• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.15-26
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• 2023

The purpose of this study is to determine the artificial intelligence-based degradation index from the image of the cross-section of the microstructure taken with a scanning electron microscope of the specimen obtained by the creep test of DA-5161 SX, a nickel-based superalloy used as a material for high-temperature parts. It proposes a new method of quantification and proposes a model that predicts degradation based on Bayesian inference without destroying components of high-temperature parts of operating equipment and a creep life prediction model that predicts Larson-Miller Parameter (LMP). It is proposed that the new degradation indexing method that infers a consistent representative value from a small amount of images based on the geometrical characteristics of the gamma prime phase, a nickel-base superalloy microstructure, and the prediction method of degradation index and LMP with information on the environmental conditions of the material without destroying high-temperature parts.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.127-133
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• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.513-520
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• 2021

Recently, research on edutech, which combines education and technology in the e-learning field called learning, education and training, has been actively conducted, but it is still insufficient to collect and utilize data tailored to individual learners based on learning activity data that can be automatically collected from digital devices. Therefore, this study attempts to detect questions in textbooks or problem papers using artificial intelligence computer vision technology that plays the same role as human eyes. The textbook or questionnaire item detection model proposed in this study can help collect, store, and analyze offline learning activity data in connection with intelligent education services without digital conversion of textbooks or questionnaires to help learners provide personalized learning services even in offline learning.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.19-19
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• 2023

최근 기후변화에 의해 단기간에 많은 양의 집중호우가 발생하여 도시지역의 침수 피해가 증가하고 있다. 이에 도시지역의 홍수 피해 해결을 위해 도심지 홍수 발생 시 홍수정도 및 상황을 파악할 수 있는 장비가 개발되었으나, 실용화 단계까지는 진행이 미흡한 상황이다. 또한 기존 도시지역 홍수 현상 및 원인을 분석하기 위해 수치모형을 활용하고 있으나, 우수관망의 노후화 및 초기 강우패턴 적용에 대한 정확한 해석결과의 어려워 활용성이 낮다. 또한 홍수정도와 발생상황 인지를 위한 계측 장비의 개발 연구는 지속적으로 진행되고 있으나, 계측 장비의 높은 가격으로 전국적으로 설치 할 수 없는 상황으로 이를 대응하기 위한 별도의 방안 마련이 필요한 실정이다. 이를 위해 본 과제에서는 고성능·저비용 계측센서를 개발하여 실용화 가능성을 높이고, 전국에 산재되어있는 CCTV(교통상황, 방법용 등)의 영상을 활용한 침수상황 인지 기술 개발, 계측 데이터와 모니터링 데이터의 활용을 위한 빅데이터 개방 플랫폼을 구축하여, 상습 침수지역에 대해 실시간 감시가 가능한 계측 시스템의 정형 데이터와 CCTV 및 영상 등 모니터링 장비의 비정형 데이터의 분석 기술을 결합한 새로운 도심지 홍수 감시 기술의 개발을 목표로 한다. 이를 위해 본 연구 1차년도에 지표면 침수심 계측센서와 우수관망 월류심 계측센서를 개발하였으며, 2차년도에는개발된 계측센서의 현장실증을 통해 데이터를 수집한다. 수집된 계측센서 데이터와 비정형(CCTV 영상) 데이터의 AI학습을 통해 분석된 침수심, 침수범위, 침수면적 데이터는 도심지 홍수 정보 프로그램을 통해 표출되며, 최종적으로는 현장 상황을 쉽게 파악 가능한 3D 레이어의 형식으로 표출하고자 한다. 추후 도심지 홍수 정보 프로그램을 통해 표출되는 3D 레이어는 환경부가 추진하는 DT(Digital Twin) 연계 인공지능(AI) 홍수예보 사업과의 연계 시 도심지 홍수 지도 구축을 위한 자료로 활용될 수 있을 것으로 판단된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.641-648
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• 2023

Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.61-85
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• 2023

Objective: This study aims to investigate whether science teaching attitude of early childhood teachers mediates the relationship between the professional learning environment of institutions and their intention to accept artificial intelligence (AI) technology, and whether the experience of using smart and digital devices moderates the effect of science teaching attitude. Methods: An online survey was conducted targeting 118 teachers with more than 1 year of experience in kindergarten and day care center settings. Descriptive statistical analysis, correlation analysis, and The Process macro model 4, 14 were performed using SPSS 27.0 and The Process macro 3.5. Results: First, the science teaching attitude of early childhood teachers served as a mediator between the professional learning environment of institutions and teachers' intention to accept AI technology. Second, the experience of using smart and digital devices was found to moderate the effect of teachers' science teaching attitude on their intention to accept AI technology. Conclusion/Implications: This results showed that an institutional environment that supports teachers' professionalism development and provides rich experience is crucial for promoting teachers' active acceptance of AI technology. The findings highlight the importance of creating a supportive institutional envionment for teacher's professional growth, enhancing science teaching attitudes, and facilitating the use of various devices.

• Korea Trade Review
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• v.42 no.3
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• pp.1-24
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• 2017

This study investigates any possible influences of the fourth industrial revolution on international trade in Korea and suggests strategies to promote export of Korea in order to secure one of the biggest international trade countries. The fourth industrial revolution is the fourth major industrial era since the third industrial revolution in the 18th century which used electronics and information technology to automate production. This can be characterized as a range of emerging technologies that are fusing the physical, digital and biological worlds, and impacting all disciplines, economies and industries. Since this revolution is expected to have effects on international trade as well as whole industrial society, it examines how it may affect international trade of Korea in terms of the subject, the object, markets and forms of international trade. After that, it provides the strategies to promote Korean export in order to overcome the risks around the low economic growth of the recent years and the depressed domestic economy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.110-110
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• 2022

본 연구는 자율운항 선박의 원격 고장 진단 기법 개발의 일부로 수행되었다. 특히, 엔진 연료 계통 장비로부터 계측된 시계열 데이터로부터 상태 진단을 위한 알고리즘 구현 결과를 제시하였다. 엔진 연료 펌프와 청정기를 가진 육상 실험 장비로부터 진동 시계열 데이터 계측하였으며, 이상 감지, 고장 분류 및 고장 예측이 가능한 심층 학습(Deep Learning) 및 기계 학습(Machine Learning) 알고리즘을 구현하였다. 육상 실험 장비에 고장 유형 별로 인위적인 고장을 발생시켜 특징적인 진동 신호를 계측하여, 인공 지능 학습에 이용하였다. 계측된 신호 데이터는 선행 발생한 사건의 신호가 후행 사건에 영향을 미치는 특성을 가지고 있으므로, 시계열에 내포된 고장 상태는 시간 간의 선후 종속성을 반영할 수 있는 학습 알고리즘을 제시하였다. 고장 사건의 시간 종속성을 반영할 수 있도록 순환(Recurrent) 계열의 RNN(Recurrent Neural Networks), LSTM(Long Short-Term Memory models)의 모델과 합성곱 연산 (Convolution Neural Network)을 기반으로 하는 Conv1D 모델을 적용하여 예측 정확성을 비교하였다. 특히, 합성곱 계열의 RNN LSTM 모델이 고차원의 순차적 자연어 언어 처리에 장점을 보이는 모델임을 착안하여, 신호의 시간 종속성을 학습에 반영할 수 있는 합성곱 계열의 Conv1 알고리즘을 고장 예측에 사용하였다. 또한 기계 학습 모델의 효율성을 감안하여 XGBoost를 추가로 적용하여 고장 예측을 시도하였다. 최종적으로 연료 펌프와 청정기의 진동 신호로부터 Conv1D 모델과 XGBoost 모델의 고장 예측 성능 결과를 비교하였다

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.543-548
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• 2023

This study emphasizes the need to understand digital transformation and addresses the development process of functional mobile games with the theme of digital transformation. Through previous research, we found that existing mobile games do not reflect the changes in industries and jobs in the future. In this study, we designed and developed an educational mobile game that can help young people develop digital literacy skills and understand core skills for future changes in industrial structure and jobs due to digital transformation. It utilizes Unity 3D and combines the best features of puzzle, card, and board games. While there may be limitations in terms of expertise in developing educational content, it is important to note that we have presented content that can provide a futuristic view of careers through a game that is highly preferred by students. Considering the direct and indirect educational effects of the game, it is expected to be useful as a vocational education content in the classroom through tablet devices that have recently been distributed in schools.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.