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.
Kim, Hyun Suk;Ko, Dong Beom;Lee, Won Gok;Bae, You Suk
KIPS Transactions on Software and Data Engineering
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v.11
no.5
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pp.211-220
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2022
Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.
According to recent government forecasts, universities face a critical situation, due to a reduction in the number of students and a decrease in tuition income. To respond to the changed population structure and the 4th Industrial Revolution, the government is supporting universities in reorganizing the structure of academics and curricula focused on lifelong education. Considering this, this study analyzed the correlation between intention to participate in lifelong education and learning outcomes oriented to workers involved in shipping and port logistics in the Port of Gwangyang and Yeosu, who are participating or have participated in lifelong education. To expand the opportunities for participation in the lifelong education of adult learners and form a learning culture, it is necessary to analyze the intention to participate in lifelong education and how participants identify their learning outcomes. According to the analysis results, the goal orientation of intention to participate in learning has a significant influence on individual features of learning outcomes, and learning orientation has a significant influence on the social characteristics of learning outcomes. Moreover, learning outcomes and the learning orientation of the intention to participate in learning have a significant influence on the intention to continue learning. In particular, the results showing that learning outcomes reflect individual changes and that interests obtained as a product of learning influence the intention to continue learning are highly suggestive.
The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.
With the advent of the 4th Industrial Revolution, the modern economy is transforming into a service-oriented economic society, and there is a growing need for companies to reorganize organizational culture, values, and human resources to suit the changing environment. Especially, even when times change, human capital is the most important factor in maintaining sustainable development and Corporate value, since all work is done by people. Therefore, in this study, in order to recognize the importance of human resources and verify the appropriate human resources for the changing service economy era, we reviewed the literature and that drew the human resources suitable for the recent service economy era Based on this, an empirical study was conducted on whether the suggested human resources factors were useful. To this end, a feasibility analysis, reliability analysis, correlation analysis, confirmatory factor analysis, and reference validity were conducted by dividing into a preliminary survey and a main survey. As a result, it was finally drawn with 30 items, 7 factors. The results of this study are expected to be used as basic data in various fields of research on human resources in the service economy era, and in-depth empirical studies are needed in the future.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.22
no.3
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pp.88-103
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2023
With the recent advancement of 4th Industrial Revolution technology, transportation systems are generating large amounts of mobility data related to the individual movement trajectories of vehicles and people. There are many constraints on utilizing mobility data containing personal information. Thus, in South Korea, the processing and generation of pseudonymized information and the analysis and utilization of this information have been managed in a dual manner by applying separate agencies and technologies through the revision of the Data 3 Act and the enactment of the Data Basic Act. However, this dual approach fails to securely support the entire data lifecycle and suffers from inefficiencies in terms of processing time and cost. Therefore, to compensate for the problems of the existing Expert Data Combination System and Data Safety Zone, this study proposes an Integrated Data Safety Zone Framework that integrates and unifies the process of generating, processing, analyzing, and utilizing mobility data. The integrated process for data processing was redesigned, and common requirements and core technologies were derived. The result is an architecture for a next-generation Integrated Data Safety Zone system that can manage and utilize the entire life cycle of mobility data at one stop.
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.
With the progress of the 4th industrial revolution, interest in smart factories is increasing. The government is implementing a smart factory support project for small and medium-sized manufacturing companies. Therefore, in this study, factors influencing small and medium-sized enterprises(SME's) intention of smart factory acceptance were analyzed. In particular, it focused on how the perception of government support affects intention of smart factory acceptance. For the empirical analysis, a research model was established by reflecting the characteristics of SMEs and the technical factors of the smart factory centering on the technology acceptance theory. Based on the model set in this way, a questionnaire survey was conducted for employees of SMEs. In this study, a total of 231 samples of valid data were used for analysis. The empirical analysis results are as follows. It was analyzed that performance expectancy, social influence, technology utilization capability, CEO will, and employee resistance to innovation, all introduced as research variables, had a significant effect on the use intention of smart factory acceptance. In particular, it was found that employees' resistance to innovation had a negative (-) effect on their use intention. Meanwhile, to analyze the moderating effect of government support, it was divided into a group with high expectations for government support and a group with low expectations. As a result, it was found that there was a difference in the effect of CEO's will, employees' resistance to innovation, and social influence on the use intention. On the other hand, no significant difference was found in the relationship between performance expectancy, technology utilization capability on the use intention. Based on the empirical analysis results, the academic and practical implications of this study were presented.
Hye-Yeon Shim;MinSeo Kweun;DaYoung Yoon;JiYoung Seo;Il-Gu Lee
Journal of the Korea Institute of Information Security & Cryptology
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v.34
no.2
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pp.207-216
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2024
As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.
Journal of the Korean Applied Science and Technology
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v.38
no.1
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pp.241-262
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2021
This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.
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