The application of machine learning (ML) techniques to metal-based nanomaterials has
contributed greatly to understanding the interaction of nanoparticles, properties prediction …

Engineered nanomaterials (ENMs) have tremendous potential in many fields, but their
applications and commercialization are difficult to widely implement due to their safety …

The accurate prediction of greenhouse gas (GHG) emissions from paddy fields is critical for
developing mitigation strategies to reduce emissions, while realizing the large-scale …

Nuclear magnetic resonance (NMR) is a robust method for the analysis of molecular
complex structures, and the measurement of the nuclear spin–spin coupling constant is the …

The rapid increase in posting personal information on social media has been noticed over
last two years especially due to heavy use of smart phones and restrictions imposed on face …

This study proposes using the Light Gradient Boosting Machine (LightGBM) to improve the
defrosting control strategy in frost-free refrigerators. By analyzing data and optimizing control …

IR-drop is a fundamental constraint by almost all integrated circuits (ICs) physical designs,
and many iterations of timing engineer change order (ECO), IR-drop ECO, or other ECO are …

Modelling of plant growth is vital for hypotheses testing and carrying out virtual plant growth
and development experiments, which may otherwise take a long time under field conditions …

Recently, Deep Learning has been applied to many medical domains, such as medical
image analysis, bioinformatic, biochemistry, drug design, and so forth, to improve the …

Nowadays, data is developing with technology. With developments in the Internet and
technology, it makes a warehouse that changes the data more rapidly and in volume. This …