PRCS is an attempt to provide a version-control system for collections of files with a simple operational model, a clean user interface, and high performance. PRCS is characterized by the use of project description fi...
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We reprove the countable splitting lemma by adapting Nawrotzki’s algorithm which produces a sequence that converges to a solution. Our algorithm combines Nawrotzki’s approach with taking finite cuts. It is construct...
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An appropriate and understandable data visualization is a key feature for the usability of a data mining system. The proper visualization methods for data exploration increase the whole acceptability of the system and...
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During the last few years new functionalities of RNA have been discovered, renewing the need for computational tools for their analysis. To this respect, multiple sequence alignment is an essential step in finding str...
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Existing approaches for solving the lattice Boltzmann equations with finite difference methods are explicit and semi-implicit;both have certain stability constraints on the time step size. In this work, a fully implic...
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The classical Gomory-Hu algorithm aims for finding, for given input flows, a network topology for data transmission and bandwidth of its channels which are optimized subject to minimal bandwidth criteria. In practice,...
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We propose a fully discrete fast Fourier-Galerkin method for solving an integral equation of the first kind with a logarithmic kernel on a smooth open arc,which is a reformulation of the Dirichlet problem of the Lapla...
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We propose a fully discrete fast Fourier-Galerkin method for solving an integral equation of the first kind with a logarithmic kernel on a smooth open arc,which is a reformulation of the Dirichlet problem of the Laplace equation in the *** optimal convergence order and quasi-linear complexity order of the proposed method are established.A precondition is *** this method with an efficient numerical integration algorithm for computing the single-layer potential defined on an open arc,we obtain the solution of the Dirichlet problem on a smooth open arc in the *** examples are presented to confirm the theoretical estimates and to demonstrate the efficiency and accuracy of the proposed method.
Maintaining data mining accuracy on distorted datasets is an important issue in privacy preserving data mining. Using matrix approximation, we propose several efficient and flexible techniques to address this issue, a...
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Maintaining data mining accuracy on distorted datasets is an important issue in privacy preserving data mining. Using matrix approximation, we propose several efficient and flexible techniques to address this issue, and utilize unique characteristics of matrix factorization to maintain data pattern. We use the support vector machine classification to compare accuracy maintenance after data distortion by different methods. With better performance than some classical data perturbation approaches, nonnegative matrix factorization and singular value decomposition are considered to be promising techniques for privacy preserving data mining. Experimental results demonstrate that mining accuracy on the distorted data used these methods is almost as good as that on the original data, with added property of privacy preservation. It indicates that the matrix factorization-based data distortion schemes perturb only confidential attributes to meet privacy requirements while preserving general data pattern for knowledge extraction.
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