509 research outputs found

    Cutting Plane Algorithms for 0-1 Programming Based on Cardinality Cuts

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    Cataloged from PDF version of article.We present new valid inequalities for 0-1 programming problems that work in similar ways to well known cover inequalities. Discussion and analysis of these cuts is followed by their revision and use in integer programming as a new generation of cuts that excludes not only portions of polyhedra containing noninteger points, also parts with some integer points that have been explored in search of an optimal solution. Our computational experimentations demonstrate that this new approach has significant potential for solving large scale integer programming problems. 2010 Elsevier B.V. All rights reserved

    An efficient and accurate technique for the incident-wave excitations in the FDTD method

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    Cataloged from PDF version of article.An efficient technique to improve the accuracy of the finite-difference time-domain (FDTD) solutions employing incident-wave excitations is developed. In the separate-field formulation of the FDTD method, any incident wave may be efficiently introduced to the three-dimensional (3-D) computational domain by interpolating from a one-dimensional (1-D) incident-field array (IFA), which is a 1-D FDTD grid simulating the propagation of the incident wave. By considering the FDTD computational domain as a sampled system and the interpolation operation as a decimation process, signal-processing techniques are used to identify and ameliorate the errors due to aliasing. The reduction in the error is demonstrated for various cases. This technique can be used for the excitation of the FDTD grid by any incident wave. A fast technique is used to extract the amplitude and the phase of a sampled sinusoidal signal

    Dynamic point-region quadtrees for particle simulations

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    Cataloged from PDF version of article.We propose an algorithm for dynamically updating point-region (PR) quadtrees. Our algorithm is optimized for simultaneous update of data points comprising a quadtree. The intended application area focuses on simulating continuum phenomena, such as crowds, fluids, and smoke. We minimize the number of tree updates by making use of small changes in the positions of data points. We compare the efficiency of the proposed algorithm with two other approaches for updating a quadtree. One of these techniques creates the tree from scratch at each time-step. The second technique subsequently deletes a data point from the tree and reinserts it in its updated position. We achieve significant performance gains with our method in both cases. (C) 2012 Elsevier Inc. All rights reserved

    Extraction of Saponins from Soapnut (Sapindus Mukorossi) and Their Antimicrobial Properties

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    In this study optimization of extraction conditions for saponin from Sapindus mukorossi was investigated. Results showed that polarity of the extraction solvent affects the yield percentage of the extraction process. Best yield percentage was obtained as 78.1 % at 1:10 solid-liquid ratio in aqueous ethanol solution (50% v/v). The antimicrobial properties of extracts containing saponins were investigated for different microorganisms. Minimum inhibition concentrations of extract were obtained against Escherichia coli, Staphylococcus aureus and Candida albicans. Minimum inhibition concentrations (MIC) of saponin extract ranged between 12.5 mg/mL to 25 mg/mL.nbs

    Emergency crowd simulation for outdoor environments

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    Cataloged from PDF version of article.We simulate virtual crowds in emergency situations caused by an incident, such as a fire, an explosion, or a terrorist attack. We use a continuum dynamics-based approach to simulate the escaping crowd, which produces more efficient simulations than the agent-based approaches. Only the close proximity of the incident region, which includes the crowd affected by the incident, is simulated. We use a model-based rendering approach where a polygonal mesh is rendered for each agent according to the agent's skeletal motion. To speed up the animation and visualization, we employ an offline occlusion culling technique. We animate and render a pedestrian model only if it is visible according to the static visibility information computed. In the pre-processing stage, the navigable area is decomposed into a grid of cells and the from-region visibility of these cells is computed with the help of hardware occlusion queries. (C) 2009 Elsevier Ltd. All rights reserved

    Motion-compensated prediction based algorithm for medical image sequence compression

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    Cataloged from PDF version of article.A method for irreversible compression of medical image sequences is described. The method relies on discrete cosine transform and motion-compensated prediction to reduce intra- and inter-frame redundancies in medical image sequences. Simulation examples are presented

    Wavelet transforms of meteorological parameters and gravity waves

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    The main purpose of this paper is to analyze some characteristics of gravity waves (GWs), and seasonal variations of atmospheric waves over Istanbul by using wavelet techniques. Daily radiosonda data of Istanbul in the troposphere and lower stratosphere (1000hPa-30hPa) between 1993 and 1997 have been considered. Wavelet analysis based on a computer simulation of data is generally close to the real data when Daubechies wavelet series are used. Daily, monthly, seasonal and annual variations of pressure heights, air temperature and deviations from mean values have been analyzed. Variations show the effects of gravity waves for different pressure levels in the troposphere. These waves lead to the meso-scale wave-form structures in spring, autumn and winter. As a result of this study, wavelet series and transforms for data construction, definition of some discontinuities and the local effects on the signal have been compared with the results of previous studies. The most similar structure between temperature, turbulence parameters and geo-potential height deviations has been defined at the 500-hPa pressure level

    Structured least squares with bounded data uncertainties

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    In many signal processing applications the core problem reduces to a linear system of equations. Coefficient matrix uncertainties create a significant challenge in obtaining reliable solutions. In this paper, we present a novel formulation for solving a system of noise contaminated linear equations while preserving the structure of the coefficient matrix. The proposed method has advantages over the known Structured Total Least Squares (STLS) techniques in utilizing additional information about the uncertainties and robustness in ill-posed problems. Numerical comparisons are given to illustrate these advantages in two applications: signal restoration problem with an uncertain model and frequency estimation of multiple sinusoids embedded in white noise. ©2009 IEEE
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