• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1633-1639
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• 2010

Recently Wireless sensor networks have been used for many purposes and is active for this study. The various methods to reduce energy consumption, which are actively being studied Wireless sensor network to reduce energy consumption, leading to improve transport efficiency, Cluster can be viewed using the research methods. Cluster method researches consists of a sensor node to the cluster and in among those they take out the Cluster head node and Cluster head node is having collects sensing information of circumferential nodes sensing to sink node transmits. Selected as cluster head sensor nodes so a lot of the energy consumption is used as a cluster head sensor nodes is lose a shorter life span have to be replaced by another sensor node. In this paper, to complement the disadvantages of a cluster-mesh method, proposes to manage memory efficiently about filtering method for sensing data. Filtering method to store the same data sensing unlike traditional methods of data filtering system sensing first sent directly by the hashing algorithm to calculate the hash table to store addresses and Sensing to store data on the calculated address in a manner to avoid duplication occurred later, and sensing data is not duplicated by filtering data to be stored in the hash table is a way.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.3
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• pp.243-246
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• 2009

A cluster-based routing with a hierachical structure for continuous query stream ubiquitous sensor network is proposed in this paper. the proposed method realizes high energy-efficiency by using a head-set instead of head for transmitting node-messages to a base station. By using head-set, the method make network lifetime increased.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.415-422
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• 2012

For statistical microarray data analysis, clustering analysis is a useful exploratory technique and offers the promise of simultaneously studying the variation of many genes. However, most of the proposed clustering methods are not rigorously solved for a time-course microarray data cluster and for a fitting time covariate; therefore, a statistical method is needed to form a cluster and represent a linear trend of each cluster for each gene. In this research, we developed a modified hierarchical mixture of an experts model to suggest clustering data and characterize each cluster using a linear mixed effect model. The feasibility of the proposed method is illustrated by an application to the human fibroblast data suggested by Iyer et al. (1999).

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.5-12
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• 1995

In the case where the set of training vectors constitute clusters, the codevectors of the codebook which is used to compression for speech and images in the vector quantization are regarded as the central vectors of the clusters constituted by given training vectors. In this work, we consider the distribution of Euclidean distance obtaining in the process of searching for the minimum distance between vectors, and propose the method searching for the proper number of and the central vectors of clusters. And then, the proposed method shows more than the about 4[dB] SNR than the LBG algorithm and the competitive learning algorithm

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.122-131
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• 1992

In this paper an approximate solution method for the large-scale Traveling Salesman Problem (TSP) is presented. The method starts with the subdivision of the problem domain into a number of cluster by considering their geometric characteristic. Each cluster has a limited number of nodes so as to get a local solution. They are linked go give the least pathe which covers the whole domain and become TSPs solution with start-and end-node. The approximate local solution in each cluster are obtained based on geometrical properties of the cluster, and combined to give an overall approximate solution for the larte-scale TSP.

• Journal of The Korean Astronomical Society
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• v.27 no.2
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• pp.119-132
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• 1994

The BVR CCD photometry was performed for the globular cluster M13 down to $V=19^m$ over the region from the center to the west 13 arcmin and the CMD of M13 is investigated. The major photometric error in the crowded field which is due to the variation in the sky background was corrected by the median filtering method and the direct sky method. Some characteristics of the CMD of M13 obtained in the present study are as follows: Firstly, the distribution of stars on the CMD is well consistent with the mean lines of Sandage(1970) along the red giant branch(RGB), horizontal branch(HB) and asymtotic giant branch(AGB). Secondly, some gaps exists along the RGB and blue horizontal branch(BHB). Thirdly, the UV-bright stars are more concentrated at the inner region of the cluster.

• Journal of The Korean Astronomical Society
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• v.29 no.2
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• pp.157-170
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• 1996

In order to determine the metallicity of a globuar cluster, M3,by using the spectral indices, a kind of index grid has been establshed by stars in globular clusters, M3, M15, M71 and old open cluster, NGC 188. The indices were measured from the medium resolution spectra of about $2{\AA}$. The summed indices were used to determine metallicity in order to increase signals. It is found that the core depth index is measured more accurately and leads result more accurate than the pseudo-equivalent width index. This method can be further improved by including many more calibration globular clusters of various metallicity to make finer grids. By this method, the metallicity of M3 is determined as $[Fe/H] = -1.46\pm0.15$.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.118-128
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• 2007

The world is interested and actively investing in culture and its cultural contents industry has grown very much. Cultural contents industry is the concentration of human creation and knowledge and the Internet and digital technology have greatly impacted such creation and knowledge. This paper presented a method of digitalization of regional cultural resources, voluntary digitalization strategies, and a method of building an innovative cluster of cultural contents industry. The proposed plan would become the future growth engine of cultural tourism industry.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.281-287
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• 2012

The customer load profile clustering method is used to make the TDLP (Typical Daily Load Profile) to estimate the quarter hourly load profile of non-AMR (Automatic Meter Reading) customers. This study examines how the repeated clustering method improves the ability to discriminate among the TDLPs of each cluster. The k-means algorithm is a well-known clustering technology in data mining. Repeated clustering groups the cluster into sub-clusters with the k-means algorithm and chooses the sub-cluster that has the maximum average error and repeats clustering until the final cluster count is satisfied.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.37-43
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• 2003

Parallel computing method is widely used in the computational fluid dynamics for efficient numerical analysis. Nowadays, low cost Linux cluster computers substitute for traditional supercomputers with parallel computing shcemes. The performance of nemerical solvers on an Linux cluster computer is highly dependent not on the performance of processors but on the performance of network devices in the cluster system. In this paper, we investigated the effects of the network devices such as Myrinet2000, gigabit ethernet, and fast ethernet on the performance of the cluster system by using some benchmark programs such as Netpipe, LINPACK, NAS NPB, and MPINS2D Navier-Stokes solvers. Finally, upon this investigation, we will suggest the method for building high performance low cost Linux cluster system in the computational fluid dynamics analysis.