• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.521-524
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• 2023

본 연구에서는 AI 인공지능을 활용한 통일신라 석탑 '경주 불국사 삼층석탑' 복원을 위해 석탑 3D모델링 과정에 대한 연구를 수행하였다. 산성비로 부식되어 갈라진 더 이상 원본의 형태를 알아 볼 수 없는 현재 통일신라 석탑 형태를 3D모델링 작업을 통하여 AI로 하여금 원활한 교육이 실시 되도록 하는 것을 목표로한다. 본래 제작 되어있는 3D 모델링은 많은 버텍스와 페이스로 학습 데이터가 많아 실제 활용하기에 어려움을 가지고 있다. 때문에 적은 양의 버텍스와 페이스로 새로운 3D 모델링 제작에 대한 필요성에 대해 확인하였다. 본 연구는 그에 필요한 석탑 모델링 과정에 대해 서술한다. 이를 위해 본 논문은 석탑에 대한 구조를 살피고 모델링에 활용된 프로그램의 장단점과 분석을 도출하였다. 본 연구를 통해 석탑 복원에 필요한 3D모델링 프로그램 활용의 전망과 더불어 인공지능 AI의 한계점을 3D 모델링의 정확도와 세밀함을 통하여 타파하고자 하였다.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.573-584
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• 2020

This study is about the development of AI algorithm education program using cognition modeling to positively improve students' image on AI. First, we analyzed the concept of user-based collaborative filtering and developed the education program using the cognition modeling method. We checked the adequacy of program through the expert validity test. Both CVR values for the content development method of cognitive modeling and the developed program showed validity above .80. We applied the developed program to elementary school students in class. The test was conducted using a semantic discrimination to examine changes in students' perception of artificial intelligence before and after. We were able to confirm that the students' AI images were significant positive change in 12 of the 23 words in the adjective pair.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.525-527
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• 2023

본 논문은 2차원적인 문화재 이미지를 모델링 하여, 대한민국의 시대 별 탑의 차이점과 특징을 분석하고 인공지능을 이용한 3D 복원과 구현을 위한 연구이다. 오늘날 현대 사회에서 디지털 매체 및 정보화 시대에서 여러 산업 분야에 적용이 되고 있다. 기존 2D 이미지를 벗어나 문화재의 모습을 다양한 각도에서 쉽게 관찰해 볼 수 있도록 하여, 3D 형태의 복원이 적합하여 연구를 진행하였다. 최근 인공지능 및 기술의 발달로 문화재 정보를 바탕으로 한 3차원 기술을 사용하여 다양한 데이터들과 프로그램을 이용한 모델링이 가능하다. 현재 문화재 복원은 다양한 자료와 전문가의 기술 및 역사적인 기록물 자료에 의존해 복구한다. 이러한 기법의 문화재 복원은 기록에 남길 수 있는 정보 수집의 효율적인 방법이 될 수 있다. 본 연구는 우리나라의 시대별 탑의 특징을 보여주며, 복원이 실제적이고도 구체적인 다각도의 방향에서 더 정밀하고 정확하게 도출하는데 기여할 것으로 기대된다.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.75-87
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• 2020

The present study determined new value that can be created through the convergence between artificial intelligence technology (AIT) and all industries by deriving and thoroughly analyzing major issues related to artificial intelligence (AI). This study analyzes domestic articles related to AI using topic modeling method based on LDA algorithm. Keywords were extracted from 3,889 articles of eleven metropolitan newspapers, eight business newspapers and major broadcasting companies; articles were selected by searching for the keyword "artificial intelligence". Keywords were extracted by optimizing the relevance parameter λ to improve the measure of pointwise mutual information (PMI), which shows the association among the keywords of each topic, and topic names were inferred from keywords based on valid evidence. The extracted topics widely showed changes occurring throughout society, economy, industries, culture, and the support policy and vision of the government.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.27-34
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• 2023

This paper studied the 3D modeling process for the restoration of the 'Three-story Stone Pagoda of Bulguksa Temple in Gyeongju', a stone pagoda from the Unified Silla Period, using artificial intelligence (AI). Existing 3D modeling methods generate numerous verts and faces, which takes a considerable amount of time for AI learning. Accordingly, a method of performing more efficient 3D modeling by lowering the number of verts and faces is required. To this end, in this study, the structure of the stone pagoda was deeply analyzed and a modeling method optimized for AI learning was studied. In addition, it is meaningful to propose a new 3D modeling methodology for the restoration of stone pagodas in Korea and to secure a data set necessary for artificial intelligence learning.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.197-209
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• 2024

This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.325-326
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• 2023

본 논문은 2차원적인 이미지를 모델링 하여, 대한민국의 보물 제750호이자 오래된 거돈사지 삼층석탑의 복원과 구현을 위한 연구이다. 기존 2D 이미지를 벗어나 문화재의 특성상 3D 형태의 복원이 적합하여 연구를 진행하였다. 문화재 복원은 자료와 전문가의 기술 및 역사적인 기록물 자료에 의존해 복구한다. 최근 인공지능 및 기술의 발달로 문화재 정보를 바탕으로 한 3차원 기술을 사용하여 다양한 데이터들과 프로그램을 이용한 모델링이 가능하다. 본 연구는 거돈사지 삼층석탑의 복원이 실제적이고도 구체적인 다각도의 방향에서 더 정밀하고 정확하게 도출하는데 기여할 것으로 기대된다.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• Journal of the Korean School Mathematics Society
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• v.26 no.1
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• pp.1-19
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• 2023

This study analyzed the international trends of research concerning artificial intelligence in education by examining 352 papers recently published in the International Journal of Artificial Intelligence in Education(IJAIED) with the topic modeling method. The IJAIED is the official, SCOPUS-indexed journal of the International AIED Society. The analysis revealed that international AIED research trends could be categorized into eight topics with topics such as analyzing student behavior model in learning systems and designing feedback to student solutions being increased over time, whereas research focusing on data handling methods was decreased over time. Based on the findings implications and suggestions for the research and development of the applications of AIED were provided.

• Informatization Policy
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• v.29 no.4
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• pp.43-66
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• 2022

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.