A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...
A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
The push to bring memecoins into the mainstream has just gained a lot of momentum, with REX Shares preparing to launch the first U.S.-listed Dogecoin (DOGE) exchange-traded fund (ETF). If approved, ...
As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...
Abstract: Extreme learning machine (ELM) is an effective and efficient neural model for universal approximation. However, its practical performance can degrade due to weight noise, node faults, and ...
Abstract: This research intends to create a novel approach for solving fractional differential equations (FDEs) of both linear and nonlinear types utilizing the fractional shifted Legendre neural ...
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