• Korean Management Science Review
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• v.10 no.1
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• pp.193-205
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• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• East Asian mathematical journal
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• v.31 no.1
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• pp.55-63
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• 2015

Let $\mathbb{B}$ be the unit ball in $\mathbb{C}^n$. For a weight function ${\omega}$, we define the generalized growth space $A^{\omega}(\mathbb{B})$ by the space of holomorphic functions f on $\mathbb{B}$ such that $${\mid}f(z){\mid}{\leq}C{\omega}({\mid}{\rho}(z){\mid},\;z{\in}\mathbb{B}$$. Our main purpose in this note is to get the corona type decomposition in generalized growth spaces on $\mathbb{B}$.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.323-341
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• 1997

Traditionally, the Process Planning problems and the Scheduling problems have been considered as independent ones. However, we can take much advantages by solving the two problems simultaneously. In this paper, we deal with the enlarged problem that takes into account both the process planning and the scheduling problems. And we present a solution algorithm for the problem assuming that the given process plan data is represented by AND/OR graph. A mathematical model(mixed ILP model) whose objective is the minimization of the makespan, is formulated. We found that we can get the optimal solutions of the small-size problems within reasonable time limits, but not the large-size problems. So we devised an algorithm based on the decomposition strategy to solve the large-scale problems (realistic problems) within practical time limits.

• ETRI Journal
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• v.36 no.6
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• pp.960-967
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• 2014

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi-channel wireless multihop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems - flow control; next-hop routing; rate allocation and scheduling; power control; and channel allocation - and finally solved by a low-complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.173-175
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• 2015

We proposed a blind watermarking scheme using singular vectors based on Discrete Wavelet Transform (DWT) and Redundant Discrete Wavelet Transform (RDWT) combined with Singular Value Decomposition (SVD) for copyright protection application. We replaced the 1st left and right singular vectors decomposed from cover image with the corresponding ones from watermark image to overcome the false-positive problem in current watermark systems using SVD. The proposed scheme realizes the watermarking system without a false positive problem, and shows high fidelity and robustness.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.1023-1033
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• 2012

An underwater planar covering problem is studied where the coverage region consists of polygonal cells, and line sweep motion is used for coverage. In many subsea applications, sidescan sonar has become a common tool, and the sidescan sonar data is meaningful only when the sonar is moving in a straight line. This work studies the optimal line sweep coverage where the sweep paths of the cells consist of straight lines and no turn is allowed inside the cell. An optimal line sweep coverage solution is presented when the line sweep path is parallel to an edge of the cell boundary. The total time to complete the coverage task is minimized. A unique contribution of this work is that the optimal sequence of cell visits is computed in addition to the optimal line sweep paths and the optimal cell decomposition.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.811-827
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• 2010

This paper deals with a density estimation method in binary choice models that can be regarded as a statistical inverse problem. We use an orthogonal basis to estimate density function and consider the choice of an appropriate truncation parameter to reflect the model complexity and the prediction accuracy. We propose a data-dependent rule to choose the truncation parameter in the context of binary choice models. A numerical simulation is provided to illustrate the performance of the proposed method.

• Honam Mathematical Journal
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• v.43 no.3
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• pp.373-383
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• 2021

In this study, a numerical method deals with the Chebyshev wavelet collocation and Adomian decomposition methods are proposed for solving Korteweg-de Vries equation. Integration of the Chebyshev wavelets operational matrices is derived. This problem is reduced to a system of non-linear algebraic equations by using their operational matrix. Thus, it becomes easier to solve KdV problem. The error estimation for the Chebyshev wavelet collocation method and ADM is investigated. The proposed method's validity and accuracy are demonstrated by numerical results. When the exact and approximate solutions are compared, for non-linear or linear partial differential equations, the Chebyshev wavelet collocation method is shown to be acceptable, efficient and accurate.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.293-301
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• 2022

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.