• International Commerce and Information Review
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• v.9 no.3
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• pp.33-57
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• 2007

This study tests e-business performance difference of the inter group by strategy type through the cluster analysis, after confirming the linear relationship between the e-business strategy type and its performance. According to the result of the study the effect on the e-business performance reveals to differ by the e-business strategy type. That is to say, while the firm's information system performance, e-business realization and the inter group competition dominance are affected positively by the e-process strategy, web application strategy and customer attracting strategy. This confirms that the information system performance, the realization performance and the competition dominance are affected by e - business strategy type. The key factor leading to the success of e-business is the commitment of e-process strategy and web application strategy. For the case of the customer attracting strategy the result shows the importance of the strategy. In the cluster group analysis, the additional analysis, the effect is seen to be more powerful in the firm's information system performance, e - business realization and securing the competition advantage for the case of the multiple strategy than that of single one. Accordingly, the firm needs to adopt the multiple strategy suited for the characteristic of the firm rather than the single strategy.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.3
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• pp.437-456
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• 2016

The purpose of this study is to understand the locational characteristics of performing art industries and to investigate the linkages with local economy. For the purpose, we examine the spatial concentration of cultural and artistic resources in Korea first, and than focus on Seoul where the resources of performing art industries are concentrated to the utmost. To distinguish the distribution aspect and locational characteristics of performing art industries, we apply the Kernel density analysis and LISA (Local Indicator of Spatial Association) on the address data of performing art theater, gallery, and movie theater. In contrast to galleries and movie theaters. the spatial distribution pattern of performing art theaters reveals a unique local cluster centered on the Daehakro area. We confirm that the Daehakro area constitutes a performing art industry cluster in their dense distribution of various related activities making up the value chain of the performing art industry. Multiple regression analysis probes the related economic activities to explain the distribution of performing art theaters as well as the linkages with the local economic landscape.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.2
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• pp.184-189
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• 2000

This study was conducted to develop the objective evaluation method for tobacco smoke. The evaluation was carried out by using the data of cut or blended tobacco components, smoke components, electric nose system (ENS), and sensory test. By using the statistical methods, such as cluster analysis, discriminant analysis, factor analysis, correlation analysis, and multiple regression analysis, the relationship among the data of tobacco, smoke, ENS, and sensory evaluation was studied. By the results of cluster analysis, the data from smoke analysis by GC and ENS were able to select the difference of tobacco leaf characteristics. As the results of discriminant analysis, grouping by the components of tobacco leaves and smoke was possible and the results of GC analysis of smoke could be used for discrimination of tobacco leaves. In the results of factor analysis, nicotine, tar, CO, puff No and pH in the smoke were the factors effecting on the tobacco leaf characteristics. From the correlation analysis, aroma, taste, irritation, and smoke volume of sensory test had high relation to tar, p-cresol threonolatone, levoglucosane, and quinic acid- ${\gamma}$ -lactone of smoke. The ENS data showed high efficiency for discriminant analysis and cluster analysis, but it was not good for factor analysis, and correlation analysis. It was possible to estimate tobacco leaves and their blending characteristics by the analytical data of tobacco leaves, smoke, ENS, and sensory test results. By the multiple regression analysis, some correlation among selected chemical components and sensory evaluation were found. This study strongly indicated that the some chemical analysis data was available for the objective evaluation of tobacco sensory attributes.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.199-206
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• 2006

Sequential pattern mining is an important data mining task with broad applications. However, conventional methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivial patterns but fail to find interesting patterns shared by many sequences. In this paper, to overcome these problems, we propose the theme of approximate sequential pattern mining roughly defined as identifying patterns approximately shared by many sequences. The proposed method works in two steps: one is to cluster target sequences by their similarities and the other is to find consensus patterns that ire similar to the sequences in each cluster directly through multiple alignment. For this purpose, a novel structure called weighted sequence is presented to compress the alignment result, and the longest consensus pattern that represents each cluster is generated from its weighted sequence. Finally, the effectiveness of the proposed method is verified by a set of experiments.

• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.401-408
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• 2015

Horticultural traits and genetic relationship were evaluated for 83 melon (Cucumis melo L.) cultivars. Survey of a total of 36 characteristics for seedling, leaf, stem, flower, fruit, and seed and subsequent multiple analysis of variance (MANOVA) were conducted. Principal component analysis (PCA) showed that 8 principle components including fruit weight, fruit length, fruit diameter, cotyledon length, seed diameter, and seed length accounted for 76.3% of the total variance. Cluster analysis of the 83 melon cultivars using average linkage method resulted in 5 clusters at coefficient of 0.7. Cluster I consisted of cultivars with high values for fruit-related traits, Cluster II for soluble solid content, and Cluster V for high ripening rate. Genotyping of the 83 cultivars was conducted using 15 expressed-sequence tagged-simple sequence repeat (EST-SSR) from the Cucurbit Genomics Initiative (ICuGI) database. Analysis of genetic relatedness by UPGMA resulted in 6 clusters. Mantel test indicated that correlation between morphological and genetic distance was very low (r = -0.11).

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.629-640
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• 2003

A shared disk (SD) cluster couples multiple nodes for high performance transaction processing, and all the coupled nodes share a common database at the disk level. In the SD cluster, a transaction routing corresponds to select a node for an incoming transaction to be executed. An affinity-based routing can increase local buffer hit ratio of each node by clustering transactions referencing similar data to be executed on the same node. However, the affinity-based routing is very much non-adaptive to the changes in the system load, and thus a specific node will be overloaded if transactions in some class are congested. In this paper, we propose a dynamic transaction routing scheme that can achieve an optimal balance between affinity-based routing and dynamic load balancing of all the nodes in the SD cluster. The proposed scheme is novel in the sense that it can improve the system performance by increasing the local buffer hit ratio and reducing the buffer invalidation overhead.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.36.2-36.2
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• 2012

The aim of this study was to explore the role of galaxy mergers on the formation and evolution of galaxies in galaxy clusters. For this purpose, u', g', r' deep optical imaging and multi-object spectroscopic observation were done for four rich Abell clusters at z ${\lesssim}$ 0.1 (A119, A2670, A3330, and A389) with a MOSAIC 2 CCD and Hydra spectrograph mounted on a Blanco 4-m telescope at CTIO. With the deep images, we found that about 25% of the bright red-sequence galaxies exhibited post-merger signatures in a cluster environment. This fraction was much higher than what was expected from the results of the field environment (-35%, van Dokkum 2005) and significantly low on-going merger fractions (about one-fifth of the field) appeared in the clusters currently. Taking advantage of the most up-to-date semi-analytic model, the results indicate that most of the post-merger galaxies may have carried over their merger features from their previous halo environment. All the brightest cluster galaxies in our cluster samples revealed faint structures in their halos as well as multiple nuclei in their centers seen in the deep optical images. We suggest that the mass of the BCGs increased mainly though major mergers at recent epochs based on their post-merger signatures and the large gaps in the total magnitudes between the BCGs and the second-rank BCGs. A UV bright tidal tail and tidal dwarf galaxy (TDG) candidates around the post-merger galaxy, NGC 4922, were discovered in the outskirts of the Coma cluster using the GALEX UV data. We did two-component stellar population modeling for the TDG candidates and the results indicate that they are an early form of dwarf galaxies frequently found around massive early-type galaxies in clusters. In conclusion, we suggest that the mergers of galaxies are an important driving force behind galaxy formation and evolution in cluster environments even until recent epochs.

• The Korean Journal of Ecology
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• v.23 no.1
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• pp.25-32
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• 2000

To analyze the relationship between climatic factors (monthly temperatures and precipitations) and the radial growths or Pinus densiflora with different topographical settings in Worak National Park, Korea, 20 stands were chosen and 10 trees were selected from each stand. After crossdating, each ring-width series was double detrended (standardized) by fitting first a negative exponential or straight regression line and secondly a 60-year cubic spline. The growth patterns coud be categorized by four groups using cluster analysis. Cluster Ⅰ stand has north aspect, but others have south or southwest aspects. Cluster Ⅰ (one), cluster Ⅱ (ten), and cluster Ⅲ (two) stands are located in lower. elevation (305∼580 m), however, cluster Ⅳ (seven) stands are located in higher elevation, mostly in 560～870 m. Cluster Ⅱ and Ⅲ stands are located at similar elevation with the same aspect, however, cluster Ⅱ stands are located on more rocky and stiff slope with shallow soil depth. The response functions were used to examine the difference in the relationships between climatic factors and tree growths among the 4 cluster chronologies. The climatic factors are not limiting the growth in the cluster Ⅰ stand as highly as in other cluster plots because of rather mesic conditions in the north slope. The precipitation in the spring appears to be the main limiting factor in the cluster Ⅱ stands. The topographical characteristics of the sites of cluster Ⅱ, shallow soil depths on the rocky slope in the south aspect at lower elevation, may enhance the sensitivity of growth to moisture stress. In cluster Ⅲ and cluster Ⅳ, winter and spring temperature prior to the growth become more important than for cluster Ⅱ. This pattern is com-mon for Pinus densiflora trees growing in higher. elevation (equation omitted 800 m) in South Korea. It nay be re-lated with preconditioning effects of temperature as the temperature decreases with increasing elevation (cluster Ⅳ) or in the valley (cluster Ⅲ). The results obtained by tree-ring analysis were digitalized by GIS and spatio-temporal information on tree-ring data and topographic setting were analyzed and displayed simultaneously. The results of this study can be used to predict the future change of Pinus densiflora ecosystem to climate change expected in central Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.145-152
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• 2010

Bayesian information criterion is used to do clustering for time series data. To acquire more stable clusters, multiple seeds are chosen first for the algorithm. Once clusters being set up, most similar time series data in the cluster to the one under consideration are to be chosen for prediction test. These chosen time series data are used to extract valid Markov rules by which we test the prediction accuracy. We confirmed that clustering with multiple seeds led to better prediction performance.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.719-732
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• 2006

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.