MathWorks has joined the EDGE AI FOUNDATION, an organisation dedicated to advancing energy‑efficient artificial intelligence ...

Collaboration supports engineers building AI models in MATLAB and PyTorch, integrating them into system simulations, and deploying to embedded devices .

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots to scalable, physics-based intelligence across assets. Here’s how SciML can ...

Honeywell’s HALO machine learning system predicted pressure disturbances and cycle delays with 12-minute notice, enabling operators to take preventive action before shutdowns occurred. The ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...

Abstract: The operational health of distribution transformers is critical for ensuring uninterrupted power delivery across smart grid infrastructures. This paper presents a predictive maintenance ...

Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...

This study retrospectively collected data from 1,128 patients who underwent general anesthesia at Sir Run Run Shaw Hospital, affiliated with Zhejiang University School of Medicine, from January 2021 ...

This project aims to develop predictive maintenance models for e-mobility vehicles (e-bikes and e-scooters) using comprehensive datasets collected in real-world conditions around Dublin City ...