• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.81-89
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• 2014

In this paper, we propose SA hash algorithm to avoid upload identical files and design server system using proposed SA hash algorithm. Client to want to upload file examines the value of SA hash and if the same file is found in server system client use the existing file without upload. SA hash algorithm which is able to examine the identical-file divides original file into blocks of n bits. Original file's mod i bit and output hash value's i bit is calculated with XOR operation. It is SA hash algorithm's main routine to repeat the calculation with XOR until the end of original file. Using SA hash algorithm which is more efficient than MD5, SHA-1 and SHA-2, we can design server system to avoid uploading identical file and save storage capacity and upload-time of server system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.915-921
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• 2009

Lenstra-Lenstra-Lovasz (LLL) algorithm, which is one of the lattice reduction (LR) techniques, has been extensively used to obtain better bases of the channel matrix. In this paper, we jointly apply Seysen's lattice reduction Algorithm (SA), instead of LLL, with the conventional linear precoding algorithms. Since SA obtains more orthogonal lattice bases compared to those obtained by LLL, lattice reduction aided (LRA) precoding based on SA algorithm outperforms the LRA precoding with LLL. Simulation results demonstrate that a gain of 0.5dB at target BER of $10^{-5}$ is achieved when SA is used instead of LLL or the LR stage.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.28-36
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• 2009

Sequence-Pair(SP) model represents the topological relation between modules. In general, SP model based floorplanners search solutions using Simulated-Annealing(SA) algorithm. Several SA based floorplanning techniques using SP model have been published. To improve the performance of those techniques they tried to improve the speed for evaluation function for SP model, to find better scheduling methods and perturb functions for SA. In this paper we propose a two phase SA based algorithm. In the first phase, white space between modules is reduced by applying compaction technique to the floorplan obtained by an SP. From the compacted floorplan, the corresponding SP is determined. Solution space has been searched by changing the SP in the SA framework. When solutions converge to some threshold value, the first phase of the SA based search stops. Then using the typical SA based algorithm, ie, without using the compaction technique, the second phase of our algorithm continues to find optimal solutions. Experimental results with MCNC benchmark circuits show that how the proposed technique affects to the procedure for SA based floorplainning algorithm and that the results obtained by our technique is better than those obtained by existing SA-based algorithms.

• Korean Journal of Optics and Photonics
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• v.16 no.1
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• pp.43-49
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• 2005

In this paper, we propose a method for optimizing a computer-generated hologram(CGH) by combining the Tabu Search(TS) algorithm with the Simulated Annealing(SA) algorithm. By replacing an initial random pattern of the SA algorithm with an approximately ideal hologram pattern of the TS algorithm, we design a CGH which has high diffraction efficiency(DE). We compared the performance of the proposed algorithm with the SA algorithm using computer simulation and an optical experiment. As a result, we confirmed diffraction efficiency and uniformity to be enhanced in the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.468-475
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• 2003

In this Paper, we design an optimal binary phase computer generated hologram for Pattern generation using combined genetic algorithm and simulated annealing algorithm together. To design an optimal binary phase computer generated hologram, in searching process of the proposed method, the simple genetic algorithm is used to get an initial random transmittance function of simulated annealing algorithm. Computer simulation shows that the proposed algorithm has better performance than the genetic algorithm or simulated annealing algorithm of terms of diffraction efficiency

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.936-943
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• 2002

The Simulated Annealing (SA) algorithm has been successfully applied to various difficult combinatorial optimization problems. Since the performance of a SA algorithm, generally depends on values of the parameters, it is important to select the most appropriate parameter values. In this paper the SA algorithm is optimally designed for performance acceleration, by using the Taguchi method. Several test problems are solved via the SA algorithm optimally designed, and the solutions obtained are compared to solution results McMullen & Frazier(2000). The performance of the SA algorithm is evaluated in terms of solution quality and computation times. Computational results show that the proposed SA algorithm is effective and efficient in finding near-optimal solutions.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.179-190
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• 2010

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and incorporate the ability of SA to avoid being trapped in a local optimum. The APSO-SA algorithm efficiency is verified using some benchmark functions. This paper presents the application of APSO-SA to find the optimal location, type and size of flexible AC transmission system devices. Two types of FACTS devices, the thyristor controlled series capacitor (TCSC) and the static VAR compensator (SVC), are considered. The main objectives of the presented method are increasing the voltage stability index and over load factor, decreasing the cost of investment and total real power losses in the power system. In this regard, two cases are considered: single-type devices (same type of FACTS devices) and multi-type devices (combination of TCSC, SVC). Using the proposed method, the locations, type and sizes of FACTS devices are obtained to reach the optimal objective function. The APSO-SA is used to solve the above non.linear programming optimization problem for better accuracy and fast convergence and its results are compared with results of conventional PSO. The presented method expands the search space, improves performance and accelerates to the speed convergence, in comparison with the conventional PSO algorithm. The optimization results are compared with the standard PSO method. This comparison confirms the efficiency and validity of the proposed method. The proposed approach is examined and tested on IEEE 14 bus systems by MATLAB software. Numerical results demonstrate that the APSO-SA is fast and has a much lower computational cost.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.189-194
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• 2004

This paper proposes a Simulated Annealing(SA) algorithm for cluster-based Multicast Routing problems. Multicasting, the transmission of data to a group, can be solved from constructing multicast tree, that is. the whole network is partitioned to some clusters and the clusters are constructed by multicast tree. Multicast tree can be constructed by minimum-cost Steiner tree. In this paper, an SA algorithm is used in the minimum-cost Steiner tree. Especially, in SA, the cooling schedule is an important factor for the algorithm. Hence, in this paper, a cooling schedule is proposed for SA for multicast routing problems and analyzed the simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.642-648
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• 2009

In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2004.06a
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• pp.61-66
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• 2004

본 논문에서는 Tabu Search(TS) 알고리듬과 Simulated Anneal ing(SA) 알고리듬을 결합하여 향상된 성능을 갖는 컴퓨터 형성 홀로그램을 설계할 수 있는 방법을 제안하였다. 회절 효율의 향상을 위해 TS 알고리듬으로 이상적인 홀로그램에 근접한 패턴을 생성하고, 이를 SA 알고리듬에서 무작위로 구성된 초기 패턴과 대체하여 컴퓨터 형성 홀로그램을 설계하였다. 컴퓨터 모의 실험과 광 실험을 통하여 제안한 방법과 SA 알고리듬과의 성능을 비교한 결과 제안한 방법으로 재생한 영상이 SA 알고리듬을 이용하였을 때보다 향상된 회절 효율을 가지는 것을 확인 할 수 있었다.