• Korean Journal of Soil Science and Fertilizer
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• v.41 no.6
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• pp.387-392
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• 2008

It is very important to characterize five major properties of topography, drainage class, soil texture, available soil depth, and gravel content for soil survey. We used multidimensional scaling method for analyzing five major properties for the soils originated from sedimentary rocks to understand their relationships. We simplified 5 major characteristics on soils derived from sedimentary rocks. That is, topographic factor was 15 to 9, soil texture was 32 to 6, drainage class was 6 to 5, available depth was 4, and gravel content was 3. For the viewpoint of eigenvector, from dimension 2, 3 to dimension 1, 4, mountain soils and more fine soils dominated. By eigenvalue, there was no tendency, but in details, was some tendency between small groups. Like this, closely observe exceptional distribution of soils, we need improved intra-group homogeneity based on weight control of soil factor, addition and subtraction of soil factors. Also, we carefully analyzed soil characteristics involved intra-group, then we need reconsideration of past classification units.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.67-75
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• 2018

Multidimensional scaling (MDS) is an exploratory analysis of multivariate data to represent the dissimilarity among objects in the geometric low-dimensional space. However, a general MDS map only shows the information of objects without any information about variables. In this study, we used MDS based on the algorithm of Torgerson (Theory and Methods of Scaling, Wiley, 1958) to visualize some clusters of objects in categorical data. For this, we convert given data into a multiple indicator matrix. Additionally, we added the information of levels for each categorical variable on the MDS map by applying the partition method of Shin et al. (Korean Journal of Applied Statistics, 28, 1171-1180, 2015). Therefore, we can find information on the similarity among objects as well as find associations among categorical variables using the proposed MDS map.

• 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.

• 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.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.1-14
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• 2004

Visualization of documents will help users when they do search similar documents. and all research in information retrieval addresses itself to the problem of a user with an information need facing a data source containing an acceptable solution to that need. In various contexts. adequate solutions to this problem have included alphabetized cubbyholes housing papyrus rolls. microfilm registers. card catalogs and inverted files coded onto discs. Many information retrieval systems rely on the use of a document surrogate. Though they might be surprise to discover it. nearly every information seeker uses an array of document surrogates. Summaries. tables of contents. abstracts. reviews, and MARC recordsthese are all document surrogates. That is, they stand infor a document allowing a user to make some decision regarding it. whether to retrieve a book from the stacks, whether to read an entire article, etc. In this paper another type of document surrogate is investigated using a grouping method of term list. lising Multidimensional Scaling Method (MDS) those surrogates are visualized on two-dimensional graph. The distances between dots on the two-dimensional graph can be represented as the similarity of the documents. More close the distance. more similar the documents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.255-261
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• 2010

The evaluation regarding a transportation policy by an evaluation volition viewpoint there is a difference. Consequently the insurgent analysis which is simple compared to against the evaluation object it was accurate, the analysis which leads the order anger probably is necessary. The research which it sees for the evaluation regarding the transportation policy of the metropolis divided in road being understood, public transportation, parking and pedestrian environment, wide area transportation and transportation information and transportation field whole. And against these field it tried the ALSCAL method and MDPREF method which is a Multidimensional Scale method and it analyzed. The regression analysis result for a dimensional analysis ALSCAL method the case of the transportation policy star improvement degree which it follows in introduction presence of intelligence transportation system and MDPREF method it confronted to the transportation policy star improvement degree which it follows in expansion to construction of specific function appeared with the fact that it is the tendency probably. And the evaluation object and evaluation in the object which will cut the positioning one result was each divided in 4 group. And two methods all it was visible a similar tendency. The ALSCAL method currently transportation system construction degree condition in base and, the MDPREF method currently improvement degree of the transportation policy which it follows in traffic system construction appeared with the fact that it is desirable to establish a hereafter traffic policy in base.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.569-582
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• 2015

This study deals with six spa touristy places to analyze the similarity in image and selection factor recognition through multidimensional scaling method. The result is as following. First, as a result of analysis in the similarity in Image of the 6 touristy Spa places, each "Asan and Onyang" and "Suanbo and Ducksan" form different similar image groups. However, Yoosung does not share the similarity in Image that other Spa places own. Second, as a result of analysis of selection factors in the six touristy spa places, it is found out that there is no big difference in selection factors such as 'spa facility', 'a fee to use', and 'quality of service' in the six spa places. Yet, Onyang, Yoosung, Ducksan, and Suanbo spa reflect high selection factor as 'a recognized spa place' different from Asan and Dogo where the reflection of selection factor is low. Onyang, Yoosung, and Dogo regions reflect high selection factor as a 'Touristy destination' while Asan reflects low selection factor.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.1-9
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• 2019

The purpose of this study is to examine the system of the Jeokbyeok-ga's version using the Computer analysis technique of bibliographies and to examine the achievements of the Jeokbyeok-ga's version studies. First, in order to provide basic data for analysis, a raw corpus was constructed for 46 species of Jeokbyeok-ga. Through this, the common narrative units of the Jeokbyeok-ga were identified as 5 layers, and thus 146 individual paragraphs could be extracted. Based on the encoded corpus, we tried to measure the similarity and the distance between the two. Next, we applied the Multidimensional scaling method, Hierarchical cluster analysis and Cladistic analysis method of the system to confirm the distribution of versions group and it was possible to visually grasp the distance between versions and the system of the work. As a result of analyzing Computer analysis technique of bibliographies, it was found that version's group of the Jeokbyeok-ga was divided into a Wanpan(完板) series and Changbon(唱本) series. Also, it was possible to examine the influence relationship between the Pansori's traditions and transmission.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.946-961
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• 2008

This study aims to provide guidelines on future policy for restructuring the scheme of aid programs associated with If small and medium-sized enterprises (i.e. SME) in Korea. For this purpose, we investigate an empirical dataset of recent aid programs deployed by Ministry of Information and Communication (i.e. MIC) for the last four years First, it is examined that the programs are practiced in accordance with their own policy objective by comparing matching samples between two groups such as program beneficiary and non-beneficiary companies. Second, positioning transition of programs within a same category is visualized in terms of two business portfolio analysis matrices. Third, an affiliation network matrix of (he programs is newly developed and then we attempt to analyze the programs relationship by the application of multidimensional scaling method to the affiliation network matrix. The empirical dataset is composed of two different kinds of corporate datasets. One is a corporate dataset of 8,994 beneficiary companies that are aided by MIC during the year of '03-'06. The other is also a corporate dataset of 18,354 non-beneficiary companies that have no records of the program supports during the years at all. Particularly, the matching samples of non-beneficiary companies are prepared in order to have comparable corporate age years (i.e. CAY) against beneficiary companies' CAY. Results show that; 1) up-to-date, the programs are properly assigned to IT SME conforming to their own policy objective; 2) however, as the year goes on, the following two distinct positioning transitions are revealed such as (1) both CAY and corporate sales (i.e. SAL) are increased simultaneously, (2) ratio of intangible assets (i.e. RIA) is decreased and ratio of operating gain to revenue (i.e. ROR) is increased. Hence, the role of the programs gets weakened with regard to providing seed money to technology innovation-typed IT SME so that a managerial adjustment of the programs is required consequently; 3) even though the model adequacy is not satisfactory through the analysis of multidimensional scaling method, the relationship of indirect-typed programs can relatively be stronger than that of direct-typed programs.