Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

This repository is about designing a database model for Global Super Store. This project is the final project of the 7th course "Advanced Data Modeling" of Meta Database Engineer Professional ...

The next generation of innovation will be defined by its ability to operate in real time. From autonomous vehicles navigating city streets to industrial systems predicting failures before they happen, ...

This view of NASA’s Ingenuity Mars Helicopter was generated using data collected by the Mastcam-Z instrument aboard the agency’s Perseverance Mars rover on Aug. 2, 2023, the 871st Martian day, or sol, ...

The potential applications of DTs extend beyond individual patient care to public health surveillance, hospital resource management, and epidemiological modeling. However, several challenges persist, ...

Behavioral information from an Apple Watch, such as physical activity, cardiovascular fitness, and mobility metrics, may be more useful for determining a person's health state than just raw sensor ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

A new artificial intelligence (AI) model called Centaur can predict and simulate human thought and behavior better than any past models, opening the door for cutting-edge research applications. When ...

Data are a crucial asset for organizations, making it essential for database designers to effectively organize and manage data using DataBase Management Systems (DBMS). DataBase design Concepts (DBCs) ...

Hydrological models are widely used to assess climate change effect on water resources at the catchment scale. However, data scarcity is one of the main challenges faced by hydrological modelers ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...