• Journal of The Korean Association of Information Education
• /
• v.25 no.2
• /
• pp.423-436
• /
• 2021

In the future, artificial intelligence (AI) technology is expected to become a general-purpose technology (GPT), and it is predicted that AI competency will become an essential competency. Several nations around the world are fostering experts in the field of AI to achieve technological proficiency while working to develop the necessary infrastructure and educational environment. In this study, we investigated the status of software education at the liberal arts level at 31 universities in Seoul, along with precedents from domestic and foreign AI education research. Based on this, we concluded that an AI literacy education model is needed to link software education at the liberal arts level with professional AI education. And we classified 20 AI-related lectures released in the KOCW according to the AI literacy competencies required; based on the results of this classification, we propose a model for AI literacy education in the liberal arts for undergraduate students. The proposed AI literacy education model may be considered as AI·SW convergence to experience AI along with literacy in the humanities, deviating from the existing theoretical and computer-science-based approach. We expect that our proposed AI literacy education model can contribute to the proliferation of AI.

• Journal of the Korea Convergence Society
• /
• v.12 no.12
• /
• pp.83-91
• /
• 2021

For agricultural products, supply is irregular due to changes in meteorological conditions, and it has high price elasticity. For example, if the supply decreases by 10%, the price increases by 50%. Due to these fluctuations in the prices of agricultural products, the Korean government guarantees the safety of prices to producers through small merchants' auctions. However, when prices plummet due to overproduction, protection measures for producers are insufficient. Therefore, in this paper, we designed a business model that can be used in the electronic transaction system by predicting the price of agricultural products with an artificial intelligence algorithm. To this end, the trained model with the training pattern pairs and a predictive model was designed by applying ARIMA, SARIMA, RNN, and CNN. Finally, the agricultural product forecast price data was classified into short-term forecast and medium-term forecast and verified. As a result of verification, based on 2018 data, the actual price and predicted price showed an accuracy of 91.08%.

• Convergence Security Journal
• /
• v.21 no.4
• /
• pp.31-39
• /
• 2021

In the R&D of the Defense Weapon System, the evaluation of technical and operational aspects has been developed with the military's own test evaluation system, and organizations and procedures have been established and implemented. However, with the recent advancement of information and communication technology in the private sector, it is often necessary to test-apply it to the field by enhancing the operability and suitability of technologies required for defense before development is complete. This paper investigates and analyzes the process for conducing empirical tests on the latest AI vaccine system R&D prototype organized by the Ministry of Science and ICT which proposes an improved demonstration plan for the existing military information system test evaluation procedure. In addition, under the specificity and security of the defense environment, we would like to present a practical demonstration plan and the improvement of the process for demonstrating the security technology prototype.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.127-130
• /
• 2024

본 연구는 기존 포털형 정보 서비스의 한계를 극복하고자, 이전 연구에서 제안된 연구자의 R&D 프로세스 과정에서의 협업을 지원하는 개방형 협업 지원 서비스 플랫폼을 기반으로 하여, 본 연구에서는 R&D 프로세스 중 '사전 단계'에 대한 설계와 구현을 소개한다. 우리는 R&D 프로세스를 문헌 리뷰와 연구 가설 설정 등을 수행하는 '사전 단계,' 실험과 데이터 분석 등을 수행하는 '실행 단계', 논문 작성 및 출판 등을 수행하는 '성과화 단계'로 구분하고, 이 중 '사전 단계'에 대해 프로젝트 뷰, 그룹 뷰, 문헌 뷰, 관계 뷰를 설계하고 구현하였다. 연구자는 이 플랫폼을 통해 문헌 내용 및 문헌 간 복잡한 연관성을 신속하게 파악할 수 있으며, 플랫폼은 연구자에 의해 자연스럽게 생성되는 사용자 정의 관계를 통해 향후 심층적인 문헌 네트워크 구축 및 분석이 가능해질 것으로 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.629-632
• /
• 2020

현대사회는 4차 산업혁명 시대가 도래하면서 초연결, 초지능, 초융합 사회로 변화되고 있다. 최근 교육부는 많은 변화가 요구되고 있는 교육분야, 교육정책 방안으로 SW(소프트웨어)교육에 AI(인공지능) 교육까지 추가되야 한다고 제안하고 2024년까지 첨단 기술을 활용한 지능형 과학실을 구축한다고 밝혔다. 이에 본 논문에서는 정부의 교육정책 방안이 원활하게 진행될 수 있고 융합 교육 분야에서 활용될 수 있는 "미래 지능형 과학실 활용을 위한 화학원소기호 이미지 기계학습 AI·SW교육 프로그램"을 제안하고자 한다.

• Journal of information and communication convergence engineering
• /
• v.21 no.4
• /
• pp.329-336
• /
• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• Journal of Korean Physical Therapy Science
• /
• v.31 no.3
• /
• pp.1-14
• /
• 2024

Purpose: This study aims to make it easier for anyone to write an autobiography by utilizing AI technology, allowing individuals to reflect on their lives and reaffirm their identity, ultimately enhancing their self-esteem. Through this research, the necessity of promoting mental health for the elderly is emphasized, and it seeks to provide foundational data contributing to new approaches for improving quality of life. Methods: Basic data for program development were collected in April 2024. Subsequently, the AI beta version was used to identify issues, which were then addressed and improved upon. Results: The results of this study are as follows: First, it was confirmed that structuring the autobiography writing program and providing clear guidelines are essential. Second, the importance of the role of conversation companions and the need for their prior training were emphasized. Third, ensuring the accessibility and ease of participation in the program was shown to enhance participant engagement. Fourth, further empirical research is necessary to verify the effectiveness of the program. Conclusion: This study confirmed that an autobiography writing model utilizing an AI-based platform can contribute to improving older adults' mental health. Older adults who struggle to use digital devices can become more comfortable with them through this program. Additionally, autobiographical writing activities that involve reflecting on their lives and narrating their stories according to various themes provide older adults with the opportunity to achieve a sense of self-integration. Finally, if this program is disseminated in a manner that suits the characteristics of older adults, it can play a significant role in improving their mental health.

• Journal of Sensor Science and Technology
• /
• v.30 no.6
• /
• pp.415-419
• /
• 2021

We developed a highly accurate, yet inexpensive, refractive index (RI)-based soil moisture sensor. To detect the RI, a light guide was set with a light-emitting diode and photodiode. When the air fills the space between the soil particles, most of the incident light is reflected at the interface between the waveguide and the air because of the large RI difference. As the moisture of the soil increases, the macroscopic soil RI increases. This allows incident light to pass through the interface. The intensity of the light reaching the photodiode was simulated according to the change in the soil RI. Using the simulation results, we designed and manufactured a curved glass waveguide. We evaluated the performance of the RI-based soil sensor by comparing it with a commercially available, high-cost and high-performance time-domain reflectometer (TDR). Our sensor was 96% accurate, surpassing the costly TDR sensor.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.912-913
• /
• 2023

이미지 처리에 관한 인공지능 모델의 발전에 따라 개인정보 유출 문제가 가속화되고 있다. 인공지능은 다방면으로 삶에 편리함을 제공하지만, 딥러닝 기술은 적대적 예제에 취약성을 보이기 때문에, 개인은 보안에 취약한 대상이 된다. 본 연구는 ResNet18 신경망 모델에 얼굴이미지를 학습시킨 후, Shadow Attack을 사용하여 입력 이미지에 대한 AI 분류 정확도를 의도적으로 저하시켜, 허가받지 않은 이미지의 인식율을 낮출 수 있도록 구현하였으며 그 성능을 실험을 통해 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.904-905
• /
• 2023

본 논문에서는 의료 영상 생성을 위한 Med-StyleGAN2를 제안한다. 생성적 적대 신경망은 이미지 생성에는 효과적이지만, 의료 영상 생성에는 한계점을 가지고 있다. 따라서 본 연구에서는 의료 영상 생성에 특화된 StyleGAN 기반 학습 모델을 제안한다. 이는 다양한 의료 영상 어플리케이션에 활용할 수 있으며, 생성된 의료 영상에 대한 정량적, 정성적 평가를 수행함으로써 의료 영상 생성 분야의 발전 가능성에 대해 연구한다.