Abstract: Federated Learning (FL) is a popular privacy-preserving machine learning paradigm, enabling collaborative training among distributed devices coordinated by a central server, without ...
The Department of Education revisited proposed changes to asynchronous clock, credit-hour, and subscription-based programs in distance education. In previous years, the Department of Education’s final ...
Abstract: This paper presents a novel robust and accurate normal-assisted learning-based rigid point set registration approach, i.e., Deep Bi-directional Hybrid Mixture Registration (DeepBHMR), where ...
Background: This study aims to investigate the efficacy of peer-assisted learning amalgamated with scenario simulation in enhancing the trauma first aid competencies and holistic abilities of ...
Machine learning-assisted metal additive manufacturing has been widely applied in performance optimization and control, such as process parameter optimization, structural optimization of formed parts, ...
Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...
As technology evolves, researchers are finding powerful ways to integrate computation, automation and artificial intelligence into their work. At the forefront of this transformation are chemists from ...
(The following is a press release from the law firm that filed a class-action lawsuit on behalf of Ryan Dickey against The Stronach Group, Churchill Downs Inc., and the New York Racing Association ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Correlative imaging is a powerful analytical approach in bioimaging, as it offers ...
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