• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.488-499
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• 2021

This study investigated the effects of the HTE creative education program, which applies blended learning methodology as a convergence class strategy between offline and online, on middle school students' creative problem solving capability. As a result of applying for five creative education practice programs in the classroom, it turned out that there was a statistically significant difference (p < .05) in the case of idea manipulation, visualization, comparison, idea generation, and deliberation, subordinate constructs of creative problem solving capability. Also, the program turned out to be positively effective, with a 0.14 point improvement in the pre and post-means of all middle school students, showing from 3.65 to 3.79 points, and 72% of middle school students who participated in the program were satisfied, and 68% were interested. According to the results, HTE creative education programs using blended learning turned out to be effective as a customized methodology in the COVID-19 situation and the era of the 4th Industrial Revolution, where various creative talents are needed. Therefore, the need for the development of creative education programs on various related topics and teacher training for teaching and learning methodologies of blended learning.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.21-29
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• 2018

In the era of the 4-th industrial revolution, the concept of smart factory is emerging. There are efforts to predict the occurrences of facility errors which have negative effects on the utilization and productivity by using data analysis. Data composed of the situation of a facility error and the type of the error, called the facility error log, is required for the prediction. However, in many manufacturing companies, the types of facility error are not precisely defined and categorized. The worker who operates the facilities writes the type of facility error in the form with unstructured text based on his or her empirical judgement. That makes it impossible to analyze data. Therefore, this paper proposes a framework for constructing a phrase network to support the identification and classification of facility error types by using facility error logs written by operators. Specifically, phrase indicating the types are extracted from text data by using dictionary which classifies terms by their usage. Then, a phrase network is constructed by calculating the similarity between the extracted phrase. The performance of the proposed method was evaluated by using real-world facility error logs. It is expected that the proposed method will contribute to the accurate identification of error types and to the prediction of facility errors.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.553-561
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• 2019

In this study, the method of quality measurement for the statistical usefulness of de-identified data was examined in terms of prediction accuracy by statistical modeling. In the era of the 4th industrial revolution, effective use of big data is essential to innovation through information and communication technology, but personal information issues are constrained to actively utilize big data. In order to solve this problem, de-identification guidelines have been established and the possibility of actual re-identification of personal information has become very low due to the utilization of various de-identification methods. On the other hand, strong de-identification can have side effects that degrade the usefulness of the data. We have studied the quality of statistical usefulness of the de-identified data by KLT model which is a representative de-identification method, A case study was conducted to see how statistical accuracy of prediction is degraded by de-identification. We also proposed a new measure of data usefulness of the de-identified data by quantifying how much data is added to the de-identified data to restore the accuracy of the predictive model.

• Food Science and Industry
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• v.54 no.2
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• pp.93-101
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• 2021

Hazard Analysis Critical Control Point (HACCP) systems were developed to ensure a high level of food safety and reduced risk of foodborne illness. This paper focuses on significant issues associated with the implementation of HACCP; it provides an overview on recent literature. The structure of the paper follows six groupings of issues in the international literature of HACCP: (1) comparative studies and unification plan between HACCP and other food safety regulations; (2) verification of the HACCP system's effectiveness in improving food safety; (3) establishment of critical control point (CCP) for various foods HACCP model development; (4) expansion of HACCP application in the various fields and small businesses;(5) the impacts of HACCP on consumer's preferences and firms' financial performance in food industry; (6) HACCP and technological changes. The paper concludes with some suggestions for the future research in order to promote safe food supply chain for global customers.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.255-273
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• 2022

This study is a basic study for establishing a comprehensive operation plan for the Incheon Global Campus Library in preparation for the 4th Industrial Revolution and the post-corona era. Based on this, it was intended to propose a direction for establishing a comprehensive operation plan in the future. As a result of the study, in the case of the first collection, a mid- to long-term plan for continuous expansion of the collection is required, and in particular, it seems that the expansion of major-related collections is necessary. In the case of the second service, it is necessary to support users' research by providing information services customized for each stage of research by users, information services customized for researchers, and research support services for departments, and it is necessary to provide information utilization education programs. Third, in the case of space, IGC users have very high demands for learning and research space, so it is necessary to improve education and related spaces that users want through space reorganization in the future. It is also necessary to expand the creative collaboration space as a place closely related to the lives of students, such as rest, etc. Lastly, in order to activate the homepage in relation to the homepage and information system, it is necessary to first expand the various contents and up-to-date data that users want on the homepage. In addition, it seems that the domestic electronic journal and DB provision plan should be implemented.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.73-94
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• 2022

This study is a basic research for establishing a mid- to long-term development plan for the library of the Korea Expressway Corporation that can establish the vision and core values of the library and continuously grow by taking advantage of the specialization of the road transportation field in preparation for the 4th industrial revolution and post-corona era. The current state, satisfaction, and demand of the library were conducted for users of the Korea Expressway Corporation, and based on this, a mid- to long-term development plan was proposed. As a result of the research, first, the library of the Korea Expressway Corporation should provide information services to respond to the immediate information needs of its members as a library that supports academic and research activities as well as the comprehensive collection and preservation of related materials as a national road transportation representative library. Second, it is necessary to establish a systematic collection development policy, and it is necessary to collect collections by detailed themes related to road traffic. Third, overall service development is necessary, and Korea Expressway Corporation library homepage and mobile service should be developed. Lastly, space improvement must be made through space reorganization, and it is necessary to expand the usability through the introduction of the latest technology.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.447-454
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• 2022

In the era of the 4th industrial revolution, we are living in a flood of information. It is very difficult and complicated to find the information people need in such an environment. Therefore, in the flood of information, a recommendation system is essential. Among these recommendation systems, many studies have been conducted on each recommendation system for movies, music, food, and clothes. To date, most personalized recommendation systems have recommended clothes, books, or movies by checking individual tendencies such as age, genre, region, and gender. Future generations will want to be recommended clothes, books, and movies at once by checking age, genre, region, and gender. In this paper, we propose a recommendation system that recommends personalized clothes and food at once according to the user's emotions and weather. We obtained user data from Twitter of social media and analyzed this data as user's basic emotion according to Paul Eckman's theory. The basic emotions obtained in this way were converted into colors by applying Hayashi's Quantification Method III, and these colors were expressed as recommended clothes colors. Also, the type of clothing is recommended using the weather information of the visualcrossing.com API. In addition, various foods are recommended according to the contents of comfort food according to emotions.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.1-20
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• 2022

As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.107-122
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• 2023

The demand for spatial information in the era of the 4th Industrial Revolution is expanding Additionally, interest in attribute data related to geography or location is increasing. In the field of spatial information, spatial information policies and services tailored to the public can be provided through linkage and integration with new attribute data, and these data are resources for this purpose. In order to meet this expanding and diverse demand for spatial information utilization, it is necessary to develop technologies for linking and utilizing various attribute information such as public data. In this study, we aim to present a technology development strategy for linking and integrating attribute data and spatial information through a review of theories related to data linkage and integration, the current status of data on public data portals, and existing prior research. As a result, it was suggested that the data identifier of the attribute data to be linked should be used to develop linkage technology between spatial information and attribute data, and an attribute data linkage process that can be used when designing a prototype for technology development was presented.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.