• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.241-249
• /
• 2022

Artificial intelligence is applied not only to the daily life of individuals but also to all industries, and it is no wonder that the age of artificial intelligence has arrived. Therefore it is important to understand the factors that influence the acceptance of AI. This study analyzes whether "AI Effect" which recognizes that commercialized or familiar artificial intelligence is no longer artificial intelligence, affects the acceptance of artificial intelligence and proposes an acceptance plan based on the results. Two experiments were conducted. The first experiment was conducted on 105 adults in the result it was found that 32.4% (34 people) had AI Effect, AI Effect existed in 43.6% (24 people) of women and 20% (10 people) of men, that is, the proportion of AI Effect exsitence in women is about twice as high.and AI Effect exists when the level of AI knowledge is low. The second experiment was conducted 240 adults and 85 participants with AI Effect were selected. We found the group that recognized experience of AI accepted AI more actively. Understanding of AI Effect is expected to suggest companies' views in order to enhance AI capabilities and acceptance. In addition, future studies are expected on considering individual differences or related to acceptance attitudes.

• Journal of The Korean Association of Information Education
• /
• v.26 no.5
• /
• pp.407-416
• /
• 2022

Although environmental education has been more important due to global extreme weather and natural desasters, environmental topics are covered by several other subjects because it is not an independent subject in elementary school and they need to distribute more class hours to cover proper amount of environmental content. This study is performed to develop method to integrate environmental education and software education in elementary school. This method helps students to learn topics about recycling by using Artificial Intelligence programming and Artificial Intelligence also helps students to practice recycling in virtual reality. A new teaching and learning module(Problem Recognition→Machine Learning↔Use of AI→Collaboration) is adopted for the learning procedure and more than 80 % of the students replied positively to the survey about the interest on integrated learning, understanding of environmental education, understanding of Artificial Intelligence, further learning on Artificial Intelligence programming.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.461-463
• /
• 2020

2025년 초고령 사회로 진입할 것으로 예상됨에 따라 고령화 시대에 발생하는 문제점들을 IT기술을 응용하여 지능적으로 해결할 수 있는 인공지능 헬스케어 솔루션이 주목받고 있다. BIS리서치의 보고서에 따르면 헬스케어 산업의 챗봇 시장 규모가 2029년 약 4억 9,800만 달러로 성장할 것으로 예상된다. 따라서 시니어 사용자를 위한 기술 연구가 적극적으로 필요한 시점이다. 본 논문에서는 사전학습한 언어모델과 BiLSTM기반 신경망 모델을 이용하여 시니어 사용자에게 특화된 질환 증상 인식 모델 구현에 관한 범위 및 방법에 관해 기술한다. 이는 시니어 대상 건강관리 챗봇 솔루션에 도입하여 시니어 사용자에게 자주 발생하는 질환들을 조기에 발견할 수 있도록 지원하여 위험의 발생 예방에 도움을 주는 서비스가 될 것으로 전망한다.

• Journal of Digital Convergence
• /
• v.15 no.5
• /
• pp.225-233
• /
• 2017

In this paper, we collected the articles related to artificial intelligence among SCI(E) journals published by Korean authors in 'Web of Science' and conducted frequency analysis and keyword network analysis. As a result of the analysis, the artificial intelligence thesis showed an average growth of about 10% per year, but the relative ratio decreased. As time went on, we could confirm that there is a lot of practical and applied research in artificial intelligence research. Unlike the US 'National Strategy for Artificial Intelligence Research and Development,' the field of research in Korea was focused on local and technical aspects. Therefore, Korea should go beyond the theoretical and technical iterations of artificial intelligence, and research should be carried out to present a comprehensive future direction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.4
• /
• pp.283-292
• /
• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• Annual Conference on Human and Language Technology
• /
• 2023.10a
• /
• pp.704-706
• /
• 2023

이 논문에서는 과학기술분야 특화 한국어 사전학습 언어모델인 KorSciDeBERTa를 소개한다. DeBERTa Base 모델을 기반으로 약 146GB의 한국어 논문, 특허 및 보고서 등을 학습하였으며 모델의 총 파라미터의 수는 180M이다. 논문의 연구분야 분류 태스크로 성능을 평가하여 사전학습모델의 유용성을 평가하였다. 구축된 사전학습 언어모델은 한국어 과학기술 분야의 여러 자연어처리 태스크의 성능향상에 활용될 것으로 기대된다.

• The Mathematical Education
• /
• v.62 no.3
• /
• pp.303-326
• /
• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Journal of Broadcast Engineering
• /
• v.26 no.1
• /
• pp.70-78
• /
• 2021

Estimating 3D information from a single image is one of the essential problems in numerous applications. Since a 2D image inherently might originate from an infinite number of different 3D scenes, thus 3D reconstruction from a single image is notoriously challenging. This challenge has been overcame by the advent of recent deep convolutional neural networks (CNNs), by modeling the mapping function between 2D image and 3D information. However, to train such deep CNNs, a massive training data is demanded, but such data is difficult to achieve or even impossible to build. Recent trends thus aim to present deep learning techniques that can be trained in a weakly-supervised manner, with a meta-data without relying on the ground-truth depth data. In this article, we introduce recent developments of weakly-supervised deep learning technique, especially categorized as scene 3D reconstruction and object 3D reconstruction, and discuss limitations and further directions.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.956-959
• /
• 2020

본 연구에서는 아파트를 대표할 수 있는 내·외적 데이터를 수집하고 인공지능 기술들을 활용하여 아파트 가격을 예측하는 시스템을 구축하고자 한다. 구체적으로 웹크롤링 기법을 통해 수집한 아파트 내·외적 데이터의 변수들에 대한 특성 선택(Feature Selection)을 수행하였고, 다양한 인공지능 기법을 활용하여 부동산 가격 예측 모형을 개발하였다. 아파트 가격 예측 모형 생성을 위해 Linear Regression, Ridge, Xgboost, Lightgbm, Catboost 등의 기계학습 알고리즘을 사용하였고, RMSE를 사용하여 각 예측 모형 간의 성능 비교를 수행하였다. 가장 성능이 좋은 예측 모형은 Xgboost기반 예측 모형이였으며, RMSE값이 약 0.0366으로 가장 낮았으며 테스트 데이터에 대한 정확도는 약 95.1%였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.01a
• /
• pp.289-290
• /
• 2022

본 논문에서는 약을 제 시간에 복용할 수 있도록 도와주는 스마트 약통 서비스를 개발한 결과를 보인다. 라즈베리파이, 자석감지센서, LED, AI스피커와 외부서버를 결합한 구조로 개발하였으며, 사용자는 약을 복용하였는지에 따라 AI스피커를 통해서 약 복용 여부를 물어볼 수 있고 LED를 통해서 아침, 점심, 저녁의 시간에 따라 복용해야 하는 약을 표시해 줄 수 있도록 하였다.