The increasing deployment of industrial robots in manufacturing requires accurate fault
diagnosis. Online monitoring data typically consist of a large volume of unlabeled data and a …

Due to the difficulty in obtaining clinical samples and the high cost of labeling, rare skin
diseases are characterized by data scarcity, making training deep neural networks for …

This study introduces the Adversarial Task Augmented Sequential Meta-Learning (ATASML)
framework, designed to enhance fault diagnosis in industrial processes. ATASML integrates …

Targeting the challenge of variable working conditions in bearing fault diagnosis, most of the
fault diagnosis methods based on transfer learning focus on the transfer of knowledge …

Intelligent fault diagnosis in various industrial applications has rapidly evolved due to the
recent advancements in data-driven techniques. However, the scarcity of fault data and a …

Early fault detection (EFD) of rolling bearings can recognize slight deviation of the health
states and contribute to the stability of mechanical systems. In practice, very limited target …

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

This paper is an attempt to show how a Human-Robot Interface (HRI) system in the Greek
language can help people with brain damage in speech and its related perception issues …

The accurate and comprehensive fault diagnosis is pivotal for the maintenance of
mechanical equipment, which may directly impact the safety in production and avoid …

Reliability is of great significance in ensuring the safe operation of modern industry, which
mainly relies on data analysis and life tests. However, as the life of mechanical systems …