Buyer’s Practical Guide to Selecting China Industrial Loading Arms for Oil and Chemical Facilities

LIANYUNGANG, JIANGSU, CHINA, February 13, 2026 /EINPresswire.com/ -- The global petrochemical and energy landscape is ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

AI tool debuts with better genomic predictions and explanations

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...

PromptSpy is the first known Android malware to use generative AI at runtime

Researchers have discovered the first known Android malware to use generative AI in its execution flow, using Google's Gemini ...
IEEE

Practical Nonlinear Model Predictive Control With Kolmogorov–Arnold Network Models

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Nonlinear Optimal Midcourse Guidance Using Sequential Pseudospectral Model Predictive Control

Abstract: A sequential pseudospectral model predictive control (SPMPC) method is proposed for nonlinear optimal midcourse guidance with a general performance index. First, the optimal midcourse ...
IEEE Spectrum on MSN

Can AI find physics beyond the standard model?

AI is searching particle colliders for the unexpected ...