• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.2
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• pp.111-119
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• 1995

In this paper, we propose an efficient SA(simulated annealing) algorithm for the synthesis of binary phase computer generated hologram. SA algorithm is a method to find the optimal solution through iterative technique. It is important that selecting cost function and parameters within this algorithm. The aplications of converentional SA algorithm to synthesize parameters within this algorithm. The applications of conventional SA algorithm to synthesize binary hologram have many problems because of inappropriate paramters and cost function. So, we propose a new cost function and a calculation technique of proper parameters required to achieve the optimal solution. Computer simulation results show that the proposed method is better than conventional method in terms of diffraction efficiency and reconstruction error. Also, we show the reconstructed images by the proposed method through optical esperiment.

• Journal of Korean Society of Transportation
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• v.9 no.2
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• pp.121-126
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• 1991

Wilson made an importent contribution to develop a trip distribution model with the general form of gravity model which is an entropy maximization program. Also Wilson suggested a technique which is called the "iterative balancing method" for soving the model. This te-chnique however is not stable to find solution because it is a heuristic method and sometimes does not converge to the correct solution. In this paper a new solution method using a numerical method for solving the non-linear simultaneous equation system is developed and evaluated in both computers VAX 8700 and PC/AT 286 The result of this method and Wilson's method are compared with each other. Wilson's method resulted in inferior solutions measured by the final norm of residuals.

• Journal of the Korean Mathematical Society
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• v.54 no.2
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• pp.613-626
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• 2017

For the overdetermined linear system, when both the data matrix and the observed data are contaminated by noise, Total Least Squares method is an appropriate approach. Since an ill-conditioned data matrix with noise causes a large perturbation in the solution, some kind of regularization technique is required to filter out such noise. In this paper, we consider a Dual regularized Total Least Squares problem. Unlike the Tikhonov regularization which constrains the size of the solution, a Dual regularized Total Least Squares problem considers two constraints; one constrains the size of the error in the data matrix, the other constrains the size of the error in the observed data. Our method derives two nonlinear equations to construct the iterative method. However, since the Jacobian matrix of two nonlinear equations is not guaranteed to be nonsingular, we adopt a trust-region based iteration method to obtain the solution.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1276-1286
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• 2002

The numerical techniques are presented to solve the static and dynamic contact problems of deformable bodies having large rotations of the contact surfaces. The contact conditions on the possible contact surfaces are enforced by using the contact error vector, and an iterative scheme similar to augmented Lagrange multiplier method is employed to reduce the contact error vector monotonically. For dynamic contact problems using implicit time integration, a contact error vector is also defined by combining the displacement, velocity, and acceleration on the contact surface. The suggested iterative technique is implemented to ABAQUS by using the UEL subroutine UEL. In this work, after the computing procedures to solve the frictional contact problems are explained, the numerical examples are presented to compare the present solutions with those obtained by ABAQUS.

• Journal of the Korean Mathematical Society
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• v.57 no.5
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• pp.1079-1101
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• 2020

This work is concerned with a geometric inverse problem in fluid mechanics. The aim is to reconstruct an unknown obstacle immersed in a Newtonian and incompressible fluid flow from internal data. We assume that the fluid motion is governed by the Stokes-Brinkmann equations in the two dimensional case. We propose a simple and efficient reconstruction method based on the topological sensitivity concept. The geometric inverse problem is reformulated as a topology optimization one minimizing a least-square functional. The existence and stability of the optimization problem solution are discussed. A topological sensitivity analysis is derived with the help of a straightforward approach based on a penalization technique without using the classical truncation method. The theoretical results are exploited for building a non-iterative reconstruction algorithm. The unknown obstacle is reconstructed using a levelset curve of the topological gradient. The accuracy and the robustness of the proposed method are justified by some numerical examples.

• Journal of the Korean Mathematical Society
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• v.41 no.2
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• pp.345-368
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• 2004

A preconditioning algorithm is developed in this paper for the iterative solution of the linear system of equations resulting from the p-version boundary element approximation of the three dimensional integral equation with hypersingular operators. The preconditioner is derived by first making the nodal and side basis functions locally orthogonal to the element internal bases, and then by decoupling the nodal and side bases from the internal bases. Its implementation consists of solving a global problem on the wire-basket and a series of local problems defined on a single element. Moreover, the condition number of the preconditioned system is shown to be of order $O((1＋ln/p)^{7})$. This technique can be applied to discretization with triangular elements and with general basis functions.

• Communications of the Korean Mathematical Society
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• v.24 no.4
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• pp.605-615
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• 2009

In this paper, we develop a reliable algorithm which is called the variation of parameters method for solving sixth-order boundary value problems. The proposed technique is quite efficient and is practically well suited for use in these problems. The suggested iterative scheme finds the solution without any perturbation, discritization, linearization or restrictive assumptions. Moreover, the method is free from the identification of Lagrange multipliers. The fact that the proposed technique solves nonlinear problems without using the Adomian's polynomials can be considered as a clear advantage of this technique over the decomposition method. Several examples are given to verify the reliability and efficiency of the proposed method. Comparisons are made to reconfirm the efficiency and accuracy of the suggested technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1194-1200
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• 2006

In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

• Bulletin of the Korean Mathematical Society
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• v.42 no.1
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• pp.17-22
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• 2005

The generalized quasilinearization technique has been employed to obtain a sequence of approximate solutions converging monotonically and rapidly to a solution of the nonlinear Neumann boundary value problem.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.101-113
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• 2000

In this paper, we introduce and study a new class of variational inclusions, called the set-valued quasi variational inclusions. The resolvent operator technique is used to establish the equivalence between the set-valued variational inclusions and the fixed point problem. This equivalence is used to study the existence of a solution and to suggest a number of iterative algorithms for solving the set-valued variational inclusions. We also study the convergence criteria of these algorithms.