A new study unveils an adaptive deep brain stimulation system that adjusts in real time to prevent Parkinson's falls.

Google DeepMind's AlphaEvolve uses large language models to automatically discover new game theory algorithms that match or outperform decades of human-designed approaches. For years, the algorithms ...

Abstract: This paper presents a new adaptive sampling strategy for the parametric macromodeling of -parameter-based frequency responses. It can be linked directly with the simulator to determine up ...

Abstract: Target tracking is an important application of underwater wireless sensor networks (UWSNs). Due to the energy constraint and energy imbalanced dissipation of underwater nodes, it is a ...

For the low efficiency and poor generalization ability of path planning algorithm of industrial robots, this work proposes an adaptive field co-sampling algorithm (AFCS). Firstly, the environment ...

This repository contains the official implementation for Reinforce-Ada, an adaptive sampling framework designed to resolve the ``signal collapse'' problem in Reinforce-style algorithm with group ...

Contrast Adaptive Sharpening (CAS) is a low overhead adaptive sharpening algorithm with optional up-sampling. The technique is developed by Timothy Lottes (creator of FXAA) and was created to provide ...

Center for Biophysics and Quantitative Biology, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States Center for Biophysics and Quantitative Biology, University of Illinois ...

The ultra-deep fault-karst structure discovered in the Tarim Basin in Western China is a fractured-vuggy carbonate reservoir with great potential for development. The diffraction generated by ...

Monte Carlo methods, tools for sampling data from probability distributions, are widely used in the physical sciences, applied mathematics, and Bayesian statistics. Nevertheless, there are many ...