OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval ...

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 ...

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

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...

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

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 ...