This is an important contribution that largely confirms prior evidence that word recognition - a cornerstone of development - improves across early childhood and is related to vocabulary growth. This ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

NTT Research, Inc., a division of NTT, announced that its Physics and Informatics (PHI) Lab, working with Cornell University and Stanford University, has developed the world's first programmable ...

Abstract: The nonlinear (NL) magnetic material law is crucial for an accurate estimation of the core losses in electromagnetic devices. However, this law comes with a certain level of uncertainty.

Do you sense something problematic about the word “problematic”? The way it’s used has changed a great deal in recent years, so much that it can now seem a little shifty. The journey that brought us ...

In today’s fast-paced, ever-evolving world, the complexity of challenges faced in both business and everyday life requires a shift in how we approach problem solving. Traditional linear thinking, ...

Word problems try and tell students a story about the math problem in front of them. They are a useful way to connect abstract numbers to concrete situations, so students can learn early on to apply ...

Working memory is like a mental chalkboard we use to store temporary information while executing other tasks. Scientists worked with more than 200 elementary students to test their working memory, ...

A recent article in Advanced Materials reports a new fabrication method for nonlinear optical components using nanostructured polycrystalline lithium niobate (LN). The study addresses key limitations ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...