• International journal of advanced smart convergence
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• 제12권3호
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• pp.186-191
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• 2023

This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.90-95
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• 2023

With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.56-61
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• 2023

The present study explored a comprehensive investigation of university professors' perspectives on the implementation of ChatGPT - an artificial intelligence-powered language model - in their teaching practices. A diverse group of 30 university professors responded to a questionnaire about the level of their interest in implementing the tool, willingness to apply it, and concerns they have regarding the intervention of ChatGPT in higher education setting. The results showed that the participants are highly interested in employing the tool into their teaching practice, and find that the students are likely to benefit from using ChatGPT in classroom settings. On the other hand, they displayed concerns regarding high depandency on data, privacy-related issues, lack of supports required, and technical contraints. In today's fast-paced society, educators are urged to mindfully apply this inevitable generative AI means with thoughtfulness and ethical considerations to and for their learners. Relevant topics are discussed to successfully intervene AI tools in teaching practices in higher education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.713-725
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• 2022

Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.

• 한국측량학회지
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• 제38권6호
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• pp.499-509
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• 2020

본 연구에서는 최근 영상판독 분야에서 활발히 연구되고, 활용성이 발전하고 있는 인공지능 기반 객체분류 학습 데이터 구축에 관한 내용을 다룬다. 영상판독분야에서 인공지능을 활용하여 정확도 높은 객체를 인식, 추출하기 위해서는 알고리즘에 적용할 많은 양의 학습데이터가 필수적으로 요구된다. 하지만, 현재 공동활용 가능한 데이터 셋이 부족할 뿐만 아니라 데이터 생성을 위해서는 많은 시간과 인력 및 고비용을 필요로 하는 것이 현실이다. 따라서 본 연구에서는 소량의 초기 항공영상 학습데이터를 GAN (Generative Adversarial Network) 기반의 생성기 신경망을 활용하여 오버샘플 영상 학습데이터를 구축하고, 품질을 평가함으로써 추가적 학습 데이터 셋으로 활용하기 위한 실험을 진행하였다. GAN을 이용하여 오버샘플 학습데이터를 생성하는 기법은 딥러닝 성능에 매우 중요한 영향을 미치는 학습데이터의 양을 획기적으로 보완할 수 있으므로 초기 데이터가 부족한 경우에 효과적으로 활용될 수 있을 것으로 기대한다.

• 한국지구과학회지
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• 제44권6호
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• pp.675-692
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• 2023

This study used a Chatbot, a generative artificial intelligence (AI), to analyze the interaction between the Chatbot and students when exploring critical minerals from an epistemological aspect. The results, issues to be kept in mind in the teaching and learning process using AI were discussed in terms of the role of the teacher, the goals of education, and the characteristics of knowledge. For this study, we conducted a three-session science education program using a Chatbot for 19 high school students and analyzed the reports written by the students. As a result, in terms of form, the students' questions included search-type questions and non-search-type questions, and in terms of content, in addition to various questions asking about the characteristics of the target, there were also questions requiring a judgment by combining various data. In general, students had a questioning strategy that distinguished what they should aim for and what they should avoid. The Chatbot's answer had a certain form and consisted of three parts: an introduction, a body, and a conclusion. In particular, the conclusion included commentary or opinions with opinions on the content, and in this, value judgments and the nature of science were revealed. The interaction between the Chatbot and the student was clearly evident in the process in which the student organized questions in response to the Chatbot's answers. Depending on whether they were based on the answer, independent or derived questions appeared, and depending on the direction of comprehensiveness and specificity, superordinate, subordinate, or parallel questions appeared. Students also responded to the chatbot's answers with questions that included critical thinking skills. Based on these results, we discovered that there are inherent limitations between Chatbots and students, unlike general classes where teachers and students interact. In other words, there is 'limited interaction' and the teacher's role to complement this was discussed, and the goals of learning using AI and the characteristics of the knowledge they provide were also discussed.

• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.182-190
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• 2024

Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

• 핵의학기술
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• 제24권1호
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• pp.15-19
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• 2020

본 연구는 최근에 활발히 연구되고 있는 딥러닝 기술인 생성적 적대 신경망(GAN)을 핵의학 영상에 적용하여 잠재적으로 유용성이 있는지 확인해보고자 하였다. 본원에서 ¹⁸F-FDG Brain PET/CT검사를 진행한 30명의 환자를 대상으로 하였고 List모드로 15분 검사한 후 이를 1, 2, 3, 4, 5분 초기획득시간 이미지로 재구성하였다. 이 중 25명의 환자를 GAN모델의 학습을 위한 트레이닝 이미지로 사용하고 5명의 환자를 학습된 GAN모델의 검증을 위한 테스트 이미지로 사용하였다. 학습된 GAN모델에 입력으로 1, 2, 3, 4, 5분의 초기획득 이미지를 넣고 출력으로 15분 인공지능 표준획득 이미지를 획득한 후 이를 기존의 15분 표준획득시간 검사 이미지와 비교 평가하였다. 평가에는 정량화된 이미지 평가방법인 평균제곱오차, 최대신호 대 잡음비, 구조적 유사도 지수를 이용하였다. 평가 결과 초기획득시간 이미지에서 1에서 5분으로 갈수록 실제 표준획득시간 이미지에 가까운 평균제곱오차, 최대신호 대 잡음비, 구조적 유사도 지수 수치를 나타내었다. 이러한 연구를 통해 앞으로 인공지능 기술이 핵의학 분야에서 의료영상의 획득시간 단축과 관련하여 중요한 영향을 미칠 수 있을 것으로 사료된다.

• 한국인터넷방송통신학회논문지
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• 제21권3호
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• pp.99-105
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• 2021

넥플릭스,유튜브로 대표되는 OTT 동영상 제작 서비스에 인공지능으로 콘텐츠를 개인별 맞춤식 추천 시스템은 보편화 되었다. 유튜브의 개인별 맞춤 추천서비스 시스템은 두 개의 신경망으로 구성되는데 신경망 하나는 추천 후보생성 모델이고 다른 하나는 순위평가 네트워크로 구성된다. Netflix의 동영상 추천 시스템은 두 개 데이터 분류 시스템으로 구성되어 있으며 콘텐츠 기반 필터링과 협업 필터링으로 나누어진다. 코로나 펜데믹으로 온라인 플랫폼 주도의 콘텐츠 제작이 활성화 되면서 인공지능을 활용한 가상 인플루언서 분야가 부각되고 있다. 가상인플루언서는 GAN(Generative Adversarial Networks) 인공지능으로 제작되는데 성격이 다른 두 시스템이 서로 경쟁하는 방식으로 학습이 반복되는 비교사(Unsupervised) 학습 알고리즘이다. 이 연구는 AI 개인별 추천 기반 플랫폼과 가상인플루언서(메타버스)가 향후 OTT의 핵심콘텐츠로의 발전 가능성도 연구해 보았다.

• 한국컴퓨터정보학회논문지
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• 제29권7호
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• pp.53-71
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• 2024

생성형 인공지능은 그 광범위한 응용 범위와 깊은 영향력으로 인해 사회의 주목을 받고 있습니다. 본 논문은 통합 기술 수용 및 사용 이론 2(UTAUT2)를 기반으로 개인의 혁신성과 인지된 위험 등의 변수를 결합하여, 기업이 생성형 인공지능을 채택하는 데 영향을 미치는 주요 요인을 연구하기 위해 종합적인 이론 모델을 구축하였습니다. 우리는 가설 경로를 검증하기 위해 구조 방정식 모델(SEM)을 사용하였고, 부트스트래핑 방법을 통해 수용 의향의 매개 효과를 검증하였으며, 계층적 회귀 분석을 통해 인지된 위험의 조절 효과를 탐구하였습니다. 연구 결과, 성과 기대, 노력 기대, 사회적 영향, 가치 평가 및 개인 혁신성이 수용 의향에 긍정적인 영향을 미치며, 수용 의향은 이러한 요인들과 사용 행동 사이에서 중요한 매개 역할을 한다는 것이 밝혀졌습니다. 반면, 인지된 위험은 수용 의향과 사용 행동 사이에서 부정적인 조절 효과를 가지는 것으로 나타났습니다. 본 연구는 기업이 생성형 인공지능을 효과적으로 채택하는 방법에 대해 이론적 근거와 실증적 지원을 제공하며, 중요한 실무적 의의를 가집니다.