• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.261-263
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• 2008

In power systems operation, state estimation takes an important role in security control. For the state estimation problem, the weighted least squares(WLS) method and the fast decoupled method have been widely used at present. But these algorithms have disadvantage of converging local optimal solution. In these days, a modern heuristic optimization method such as Particle Swarm Optimization(PSO), are introduced to overcome the problems of classical optimization. In this paper, we proposed particle swarm optimization (PSO) to search an optimal solution of state estimation in power systems. To demonstrate the usefulness of the proposed method, PSO algorithm was tested in the IEEE-57 bus systems. From the simulation results, we can find that the PSO algorithm is applicable for power system state estimation.

• Journal of the Korea Society of Computer and Information
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• v.3 no.3
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• pp.89-98
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• 1998

In this paper, we propose new image coding using wavelet transform. The new method constructs hierarchical bit plane and progressively transports each bit plane. The proposed algorithm not only supports multi-resolution, dividing original image into special band and various resolution but also reduces blocking effects that come into JPEG In encoding time, this algorithm considers each band characters and priority of transport order, and applies to fast search of image.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.795-796
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• 2008

H.264/AVC standard adopts multiple reference frames for motion estimation. This method improves coding efficiency, but it increases complexity of encoder. In this paper, we propose a algorithm that reduces the search range by using the correlation of motion vector. Consequently, motion estimation processing time is 47.5% when compared with standard of five reference frames, and SNR and bitrate are better than that of standard of three multi reference frames.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.298-299
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• 2002

WERC (Wakasa Wan Energy Research Center) has started the proton cancer therapy since June 2002. We use Hitachi 3D treatment planning (version 1.6) that can calculate the proton dose distribution by use of the pencil beam algorithm as well as the broad beam algorithm practically fast. This treatment planning software satisfies almost functions required in the proton therapy and includes some advanced techniques such as the 3D region glowing function that can search the target region three-dimensionally based on the CT-values. In this paper, we will introduce this planning system and present our evaluation from point of view of both clinical usage and QA.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.303-304
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• 2008

For the state estimation problem, the weighted least squares (WLS) method and the fast decoupled method are widely used at present. However, these algorithms can converge to local optimal solutions. Recently, modern heuristic optimization methods such as Particle Swarm Optimization (PSO) have been introduced to overcome the disadvantage of the classical optimization problem. However, heuristic optimization methods based on populations require a lengthy computing time to find an optimal solution. In this paper, we used PSO to search for the optimal solution of state estimation in power systems. To overcome the shortcoming of heuristic optimization methods, we proposed parallel processing of the PSO algorithm based on the PC cluster system. the proposed approach was tested with the IEEE-118 bus systems. From the simulation results, we found that the parallel PSO based on the PC cluster system can be applicable for power system state estimation.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.159-161
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• 1994

This paper presents a combined algorithm of simulated annealing and determinstic method which overcomes the defects of two methods and guarantees the fast convergence to the global optimum. This optimization method is applied to optimal design of Interior Permanent Magnet Synchronous Motor. And the result of the proposed algorithm is compared with that of simulated annealing alone.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.9-16
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• 2006

The Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. An algorithm has been developed for robots which explore the environment to measure the physical properties (dust in this paper). While the robot is moving, it measures the amount of dust and registers the value in the corresponding grid cell. The robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, simple gradient following is used. Robust estimation of the gradient using perturbation/correlation, which is very effective when analytical solution is not available, is described. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn't have to visit all the grid cells in the environment still providing fast and efficient sensing. The extended algorithm to coordinate multiple robots is presented with simulation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.258-264
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• 2018

This paper presents application of a differential search (DS) meta-heuristic optimization algorithm for optimal operation of a micro grid system. The DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. The micro grid system consists of a wind turbine, a diesel generator, a fuel cell, and a photovoltaic system. The wind turbine generator is modeled by considering the characteristics of variable output. Optimization is aimed at minimizing the cost function of the system, including fuel costs and maximizing fuel efficiency to generate electric power. The simulation was applied to a micro grid system only. This study applies the DS algorithm with excellence and efficiency in terms of coding simplicity, fast convergence speed, and accuracy in the optimal operation of micro grids based on renewable energy resources, and we compared its optimum value to other algorithms to prove its superiority.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.155-165
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• 2012

This paper suggests traveling salesman problem algorithm that have been unsolved problem with NP-Hard. The proposed algorithm is a heuristic with edge-swap method. The classical method finds the initial solution starts with first node and visits to mostly adjacent nodes then decides the traveling path. This paper selects minimum weight edge for each nodes, then perform Min-Min method that start from minimum weight edge among the selected edges and Min-Max method that starts from maximum weight edges among it. Then we decide tie initial solution to minimum path length between Min-Min and Min-Max method. To get the final optimal solution, we apply previous two-opt to initial solution. Also, we suggest extended 3-opt and 4-opt additionally. For the 7 actual experimental data, this algorithm can be get the optimal solutions of state-of-the-art with fast and correct.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1119-1128
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• 2013

In this paper, we propose an algorithm to detect and track the human face with a GPU-based high speed. Basically the detection algorithm uses the existing Adaboost algorithm but the search area is dramatically reduced by detecting movement and skin color region. Differently from detection process, tracking algorithm uses only depth information. Basically it uses a template matching method such that it searches a matched block to the template. Also, In order to fast track the face, it was computed in parallel using GPU about the template matching. Experimental results show that the GPU speed when compared with the CPU has been increased to up to 49 times.