• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.691-698
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• 2003

In this paper, we propose a problem, called one-to-one disjoint path cover problem, whether or not there exist k disjoint paths joining a pair of vertices which pass through all the vertices other than the two exactly once. A graph which for an arbitrary k, has a one-to-one disjoint path cover between an arbitrary pair of vertices has a hamiltonian property stronger than hamiltonian-connectedness. We investigate this problem on recursive circulants and prove that for an arbitrary k $k(1{\leq}k{\leq}m)$$ G(2^m,4)$,$m{\geq}3$, has a one-to-one disjoint path cover consisting of k paths between an arbitrary pair of vortices.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.8
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• pp.399-405
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• 2001

이 논문은 재귀원형군 G(2$^{m}$ , 2$^{k}$ )의 강한 해밀톤 성질을 그래프 이론적 관점에서 고찰한다. 재귀원형군은 [9]에서 제안된 다중 컴퓨터의 연결망 구조이다. G(2$^{m}$ , 2$^{k}$ )가 임의의 정점 쌍 ν, $\omega$를 잇는 길이 ι인 경로를 가지는가 하는 문제를 고려하여, (a) G(2$^{m}$ , 2$^{k}$ )는 ι$\geq$d(ν, $\omega$)을 만족하는 모든 ι에 대해서 길이 ι인 경로를 가지며, (b) G(2$^{m}$ , 4)는 ι$\geq$d(ν, $\omega$)+2인 모든 길이의 경로를 가지며, (c)G(2$^{m}$ , 2$^{k}$ ), k$\geq$3은 길이 d(ν, $\omega$)+2$^{k}$ -3인 경로를 가지지 않는 정점 쌍이 있음을 보인다. 여기서, d(ν, $\omega$)는 ν와 $\omega$ 사이의 거리이다.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.387-393
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• 2004

DNA computing is technology that applies immense parallel castle of living body molecules into information processing technology, and has used to solve NP-complete problems. However, there are problems which do not look for solutions and take much time when only DNA computing technology solves NP-complete problems. In this paper we proposed an algorithm called ACO(Algorithm for Code Optimization) that can efficiently express DNA sequence and create good codes through composition and separation processes as many as the numbers of reaction by DNA coding method. Also, we applied ACO to Hamiltonian path problem of NP-complete problems. As a result, ACO could express DNA codes of variable lengths more efficiently than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for accurate paths in a short time.