• 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'.

• Communications of Mathematical Education
• /
• v.37 no.2
• /
• pp.277-297
• /
• 2023

In mathematics, the concept of convolution is widely used. The convolution operation is required for understanding computer vision and deep learning in artificial intelligence. Therefore, it is vital for this concept to be explained in college mathematics education. In this paper, we present our new teaching and learning materials on convolution available for engineering mathematics. We provide the knowledge and applications on convolution with Python-based code, and introduce Convolutional Neural Network (CNN) used for image classification as an example. These materials can be utilized in class for the teaching of convolution and help students have a good understanding of the related knowledge in artificial intelligence.

• Convergence Security Journal
• /
• v.23 no.2
• /
• pp.55-66
• /
• 2023

Recently, there is an increasing movement to increase the value of AI learning data and to secure high-quality data based on previous research on AI learning data in all areas of society. Therefore, quality management is very important in construction projects to secure high-quality data. In this paper, quality management to secure high-quality data when building AI learning data and improvement plans for each construction process are presented. In particular, more than 80% of the data quality of unstructured data built for AI learning is determined during the construction process. In this paper, we performed quality inspection of image/video data. In addition, we identified inspection procedures and problem elements that occurred in the construction phases of acquisition, data cleaning, labeling, and models, and suggested ways to secure high-quality data by solving them. Through this, it is expected that it will be an alternative to overcome the quality deviation of data for research groups and operators participating in the construction of AI learning data.

• Electronics and Telecommunications Trends
• /
• v.27 no.5
• /
• pp.55-63
• /
• 2012

빅데이터 시대를 맞이하여 이를 분석하여 지능형 서비스로 활용할 수 있는 기술로 인공지능 기술이 다시 관심을 받고 있다. 본고에서는 인공지능의 여러 요소 기술 중 기계학습(machine learning) 분야의 빅데이터 처리를 위한 동향을 소개한다. 현재 사용 가능한 병렬처리 기반의 기계학습, 빅데이터를 이용한 기계학습 기반으로 진행되고 있는 프로젝트, 다양한 분야에 쉽게 기계학습을 적용할 수 있는 domain adaptation 기술에 대해서 정리한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.177-179
• /
• 2022

In the Google Deepmind Challenge match, Alphago defeated Korea's Sedol Lee (human) with 4 wins and 1 loss in the Go match. Finally, artificial intelligence is going beyond the use of human intelligence. The Korean government's budget for the Digital New Deal is 9 trillion won in 2022, and an additional 301 types of data construction projects for artificial intelligence learning will be secured. From 2023, the industrial paradigm will change with the use and application of learning of artificial intelligence in all fields of industry. This paper conducts research to utilize artificial intelligence algorithms. Focusing on the analysis and judgment of data in artificial intelligence learning, research on the appropriate target and scope of application of algorithms in artificial intelligence machine learning and deep learning learning is conducted. This study will provide basic data for artificial intelligence in the 4th industrial revolution technology and artificial intelligence robot use in the 5th industrial revolution technology.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.123-129
• /
• 2021

Recently, various platforms and contents for artificial intelligence education have been developed, but artificial intelligence education programs for the lower grades of elementary school are insufficient. Therefore, the purpose of this study is to develop an artificial intelligence education program for learners in the lower grades of elementary school. It was designed using the Novel Engineering, and its validity was verified by expert validation. It was necessary to construct a program based on spoken language rather than written language in consideration of the level of learners in the lower grades in the process of acquiring Hangeul, and to secure the number of educational hours through integration between subjects. There have been various research cases of software education with Novel Engineering, and its effectiveness has been verified. Artificial intelligence education is also expected to be applied in the school field through Novel Engineering.

• Journal of The Korean Association of Information Education
• /
• v.25 no.5
• /
• pp.761-768
• /
• 2021

Recently, various platforms and contents for artificial intelligence education have been developed, but artificial intelligence education programs for the lower grades of elementary school are insufficient. Therefore, the purpose of this study is to develop an artificial intelligence education program for learners in the lower grades of elementary school. It was designed using the Novel Engineering with various convergence education research cases for software education. After the first program was developed, it was verified by expert validity test, and the program was modified and developed accordingly. It was necessary to construct a program based on spoken language rather than written language in consideration of the level of learners in the lower grades in the process of acquiring Hangeul, and to secure the number of educational hours through integration between subjects. It is expected that this study can suggest a new direction for artificial intelligence education for elementary and lower grade learners.

• Journal of Christian Education in Korea
• /
• v.66
• /
• pp.309-341
• /
• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Review of KIISC
• /
• v.27 no.3
• /
• pp.27-32
• /
• 2017

머신러닝을 위주로 하는 인공지능 기술이 여러 분야에서 다양하게 적용되고 있다. 머신러닝 기술은 시험 데이터에 대해 높은 성능을 보였지만, 악의적으로 만들어진 데이터에 대해서는 오동작을 하는 경우가 보고되고 있다. 그 외에도 학습데이터 오염시키기, 학습된 모델 탈취 등 새로운 공격 유형이 보고되고 있다. 기계학습에 사용된 훈련데이터에 대한 보안과 프라이버시 또한 중요한 이슈이다. 인공지능 기술의 개발 및 적용에 있어 이러한 위험성에 대한 고려와 대비가 반드시 필요하다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.12A
• /
• pp.1181-1187
• /
• 2010

This paper proposes a mobile AI (Artificial Intelligence) conducting decision-making in the game through education for intelligent character on the basis of Neural Network. Neural Network is learned through the input/output value of the algorithm which defines the game rule and the problem solving method. The learned character is able to perceive the circumstances and make proper action. In this paper, the mobile AI using Neural Network has been step-by-step designed, and a simple game has been materialized for its functional experiment. In this game, the goal, the character, and obstacles exist on regular 2D space, and the character, evading obstacles, has to move where the goal is. The mobile AI can achieve its goals in changing environment by learning the solution to several problems through the algorithm defined in each experiment. The defined algorithm and Neural Network are designed to make the input/output system the same. As the experimental results, the suggested mobile AI showed that it could perceive the circumstances to conduct action and to complete its mission. If mobile AI learns the defined algorithm even in the game of complex structure, its Neural Network will be able to show proper results even in the changing environment.