• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1120-1122
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• 1999

This paper introduces a clustering for Central Control System in New Distribution Automation System. There are three primary benefits to use clustering: improved availability, easier manageability and more cost-effective scalability. Availability: Clustering can automatically detect the failure of an application or server and quickly restart it on a surviving server. Clients only experience a momentary pause in service. Manageability: Clustering lets administrators quickly inspect the status of all cluster resources and easily move workload around onto different servers within a cluster. Scalability: Applications can use the Clustering services through the MSCS Application Programming Interface(API) to do dynamic load balancing and scale across multiple servers within a cluster.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.41-44
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• 2002

The Semiconductor Industrial are developed after 1940. It was called “Rice of Industrial”. It needs great effect in Electronics. It was developed highly in recent several years with semiconductor manufacturing equipments. Semiconductor manufacturing devices are developed “In-line” type in the first stage. But It was non-effective in modem many type process. Because this reason, Cluster type manufacturing equipments are proposed. Cluster have ability of many-type-process and effective-scheduling by circular type process chamber In this paper. we propose a real-time 3D monitoring and simulation of this semiconductor manufacturing equipments. By proposed monitoring method, we have capability real visual maintanance & virtual simulation. This effective visual 3D monitoring could apply another dangerous environment in entire industrial.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.75.3-75.3
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• 2017

We Investigate dust stripping of Virgo cluster galaxies that are known to suffer HI gas stripping. The gas stripping phenomena of these galaxies may result from either ram pressure induced by the hot intracluster medium or gravitational tidal interactions between galaxies. While much efforts have been made to directly detect gas removed from cluster galaxies, the spatial distributions of dust, which should also be affected, are hardly known. Several previous studies have tried to directly detect the morphology of gas or dust using radio or infrared observations, but such approaches are hard to widely apply because of the limit of observational resolution and sensitivity. In this study, we try a different approach using optical data: measuring the background galaxy reddening by the dust stripped from the Virgo cluster members. Based on optical color excess maps of the background galaxies, we compare the ambient dust distribution with the HI morphology of the Virgo galaxies. We discuss how efficiently dust stripping can be detected with this method and how the stripped dust is associated with the removed gas according to HI gas stripping stage over the sample.

• Journal of Life Science
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• v.13 no.5
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• pp.590-595
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• 2003

The objective of this study was to assess of genetic variation within and between pumpkin species including Cucurbita maxima, C. moschata, C. pepo and C. maxima${\times}$C. moschata using RAPD markers. The 16 primers showed the amplification of 136 scorable fragments ranging from about 100 bp to 2300 bp. A total of 94 DNA fragments were polymorphic with an average 5.9 polymorphic bands per primer. A species $(C. maxima\timesC. moschata)$ has the highest number of polymorphic loci. Based on obtained data, UPGMA cluster analysis was conducted. Twenty pumpkin cultivars were classified into three large categories and identified genetic distance of cluster ranging from 0.38 and 1.00. Clustering was in accordance with the division of Curcurbitaceae into four species, C. maxima, C. moschata, C. pepo and C. $C. maxima\timesC. moschata$. Therefore, RAPD method may be essential tool for enabling discrimination of pumpkin cultivars.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.143-153
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• 1994

Cluster analysis is a primitive technique in which no assumptions are made concerning the data structure. And the number of groups is known a priori discriminant analysis provides an information how well N individuals are classified into their own groups. In this study, clustering, which is any partition of a collection of data points, generated by the application of eight hierarchical clustering methods was re-classified by discriminant analysis. Then correct classification ratios were obtained for the application of discriminant analysis through each clustering method and the direct application of discriminant analysis. By comparing the correct classification ratios, the applicability of cluster analysis and discriminant analysis considered.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.50.3-51
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• 2017

Discovered in the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey, the galaxy cluster SPT-CL J0205-5829 at z = 1.322 might be the most massive known SZ-selected galaxy cluster at z > 1.2. The SZ and X-ray combined mass estimate is $M500=(4.8{\pm}0.8){\times}10^{14}M_{\odot}$. To confirm this extreme mass, we perform weak lensing analysis of SPT-CL J0205-5829 using HST data. Our analysis produces a mass estimate consistent with the previous results obtained from non-lensing methods. In this poster, we describe details of the method including shape measurement, PSF correction, source selection, and mass estimation. We also present a two-dimensional mass map and compare this to the galaxy distribution.

• International Journal of Advanced Culture Technology
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• v.5 no.3
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• pp.40-45
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• 2017

This data mining technique was used to extract useful information from percutaneous coronary intervention data obtained from the US public data homepage. The experiment was performed by extracting data on the area, frequency of operation, and the number of deaths. It led us to finding of meaningful correlations, patterns, and trends using various algorithms, pattern techniques, and statistical techniques. In this paper, information is obtained through efficient decision tree and cluster analysis in predicting the incidence of percutaneous coronary intervention and mortality. In the cluster analysis, EM algorithm was used to evaluate the suitability of the algorithm for each situation based on performance tests and verification of results. In the cluster analysis, the experimental data were classified using the EM algorithm, and we evaluated which models are more effective in comparing functions. Using data mining technique, it was identified which areas had effective treatment techniques and which areas were vulnerable, and we can predict the frequency and mortality of percutaneous coronary intervention for heart disease.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.177-180
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• 2002

This paper introduces a new distributed QoS (Quality of Service) control system for clusters of web servers. The proposed system can employ not only network bandwidth but also other metrics such as processor load, memory usage, and storage access load that affect the overall system performance. Moreover, it controls over clustered\ulcorner workstations in of-der to utilize idle resources among workstations. This architecture maximizes overall usage of cluster of web servers while it provides predictable and differentiated performance for each contents volume. We implemented a prototype of introduced system, and the test results showed the proposed method can control QoS in a cluster server system.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.83-88
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• 2010

This paper has analyzed Seoul metropolitan area on the basis of cluster characteristics and it is to understand the traits of each clusters. In order to modelize the area, 10 different indicators were selected among components of a city such as population, activities, land and facilities. Also through principal component analysis, similar characteristics or congenialities of the variables were derived as a common factor. The result was organized by factor score from hierarchical clustering method and as a final result, metropolitan area was clustered into five areas.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.41-47
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• 2012

MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.