In its Modernize Your Data Strategy to Enable AI/ML in Banking blueprint, Info-Tech details a structured five-step approach designed to help financial institutions expand data strategies, reduce AI ...
Dynamic Machine Learning Framework for Secure, Ultra-Reliable, and Energy-Efficient Open RAN Systems
Abstract: This paper proposes a machine learning (ML)-driven framework for Open Radio Access Networks (ORAN) to address security, Ultra-Reliable Low-Latency Communication (URLLC), and energy ...
Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
Type 2 diabetes mellitus (T2DM) constitutes a rapidly expanding global epidemic whose societal burden is amplified by deep-rooted health inequities. Socio-economic disadvantage, minority ethnicity, ...
Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...
Abstract: Dynamic Machine Allocation (DMA) is a vital aspect of production scheduling in semiconductor manufacturing. Current DMA practices heavily rely on engineers’ domain expertise and require a ...
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