• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.151-152
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• 2012

This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.3
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• pp.25-34
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• 2017

K-means is a popular and efficient data clustering method that only uses intra-cluster distance to establish a valid index with a previously fixed number of clusters. K-means is useless without a suitable number of clusters for unsupervised data. This paper aimsto propose the Group Search Optimization (GSO) using Silhouette to find the optimal data clustering solution with a number of clusters for unsupervised data. Silhouette can be used as valid index to decide the number of clusters and optimal solution by simultaneously considering intra- and inter-cluster distances. The performance of GSO using Silhouette is validated through several experiment and analysis of data sets.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.119-131
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• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.29.1-29.1
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• 2015

We study the environmental dependence of the mass-size relation for the most massive early type galaxies (M > $10^{10.7}M_{\odot}$) in the redshift range 0.10~0.15. As a measure of the environment, galaxy number densities are measured by the $10^{th}$ nearest galaxies within 6500km/s from galaxies with spectroscopic redshifts. The sizes of galaxies are measured by non-parametric method. We find that galaxies more massive than $10^{11.1}M_{\odot}$ show the environmental dependence in the mass-size relation. The galaxies with M > $10^{11.1}M_{\odot}$ located in the densest, cluster like environment have larger sizes and extended surface brightness profiles than their counterparts located in a low dense environment. We also find that the environmental dependence of the mass-size relation is more significant for the brightest cluster galaxies (BCGs) than non-BCGs. Our result can be explained with a hierarchical growth of the most massive galaxies through dissipation-less merger in dense environment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.1
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• pp.56-62
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• 2006

An experimental investigation was performed to study the characteristics of ER(Electro-Rheological) fluid flow in a horizontal rectangular tube with or without D.C voltage. To determine some characteristics of the ER flow, 2D PIV(Particle Image Velocimetry) technique is employed for velocity measurement. This research found the mean velocity distribution with 0kV/mm, 1.0kV/mm and 1.5kV/mm for Re = 0, 0.62, 1.29 and 2.26. When the strength of the electric field increased, the cluster of ERF are clearly strong along the test tube and the flow rate decreased. In this study, the rheology of ER fluid stagnating or flowing through a dispersion meter will be investigated by PIV method. And then the ER effect, which appears at the ER valves and their appliance will be visualized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4272-4286
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• 2016

In resource constrained sensor networks, usage of efficient routing protocols can have significant impact on energy dissipation. To save energy, we propose an energy efficient routing protocol. In our approach, which integrates clustering and routing in sensor networks, we perform network coding during data routing in order to achieve additional power savings in the cluster head nodes. Efficacy of the proposed method in terms of the throughput and end-to-end delay is demonstrated through simulation results. Significant network lifetime is also achieved as compared with other techniques.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.159-166
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• 2002

Today print media survives in tough struggle for existence and is deep to development of new technology as well as edit style and manufacture environment improvement that utilize actively a computer to establish new phase, and Desk Top Publishing or information industry department and link development are required. Propose analysis and solution way that this paper is examining concept of electronic publishing and manufacture progress, and analyze reciprocity degree of electronic publishing process through active and cluster analysis, and electronic publishing knows.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.27-32
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• 2010

This paper presents an investigation into the pinhead forming process with the objective of finding the optimal forming conditions. In order to this, the orbital forming analysis of a heading MIG was carried out using the explicit finite element method. Relationships between temperature by forming of load and stresses, rake angle by forming final shape and stress distribution were investigated through analysises in order to find an efficient solution. As a result, the higher temperature and orbital rake angle were the better forming conditions.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.225-234
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• 2014

We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of large and complex data has attracted significant interest. Symbolic Data Analysis (SDA) was proposed by Diday in 1980's, which provides a new framework for statistical analysis. In SDA, we analyze an object with internal variation, including an interval, a histogram and a distribution, called a symbolic object. In the study, we focus on a cluster analysis for distribution valued dissimilarities, one of the symbolic objects. A hierarchical clustering has two steps in general: find out step and update step. In the find out step, we find the nearest pair of clusters. We extend it for distribution valued dissimilarities, introducing a measure on their order relations. In the update step, dissimilarities between clusters are redefined by mixture of distributions with a mixing ratio. We show an actual example of the proposed method and a simulation study.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.433-444
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• 2016

When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.