The milage of asphalt pavement growth explosively around the world in the past decades
resulted in a tremendous maintenance workload. Preventive maintenance (PM) is an …

Traditional building energy prediction (BEP) methods usually solve time-series prediction
problems using either recursive strategy or direct strategy, which may ignore time …

Urban public transport systems, characterised by their complexity, generate vast data sets
that pose challenges to traditional analytical methods. To address this issue, our research …

In this paper we propose ConvXSS, a novel deep learning approach for the detection of XSS
and code injection attacks, followed by context-based sanitization of the malicious code if …

Bus passenger flow is one of the decisive factors for the development of public
transportation. Therefore, accurate prediction of real-time passenger flow on bus routes not …

The tap-on smart-card data provides a valuable source to learn passengers' boarding
behaviour and predict future travel demand. However, when examining the smart-card …

Bus operation scheduling is closely related to passenger flow. Accurate bus passenger flow
prediction can help improve urban bus planning and service quality and reduce the cost of …

This study examines bus bunching along a common-line corridor, considering crucial factors
underexplored in existing literature, such as stochastic travel times, passenger arrival …

Accurate prediction of passenger demand is essential for the efficient operation and
management of metro systems. In practical scenarios, strategies to enhance metro service …

The insight into origin–destination (OD) demand patterns aids transport planners in making
the public transit system more efficient and attractive. This may encourage individuals to shift …