• Journal of Digital Convergence
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• v.19 no.11
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• pp.85-93
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• 2021

The government is pursuing plans to create new e-government services. In terms of improving business procedures, dBrain (finance), e-people (personnel), and Onnara (electronic payment and business management) have achieved considerable results, and are currently making efforts to improve existing administrative services using newly emerged ICT. Among them, this paper attempted to study whether self-learning-based intelligent administrative services are efficient in the work process of public officials promoting actual work and affect their continued use. Based on individual perceptions and attitudes toward advanced ICTs such as AI, big data, and blockchain, public officials' influences on administrative services were identified and verified using UTAUT variables. They believe that the establishment and introduction of innovative administrative services can be used more efficiently, and they have high expectations for the use and provision of services as ICT develops. In the future, a model will be also applied to citizens

• Journal of Korea Port Economic Association
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• v.39 no.1
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• pp.17-34
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• 2023

The maritime industry is undergoing significant changes due to digitalization and decarbonization, collectively known as "2D." This study investigates how these transformations are impacting the industry's business models. Since the changes are still ongoing, a cognitive approach was used to derive business models, rather than relying on actual case studies. The study presents experimental maritime business models that correspond to the four types of business model frameworks (or archetypes), along with recent trends for each model. The research results show that new business models are emerging in various areas, including the commercial and technical fields of the maritime industry. This thought-provoking study is significant as a pioneering investigation that will stimulate subsequent case-based research in academia and provide strategic guidance to market participants or policy makers in the maritime industry.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.53-61
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• 2022

The purpose of this study was to test whether or not the AI chatbot is effective in acquiring target grammar for Korean EFL college students: prepositions and articles. A quasi-experiment was conducted with 46 first-year students taking part in a required English course. They were randomly divided into two groups: the experimental and control groups (23 students for each, respectively). The experimental group was engaged in six chat sessions with a chatbot over 6 weeks. A pretest and a posttest were used to examine the effectiveness of the chatbot by comparing any changes made in error frequencies of the target grammar in participants' English compositions. The results show that after a conversation with the chatbot, the experimental group significantly reduced the mean of omission errors in both prepositions and articles. To have a great effect in other error categories, chatbot feedback needs to be improved to reduce short responses or inaccurate utterances of students and induce them to actively participate in the conversation.

• Advanced Industrial SCIence
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• v.2 no.2
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• pp.25-30
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• 2023

The purpose of this study is to empirically analyze the impact of corporate innovation activities on corporate innovation performance using data from companies participating in the smart farm project. A company's innovation activities were divided into planning capacity, R&D capacity, and commercialization capacity, and the impact of each innovation activity on the company's sales and patent creation was estimated. The moderating effect was also analyzed. Regression analysis was conducted as a research method, and as a result of the analysis, it was found that planning capacity, R&D capacity, and commercialization capacity related to innovation within a company have an impact on corporate performance creation. appeared to be In order to increase the business performance of technology commercialization, it was confirmed that planning and R&D capabilities as well as governmental technology policy support are needed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.310-316
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• 2023

This study aims to predict uncertain future scenarios that may unfold in South Korea in the near future, utilizing the theory of extreme events(X-events). A group of 32 experts, consisting of government emergency planning officers, was selected as the focus group to achieve this objective. Using the Focus Group Interview (FGI) technique, opinions were gathered from this focus group regarding potential X-events that may occur within the advanced science and technology domains over the next 10 years. The analysis of these opinions revealed that government emergency planning officers regarded the "Obsolescence of current technology and systems," particularly in the context of cyber network paralysis as the most plausible X-event within science and technology. They also put forth challenging and intricate opinions, including the emergence of new weapon systems and ethical concerns associated with artificial intelligence (AI). Given that X-events are more likely to emerge in unanticipated areas rather than those that are widely predicted, the results obtained from this study carry significant importance. However, it's important to note that this study is grounded in a limited group of experts, highlighting the necessity for subsequent research involving a more extensive group of experts. This research seeks to stimulate studies on extreme events at a national level and contribute to the preparation for future X-event predictions and strategies for addressing them.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.191-199
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• 2023

The purpose of this study is to examine the impact of ChatGpt's quality on users' satisfaction and intention to continuous use it. For this purpose, a survey was conducted targeting college students in the Busan and Gyeongnam regions, and responses from a total of 155 people were verified using the SPSS 28.0 program. As a result of the study, reliability and stability among ChatGPT quality factors were found to have a positive effect on satisfaction with use and intention to continuous use. Satisfaction with the use of ChatGPT was found to have a positive effect on intention to continuous use.. Satisfaction with use was found to have a positive mediating effect between the reliability and stability of ChatGPT quality and intention to continous use it. As a result of this study, we aim to contribute to suggesting educational and policy directions necessary to promote the use of ChatGPT by presenting factors that affect users' intention to continuous use ChatGPT among the qualities of ChatGPT.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.93-98
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• 2024

With the rapid advance in AI (artificial intelligence) and high-performance computing technologies, deep learning is being used in various fields. Deep learning proceeds training by randomly reading a large amount of data and repeats this process. A large number of files are randomly repeatedly referenced during deep learning, which shows different access characteristics from traditional workloads with temporal locality. In order to cope with the difficulty in caching caused by deep learning, we propose a new sampling method that aims at reducing the randomness of dataset reading and adaptively operating on existing buffer cache algorithms. We show that the proposed policy reduces the miss rate of the buffer cache by 16% on average and up to 33% compared to the existing method, and improves the execution time by up to 24%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.123-131
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• 2024

The dispute between SK and Netflix, which has been going on for more than three years, ended in the direction of dropping the lawsuit and establishing a cooperative relationship between the two companies. However, as Internet traffic usage is likely to increase further in the future due to digital transformation and activation of generated AI, conflicts between domestic mobile carriers and global CP operators over network usage fees can arise at any time. In this study, the issues of the dispute related to network usage fees that occurred between SK and Netflix were examined, and different implications were drawn for each issue. The cost and scope of network usage considerations are an issue that must be determined entirely by negotiations between operators. However, if a dispute occurs between operators, user damage such as speed delays may occur, so it is necessary to prepare a policy alternative. As the domestic media industry has grown cooperatively with global CPs, it is considered important to form a reciprocal relationship between domestic mobile telecommunication operators and global CP operators regarding network usage fees in the future.