Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

Objectives This study assessed whether a previously developed Monte Carlo simulation model can be reused for evaluating various strategies to minimise time-to-treatment in southwest Netherlands for ...

Objective To analyse temporal trends of respiratory infectious diseases (RIDs) in Baiyin City from 2014 to 2023, aiming to explore the epidemiological patterns of these diseases (tuberculosis, scarlet ...

The use of AI frequently leads to uncertainties for public bodies. The latest publication by the Federal Commissioner for ...

Download the latest Karnataka 2nd PUC Computer Science Model Question Paper 2025–26 with answers. Master the DPUE blueprint, ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

The total number of questions in every subject has been doubled. However, students only need to answer 50% (half) of the total questions given. This rule applies to all types of questions: Objective ...

Activated sludge models are crucial for designing and optimizing wastewater treatment systems, which are the cornerstone of sustainable water resource management. However, their complexity creates a ...

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.

On Tuesday, OpenAI announced that o3-pro, a new version of its most capable simulated reasoning model, is now available to ChatGPT Pro and Team users, replacing o1-pro in the model picker. The company ...

As CEOs trip over themselves to invest in artificial intelligence, there’s a massive and growing elephant in the room: that any models trained on web data from after the advent of ChatGPT in 2022 are ...

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, ...