• Journal of the Optical Society of Korea
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• 제20권1호
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• pp.13-21
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• 2016

Since the direct-gradient (DG) method uses the Shack-Hartmann wave front sensor (SH-WFS), based on the phase-conjugation principle, for atmospheric compensation in free-space optical (FSO) communication, it cannot effectively correct high-order aberrations. While the stochastic parallel gradient descent (SPGD) can compensate the distorted wave front, it requires more calculations, which is sometimes undesirable for an FSO system. A hybrid compensation (HC) method is proposed by properly using the DG method and SPGD algorithm to improve the performance of FSO communication. Simulations show that this method can well compensate wave-front aberrations and upgrade the coupling efficiency with few computations, preferable correction results, and rapid convergence rate.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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• pp.125-128
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• 2002

This paper is about a high-speed MAC (multiplier and accumulator) design applying radix-4 and radix-8 Booth's algorithm at the same time. The optimized hybrid radix design for high speed MAC has taken advantage of both a radix-4 and a radix-8 architectures. A radix-4 architecture meets high-speed, but it takes much more power and chip area than a radix-8 architecture. A radix-8 architecture needs less power and chip area than the other, but it has a bottleneck of generating three times the multiplicand problem. An optimized hybrid architecture performs tile radix-4 multiplication partially in parallel with the generation of three times the multiplicand for use of tile radix-8 multiplication. It reduces the concerned bit width of multiplier in radix-8 multiplication.

• 한국자동차공학회논문집
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• 제10권5호
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• pp.121-128
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• 2002

In this paper, the fuel economy of plug-in type hybrid electric vehicle is investigated through simulation. For the simulation study, 2 shaft type parallel hybrid powertrain is chosen and its operation modes are described. The operation algorithm which yields operation points of minimal fuel cost is suggested. Dynamic model fur operation of HEV and simulation procedure is described. Simulation results of fuel economy is compared to non plug-in type HEV as well as conventional vehicle. With total driving distance of 37km and full usage of 2kwh of electric energy stored in battery pack, plug-in type HEV shows 28-30% improved fuel economy compared to non plug-in type HEV and 86-93% improved fuel economy compared to conventional vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5972-5989
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• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.120-122
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• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.159-165
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• 2002

진화연산에는 교배, 돌연변이, 경쟁, 선택이 있다. 이러한 과정 중에서 선택은 새로운 개체를 생산하지는 않지만, 모든 해중에서 최적의 해가 될만한 해는 선택하고, 그러지 않은 해는 버리는 판단의 역할을 한다. 따라서 아무리 좋은 해를 만들었다고 해도, 취사 선택을 잘못하면, 최적의 해를 찾지 못하거나, 또 많은 시간이 소요되게 된다. 따라서 본 논문에서는 stochastic한 성질을 갖고 있는 Tournament selection에 Local selection개념을 도입하여, 지역 해에서 벗어나 전역 해를 찾는데, 개선이 될 수 있도록 하였고 Fast Evolutionary Programming의 mutation과정을 개선하고, Genetic Algorithm의 연산자인 crossover와 mutation을 도입하여 Parallel search로 지역 해에서 벗어나 전역 해를 찾는 하이브리드 알고리즘을 제안하고자 한다.

• 해양환경안전학회지
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• 제8권1호
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• pp.127-137
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• 2002

This paper deals with developing a Web-based Solver NRO(Network Reliability Optimizer) for solving three classes of reliability redundancy optimization problems which are generated in series systems. parallel systems and complex systems. Inputs of NRO consisted in four parts. that is, user authentication. system selection. input data and confirmation. After processing of inputs through internet, NRO provides conveniently the optimal solutions for the given problems on the Web-site. To alleviate the risks of being trapped in a local optimum, HH(Hybrid-Heuristic) algorithm is incorporated in NRO for solving the given three classes of problems, and moderately combined GA(Genetic Algorithm) with the modified SA(Simulated Annealing) algorithm.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.193-198
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• 2022

Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

• International Journal of Automotive Technology
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• 제5권3호
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• pp.201-208
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• 2004

Response characteristics of the CVT system for a parallel hybrid electric vehicle (HEV) are investigated. From the experiment, CVT ratio control algorithm for the optimal engine operation is obtained. To investigate the effect of the CVT system dynamic characteristics on the HEV performance, a hardware in the loop simulation (HILS) is performed. In the HILS, hardwares of the CVT belt-pulley and hydraulic control valves are used. It is found that the engine performance by the open loop CVT ratio control shows some deviation from the OOL in spite of the RCVs open loop control ability. To improve the engine performance, a closed loop control of the CVT ratio is proposed with variable control gains depending on the shift direction and the CVT speed ratio range by considering the nonlinear characteristics of the RCV and CVT belt-pulley dynamics. The HILS results show that the engine performance is improved by the closed loop control showing the operation trajectory close to the OOL.

• 전자공학회논문지C
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• 제34C권7호
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• pp.70-81
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• 1997

In this paper, we propose HMCNN(hybrid multiple component neural networks) that enhance performance of MCNN by adapting new pattern partitioning algorithm which can cluster many input patterns efficiently. Added neural network performs similar learning procedure that of kohonen network. But it dynamically determine it's number of output neurons using algorithms that decide self-organized number of clusters and patterns in a cluster. The proposed network can effectively be applied to problems of large data as well as huge networks size. As a sresutl, proposed pattern partitioning network can enhance performance results and solve weakness of MCNN like generalization capability. In addition, we can get more fast speed by performing parallel learning than that of other supervised learning networks.