• Korean Journal of Mathematics
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• v.31 no.3
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• pp.269-294
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• 2023

The purpose of this paper is to introduce a new three-step iterative process and show that our iteration scheme is faster than other existing iteration schemes in the literature. We provide a numerical example supported by graphs and tables to validate our proofs. We also prove convergence and stability results for the approximation of fixed points of the contractive-like mapping in the framework of uniformly convex Banach space. In addition, we have established some weak and strong convergence theorems for nonexpansive mappings.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.103-108
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• 1995

By applying the P$_1$ and P$_2$ equations to the operator form of a synthetic acceleration, we derive the p,-acceleration (diffusion synthetic acceleration: DSA) and P$_2$-acceleration (p$_2$SA) schemes in one dimensional slab geometry. We Fourier-analyze the derived acceleration schemes with the discrete-ordinates transport equation and showed that the DSA outperforms the P$_2$SA. These results confirm that one cannot simply assume that replacement of the DSA with a higher order approximation will lead to a better acceleration performance.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.379-383
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• 2001

The restricted shortest path problem is known to be weakly NP-hard and solvable in pseudo-polynomial time. Four fully polynomial approximation schemes (FPAS) are available in the literature, and most of these are based on pseudo-polynomial algorithms. In this paper, we propose a new FPAS that can be easily derived from a combination of a set of standard techniques. Although the complexity of the suggested algorithm is not as good as the fastest one available in the literature, it is practical in the sense that it does not rely on the bound tightening phase based on approximate binary search as in Hassin's fastest algorithm. In addition, we provide a review of standard techniques of existing works as a useful reference.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.419-424
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• 1999

In this paper, the comparison of the first order approximation schemes such as SLP (sequential linear programming), CONLIN(convex linearization), MMA(method of moving asymptotes) and the second order approximation scheme, SQP(sequential quadratic programming) was accomplished for optimization of and nonlinear structures. It was found that MMA and SQP(sequential quadratic programming) was accomplished for optimization of and nonlinear structures. It was found that MMA and SQP are the most efficient methods for optimization. But the number of function call of SQP is much more than that of MMA. Therefore, when it is considered with the expense of computation, MMA is more efficient than SQP. In order to examine the efficiency of MMA for complex optimization problem, it was applied to the helicopter tail boom considering column buckling and local wall buckling constraints. It is concluded that MMA can be a very efficient approximation scheme from simple problems to complex problems.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• Wind and Structures
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• v.9 no.3
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• pp.231-243
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• 2006

An improvement to the spectral representation algorithm for the simulation of wind velocity fields on large scale structures is proposed in this paper. The method proposed by Deodatis (1996) serves as the basis of the improved algorithm. Firstly, an interpolation approximation is introduced to simplify the computation of the lower triangular matrix with the Cholesky decomposition of the cross-spectral density (CSD) matrix, since each element of the triangular matrix varies continuously with the wind spectra frequency. Fast Fourier Transform (FFT) technique is used to further enhance the efficiency of computation. Secondly, as an alternative spectral representation, the vectors of the triangular matrix in the Deodatis formula are replaced using an appropriate number of eigenvectors with the spectral decomposition of the CSD matrix. Lastly, a turbulent wind velocity field through a vertical plane on a long-span bridge (span-wise) is simulated to illustrate the proposed schemes. It is noted that the proposed schemes require less computer memory and are more efficiently simulated than that obtained using the existing traditional method. Furthermore, the reliability of the interpolation approximation in the simulation of wind velocity field is confirmed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.130-138
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• 2003

The classical image reconstruction for stripmap-mode Synthetic Aperture Radar is the Range-Doppler algorithm. When the spotlight-mode SAR system was envisioned, Range-Doppler algorithm turned out to fail rapidly in this SAR imaging modality. Thus, what is referred to as Polar format algorithm, which is based on the Plane wave approximation, was introduced for imaging from spotlight-mode SAR raw- data. In this paper, we have studied for the raw data processing schemes in the spotlight-mode Synthetic Aperture Radar. We apply the Wavefront Reconstruction scheme that does not utilize the approximation in spotlight-mode SAR imaging modelity, and compare the performance of target imaging with the Polar format inversion scheme.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.18-27
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• 2002

A hierarchical representation scheme for planar curves, MBO-tree, is proposed in this paper, which provides natural approximation and efficient localization. MBO-tree is based on the Douglas-Peucker algorithm (iterative end-point fit algorithm), but approximation errors that are stored with corresponding points in MBO-tree nodes and are used for abstraction measures are adjusted by force to eliminate unnatural approximation. The error adjusting is just making the approximation error of a node in a MBO-tree to be less than or equal to that of its parent. In point of localization, the bounding area of a curve is represented with a minimum bounding octangle (MBO), which can enclose the curve more compactly compared with those of other hierarchical schemes, such as the strip tree, the arc tree and the HAL tree. The MBO satisfies the hierarchical inclusion property that is useful for hierarchical geometrical operations, such as the point-inclusion test and the polygon intersection test. Through several experiments, we found that the proposed scheme was able to approximate more naturally and to localize more effectively.

• Bulletin of the Korean Mathematical Society
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• v.50 no.1
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• pp.321-341
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• 2013

In this paper, we discuss the a posteriori error estimates of the semidiscrete mixed finite element methods for quadratic optimal control problems governed by linear hyperbolic equations. The state and the co-state are discretized by the order $k$ Raviart-Thomas mixed finite element spaces and the control is approximated by piecewise polynomials of order $k(k{\geq}0)$. Using mixed elliptic reconstruction method, a posterior $L^{\infty}(L^2)$-error estimates for both the state and the control approximation are derived. Such estimates, which are apparently not available in the literature, are an important step towards developing reliable adaptive mixed finite element approximation schemes for the control problem.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.539-557
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• 1998

This paper is concerned with the performance evaluation of loss networks. We shall review the Erlang Fixed Point (EFP) method for estimating the blocking probabilities, which is based on an assumption that links are blocked independently. For networks with linear structure, the behaviour of adjacent links can be highly correlated. We shall give particular attention to recently-developed fixed-point methods which specifically account for the dependencies between neighbouring links. For the network considered here, namely a ring network with two types of traffic, these methods produce relative errors typically $10^{-5}$ of that found using the basic EFP approximation.