With the development of industry, more and more crucial mechanical machinery generate
wildness demand of effective fault diagnosis to ensure the safe operation. Over the past few …

Workplace safety accidents are a pervasive issue worldwide. According to the National Work
Safety Supervision Administration, a striking 67.95% of construction accidents occur due to …

Earthquake prediction is considered a vital endeavour for human safety. Effective
earthquake prediction can drastically reduce human damage, which is of utmost importance …

While transfer learning-based intelligent diagnosis has achieved significant breakthroughs,
the performance of existing well-known methods still needs urgent improvement, given the …

Deep learning has been employed widely in bearing fault diagnosis. However, in industry,
sufficient and complete fault samples are hard to acquire and the working conditions vary …

A prescribed time fuzzy adaptive consensus control method is constructed for multiagent
systems with sensor faults and dead-zone input. Sensor faults inevitably occur in actual …

The aim of this study is to improve ride comfort among tractor drivers by utilizing Internet of
Things (IoT) technology and Machine Learning (ML) techniques to analyze and predict …

Despite significant progress, estimating 3D human poses from monocular videos remains a
challenging task due to depth ambiguity and self-occlusion. Most existing works attempt to …

Detecting defects in industrial products is one of the most widespread applications of
industrial automation. Various product defects, large similarities, and drastic changes in …

Deep learning has been widely applied to automated leakage detection and location of
natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial …