The emergence of metamaterials and their continued prosperity have built a powerful
working platform for accurately manipulating the behavior of electromagnetic waves …

Abstract In the Chemical Processing Industry, shifts in market demand often require the
implementation of new operational modes that balance economic advantages with the need …

The development and commercial use of virtualized sensing (smooth) in the manufacturing
of Polyethylene Terephthalate (PET) and sewage treatment are both covered in this paper …

Complex industrial processes with dynamic and time-varying characteristics, as well as
diverse operating conditions, pose challenges in developing accurate real-time online …

We present an automated framework that integrates rectified linear unit activated artificial
neural network (ReLU-ANN) and mixed-integer linear programming (MILP) to enable …

In this article, a new deep learning enhanced microwave photonic (MWP) sensor based on
optical sideband processing with linear frequency modulated (LFM) pulse to enable fast and …

With the rapid development of machine vision technology, this technology is being widely
used in grade prediction for the froth flotation process. Several previously proposed froth …

Abstract Physical models for Packed Bed Thermal Energy Storage (PBTES) system plays a
crucial role in predicting its dynamic behavior and long-term performance under various …

Modeling of improved amine scrubbers using artificial neural networks (ANNs) were carried
out in this study. Instead of training models from scratch with the case-by-case method, the …

Ensuring the interpretability of machine learning models in chemical engineering remains
challenging due to inherent limitations and data quality issues, hindering their reliable …