• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.391-400
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• 2020

While artificial intelligence (AI) is attracting attention as a core technology in the era of the 4th industrial revolution, needs for artificial intelligence education to cultivate AI literacy is emerging. In this regard, we developed and applied a project-based AI education program for elementary and middle school students, and analyzed its effects. Participants were assigned into teams with three members, and each team engaged in a project-based AI education program for two nights and three days. In the project, they selected an real-world problem they wanted and devised an AI-enabled artifact to solve it. The effectiveness of the program was investigated with the changes in attitude and efficacy of learners toward artificial intelligence. The results showed that the AI project learning positively changed both attitudes and efficacy toward artificial intelligence at a statistically significant level. This change was more pronounced as the level of perceived programming skills increased, and the level of interest in the project learning increased.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.489-499
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• 2021

This paper proposes an arts and culture content creation tool powered by artificial intelligence. With the recent advances in technologies including artificial intelligence, there are active research activities on creating art and culture contents. However, it is still difficult and cumbersome for those who are not familiar with programming and artificial intelligence. In order to deal with the content creation with new technologies, we analyze related creation tools, services and technologies that process with raw visual and audio data, generate new media contents and visualize intermediate results. We then extract key requirements for a future creation tool for creators who are not familiar with programming and artificial intelligence. We finally introduce an intuitive and integrated content creation tool for end-users. We hope that this tool will allow creators to intuitively and creatively generate new media arts and culture contents based on not only understanding given data but also adopting new technologies.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.45-53
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• 2022

The need for artificial intelligence education has emerged, and countries around the world are announcing artificial intelligence strategies. Artificial intelligence education is reflected in the main points of the 2022 revised curriculum general published in Korea. Along with this interest, programs related to artificial intelligence education are being developed, but it is difficult to find artificial intelligence programs for lower grades of elementary school. This study aims to develop a data collection education program for the lower grades of elementary school through a series of analysis-design-development-application-evaluation processes and apply it to first-grade elementary school students to verify its effectiveness. Through the developed program, it is expected that students will be able to understand and feel interested in artificial intelligence, and develop an attitude of collecting data in their daily lives through the process of searching for various types of data in their daily lives.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.117-123
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• 2023

While applying new digital technologies, interest in software and artificial intelligence is quite high. In particular, many changes are being made for the development of software and artificial intelligence in the field of education. From 2025, software and artificial intelligence-related curricula will be applied to public education in elementary, middle and high schools. The Ministry of Education is also conducting various camps to experience software and artificial intelligence in various ways in elementary, middle and high schools before they are applied to public education. Several platforms for experience camps related to software and artificial intelligence are also being used. In this study, we intend to increase the educational efficiency of the learning method for software and artificial intelligence to be developed in the future by designing a model for software and artificial intelligence experiential learning platforms.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.141-147
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• 2022

In a broad sense, the definition of digital health care is an industrial area that manages personal health and diseases through the convergence of the health care industry and ICT. In a narrow sense, various medical technologies are used to manage medical services to improve patient health. This paper aims to provide design guidelines so that artificial intelligence technology can be applied stably and efficiently to more diverse digital health care fields in the future by introducing use cases of artificial intelligence and machine learning techniques applied in the digital health care field. For this purpose, in this thesis, the medical field and the daily life field are divided and examined. The two regions have different data characteristics. By further subdividing the two areas, we looked at the use cases of artificial intelligence algorithms according to data characteristics and problem definitions and characteristics. Through this, we will increase our understanding of artificial intelligence technologies used in the digital health care field and examine the possibility of using various artificial intelligence technologies.

• ETRI Journal
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• v.41 no.6
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• pp.760-770
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• 2019

Based on the growing demand for neural network technologies, various neural network inference engines are being developed. However, each inference engine has its own neural network storage format. There is a growing demand for standardization to solve this problem. This study presents interworking techniques for ensuring the compatibility of neural networks and data among the various deep learning frameworks. The proposed technique standardizes the graphic expression grammar and learning data storage format using the Neural Network Exchange Format (NNEF) of Khronos. The proposed converter includes a lexical, syntax, and parser. This NNEF parser converts neural network information into a parsing tree and quantizes data. To validate the proposed system, we verified that MNIST is immediately executed by importing AlexNet's neural network and learned data. Therefore, this study contributes an efficient design technique for a converter that can execute a neural network and learned data in various frameworks regardless of the storage format of each framework.

• Journal of Distribution Science
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• v.22 no.6
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• pp.83-93
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• 2024

Purpose: The present study is developed with the aim of mapping the trends in scientific production related to the implementation of artificial intelligence systems for agro-food supply chains. Research design, data and methodology: The methodological approach of the research shows a descriptive documentary process based on bibliometric techniques for mapping the main indicators of the area of knowledge through the establishment of a search equation in Scopus. Results: The research results show a total of 633 documents published between 2019 and 2023, with a great annual growth rate of 61.68%; In addition to a notable participation of countries such as India, China, the United Kingdom and the United States in the generation of new knowledge related to artificial intelligence applied to food distribution systems. Conclusions: It is concluded that the rise of new artificial intelligence technologies has shown extremely important results in the development of industries worldwide, with increasingly accelerated steps; which certainly translates into the creation of spaces and incentives in the production of research aimed at understanding these dynamics and in turn to propose new alternatives and proposals for the reduction of the large technological gaps that are present within the agro-food sector.

• Land and Housing Review
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• v.11 no.4
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• pp.99-104
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• 2020

This paper presents the recent research developments identified through a review of literature on the application of artificial intelligence in developing automated designs of fire protection facilities. The literature review covered research related to image recognition and applicable neural networks. Firstly, it was found that convolutional neural network (CNN) may be applied to the development of automating the design of fire protection facilities. It requires a high level of object detection accuracy necessitating the classification of each object making up the image. Secondly, to ensure accurate object detection and building information, the data need to be pulled from architectural drawings. Thirdly, by applying image recognition and classification, this can be done by extracting wall and surface information using dimension lines and pixels. All combined, the current review of literature strongly indicates that it is possible to develop automated designs for fire protection utilizing artificial intelligence.

• Electronics and Telecommunications Trends
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• v.38 no.3
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• pp.38-46
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• 2023

The value of living a long and healthy life without suffering has increased owing to aging populations, transition to welfare societies, and global interest in health deriving from the novel coronavirus disease pandemic. New drug development has gained attention as both a tool to improve the quality of life and high-value market, with blockbuster drugs potentially generating over 10 billion dollars in annual revenue. However, for newly discovered substances to be used as drugs, various properties must be verified over a long period in a time-consuming and costly process. Recently, the development of artificial intelligence technologies, such as deep and reinforcement learning, has led to significant changes in drug development by enabling the effective identification of drug candidates that satisfy desired properties. We explore and discuss trends in artificial intelligence for de novo drug design.