Researchers explore glioblastoma's genetic complexity using innovative spatial profiling, aiming to enhance treatment ...

As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

Esri announced new artificial intelligence tools based on its partnership with Microsoft, Gaussian splats in its flagship ArcGIS platform and more extended reality tools at its 45th user conference in ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Communication-Efficient Adam-Type Algorithms for Distributed Data Mining Distributed data mining is an emerging research topic to effectively and efficiently address hard data mining tasks using big ...

Comparing Modeling Approaches for Distributed Contested Logistics. American Journal of Operations Research, 15, 125-145. doi: ...

CENIEH co-leads a pioneering study that, for the first time, applies hyperspectral imaging to effectively discriminate rock blocks, sediment ...

I’ve been conducting a large-scale bibliometric study on publicly available Chinese academic literature related to hacking and crashing Western power grids. In this article, I’m sharing the main ...

Deep-learning reconstruction algorithms clarify low-dose CT or limited-echo MRI data so sharply that technologists can ...

Principal Subspace Analysis (PSA)—and its sibling, Principal Component Analysis (PCA)—is one of the most popular approaches for dimensionality reduction in signal processing and machine learning. But ...

Aim This study evaluates if characteristics (eg, location, size, volume) of clusters of defects on an initial visual field ...