• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.281-285
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• 1998

Consider the two-dimensional sorted-set convex hull problem: Given N points in a plane sorted by the x coordinates, compute the convex hull of the points. We propose an O(logNlog logN)-time algorithm that solves the sorted-set convex hull problem on an N\ulcorner\ulcorner${\times}$N\ulcorner\ulcorner reconfigurable mesh. The best known algorithm for the problem on an N\ulcorner\ulcorner${\times}$N\ulcorner\ulcorner reconfigurable mesh takes O(log\ulcornerN) time. Although there is a constant-time algorithm on an N${\times}$N reconfigurable mesh for general two-dimensional convex hull problem, the general convex hull problem requires Θ(N\ulcorner\ulcorner) time on an N\ulcorner\ulcorner${\times}$N\ulcorner\ulcorner reconfigurable mesh due to bandwidth constraints.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.535-543
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• 1997

The application of Hadamard matrix to the paral-lel routings on the hypercube network was presented by Rabin. In this matrix every two rows differ from each other by exactly n/2 positions. A set of n disjoint paths on n-dimensional hypercube net-work was designed using this peculiar property of Hadamard ma-trix. Then the data is dispersed into n packets and these n packet are transmitted along these n disjoint paths. In this paper Rabin's routing algorithm is analyzed in terms of covering problem and as-signment problem. Finally we conclude that n packets dispersed are placed in well-distributed positions during transmisson and the ran-domly selected paths are almost a set of n edge-disjoint paths with high probability.

• Communications of the Korean Mathematical Society
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• v.22 no.3
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• pp.383-389
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• 2007

In this paper we examine the hyperinvariant subspace problem for quasi-n-hyponormal operators. The main result on this problem is as follows. If T = N + K is such that N is a quasi-n-hyponormal operator whose spectrum contains an exposed arc and K belongs to the Schatten p-ideal then T has a non-trivial hyperinvariant subspace.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.141-154
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• 2007

The connectivity problem is a fundamental problem in graph theory. The best known algorithm to solve the connectivity problem on general graphs with n vertices and m edges takes $O(K(G)mn^{1.5})$ time, where K(G) is the vertex connectivity of G. In this paper, an efficient algorithm is designed to solve vertex connectivity problem, which takes $O(n^2)$ time and O(n) space for a trapezoid graph.

• Bulletin of the Korean Mathematical Society
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• v.44 no.2
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• pp.337-350
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• 2007

Given a collection of complex numbers ${\gamma}{\equiv}\{{\gamma}ij\}$ $(0{\leq}i+j{\leq}2n,\;|i-j|{\leq}n)$ with ${\gamma}00>0\;and\;{\gamma}ji=\bar{\gamma}ij$, we consider the moment problem for ${\gamma}$ in the case of n=2, which is referred to Embry quartic moment problem. In this note we give a partial solution for the nonsingular case of Embry quartic moment problem.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.33-40
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• 2015

The time slot assignment problem (TSAP) or Satellite Communications scheduling problem (SCSP) for a satellite performs $n{\times}n$ ground station data traffic switching has been known NP-hard problem. This paper suggests $O(n^2)$ time complexity algorithm for TSAP of a satellite that performs $n^2{\times}n^2$ ground station data traffic switching. This problem is more difficult than $n{\times}n$ TSAP as NP-hard problem. Firstly, we compute the average traffic for n-transponder's basic coverage zone and applies ground station exchange method that swap the ground stations until all of the transponders have a average value as possible. Nextly, we transform the D matrix to $D_{LB}$ traffic matrix that sum of rows and columns all of transponders have LB. Finally, we select the maximum traffic of row and column in $D_{LB}$, then decide the duration of kth switch mode to minimum traffic from selected values. The proposed algorithm can be get the optimal solution for experimental data.

• Convergence Security Journal
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• v.14 no.7
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• pp.59-64
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• 2014

We investigate $p(n){\cdot}2^{O(\sqrt{n})}$ algorithm for 0/1 knapsack problem where x is the total bit length of a list of sizes of n objects. The algorithm is adaptable of method that achieves a similar complexity for the partition and Subset Sum problem. The method can be applied to other optimization or decision problem based on a list of numerics sizes or weights. 0/1 knapsack problem can be used to solve NP-Complete Problems with pseudo-polynomial time algorithm. We try to apply this technique to bio-informatics problem which has pseudo-polynomial time complexity.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.396-403
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• 2014

The multi-divisional knapsack problem is defined as a binary knapsack problem where each mutually exclusive division has its own capacity. In this paper, we present an extension of the multi-divisional knapsack problem that has generalized multiple-choice constraints. We explore the linear programming relaxation (P) of this extended problem and identify some properties of problem (P). Then, we develop a transformation which converts the problem (P) into an LP knapsack problem and derive the optimal solutions of problem (P) from those of the converted LP knapsack problem. The solution procedures have a worst case computational complexity of order $O(n^2{\log}\;n)$, where n is the total number of variables. We illustrate a numerical example and discuss some variations of problem (P).

• Journal of the Korean Mathematical Society
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• v.56 no.4
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• pp.1001-1016
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• 2019

We are concerned with optimization methods for the $L^2$-Wasserstein least squares problem of Gaussian measures (alternatively the n-coupling problem). Based on its equivalent form on the convex cone of positive definite matrices of fixed size and the strict convexity of the variance function, we are able to present an implementable (accelerated) gradient method for finding the unique minimizer. Its global convergence rate analysis is provided according to the derived upper bound of Lipschitz constants of the gradient function.

• Communications of the Korean Mathematical Society
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• v.17 no.4
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• pp.719-729
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• 2002

Consider the random n $\times$ m assignment problem with m $\geq$ $_{i,j}$ Let $u_{i,j}$ be iid uniform random variables on [0, 1] and exponential random variables with mean 1, respectively, and let $U_{n, m}$ and $T_{n, m}$ denote the optimal assignment costs corresponding to $u_{i, j}$ and $t_{i, j}$. In this paper we first give a comparison result about the discrepancy E $T_{n, m}$ -E $U_{n, m}$. Using this comparison result with a known lower bound for Var( $T_{n, m}$) we obtains a lower bound for Var( $U_{n, m}$). Finally, we study the way that E $U_{n, m}$ and E $T_{n, m}$ vary as m does. It turns out that only when m - n is large enough, the cost decreases significantly.tly.