• Journal of radiological science and technology
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• v.47 no.4
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• pp.255-262
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• 2024

Although a universally accepted definition of artificial intelligence (AI) remains elusive, the terminology has gained widespread familiarity owing to its pervasive integration across diverse domains in our daily lives. The application of AI in healthcare, notably in radiographic imaging, is no longer a matter of science fiction but a reality. Consequently, AI education has emerged as an indispensable requirement for radiological technologists responsible for the field of radiology. This paper underscores this imperative and advocates for the incorporation of AI education, using the Orange platform in university radiology department as part of the solution. Furthermore, this paper presents a case study featuring machine learning analysis using structured data on exposure doses for radiation related workers and unstructured data consisting of X-ray data encompassing 69 COVID-19-infected cases and 25 individuals with normal findings. The emphasized importance of AI education for radiology professionals in this research is expected to contribute to the job stability of radiologic practitioners in the future.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.361-364
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• 2022

This study was carried out for the purpose of Exploring the types of AI platforms for creative activities and how to use them. In order to learn AI in the fields of art creation and music creation, which are representative areas of creative activity, types of AI platforms that can experience AI and perform simple programming were investigated. In addition, the utilization plan was presented so that each AI platform can be used to express students' ideas abundantly and to enhance their creativity. Through this, it is meaningful to suggest that the AI platform can be used as a teaching aid to enhance students' expressive power and creativity in creative activities.

• Journal of Smart Tourism
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• v.3 no.2
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• pp.1-3
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• 2023

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.79-84
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• 2022

Due to a series of online sex crimes cases and online class conversions caused by the spread of the coronavirus, alternatives to sex education in schools are urgently required. As a result of this study, the metaverse sex education platform was designed. Using this platform, learners are expected to cultivate correct adult awareness and digital citizenship. Within the metaverse platform, learners can participate more actively in learning. Instead of exposing one's name and face in a place dealing with sensitive gender issues, one can participate in education through his or her decorated avatar and participate in education much more actively than face-to-face education and express one's opinion through chat. In addition, education by level can be received regardless of time and place, which can have the effect of bridging the educational gap between urban and rural areas. In this paper, we propose a new sex education platform without time and space constraints by utilizing metaverse.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.395-396
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• 2023

본 논문에서는 디지털 전환 시대에 모든 사람들이 인공지능(AI) 체험부터 피지컬컴퓨팅을 통해서 SW·AI 융합해 아이디어를 쉽게 구현하고 교육 받을 수 있는 플랫폼을 구현하였다. AI 체험을 위해 P5.js와 텐서플로우에 기반한 ML5.js 라이브러리를 이용해 블록 코딩을 할 수 있도록 하였다. 또한 피지컬컴퓨팅에서는 마이크로비트와 아두이노, 라즈베리파이 등을 WebUSB를 통해서 PC와 연결하고 플랫폼에서 인공지능의 다양한 서비스와 융합시킬 수 있도록 제공한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.387-388
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• 2023

본 논문에서는 인공지능(AI) 체험부터 초중등, 대학 및 평생교육에서 필요한 광범위한 응용과 활용을 할 수 있는 라이브러리를 디지털북 형태로 지원하며, 블록과 텍스트 코딩의 장점을 취합해 입문자들이 쉽고 재미있게 SW·AI 융합 교육을 할 수 있는 플랫폼을 구현하였다. 플랫폼은 웹어셈블리 기반의 파이오다이드를 통해 웹 브라우저에서 파이썬 코딩을 가능하게 하고 복잡한 설치과정 없이 쉽게 이용이 가능하다. 다양한 LMS와 연동이 가능하도록 API를 제공하며, Drag & Fill 블록으로 입문자가 코딩에 겪는 어려움 중 하나인 많은 양의 함수와 파라미터 사용법의 어려움을 해소하였다. 플랫폼은 블록으로 코딩하여 문법의 어려움, 오탈자, 오류 등을 줄이는 동시에 블록에서 생성되는 파이썬 텍스트 코드로 입문자가 텍스트 코드에 익숙해질 수 있는 경험을 제공한다.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Information Systems Review
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• v.26 no.1
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• pp.119-149
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• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.