Due to the greatly improved capabilities of devices, massive data, and increasing concern
about data privacy, Federated Learning (FL) has been increasingly considered for …

Detecting spoofing attacks on the positions of unmanned aerial vehicles (UAVs) within a
swarm is challenging. Traditional methods relying solely on individually reported positions …

The utilization of information and intelligent technology promotes the development and
innovation of the safety industry, which is also a research hotspot in recent years. This study …

CNC machines are engaged in numerous industries, including critical ones like the
aerospace, automotive, and military sectors, among others. Sensor data are time-series that …

This paper proposes a Cyber–Physical System (CPS) scheme to address the challenge of
developing self-improvement and online risk control for Electric Buses (E-Bus) in the …

Pressure relief valves are widely used in hydraulic systems but often fail when operating in
harsh environments. Developing effective and robust fault diagnosis models is essential for …

Fault diagnosis is critical to maintaining the performance of rotating machinery and ensuring
the safe operation of the equipment. Convolutional neural networks (CNNs) have recently …

Accurate and reliable bearing-fault diagnosis is important for ensuring the efficiency and
safety of industrial machinery. This paper presents a novel method for bearing-fault …

As a critical component of reusable rocket engines (RRE), the cyclic life of the turbine rotor
blisk often varies due to uncertainties such as machining errors and other factors. However …

The advent of communication technologies marks a transformative phase in critical
infrastructure construction, where the meticulous analysis of failures becomes paramount in …