• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.333-342
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• 2007

A nonsmooth PGD scheme for minimizing a nonsmooth convex function is presented. In the parallelization step of the algorithm, a method due to Pang, Han and Pangaraj (1991), [7], is employed to solve a subproblem for constructing search directions. The convergence analysis is given as well.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.285-286
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• 2008

In this paper, we propose adaptive search channel estimate algorithm. The proposed algorithm is modified LMS algorithm which has a variable step size and parallel convolution. In simulation result, a error estimate accuracy of the proposed algorithm is about -20 dB and general LMS algorithm is about 10 dB. The proposed algorithm is better error estimate accuracy than general LMS algorithm.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.373-376
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• 2003

This paper presents a image modification algorithm using the convergence camera model and the two perspective projection matrixes of the original cameras. Any pair of images can be transformed se that epipolar lines are parallel and horizontal in each image. The advantage of modification is that a 2-D search problem is reduced to a 1-D search problem. Reconstruction can be performed directly from the rectified images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.27-34
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• 1994

Block matching motion estimation is the most widely used method for motion compensated coding of image sequences. Based on a two dimensional systolic array, VLSI architecture and implementation of the full search block matching algorithm are described in this paper. The proposed architecture improves conventional array architecture by designing efficient processing elements that can control the data prodeuced by efficient search window division method. The advantages are that 1) it allows serial input to reduce pin counts for efficient composition of local memories but performs parallel processing. 2) It is flexible and can adjust to dimensional changes of search windows with simple control logic. 3) It has no idel time during the operation. 4) It can operate in real/time for low and main level in MPEG-2 standard. 5) It has modular and regular structure and thus is sutiable for VLSI implementation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.880-886
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• 2016

With lots of information occurring on the Internet, the search engine plays a role in gathering the scattered information on the Internet. Some search engines show not only search result pages including search keyword but also search result numbers of the keyword. The number of keyword searching result provided by the Google search engine can be utilized to identify overall trends for this search word on the internet. This paper is aimed designing and realizing the system which can efficiently manage the number of searching result provided by Google search engine. This paper proposed system operates by Web, and consist of search agent, storage node, and search node, manage keyword and search result, numbers, and executing search. The proposed system make the results such as search keywords, the number of searching, NGD(Normalized Google Distance) that is the distance between two keywords in Google area.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.2
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• pp.41-50
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• 2003

In this paper, nonlinear parallel structural analyses are introduced by using the parallel multifrontal solver and damage localization for 2D and 3D crack models is presented as the application of nonlinear parallel computation. The parallel algorithms related with nonliear reduce the amount of memory used is carried out because many variables should be utilized for this highly nonlinear damage analysis. Also, Riks' continuation method is parallelized to search the solution when strain softening occurs due to damage evolution. For damage localization problem, several computational models having up to around 1-million degree of freedoms are used. The parallel performance in this nonlinear parallel algorithm is shown through these examples and the local variation of damage at crack tip is compared among the models with different degree of freedoms.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.385-391
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• 2013

Big Data is data of big size which is not processed, collected, stored, searched, analyzed by the existing database management system. The parallel genetic algorithm using the Hadoop for BigData technology is easily realized by implementing GA(Genetic Algorithm) using MapReduce in the Hadoop Distribution System. The previous study that the genetic algorithm using MapReduce is proposed suitable transforming for the GA by MapReduce. However, they did not show good performance because of frequently occurring data input and output. In this paper, we proposed the MRPGA(MapReduce Parallel Genetic Algorithm) using improvement Map and Reduce process and the parallel processing characteristic of MapReduce. The optimal solution can be found by using the topology, migration of parallel genetic algorithm and local search algorithm. The convergence speed of the proposal method is 1.5 times faster than that of the existing MapReduce SGA, and is the optimal solution can be found quickly by the number of sub-generation iteration. In addition, the MRPGA is able to improve the processing and analysis performance of Big Data technology.

• Journal of computational fluids engineering
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• v.4 no.3
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• pp.52-62
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• 1999

The development of a parallelized aerodynamic simulation process involving moving bodies is presented. The implementation of this process is demonstrated using a fully systemized Chimera methodology for steady and unsteady problems. This methodology consists of a Chimera hole-cutting, a new cut-paste algorithm for optimal mesh interface generation and a two-step search method for donor cell identification. It is fully automated and requires minimal user input. All procedures of the Chimera technique are parallelized on the Cray T3E using the MPI library. Two and three-dimensional examples are chosen to demonstrate the effectiveness and parallel performance of this procedure.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.360-368
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• 1999

We consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, a hybrid genetic algorithm is proposed. The algorithm combines a genetic algorithm for global search and a heuristic for local optimization to improve the speed of evolution convergence. The genetic operators are developed such that parallel machines can be handled in an efficient and effective way. For local optimization, the adjacent pairwise interchange method is used. The proposed hybrid genetic algorithm is compared with two heuristics, the nearest setup time method and the maximum penalty method. Computational results for a series of randomly generated problems demonstrate that the proposed algorithm outperforms the two heuristics.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.64-67
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• 2017

Applying concurrent structure and parallel processing are a common issue for these day's programs. In this research, Dynamic Programming is used to compare the parallel performance of Go language and Intel C++ Thread Building Blocks. The experiment was performed on 4 core machine and its result contains execution time under Simultaneous Multi-Threading environment. Static Optimal Binary Search Tree was used as an example. From the result, the speed-up of Go was higher than the number of cores, and that of TBB was close to it. TBB performed better in general, but for larger scale, Go was partially faster than the other.