "hot spots" of fibril-forming happens, in consequence a further opportunity for protein aggregation is Provided; 188-202) of the conformational conversion of the normal alpha-helix-rich prion protein PrPC to the beta-sheet-rich PrPSc that is thought to be responsible for a group of fatal neurodegenerative diseases, transmissible spongiform encephalopathies. Efforts in analyzing other proteins related to various conformational diseases are also introduced. (C) 2009 Elsevier Ltd. All rights reserved.
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Network biology is conceptualized as an interdisciplinary field, lying at the intersection among graph theory, statistical mechanics and biology. Great efforts have been made to promote the concept of network biology and its various applications in life s
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In this paper, we proposed a method of classification for viruses' complete genomes based on graph geometrical theory in order to viruses classification. Firstly, a model of triangular geometrical graph was put forward, and then constructed feature-space-samples-graphs for classes of viruses' complete genomes in feature space after feature extraction and normalization. Finally, we studied an algorithm for classification of viruses' complete genomes based on feature-space-samples-graphs. Compared with the BLAST algorithm, experiments prove its efficiency.
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In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.
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A detailed study of the characteristics of undoped GaN films, grown on either vicinal or nominal flat SiC (0001) substrates by molecular beam epitaxy, has been carried out using photoluminescence and Raman scattering techniques. The I I K photoluminescence spectra of the GaN film grown on the vicinal SiC (0001) substrate show a strong and sharp near-bandgap peak (full width at half maximum (FWHM) similar to 16 meV). This feature contrasts with that of the GaN film grown on the nominal flat SiC (0001) substrate where the I I K photoluminescence spectra exhibit the near-bandgap peak (FWHM similar to 25 meV) and the intensity is approximately seven times weaker than that of the vicinal film sample. The redshift of the near-bandgap peak associated with excitons bound to shallow donors is related to the stress caused by both the lattice mismatch and the thermal expansion coefficient difference between GaN and SiC substrates. The measured thermal activation energy of the shallow donor of 33.4 meV is determined by using an Arrhenius plot of the near-bandgap luminescence versus I IT from the slope of the graph at high temperature. The temperature dependence of the FWHM of the near-bandgap luminescence has also been studied. The Raman scattering measurements from the vicinal film reveal that the E-2 phonon peak is strengthened and the A(1)(LO) phonon peak is shifted towards the low-frequency side with enhanced intensity, in comparison to that from the nominal flat film, suggesting a reduction in the density of defects and a lower free carrier concentration in the vicinal GaN film.
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A novel analog-computation system using a quantum-dot cell network is proposed to solve complex problems. Analog computation is a promising method for solving a mathematical problem by using a physical system analogous to the problem. We designed a novel quantum-dot cell consisting of three-stacked. quantum dots and constructed a cell network utilizing the nearest-neighbor interactions between the cells. We then mapped a graph 3-colorability problem onto the network so that the single-electron configuration of the network in the ground state corresponded to one of the solutions. We calculated the ground state of the cell network and found solutions to the problems. The results demonstrate that analog computation is a promising approach for solving complex problems.
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In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.