• 정보처리학회논문지A
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• 제18A권6호
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• pp.225-232
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• 2011

Restricted Hypercube-Like(RHL) 그래프는 교차큐브, 뫼비우스큐브, 엠큐브, 꼬인큐브, 지역꼬인큐브, 다중꼬인큐브, 일반꼬인큐브와 같이 유용한 상호연결망들을 광범위하게 포함하는 그래프군이다. 본 논문에서는 $m{\geq}4$ 인 m-차원 RHL 그래프 G에 대해서 임의의 에지 집합 $F{\subset}E(G)$, ${\mid}F{\mid}{\leq}m-2$, 가 고장일 때, 고장 에지들을 제거한 그래프 $G{\setminus}F$는 임의의 서로 다른 두 정점 s와 t에 대해서 dist(s, V(F))${\neq}1$ 이거나 dist(t, V(F))${\neq}1$이면 해밀톤 경로가 있음을 보인다. V(F)는 F에 속하는 에지들의 양 끝점들의 집합이고 dist(v, V(F))는 정점 v와 집합 V(F)의 정점들 간의 최소 거리이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4343-4355
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• 2014

Multicast group communication has many advantages in data centers and thus is widely used by many applications. It can efficiently reduce the network traffic and improve the application throughput. For the multicast application in data centers, an essential problem is how to find a minimal multicast tree, which has been proved to be NP-hard. In this paper, we propose an approximation tree-building method for the minimal multicast problem, named HD（Hamming Distance）-based multicast tree. Consider that many new network structures have been proposed for data centers. We choose three representative ones, including BCube, FBFLY, and HyperX, whose topological structures can be regarded as the generalized hypercube. Given a multicast group in BCube, the HD-based method can jointly schedule the path from each of receiver to the only sender among multiple disjoint paths; hence, it can quickly construct an efficient multicast tree with the low cost. The experimental results demonstrate that our method consumes less time to construct an efficient multicast tree, while considerably reduces the cost of the multicast tree compared to the representative methods. Our approach for BCube can also be adapted to other generalized hypercube network structures for data centers after minimal modifications.

• Nuclear Engineering and Technology
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• 제56권8호
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• pp.2999-3029
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• 2024

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.