Deep research and communicating new trends in the design, control and applications of the real time control of intelligent sensors systems using advanced intelligent control methods and techniques is the main purpose of this research. The innovative...
Excitation–emission matrix (EEM) fluorescence spectroscopy, when combined with machine learning algorithms, has emerged as a highly promising tool for non-invasive biomedical diagnosis, demonstrating significant potential across various applica...
Metal–organic framework (MOF)-based surface-enhanced Raman scattering (SERS) sensors have emerged as a versatile platform for high-sensitivity and selective detection in agricultural, environmental, and biomedical applications. By integrating p...
The widespread and persistent occurrence of micropollutants—such as pesticides, pharmaceuticals, heavy metals, personal care products, microplastics, and per- and polyfluoroalkyl substances (PFAS)—has emerged as a critical environmental a...
The aim of this research was to develop and deploy efficient deep convolutional neural network (DCNN) frameworks for detecting and discriminating between various categories of designer drugs. These are of particular relevance in forensic contexts, ai...