• Journal of Fashion Business
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• v.26 no.2
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• pp.28-47
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• 2022

Rapid development of information and communication technology is leading the digital transformation (hereinafter, DT) of various industries. At this point in rapid online transition, fashion manufacturers operating offline-oriented businesses have become highly interested in DT and artificial intelligence (hereinafter AI), which leads DT. The purpose of this study is to examine the development status and application case of AI-based digital technology developed for the fashion industry, and to examine the DT stage and AI application status of domestic fashion manufacturers. Hence, in-depth interviews were conducted with five domestic IT companies developing AI technology for the fashion industry and six domestic fashion manufacturers applying AI technology. After analyzing interviews, study results were as follows: The seven major AI technologies leading the DT of the fashion industry were fashion image recognition, trend analysis, prediction & visualization, automated fashion design generation, demand forecast & optimizing inventory, optimizing logistics, curation, and ad-tech. It was found that domestic fashion manufacturers were striving for innovative changes through DT although the DT stage varied from company to company. This study is of academic significance as it organized technologies specialized in fashion business by analyzing AI-based digitization element technologies that lead DT in the fashion industry. It is also expected to serve as basic study when DT and AI technology development are applied to the fashion field so that traditional domestic fashion manufacturers showing low growth can rise again.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.237-244
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• 2023

Today, AI is being applied to various industrial fields, leading to a paradigm shift in the overall industry. In the fashion industry, AI is also used to predict trends and provide various services for consumers, and in particular, AI image creation tools have the potential as a tool for fashion design development. This study investigated the possibilities and limitations of using Midjourny for fashion design development by creating images using Midjourney among AI image creation tools and identifying its characteristics. The characteristics of images created in Midjourney are as follows. First, it has the intuitiveness to create images by intuitively applying or combining images corresponding to commands. Second, there is randomness in which different images are generated when the same command is entered at different times. Third, when using existing images and commands together, the image created in Midjourney is more dependent on the existing image than the command. In conclusion, Midjourny's various image creation functions and the ability to change images according to commands can be helpful in developing original fashion designs. However, it is important to note that fashion designs that cannot be worn or made are sometimes presented. It is expected that the results of this study will serve as basic data for the use of AI image creation tools for fashion design development.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.343-347
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• 2022

To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.283-289
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• 2023

AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.115-123
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• 2024

The purpose of this study is to contribute to how the advantages of artificial intelligence (AI) services and the associated limitations can be simultaneously overcome, using the keywords AI and risk management. To achieve this, two cases were introduced: (1) presenting a risk monitoring process utilizing AI and (2) introducing an operational toolkit to minimize the emerging limitations in the development and operation of AI services. Through case analysis, the following implications are proposed. First, as AI services deeply influence our lives, the process are needed to minimize the emerging limitations. Second, for effective risk management monitoring using AI, priority should be given to obtaining suitable and reliable data. Third, to overcome the limitations arising in the development and operation of AI services, the application of a risk management process at each stage of the workflow, requiring continuous monitoring, is essential. This study is a research effort on approaches to minimize limitations provided by advancing artificial intelligence (AI). It can contribute to research on risk management in the future growth and development of the related market, examining ways to mitigate limitations posed by evolving AI technologies.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.432-438
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• 2023

Purpose: The purpose of this study is to enable users to conveniently report risks by automatically classifying risk categories in real time using AI for images reported in the life safety prevention service app. Method: Through a system consisting of a life safety prevention service platform, life safety prevention service app, AI model serving server and sftp server interconnected through the Internet, the reported life safety images are automatically classified in real time, and the AI model used at this time An AI learning algorithm for generation was also developed. Result: Images can be automatically classified by AI processing in real time, making it easier for reporters to report matters related to life safety.Conclusion: The AI image automatic classification system presented in this paper automatically classifies reported images in real time with a classification accuracy of over 90%, enabling reporters to easily report images related to life safety. It is necessary to develop faster and more accurate AI models and improve system processing capacity.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.21-31
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• 2024

Major global powers are investing heavily in artificial intelligence (AI) and hyper-connected networks, demonstrating their crucial role in future warfare. To advance and utilize AI in national defense, it is essential to have policy support at the governmental or national level. This includes establishing a research and development infrastructure, creating a common development environment, and fostering AI expertise through education and training programs. To achieve advancements in hyper-connected networks, it is essential to establish a foundation for a robust and resilient infrastructure by comprehensively building integrated satellite, aerial, and ground networks, along with developing 5G & edge computing and low-orbit satellite communication technologies. This multi-faceted approach will ensure the successful integration of AI and hyper-connected networks, strengthening national defense and positioning nations at the forefront of technological advancements in warfare.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.733-740
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.