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Articles

Data-augmented machine learning approach for determination of over-excavation criteria in earth pressure balance shield tunnel boring machine operations

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By kibeom kwon, Jaehoon Jung, Hangseok Choi, Byeonghyun Hwang
| Nature Verified
Abstract Regulating the discharged muck volume is essential for preventing over-excavation in projects constructed by tunnel boring machines (TBMs). Over-excavation is typically identified when the over-excavation ratio (OER) exceeds a predefined criterion for over-excavation (COE). However, this criterion has traditionally been determined subjectively, and the site and operational conditions associated with anomalous over-excavation have not been systematically characterized.
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Data‐augmented machine learning for risk management of tunnel boring machine jamming considering coupled geological factors

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By Hangseok Choi, kibeom kwon, Yerim Yang, Yuri Yeom
| Wiley Online Library Verified
REFERENCES , , , & (2021). Evaluating deterioration of tunnels using computational machine learning algorithms. Journal of Construction Engineering and Management, 147(10), 04021125. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002162 , , , , , , & (2023). Enhancing small medical dataset classification performance using GAN. Informatics, 10(1), 28. https://doi.org/10.3390/informatics10010028 , & (1996). Face stability conditions with earth-pressure-balanced shields.
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Insights gained by attending vascular surgery conferences as a medical student: tips and lessons learned

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By kibeom kwon, Michelle Ikoma, Scott Landman, Nicholas Bellacicco
| KevinMD.com
Attending academic conferences as a medical student offers a wealth of opportunities. Whether it’s networking, finding potential mentors, deepening your knowledge of specialties, or simply exploring new cities, conferences provide unique experiences that can significantly shape your career.
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