Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers’ Perspectives This study explores how artificial intelligence (AI) ...

Abstract: Mobile crowdsensing (MCS) is an emerging technology, which provides a promising paradigm for completing complex sensing tasks. While existing studies for MCS mainly focus on designing ...

Abstract: Cancer remains one of the most challenging diseases to treat in the medical field. Machine learning (ML) has enabled in-depth analysis of complex patterns from large, diverse datasets, ...

Sharper views of black holes are turning what once looked like a fuzzy cosmic icon into a precision tool for testing gravity ...

When someone tells you that AI is going to replace human intelligence, you can honestly tell them that, as of this writing, ...

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

A new study identifies how LLMs develop social reasoning capabilities and form theory of mind (ToM), an important discovery ...

Professor James Rondinelli and Dean Christopher Schuh were honored as MRS Fellows for their outstanding contributions to the ...

To identify and evaluate candidate materials, process engineers must analyze an enormous amount of data. Bulk properties like ...

Artificial intelligence and machine learning are rapidly transforming scientific research, with researchers across multiple ...

It’s useful to think of our engagement with algorithms as a social contract. Political theorists have long used the social contract as a device to explain why individuals submit to the authority of a ...