TV has transformed from a tightly controlled industry with a few powerful gatekeepers to a vast landscape of limitless ...

Abstract: Scheduling of emergency materials is particularly important after an emergency, in order to efficiently schedule emergency materials after a disaster, this paper designs a graph neural ...

India's employment marketplace is experiencing a critical efficiency crisis. Despite 10-12 million job seekers entering the ...

Note: All implementations are based on published papers and publicly available code. Contributions and corrections are welcome via PR.

Aston University has joined forces with Aurrigo, to develop AI to make its airport autonomous vehicles (AVs) fleet even more efficient, responsive and sustainable. As the number of autonomous vehicles ...

Abstract: The distributed shop scheduling problem is a hotspot in the shop scheduling field. Online scheduling requires making prompt decisions in response to environmental changes during ongoing ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

RBIS (Reinforcement Learning-Based Intelligent Scheduling) is a research project that integrates Deep Reinforcement Learning (DRL) agents with ns-3's 5G NR MAC scheduler to optimize resource ...

While the tech industry celebrates each breakthrough in artificial intelligence, real value is quietly being created in ...

Company cites changes in content discovery and creator behavior as drivers of service expansion NEW YORK, NY – January ...

The purpose of this paper is to explore the mechanism of 18β glycyrrhetinic acid (18β-GRA) in treating gastric cancer. Firstly, the toxicological effects of 18β-GRA were predicted using the ProTox3.0 ...

Rheumatologists share how they are using AI platforms for clinical documentation, reducing EHR time, streamlining workflows, ...