Abstract: Autonomous underwater vehicles (AUVs) present several challenges due to the complex and simultaneous interplay of various factors, including but not limited to unmodeled dynamics, highly ...

In a recent article, researchers from the University of Jyväskylä, Finland, emphasize the importance of multiscale modeling of catalysis in understanding and developing (electro)chemical processes.

Autoregressive models predict future values using past data patterns. Discover how these models work and their application in ...

The UK-led OpenBind initiative has reached a major milestone with the release of its first publicly available dataset and ...

The UK‑led OpenBind initiative has reached a major milestone with the release of its first publicly available dataset and predictive AI model, a ...

The transition between wakefulness and states of reduced consciousness, whether pharmacologically induced via anesthesia or pathologically necessitated by ...

Discover how quality-driven drug development and AI accelerate safer medicines, reduce risk, and improve patient outcomes.

Opinion: As AI use becomes more frequent in the invention of new drugs, it’s important to determine how it affects who’s ...

Predictive modeling is reshaping how businesses anticipate challenges, seize opportunities, and optimize processes. By leveraging machine learning, ensemble methods, and advanced analytics, ...

Brands have gotten adept at finding and following their audiences across the media landscape. Today, that means everywhere: linear TV, CTV, YouTube and the open web, often in the same evening. But ...

Enterprise technology vendors are racing to make AI work against the structured and relational data inside databases, data warehouses, and transaction systems.

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...