Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges

Modelling, predicting and analysing driver behaviours are essential to advanced driver assistance systems (ADAS) and the comprehensive understanding of complex driving scenarios. Recently, with the development of deep learning (DL), numerous driver behaviour learning (DBL) methods have been proposed and applied in connected vehicles (CV) and...

A literature review of Artificial Intelligence applications in railway systems

Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective,...

Automatic depression recognition by intelligent speech signal processing: A systematic survey

Depression has become one of the most common mental illnesses in the world. For better prediction and diagnosis, methods of automatic depression recognition based on speech signal are constantly proposed and updated, with a transition from the early traditional methods based on hand-crafted features to the application of architectures of deep...

Review of Packaging Schemes for Power Module

SiC devices are promising for outperforming Si counterparts in high-frequency applications due to its superior material properties. Conventional wirebonded packaging scheme has been one of the most preferred package structures for power modules. However, the technique limits the performance of a SiC power module due to parasitic inductance...