• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.387-394
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• 2007

This paper considers several stratification strategies for multivariate and multipurpose survey with several quantitative stratification variables. We propose three methods of stratification based on, respectively, the method of cumulative frequency square root which is the most popular one in univariate stratification, cluster analysis, and factor analysis followed by cluster analysis. We then compare the efficiency of those methods using the Dong-Eup-Myun data of the holding numbers of farming machines, extracted from the 2001 Agricultural Census. It turned out that the method based on cluster analysis with factor analysis would be a relatively satisfactory strategy.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.571-571
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• 2012

We discovered the formation of C60 aggregates in solution by means of photoluminescence spectroscopic study on C60 in solutions. From the in-depth investigation of temperature dependence of the luminescence of C60 in toluene, benzene and CS2 solutions, we reported that the C60 aggregates are formed during cooling at the freezing temperature of these solvents. Furthermore, the C60 aggregates can be changed to stable structures by irradiating with UV pulse-laser (Nd:YAG laser, 355nm). As a consequence, we could obtain nano-scale photo-polymerized C60 clusters, which appear as round-shaped nano- scale particles in high resolution transmission electron-microscopy (HRTEM) images. However, the yield of the nano-scale C60 clusters obtained by this method is too small. So we designed and developed a system to obtain C60 cluster of macroscopic quantity by using ultrasonic nebulizer. In this system, C60 solution was vaporized to several micro-sized droplets in vacuum, resulting in the formation of C60 aggregates by evaporating solvent (toluene). The system was invented to produce nano-scale carbon clusters by the irradiation of UV light upon C60 aggregates in vacuum. We have characterized the products, C60 cluster, obtained from the system by using UV absorption spectra and HPLC spectra. Although the products have a possibility of inclusion various forms of C60 cluster, results support that the product formed from the system by using vaporizer method establishes a new method to obtain C60 cluster in macroscopic quantity. In the presentation, the details of the system and the results of characterization are reported.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.248-257
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• 2002

Clustering is a method for grouping objects with similar properties into a same cluster. SVD(Singular Value Decomposition) is known as an efficient preprocessing method for clustering because of dimension reduction and noise elimination for a high dimensional and sparse data set like E-Commerce data set. However, it is hard to evaluate the worth of original attributes because of information loss of a converted data set by SVD. This research proposes a cluster feature selection method, called ENTROPY-SVD, to find important attributes for each cluster based on entropy weighting and SVD. Using SVD, one can take advantage of the latent structures in the association of attributes with similar objects and, using entropy weighting one can find highly dense attributes for each cluster. This paper also proposes a model-based collaborative filtering recommendation system with ENTROPY-SVD, called CFS-CF and evaluates its efficiency and utilization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.17-25
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• 2018

Recently, with the development of ICT technology and the rapid spread of smart devices, a huge amount of information is being generated. The recommendation system has helped the informant to judge the information from the information overload, and it has become a solution for the information provider to increase the profit of the company and the publicity effect of the company. Recommendation systems can be implemented in various approaches, but social information is presented as a way to improve performance. However, no research has been done to utilize trust cluster information among users in the recommendation system. In this paper, we propose a method to improve the performance of the recommendation system by using the influence between the intra-cluster objects and the information between the trustor-trustee in the cluster generated in the online review. Experiments using the proposed method and real data have confirmed that the prediction accuracy is improved than the existing methods.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.119-124
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• 2008

The LEACH is a study method of a clustering base that was representative in many routing techniques that was suggested in sensor network environment. This is suggested technique to manage the sensor network group which consisted of many sensors in efficiency. However, it does not consider energy remaining quantity of the cluster header to manage cluster group, the problem where the cluster group is able to destroyed on the middle which transmits data. We are going to propose to solve such a problem by this paper for new clustering technique to accomplish management for a cluster group. It uses the technique which it proposes from the dissertation which it sees and are to the data transfer and the control also the connection directivity of the cluster group to improve also the lag time diminishes, test result it will lead and the possibility which it will know it was.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.3-17
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• 2004

With the rapid growth of the Internet geographic information services through the WWW such as a location-based service and so on. Web GISs (Geographic Information Systems) have also come to be a cluster-based architecture like most other information systems. That is, in order to guarntee high quality of geographic information service without regard to the rapid growth of the number of users, web GISs need cluster-based architecture that will be cost-effective and have high availability and scalability. This paper proposes the design of the cluster-based web GIS with high availability and scalability. For this, each node within a cluster-based web GIS consists of main memory spatial databases which accomplish role of caching by using data declustering and the locality of spatial query. Not only simple region queries but also the proposed system processed spatial join queries effectively. Compare to the existing method. Parallel R-tree spatial join for a shared-Nothing architecture, the result of simulation experiments represents that the proposed spatial join method achieves improvement of performance respectively 23% and 30% as data quantity and nodes of cluster become large.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.435-444
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• 2007

Caching web pages is an important part of web infrastructures. The effects of caching service are even more pronounced for wireless infrastructures due to their limited bandwidth. Medium to large-scale infrastructures deploy a cluster of servers to solve the scalability problem and hot spot problem inherent in caching. In this paper we present scheduling scheme based on cache utilization in a wireless internet proxy server cluster environment. The proposed method uses cache utilization for distributing evenly client requests to a cluster of cache servers and solving hot spot problem. We have implemented our approach and performed various experiments using publicly available traces. Experimental results on a cluster of 16 cache servers demonstrate that the proposed hashing method gives 45% to 114% Performance improvement over other widely used methods while addressing the hot spot problem.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.39-46
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• 2010

The growth of function in vehicle needs complex display and control system, the In-Vehicle Information System(IVIS). Although current IVISs are widely implemented in commercial vehicles, a new form of IVIS has been recently studied in order to reduce drivers' workloads. The purpose of this study is to suggest an appropriate menu structure of a new type IVIS, to be implemented on the instrument cluster panel, using Taguchi's parameter design. In the research, firstly, functions were selected that are appropriate to control through the instrument cluster among existing functions of current IVISs by quantitative evaluation of ergonomic principles. Then, menu structure alternatives were extracted by investigating priorities to those functions selected. Finally, menu structure alternatives were evaluated through an experiment and suggest the most appropriate one by applying Taguchi's parameter design. Taguchi method was used not only for planning an experiment but also evaluating alternatives. SN ratios were a key value to evaluate the alternatives and to find the most proper one. Through the research, the most appropriate menu structure for the instrument cluster IVIS was finally suggested among the alternatives and it is expected that the results of this research could provide a guideline to the instrument cluster IVIS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5865-5872
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• 2011

Multi-hop communication in clustering system is the technique that forms the cluster to aggregate the sensing data and transmit them to base station through midway cluster head. Cluster head around base station send more packet than that of far from base station. Because of this hot spot problem occurs and cluster head around base station increases energy consumption. In this paper, I propose a cluster group head selection using trajectory clustering technique(CHST). CHST select cluster head and group head using trajectory clustering technique and fitness function and it increases the energy efficiency. Hot spot problem can be solved by selection of cluster group with multi layer and balanced energy consumption using it's fitness function. I also show that proposed CHST is better than previous clustering method at the point of network energy efficiency.