Abstract: This article presents a deep autoencoder-based methodology for unsupervised anomaly detection in centrifugal pumps under limited failure data conditions, focusing on real-world applications ...

Published in the Ain Shams Engineering Journal, the study Leveraging Artificial Intelligence for Minimizing Environmental Footprints in the Mining Industry was conducted by researchers from ...

AI video tools promise total control, but hidden ‘concept entanglement’ glues identities, expressions and behaviors together, ...

Chinese researchers have published a new AI-driven system designed to interpret scramjet combustion simulations at speeds ...

AI is helping scientists make sense of messy dinosaur footprints, offering new clues about how dinosaurs moved and when birds ...

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and ...

Abstract: Accurate sensor fault detection and diagnosis in industrial processes are essential for maintaining system reliability and operational safety. However, under closed-loop control conditions, ...

As organizations race to operationalize AI agents across critical workflows, performance alone is no longer enough--enterprises must also understand, validate, and govern how those systems arrive at ...

Cambridge, MA — In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its ...

Insomnia disorder (ID) is neurobiologically heterogeneous and often eludes characterization by traditional group-level neuroimaging. Subtyping based on neuroimaging and clinical data offers a ...