• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1418-1421
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• 1987

An important problem in edge detection is to select a proper threshold that transforms the gradient picture to e two level picture containing optimum edges between regions, Such a threshold is determined depending on some measures of errors in tresholding. In this paper, an error criterion on extracting edges by thresholding the block gradient image is presented. Based on the error measure, the optimum threshold is chosen for the detection of acceptable edges.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.137-142
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• 2017

A general linearly constrained narrowband adaptive array is examined in the eigenvector space. The optimum weight vector in the eigenvector space is shown to have the same performance as in the standard coordinate system, except that the input signal correlation matrix and look direction steering vector are replaced with the eigenvalue matrix and transformed steering vector. It is observed that the variation in gain factor results in the variation in the distance between the constraint plane and the origin in the translated weight vector space such that the increase in gain factor decreased the distance from the constraint plane to the origin, thus affecting the nulling performance. Simulation results showed that the general linearly constrained adaptive array performed better at an optimal gain factor compared with the conventional linearly constrained adaptive array in a coherent signal environment and the former showed similar performance as the latter in a noncoherent signal environment.

• 한국전산유체공학회지
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• 제1권1호
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• pp.134-141
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• 1996

Wall interference is one of the major obstacles to increase the model size and data accuracy. There have been many treatments for wall interference including interference correction and adaptive wall test section. Recently, two-flexible-walled adaptive wall test section is concluded adequate for three-dimensional test. But proper location of target line and pressure holes are critical to its success. In this study, a new adaptive algorithm which dispenses target line and dependency of pressure hole distribution is suggested. The wind tunnel and free air tests are simulated by the numerical computation of Euler equations. The optimum wall shape is achieved by two variable optimization which is composed of two base streamlines. The wall interference is reduced well in the optimized result which is not sensitive to the base streamlines.

• Smart Structures and Systems
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• 제15권3호
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• 대한전자공학회논문지
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• 제21권2호
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• pp.61-70
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• 1984

본 논문에서는 adaptive array의 이론해석을 통해 antenna array의 물리적인 현상에 따른 비임폭과 지향 특성을 분석하였으며, 최대 신호대 잡음비 (maximum signal-to-rloise ratio) 알고리즘에 의한 array시스템 설계시 유용한 몇가지 요소들을 도출된 관계식과 37-elemellt 비임안테나의 시험 결과를 예로 들어 제시하고 있다. 본 논문은 또한 위성통신, 마이크로파 통신등에서 간섭신호 제거에 유용한 측엽 제거기법의 성능 특성을 표시하는 관계식을 새로이 도출하여 제시하고 있다.

• Journal of Welding and Joining
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• 제33권6호
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• pp.13-20
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• 2015

Many automotive companies are endeavoring to improve the quality of resistance spot welding by updating body-in-white (BIW) production line with adaptive control spot welding system to compensate the process disturbances such as gap, electrode wear, oxidized surfaces, poor fit up and adhesive etc. Most of the commercial adaptive weld controllers require proper "Initial Welding Schedule" or "Reference weld" to achieve compensation in welding parameters during real time welding. In this study, the compensation of a commercial adaptive weld controller had been observed and analyzed thoroughly for various process disturbances to find optimal initial welding schedule. It was observed that 90 percent of the expulsion current in constant current control as reference welding schedule conferred the maximum button diameter in adaptive control welding. Finally, effects of each disturbance in combined field disturbances system with adaptive control had also been confirmed with the design of experiment (DOE) by minitab(R)16 for combined disturbances situation and suitability of optimum initial weld current had also established with real body part validation test.

• 한국안전학회지
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• 제16권4호
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• pp.88-95
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• 2001

Stator core loss has significant adverse effects when an induction motor is controlled by the conventional vector control method. Therefore, taking core toss into account should make it possible to control the torque very precisely. This paper proposes a speed sensorless vector control method for an induction motor at optimum efficiency and high response taking core loss account. The proposed vector control system consists of a speed adaptive rotor flux observer which takes core loss into account and employs a direct vector control which compensates for the influence of core loss. Also, in this paper, a vector controlled induction motor with a deadbeat rotor flux controller is developed. The method ensures optimum efficiency in the steady state without degradation of the dynamic response. The validity of the proposed technique is confirmed by simulation results for induction motor drive system.

• Geomechanics and Engineering
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• 제5권6호
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• pp.519-540
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• 2013

This paper presents an optimal design method for determining pile lengths of piled raft foundations. The foundation settlement is evaluated by taking into account the raft-pile-soil interaction. The analysis of settlement is simplified by using Steinbrenner's equation. Then the total pile length is minimized under the settlement constraint. An extended sequential linear programming technique combined with an adaptive step-length algorithm of pile lengths is used to solve the optimal design problem. The accuracy of the simplified settlement analysis method and the validity of the obtained optimal solution are investigated through the comparison with the actual measurement result in existing piled raft foundations.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• 한국정밀공학회지
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• 제21권9호
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• pp.149-157
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• 2004

This paper presents a new method for hi-objective optimization. Ordinary weighted sum method is easy to implement, but it has two significant drawbacks: (1) the solution distribution by the weighted sum method is not uniform, and (2) the method cannot determine any solutions that reside in non-convex regions of a Pareto front. The proposed adaptive weighted sum method does not solve a multiobjective optimization in a predetermined way, but it focuses on the regions that need more refinement by imposing additional inequality constraints. It is demonstrated that the adaptive weighted sum method produces uniformly distributed solutions and finds solutions on non-convex regions. Two numerical examples and a simple structural problem are presented to verify the performance of the proposed method.