[HTML][HTML] Edge AI: a survey
Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …
refers to the practice of doing AI computations near the users at the network's edge, instead …
Reinforcement learning-based physical cross-layer security and privacy in 6G
Sixth-generation (6G) cellular systems will have an inherent vulnerability to physical (PHY)-
layer attacks and privacy leakage, due to the large-scale heterogeneous networks with …
layer attacks and privacy leakage, due to the large-scale heterogeneous networks with …
Anomaly traffic detection based on communication-efficient federated learning in space-air-ground integration network
In this paper, we study the architectures of space-air-ground integration network (SAGIN)
proposed by domestic scientific research institutes, and put forward an collaborative federal …
proposed by domestic scientific research institutes, and put forward an collaborative federal …
Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning
Unsorted retired batteries with varied cathode materials hinder the adoption of direct
recycling due to their cathode-specific nature. The surge in retired batteries necessitates …
recycling due to their cathode-specific nature. The surge in retired batteries necessitates …
Double-gradient-structured composite aerogels for ultra-high-performance moisture energy harvesting
X Zhang, Z Dai, J Chen, X Chen, X Lin… - Energy & …, 2023 - pubs.rsc.org
Currently, the introduction of a gradient structure in moisture-electricity generators (MEGs)
has been shown to significantly improve their output performance. However, due to the …
has been shown to significantly improve their output performance. However, due to the …
Decentral and incentivized federated learning frameworks: A systematic literature review
The advent of federated learning (FL) has sparked a new paradigm of parallel and
confidential decentralized machine learning (ML) with the potential of utilizing the …
confidential decentralized machine learning (ML) with the potential of utilizing the …
Environment‐Responsive Therapeutic Platforms for the Treatment of Implant Infection
The application of medical implants has greatly improved the survival rate and life quality of
patients. Nevertheless, in recent years, there are increasing cases of implant dysfunction or …
patients. Nevertheless, in recent years, there are increasing cases of implant dysfunction or …
Liquid metals: preparation, surface engineering, and biomedical applications
Liquid metals (LMs) with high thermal/electrical conductivity, extraordinary fluidity, and
excellent biocompatibility have garnered considerable attention in the last decade …
excellent biocompatibility have garnered considerable attention in the last decade …
Reinforcement learning based energy-efficient collaborative inference for mobile edge computing
Collaborative inference in mobile edge computing (MEC) enables mobile devices to offload
the computation tasks for the computation-intensive perception services, and the inference …
the computation tasks for the computation-intensive perception services, and the inference …
Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip
By mimicking the neurons and synapses of the human brain and employing spiking neural
networks on neuromorphic chips, neuromorphic computing offers a promising energy …
networks on neuromorphic chips, neuromorphic computing offers a promising energy …