• KCID journal
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• v.18 no.2
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• pp.66-75
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• 2011

Multivariate statistical analysis was applied to 110 dam heightening reservoir to classify the building conditions for waterfront centered around cultivated area using data of land cover, landscape, additional water quantity, local economic, tourism resources, and accessibility related variables. Five factors were extracted through factor analysis based on eigen value criteria of more than one. These five factors together account for 68.2% of the total variance. Characteristics of five factors for the downstream of dam heightening reservoirs are building conditions of waterfront, economic conditions, additional water quantity, eco-tours, and accessibility of tourism resources respectively. Five clusters were classified through cluster analysis based on factor score. The classified result shows that third cluster has remunerative terms for building waterfront.

• Journal of the Korean Society of Costume
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• v.37
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• pp.181-190
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• 1998

The purpose of this study was to provide basic information for women's women's head type for mil-inary. The subjects were 141 college women aged from 19∼23. Data were collected from the real anthropometric measurements and 4 index. Correlation coefficientss, factor analysis, cluster analysis and analysis of variance in SAS package. The results were as follows : 4 factors were extracted from 20 anthrometric measurements and in index data, which explain 60.0% of variance. The subjectss were classified into 4 clusters by 11 measurement and 4 index data. Each charicteristics of cluster by the measurements was flat, big, thick, small types in women's head. Each charicteristics of cluster by the index data was mostly flat in head thickness and wide, midium, narrow, very wide type in face.

• 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.

• Journal for History of Mathematics
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• v.11 no.1
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• pp.52-57
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• 1998

Since cluster analysis encompasses many diverse techniques for discovering structure within complex bodies of data, it has been employed as an effective tool in scientific inquiry. Recent works on cluster analysis softwares carried out by SAS, SPSS, S-PLUS and BMDP are briefly summarized and investigated in this paper. The inferred statistical package for windows executing a nay for data analysis in modern statistical techniques has several merits superior to other packages. Especially, S-PLUS can be designed and tried out much faster than other statistical packages. S-PLUS provides a graphic which is interactive, informative, flexible ways of looking at data. Also, if a statistical computation time is long and programs are complex, these can be shorten by providing interfaces to the UNIX systems (or C, Fortran).

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.49-60
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• 2003

The human sensibility product design requires information on consumer's emotions such as vision, auditory, olfactory, gustatory, or tactile perceptions. In this study, tactile sense which has not been well studied compared to other senses, is measured and statistically analysed. The emotional responses of 37 pairs of positive and negative adjectives describing tactile senses are collected and analysed through the questionnaire to find the correlation between adjectives and surface roughness of the sample. Mean ranks for 37 pairs of adjectives on four samples are obtained, and used to cluster these adjectives by factor analysis, multidimensional scaling, or cluster analysis.

• Korean Journal of Plant Resources
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• v.19 no.6
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• pp.716-720
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• 2006

The genetic diversity among the genus Viola was evaluated using the random amplified polymorphic DNA (RAPD) method. A total of 142 distinct amplification fragments by 18 random primers were scored to perform the cluster analysis with UPGMA. Viola species from the subsection Patellares were clustered into group I to IV. The groups from I to IV were consistent with its morphological taxonomy, series Pinnatae, Chinensis, Variegatae, and Patellares in the subsection Patellares, respectively. Even though V. albida and V. albida var. takahasii were classified in Chinensis, they were assigned into group I. The cluster analysis separated other subsections from Patellares in the section Nomimium. Interestingly, V. verecunda and V. grypoceras in subsections Biobatae and Trigonocarpae, respectively, were clustered into group C with a high similarity coefficient. Therefore, RAPD analysis can be used for providing an alternative classification system to identify genotypes and morphological characters of Viola species.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.135-142
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• 2004

The severe frontal crash tests are NCAP with belted occupant at 35mph and FMVSS 208 with unbelted occupant at 25mph, This paper describes the design process of occupant protection systems, airbag and seat belt, under the two tests. In this study, NCAP simulations are performed by Monte Carlo search method and cluster analysis. The Monte Carlo search method is a global optimization technique and requires execution of a series of deterministic analyses, The procedure is as follows. 1) Define the region of interest 2) Perform Monte Carlo simulation with uniform distribution 3) Transform output to obtain points grouped around the local minima 4) Perform cluster analysis to obtain groups that are close to each other 5) Define the several feasible design ranges. The several feasible designs are acquired and checked under FMVSS 208 simulation with unbelted occupant at 25mph.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.75-85
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• 2012

In this study, the representative hand shapes for the adult Koreans were analyzed by factor analysis and cluster analyses. The analyses were conducted on the anthropometric data of 58 hand dimensions from 325 subjects having nonhomogeneous demographics. Maximum hand circumference, first phalanx length of index finger, and ratio between the two measures were the independent variables for the cluster analyses. The results of the study showed that Korean hand shapes can be divided into 2 clusters irrespective of their size for each of the male and female group. There were slight differences in component ratio of hand shapes with respect to the occupation and the age, but their differences were not statistically significant. The representative Korean hand shapes and their anthrpometric dimensions could be used to design and establish proper sizing system for various hand operating devices.

• Journal of Veterinary Science
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• v.22 no.6
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• pp.88.1-88.6
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• 2021

Toxoplasma gondii consists of three genotypes, namely genotype I, II and III. Based on its virulence, T. gondii can be divided into virulent and avirulent strains. This study intends to evaluate an alternative method for predicting T. gondii virulence using hierarchical cluster analysis based on complete coding sequences (CDS) of sag1, gra7 and rop18 genes. Dendrogram was constructed using UPGMA with a Kimura 80 nucleotide distance measurement. The results showed that the prediction errors of T. gondii virulence using sag1, gra7 and rop18 were 7.41%, 6.89% and 9.1%, respectively. Analysis based on CDS of gra7 and rop18 was able to differentiate avirulent strains into genotypes II and III, whereas sag1 failed to differentiate.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.157-163
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• 2023

Recently, as businesses and data types become more complex and diverse, efficient data analysis using machine learning is required. However, since communication in the cloud environment is greatly affected by network latency, data analysis is not smooth if information delay occurs. In this paper, SPT (Safe Proper Time) was applied to the cluster-based machine learning data analysis agent proposed in previous studies to solve this delay problem. SPT is a method of remotely and directly accessing memory to a cluster that processes data between layers, effectively improving data transfer speed and ensuring timeliness and reliability of data transfer.