Contrast-Agnostic Groupwise Registration by Robust PCA for Quantitative Cardiac MRI

Quantitative cardiac magnetic resonance imaging (MRI) is an increasingly important diagnostic tool for cardiovascular diseases. Yet, co-registration of all baseline images within the quantitative MRI sequence is essential for the accuracy and precision of quantitative maps. However, co-registering all baseline images from a quantitative...

A 2m-Range 711uW Body Channel Communication Transceiver Featuring Dynamically-Sampling Bias-Free Interface Front End

Body Channel Communication (BCC) offers a low-loss signal transmission medium for ultra-low-power wearable devices on human body [1]. However, the effective communication range on human body is limited to less than 1m in the state-of-the-art BCC transceivers [2], where the signal loss at the interface of body surface and BCC receiver remains to...

Train scheduling with flexible coupling and decoupling at stations for an urban rail transit line

More and more people in big cities choose urban rail transit as the main means of public transportation. With the increasing unbalanced passenger flow in time and space, the traditional operation mode with fixed train formation (or composition) is difficult to satisfy the varying passenger demands. This paper distinguishes different train...

Finite Element Analysis of Power Module Packages with One-step Molding for Power Inductors

With the development of 5G communication technology and the rise of power semiconductors, the switching frequency of the circuit keeps increasing, which pushes for miniaturization of power modules and related components. Therefore, in this paper, a one-step molding technology was proposed for a DC/DC buck converter power module. We proposed a...

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)...

3D cadastre in China: A case study in Shenzhen City