This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

Background Understanding the intricacies of wildfire impact across diverse geographical
landscapes necessitates a nuanced comprehension of fire dynamics and areas of …

Background Chemical process modeling is essential for the optimization, precise control
and prediction of processes performance. As the modeling based on the first principles is …

Background Concurrent chemoradiotherapy (CCRT) is a crucial treatment for non-small cell
lung carcinoma (NSCLC). However, the use of deep learning (DL) models for predicting the …

Understanding heat transfer in composite materials is essential for optimizing their
performance in critical applications across industries such as aerospace, automotive …

This perspective article presents the density functional theory and traces its evolution. With
the advancement in density functional theory-based computations and the efforts to collate …

The root mean square deviation is a common way to measure the electromechanical
impedance of piezoceramic transducers that are used for traditional preload monitoring …

Chemical mechanical planarization (CMP) stands as a critical process in semiconductor
manufacturing, necessitating precise prediction of material removal rate (MRR) to achieve …

Artificial intelligence methods, especially artificial neural networks (ANNs), have increasingly
been utilized for the mathematical description of physical phenomena in (metallic) material …

Prediction of diaphragm wall deformation is vital to intelligent construction and environment
safety in excavation engineering. This paper presents a novel prediction model entitled …