• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.87-96
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• 2024

Information power has been a major criterion for wealth disparity in human history, and since the advent of the Fourth Industrial Revolution, referred to as the data economy era, personal information has also gained economic value. Additionally, companies collect and analyze customer information to use as a marketing tool, providing personalized services, making the collection of quality customer information crucial to a company's success. However, as the amount of data held by companies increases, crimes of stealing personal information for financial gain have surged, making corporate customer information a target for criminals. The leakage of personal information and its circumstances lead to a decline in corporate trust from the customer's perspective, threatening corporate sustainability with falling stock prices and decreased sales. Therefore, companies find themselves in a paradoxical situation where the utilization of personal information is increasing while the risk of personal information leakage is also growing. This study used the news big data analysis system, BIG KINDS, to analyze major keywords before and after media coverage on personal information leaks, examining domestic media coverage trends. Through this, we identified the impact of personal information leakage on corporate sustainability and analyzed the connection between personal information protection and sustainable corporate management. The results derived from this study are expected to serve as foundational data for companies seeking ways to enhance sustainable management while increasing the utilization of personal information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.478-485
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• 2019

This is an exploratory study to examine factors affecting South Korean companies' intentions to use big data technology and services based on whether the companies use public data or not. This study, using R, conducted chi-squared tests and logistic regression analysis. As a result of the logistic regression analysis, cost reduction had a positive effect on the big data-use intentions in companies that use public data, whereas with companies that do not use public data, customer satisfaction had a positive impact, and support for decision-making had a negative impact on the intention to use big data. Recently, the South Korean government has focused on improving the utilization of public data and big data. However, as a result of this study, the use of public data and big data in South Korea is still insufficient. Yet, considering that the data utilized for this study was created in 2017, additional study using public data and big data is also required.

• Korean Journal of Food Science and Technology
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• v.17 no.6
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• pp.437-441
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• 1985

In order to elucidate the flavor compounds of fermented big eyed herring, Harengula zunasi (BLEEKER), and slimy, Leiognathus nuchalis (TEMMINCK et SCHEGEL), the volatile constituents of products were analysed by GLC. In the volatile compounds of fermented big eyed herring, eight kinds of volatile fatty acids, nine kinds of volatile carbonyls, and five kinds of volatile amines were identified. While in the fermented slimy, seven kinds of volatile fatty acids, six kinds volatile carbonyls, and five kinds of volatile amines were also identified. In the volatile fatty acids and volatile amines, n-butyric acid and trimethylamine were the most dominant component in both fermented products. In the fermented big eyed herring 2-methylpropanal, ethanal, and propanal were abundant holding 36.2%, 28.5%, and 16.2%, while in the fermented slimy ethanal, 2-methylpropanal, and propanal were abundant holding 44.7%, 24.1%, and 14.4% of total volatile carbonyls, respectively. From the experimental results, it was concluded that n-butyric acid, trimethylamine and volatile carbonyls such as 2-methylpropanal, ethanal and propanal played an important role in the flavor of the fermented big eyed herring and slimy.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.253-277
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• 2019

In the era of the 4th Industrial Revolution, the importance of data is intensifying, but there are many cases where it is not easy to use data due to personal information protection. Although criminal justice information is expected to have various useful values such as crime prediction and prevention, scientific investigation of criminal investigations, and rationalization of sentencing, the use of criminal justice information is currently limited as a matter of legal interpretation related to privacy protection and criminal justice information. This study proposed to convert criminal justice information into 'crime data' and use it as big data through the structuralization and categorization of criminal justice information. And when using "crime data," legal issues, value in use, considerations for data generation and use were verified by experts, and future strategic development plans were identified. Finally we found that 'crime data' seems to have solved the privacy problem, but it is necessary to specify in the criminal justice information related law and it is urgent to be organized in a standardized form for analysis to use big data. Future directions are to derive data elements, construct a dictionary thesaurus, define and classify personal sensitive information for data grading, and develop algorithms for shaping unstructured data.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.463-476
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• 2022

After industrialization in the past, the automobile industry has continued to grow centered on internal combustion engines, but is facing a major change with the recent 4th industrial revolution. Most companies are preparing for the transition to electric vehicles and autonomous driving. Therefore, in this study, topic modeling was performed based on LDA algorithm by collecting 4,002 domestic papers and 68,372 overseas papers that contain keywords related to CASE (Connectivity, Autonomous, Sharing, Electrification), which represent future automobile trends. As a result of the analysis, it was found that domestic research mainly focuses on macroscopic aspects such as traffic infrastructure, urban traffic efficiency, and traffic policy. Through this, the government's technical support for MaaS (Mobility-as-a-Service) is required in the domestic shared car sector, and the need for data opening by means of transportation was presented. It is judged that these analysis results can be used as basic data for the future automobile industry.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.5
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• pp.383-388
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• 2017

The $4^{th}$ Industry Revolution was advocated by Klaud Schwab who is founder of World Economic Forum at the Davos Forum in 2016, and there are big differences on ICT based $4^{th}$ Industry revolution in the aspects of speed, scope and impact compared with the 3rd Industry revolution. Creating new industries and values through technology such as internet of things, cloud, big data, and artificial intelligence are included in the meaning of The $4^{th}$ industry revolution. In this article, the direction of change to water technology in response to the $4^{th}$ Industry revolution is surveyed. 4G Water Infra should minimize environmental impact under the consideration of sustainable development and advanced technologies. To solve the existing water infra problems, it is common and fundamental that the intake water from nature can be regarded as borrowed from nature and it should be returned to natural state with improved water quality. Government, academic organizations and industries should prepare and collaborate together in order to help our country with outstanding capabilities in infrastructure construction and ICT to lead the 4G water technology development.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.4
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• pp.36-44
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• 2013

• The Monthly Technology and Standards
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• s.40
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• pp.17-20
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• 2005

• Acute and Critical Care
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• v.33 no.4
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• pp.269-270
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• 2018

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.279-286
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• 2021

In this study, we looked at the appearance of Edutech, which is being put into the educational field after Corona 19, with the advent of the 4th industrial revolution. In the era of the 4th industrial revolution, the infrastructure, data, and service of Smart Stick that actively utilized ICT became the main pillars of smart education. In particular, smart education is being implemented through e-learning, smart learning, and edutech, and on this basis, it has become possible through the expansion and use of the Internet and computers, the dissemination of smart devices, and a software foundation using big data. Based on this, it was confirmed that Edutech is being implemented through the establishment of a quarantine safety net, a learning safety net, and a care safety net for individual learners and safe life based on artificial intelligence. Lastly, in order for edutech education using big data to become a discourse for everyone, it is necessary to consider artificial intelligence and ethics in the use and application of edutech.