A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform

Spatiotemporal residual noise in terrestrial earth observation products, often caused by unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to use gap-filled remote sensing products with time series reconstruction (TSR) algorithms. Applying currently available implementations of TSR to large-volume...

Life cycle assessment of material footprint in recycling: A case of concrete recycling

Meeting the current demand for concrete requires not only mining tons of gravel and sand, but also burning large amounts of fossil fuel resources in cement kilning. Consequently, concrete recycling is crucial to achieving a material-efficient society, especially with the application of various categories of concrete and the goal of phasing...

A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles

The deep reinforcement learning-based energy management strategies (EMS) have become a promising solution for hybrid electric vehicles (HEVs). When driving cycles are changed, the neural network will be retrained, which is a time-consuming and laborious task. A more efficient way of choosing EMS is to combine deep reinforcement learning (DRL)...