• KEPCO Journal on Electric Power and Energy
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• 제6권4호
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• pp.399-404
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• 2020

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.

• 전자통신동향분석
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• 제35권7호
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• pp.56-66
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• 2020

As the development of artificial intelligence (AI) technology spreads to various industrial sectors, diversity in AI utilization rapidly increases, creating rich user experience. In addition, AI is required to solve various social problems through the use of public data. The spread of AI utilization across all sectors will continue, covering such industrial and public demands. This article examines the domestic and international trends in AI utilization technologies and establishes the direction of research and development (R&D), which is highly consistent with Korea's AI policy. ETRI, which leads AI's national R&D, has used its experience to establish AI R&D implementation strategies as well as technology roadmaps for the utilization of AI to improve individual quality of life, continuous growth in society, industrial innovation, and the solutions to public societal problems. In addition, it has derived tasks and implementation strategies for developing AI utilization technologies in 10 major areas including medical services.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.442-448
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• 2023

Artificial Intelligence (AI) technology has recently grown explosively and is being used in a variety of application fields. Accordingly, the number of AI models is rapidly increasing. AI models are adapted and developed to fit a variety of data types, tasks, and environments, and the variety and volume of models continues to grow. The need to share models and collaborate within the AI community is becoming increasingly important. Collaboration is essential for AI models to be shared and improved publicly and used in a variety of applications. Therefore, with the advancement of AI, the introduction of Model Hub has become more important, improving the sharing, reuse, and collaboration of AI models and increasing the utilization of AI technology. In this paper, we collect data on the model hub and analyze the characteristics of the model hub and the AI models provided. The results of this research can be of great help in developing various multimodal AI models in the future, utilizing AI models in various fields, and building services by fusing various AI models.

• 한국BIM학회 논문집
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• 제14권2호
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• pp.13-24
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• 2024

This research suggests a novel visualization approach utilizing Generative AI to render photorealistic architectural alternatives images in the early design phase. Photorealistic rendering intuitively describes alternatives and facilitates clear communication between stakeholders. Nevertheless, the conventional rendering process, utilizing 3D modelling and rendering engines, demands sophisticate model and processing time. In this context, the paper suggests a rendering approach employing the text-to-image method aimed at generating a broader range of intuitive and relevant reference images. Additionally, it employs an Text-to-Image method focused on producing a diverse array of alternatives reflecting architects' styles when visualizing the exteriors of residential buildings from the mass model images. To achieve this, fine-tuning for architects' styles was conducted using the Low-Rank Adaptation (LoRA) method. This approach, supported by fine-tuned models, allows not only single style-applied alternatives, but also the fusion of two or more styles to generate new alternatives. Using the proposed approach, we generated more than 15,000 meaningful images, with each image taking only about 5 seconds to produce. This demonstrates that the Generative AI-based visualization approach significantly reduces the labour and time required in conventional visualization processes, holding significant potential for transforming abstract ideas into tangible images, even in the early stages of design.

• 실천공학교육논문지
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• 제15권2호
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• pp.357-364
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• 2023

인공지능 기술의 급속한 발전으로 인해 생성형 인공지능 플랫폼은 다양한 분야에서 혁신적인 활용이 이루어지고 있다. 본 논문에서는 인공지능을 교육에 활용한 연구사례, 생성형 인공지능 플랫폼이 컴퓨터그래픽 영역에 활용된 사례를 살펴보고, 생성형 인공지능 교육 방향성에 대해 논의하였다. 컴퓨터그래픽에서 이미지 생성과 편집, 영상편집에 활용 가능한 생성형 인공지능 플랫폼을 소개하고, 영상편집 제작과정에 적용할 수 있도록 활용방법을 제안하였다. 이러한 생성형 인공지능 플랫폼은 제작공정에서 창작자의 수고를 덜고, 시간을 단축시킨다는 효율성 측면에서도 장점뿐만 아니라 개인의 역량을 증진할 수 있다. 컴퓨터그래픽 제작에 있어 생성형 인공지능 플랫폼은 다양한 변화를 가져다 주었다. 그런 변화를 살펴보고 생성형 인공지능 플랫폼을 활용한 창작 교육에 방향성을 제시하고자 한다.

• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.225-230
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• 2023

With the development of AI technology, there is a growing discussion about Text-to-Image Generative AI. We presented a Generative AI video production method and delineated a methodology for the production of personalized AI-generated videos with the objective of broadening the landscape of the video domain. And we meticulously examined the procedural steps involved in AI-driven video production and directly implemented a video creation approach utilizing the VQGAN-CLIP model. The outcomes produced by the VQGAN-CLIP model exhibited a relatively moderate resolution and frame rate, and predominantly manifested as abstract images. Such characteristics indicated potential applicability in OTT-based video content or the realm of visual arts. It is anticipated that AI-driven video production techniques will see heightened utilization in forthcoming endeavors.

• 정보교육학회논문지
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• 제25권3호
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• pp.437-448
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• 2021

4차 산업혁명의 핵심 기술인 인공지능은 정치, 문화, 산업, 경제 등 사회의 여러 분야에 적용되며 혁명적인 변화를 야기하고 있다. 이에 따라 인공지능 시대를 이끌 학생들에게 인공지능으로 인한 사회의 변화를 인식하고, 인공지능에 대한 지식을 습득하며, 다양한 상황에서 인공지능을 활용할 수 있는 역량이 요구된다. 하지만 초등학생의 평균적 발달 수준에서는 인공지능의 개념과 원리를 학습하기에 어려움이 있다. 따라서 본 연구는 초등학생의 수준에 맞는 인공지능 교육 내용과 방법을 선정하여 교육 프로그램을 체계적으로 개발하고 이를 실제 교육현장에 적용함으로써 그 효과를 검증하고자 하였다. 본 연구에서 선정한 내용 체계는 인공지능으로 변화된 사회를 인식하는 'AI 사회인식', 인공지능을 체험하고 원리를 이해하는 'AI 이해하기', 인공지능을 활용해 실생활의 문제를 해결하는 'AI 활용하기'이고, 이에 따라 세부적으로 8가지 내용 요소들을 함께 구성하였다. 교육 방법으로는 활동중심, 타 교과 융합, 프로젝트기반학습으로 선정하여 초등학생의 수준에서 쉽고 즐겁게 인공지능을 학습할 수 있도록 총 20차시의 교육 프로그램을 개발하여 적용하였다. 또한 '인공지능에 대한 인식', '융합적 사고력', '창의적 문제해결력'과 '협업 역량'의 측면에서 프로그램의 적용 효과를 분석하였으며, 4가지 측면 모두에 대해 긍정적인 변화를 검증하였다.

• 정보화정책
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• 제31권2호
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• pp.39-64
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• 2024

본 연구는 AI 인적자본, AI 기반 인프라, AI 기술혁신역량 요인을 중심으로 OECD 38개국의 국가 AI 경쟁력 수준을 확인하고, 퍼지셋 이상형 분석방법을 활용하여 OECD 38개국을 국가 AI 경쟁력 수준에 따라 여덟 가지 유형으로 분류, 시사점을 도출하였다. 분석 결과, "AI 선도국" 유형에는 대체적으로 북미, 서유럽, 북유럽 국가와 함께, 대한민국을 포함하는 아시아 국가들이 포함되었다. 특히 미국은 국가 AI 경쟁력 3개 요인 모두에서 분석 대상 국가 중 가장 높은 퍼지점수를 보이는 등 글로벌 국가AI 경쟁력을 압도하는 모습을 보였다. 대한민국의 경우, 우수한 AI 기반 인프라 수준을 바탕으로 AI 선도국 유형에 포함되었으나, AI 인적자본과 AI 기술혁신역량 요인은 분석 대상 국가 중 중위권 수준에 머무르고 있어 향후 장기적 관점에서의 AI 인적자본 축적과 AI 기술혁신역량 강화가 요구된다.

• 전자통신동향분석
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• 제36권1호
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• pp.81-88
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• 2021

Post COVID-19, the medical legacy system will be transformed for utilizing medical resources efficiently, minimizing medical service imbalance, activating remote medical care, and strengthening private-public medical cooperation. This can be realized by achieving an entire medical paradigm shift and not simply via the application of advanced technologies such as AI. We propose a medical system configuration named "Medical AI Hub" that can realize the shift of the existing paradigm. The development stage of this configuration is categorized into "AI Cooperation Hospital," "AI Base Hospital," and "AI Hub Hospital." In the "AI Hub Hospital" stage, the medical intelligence in charge of individual patients cooperates and communicates autonomously with various medical intelligences, thereby achieving synchronous evolution. Thus, this medical intelligence supports doctors in optimally treating patients. The core technologies required during configuration development and their current R&D trends are described in this paper. The realization of the central configuration of medical AI through the development of these core technologies will induce a paradigm shift in the new medical system by innovating all medical fields with influences at the individual, society, industry, and public levels and by making the existing medical system more efficient and intelligent.

• 한국IT서비스학회지
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• 제20권5호
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• pp.43-54
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• 2021

Currently, citizens' expectations and concerns on utilizing artificial intelligence (AI) technologies in the public sector are widening with the rapid digital transformation. Furthermore the level of global acceptance on the AI and other intelligent digital technologies is augmenting with the needs of non-face-to-face types of public services more than ever due to the unforeseen and unpredictable pandemic, COVID-19. Thus, this study intended to empirically examine what policy directions for the public should be considered to provide well-designed services as well as to promote the evidence-based public policies in terms of Al speaker technology as a non-contact smart city service. Based on the survey of senior citizens' perceptions on AI (AI Speaker technology), this study conducted structure equation modeling analyses to identify whether technology acceptance models on to the varied dependent variables such as actual use, perception, attitude, and brand royalty. The Results of the empirical analyses showed that AI increased the positive level of citizens' perception, attitude and brand royalty on non-contact public services (smart city services) which are becoming more crucial for developing AI oriented government and providing intelligent public services effectively. In addition, theoretical and practical implications are discussed for understanding the changes of public service in the post-corona.