• 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.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.9
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• pp.103-110
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• 2010

This paper presents the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method and approximation modeling method with Radial Basis Function (RBF) neural network structure. The complex tool holder is used for holding a (milling/drilling) tool of a machine tool. The engineering problem of complex tool holder results from the twisting of spindle of tool holder. For this purpose, we present the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method (specifically a module of $iSight^{(R)}$ FD-3.1) and approximation modeling method with Radial Basis Function (RBF) (another module of $iSight^{(R)}$ FD-3.1) neural network structure

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1361-1368
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• 2014

In this paper, we analyze emddings among HFCube(n,n), HCN(n,n), HFN(n,n) with lower network cost than that of Hypercube. The results are as follows. We propose that $Q_{2n}$ can be embedded into HFCube(n,n) with dilation 5, congestion 2. HCN(n,n) and HFN(n,n) are subgraphs of HFCube(n,n). HFCube(n,n) can be embedded into HFN(n,n) with dilation 3. HFCube(n,n) can be embedded into HCN(n,n) with dilation O(n). The results will be helpful to analyze several efficient properties in each interconnection network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.412-418
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• 2000

In this paper, we will propose that HCN(n,n) gets Hamiltonian Cycles and analyze embedding among HCN(n,n) and UFN(n,n), and HFN(n,n) and In-hypercube. Further, we will prove that HCN(n,n) can be embedded into HFN(n,n) with dilation 3 and the cost for HFN(n,n) to be embedded into HCN(n,n) will be O(n), and HW(n,n) can be embedded into 2n-hypercube with dilation 3 and the cost for In-hypercube to be embedded into HFN(n,n) will be O(n).

• Transactions on Electrical and Electronic Materials
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• v.7 no.4
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• pp.210-214
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• 2006

In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.361-371
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• 2008

In this paper, the hypercube, hyperpetersen networks, whose degree is increasing in accordance with expansion of number of node and complete binary tree are one-to-one embedded into peterson-torus(PT) network which has fixed degree. The one-to-one embedding has less risk of overload or idle for the processor comparative to one-to-many and many-to-one embedding. For the algorithms which were developed on hypercube or hyperpetersen are used for PT network, it is one-to one embedded at expansion ${\doteqdot}1$, dilation 1.5n+2 and link congestion O(n) not to generate large numbers of idle processor. The complete binary tree is embedded into PT network with link congestion =1, expansion ${\doteqdot}5$ and dilation O(n) to avoid the bottleneck at the wormhole routing system which is not affected by the path length.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.221-233
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• 2008

In general, we use a Parallel processing computer manufactured specially for the purpose of parallel processing to do high performance computings. But we can depoly and use a PC cluster composed of several common PCs instead of the very expensive parallel processing computer. A common way to get a PC cluster is to adopt the star topology network connected by a switch hub. But in this paper, we grope efficient implementations of hypercube networks based on TCP/IP to connect 8 PCs directly for more useful parallel processing environment, and make evaluations on functionality and efficiency of them using ping, netperf, MPICH. The two proposed methods of implementation are IP configuration based on link and IP configuration based on node. The results of comparison between them show that there is not obvious difference in performance but the latter is more efficient in simplicity of routing table. For verification of functionality, we compare the parallel processing results of an application in them with the same in a star network based PC cluster. These results also show that the proposed hypercube networks support a perfect parallel processing environment respectively.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.825-834
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• 2018

Broadcasting is a basic data communication method for interconnection networks. There are two types of broadcasting. One-to-all broadcasting is to transmit a message from one node to all other nodes and all-to-all broadcasting is to transmit a message from all the nodes that have messages to other nodes. And by the using way of the transmission port per unit time, there are two schemes of broadcasting. Single port telecommunication(SLA) is to transmit messages from one node that contains the messages to one adjacent node only and all port telecommunication(MLA) is to transmit messages from one node to all adjacent nodes within a time of unit. Matrix hypercube is that an interconnection network has improved network cost than that of hypercube with the same number of nodes. In this paper, we analyze broadcasting scheme of matirx hypercube. First, we propose one-to-all and all-to-all broadcasting algorithms of matrix hypercube. And we prove that one-to-all broadcasting times are 2n+1 and $2{\lceil}{\frac{n}{2}}{\rceil}+1$ based on the SLA and MLA models, respectively. Also, we show all-to-all broadcasting time using SLA model is $5{\times}2^{\frac{n}{2}}-2$ when n=even, and is $5{\times}2^{\frac{n-1}{2}}+2$ when n=odd.

• The KIPS Transactions:PartA
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• v.15A no.6
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• pp.345-350
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• 2008

Recently, a HyperStar network HS(2n,n) has been introduced as a new interconnection network of new topology for parallel processing. HyperStar network 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 a construction algorithm of edge-disjoint spanning trees in HyperStar network HS(2n,n). Also, we prove that edge-disjoint spanning tree by the algorithm is optimal.

• The KSFM Journal of Fluid Machinery
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• v.12 no.3
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• pp.7-12
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• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.