Principal component analysis is a versatile statistical method for reducing a cases-by-
variables data table to its essential features, called principal components. Principal …

The chemical processing industry has relied on modeling techniques for process monitoring,
control, diagnosis, optimization, and design, especially since the third industrial revolution …

Last decade's advances and modern aspects of near infrared spectroscopy are critically
examined and reviewed. Innovative instrumentation, highlighted by portable and imaging …

Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …

Rapid developments in hardware, software, and communication technologies have
facilitated the emergence of Internet-connected sensory devices that provide observations …

Mass spectrometry imaging (MSI) is a powerful tool that enables untargeted investigations
into the spatial distribution of molecular species in a variety of samples. It has the capability …

Deep spectral modelling for regression and classification is gaining popularity in the
chemometrics domain. A major topic in the deep learning (DL) modelling of spectral data is …

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman
spectroscopy, have been successful methods for studying the interaction of light with …

Formaldehyde sensors are essential devices in the indoor air quality monitoring and gas
leakage detection in industrial areas. Enormous efforts are made to promote the …

In this technical article, to seek the optimal solution to time-dependent nonlinear optimization
subject to linear inequality and equality constraints (TDNO-IEC), the gradient-based …