• Management Science and Financial Engineering
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• v.15 no.1
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• pp.71-79
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• 2009

This paper considers the two kinds of integer multicommodity flow problems, a feasibility problem and a maximization problem, on two types of directed cycles, a unidirectional and a bidirectional cycle. Both multicommodity flow problems on an undirected cycle have been dealt with by many researchers and it is known that each problems can be solved by a polynomial time algorithm. However, we don't find any result on the directed cycles. Here we show that we can also solve both problems for a unidirectional and a bidirectional cycle in polynomial time.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.47-53
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• 2016

This paper deals with the capacity constrained time slot assignment problem(CTSAP) that a satellite switches to traffic between $m{\times}n$ ground stations using on-board $k{\leq}_{min}\{m,n\}$ k-transponders switching modes in SS/TDMA time-division technology. There was no polynomial time algorithm to solve the optimal solution thus this problem classified by NP-hard. This paper suggests a heuristic algorithm with O(mn) time complexity to solve the optimal solution for this problem. Firstly, the proposed algorithm selects maximum packet lengths of $\({mn \atop c}\)$ combination and transmits the cut of minimum packet length in each switching mode(MSMC). In the case of last switching mode with inefficient transmission, we applies a compensation strategy to obtain the minimum number of switching modes and the minimum makespan. The proposed algorithm finds optimal solution in polynomial time for all of the experimental data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.35-42
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• 2001

The primitive polynomial on GF(q) is used in the area of the scrambler, the error correcting code and decode, the random generator and the cipher, etc. The algorithm that generates efficiently the primitive polynomial on GF(q) was proposed by A.D. Porto. The algorithm is a method that generates the sequence of the primitive polynomial by repeating to find another primitive polynomial with a known primitive polynomial. In this paper, we propose the algorithm that is improved in the A.D. Porto algorithm. The running rime of the A.D. Porto a1gorithm is O($\textrm{km}^2$), the running time of the improved algorithm is 0(m(m+k)). Here, k is gcd(k, $q^m$-1). When we find the primitive polynomial with m odor, it is efficient that we use the improved algorithm in the condition k, m>>1.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2617-2620
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• 2003

This paper presents the construction algorithm of the irreducible polynomial which needs to multiply over GF(2$\^$m/) and the flow chart representing the proposed algorithm has been proposed. And also, we get the degree from the value of xm＋k formation to the value of k = 7 using the proposed flow chart. The multiplier circuit has been implemented by using the proposed irreducible polynomial generation(IPG) algorithm in this paper, and we compared the proposed circuit with the conventional one. In the case of k = 7, one AND gate and five Ex-or gates are needed as the delay time for the irreducible polynomial in the proposed algorithm, but seven AND gates and sever Ex-or gates in the conventional one. As a result, the proposed algorithm shows the improved performance on the delay time.

• 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 the military operations research society of Korea
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• v.23 no.2
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• pp.103-119
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• 1997

This paper considers the shortest path problem combined with Min-Min-Sum objective for solving the problem of the military logistics. This paper develops a polynomial-time algorithm for the optimal solution. To analyze the real combat situation, the ability time and distance time of communication line are considered. The complexities of algorithm between previous study and the algorithm developed in this paper is presented. Finally we provide a simple example of application with randomly generated problem.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1991.11a
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• pp.40-48
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• 1991

McEliece 공개키 암호체계에 대한 새로운 암호해독적 공격이 제시되어진다. 기존의 암호해독 algorithm이 exponential-time의 complexity를 가지는 반면, 본고에서 제시되어지는 algorithm은 polynomial-time의 complexity를 가진다. 모든 linear codes에는 systematic generator matrix가 존재한다는 사실이 본 연구의 동기가 된다. Public generator matrix로부터, 암호해독에 사용되어질 수 있는 새로운 trapdoor generator matrix가 Gauss-Jordan Elimination의 역할을 하는 일련의 transformation matrix multiplication을 통해 도출되어진다. 제시되어지는 algorithm의 계산상의 complexity는 주로 systematic trapdoor generator matrix를 도출하기 위해 사용되는 binary matrix multiplication에 기인한다. Systematic generator matrix로부터 쉽게 도출되어지는 parity-check matrix를 통해서 인위적 오류의 수정을 위한 Decoding이 이루어진다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.9
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• pp.430-438
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• 2001

In this study, we introduce the adaptive Polynomial Neuro-Fuzzy Networks(PNFN) architecture generated from the fusion of fuzzy inference system and PNN algorithm. The PNFN dwells on the ideas of fuzzy rule-based computing and neural networks. Fuzzy inference system is applied in the 1st layer of PNFN and PNN algorithm is employed in the 2nd layer or higher. From these the multilayer structure of the PNFN is constructed. In order words, in the Fuzzy Inference System(FIS) used in the nodes of the 1st layer of PNFN, either the simplified or regression polynomial inference method is utilized. And as the premise part of the rules, both triangular and Gaussian like membership function are studied. In the 2nd layer or higher, PNN based on GMDH and regression polynomial is generated in a dynamic way, unlike in the case of the popular multilayer perceptron structure. That is, the PNN is an analytic technique for identifying nonlinear relationships between system's inputs and outputs and is a flexible network structure constructed through the successive generation of layers from nodes represented in partial descriptions of I/O relatio of data. The experiment part of the study involves representative time series such as Box-Jenkins gas furnace data used across various neurofuzzy systems and a comparative analysis is included as well.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.175-181
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• 2014

This paper suggests O(m) polynomial time heuristic algorithm to obtain the solution for the driver scheduling problem, DSP, that has been classified as NP-complete problem. The proposed algorithm gets the initial assignment of n minimum number of drivers from given m schedules. Nextly, this algorithm gets the minimum total time (TC) using 5 rules of swap and insert for decrease of over times (OT) and idle times (IT). Although this algorithm is a heuristic polynomial time algorithm with O(m) time complexity rules to be find a optimal (or approximate) solution, this algorithm is equal to metaheuristic methods for the 5 experimental data. To conclude, this paper shows the DSP is not NP-complete problem but Polynomial time (P)-problem with polynomial time rules.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.159-164
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• 2022

The linear assignment problem (LAP) and linear bottleneck assignment problem (LBAP) has been unknown the algorithm to solve the optimal solution within polynomial-time. These problems are classified by NP-hard. Therefore, we can be apply metaheuristic methods or linear programming (LP) software package or Hungarian algorithm (HA) with O(m⁴) computational complexity. This paper suggests polynomial time algorithm with O(mn)=O(m²),m=n time complexity to LAP and LBAP. The select-delete method is simply applied to LAP, and the delete-select method is used to LBAP. For the experimental data without the unique algorithm can be apply to whole data, the proposed algorithm can be obtain the optimal solutions for whole data.