O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...
This paper examines EU global value-chain (GVC) integration and analyzes its drivers using machine learning models, with case ...
Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...
That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...
Abstract: The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
Post Doc Fellow: AI and Data Systems in Nuclear/Particle Physics, Stellenbosch University In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, ...
1 Architectural and Civil Engineering, Jinken College of Technology, Nanjing, Jiangsu, China 2 College of Civil Engineering and Architecture, Xinjiang University, Urumqi, Xinjiang, China Therefore, ...
Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...
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