Machine learning-driven carrier risk modeling enables supply chains to predict and prevent pickup defects, reducing costs and improving on-time performance.
From fishing quotas in Norway to legislative accountability in California, investigative journalists share practical, ...
I test-drove both. Here’s what I learned. In early March, OpenAI unleashed a one-two punch, dropping two major frontier ...
You can now run LLMs for software development on consumer-grade PCs. But we’re still a ways off from having Claude at home.
This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to ...
Abstract: We propose an explainable topic modeling method that tracks user interests to elucidate their association with social events while ensuring high reliability and low computational cost.
Abstract: The advent of the unstructured textual data has increased the pressure on the development of sophisticated methods that can be used to systematize and classify data. To overcome this issue, ...
This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experiences as discussed on the social media platform ...
One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery ...
I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Best laptop cooling pads Best flip ...
ABSTRACT: This study investigates projectile motion under quadratic air drag, focusing on mass-dependent dynamics using the Runge-Kutta (RK4) method implemented in FreeMat. Quadratic drag, predominant ...
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