• The Journal of Economics, Marketing and Management
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• v.10 no.2
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• pp.1-13
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• 2022

Purpose: The findings are expected to be used as basic data for policy establishment for systematic support and upbringing of small and medium-sized suppliers through the current status and characteristics of the industrial structure of the MRO consumable materials industry as a whole and the market trend. Research design, data, and methodology: This survey is conducted in 2019 mainly for companies that operate consumable materials delivery business, and the survey size is about 25,000 in advance (selected) and about 2,000 in the main survey. Using cluster analysis and multidimensional scaling, we derive the visualization of the homogeneous grouping of cases and the relationship structure between them. Results: Based on the attributes of reason for not having an online trading system, it is classified into three and four clusters for industry and company size, respectively, and the feature and pattern of each individual can be are relatively evaluated and visualized. Conclusions: Small and medium-sized consumable material suppliers specialize in products rather than fierce pricing strategies or external expansion strategies and it is more effective to establish a plan to promote the growth of both large and small enterprises through cooperation with large corporations.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.503-506
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• 2002

Electrorheological fluids(ERFs) show a rapid and reversible increase in viscosity by applied electric field. It is called the electrorheological effect (ER effect). The reason for ER effect is the induction of an electric dipole in each particle, leading to the formation of clusters in the direction of the field, which resist fluid flow. Generally, the behavior of ER fluids has been modeled on those of Bingham fluids. But there are some differences between Bingham fluids and ER fluids. The visualization of ER fliuds are presented and ER effects by the forming, growing and breaking of clusters are discussed. In the low shear rate area, the pressure drop is measured by a pressure sensor and the formation of ER particles is visualized by video camera. The reason for the nonlinear behavior of ER fluids at low shear rate is explained through results of visualization.

• East Asian mathematical journal
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• v.34 no.2
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• pp.177-189
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• 2018

Recently, Topological Data Analysis (TDA) has attracted attention among various techniques for analyzing big data. Mapper algorithm, which is one of TDA techniques, is used to visualize the cluster diagram. In this study, students were clustered according to the characteristics and degree of mathematics anxiety using a mapper, and students were visualized according to mathematics anxiety. In order to do this, Mathematical Anxiety Scale (Ko & Yi, 2011) in the aspect of mathematical instability in terms of teaching - learning, ie, Nature of Mathematics, Learning Strategy, Test/Performance is used. And the number of questions that measure the anxiety of mathematics can be extracted by extracting the most relevant items among the items that measure the anxiety of mathematics.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.9_10
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• pp.1026-1035
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• 2003

The purposes of this study were to analyze the new lifestyle of female consumer of age in the range of 19∼35 and to investigate their clothing-purchasing behavior and preferred sensation by lifestyle group. The questionnaire survey was carried out on 402 subjects with 31 lifestyle questions, 32 questions of clothing purchasing behavior and 18 questions of preferred sensation. Through factor, cluster analysis and anova using SPSS, we found that the female consumers were composed of 6 lifestyle groups; Traditional Appearance Pursuit(19.4%), Personal Life Pursuit(15.7%), Outer Beauty Pursuit(15.9％), Active Practical Pursuit(11.4%), Digital Leisure Pursuit(13.4%) and Unconcern(21.6%). The location of 6 lifestyle group were visualized in 2-D as the horizontal axis of 'Internal↔Appearance' and the vertical axis of 'Personal↔Collective'. Six groups by lifestyle showed different clothing-purchasing behavior and preferred sensations, and had different socio statistical parameters, such as age, income, job and education.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.147-178
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• 2021

In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

• 한국가시화정보학회:학술대회논문집
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• 2005.12a
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• pp.64-68
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• 2005

In this study, the smoke flows of the inner subway station were visualized through a numerical analysis and visualization experiment in the subway fire. A transparent acrylic model was designed and installed as 1:25th scale-down as the actual subway station by using geometrical similarity The properties of subway fire were reconstructed according to Densimetric Froude Similarity. The 47 to 53 ratio of the mixed air and Helium was inputted in the inner acrylic model to describe 1MW fire intensity with reference to the experiment paper. For the same time, the fire smoke from a smoke generator was inputted in the inner acrylic model with the mixture. At this time, the buoyancy effect of Helium gas went up the smoke to the acrylic model. When the sheet beam of Ar-lon laser was given out to the top and stair of subway model, the digital camcorder took the images of the scattered cluster of smoke particles when applying the smoke management system and PSD.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.99-113
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• 2013

The study investigated the intellectual structure of the library and information science field by journal co-citation analysis on thirty LIS journals with high journal impact factors. Patterns of journal-to-journal citation show the structure of journals in the field, visualized by a networked map of the journals. The result shows journals that can be considered as the core group and as the peripheral group, which corresponds to other studies for investigating the field's intellectual structure using other techniques, such as cluster analysis and multidimensional scaling.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.183-194
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• 2015

This paper proposes a novel method for visualizing the thickness and clearance of 3D objects in a polyhedral representation. The proposed method uses the distance field of the objects in the visualization. A parallel algorithm is developed for constructing the distance field of polyhedral objects using the GPU. The distance between a voxel and the surface polygons of the model is computed many times in the distance field construction. Similar sets of polygons are usually selected as close polygons for close voxels. By using this spatial coherence, a parallel algorithm is designed to compute the distances between a cluster of close voxels and the polygons selected by the culling operation so that the fast shared memory mechanism of the GPU can be fully utilized. The thickness/clearance of the objects is visualized by distributing points on the visible surfaces of the objects and painting them with a unique color corresponding to the thickness/clearance values at those points. A modified ray casting method is developed for computing the thickness/clearance using the distance field of the objects. A system based on these algorithms can compute the distance field of complex objects within a few minutes for most cases. After the distance field construction, thickness/clearance visualization at a near interactive rate is achieved.

• Korean Journal of Occupational Health Nursing
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• v.24 no.2
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• pp.76-85
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• 2015

Purpose: The purpose of this study was to identify knowledge structure of the Korean Journal of Occupational Health Nursing from 1991 to 2014. Methods: 400 articles between 1991 and 2014 were collected. 1,369 keywords as noun phrases were extracted from articles and standardized for analysis. Co-occurrence matrix was generated via a cosine similarity measure, then the network was analyzed and visualized using PFNet. Also NodeXL was applied to visualize intellectual interchanges among keywords. Results: According to the results of the content analysis and the cluster analysis of author keywords from the Korean Journal of Occupational Health Nursing articles, 7 most important research topics of the journal were 'Workers & Work-related Health Problem', 'Recognition & Preventive Health Behaviors', 'Health Promotion & Quality of Life', 'Occupational Health Nursing & Management', 'Clinical Nursing Environment', 'Caregivers and Social Support', and 'Job Satisfaction, Stress & Performance'. Newly emerging topics for 4-year period units were observed as research trends. Conclusion: Through this study, the knowledge structure of the Korean Journal of Occupational Health Nursing was identified. The network analysis of this study will be useful for identifying the knowledge structure as well as finding general view and current research trends. Furthermore, The results of this study could be utilized to seek the research direction in the Korean Journal of Occupational Health Nursing.