• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.191-200
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• 2009

Location based services (LBSs) have drawn huge attention as the growing number mobile devices and wireless technology demand more pervasive information access. In LBSs, Constraint nearest neighbor queries are one of the important queries of human to fulfill his desired quickly through wireless technology. We propose new query processing of constrained nearest neighbor query on the air to support mobile clients which demand optimal uses of wireless broadcast channel and using minimum battery power of client. First we proposed NN query processing with constrained region and then explain the novel NN query processing with various types of constraints. We have proposed novel algorithms to support Constrained Nearest Neighbor queries on the air based on Distributed Spatial Index and Bitmap-based Spatial Index.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.61-65
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• 1993

절삭작업에 있어서 생산기술자가 제품을 경제적으로 생산하기 위해서는 기계의 사양이나 요구되는 제품의 정밀도 등 을 고려하여 목적에 맞는 절삭조건을 선택하여야 한다. 특히 임금이 과거에비해 크게 오르고 기계의 가격이 자동화로 인하여 고가가 됨에 따라서 기계의 효율적 운용이 점점 더 중요하게 되었다. 따라서 목적에 맞는 절삭조건의 선정은 기업의 경쟁력 향상에 있어서 중요한 문제로 부상되고 있다. 본 논문에서는 정면밀링작업시, 인서트 초기위치오차( Runout)를 고려한 표면조도와 절삭력 시뮬레이션 프로그램을 이용하여 구한 허용동력을 제한조건으로 고려하여 보다 실제에 가까운 상황에서 최소비용과 최대 생산율을 얻도록 프로그램을 개발하였다.

• The Journal of the Acoustical Society of Korea
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• v.21 no.6
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• pp.522-530
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• 2002

This paper introduces a neural network (NN) -based nonlinear predictor for the LP (Linear Prediction) residual. To evaluate the effectiveness of the NN-based nonlinear predictor for LP-residual, we first compared the average prediction gain of the linear long-term predictor with that of the NN-based nonlinear long-term predictor. Then, the effects on the quantization noise of the nonlinear prediction residuals were investigated for the NN-based nonlinear predictor A new NN predictor takes into consideration not only prediction error but also quantization effects. To increase robustness against the quantization noise of the nonlinear prediction residual, a constrained back propagation learning algorithm, which satisfies a Kuhn-Tucker inequality condition is proposed. Experimental results indicate that the prediction gain of the proposed NN predictor was not seriously decreased even when the constrained optimization algorithm was employed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2109-2124
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• 1991

A simulation program is developed to analyse the performance of an axial flow turbine stage based on the meanline prediction method. The gradient projection method is utilized to minimize the aerodynamic losses under the specified constraints on such as flow coefficient, total pressure ratio, stage power and blade loading coefficient. After obtaining the optimum point for minimizing the stage loss, a sensitivity analysis is carried out ground the optimum point to find the effects of the design variables and the design constraints on the stage performance. The result of the senitivity analysis under a constant blade loading coefficient shows that the total loss is more sensitive to the mean diameter, the absolute flow angle at nozzle outlet, the relative flow angle at rotor outlet and the axial mean velocity compared to the chords and the pitches. Moreover, the design constraints on the degree of reaction at root and the blade length-to-diameter ratio are found to be most influencial on the maximization of the overall aerodynamic efficiency.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.1-6
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• 2002

Hopfield introduced the neural network for linear program with linear constraints. In this paper, Hopfield neural network has been generalized to solve the optimization problems including nonlinear constraints. Also, it has been discussed the methods hew to reconcile optimization problem with neural networks and how to implement the circuits.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.36-43
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• 2003

In this study, a satellite payload module was optimized by considering local stabilities. As design constraints in the satellite structure, local instabilities such as wrinkling, dimpling, crippling for honeycomb structures and crippling failure mode for beams were considered in addition to frequency and stress constraints. The constraints for the local instabilities (uncommon in general structures) were taken for the optimization of a satellite structures under severe launching environments. The analysis was performed combining the finite element analysis and optimization program. From the optimization results, it was found that frequency, crippling and wrinkling were the most critical constraints to achieve the design goals. Also, the importance of each design variable was estimated. Finally, the optimum design of the payload module was achieved for various design constraints and design parameters.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2002.04a
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• pp.77-77
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• 2002

초소형 공중발사체 설계 시 하이브리드 모터의 적용가능성에 대한 연구를 실시하였다. HTPB/LOX를 추진제로 하여 마차바퀴형 연료 그레인, 산화제 탱크 가압방식을 사용하였고, 성능특성을 계산하기 위하여 하이브리드 연료의 연소율이 일정하다고 가정 하였다. 본 연구에 사용된 임무는 중량 3.5kg의 나노위성을 근지점 고도 200km, 원지점 고도 1,500km의 타원궤도로 진입시키는 것을 목적으로 하는 로켓의 1단 부분에 관한 것으로 1단의 발사속도는 M=1.3, 발사고도는 12km, 연소종료 고도는 40km이다. 1단에 대한 페이로드 중량은 127.5kg이고, 속도증가분($\Delta$V)은 3,330m/s이다. 모선은 F-4E를 사용하였고 모선의 특성상 발사체의 총 중량이 1,000kg이하로 제한되고 길이와 직경이 5m${\times}$5m로 제한되나 1단에 대한 길이의 제한조건은 현재까지 명확히 정립되지 않은 상태이다. 설계과정에서의 변수는 연료 그레인 포트 개수, 초기 산화제 플럭스, 연소실 압력을 사용했고, 설계 제한조건은 추진제 중량, 평균 비추력, 평균 추력, 연소시간, 1단 길이, 직경, 연소시간이고, 이들의 범위는 모선의 특성과 초소형 공중발사체의 임무특성에 맞게 설정하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.602-610
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• 2018

The model predictive control is an effective method to optimize the current control input that predicts the current control state and the future error using the predictive model of the control system when the reference trajectory is known. Since the control input can not have a physically infinitely large value, a predictive controller design with constraints should be considered. In addition, the reference model $A_r$ and the weight matrices Q, R that determine the control performance of the predictive controller are not optimized as arbitrarily designated should be considered in the controller design. In this study, we construct a predictive controller of a mobile robot by transforming it into a quadratic programming problem with constraints, The control performance of the mobile robot can be improved by optimizing the control parameters of the predictive controller that determines the control performance of the mobile robot using genetic algorithm. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.432-440
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• 2011

This paper focus on lane recognition performance test using a road lane constraint with transport infrastructure information. The constraint is determined through the relation of the drive direction and vehicle position. The road lane constraint sets large limit for first and last lane. To analyze the performance of the proposed method, simulations are carried out. The results show that the lane recognition performance using a constraint is improved 40% at four-lane, 25% at six-lane, 15% at eight-lane.