Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...
Researchers developed a new model to predict the likelihood of critical illness in patients with connective-tissue disease-associated ILD.
Encryption systems rely on “random” numbers, but conventional computers can’t generate them perfectly. New research shows that quantum physics can. By Alexander Nazaryan Researchers in Switzerland ...
Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...
The growing demand for smaller, lighter, and more embedded hardware has made Physical Unclonable Functions (PUFs) a promising solution for authentication in Int ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
ABSTRACT: Biogas is gaining prominence as a renewable energy source with significant potential to reduce greenhouse gas emissions and mitigate environmental impacts associated with fossil fuels. This ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results