• Journal of Digital Convergence
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• v.17 no.6
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• pp.193-200
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• 2019

This study analyzes the current status and performance of regional industrial policy in the face of the weakening industrial competitiveness under the global trend of the 4th industrial revolution and suggests the policy direction that regional industrial policy as a new national growth strategy. This study focuses on the suggestion of new regional industrial policy framework under new policy environment based on literature review. We propose a new industrial policy framework that simultaneously pursues equality between regions and efficiency within the region at the same time. As a core policy recommendation, we suggest first, establishing the region-centered industrial policy governance, second, strengthening planning function of local government through human resource development and institutionalized national government consulting, and the third, constructing lifestyle industry-ecosystem based on cultural asset and identity of region, fourth, utilizing Smart City, as a platform for participatory innovation, entrepreneurial and capital attraction, and cultivating new industry based on public procurement and data. Main suggestions of this study would be a new guideline coping with the declining industrial competitiveness and the Fouth Industrial Revolution. Details would be necessary.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.163-170
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• 2019

Over the past decade, the development of the Web explosively increased the data. Feature selection step is an important step in extracting valuable data from a large amount of data. This study proposes a novel opinion mining model based on combining feature selection (FS) methods with Word embedding to vector (Word2vec) and BOW (Bag-of-words). FS methods adopted for this study are CFS (Correlation based FS) and IG (Information Gain). To select an optimal FS method, a number of classifiers ranging from LR (logistic regression), NN (neural network), NBN (naive Bayesian network) to RF (random forest), RS (random subspace), ST (stacking). Empirical results with electronics and kitchen datasets showed that LR and ST classifiers combined with IG applied to BOW features yield best performance in opinion mining. Results with laptop and restaurant datasets revealed that the RF classifier using IG applied to Word2vec features represents best performance in opinion mining.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.825-838
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• 2018

The purpose of this study is to develop a survey tool of scientific character for elementary student which connects science education and character education effectively by figuring out traits of elementary students' character being presented in teaching and learning context of elementary school science. For this, we adapted the theocratical model from the previous research which defined scientific character as the competencies being able to practice in concrete teaching and learning context of science. Based on this model, we developed the survey tool as 'Scientific Character Inventory for Elementary Student' to assess elementary students' scientific character as the competences to practice the virtues being pursued in the context of elementary school science and verified its reliability and validity. As a result of an exploratory and confirmatory factor analysis, we confirmed all the items could be summarized into 28 items and eight constructs such as scientific problem-solving, self-management, self-reflection, communication, interpersonal skill, community participation, global citizenship, and environmental ethics awareness. We found that minimum reliability coefficient of constructs was over than 0.5 and reliability coefficient of the total items was 0.878. And also, there was modest relationship between each construct and the total score of scientific character. These results show that the developed survey tool can be useful in evaluating the effectiveness of science character education. This study is meaningful in that it systematically reveals constructs of scientific character which can be raised in concrete context of science teaching and learning so as to suggest the survey tool to assess this.

• Journal of Industrial Convergence
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• v.17 no.2
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• pp.9-14
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• 2019

This study was carried out to investigate how the basic plan of the Saemangeum development project that has been developed by the government since 1991 has been changed and to present a new development strategy by analyzing the future value and tourism resource value of Saemangeum development. The research methodology is based on the in - depth analysis methodology of the time series research materials and press releases published by the Saemangeum Development Administration, which oversees the development of Saemangeum. The government announced a plan to significantly reduce agricultural land and increase the proportion of non-agricultural land to 70% in order to create a multifunctional complex. After that, the government revised the basic plan of Saemangeum in 2014 and changed the plan to tailor the investment demand in order to cultivate investment demand, and introduced the special economic cooperation system for global economic cooperation. Therefore, the purpose of this paper is to analyze the process of Saemangeum development to date and to evaluate the value of Saemangeum development as a tourism resource, centered on the Master Plan of the Saemangeum Development Project changed by the government. Based on the results of this analysis, I would like to present the vision of Saemangeum tourism development considering Saemangeum 's environment and characteristics of the surrounding scenery by referring to trends and similar cases of international tourism.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.102-110
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• 2019

The shipbuilding and offshore plant industry of Korea is important and leads Korea's economic growth, designated as the 1st to 4th export items in Korea in terms of export contribution over the period from 2011 to 2015. This study proposes ways to improve the national competitiveness of Korean shipyards in the global offshore drilling market by reviewing a business model for providing an integrated offshore drilling commissioning service in Korea. This commissioning service model, which was attempted in 2014, was reviewed, and a new proposed business model for overcoming the limitations of the previous model and activating further business was evaluated. As a result of an economic evaluation, it was found that a 150-meter water depth model is economically more effective. As the number of integrated commissions increased from 2 to 5 times per year, NPV, IRR and B/C ratios increased and the fee per use decreased. Therefore, for offshore drilling facilities constructed and delivered in Korea, it will be necessary to encourage integrated offshore commissioning.

• Korean Journal of Heritage: History & Science
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• v.51 no.3
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• pp.54-71
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• 2018

This year marks the 40th anniversary of the first inscription of 12 UNESCO World Heritage sites in 1978. Based on an overview of the implementation of the 'Convention Concerning the Protection of the World Cultural and Natural Heritage', this article examines the current issues of the inscription of cultural heritage over the past 40 years. In particular, this paper focuses on the case study of 'Sacred Island of Okinoshima and Munakata Region' nominated by Japan, which was inscribed on the World Heritage List at the 41st World Heritage Committee in 2017. Also, it demonstrates the recent trend and investigates the issues of imbalances in the evaluation and the decisions among relevant actors in the nomination process of World Heritage. Furthermore, this article attempts to derive feasible implications and lessons, and to generate heritage discourse by examining Japan's management in 'heritage diplomacy' of the World Heritage Convention, which is rapidly changing in the course of its nearly half a century of implementation. In conclusion, the research is expected to provide Korea with strategic guidance marking the 30th anniversary of its entry into the Convention, and to steer the future direction for the inscription and conservation of cultural heritage.

• Industry Promotion Research
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• v.4 no.2
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• pp.9-18
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• 2019

This study investigated the relationship between ICT environment and business performance. In the case of Korea's major industries, large corporations have already established and operate a considerable level of smart factories, leading the global market. However, SMEs, which account for 95% of the total companies, are not able to build smart factories themselves. Smart factory construction The total number of government-supported enterprises is 4.891 companies (3,984 companies, 907 companies in construction) 2.9% of factories and 97.1% (166,344 companies) There is a big problem to be improved. The result of this study is that the first research objective of this study, which suggests the theoretical system that the will of the manager is most important for the successful establishment of the smart factory, which is part of the corporate innovation to meet the rapidly changing environment. Second, it can be seen that financing for building a smart factory is a key factor in building a smart factory, as well as funding itself. Third, it was found that besides its own technology, technology support for government and external technology consulting support are very important for smart construction. Fourth, organizational participation of internal organizers showed that cooperative and positive positive participation is also a factor of success. As a follow-up study, we analyzed the cause of the company's operation, analyzed the cause of the problem with the 4M1E technique, developed the countermeasures, and compared it before and after the improvement, standardized the improvement and needed further study. It is meaningful that the study provided basic data for building a smart factory through the analysis of the relationship between the ICT environment and business performance of the company.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.137-143
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• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.333-346
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• 2019

The purpose of this study is to find out the direction of overseas expansion strategy that should be established as a public broadcaster and a media company in order to overseas expand Korea EBS's. This study used a literature research method to analyze the related literature and data for analyzing strategies of major global media companies and overseas public service broadcasters (PSBs). As a result of the research, it suggests that the direction of EBS overseas expansion should approach both commercial business diversification and fulfillment of public responsibility. In particular, it suggests that transferring project of Korea's educational broadcasting system to developing country should be developed as a core business for spreading overseas expansion. In a follow-up study, it is necessary to carry out a research that suggests a comprehensive strategy of overseas expansion of EBS based on the result of this study.