Jongmyon Kim
Jongmyon Kim
울산대 IT융합학부 교수
Verified email at - Homepage
Cited by
Cited by
Reliable fault diagnosis for low-speed bearings using individually trained support vector machines with kernel discriminative feature analysis
M Kang, J Kim, JM Kim, ACC Tan, EY Kim, BK Choi
IEEE Transactions on Power Electronics 30 (5), 2786-2797, 2014
A hybrid prognostics technique for rolling element bearings using adaptive predictive models
W Ahmad, SA Khan, JM Kim
IEEE Transactions on Industrial Electronics 65 (2), 1577-1584, 2017
A hybrid feature model and deep-learning-based bearing fault diagnosis
M Sohaib, CH Kim, JM Kim
Sensors 17 (12), 2876, 2017
Time-varying and multiresolution envelope analysis and discriminative feature analysis for bearing fault diagnosis
M Kang, J Kim, LM Wills, JM Kim
IEEE Transactions on Industrial Electronics 62 (12), 7749-7761, 2015
Automated irrigation system using solar power
J Uddin, SMT Reza, Q Newaz, J Uddin, T Islam, JM Kim
2012 7th International Conference on Electrical and Computer Engineering …, 2012
Fire flame detection in video sequences using multi-stage pattern recognition techniques
TX Truong, JM Kim
Engineering Applications of Artificial Intelligence 25 (7), 1365-1372, 2012
An effective four-stage smoke-detection algorithm using video images for early fire-alarm systems
TX Tung, JM Kim
Fire Safety Journal 46 (5), 276-282, 2011
A hybrid feature selection scheme for reducing diagnostic performance deterioration caused by outliers in data-driven diagnostics
M Kang, MR Islam, J Kim, JM Kim, M Pecht
IEEE Transactions on Industrial Electronics 63 (5), 3299-3310, 2016
A reliable technique for remaining useful life estimation of rolling element bearings using dynamic regression models
W Ahmad, SA Khan, MMM Islam, JM Kim
Reliability Engineering & System Safety 184, 67-76, 2019
Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm
M Kang, J Kim, JM Kim
Information Sciences 294, 423-438, 2015
Overview of KSTAR initial operation
M Kwon, YK Oh, HL Yang, HK Na, YS Kim, JG Kwak, WC Kim, JY Kim, ...
Nuclear Fusion 51 (9), 094006, 2011
An FPGA-based multicore system for real-time bearing fault diagnosis using ultrasampling rate AE signals
M Kang, J Kim, JM Kim
IEEE Transactions on Industrial Electronics 62 (4), 2319-2329, 2014
Adaptive ECG denoising using genetic algorithm-based thresholding and ensemble empirical mode decomposition
P Nguyen, JM Kim
Information Sciences 373, 499-511, 2016
Singular value decomposition based feature extraction approaches for classifying faults of induction motors
M Kang, JM Kim
Mechanical Systems and Signal Processing 41 (1-2), 348-356, 2013
Robust condition monitoring of rolling element bearings using de-noising and envelope analysis with signal decomposition techniques
P Nguyen, M Kang, JM Kim, BH Ahn, JM Ha, BK Choi
Expert Systems with Applications 42 (22), 9024-9032, 2015
Reliable multiple combined fault diagnosis of bearings using heterogeneous feature models and multiclass support vector machines
MMM Islam, JM Kim
Reliability Engineering & System Safety 184, 55-66, 2019
An overview of KSTAR results
JG Kwak, YK Oh, HL Yang, KR Park, YS Kim, WC Kim, JY Kim, SG Lee, ...
Nuclear Fusion 53 (10), 104005, 2013
A hybrid technique for medical image segmentation
A Nyma, M Kang, YK Kwon, CH Kim, JM Kim
Journal of Biomedicine and Biotechnology 2012, 2012
High-performance and energy-efficient fault diagnosis using effective envelope analysis and denoising on a general-purpose graphics processing unit
M Kang, J Kim, JM Kim
IEEE Transactions on Power Electronics 30 (5), 2763-2776, 2014
An efficient scheduling scheme using estimated execution time for heterogeneous computing systems
HJ Choi, DO Son, SG Kang, JM Kim, HH Lee, CH Kim
The Journal of Supercomputing 65 (2), 886-902, 2013
The system can't perform the operation now. Try again later.
Articles 1–20