Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …

Prognostics and health management (PHM) is critical for enhancing equipment reliability
and reducing maintenance costs, and research on intelligent PHM has made significant …

The field of machine learning is comprised of techniques, which have proven powerful
approaches to knowledge discovery and construction of 'digital twins' in the highly …

Simple Summary Transfer learning plays a major role in medical image analyses; however,
obtaining adequate training image datasets for machine learning algorithms can be …

Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess
development provides large amounts of heterogeneous experimental data, containing …

Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …

As failure data is usually scarce in practice upon preventive maintenance strategy in
prognostics and health management (PHM) domain, transfer learning provides a …

The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and
digital technologies within industrial production and manufacturing systems. The objective of …

Bayesian Optimization is a useful tool for experiment design. Unfortunately, the classical,
sequential setting of Bayesian Optimization does not translate well into laboratory …

Transfer learning has been applied to deal with the insufficient labeled target dataset
problem in data-driven fault diagnosis. However, most existing solutions cannot work well …