• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.341-346
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• 2004

Recently A Hyper-Star Graph HS(m, k) has been introduced as a new interconnection network of new topology for parallel processing. Hyper-Star Graph has properties of hypercube and star graph, further improve the network cost of a hypercube with the same number of nodes. In this paper, we show that Hyper-Star Graph HS(m, k) is subgraph of hypercube. And we also show that regular graph, Hyper-Star Graph HS(2n, n) is node-symmetric by introduced mapping algorithm. In addition, we introduce an efficient one-to-all broadcasting scheme - takes 2n-1 times - in Hyper-Star Graph HS(2n, n) based on a spanning tree with minimum height.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1075-1084
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• 2022

Internet of Things(IoT) has become a key available technology for efficiently implementing device to device(D2D) services in various domains such as smart home, healthcare, smart city, agriculture, energy, logistics, and transportation. A lightweight publish/subscribe(Pub/Sub) messaging protocol not only establishes data dissemination pattern but also supports connectivity between IoT devices and their applications. Also, a Pub/Sub broker is deployed to facilitate data exchange among IoT devices. A scalable edge-based publish/subscribe (Pub/Sub) broker overlay networks support latency-sensitive IoT applications. In this paper, we design a hypercube grid quorum(HGQ) for distributed Pub/Sub systems based IoT applications. In designing HGQ, the network of hypercube structures suitable for the publish/subscribe model is built in the edge layer, and the proposed HGQ is designed by embedding a mesh overlay network in the hypercube. As their applications, we propose an HGQ-based mechansim for dissemination of the data of sensors or the message/event of IoT devices in IoT environments. The performance of HGQ is evaluated by analytical models. As the results, the latency and load balancing of applications based on the distributed Pub/Sub system using HGQ are improved.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2823-2834
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• 1998

This paper deals with the problem of one-to-one mapping of $2^n$ task modules of a parallel program to an n-dimensional hypercube multicomputer so as to minimize to total communication cost during the execution of the task. The problem of finding an optimal mapping has been proven to be NP-complete. We first propose a graph modification technique which transfers the mapping problem in a hypercube multicomputer into the problem of finding a set of maximum cutsets on a given task graph. Using the graph modification technique, we then propose a repeated mapping scheme which efficiently finds a one-to-one mapping of task modules to a hypercube multicomputer by repeatedly applying an existing bipartitioning algorithm on the modified graph. The repeated mapping scheme is shown to be highly effective on a number of test task graphs, it increasingly outperforms the greedy and recursive mapping algorithms as the number of processors increase. The proposed algorithm is shown to be very effective for regular graph, such as hypercube-isomorphic or 'almost' isomorphic graphs and meshes; it finds optimal mapping on almost all the regular task graphs considered.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.7
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• pp.900-910
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• 1997

Multiblock structured grids are, to a large extent, capable of filling up topologically complex flow domains in an efficient way. The proposed approach enables to use different flow models in each different block and the easy incorporation of different grid refinement strategies for different blocks. Furthermore, it may be expected that this multiblock structured approach will naturally lead to the parallel executions of calculations per block on different vector processors. In this paper, the hypercube + + structure is proposed for topological informations on multiblock grids and the B-spline volume for geometrical informations. Three samples of the-three dimensional results are presented to demonstrate the capabilities of the present approach.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.263-268
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• 2007

In this paper, we analyze some topological properties of Folded Hyper-Star FHS(2n,n). First, we prove that FHS(2n,n) has maximal fault tolerance, and broadcasting time using double rooted spanning tree is 2n-1. Also we show that FHS(2n,n) can be embedded into Folded hypercube with dilation 1, and Folded hypercube can be embedded into FHS(2n,n) ith dilation 2 and congestion 1.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.162-164
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• 2007

This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1207-1214
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• 1996

We present an efficient decentralized, symmetric mutual exclusion algorithm for the hypercube architecture. The algorithm is based on the technique which embeds a mesh into a hypercube. We compare the performance of our algorithm with that of Gupta et al.'s algorithm. As a result of performance comparison, the minimum round-trip delay is equal to that of Gupta et al.'s algorithm, the average blocking delay is a little longer than that of Gupta et al.'s algorithm, and the number of messages per access to critical resource is fewer than that of Gupla et al.'s algorithm.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.87-93
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• 2002

In this paper, an advanced load balancing algorithm in nth order Hypercube distributed system has been proposed. The new algorithm uses centralized load-balancing to avoid blocking phenomenon and processor thrashing, and shows the results which makes loads to approach average value of loads. The new algorithm is compared with several other algorithm and it shows a merit in cost function value.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.123-152
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• 1993

This paper discusses how to automatically extract fuzzy rules from given data.The fuzzy space which contain given data are fitst subdivided into a set of hypercubes.each of which contains the homogeneous data belonging to the same class, and then a fuzzy rule is defined based on the constructed hypercube.In order to dynamically agjust the size of a hypercube. the fuzzy space is to be splitted based on a center vector and then the splitted subspaces are to be merged throungh the adjacency relation.The membership functions.which are to be embedded in a fuzzy rule.are to be formed through analyzing the cummulative histogram of given data along each axis of the constructed hypercube.