In this survey, we delve into the integration and optimization of Large Language Models
(LLMs) within edge computing environments, marking a significant shift in the artificial …

With the development of multimedia technology, people have fully enjoyed the pleasure of
audio and video and start to pursue the immersion of multi-sensory interactive experience …

With the development of 5G and the enrichment of application functions, applications have
put forward higher requirements on the computing power of terminal devices. To improve the …

We propose an algorithm that combines Reinforcement Learning (RL) and a PID cascade
control for landing a drone on a moving unmanned ground vehicle (UGV). Unlike other …

In urban environments, intersection scenarios with dynamic pedestrians are challenging for
intelligent vehicles (IV). To ensure safety and efficiency, it is crucial to develop an effective …

Technological development represents an excellent opportunity for the growth and spread of
smart healthcare services based on cloud computing and the Internet of things. Cloud …

With the current market of electric vehicles (EVs) in full swing, the real-time and accuracy of
lithium batteries are getting more and more attention. Due to the EV's complexity and …

Reinforcement learning based task offloading is a promising research direction in edge
computing. This paper proposes a Deep Reinforcement Learning (DRL) Task Offloading …

Aiming to strengthen the stability of operation and maintenance of the urban rail transit
network cloud platform at this stage, it is emerging to solve the security mechanism of the …

The computation of image normalization and standardization, consisting of division and
square root calculations can be described with an N-dimensional vector normalization …