Modelling of hydrological processes at any scale is hampered by large uncertainties in parameters and forcing data, incomplete process representations (the scientific conceptualization of a phenomena ...
Here, the authors analyse real world multi-omics data from 400 breast cancer patients ... using deep neural networks to model SARS-CoV-2 spike protein sequence for novel mutation prediction ...
Abstract: Addressing the challenges of limited accuracy in anomaly detection within comprehensive environmental monitoring of industrial and mining enterprises, and the constraints posed by singular ...
How data modeling software tools enable better business intelligence. Organize your data landscape with Power BI—a scalable solution to organize, arrange, and present data insights, ensuring better ...
The course is designed to emphasize hydrological concepts while providing useful skills for using well-known hydrological models in simulating hydrological processes. The course is divided into two ...