• Journal of Environmental Science International
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• v.16 no.5
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• pp.549-559
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• 2007

Vegetation surveys were performed at 45 plots along 10 highways cut slopes in South Korea. Total floral inventory, species richness and exotic plant percentage were obtained within each plot. Life history and life form of each species appeared were analyzed. Community types were classified using hierarchical cluster analysis and detrended correspondence analysis and non-metric multidimensional scaling were conducted from vegetation matrix. 292 species of vascular plants were discovered and the number of natives and exotics were 226 and 66, respectively. There were no significant differences of species richness and exotic plant percentage between cut slopes and rest areas. Hierarchical cluster analysis indicated five clear vegetation associations in cut slopes and rest areas. Detrended correspondence analysis indicated that species composition of total and native plants were similar along the highway cut slopes whereas exotic plants were distributed differentially along the highway cut slopes. in non-metric multidimensional scaling, the studied sites were more separated from each other on the basis of their species composition than the results of detrended correspondence analysis with respect to total, native and exotic plants. The both ordination represented that exotic plants have not been made uniform yet on cut slopes and rest areas by highway corridor in spite of diverse chronosequences after highway construction termination (1 to 22 years). This study showed that the distribution of species composition in exotic plants was different and localized on cut slopes and rest areas of highway in this representative peninsula area of North East Asia and the invasion of exotic plants can retard the process of plant species homogenization.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.83-94
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• 2002

This study was intended to identify fabric impact on decision-making process for clothing purchase, to determine evaluation factors of clothing, and to analyze consumer's preference for fabric on clothing purchase. 396 questionnaires distributed to college students were analyzed by descriptive statistics, oneway ANOVA, correlation, factor analysis and multidimensional scaling. The results are as follows; (1) Fabric impacted on the pre-purchase evaluation and the post-purchase process. (2) 4 factors - physical properties, outer-consciousness, self-satisfaction, and appropriateness- were determined as evaluation factors. Though fabric was included in the physical properties, fabric presented high correlations with other evaluative elements. (3) The most preferred fabric was being composed of natural fiber in fiber contents and having softness in sensation. As a result of multidimensional scaling, 2 dimensions of fabric sensation were developed as 'soft-hard'and 'thin-thick'.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.305-320
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• 2001

다차원선호분석(mutidimensional preference analysis)은 여러 상품들에 대한 개인(또는 그룹)의 선호도를 알아보기 위한 분석방법으로 결과는 보통 2차원 그림으로 제공된다. 본 연구에서는 의미있는 두 가지 최적척도 기준을 제안하고 이와 연관된 행 및 열표시자를 유도하고 있으며, 아울러 사전지식을 반영하기 위해 부분수량화를 다차원선호분석에 도입하는 방법을 제시한다. 또한 본 연구에서 제시한 다차원분석기법들을 실제 인터넷 검색엔진에 대한 선호도 자료에 적용한다.

• The Journal of Korean Society for School & Community Health Education
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• v.7
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• pp.1-17
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• 2006

Background: School is a primary health education setting for adolescents and the continuous support should be provided to renew school health education curriculum correspondent to cultural changes in Korean society. Objectives: This study was conducted to identify the principals and teachers' health education needs for their students and to analyze their conceptual map for health education curriculum at school. Methods: The sample size of the preliminary study was 321 of the teachers in elementary, middle, and high school, and that of the main study was 355 middle school principals and teachers over the country. The self-administered mailing survey was conducted to collect the available health education topics in the preliminary study, to identify the factor structure of the health education topics and to analyze the conceptual properties on health education with exploratory factor analysis and multidimensional scaling analysis in SPSS 12.0. Results: A total of 21 health education topics were collected from the preliminary survey and 31 topics were, comprehensively, generated for the main survey. In exploratory factor analysis, seven factors were generated in 1.0 or greater Eigen value standard. The seven factors were 'life health promotion,' 'disease prevention and drug control,' 'bulling and aggression prevention,' 'injury and sexual harassment prevention,' human-efficacy and regulation,' 'health protection for adolescence,' and 'alcohol and tobacco control.' The educational need scores were the highest in 'human-efficacy and regulation' and 'injury and sexual harassment prevention.' The two-dimensional cooperates were generated for the 31 health education topics and the two dimensional properties which divided the conceptual space were 'health-safety' for one and 'public/environmental-individual/personal' for the other. That is, middle school principals and teachers primarily, understand the health education curriculum in the sense of 'health vs. safety' and 'public/environmental vs individual/personal.' Conclusions: Health education curriculum and textbook should be developed based on teachers' needs and conditions for health education in school fields. The field-based health education programs or textbook would make more possible problem-solving health education for youth in real school fields.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.33-42
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• 2023

Previous emotion studies employing facial expressions have focused on the differences between age groups for each of the emotion categories. Instead, Kim (2021) has compared representations of facial expressions in the lower-dimensional emotion space. However, he reported descriptive comparisons without statistical significance testing. This research used representational similarity analysis (Kriegeskorte et al., 2008) to directly compare empirical datasets from young, middle-aged, and old groups and conceptual models. In addition, individual differences multidimensional scaling (Carroll & Chang, 1970) was conducted to explore individual weights on the emotional dimensions for each age group. The results revealed that the old group was the least similar to the other age groups in the empirical datasets and the valence model. In addition, the arousal dimension was the least weighted for the old group compared to the other groups. This study directly tested the differences between the three age groups in terms of empirical datasets, conceptual models, and weights on the emotion dimensions.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1241-1251
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• 2014

Based on the 4 principal research-performance criteria in 28 national universities in Korea, both cluster analysis and multidimensional scaling are performed in this paper. We can classify and/or specialize the initially unknown groups into a group of relatively homogeneous universities and then create new groupings without any preconceived notion of what clusters may arise. Furthermore, the level of similarity of individual universities can be visualized on the multidimensional space so that each university is then assigned coordinates in each of the 2 dimensions. Both types and characteristics of each university can be relatively evaluated and be practically exploited for the policy of the university authority through these results.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.17.1-17
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• 2001

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.517-528
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• 2018

We provide R scripts to detect outliers in multivariate data and visualization. Detecting outliers is provided using three approaches 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) density-based approach methods. We use the following techniques to visualize detected potential outliers 1) multidimensional scaling (MDS) and minimal spanning tree (MST) with k-means clustering, 2) MDS with fviz cluster, 3) principal component analysis (PCA) with fviz cluster. For real data sets, we use MLB pitching data including Ryu, Hyun-jin in 2013 and 2014. The developed R scripts can be downloaded at "http://www.knou.ac.kr/~sskim/ddpoutlier.html" (R scripts and also R package can be downloaded here).

• Journal of the Korean Society for Library and Information Science
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• v.41 no.2
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• pp.335-357
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• 2007

There has been many studies representing intellectual structures with multidimensional scaling(MDS) However MDS configuration is limited in representing local details and explicit structures. In this paper, we identified two components of MDS mapping approach; one is MDS algorithm and the other is preparation of data matrix. Various combinations of the two components of MDS mapping are compared through some measures of fit. It is revealed that the conventional approach composed of ALSCAL algorithm and Euclidean distance matrix calculated from Pearson's correlation matrix is the worst of the compared MDS mapping approaches. Otherwise the best approach to make MDS map is composed of PROXSCAL algorithm and z-scored Euclidean distance matrix calculated from Pearson's correlation matrix. These results suggest that we could obtain more detailed and explicit map of a knowledge domain through careful considerations on the process of MDS mapping.

• Korean Journal of Social Welfare Studies
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• no.36
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• pp.81-101
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• 2008

The purpose of this study is to analyze characteristics of welfare level for the persons with disabilities in Korean local governments. The study adopted multidimensional scaling and cluster analysis. Based on prior studies and comparative importance research, three indicators were extracted from the welfare circumstance index for the disabled. They are the ratio of the registered disabled population, the ratio of the disabled household in poor households, the ratio of dependence on public finance. Also, nine dimensions and twenty seven indicators were extracted from the welfare level index. The dimensions are as follows : Education, income & economic activities support, welfare services infra-structure, health & welfare service support, movement convenience & safety, rights protection, culture, leisure & information accessibility, welfare administration & budget for the disabled. The findings from the welfare circumstance index show that local governments are divided into three groups and all indicators are statistically significant. On the other hand, the findings from the welfare level index, show that local governments are divided into four groups and five indicators are statistically significant. Based on these findings, the study proposes improvement in the disabled welfare level, and balanced development of local governments.