• Journal of The Korean Association of Information Education
• /
• v.25 no.6
• /
• pp.1005-1013
• /
• 2021

With the prolonged COVID-19, the existing academic gap is widening. The purpose of this study is to provide homeroom teachers with a visual confirmation of the academic achievement gap in grades and classrooms through academic achievement analysis, and to use this to help them design lessons and explore ways to improve the academic achievement gap. The data of students' Korean and math diagnostic evaluation scores at the beginning of the school year were visualized as clusters using the K-means algorithm, and as a result, it was confirmed that a meaningful clusters were formed. In addition, through the results of the teacher interview, it was confirmed that this system was meaningful in improving the academic achievement gap, such as checking the learning level and academic achievement of students, and designing classes such as individual supplementary instruction and level-specific learning. This means that this academic achievement data analysis system helps to improve the academic gap. This study provides practical help to homeroom teachers in exploring ways to improve the academic gap in grades and classes, and is expected to ultimately contribute to improving the academic gap.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.20 no.6
• /
• pp.1016-1026
• /
• 1996

The purpose of this study was to extract protypes from features and concrete images of Lotus and Crane patterns. A qualitative and a quantitative methods were used. Qualitative informations were obtained from depth Interviews for pattern selection and feature extraction, and quantitative informations from a quail-experiment for pattern caregorization. The subjects were 20 female design students and non-design, students in Teajon. The results were summerized into a similarity metrix which was interpreted by the cluster analysis and the multi-dimensional scling(MDS). The patterns for the study were grouped into 8 clusters. Four dimensions were chosen for the MDS. The location of each pattern was visualized in a 2-dimesional spaces and the location of each cluster in a 3-dimensional spaces. The first dimension, "Lotus" vs "Crane" refired to pattern types, and the second dimension, "realistic" vs "transformable", the transformability. The third dimension, "simple" vs "complex", refired to the degree of simplification, and the forth dimension, "continuous" vs "discontinuous", continuity. The results of the Quantitative analysis could be summerized into 3-level prototype hiararchy In the first level, the patterns were devided clearly into two groups. Lotus and Crane by pattern types. In the second levelk, each group was devided into twosubgroups by continuity. In the third, each subgroup was divided into four subgroups by transformability and the degree of simplification. Four protypes, the final targets of the present study, were extracted from the third level. The are Stylized, Realistic, Decorative, Abstract types.d from the third level. The are Stylized, Realistic, Decorative, Abstract types.

• Korean Journal of Acupuncture
• /
• v.36 no.4
• /
• pp.281-291
• /
• 2019

Objectives : As acupuncture treatment has been widely practiced in many countries around the world, clinical trials of acupuncture treatments also have become popular. The objective of the study was to explore the trends of research investigating the effect of acupuncture treatment in clinical trials using a bibliometric approach, a quantitative analytical methods. Methods : Publications related to clinical trials using acupuncture from 2000 to 2019 were retrieved from the Web of Science database. Extracted articles were analyzed in terms of publication year, country, journal, research area, organizations and authors. Trends in research on acupuncture in clinical trials were visualized using the VOSviewer program. Results : A total of 3,166 articles of acupuncture clinical trials published from 2000 to 2019 were identified and analyzed. The country producing the most articles in this field was USA followed by China, England, South Korea, and Germany. A network analysis based on the co-occurrence of keywords showed following three clusters: clinical studies, pain management studies, and methodology studies. Conclusions : This study provided a macroscopic overview of research in acupuncture clinical trials. These findings provide an expansive strategy for researchers in this field to cooperate with other researchers or organizations.

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

• Journal of Korean Clinical Nursing Research
• /
• v.25 no.3
• /
• pp.209-220
• /
• 2019

Purpose: A significant amount of public opinion about nurse bullying is expressed on the internet. The purpose of this study was to analyze the linkage structures among words extracted from comments on internet articles related to nurse workplace bullying using semantic network analysis. Methods: From February 2018 to April 2019, comments made on news articles posted to the Daum and Naver web portal containing keywords such as "nurse", "Taeum", and "bullying" were collected using a web crawler written in Python. A morphological analysis performed with Open Korean Text in KoNLPy generated 54 major nodes. The frequencies, eigenvector centralities, and betweenness centralities of the 54 nodes were calculated and semantic networks were visualized using the UCINET and NetDraw programs. Convergence of iterated correlations (CONCOR) analysis was performed to identify structural equivalence. Results: This paper presents results about March 2018 and January 2019 because these months had highest number of articles. Of the 54 major nodes, "nurse", "hospital", "patient", and "physician" were the most frequent and had the highest eigenvector and betweenness centralities. The CONCOR analysis identified work environment, nurse, gender, and military clusters. Conclusion: This study structurally explored public opinion about nurse bullying through semantic network analysis. It is suggested that various studies on nursing phenomena will be conducted using social network analysis.

• Fashion & Textile Research Journal
• /
• v.23 no.3
• /
• pp.380-389
• /
• 2021

This study aimed to reveal the perceptions and trends of digital fashion technology through an informational approach. A big data analysis was conducted after collecting the text shown in a web environment from April 2019 to April 2021. Key words were derived through text mining analysis and network analysis, and the structure of perception of digital fashion technology was identified. Using textoms, we collected 8144 texts after data refinement, conducted a frequency of emergence and central component analysis, and visualized the results with word cloud and N-gram. The frequency of appearance also generated matrices with the top 70 words, and a structural equivalent analysis was performed. The results were presented with network visualizations and dendrograms. Fashion, digital, and technology were the most frequently mentioned topics, and the frequencies of platform, digital transformation, and start-ups were also high. Through clustering, four clusters of marketing were formed using fashion, digital technology, startups, and augmented reality/virtual reality technology. Future research on startups and smart factories with technologies based on stable platforms is needed. The results of this study contribute to increasing the fashion industry's knowledge on digital fashion technology and can be used as a foundational study for the development of research on related topics.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.66-71
• /
• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• The Journal of Economics, Marketing and Management
• /
• v.10 no.2
• /
• pp.1-13
• /
• 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 the Korean Society of Visualization
• /
• v.20 no.2
• /
• pp.70-77
• /
• 2022

Skeletal muscle tissues feature cellular heterogeneity, including differentiated myofibers, myoblasts, and satellite cells. Thanks to the presence of undifferentiated myoblasts and satellite cells, skeletal muscle tissues can self-regenerate after injury. In skeletal muscle regeneration, the collective motions among these cell types must play a significant role, but little is known about the dynamic collective behavior during the regeneration. In this study, we constructed in vitro platform to visualize the migration behavior of skeletal muscle cells in specific conditions that mimic the biochemical environment of injured skeletal muscles. We then visualized the spatiotemporal distribution of stresses arising from the differential collectiveness in the cellular clusters under different conditions. From these analyses, we identified that the heterogeneous population of muscle cells exhibited distinct collective migration patterns in the injury-mimicking condition, suggesting selective activation of a specific cell type by the biochemical cues from the injured skeletal muscles.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.4
• /
• pp.41-46
• /
• 2022

The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.