Abstract: With the advent in industrial technologies, it is mandatory to identify the fault occurring in induction motors at early stages since prolonged defects can severely damage the motor and lead ...

This project presents a machine learning-based predictive model developed in MATLAB to forecast hospital resource requirements using historical healthcare data. The system helps in predicting future ...

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...

The current microgrids are experiencing growing difficulties in voltage stability and operational capacity, particularly with constant power loads (CPLs), leading to negative impedance behavior and ...

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 ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

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 ...

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 ...