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A Control Framework for CUBESAT Rendezvous and Proximity Operations using Electric Propulsion

Autor: Lin, Bo-Chuan, Kong, Chun-Wei, Semeraro, Simone, McMahon, Jay W.

A control framework is presented to solve the rendezvous and proximity operations (RPO) problem of the EP-Gemini mission. In this mission, a CubeSat chaser is controlled to approach and circumnavigate the other uncooperative CubeSat target. Such a pr

Externí odkaz: http://arxiv.org/abs/2412.00827

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Error Bounds for Deep Learning-based Uncertainty Propagation in SDEs

Autor: Kong, Chun-Wei, Laurenti, Luca, McMahon, Jay, Lahijanian, Morteza

Stochastic differential equations are commonly used to describe the evolution of stochastic processes. The uncertainty of such processes is best represented by the probability density function (PDF), whose evolution is governed by the Fokker-Planck p

Externí odkaz: http://arxiv.org/abs/2410.22371

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Enhancing AI Accessibility in Veterinary Medicine: Linking Classifiers and Electronic Health Records

Autor: Kong, Chun Yin, Vasquez, Picasso, Farhoodimoghadam, Makan, Brandt, Chris, Brown, Titus C., Reagan, Krystle L., Zwingenberger, Allison, Keller, Stefan M.

In the rapidly evolving landscape of veterinary healthcare, integrating machine learning (ML) clinical decision-making tools with electronic health records (EHRs) promises to improve diagnostic accuracy and patient care. However, the seamless integra

Externí odkaz: http://arxiv.org/abs/2410.14625

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