A mysterious signal, a missing container, and a new breed of threat that strikes and vanishes before tools can react: how a ...

Learn how GraphRAG transforms unstructured text into structured data, revolutionizing AI retrieval with deeper insights and connections.

Alireza Doostan is leading a major effort for real-time data compression for supercomputer research. A professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the ...

1) A compressed sensing-based electricity consumption data compression and synchronous encryption algorithm is proposed. The algorithm effectively leverages the sparse characteristics of voltage and ...

Research in graph signal processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper, we first provide an overview of core ideas in GSP and their ...

In situ 1D NMR spectroscopic reaction monitoring allows detailed investigation of chemical kinetics and mechanism. Concentration versus time data are derived from a time series of NMR spectra. Each ...

In applications such as social, energy, transportation, sensor, and neuronal networks, high-dimensional data naturally reside on the vertices of weighted graphs. The emerging field of signal ...

Many scientific simulations and experiments generate terabytes to petabytes of data daily, necessitating data compression techniques. Unlike video and image compression, scientists require methods ...