Silva, both Engineers at Netflix, presented “Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale” at QCon London 2026, where they discussed the design and implementation ...

Urban congestion is a big problem in our cities. It leads to commuter delays and economic inefficiency. More tragically, though, it leads to a million deaths annually worldwide. Research appearing in ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

AI-driven material development and new additive manufacturing technology are accelerating new aluminum alloy, battery, and material processing innovations.

Motor imagery (MI) is the mental process of imagining a specific limb movement, such as raising a hand or walking, without physically performing it. These imagined movements generate distinct patterns ...

Researchers at Chiba University in Japan have developed a new artificial intelligence framework capable of decoding complex brain activity with significantly improved accuracy, marking an important ...

Motor imagery electroencephalography (EEG) signals depict changes in brain activity during imagined limb movements. Conventional methods, however, often fail to capture these spatiotemporal variations ...

Motor imagery (MI) is the mental process of imagining a specific limb movement, such as raising a hand or walking, without physically performing it ...

Motor imagery or imagined limb movements can power brain–computer interface (BCI) devices, such as prostheses and wheelchairs, supporting rehabilitation for people with neuromusculoskeletal disorders.

Abstract: Graph Convolutional Networks (GCNs) have shown significant performance in various domains. However, their performance is limited by the reliance on static adjacency matrices, which fail to ...

Steven Weisberg, a researcher at The University of Texas at Arlington, put some of the most advanced artificial intelligence ...

Abstract: A dynamic graph (DG) is commonly encountered in many big data-related application scenarios, like cryptocurrency transaction analysis. A dynamic graph convolutional network (GCN) can ...