Xiaoyang Li
Xiaoyang Li
Southern University of Science and Technology
Verified email at mail.sustech.edu.cn
Cited by
Cited by
Measuring reliability under epistemic uncertainty: Review on non-probabilistic reliability metrics
R Kang, Q Zhang, Z Zeng, E Zio, X Li
Chinese Journal of Aeronautics 29 (3), 571-579, 2016
Optimal design for step-stress accelerated degradation testing with competing failure modes
X Li, T Jiang
2009 Annual Reliability and Maintainability Symposium, 64-68, 2009
Wirelessly powered data aggregation for IoT via over-the-air function computation: Beamforming and power control
X Li, G Zhu, Y Gong, K Huang
IEEE Transactions on Wireless Communications 18 (7), 3437-3452, 2019
Agrobacterium delivers VirE2 protein into host cells via clathrin-mediated endocytosis
X Li, SQ Pan
Science advances 3 (3), e1601528, 2017
Direct visualization of Agrobacterium‐delivered VirE2 in recipient cells
X Li, Q Yang, H Tu, Z Lim, SQ Pan
The Plant Journal 77 (3), 487-495, 2014
Stochastic modeling and analysis of multiple nonlinear accelerated degradation processes through information fusion
F Sun, L Liu, X Li, H Liao
Sensors 16 (8), 1242, 2016
Model uncertainty in accelerated degradation testing analysis
L Liu, XY Li, E Zio, R Kang, TM Jiang
IEEE Transactions on Reliability 66 (3), 603-615, 2017
Modeling accelerated degradation data based on the uncertain process
XY Li, JP Wu, L Liu, ML Wen, R Kang
IEEE Transactions on Fuzzy Systems 27 (8), 1532-1542, 2018
Review of multiple-stress models in accelerated life testing [J]
Systems engineering and electronics 29 (5), 828-831, 2007
A general accelerated degradation model based on the Wiener process
L Liu, X Li, F Sun, N Wang
Materials 9 (12), 981, 2016
A Bayesian optimal design for accelerated degradation testing based on the inverse Gaussian process
X Li, Y Hu, E Zio, R Kang
IEEE Access 5, 5690-5701, 2017
A random fuzzy accelerated degradation model and statistical analysis
XY Li, JP Wu, HG Ma, X Li, R Kang
IEEE Transactions on Fuzzy Systems 26 (3), 1638-1650, 2017
Planning of step-stress accelerated degradation test with stress optimization
ZZ Ge, XY Li, JR Zhang, TM Jiang
Advanced Materials Research 118, 404-408, 2010
Life prediction of jet engines based on LSTM-recurrent neural networks
D Dong, XY Li, FQ Sun
2017 Prognostics and system health management conference (PHM-Harbin), 1-6, 2017
Agrobacterium-delivered virulence protein VirE2 is trafficked inside host cells via a myosin XI-K–powered ER/actin network
Q Yang, X Li, H Tu, SQ Pan
Proceedings of the National Academy of Sciences 114 (11), 2982-2987, 2017
Optimal design for step-stress accelerated degradation testing based on D-optimality
Z Ge, X Li, T Jiang, T Huang
2011 Proceedings-Annual Reliability and Maintainability Symposium, 1-6, 2011
Wirelessly powered crowd sensing: Joint power transfer, sensing, compression, and transmission
X Li, C You, S Andreev, Y Gong, K Huang
IEEE Journal on Selected Areas in Communications 37 (2), 391-406, 2018
Bayesian step stress accelerated degradation testing design: A multi-objective Pareto-optimal approach
X Li, Y Hu, J Zhou, X Li, R Kang
Reliability Engineering & System Safety 171, 9-17, 2018
Differentiation of spiral ganglion-derived neural stem cells into functional synaptogenetic neurons
X Li, A Aleardi, J Wang, Y Zhou, R Andrade, Z Hu
Stem cells and development 25 (10), 803-813, 2016
A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component
F Sun, X Li, H Liao, X Zhang
Advances in mechanical engineering 9 (1), 1687814016685963, 2017
The system can't perform the operation now. Try again later.
Articles 1–20