• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.203-204
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• 2018

This research was conducted to identify adolescent problems in internet articles. This research defines adolescent problems as diverse issues related to adolescents and examine how it was dealt in the media to find out how different categories and the aspect of adolescent problems are changing by time. The result of the research was that in 1990's, education policy and family were mainly dealt with when it came to adolescent problems. As the era is changing, adolescent problems were far diversified compared to the past, and each problems are dealt with similar importance. This research is significant in that it does not only examine the social trend adolescent problems but also expand the range of adolescent counselling and utilizes quantitative analysis in considering diversity to provide new information.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.67-78
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• 2016

Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.371-382
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• 2017

This study aims to analyze the research trend of cultural policy-related papers based on 832 key words among 186 whole articles in the Journal of Cultural Policy by the Korea Culture & Tourism Institute from October 2008 to January 2017. The analysis was performed using a big data analysis technique called the Semantic Network Analysis. The Semantic Network Analysis consists of frequency analysis, density analysis, centrality analysis including degree centrality, betweenness centrality, and eigenvector centrality. Lastly, the study shows a figure visualizing the results of the centrality analysis through Netdraw program. The most frequently exposed key words were 'culture', 'cultural policy/administration', 'cultural industry/cultural content', 'policy', 'creative industry', in the order. The key word 'culture' was ranked as the first in all the analysis of degree centrality, betweenness centrality and eigenvector centrality, followed by 'policy' and 'cultural policy/administraion'. The key word 'cultural industry/cultural content' with very high frequency recorded high points in degree centrality and eigenvector centrality, but showed relatively low points in betweenness centrality.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.317-325
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• 2018

With the aim of creating new economic values and strengthening national competitiveness, governments and major private companies around the world are continuing their interest in big data and making bold investments. In order to collect objective data, such as news, securing data integrity and quality should be a prerequisite. For researchers or practitioners who wish to make decisions or trend analyses based on objective and massive data, such as portal news, the problem of using the existing Crawler method is that data collection itself is blocked. In this study, we implemented a method of collecting web data by addressing existing crawler-style problems using the cloud service platform provided by Amazon Web Services (AWS). In addition, we collected 'gas safety' articles and analyzed issues related to gas safety. In order to ensure gas safety, the research confirmed that strategies for gas safety should be established and systematically operated based on five categories: accident/occurrence, prevention, maintenance/management, government/policy and target.

• Health Policy and Management
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• v.27 no.3
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• pp.241-246
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• 2017

Background: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. Methods: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was 'induced abortion' in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. Results: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46-7.47; p< 0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. Conclusion: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.181-190
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• 2024

The era of logistics 4.0 in which new technologies are applied to existing traditional logistics management has approached. It is developing based on the convergence between various technologies, and R&D are being conducted worldwide to build smart logistics by synchronizing various services with the logistics industry. Therefore, this study proposes a methodology and technology strategy that can achieve trend analysis using patent analysis and promote the development of the domestic smart logistics industry based on this. Based on the preceding research, eight key technology fields related to smart logistics were selected, and technology trends were derived through LDA techniques. After that, for the development of the domestic logistics industry, the strategy of the domestic smart logistics industry was derived based on analysis including technology capabilities. It proposed a growth plan in the field of big data and IoT in terms of artificial intelligence, autonomous vehicles, and marketability. This study confirmed smart logistics technologies by using LDA and quantitative indicators expressing the market and technology of patents in literature analysis-oriented research that mainly focused on trend analysis. It is expected that this method can also be applied to emerging logistics technologies in the future.

• Convergence Security Journal
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• v.15 no.7
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• pp.47-53
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• 2015

Recently, the Internet of Things is an important technology with a Cloud computing services and a Big data in the IT fields. and The Internet of Things is widely used in various industries. This trend may be referred to as the emergence of significant based technologies for realizing a ubiquitous times. But the security problems of Internet of things are expected to increase with being realized in a variety of industries. and it will be have to provide a corresponding technology to the security threat for this. Therefore, this paper will be analyzed to the security threats of the Internet of Things by the cases. Thereby this is expected to be utilized as a basis for the countermeasure of Internet of Things in a future.

• The Journal of Bigdata
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• v.3 no.2
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• pp.123-130
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• 2018

As the demand for analytics technologies in both industry and academia increases, the demand for analytics experts is also increasing. To meet this trend, universities have begun to develop new analytics curriculum and provide courses for training analytics experts. In this study, we surveyed curriculum of master's analytics programs of 9 Korean universities and 20 overseas universities. As a result of comparing the domestic university program with the overseas university programs, the average number of subjects per school program is more than that of the Korean university program, but it was found to be less in terms of diversity of subjects.

• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.3
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• pp.33-40
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• 2017

Purpose - This paper suggests approaching methods for a way of strategies for traditional market extend and new ebusiness, market development, and plan of new product in the future and develop a way of method for cooperation through analysis on the smart phone market trend in different culture, effectively. Research design, data, methodology - As research design, data, and methodology, this paper suggests new idea and approaches from comparing characteristics analysis of smart phone market in different culture in AEC. This paper takes data to analysis from ITU, World Bank, AEC, and IMF. These organizer's data can be trusted as official society in the world. This paper can prove market and the characteristics of society through the corresponding results. Results - This paper can suggest the novel idea on market development and the big possibility depend on ACE country and can describe the possibility on new market because of low smart phone market penetration and low digital market penetration. Conclusions - This paper concludes to develop e-business, culture friendly ship, linking with education, development of appropriate technology depend on country, and should develop new strategy for market extend to low penetration.