Yang Yang

TL;DR: Two adaptive reinforcement learning based spectrum-aware routing protocols are introduced and Q-Learning and Dual Reinforcement Learning are applied respectively, which are simpler and easier to implement, more cost-effective, and can avoid drawbacks in on-demand protocols but still keep adaptive and dynamic routing.

TL;DR: In vitro and in vivo studies demonstrated that the FSL induced micropattern and Ca/P phase had positive effects on the acceleration of early osseointegration of Ti implants with bone tissue.

TL;DR: Detailed simulation results show that FEMOS is a fair and efficient algorithm for all user terminals and, more importantly, it can offer much better performance, in terms of network throughput, service delay, and queue backlog, than traditional node assignment and resource allocation algorithms.

TL;DR: The analytical and simulation results show that the proposed paired offloading of multiple tasks (POMT) algorithm can offer the near-optimal performance in system average delay and delay reduction ratio (DRR), and achieve more number of beneficial TNs, at two orders of magnitude lower complexity than a centralized optimal algorithm for computation offloading.