• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.103-111
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• 2011

Clustering methods is divided into hierarchical clustering, partitioning clustering, and more. If the amount of documents is huge, it takes too much time to cluster them in hierarchical clustering. In this paper we deal with K-Means algorithm that is one of partitioning clustering and is adequate to cluster so many documents rapidly and easily. We propose the new method of selecting initial seeds in K-Means algorithm. In this method, the initial seeds have been selected that are positioned as far away from each other as possible.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.61-68
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• 2001

A parallel nonlinear analysis program of prestressed concrete frame is migrated on a PC cluster system and a massively parallel processing system, CRAY T3E system, using MPI. The PC cluster system is configured with Pentium Ⅲ class PCs and fast ethernet. The CRAY T3E system is composed of a set of nodes each containing one Processing Element (PE), a memory subsystem and its distributed memory interconnect network. Parallel computing algorithms are implemented on element-wise processing parts including the calculation of stiffness matrix, element stresses and determination of material states, check of material failure and calculation of unbalanced loads. Parallel performance of the migrated program is evaluated through typical numerical examples.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.400-409
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• 2003

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning) by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.200-209
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• 2017

In this paper, we investigate the tradeoff between security and reliability for a multi-hop protocol in cluster-based underlay cognitive radio networks. In the proposed protocol, a secondary source communicates with a secondary destination via the multi-hop relay method in the presence of a secondary eavesdropper. To enhance system performance under the joint impact of interference constraint required by multiple primary users and hardware impairments, the best relay node is selected at each hop to relay the source data to the destination. Moreover, the destination is equipped with multiple antennas and employs a selection combining (SC) technique to combine the received data. We derive closed-form expressions of the intercept probability (IP) for the eavesdropping links and the outage probability (OP) for the data links over a Rayleigh fading channel. Finally, the correction of our derivations is verified by Monte-Carlo simulations.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.101-108
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• 2004

As the dependency to network system and demands of efficient storage systems rapidly grows in every networking filed, the current trends initiated by explosive networked data grow due to the wide-spread of internet multimedia data and internet requires a paradigm shift from computing-centric to data-centric in storagesystems. Furthermore, the new environment of file systems such as NAS(Network Attached Storage) and SAN(Storage Area Network) is adopted to the existing storage paradigm for Providing high availability and efficient data access. We describe the design issues and system components of SANiqueTM, which is the cluster file system based on SAN environment. SANiqueTM has the capability of transferring the user data from the network-attached SAN disk to client applications directly We, especially, present the protocol and functionality of the global buffer manager in our cluster file system.

• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.2007-2015
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• 2005

A large-scale analysis to evaluate complex material and structural behaviors is one of interesting topic in diverse engineering and scientific fields. Also, the utilization of massively parallel processors has been a recent trend of high performance computing. The objective of this paper is to introduce a parallel process system which consists of general purpose finite element analysis solver as well as parallelized PC cluster. The later was constructed using eight processing elements and the former was developed adopting both hierarchical domain decomposition method and balancing domain decomposition method. Then, to verify the efficiency of the established system, it was applied for structural analysis of steam generator in nuclear power plant. Since the prototypal evaluation results agreed well to the corresponding reference solutions it is believed that, after reinforcement of PC cluster by increasing number of processing elements, the promising parallel process system can be utilized as a useful tool for advanced structural integrity evaluation.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.457-461
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• 2008

Previous studies on overlay ad hoc multi-casting are mainly divided into two categories: hierarchical structure-based multicast schemes and non-hierarchical structure-based multicast schemes. They do not reflect their real-time location information for routing updates. This can be a cause of low performance on energy consumption, throughput, and latency. For improving the problems, we propose an implicit cluster based overlay ad hoc multicast scheme with analysis of related work, and then we evaluate performance through computer simulation.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.15-24
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• 2003

In this paper, an optimization model for the clustered node allocation systems in the distributed computing environment is presented. In the presented model with a distributed file system framework, the dynamics of system behavior over times is carefully thought over the nodes and hence the functionality of the cluster monitor node to check the feasibility of the current set of clustered node allocation is given. The cluster monitor node of the node allocation system capable of distributing the parallel modules to clustered nodes provides a good allocation solution using Genetic Algorithms (GA). As a part of the experimental studies, the solution quality and computation time effects of varying GA experimental parameters, such as the encoding scheme, the genetic operators (crossover, mutations), the population size, and the number of node modules, and the comparative findings are presented.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.1-15
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• 2007

In this study 8 nodes parallel linux cluster system is constructed and tested for the evaluation of computational efficiency and reliability of the Yellow Sea tidal hydrodynamics prior to compute storm surge inundation along the west coast of the Korean Peninsular. Computational efficiency increases up to 7 times based on NPB bench-marking test. Simulated results by pADCIRC on reproduction of the Yellow Sea tidal hydrodynamics resemble well with previous studies. According to model parameter tests, bottom friction coefficient, which should be appropriately represented shallow depth along the west coast, is essential factor in simulation.