50+ multitask evolutionary algorithms for multitask optimization 50+ single-task evolutionary algorithms that can handle multitask optimization problems 200+ multitask optimization problem cases with ...

Robotic-guided system Researchers at Zeta Surgical are working to make transcranial focused ultrasound treatment safer and more successful. (Courtesy: CC BY 4.0/Bioengineering ...

Growing data center power demands are driving server end-equipment manufacturers to reach higher power-conversion efficiencies in order to reduce the thermal footprint of their systems. The transition ...

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...

A common use case for high-level synthesis (HLS) is taking 3rd party generated or legacy C/C++ algorithms and converting the algorithm to a hardware implementation using an HLS compiler. This can ...

Abstract: Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto-date and ...