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.

Data Volume. Cloud usage generates data at a per-hour level that leads to volumes of data that can reach ~150TB, making it ...

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 process of continually tracking equipment and asset health gives operations a foundation for establishing predictive maintenance strategies by enabling early detection of potential issues before ...

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

Abstract: Accurate model selection is essential in predictive modelling across various domains, significantly impacting decision-making and resource allocation. Despite extensive research, the model ...

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, ...