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Yun-Sik Kim, Myung-Il Roh, Ha-Yun Kim, In-Chang Yeo, Nam-Sun Son, "An Improved Method for Detection and Tracking of Maritime Obstacles Using Multiple-Sensor Fusion", Proceedings of OMAE 2026, Tokyo, Japan, 2026.06.07-12
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Ha-Yun Kim, Myung-Il Roh, Do-Hyeok Ahn, Min-Chul Kong, In-Chang Yeo, and Seong-Won Choi, "A Method for Ship Modeling in a Virtual Environment for SILS-Based Collision Avoidance Simulation", Proceedings of 11th PAAMES 2025, Singapore, 2025.12.10-12
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In-Chang Yeo, Myung-Il Roh, , Jin-Hyeok Kim, In-Su Han, Dong-Woo Kim,"A Method for Optimizing Pump Tower Design in LNG Tanks Considering Structural Safety", PRADS 2025, Ann Arbor, United States, 2025.10.19-23
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In-Su Han, Myung-Il Roh, Min-Chul Kong, "A Generative AI-based Q&A System for Design Regulations", Proceedings of International Symposium on PRADS 2025, Ann Arbor, United States, 2025.10.19-23
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Do-Hyeok Ahn, Myung-Il Roh, In-Chang Yeo, Hye-Won Lee, Seung-Ho Ham, "A Control Method Based on Safe Reinforcement Learning for Cranes in Shipyards", Proceedings of OMAE 2026, Tokyo, Japan, 2026.07.07-12
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Dong-Woo Kim, Myung-Il Roh, Minkyu Park, ..., "A METHOD FOR IMPROVING SLOSHING ASSESSMENT IN MEMBRANE-TYPE CARGO TANKS CONSIDERING STRUCUTRAL NONLINEARITY", Proceedings of OMAE2025, Vancouver, Canada, 2025.06.22-27
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Min-Chul Kong, Myung-Il Roh, In-Su Han, Seong-Won Choi, Mijin Kim, Jeoungyoun Kim, Inseok Lee, "A Method for Ship Piping Design Using Past Data and Expert Knowledge", Proceedings of OMAE 2025, Vancouver, Canada, 2025.06.22-27
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Seong-Won Choi, Myung-Il Roh, In-Chang Yeo, "A Method for Collision Avoidance of an Autonomous Ship in Dynamic Environments", Proceedings of ISOPE 2025, Goyang, Korea, 2025.06.01-06
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Yun-Sik Kim, Myung-Il Roh, Ha-Yun Kim, In-Chang Yeo, Nam-Sun Son, "A Method for Robust Tracking and Fusion of Maritime Obstacles Using Multiple Sensor Data", Proceedings of ISOPE 2025, Goyang, Korea, 2025.06.01-06
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Do-Hyeok Ahn, Myung-Il Roh, In-Chang Yeo, Do-Hyun Chun, "A Method for Automatic Control of the Block Lifting by an Offshore Floating Crane Based on Deep Reinforcement Learning", Proceedings of ISOPE 2025, Goyang, Korea, 2025.06.01-06
