Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

Abstract: In recent years, kernel machine learning algorithm (e.g. least square support vector machine, LSSVM) is a commonly method for time series prediction, as the main unit, the type of kernel ...

I used to laugh when people would say things like "gambling is becoming a real problem in this country." I mean, sure, it probably isn't the best thing to get addicted to, but back in my day you used ...

Valve continues to inch toward the inevitable Steam Machine release confirmed for this year, now by adding "initial support" for the hardware in the latest SteamOS preview update. That's the most ...

Valve’s Steam Machine desktop is currently in a state of involuntary limbo, driven by historically awful pricing and availability for memory and storage chips. AI data centers are absorbing much of ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Artificial intelligence is currently an active topic in both scientific research and commercial application as well as daily life. The linear operations of high-dimensional vectors are fundamental and ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

This is the repository directly corresponding to the Arnoldi Singular Vector (A-SV) perturbation approach Arnoldi Singular Vector perturbations for machine learning weather prediction, arXiv preprint: ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...