A special method for construction of transitive orientations of the undirected graph G = (X; U) is proposed. The method uses an iterative procedure for factorization of graph G. Factorization procedure consists in replacing of a B-stable subgraph with a vertex. Transitive orientations are obtained by a polynomial time algorithm which is presented in the paper.

In this paper we present a new alternative noise reduction method for color images that were corrupted with additive Gaussian noise. We illustrate that color images have to be processed in a different way than most of the state-of-the-art methods. The proposed method consists of two sub-filters. The main concern of the first subfilter is to distinguish between local variations due to noise and ...

We present an algorithm which solves a convex program with faithfully convex (not necessarily differentiable) constraints. While finding a feasible starting point, the algorithm reduces the program to an equivalent program for which Slater's condition is satisfied. Included are algorithms for calculating various objects which have recently appeared in the literature. Stability of the algorithm ...

Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been ...

For a given set of data points lying on a low-dimensional manifold embedded in a high-dimensional space, the dimensionality reduction is to recover a low-dimensional parametrization from the data set. The recently developed Hessian Eigenmaps is a mathematically rigorous method that also sets a theoretical framework for the nonlinear dimensionality reduction problem. In this paper, we develop a ...

We develop a new dimension reduction method for large size ODE systems obtained from a discretization of partial differential equations of viscous single and multiphase fluid flow. The method is also applicable to other large size classical particle systems with negligibly small variations of particle concentration. We propose a new computational closure for mesoscale balance equations based on...

Categorical data clustering constitutes an important part of data mining; its relevance has recently drawn attention from several researchers. As a step in data mining, however, clustering encounters the problem of large amount of data to be processed. This article offers a solution for categorical clustering algorithms when working with high volumes of data by means of a method that summarizes...

We are often interested in finding out if a given predicate on states of a system can be satisfied in any or all of the systems reachable states. To determine this, one approach is to calculate the complete set of reachable states and evaluate the predicate on each of these states. To know which states we have already examined and which we have yet to examine—and thus knowing when we have exami...

This paper reports on the finite element analysis (FEA) of crosstalk in capacitive micromachined ultrasonic transducer (CMUT) arrays. Finite element calculations using a commercial package (LS-DYNA) were performed for an immersed 1-D CMUT array operating in the conventional and collapsed modes. LS-DYNA was used to model the crosstalk in CMUT arrays under specific voltage bias and excitation con...

Lattice reduction has a wide range of applications. In this paper, we first present a polynomial time Jacobi method for lattice basis reduction by modifying the condition for the Lagrange reduction and integrating the size reduction into the algorithm. We show that the complexity of the modified Jacobi algorithm is O(n5 logB), where n is the dimension of the lattice and B is the maximum length ...