Abstract Advanced Machine Learning (ML) algorithms can be applied using Edge
Computing (EC) to detect anomalies, which is the basis of Artificial Intelligence of Things …

Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …

Accurate forecasts for pressurized water reactor safety parameters are essential to ensure
the safe operation of nuclear reactors. Potential of artificial neural networks on this task is …

Anomaly detection (AD) plays a crucial role in identifying unusual data patterns indicative of
potential issues or opportunities. Recent data-driven AD models require extensive training …

Stochastic configuration network (SCN) is a powerful prediction model whose performance
is significantly influenced by the configuration of the network parameters. To improve the …

The Industrial Revolution 4.0 has catapulted the integration of advanced technologies in
industrial operations, where interconnected systems rely heavily on sensor information …

Recent years have seen a growing involvement of researchers and practitioners in crafting
Deep Neural Networks (DNNs) that seem to outperform existing machine learning …

Crowd monitoring is a primary function in diverse industrial domains, such as smart cities,
public transport, and public safety. Recent advancements in low-energy devices and rapid …

Advances in manufacturing technology have made it possible to replace some components
anywhere to meet the needs of different functions with multi-function devices. However …

Training a deep learning model generally requires a huge amount of memory and
processing power. Once trained, the learned model can make predictions very fast with very …