Nowadays, machine learning (ML) has attained a high level of achievement in many
contexts. Considering the significance of ML in medical and bioinformatics owing to its …

Online real-time traffic flow prediction typically offers better real-time performance than
offline prediction. However, existing studies rarely discussed online real-time traffic flow …

Wireless sensor nodes come with small-sized batteries that provide the energy required to
do all kinds of activities. Unnecessary usage of the radio, especially during idle listening …

Determination of small-molecule API (Active Pharmaceutical Ingredient) solubility in solvents
is of great importance for drug development in pharmaceutical industry. This study uses …

This study presents a comparative analysis of three different models, namely Deep Neural
Network (DNN), Quantile Regression (QR), and K-Nearest Neighbors (KNN) for the …

Modeling and simulations based on machine learning techniques were conducted in this
research for determination of pharmaceutical solubility in supercritical solvent for the sake of …

Hydrodesulfurization (HDS) process is an important process for separation of sulfur
compounds from petroleum-based products due to operational and environmental problems …

Membrane system for molecular separation was studied in this work using combined
modeling approach. Computational fluid dynamics (CFD) was conducted and integrated to …

Understanding the solubility of drug particles in solvents has remained a big challenge in
different fields. Development of advanced computational methods to predict the solubility of …

In this study, the solubility of phenytoin and the supercritical CO 2 (solvent) density were
investigated using three different models: Multilayer Perceptron (MLP), NU-SVR, and …