• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.235-238
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• 1995

In this paper, we propose an effective coding method of the angiography by using the scalable structure in the frequency domain for MPACS(Medical Picture Archiving and Communication System). We employed the subband decomposition method and MPEG-2 system which is the international standard coding method of the general moving picture. After the subband decomposition is applied to split an input image into 4 bands in the spatial frequency domain, the motion compensated DPCM coding method of MPEG-2 is carried out for each subband. As a result, an easily controllable coding Structure is accomplished by composing the compound hit stream for each subband group. Follows are the simulation results of the proposed sheme for the angiography. A scalable structure which can be easily controlled for a loss of transmission or the band limit can be accomplisbed in the MPEG-2 stucture by the subband decomposition minimizing the side information. And by reducing the search area of the motion vector between -4 and 3, the processing speed of a codec is enhanced by more than two times without a loss of the picture quality compare with the conventional DCT coefficients decompositon method. And the processing speed is considerably improved in the case of the parallel construction of each subband in the hardware.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.300-309
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• 2003

The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.

• Journal of IKEEE
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• v.21 no.1
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• pp.100-103
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• 2017

Motion estimation occupies the largest computation in the video compression. Multiple processing elements are often exploited in parallel to meet processing speed. More processing elements increase processing speed, but they also increase hardware area. therefore, it is important to optimize the number of processing element. HEVC (high efficiency video coding) usually exploits multi-stage motion estimation algorithms for low computation and high performance. Since the number and position of search points are different in each stage, the utilization of the processing elements is not always 100% and the utilization is quite different with the number of processing elements. In this paper, the optimizing method is proposed on the number of processing elements. It finds out the optimal number of the processing elements for the given multi-stage motion estimation algorithm by calculating utilization and execution cycle of the processing elements.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.23-34
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• 2002

This paper proposes a new neuro-fuzzy system that is fast trained by evolution strategy and describes application results of the proposed system to nonlinear system identification to show its usefulness. As training methods of neuro-fuzzy systems, modified error back-propagation algorithms and genetic algorithms have been used so far. However, the former has some drawbacks such as long training time, falling to local optimum, and experimental selecting of learning rates and the latter has difficulty in precise searching solutions because genetic algorithms represents solutions as genotype individuals. The evolution strategy we used can do precise search because its individuals are represented as phenotype real values, it seldom falls into a local optimum, and its training speed is faster than error back-propagation algorithms. We apply our neuro-fuzzy systems to nonlinear system identification. It was found from experiments that training speed is fast and the training results were considerably good.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.307-312
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• 2015

ARPA(Automatic Radar Plotting Aid) is a device to calculate CPA(closest point of approach)/TCPA(time of CPA), true course and speed of targets by vector operation of relative courses and speeds. The purpose of this study is to develop target acquisition and tracking technology for ARPA Radar implementation. After examining the previous studies, applicable algorithms and technologies were developed to be combined and basic ARPA functions were developed as a result. As for main research contents, the sequential image processing technology such as combination of grayscale conversion, gaussian smoothing, binary image conversion and labeling was deviced to achieve a proper target acquisition, and the NNS(Nearest Neighbor Search) algorithm was appllied to identify which target came from the previous image and finally Kalman Filter was used to calculate true course and speed of targets as an analysis of target behavior. Also all technologies stated above were implemented as a SW program and installed onboard, and verified the basic ARPA functions to be operable in practical use through onboard test.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.123-134
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• 2004

In this paper a high speed architecture of the RC4 stream cipher is proposed and its FPGA implementation is presented. Compared to the conventional RC4 designs which have long initialization operation or use double or triple S-arrays to reduce latency delay due to S-array initialization phase, the proposed architecture for RC4 stream cipher eliminates the S-array initialization operation using 256-bit valid entry scheme and supports 40/128-bit key lengths with efficient modular arithmetic hardware. The proposed RC4 stream cipher is implemented using Xilinx XCV1000E-6H240C FPGA device. The designed RC4 stream cipher has about a throughput of 106 Mbits/sec at 40 MHz clock and thus can be applicable to WEP processor and RC4 key search processor.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2690-2695
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• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.663-668
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• 2010

In driving a car, turns such as left turns, right turns, or u-turns, make the speed of the car decrease considerably. A more straight path, therefore, is probably faster to arrive at the destination than zig-zag path with same distance. In this paper, we have newly proposed the turn heuristic to make more straight path. The path navigation algorithm with turn heuristic(called as TA* algorithm) could enhance the straightness of a path by putting the turned-edges to the turn cost. It requires higher cost to use TA* algorithm than traditional A* algorithm because the straight-edge first searching have increased the search space. We have improved the TA* algorithm into the variable TA* algorithm(called as VTA* algorithm) which adopt the turn-heuristic during the a portion of the whole path.

• MALSORI
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• no.50
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• pp.51-69
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• 2004

In this paper, we present a one-pass semi-dynamic network decoding framework that inherits both advantages of fast decoding speed from static network decoders and memory efficiency from dynamic network decoders. Our method is based on the novel language model network representation that is essentially of finite state machine (FSM). The static network derived from the language model network [1][2] is partitioned into smaller subnetworks which are static by nature or self-structured. The whole network is dynamically managed so that those subnetworks required for decoding are cached in memory. The network is near-minimized by applying the tail-sharing algorithm. Our decoder is evaluated on the 25k-word Korean broadcast news transcription task. In case of the search network itself, the network is reduced by 73.4% from the tail-sharing algorithm. Compared with the equivalent static network decoder, the semi-dynamic network decoder has increased at most 6% in decoding time while it can be flexibly adapted to the various memory configurations, giving the minimal usage of 37.6% of the complete network size.