• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1658-1666
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• 2009

This paper proposes an approach of Mult_HPSO based on the PC cluster system to reduce or remove the stagnation on an early convergence effect of PSO, reduce an execution time and improve a search ability on an optimal solution. Hybrid PSO(HPSO) is combines the PSO(Particle Swarm Optimization) with the mutation of conventional GA(Genetic Algorithm). The conventional PSO has operated a search process in a single swarm. However, Multi_PSO operates a search process through multiple swarms, which increments diversity of expected solutions and reduces the execution time. Multiple Swarms are composed of unsynchronized PC clusters. We apply to SCED(security constrained economic dispatch) problem, a nonlinear optimization problem, which considers line flow constraints and N-1 line contingency constraints. To consider N-1 line contingency in power system, we have chosen critical line contingency through a process of Screening and Selection based on PI(performace Index). We have applied to IEEE 118 bus system for verifying a usefulness of the proposed approaches.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• Journal of Crop Science and Biotechnology
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• v.10 no.2
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• pp.73-78
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• 2007

The green revolution has significantly helped in increasing the food production. So far, various breeding methods have been exploited, besides them recombination DNA technology provides another approach for increasing the food production. By means of this technology the losses in food production incurred by various biotic and abiotic stresses can be effectively controlled. In most of the transgenic studies scientists have used antibiotic resistant genes as markers for easy selection of transformants but there are risks involved in use of GM foods. To make such foods safer and environment friendly we have discussed a novel strategy i.e. Cre-lox which involves site specific recombination. By means of Cre-lox the marker genes can be specifically removed once the selection of transformants is over. In addition, this strategy can be used to module the hybrid chromosomes, avoid gene silencing and incorporate single copy of a transgene for its higher expression.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.893-898
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• 2014

Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.155-171
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• 2012

With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners' effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.6
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• pp.471-478
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• 2008

Detached Eddy Simulation (DES) is performed for developing turbulent flow of the $270^{\circ}$ curved duct at a Reynolds number of 56,690. The curvature ratio on the basis of a centric radius $R_c$ and a duct height H is 3.357. Turbulence models adopted are k-$\omega$ model for Reynolds Average Navier-Stokes (RANS) equation Simulation and Shear Stress Transport (SST) model for DES. DES is used as the hybrid computation technique combined with RANS-SST and Large Eddy Simulation (LES). Predicted results are compared with measured results including the distributions of Reynolds stresses and the flow characteristics on the symmetric plane of curved duct are presented. Judging from the comparison between the predicted and the measured results, the DES approach is applicable to calculate the developing turbulent flow in a $270^{\circ}$ curved duct.

• Journal of Institute of Convergence Technology
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• v.1 no.1
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• pp.34-40
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• 2011

In this paper, a hybrid design tool combining one-dimensional(1D) lumped model and three-dimensional computational fluid dynamics(CFD) approach has been developed in order to evaluate the performance of inkjet print head and droplet control process are studied to reduce the deviations between nozzles which affect the size of the printed line for the industrial application of direct writing on printed circuit boards(PCB). 1D lumped model analysis shows that it is useful tool for evaluating performance of an inkjet head by varying the design parameters. The differences in ejected volume and droplet velocity between analytical and experimental result are within 12%. Time sequence of droplet generation is verified by the comparison between 3D analysis result and photographic images acquired by stroboscopic technique. In addition, by applying DPN process, velocity and volume uniformity between nozzles is dramatically improved that the tolerance achieved by the piezoelectric inkjet printhead across the 64 nozzles is 5 to 8%. A printed line pattern is successfully obtained using the fabricated inkjet print head and droplet calibration system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.82-94
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• 2004

This paper addresses solutions to the challenges of carrier phase integer ambiguity resolution and cycle slip detection/identification, for maintaining high accuracy of an integrated GPS/Pseudolite/INS system. Such a hybrid positioning and navigation system is an augmentation of standard GPS/INS systems in localized areas. To achieve the goal of high accuracy, the carrier phase measurements with correctly estimated integer ambiguities must be utilized to update the system integration filter's states. The occurrence of a cycle slip that is undetected is, however, can significantly degrade the filter's performance. This contribution presents an effective approach to increase the reliability and speed of integer ambiguity resolution through using pseudolite and INS measurements, with special emphasis on reducing the ambiguity search space. In addition, an algorithm which can effectively detect and correct the cycle slips is described as well. The algorithm utilizes additional position information provided by the INS, and applies a statistical technique known as the cumulative-sum (CUSUM) test that is very sensitive to abrupt changes of mean values. Results of simulation studies and field tests indicate that the algorithms are performed pretty well, so that the accuracy and performance of the integrated system can be maintained, even if cycle slips exist in the raw GPS measurements.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.907-910
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• 2019

본 연구에서는 X-ray 영상에서 비산란 그리드 장치의 영향으로 인한 아티팩트를 제거하기 위하여 이산코사인변환(DCT: discrete cosine transform) 기반의 주파수 분석 기법과 딥러닝 네트워크의 학습 기법을 상호 보완적으로 결합하는 방법론을 제안한다. 피사체의 특성에 따라 다양하게 나타나는 그리드 라인의 억제 기능을 학습하기 위하여 서로 다른 특성을 반영하는 3 종류의 학습데이터를 생성한다. 학습에 사용되는 그리드 라인 영상의 타겟 데이터를 산출하기 위하여 DCT 기반의 밴드스톱 필터링 기법을 사용하였으며 학습데이터의 양적인 부족을 해결하기 위하여 패치 기반의 학습 방법을 적용하였다. 제안된 방법에 대해 기존의 방법과 비교하여 피사체 경계선 영역에서 발생하는 성능저하 현상, 분할의 가장자리에서 발생하는 블로킹 현상, 배경 영상에서의 성능저하 현상 등을 상대적으로 개선할 수 있음을 실험적으로 평가하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.