• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.212-213
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• 2023

항·포구내에서 주.야간에 걸쳐 미등록 선박을 검출하기 위해, 가시광 및 IR, 라이다 센서를 통해 선박 영상 및 거리정보를 획득하고, 딥러닝 기술을 적용하여 선박의 외관에 대한 특징 분석 및 선박에 표기된 문자열의 인식, 선박의 크기 측정을 통해 선박을 분류하고 특정하는 기술 개발

• Journal of the Speleological Society of Korea
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• no.44
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• pp.27-36
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• 1995

외국의 자연학습원은 크게 나누어 구미 각국의 "자연교육센타" 개념과 일본의 "청소년자연의 집"의 개념으로 대별할 수 있다. 서구의 자연교육센터는 통상 원시림이나 교육적 가치가 큰 특수한 식생이 존재하는 지역에 관람객을 위한 써비스적 기능을 담당하는 건물(Nature Center)을 짓고 건물내에 그 지역의 자연자원을 설명하는 사진, 도표, 표본 및 팜플렛 등을 비치하여 전문안내원으로 하여금 구체적인 설명과 질문에 답하도록 하고 있다.(중략)

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.6
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• pp.258-263
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• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.160-161
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• 2023

Currently, the ship's passage planning relies on the navigator officer's knowledge and empirical methods. However, as ship autonomous navigation technology has recently developed, automation technology for passage planning has been studied in various ways. In this study, we intend to generate an optimal route for a ship based on Q-learning, one of the reinforcement learning techniques. Reinforcement learning is applied in a way that trains experiences for various situations and makes optimal decisions based on them.

• Digital Contents
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• no.10 s.5
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• pp.38-46
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• 1993

• Journal of Information Management
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• v.16 no.4
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• pp.32-42
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• 1983

• 대학교육
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• s.125
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• pp.100-103
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• 2003

• Journal of the Korean Institute of Educational Facilities
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• v.23 no.5
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• pp.21-25
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• 2016

• Ingenium
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• v.26 no.1
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• pp.21-23
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• 2019

• Ingenium
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• v.28 no.3
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• pp.22-27
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• 2021