A Framework for Real-Time Volcano-Seismic Event Recognition Based on Multi-Station Seismograms and Semantic Segmentation Models

Posted by klaurent Cornell

Kavli Affiliate: Daniel Ralph | First 5 Authors: Camilo Espinosa-Curilem, Camilo Espinosa-Curilem, , , | Summary: In volcano monitoring, effective recognition of seismic events is essential for understanding volcanic activity and raising timely warning alerts. Traditional methods rely on manual analysis, which can be subjective and labor-intensive. Furthermore, current automatic approaches often tackle detection and […]


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Evidence for a shock-compressed magnetic field in the northwestern rim of Vela Jr. from X-ray polarimetry

Posted by dbos MIT

Kavli Affiliate: Herman L. Marshall | First 5 Authors: Dmitry A. Prokhorov, Yi-Jung Yang, Riccardo Ferrazzoli, Jacco Vink, Patrick Slane | Summary: Synchrotron X-ray emission has been detected from nearly a dozen young supernova remnants (SNRs). X-rays of synchrotron origin exhibit linear polarization in a regular, non-randomly oriented magnetic field. The significant polarized X-ray emission […]


Continue.. Evidence for a shock-compressed magnetic field in the northwestern rim of Vela Jr. from X-ray polarimetry

A simple accurate way to model noise-seeded ultrafast nonlinear processes

Posted by klaurent Cornell

Kavli Affiliate: Frank Wise | Summary:Noise can play an important role in nonlinear pulse propagation. It is not only the origin of fluctuations in supercontinuum but can also determine the generated signal amplitude and phase, as seen in phenomena such as noise-seeded four-wave mixing and spontaneous Raman scattering. Current models rely on input-pulse shot noise […]


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EACO-RAG: Towards Distributed Tiered LLM Deployment using Edge-Assisted and Collaborative RAG with Adaptive Knowledge Update

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Jiaxing Li, Chi Xu, Lianchen Jia, Feng Wang, Cong Zhang | Summary: Large language models (LLMs) have demonstrated impressive capabilities in language tasks, but they require high computing power and rely on static knowledge. To overcome these limitations, Retrieval-Augmented Generation (RAG) incorporates up-to-date external information into LLMs […]


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EACO-RAG: Edge-Assisted and Collaborative RAG with Adaptive Knowledge Update

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Jiaxing Li, Chi Xu, Lianchen Jia, Feng Wang, Cong Zhang | Summary: Large Language Models are revolutionizing Web, mobile, and Web of Things systems, driving intelligent and scalable solutions. However, as Retrieval-Augmented Generation (RAG) systems expand, they encounter significant challenges related to scalability, including increased delay and […]


Continue.. EACO-RAG: Edge-Assisted and Collaborative RAG with Adaptive Knowledge Update