• Journal of Environmental Science International
• /
• v.11 no.12
• /
• pp.1281-1289
• /
• 2002

This study was conducted to evaluate water quality in the Keum River using multivariate analysis. The analysis data in Keum river made use of surveyed data by the ministry of environment from January 1994 to December 2001. Thirteen water quality parameter were determined on each sample. The results was summarized as follow; Water quality in the Keum River could be explained up to 71.39% by four factors which were included in loading of organic matter and nutrients by the tributaries (32.88%), seasonal variation (16.09%), loading of pathogenic bacteria by domestic sewage of Gapcheon (13.39%) and internal metabolism in estuary as lakes(9.03%). For spatial variation of factor score, four group was classified by each factor characterization. Station 1 and 2 was influenced by Daechung dam, station 3 was affected by domestic sewage of Gapcheon, station 10~12 was affected by estuary dyke and the rest station. The result of cluster analysis by station was classified into four group that has different water quality characteristics. In monthly cluster analysis, three group was classified according to seasonal characteristic. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by Gapcheon inflow domestic sewage in Daejeon city for the sake of water quality management of Keum river.

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

• Review of Culture and Economy
• /
• v.21 no.3
• /
• pp.89-124
• /
• 2018

Although design industry belongs to one of the creative industries and contributes significantly to urban cultural economy based on its cluster formation, researches on design industry are rarely made explicit from the perspective of creative industry cluster. After reviewing the life cycle of design industry clusters in Euljiro and Hongdae Area in Seoul, this study compares these two clusters with respect of diverse dimensions of creative industry cluster such as agglomeration economy, spin-off activities and institutional environments. Research methodology includes the analysis of ?Seoul Business Statistics? and the in-depth interviews with 14 professional designers. The result shows that design industry cluster in Euljiro is close to the traditional industry cluster mainly dependent on printing industry with very limited impact on urban economy, while Hongdae Area develops creative industry cluster by virtue of university spin-offs, art markets, hybrid cultural consumption spaces and the active participation of designers contributing to urban economy in diverse ways. This comparative analysis highlights the importance of various environmental components to encourage creative activities in developing the creative industry cluster.

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

• Journal of the Korea Safety Management & Science
• /
• v.12 no.2
• /
• pp.231-236
• /
• 2010

The investigation was initiated with data from 27 abandoned mines along with 12 locations in Kyongbuk abandoned mines. The analyses for soil pollution by heavy metal pollutants were conducted by using correlation analysis, cluster analysis, and principal component analysis. The correlation analysis indicated that Ni and pH were highly correlated compared to those of other heavy metal ions. The principal component analyses showed that the heavy metal ions might be classified into two catagories, such as antropogenic and lithogenic components. The cluster analysis was also clearly divided by two groups. The respective two groups might be Pb-Zn-Cd-Cu and As-Hg-Ni.

• Journal of Soil and Groundwater Environment
• /
• v.7 no.3
• /
• pp.19-32
• /
• 2002

This study is objected to identify the relations between surface- and shallow ground-water and the seasonal variation of their qualities in watersheds near Muju area. The water type shows mainly Ca-$HCO_3$type. Heavy-metal contamination of surface water is locally detected, due to the mixing with mine drainage. In October nitrate concentration is especially high in densely populated area. Cluster Analysis and Principal Component Analysis are implemented to interpret the complexity of the chemical variation of surface- and ground-water with large amount of chemical data. Based on the cluster analysis, surface-water was divided into five groups and ground-water into three groups. Principal Component Analysis efficiently supports the result of cluster analysis, allowing the identification of three main factors controlling the water quality. There are (1) hydrogeochemical factor, (2) anthropogenic factor and (3) heavy metal contaminated by mine drainage.

• Proceedings of the KAIS Fall Conference
• /
• 2012.05a
• /
• pp.254-257
• /
• 2012

본 논문은 혁신클러스터 추진의 전략방향 설정을 위해서 클러스터 현황을 클러스터 분석을 통하여 살펴보았다. 본 논문에서는 광교테크노밸리의 발전단계에 따른 협력현황 파악을 위하여 산학연 협력체계 분석과 진단을 위한 클러스터분석(Cluster Analysis)을 실시하였다. 클러스터 분석결과 광교테크노밸리내 입주기업의 산학연 협력경험은 67.3%로 매우 높은 것으로 나타났다. 대학과, 기업과는 연구개발, 연구기관과는 장비활용 중심으로 협력하고 있었다. 또한, 산학연 협력의 지원정책수요는 협력기관 현황제공, 기술별 정보취득지원 등 다양한 부문에서 협력의 수요가 존재하고 있었다. 이러한 분석결과를 토대로 다음의 전략이 도출되었다. 첫째, 혁신클러스터 발전을 위한 새로운 비전을 조속히 제시하고 단지인근에서 입주기업의 산학연 협력의 활성화를 위한 지원을 추진해야 한다. 둘째, 혁신클러스터 단계별 발전을 위한 통합적인 지원역량 강화가 필요하다. 마지막으로 인근의 타 혁신거점과 정책적 네트워크 구축을 통해서 타 혁신클러스터의 자원과 역량을 활용할 수 있는 지원망 구축이 필요하다.

• Biomedical Science Letters
• /
• v.10 no.4
• /
• pp.523-528
• /
• 2004

The core factor of the study is integrated environment based PC-Cluster system and high speed access rate up to 155 Mbps, continuous collection system for bioinformatics information at home and abroad. The results of the study are establishment and stabilization of information and communication infrastructure, establishment and stabilization of high performance computer network up to 155 Mbps, development of PC-Cluster system with 32 nodes, a parallelized BLAST on Cluster system, which can provides scalable speedup in terms of response time, and development of collection and search system for bioinformatics information.

• Journal of Information Technology Applications and Management
• /
• v.12 no.3
• /
• pp.41-56
• /
• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.3
• /
• pp.105-112
• /
• 2019

In this paper, we propose a technique to analyze similarity between SQL queries and to assist integrating similar tables. First, the table information was extracted from the SQL queries through the query structure analyzer, and the similarity between the tables was measured using the Jacquard index technique. Then, similar table clusters are generated through hierarchical cluster analysis method and the co-occurence probability of the table used in the query is calculated. The possibility of integrating similar tables is classified by using the possibility of co-occurence of similarity table and table, and classifying them into an integrable cluster, a cluster requiring expert review, and a cluster with low integration possibility. This technique analyzes the SQL query in practice and analyse the possibility of table integration independent of the existing business, so that the existing schema can be effectively reconstructed without interruption of work or additional cost.