The rapid growth and adaptation of medical information to identify significant health trends
and help with timely preventive care have been recent hallmarks of the modern healthcare …

The human kind is facing various natural calamities such as Elnino, forest fires, climate
change, etc., due to environmental degradation and pollution. The United Nations has come …

To adequately elucidate the complex in-cylinder flow structures and its underlying effects on
the thermal processes inside an internal combustion engine (ICE) has long been a daunting …

Biodiesel has appeared as a renewable and clean energy resource and a means of
diminishing global warming. This study provides Bayesian optimization algorithm (BOA) …

Accurate prediction of domestic waste generation is a challenging task for municipalities to
implement sustainable waste management strategies. In the present study, domestic waste …

A novel design optimization approach (ActivO) that employs an ensemble of machine
learning algorithms is presented. The proposed approach is a surrogate-based scheme …

In recent years, the use of machine learning-based surrogate models for computational fluid
dynamics (CFD) simulations has emerged as a promising technique for reducing the …

Electricity generation from microbial fuel cells (MFCs) is a potential environment-friendly
technology. This study provides Bayesian Algorithm (BA) based Support Vector Regression …

The microfluidic concentration gradient generator (μ CGG) is an important biomedical device
to generate concentration gradients (CGs) of biomolecules at the microscale. Nonetheless …

Data-driven intelligent computational design (DICD) is a research hotspot that emerged
under fast-developing artificial intelligence. It emphasizes utilizing deep learning algorithms …