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Duck Young Kim
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2020 – today
- 2024
- [c6]Harry Lim, Hyoung Seok Kang, Duck Young Kim:
Information Modeling for Data-Driven Digital Twin Simulation: Insights from Case Studies of Port Logistics and Urban Traffic Systems. APMS (4) 2024: 307-322 - 2023
- [c5]Harry Lim, Minseop Go, Taekyu Lim, Duck Young Kim:
Adaptive Traffic Signal Control for a Mixed Autonomous and Traditional Vehicles by Agent-Based Digital Twin Simulation. APMS (3) 2023: 603-618 - 2022
- [j12]J. W. Park, K. H. Min, Duck Young Kim:
Auto-calibration of robot workcells via remote laser scanning. Robotics Comput. Integr. Manuf. 78: 102394 (2022) - [j11]Jin Woo Park, Jongil Park, Hansol Kim, Namhun Kim, Duck Young Kim:
Assembly Part Positioning on Transformable Pin Array Fixture by Active Pin Maximization and Joining Point Alignment. IEEE Trans Autom. Sci. Eng. 19(2): 1047-1057 (2022) - [e2]Duck Young Kim, Gregor von Cieminski, David Romero:
Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action - IFIP WG 5.7 International Conference, APMS 2022, Gyeongju, South Korea, September 25-29, 2022, Proceedings, Part I. IFIP Advances in Information and Communication Technology 663, Springer 2022, ISBN 978-3-031-16406-4 [contents] - [e1]Duck Young Kim, Gregor von Cieminski, David Romero:
Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action - IFIP WG 5.7 International Conference, APMS 2022, Gyeongju, South Korea, September 25-29, 2022, Proceedings, Part II. IFIP Advances in Information and Communication Technology 664, Springer 2022, ISBN 978-3-031-16410-1 [contents] - 2021
- [j10]Woonsang Baek, Duck Young Kim:
In-Process Noise Inspection System for Product Fault Detection in a Loud Shop-Floor Environment. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [c4]Jeongha Shin, Duck Young Kim:
Software Architecture for an Active Device Driver in Reconfigurable Manufacturing Systems. APMS (1) 2021: 596-603 - 2020
- [j9]Duck Young Kim, Jin Woo Park, Sujeong Baek, K.-B. Park, H.-R. Kim, J.-I. Park, H.-S. Kim, B.-B. Kim, H.-Y. Oh, Kichang Namgung, Woonsang Baek:
A modular factory testbed for the rapid reconfiguration of manufacturing systems. J. Intell. Manuf. 31(3): 661-680 (2020) - [j8]Woonsang Baek, Duck Young Kim:
An in-Process Inspection System to Detect Noise Originating from within the Interior Trim Panels of Car Doors. Sensors 20(3): 630 (2020) - [j7]Kichang Namgung, Hyunsik Yoon, Sujeong Baek, Duck Young Kim:
Estimating System State through Similarity Analysis of Signal Patterns. Sensors 20(23): 6839 (2020)
2010 – 2019
- 2019
- [j6]Sujeong Baek, Duck Young Kim:
Abrupt variance and discernibility analyses of multi-sensor signals for fault pattern extraction. Comput. Ind. Eng. 128: 999-1007 (2019) - [j5]Sujeong Baek, Duck Young Kim:
Fault Prediction via Symptom Pattern Extraction Using the Discretized State Vectors of Multisensor Signals. IEEE Trans. Ind. Informatics 15(2): 922-931 (2019) - [j4]Jin Woo Park, Moonsoo Shin, Duck Young Kim:
An Extended Agent Communication Framework for Rapid Reconfiguration of Distributed Manufacturing Systems. IEEE Trans. Ind. Informatics 15(7): 3845-3855 (2019) - [c3]Woonsang Baek, Duck Young Kim:
In-Process Noise Detection System for Product Inspection by Using Acoustic Data. APMS (2) 2019: 413-420 - 2018
- [j3]Woonsang Baek, Sujeong Baek, Duck Young Kim:
Characterization of System Status Signals for Multivariate Time Series Discretization Based on Frequency and Amplitude Variation. Sensors 18(1): 154 (2018) - [j2]Jin Woo Park, Duck Young Kim:
Standard Time Estimation of Manual Tasks via Similarity Measure of Unequal Scale Time Series. IEEE Trans. Hum. Mach. Syst. 48(3): 241-251 (2018) - [c2]Woonsang Baek, Duck Young Kim:
An In-Process BSR-Noise Detection System for Car Door Trims. APMS (2) 2018: 35-38 - [c1]Minseok Kim, Kyeong-Beom Park, Sung Ho Choi, Jae Yeol Lee, Duck Young Kim:
AR/VR-Based Live Manual for User-Centric Smart Factory Services. APMS (2) 2018: 417-421 - 2017
- [j1]Sujeong Baek, Duck Young Kim:
Empirical Sensitivity Analysis of Discretization Parameters for Fault Pattern Extraction From Multivariate Time Series Data. IEEE Trans. Cybern. 47(5): 1198-1209 (2017)
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last updated on 2024-10-16 21:25 CEST by the dblp team
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