• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.315-320
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• 2015

Proposal algorithm in this paper introduced cells, units of router group, for distributed processing of previous genetic algorithm. This paper presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was verified superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.397-400
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• 2016

In this paper, we propose an efficient algorithm for computing architecture for high-performance Inter Prediction SAD HEVC encoder. HEVC Motion Estimation (ME) of the Inter Prediction is a process for searching for the currently high prediction block PU and the correlation in the interpolated reference picture in order to remove temporal redundancy. ME algorithm uses full search(FS) or fast search algorithm. Full search technique has the guaranteed optimal results but has many disadvantages which include high calculation and operational time due to the motion prediction with respect to all candidate blocks in a given search area. Therefore, this paper proposes a new algorithm which reduces the computational complexity by reusing the SAD operation in full search to reduce the amount of calculation and computational time of the Inter Prediction. The proposed algorithm is applied to an HEVC standard software HM16.12. There was an improved operational time of 61% compared to the traditional full search algorithm, BDBitrate was decreased by 11.81% and BDPSNR increased by about 0.5%.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.843-846
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• 2000

An optical flow-based motion estimation algorithm is proposed for video coding. The algorithm uses block-matching motion estimation with an adaptive search region. The search region is computed from motion fields that are estimated based on the optical flow. The algorithm is based on the fact that true block-motion vectors have similar characteristics to optical flow vectors. Thereafter, the search region is computed using these optical flow vectors that include spatial relationships. In conventional block matching, the search region is fixed. In contrast, in the new method, the appropriate size and location of the search region are both decided by the proposed algorithm. The results obtained using test images show that the proposed algorithm can produce a significant improvement compared with previous block-matching algorithms.

• Structural Engineering and Mechanics
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• v.58 no.1
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• pp.163-179
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• 2016

The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.338-347
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• 2005

In this paper, a decimation-in-time search direction algorithm for displacement prediction of moving object is proposed. The initialization of the proposed algorithm for moving direction prediction is performed by detecting moving objects at sequential frames and by obtaining a moving angle and a moving distance. A moving direction of the moving object at current frame is obtained by applying the decimation-in-time search direction mask. The decimation-in-tine search direction mask is that the moving object is detected by thinning out frames among the sequential frames, and the moving direction of the moving object is predicted by the search mask which is decided by obtaining the moving angle of the moving object in the 8 directions. to examine the propriety of the proposed algorithm, velocities of a driving car are measured and tracked, and to evaluate the efficiency, the proposed algorithm is compared to the full search algorithm. The evaluated results show that the number of displacement search times is reduced up to 91.8$\%$ on the average in the proposed algorithm, and the processing time of the tracking is 32.1ms on the average.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.379-382
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• 1996

Evolution Strategy is used as an effective search algorithm in optimization problems and Sliding Mode Control is well known as a robust control algorithm. In this paper, we propose a Sliding Mode Control Method for robot manipulator using Evolution Strategy. Evolution Strategy is used to estimate Sliding Mode Control Parameters such as sliding surface gradient, continuous function boundary layer, unknown plant parameters and switching gain. Experimental results show the proposed control scheme has accurate and robust performances with effective search ability.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.158-168
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• 2001

We present a tabu search (TS) algorithm to minimize maximum lateness on a single machine in the presence of sequence dependent setup times and dynamic job arrivals. The TS algorithm starts with a feasible schedule generated by a modified ATCS (Apparent Tardiness Cost with Setups) rule, then through a series of search steps it improves the initial schedule. Results of extensive computational experiments show that the TS algorithm significantly outperforms a well-known RHP heuristic by Ovacik and Uzsoy, both on the solutions quality and the computation time. The performance advantage is particularly pronounced when there is high competition among jobs for machine capacity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.32-39
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• 2002

Vector quantization for image compression needs expensive encoding time to find the closest codeword to the input vector. This paper proposes a search algorithm for fast vector quantization encoding. Firstly, we derive a robust condition based on the efficient topological structure of the codebook to dramatically eliminate unnecessary matching operations from the search procedure. Then, we Propose a fast search algorithm using the elimination condition. Simulation results show that with little preprocessing and memory cost, the encoding time of the proposed algorithm is reduced significantly while the encoding quality remains the same with respect to the full search algorithm. It is also found that the Proposed algorithm outperforms the existing search algorithms.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.279-283
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• 2014

Recently, a topology algorithm based on the artificial bee colony algorithm (ABCA) has been proposed for static and dynamic topology optimization. From the results, the convergence rate of the algorithm was determined to be slightly slow. Therefore, we propose a new search method to improve the convergence rate of the algorithm using a chaotic map. We investigate the effect of the chaotic map on the convergence rate of the algorithm in static and dynamic topology optimization. The chaotic map has been applied to three cases, namely, employ bee search, onlooker bee search, and both employ bee as well as onlooker bee search steps. It is verified that the case in which the logistic function of the chaotic map is applied to both employ bee as well as onlooker bee search steps shows the best dynamic topology optimization, improved by 5.89% compared to ABCA. Therefore, it is expected that the proposed algorithm can effectively be applied to dynamic topology optimization to improve the convergence rate.

• IE interfaces
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• v.22 no.1
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• pp.10-16
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• 2009

In this paper, we propose an efficient search algorithm for finding an optimal schedule to minimize makespan, while avoiding deadlock situation in Flexible Manufacturing Systems (FMS) with finite capacity, in which each job needs to be processed in several job stages for completion. The proposed algorithm uses a modeling and control method based on Petri-net. Especially, we improve the efficiency of the search algorithm by using a priority rule and an efficient bounding function during the search procedure. The performance of the proposed algorithm is evaluated through a numerical experiment, showing that it holds considerable promise for providing an optimal solution efficiently comparing to past work.