When checking that solutions to certain problems are correct, it turns out, you can’t get around the inherent complexity of ...

Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Many students appear to be completing assignments faster while learning less from them. This conclusion comes from one of the largest studies of how generative AI is changing student behavior and ...

AI companies are hiring philosophy graduates to help them understand the nature of consciousness, whether it can be ...

New Iterative Block Particle Filter algorithm makes genomic surveillance faster, cheaper and more scalable, improving early ...

What if your biggest challenges could become your greatest teachers? Learn five ACT-based ways to work with problems instead ...

A mathematical problem that had remained unsolved for more than 10 years in the physics of complex systems has finally been ...

Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...

Abstract: Ontology applies commonly to solve the problem of heterogeneity of data in the Semantic Web, but the heterogeneity problem between two ontologies seriously affects their communication. As an ...

Studying the epic journey of the iconic jumping plumber can lead to new insights in theoretical computer science—and may help ...

Abstract: The emergence of fuzzy sets makes job-shop scheduling problem (JSSP) become better aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy completion ...