• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.221-228
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• 2021

Recently, environmental DNA (eDNA)-based metabarcoding approaches have been proposed to evaluate the status of freshwater ecosystems owing to various advantages, including fast and easy sampling and minimal habitat disruption from sampling. Therefore, as a case study, we applied eDNA metabarcoding techniques to evaluate the effects of an abandoned mine land located near a headwater stream of Nakdonggang River, South Korea, by examining benthic macroinvertebrate diversity and compared the results with those obtained using the traditional Surber-net sampling method. The number of genera was higher in Surber-net sampling (29) than in the eDNA analysis (20). The genus richness tended to decrease from headwater to downstream in eDNA analysis, whereas richness tended to decrease at sites with acid-sulfated sediment areas using Surber-net sampling. Through cluster analysis and non-metric multidimensional scaling, the sampling sites were differentiated into two parts: acid-sulfated and other sites using Surber-net sampling, whereas they were grouped into the two lowest downstream and other sites using eDNA sampling. To evaluate freshwater ecosystems using eDNA analysis in practical applications, it is necessary to constantly upgrade the methodologies and compare the data with field survey methods.

• ALGAE
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• v.31 no.1
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• pp.1-16
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• 2016

Paralia species have been frequently reported as P. sulcata in Korea, despite the species diversity within the genus. To understand the species diversity of Paralia in Korea, we collected phytoplankton samples at 79 sites from April 2006 to April 2015. Five Paralia species, P. fenestrata, P. guyana, P. marina, P. cf. obscura, and P. sulcata, were observed during this study, and we described their fine structure in terms of quantitative and qualitative morphological characteristics. To provide additional criteria to identify Paralia species more clearly, we morphometrically analysed four quantitative characteristics on valve diameter: pervalvar axis / diameter, internal linking spines / diameter, marginal linking spines / diameter, and fenestrae/diameter using non-metric multidimensional scaling (MDS). MDS analysis distinguished four Paralia species: P. guyana, P. marina, P. cf. obscura, and P. sulcata, with the exception of P. fenestrata. This new approach in using morphometric analysis is useful for the accurate identification of Paralia species.

• Asian Journal of Business Environment
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• v.7 no.1
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• pp.25-29
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• 2017

Purpose - In this paper, we categorize and segment the 28 national universities in South Korea and measure the degree of dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.

• Proceedings of the Korean Society for Information Management Conference
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• 2010.08a
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• pp.3-6
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• 2010

연구동향 분석이나 연구영역 분석에서 널리 사용되고 있는 다차원척도법은 표현할 개체의 수가 많을 경우에 군집분석 결과와 잘 결합되지 못하는 단점이 있다. 이를 해결하기 위해서 군집분석과 다차원척도법을 결합하는 새로운 방법을 제안하고 실제 사례에 적용해보았다.

• Journal of the korean academy of Pediatric Dentistry
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• v.37 no.2
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• pp.159-167
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• 2010

The purpose of this study was to identify patterns of caries in the dentition of preschool children using cluster analysis and multidimensional scaling. 815 preschool children aged 36-71 months old were examined for caries experience. The first four clusters in the cluster analysis were (1) molars, (2) upper incisors, (3) lower 1st molars, and (4) upper 1st molars in teeth, (1) occlusal surfaces of lower molars and upper 2nd molars, (2) mesial surfaces of upper central incisors, (3) occlusal surfaces of lower 1st molars, and (4) separation between occlusal surfaces of upper and lower 2nd molars in tooth surfaces, and (1) proximal surfaces of upper anterior teeth, (2) occlusal surfaces of lower molars, (3) buccolingual surfaces of upper anterior teeth and (4) buccolingual, proximal, and occlusal surfaces of upper molars and buccolingual and proximal surfaces of lower molars in tooth surfaces groups. In the multidimensional scaling analysis, teeth could be divided into lower 1st molars, upper 1st molars, upper central incisors, upper lateral incisors, lower 2nd molars, upper 2nd molars, and the rest(canines, lower incisors), tooth surfaces could be divided into occlusal surfaces of lower molars, mesial surfaces of upper central incisors, occlusal surfaces of upper molars, and the rest, and tooth surface groups could be divided into proximal surfaces of upper anterior teeth, buccolingual surfaces of upper anteiror teeth, occlusal surfaces of lower molars, and the rest in the order of the distance from others. In the cluster analysis and the multidimensional scaling analysis, caries patterns were different according to the age.

• East Asian Journal of Business Economics (EAJBE)
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• v.7 no.2
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• pp.21-30
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• 2019

Purpose - In this work, we categorize the 21 shopping items which foreign tourists purchase in South Korea and monitor the level of dissimilarity (or similarity) between each item by utilizing distance matrix, and both hierarchical and k-means cluster analyses, respectively, based on several purpose of visit attributes in 2017. In addition, multidimensional scaling (MDS) method is applied for mining visual appearance of proximities among shopping items based on purpose of visit attributes. Research design and methodology - This study is carried out in 2017 by Ministry of Culture, Sports and Tourism and conduct a face-to-face survey of foreign tourists from 20 countries who purchase shopping items in South Korea. CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0 are used to perform this work. Results - We ascertain that 21 shopping items can be classified into five similar groups which have homogeneous traits by going through two-step cluster analysis. We can position homogeneous places of cluster and shopping items joining each cluster. Conclusions - We can relatively assess patterns and characteristics of each shopping item, come by useful information in activating shopping tour based on the actual state of recognition of foreign tourists and practically apply to each tourism industry on underlying results.

• Applied Chemistry for Engineering
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• v.18 no.4
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• pp.366-370
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• 2007

New product development requires information on customers' 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, was measured and statistically analysed for different surface roughnesses of plastic samples. The emotional responses of 37 pairs of positive and negative adjectives describing tactile senses were collected and analysed through the questionnaire to find the correlation between adjectives and surface roughness. Frequency of the first preference for each adjective on four different roughness is obtained, and used for the statistical studies such as factor analysis, multidimensional scaling, or clustering.

• Korean Journal of Ecology and Environment
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• v.53 no.1
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• pp.22-30
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• 2020

In this study, we investigated the relationships between benthic macroinvertebrate assemblages and various environmental factors in Iancheon (NIA) and Bukcheon (NBC) streams, Korea. We collected benthic macroinvertebrates and 33 environmental factors in April 2017 at 9 sites (5 sites in NIA and 4 sites in NBC). We identified 93 species(5 phyla, 9 classes, 16 orders, and 53 families) and 69 species(5 phyla, 9 classes, 17 orders, and 47 families) in NIA and NBC streams, respectively. Considering benthic macroinvertebrate index (BMI), NIA (88.2) and NBC (80.2) streams were in "very good" status. Upstream areas showed the highest scores, 95.5 (NIA1) and 94.2 (NBC1), whereas BMI score was the lowest in downstream areas of both streams, especially in NBC4 (51.0 "bad" status). Cluster analysis and non-metric multidimensional scaling analysis represented the differences of benthic macroinvertebrate assemblages according to spatial and anthropogenic gradients. Our findings provide reference data and highlight the need for the continued monitoring to maintain the good status and manage macroinvertebrate diversity in these two streams, in Sangju-si, Korea.

• Journal of Fashion Business
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• v.7 no.4
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• pp.43-56
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• 2003

The main purpose of this study was to investigate the difference of perceptional degree of imported make-up cosmetics brand and importance of brand image attributes, and the evaluation of brand image attributes of imported make-up cosmetics according to fashion involvement and to provide positioning the imported make-up cosmetics brands according to brand image attributes. Survey was conducted to 301 people from age 20 to 30 year female woman who is leaving in Seoul and Kyunggee Inchon using convenience editing. Material analyzing was done using t-test, factor analysis, cluster analysis, multidimensional scaling. The results were as follows. 1. The perceptional degree of brand and the importance brand image attributes showed significant difference according to fashion involvement. 2. The evaluation of brand image attributes of imported make-up cosmetics were different between high involvement group and low involvement group. 3. As a result of multidimensional scaling, the imported make-up cosmetics brands were positioned different according to brand image attributes between high involvement group and low involvement group.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.167-173
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• 2023

This paper investigates several methods of visualizing high-dimensional data in a low-dimensional space. At first, principal component analysis and multidimensional scaling are briefly introduced as linear approaches, and then kernel principal component analysis, self-organizing map, locally linear embedding, Isomap, Laplacian Eigenmaps, and local multidimensional scaling are introduced as nonlinear approaches. In particular, t-SNE, which is widely used but relatively unfamiliar in the field of statistics, is described in more detail. We also present a simple example for several methods, including t-SNE. Finally, we provide a review of several recent studies pointing out the limitations of t-SNE and discuss the future research problems presented.