Deep Bayesian survival analysis of rail useful lifetime

Reliable estimation of rail useful lifetime can provide valuable information for predictive maintenance in railway systems. However, in most cases, lifetime data is incomplete because not all pieces of rail experience failure by the end of the study horizon, a problem known as censoring. Ignoring or otherwise mistreating the censored cases...

Rail break prediction and cause analysis using imbalanced in-service train data

Timely detection and identification of rail breaks are crucial for safety and reliability of railway networks. This paper proposes a new deep learning-based approach using the daily monitoring data from in-service trains. A time-series generative adversarial network (TimeGAN) is employed to mitigate the problem of data imbalance and preserve the...

Photoluminescence from Radiative Surface States and Excitons in Methylammonium Lead Bromide Perovskites

In view of its band gap of 2.2 eV and its stability, methylammonium lead bromide (MAPbBr₃) is a possible candidate to serve as a light absorber in a subcell of a multijunction solar cell. Using complementary temperature-dependent time-resolved microwave conductance (TRMC) and photoluminescence (TRPL) measurements, we demonstrate...