• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.214-227
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• 2003

Developing an application, it is difficult to catch an exact requirement with the conventional text-based method. It has also problems in verification and analysis at each developing stage. Therefore, if an adjustment is required with an error and change of requirement, a bad effect happen in the whole system. In this case, it also affect adversely on the developing cost and period. Meanwhile, if an analysis or verification is performed, the possibility of an error frequency reduces. Thus, not only is it easier to correct the error but also add an new requirement. This thesis embody a TCP/IP congestion control algorithm with SDL which provides automatically graphic interface, verification and analysis to each developing stage. Using SDL gave a clear representation embodiment in each developing stage and easiness of adjustment due to changing requirements or correcting errors. In addition, the stages of protocol have been certified in a simulation by verification of MSC and the results showed a possibility of developing a better TCP/IP protocol.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.175-199
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• 2019

Uncertainty means incomplete stages of knowledge of propositions due to the lack of consensus of information and existing knowledge. As the amount of academic literature increases exponentially over time, new knowledge is discovered as research develops. Although the flow of time may be an important factor to identify patterns of uncertainty in scientific knowledge, existing studies have only identified the nature of uncertainty based on the frequency in a particular discipline, and they did not take into consideration of the flow of time. Therefore, in this study, we identify and analyze the uncertainty words that indicate uncertainty in the scientific literature and investigate the stream of knowledge. We examine the pattern of biomedical knowledge such as representative entity pairs, predicate types, and entities over time. We also perform the significance testing using linear regression analysis. Seven pairs out of 17 entity pairs show the significant decrease pattern statistically and all 10 representative predicates decrease significantly over time. We analyze the relative importance of representative entities by year and identify entities that display a significant rising and falling pattern.

• Health Policy and Management
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• v.31 no.2
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• pp.148-157
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• 2021

Background: Based on that the key function of health technology is improving the quality of healthcare services, our study purports to explore the process of medical device development in detail and to discuss its policy implications. Methods: A total of 12 in-depth interviews were conducted with four groups of industry, hospital, academia, and civil society. All of the interviewees except those from civil society were involved in the new medical device development between 2009 and 2018. We performed a text network analysis and content analysis of the interview data. Results: The frequency and the degree centrality rankings suggested a close association between the utilization issue and the technology development. Similarly, the results of the content analysis showed that the appropriate intervention in the utilization of technology has a direct impact on the progress of development. Under the continuous industrial effort to boost profits by developing new technology, service providers and citizens should be knowledgeable of and make good use of the new technology for the provision of better services. Conclusion: As the development itself would not guarantee the improvement of service quality and better health outcomes, health technology policies should take a more comprehensive view to serve the unmet needs and even to facilitate the technology development.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.65-73
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• 2024

This paper aims to identify the major research trends in organizational effectiveness over the past 20 years. For this purpose, SCOPUS, an international academic database provided by Elsevier, was used to identify research trends in organizational effectiveness over the past 24 years (2000~2023). According to the frequency analysis, there were 2,789 cases of organizational, 2,714 cases of effectiveness, 850 cases of management, 689 cases of performance, 632 cases of organizations, and 597 cases of leadership. Trend analysis. While effectiveness and organizational have been consistently researched, the trends of leadership and management have been declining in recent years. LDA analysis shows that effectiveness and organizational are important topics. This shows that it is important to be able to predict the future when it is difficult to predict the future. The results of this study can be used as a guide for companies to establish organizational management at a strategic level and improve organizational effectiveness.

• Journal of Industrial Convergence
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• v.22 no.7
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• pp.23-30
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• 2024

This study aims to identify the major recent research trends on person-organizational fit, and uses SCOPUS, an academic database, to identify research trends on person-organizational fit over the past 24 years (2000-2023). Frequency analysis showed that organizational was the most important term with 2,789 articles, followed by effectiveness with 2,714 articles, management with 850 articles, performance with 689 articles, organizations with 632 articles, and leadership with 597 articles. The trend analysis shows that research on fit, organization, and job is steadily increasing. The LDA analysis showed that fit, personorganization(po), and job are important topics, which shows that fit, i.e., the alignment of an individual's goals or values with the organization's goals or values, is important in the operation of an organization. The results of this study can be used as a useful guideline for organizations to establish measures to attract and cultivate excellent human resources and create organizational performance.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.162-171
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• 2020

The purpose of this study is to examine the social perception of disaster safety education for young children based on Textom big data and to explore the direction of young children's disaster safety education. Researchers collected and analyzed online text data using the keywords 'young children+disaster+safety education' from portal websites from 2014 to 2017. The raw data were then subjected to first and second data refinement process. Based on the frequency analysis results, 50 keywords were selected, and the selected keywords were converted into matrix data for network analysis. The results of the study are: first, the most frequently appeared keyword together with young children's disaster safety education was 'education', followed by 'experience', 'kindergarten', 'prevention', and 'school.' Second, keywords with high centrality in the analysis of centrality also were 'education', 'experience', and 'prevention'. In addition, keywords like 'prevention', 'life', and 'evacuation' appear higher in connection-centricity than frequency ranking, which means that the degree of connection between the words is high. These results suggest that young children need education in during early childhood in order to improve their disaster safety skills, and disaster safety education should be accomplished through 'prevention' and 'experience' in early childhood education institutions.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.123-141
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• 2021

As the dependence of technology on the economic structure increases, the importance of National Core Technology is increasing. However, due to the nature of the technology itself, it is difficult to determine the scope of the technology to be protected because the scope of the relation is abstract and information disclosure is limited due to the nature of the National Core Technology. To solve this problem, we propose the most appropriate literature type and method of analysis to distinguish important technologies related to National Core Technology. We conducted a pilot test to apply TF-IDF, and LDA topic modeling, two techniques of text mining analysis for big data analysis, to four types of literature (news, papers, reports, patents) collected with National Core Technology keywords in the field of Display industry. As a result, applying LDA theme modeling to patent data are highly relevant to National Core Technology. Important technologies related to the front and rear industries of displays, including OLEDs and microLEDs, were identified, and the results were visualized as networks to clarify the scope of important technologies associated with National Core Technology. Throughout this study, we have clarified the ambiguity of the scope of association of technologies and overcome the limited information disclosure characteristics of national core technologies.

• Journal of Environmental Impact Assessment
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• v.31 no.5
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• pp.310-320
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• 2022

This study aimed to identify the change in the public perception of "bats" after the outbreak of the coronavirus (COVID-19) infection. Text mining and network analysis were conducted for blog posts, the largest social network in Korea. We collected 9,241 Naver blog posts from 2019 to 2020 just before the outbreak of COVID-19 in Korea. The data were analyzed with Python and NetMiner 4.3.2, and the public's perception of bats was examined through the relationship of keywords by period. Findings indicated that the frequency of bat keywords in 2020 increased more than 25 times compared to 2019, and the centrality value increased more than three times. The perception of bats changed before and after the outbreak of the pandemic. Prior to COVID-19, bats were highly recognized as a species of wildlife while in the first half of 2020, they were strongly considered as a threat to human society in relation to infectious diseases and health. In the second half of 2020, it was confirmed that the area of interest in bats expanded as the proportion of ecological and cultural types ofresearch increased. This study seeks to contribute to the expansion and direction of future research in bats by understanding the public's interest in the potential impact of the species as disease hosts post the COVID-19 pandemic.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.1-19
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• 2022

The purpose of this study is to analyze the keywords of the middle school textbooks based on the 2015 revision of the technology and home economics curriculum to understand the core concepts and contents composition of the 'housing' unit. Using TEXTOM and UCINET programs, the frequencies and centralities of the keywords were analyzed, and CONCOR analysis was performed. The results are as follows. First, the content system of the 'housing' unit is divided into 'life culture' and 'safety' in the 'family life and safety' area. Second, in the 'safety' section, the frequencies of occurrence of the words were high in the order of indoor, occurrence, use, noise, and safety accidents, in the order of frequency of occurrence. It was confirmed that words related to daily life, safety accidents, and prevention were closely connected to each other. In the 'life culture' section, the frequencies of occurrence were high in the order of space, housing, family, and residential space, and the correlations between these keywords were also high. Third, the most influential core keywords were, indoor and occurrence in the 'safety' section, and space, family, and housing, in the 'life culture' section. Fourth, the 'safety' section were divided into two subunits, 'safe living environment' and 'comfortable living environment', and the 'life culture' section were divided into four subunits, 'living space composition', 'space utilization', 'housing value and lifestyle', and 'housing culture'.