Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control.

Abstract: This paper introduces a new hybrid time series forecasting technique to obtain an efficient and accurate daily crude oil prices forecast. The proposed hybrid technique combines the features ...

Start your journey into machine learning with EEG time-series data in this easy-to-follow Python project. Perfect for ...

Real-time performance is about fidelity. Think of data like video: A grainy, low-resolution feed might capture broad shapes, ...

The Francis College of Engineering, Department of Electrical and Computer Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Masoumeh Farhadi Nia on: "Machine Learning for ...

TORONTO — Game 7 was so insane, so compelling, so breathtaking, so dramatic, that when the final out was made early Sunday morning, Dodgers three-time Cy Young winner Clayton Kershaw looked at his ...

Los Angeles Dodgers' Freddie Freeman shared his emotions after winning 2025 World Series against the Toronto Blue Jays. Court Deals Blow to Trump Officials Over Veterans’ Cases 'Charlie's Angels' star ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Researchers utilize 2D electrical resistivity imaging and borehole data to estimate the N60-value of soils with k-means clustering technique Thailand's northern regions, characterized by complex ...

In this paper, we explore applying multivariate time series models using Python to forecast the impacts of severe weather on agricultural supply chains. Using data on key environmental variables from ...