Spatial–temporal short-term traffic flow prediction model based on dynamical-learning graph convolution mechanism

Short-term traffic flow prediction is a core branch of intelligent traffic systems (ITS) and plays an important role in traffic management. The graph convolution network (GCN) is widely used in traffic prediction models to efficiently handle the graphical structural data of road networks. However, the influence weights among different road...

A reappraisal of the ink-bottle effect and pore structure of cementitious materials using intrusion-extrusion cyclic mercury porosimetry

Reliable characterization of the pore structure is essentially important for transport-related durability studies of cementitious materials. Mercury intrusion porosimetry has been commonly used for pore structure measurement while the ink-bottle effect significantly affects the trustworthiness of pore size features of cementitious materials....