• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.977-985
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• 2009

This paper proposes a real-time algorithm for tracking the fast moving human body. Although Iterative closest point (ICP) algorithm is suitable for real-time tracking due to its efficiency and low computational complexity, ICP often fails to converge when the human body moves fast because the closest point may be mistakenly selected and trapped in a local minimum. To overcome such limitation, we combine a particle filter based on a motion history information with the ICP. The proposed human body motion tracking algorithm reduces the search space for each limb by employing a hierarchical tree structure, and enables tracking of the fast moving human bodies by using the motion prediction based on the motion history. Experimental results show that the proposed human body motion tracking provides accurate tracking performance and fast convergence rate.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.214-217
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• 2000

Many researches have been performed for human recognition and coding schemes recently. For this situation, we propose an automatic facial feature extraction algorithm. There are two main steps: the face region evaluation from original background image such as office, and the facial feature extraction from the evaluated face region. In the face evaluation, Genetic Algorithm is adopted to search face region in background easily such as office and household in the first step, and Template Matching Method is used to extract the facial feature in the second step. We can extract facial feature more fast and exact by using over the proposed Algorithm.

• Advances in Energy Research
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• v.4 no.2
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• pp.163-176
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• 2016

Rapid depletion of fossil based oil, coal and gas reserves and its greater demand day by day necessitates the search for other alternatives. Severe environmental impacts caused by the fossil fire based power plants and the escalating fuel costs are the major challenges faced by the electricity supply industry. Integration of Distributed Generators (DG) especially, wind and solar systems to the grid has been steadily increasing due to the concern of clean environment. This paper focuses on a new simple and fast load flow algorithm named Backward Forward Sweep Algorithm (BFSA) for finding the voltage profile and power losses with the integration of various sizes of DG at different locations. Genetic Algorithm (GA) based BFSA is adopted in finding the optimal location and sizing of DG to attain an improved voltage profile and considerable reduced power loss. Simulation results show that the proposed algorithm is more efficient in finding the optimal location and sizing of DG in 15-bus radial distribution system (RDS).The authenticity of the placement of optimized DG is assured with other DG placement techniques.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.99-105
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• 2018

k-Nearest neighbor join (k-NN Join) is a computationally intensive algorithm that is designed to find k-nearest neighbors from a dataset S for every object in another dataset R. Most related studies on k-NN Join are based on single-computer operations. As the data dimensions and data volume increase, running the k-NN Join algorithm on a single computer cannot generate results quickly. To solve this scalability problem, we introduce the locality-sensitive hashing (LSH) k-NN Join algorithm implemented in Spark, an approach for high-dimensional big data. LSH is used to map similar data onto the same bucket, which can reduce the data search scope. In order to achieve parallel implementation of the algorithm on multiple computers, the Spark framework is used to accelerate the computation of distances between objects in a cluster. Results show that our proposed approach is fast and accurate for high-dimensional and big data.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.67-76
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• 1996

In the present paper we propose two new improved iterative restoration algorithms. One is to accelerate convergence of the steepest descent method using the improved search directions, while the other accelerates convergence by using preconditioners. It is also shown that the proposed preconditioned algorithm can accelerate iteration-adaptive iterative image restoration algorithm. The preconditioner in the proposed algorithm can be implemented by using the FIR filter structure, so it can be applied to practical application with manageable amount of computation. Experimental results of the proposed methods show good perfomance improvement in the sense of both convergence speed and quality of the restored image. Although the proposed methods cannot be directly included in spatially-adaptive restoration, they can be used as pre-processing for iteration-adaptive algorithms.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.12
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• pp.48-54
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• 2010

This paper presents a high-performance architecture of integer-pel motion estimation circuit for H.264 video CODEC. Full search algorithm guarantees the best results by examining all candidate blocks. However, the full search algorithm requires a huge amount of computation and data. Many fast search algorithms have been proposed to reduce the computational efforts. The disadvantage of these algorithms is that data access from or to memory is very irregular and data reuse is difficult. In this paper, we propose an efficient integer-pixel motion estimation algorithm and the circuit architecture to improve the processing speed and reduce the external memory bandwidth. The proposed circuit supports seven kinds of variable block sizes and generates 41 motion vectors. We described the proposed high-performance motion estimation circuit at R1L and verified its operation on FPGA board. The circuit synthesized by using l30nm CMOS standard cell library processes 139.8 1080HD ($1,920{\times}1,088$) image frames per second and supports up to H.264 level 5.1.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.64-70
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• 2011

In an H.264/AVC video encoder, the motion estimation at fractional pixel accuracy improves a coding efficiency and image quality. However, it requires additional computation overheads for fractional search and interpolation, and thus, reducing the computation complexity of fractional search becomes more important. This paper proposes a Pixel Re-composition Fractional Motion Estimation (PRFME) algorithm for an H.264/AVC video encoder. Fractional Motion Estimation performs interpolation for the overlapped pixels which increases the computational complexity. PRFME can reduce the computational complexity by eliminating the overlapped pixel interpolation. Compared with the fast full search, the proposed algorithm can reduce 18.1% of computational complexity, meanwhile, the maximum PSNR degradation is less than 0.067dB. Therefore, the proposed PRFME algorithm is quite suitable for mobile applications requiring low power and complexity.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.255-261
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• 2008

RFID(Radio Frequency IDentification) is a technology that automatically identifies objects containing the electronic tags by using radio frequency. In RFID system, the reader needs the anti collision algorithm for fast identifring all of the tags in the interrogation zone. This Paper proposes the tree based TPAE(Tag Prediction Algorithm using Extra bit) algorithm to arbitrate the tag collision. The proposed algorithm can identify tags without identifring all the bits in the tag ID. The reader uses the extra bit which is added to the tag ID and if there are two collided bits or multiple collided bits, it checks the extra bit and grasps the tag IDs concurrently. In the experiment, the proposed algorithm had about 50% less query iterations than query tree algorithm and binary search algorithm regardless of the number of tags and tag ID lengths.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.656-661
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• 2013

In Guided Scrambling (GS) encoding for the holographic storage, after scrambling augmented source word into codeword, the best codeword satisfying modulation constraint is determined. Modulation constraints considered in this paper are strength which is the minimum number of transition between '0' and '1' in each row and column of codeword array and the symbol balancedness of codeword array. In this paper, we show that GS encoding procedure can be formulated as an integer programming model and develop a fast neighborhood search heuristic for fast computation of control bits. In the simulation, we compared the performance of heuristic algorithm with the integer programming model for various array and control bit size combinations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2525-2532
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• 2009

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.