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Machine learning method improves accuracy of inverse protein folding for drug design
An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design ...
A data-driven model to help avoid ecosystem collapse
Tipping points are the death of ecosystems. So scientists watch as warning signs gradually worsen until an ecosystem reaches ...
IEEE15d
NURBS values based on multi-objective particle swarm optimization algorithm for optimal power flow problem in power system
Abstract: The research on Optimal Power Flow (OPF) problems in power systems has undergone ... curve concept into the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm can significantly ...
IEEE22d
Optimization of Methodology for Identifying Partial Discharges in Insulating Liquids Through Optical Radiation Analysis Using Machine Learning
Optical radiation in the ultraviolet, visible light, and near-infrared range, emitted by electrical discharges in insulating liquids commonly used in electrical engineering ... was proposed, utilizing ...
Frontiers25d
Research on mobile ultrasonic stratified flow velocity measurement based on machine learning algorithms
The experimental results demonstrated that the use of the AdaBoost algorithm from machine learning for the mobile ultrasonic stratified flow velocity measurement device was feasible and effective.
Wired26d
DOGE Used a Meta AI Model to Review Emails From Federal Workers
Elon Musk’s so-called Department of Government Efficiency (DOGE) used artificial intelligence ... Point the Way to AGI Google’s AI models are learning to reason, wield agency, and build ...
C&EN29d
MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules
Engineering Laboratory, University of Cambridge, Cambridge CB2 1PZ, U.K. Department of Physics and Astronomy, University College, London WC1E 6BT, U.K. Yusuf Hamied Department of Chemistry, University ...