• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.490-505
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• 2017

The purpose of this study was to analyze the research trend of transformational leadership published in domestic journals in the last 10 years and to find some implications for future research. For this purpose, 337 research papers on transformational leadership from 2007 to 2016 were reviewed. This study used descriptive statistics by frequency and percentage and a network text analysis method. The findings of the study are as follows. First, the annual average number of papers published was 33. Second, 'human resource management research' was the most common topic. Third, most of the research subjects were business employees. Fourth, the research method trend analysis showed that the highest proportion was in the quantitative research. Fifth, 'transactional leadership' showed the highest frequency as a result of analyzing the keywords presented in the abstract of the paper. Sixth, as a result of analyzing the network texts, those having the trend of being analyzed with a close connections were 'transactional leadership', which had the highest connection to transformational leadership, showing the closest relationship with 'role satisfaction'.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.415-423
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• 2017

This study explored research trends by investigating articles published in the Journal of Korean Society of Fashion Design from 2001 through 2015. English key words and abstracts were analyzed using text mining and topic modeling techniques. The findings are as followings. By the text mining technique, 183 core terms, appeared more than 30 times, were derived from 7137 words used in total 338 articles' key words and abstracts. 'Fashion' and 'design' showed the highest frequency rate. After that, the well-received topic modeling technique, LDA, was applied to the collected data sets. Several distinct sub-research domains strongly tied with the previous fashion design field, except for topics such as fashion brand marketing and digital technology, were extracted. It was observed that there are the growing and declining trends in the research topics. Based on findings, implication, limitation, and future research questions were presented.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.345-368
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• 2012

As science and technology are the core engines of economic and social affairs, it is becoming increasingly necessary to explore new promising technologies in order to secure competitiveness in science and technology with a view to helping upgrade the country's overall competitiveness and promoting industrial development. The governments of major advanced countries provide R&D support for promising future technologies. Even in South Korea, a study is being carried out to set up a model for forecasting future technologies and reinforcing the relevant survey system. This study intends to explore methods of identifying promising future technologies in the bio-science sector, which has emerged as a new growth engine. It will use a text-mining technique to collect and analyze theses in the bio science sector. It will identify key research sectors by analyzing thesis contour lines, and then review promising future key research subjects through in-depth study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.721-732
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• 2021

This study analyzed keywords for agricultural R&D using the textmining method to examine the trend of agricultural R&D. Data used for the analysis included R&D project information provided by NTIS, and the research and development step by year from 2003 to 2018 were classified and applied. The TF-IDF approach was used as the analysis method, and ranking was derived based on score. Furthermore, we analyzed by grouping for similar keywords. The main analysis results are as follows. First, agricultural R&D trends are changing according to the introduction of new technologies and changes in the external environment. Second, keyword changes appeared with a time lag in the R&D step. The main keywords are changing in the order of basic research - applied research - development research. Third, the main keyword of agricultural R&D was 'rice.' However, the direction and purpose of the research were changing according to changes in the domestic and foreign agricultural environments.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.41-50
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• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.47-60
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• 2002

The study investigated the effects of types of presentation and cognitive load on multimedia learning. In experiment 1, subject were 90 elementary school students. The subject were assigned in three conditions: Narration and Text (NT) condition, Animation and Narration(AN) condition, Animation and Text(AT) condition. The result showed that AN condition improved the learning performances in comparison with AT condition, NT condition. Experiment 2 was administrated to 87 undergraduate students. They were participated in three conditions, also. The conditions were Animation and Text (AT) condition, Animation and Narration (AN) condition, Animation, Narration and Text (ANT) condition. the results showed that AN condition was greater in AT, ANT condition. The results from a series of these experiments imply that varying the types of presentation of identical learning materials had influences on the performances. Multimedia presentation(animation and verbal conditions) improved the learning performances in comparison with monomedia presentation(verbal condition), and the advantage was raised when learners were provided the learning material in the multimodal and multimedia environment(AN condition). Also, it came out that redundant text identical to narration disrupted learning when learners were in the picture (either animation or illustration) and narration conditions. Likewise, also for adults, performances were improved in the multimodal conditions and redundant text identical to narration was not helpful for learning. These results are evidences for the dual-coding theory and the cognitive load theory.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.53-82
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• 2012

The purpose of this paper is to show the clustering trend by using the context-dependent and measure-specific models for 38 Asian ports during 10 years(2001-2009) with 4 inputs and 1 output. The main empirical results of this paper are as follows. First, clustering results by using context-dependent and measure-specific models are same. Second, the most efficient clustering was shown among the Hong Kong, Singapore, Ningbo, Guangzhou, and Kaosiung ports. Third, Port Sultan Qaboos, Jeddah, and Aden ports showed the lowest level clustering. Fourth, ranking order of attractiveness is Guangzhou, Dubai, HongKong, Ningbo, and Shanghai, and the results of progressive scores confirmed that low level ports can increase their efficiency by benchmarking the upper level ports. Fifth, benchmark share showed that Dubai(birth length), and HongKong(port depth, total area, and no. of cranes) have affected the efficiency of the inefficient ports.

• Cartoon and Animation Studies
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• s.41
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• pp.169-185
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• 2015

This thesis will observe and study the acting pattern and subtext of Ahn, Sung-kee who is known to be "The Nation's Actor" in South Korea's movie industry and currently has been on the screen with multiple different characters in about 120 films. He started his career as a child actor in Kim, Ki-young's movie at the age of five. Ahn is exceptional at communicating through solely on screen in terms of delivering characters' characteristics to audience with variety of characters. We provided some of the acting patterns he has shown in different roles of characters that he played such as in comedic, mellow and extraordinary acting. Following will be analysis on subtext of Professor Kim, Kyung-ho the role Ahn played in Jung, Ji-young's movie in terms of what type of factors was prepared and how it has delivered in each important scene. Generally, acting's basic skills and talents are similar between theater and movie. However, in movies, understanding of shots and preparation is needed. To deliver this well, a depth study of those characteristics such as expression method of subtext and continuous practice is necessary. Based on researches, we will talk about how important screen actors need to understand and prepare those characteristics when they act their roles and express the subtext of each character.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.17-27
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• 2021

The aim of this research was to identify the issue of the work permit system and consciousness of the people on the system, and to suggest some ideas on the government policies on it. To achieve the aim of research, this research used text mining based on social data. This research collected 1,453,272 texts from 6,217 units of online documents which contained 'work permit system' from January to December, 2020 using Textom, and did text-mining and social network analysis. This research extracted 100 key words frequently mentioned from the analyses of data top-level key word frequency, and degree centrality analysis, and constituted job problem, importance of policy process, competitiveness in the respect of industries, and improvement of living conditions of foreign workers as major key words. In addition, through semantic network analysis, this research figured out major awareness like 'employment policy', and various kinds of ambient awareness like 'international cooperation', 'workers' human rights', 'law', 'recruitment of foreigners', 'corporate competitiveness', 'immigrant culture' and 'foreign workforce management'. Finally, this research suggested some ideas worth considering in establishing government policies on the work permit system and doing related researches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.305-316
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• 2021

Construction accidents occur due to a number of reasons-worker carelessness, non-adoption of safety equipment, and failure to comply with safety rules are some examples. Because much construction work is done outdoors, weather conditions can also be a factor in accidents. Past construction accident data are useful for accident prevention, but since construction accident data are often in a text format consisting of natural language, extracting construction hazards from construction accident data can take a lot of time and that entails extra cost. Therefore, in this study, we extracted construction hazards from 2,026 domestic construction accident reports using text mining and performed a seasonal analysis of construction hazards through frequency analysis and centrality analysis. Of the 254 construction hazards defined by Korea's Ministry of Land, Infrastructure, and Transport, we extracted 51 risk factors from the construction accident data. The results showed that a significant hazard was "Formwork" in spring and autumn, "Scaffold" in summer, and "Crane" in winter. The proposed method would enable construction safety managers to prepare better safety measures against outdoor construction accidents according to weather, season, and climate.