• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.2007-2015
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• 2005

A large-scale analysis to evaluate complex material and structural behaviors is one of interesting topic in diverse engineering and scientific fields. Also, the utilization of massively parallel processors has been a recent trend of high performance computing. The objective of this paper is to introduce a parallel process system which consists of general purpose finite element analysis solver as well as parallelized PC cluster. The later was constructed using eight processing elements and the former was developed adopting both hierarchical domain decomposition method and balancing domain decomposition method. Then, to verify the efficiency of the established system, it was applied for structural analysis of steam generator in nuclear power plant. Since the prototypal evaluation results agreed well to the corresponding reference solutions it is believed that, after reinforcement of PC cluster by increasing number of processing elements, the promising parallel process system can be utilized as a useful tool for advanced structural integrity evaluation.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.159-164
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• 2019

Recent developments in ICT technology have increased interest in the care and health of pets such as dogs and cats. In this paper, cluster analysis was performed based on the component data of pet food to be used in various fields of the pet industry. For cluster analysis, the similarity was analyzed by analyzing the correlation between components of 300 dogs and cats in the market. In this paper, clustering techniques such as Hierarchical, K-Means, Partitioning around medoids (PAM), Density-based, Mean-Shift are clustered and analyzed. We also propose a personalized recommendation system for pets. The results of this paper can be used for personalized services such as feed recommendation system for pets.

• Journal of The Korean Association For Science Education
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• v.33 no.3
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• pp.679-693
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• 2013

The purpose of this study is to develop an inventory to classify task commitment types of science learning and to classify highschool students' task commitment types. Firstly, inventory questions were designed following the literature analysis on the task commitment components which involve self confidence, high goal setting, and focused attention. Prototype inventory underwent the content validity test, pilot test, and reliability test. Through these steps, final inventory was input to 462 high school students and underwent the factor analysis and cluster analysis. Factor analysis confirmed three components of task commitment as the three factors of inventory questions. In order to find how many clusters exist, factors of developed inventory became new variables. Each factor's factor mean was calculated and served as the new variable of the cluster analysis. Cluster analysis extracted five clusters as task commitment types. The 5 clusters were suggested by the agglomarative schedule and dendrogram gained from a hierarchical cluster analysis with the setting of the Ward algorithm and Squared Euclidean distance. Based on the factor mean score, traits of each cluster could be drawn out. Inventory developed by this study is expected to be used to identify student commitment types and assess the effectiveness of task commitment enhancement programs.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.4
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.211-227
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• 1992

In this paper we consider the definition and mathematical properties of similarity or dissimilarity which have often used in clust analysis, and we apply a hierarchical agglomerative cluster algorithm to a dissimilarity metrx generated by these distance. Here we investigate the effect of relation between distance function and cluster algorithm on the retrieval ability of natural clusters. We present an empirical results for qualitative data as well as quantitative data.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.219-226
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• 1996

Basic objective in cluster analysis is to discover natural groupings of items or variables. In general, variable clustering was conducted based on some similarity measures between variables which have binary characteristics. We propose a variable clustering method when variables have more categories ordered in some sense. We also consider some measures of association as a similarity between variables. Numerical example is included.

• 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.

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

• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.234-241
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• 2024

Objectives: Health development is a key element of national development. The goal of improving health development at the societal level will be readily achieved if it is directed from the smallest social unit, namely the family. This was the goal of the Healthy Indonesia Program with a Family Approach. The objective of the study was to analyze variables of family health indicators across all provinces in Indonesia to identify provincial disparities based on the status of healthy families. Methods: This study examined secondary data for 2021 from the Indonesia Health Profile, provided by the Ministry of Health of the Republic of Indonesia, and from the 2021 welfare statistics by Statistics Indonesia (BPS). From these sources, we identified 10 variables for analysis using the k-means method, a non-hierarchical method of cluster analysis. Results: The results of the cluster analysis of healthy family indicators yielded 5 clusters. In general, cluster 1 (Papua and West Papua Provinces) had the lowest average achievements for healthy family indicators, while cluster 5 (Jakarta Province) had the highest indicator scores. Conclusions: In Indonesia, disparities in healthy family indicators persist. Nutrition, maternal health, and child health are among the indicators that require government attention.

• Development and Reproduction
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• v.17 no.4
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• pp.363-367
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• 2013

PCR analysis generated on the genetic data showed that the geographic hairtail (Trichiurus lepturus) population from Korea in the Yellow Sea was more or less separated from geographic hairtail population from China in the South Sea. The average bandsharing value ($mean{\pm}SD$) within hairtail population from Korea showed $0.859{\pm}0.031$, whereas $0.752{\pm}0.039$ within population from China. Also, bandsharing values between two hairtail populations ranged from 0.470 to 0.611, with an average of $0.542{\pm}0.059$. As compared separately, the bandsharing values of individuals within hairtail population from Korea were comparatively higher than those of individuals within population from China. The hierarchical dendrogram resulted from reliable oligonucleotides primers, indicating two genetic clusters composed of cluster 1 (KOREANHAIR1~KOREANHAIR11) and cluster 2 (CHINESEHAI12~CHINESEHAI22). The genetic distances between two geographic populations ranged from 0.038 to 0.476. Individual No. 11 within hairtail population from Korea was genetically closely related with No. 10 (genetic distance=0.038). The longest genetic distance (0.476) displaying significant molecular difference was also between individual No. 01 within hairtail population from Korea and No. 22 from Chinese. In the present study, PCR analysis has revealed significant genetic distances between two hairtail population pairs (P<0.05).