In the modern era, deep learning (DL), and machine learning (ML), have emerged as
potential technologies that are widely applied in the fields of science, engineering, and …

Textile effluent treatment has gained significant attention due to the carcinogenic effects of
the dye pollutants present and their enhanced resistance to degradation. Porous ceramic …

Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …

Efficiency improvement in contaminant removal by nanofiltration (NF) and reverse osmosis
(RO) membranes is a multidimensional process involving membrane material selection and …

As decision-makers, researchers encounter highly dynamic, complex problems requiring
suitable nature-based and industrial quantitative tools for performance analyses, syntheses …

The escalating quantity of wastewater from multiple sources has raised concerns about both
water reuse and environmental preservation. Therefore, there is a pressing need for …

Data-driven machine learning (ML) provides a promising approach to understanding and
predicting the rejection of trace organic contaminants (TrOCs) by polyamide (PA). However …

This paper proposes a new novel approach to find an optimal path for a mobile robot in a
two‐dimensional environment. Finding the optimal path is done using the Bees Algorithm …

Water is a vital resource that makes it possible for human life forms to exist. The need for
freshwater consumption has significantly increased in recent years. Seawater treatment …

Diversified ion-selective separation applications have dramatically incentivized the
exploitation and performance modulation of highly ion-selective nanofiltration (NF) …