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Titlebook: Computational Science -- ICCS 2005; 5th International Co Vaidy S. Sunderam,Geert Dick Albada,Jack J. Dongar Conference proceedings 2005 Spr

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31#
發(fā)表于 2025-3-26 23:11:43 | 只看該作者
Sliced-Time Computations with Re-scaling for Blowing-Up Solutions to Initial Value Differential Equawing-up in a finite time. For that purpose, we introduce the concept of “sliced-time computations”, whereby, a sequence of time intervals (slices) {[.., ..]| .?≥?1} is defined on the basis of a change of variables (re-scaling), allowing the generation of computational models that share symbolically
32#
發(fā)表于 2025-3-27 02:19:29 | 只看該作者
Application of the Pseudo-Transient Technique to a Real-World Unsaturated Flow Groundwater Problemure of the governing equations. This problem is even more challenging when a steady-state solution is needed. This paper describes the implementation of a pseudo-transient technique to drive the solution to steady-state and gives results for a real-world problem. The application discussed in this pa
33#
發(fā)表于 2025-3-27 07:15:41 | 只看該作者
34#
發(fā)表于 2025-3-27 10:41:08 | 只看該作者
Predictor-Corrector Preconditioned Newton-Krylov Method For Cavity Flowhe method: employing the predictor-corrector method as preconditioner, and solving the equations without the preconditioner. The standard driven cavity flow is selected as the test problem to demonstrate the efficiency and the reliability of the present preconditioned method. It is found that the Ne
35#
發(fā)表于 2025-3-27 15:51:38 | 只看該作者
Vectorized Sparse Matrix Multiply for Compressed Row Storage Formatmat. Unlike the vectorizable jagged diagonal format (JAD), this algorithm requires no data rearrangement and can be easily adapted to a sophisticated library framework such as PETSc. Numerical experiments on the Cray X1 show an order of magnitude improvement over the non-vectorized algorithm.
36#
發(fā)表于 2025-3-27 21:00:54 | 只看該作者
37#
發(fā)表于 2025-3-27 22:46:56 | 只看該作者
38#
發(fā)表于 2025-3-28 05:36:49 | 只看該作者
39#
發(fā)表于 2025-3-28 09:19:20 | 只看該作者
40#
發(fā)表于 2025-3-28 12:20:35 | 只看該作者
Occlusion Activity Detection Algorithm Using Kalman Filter for Detecting Occluded Multiple Objectsetween them, a simultaneous feature based tracking of multiple objects using tracking filters fails. To estimate feature vectors such as location, color, velocity, and acceleration of a target are critical factors that affect the tracking performance and reliability. To resolve this problem, the occ
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