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edge computing

2,571 papers

#edge computing Dataset Open access Sep 2026

Data, figures and code for: A single oscillator response sets the exponents of synchronization transitions

Changes in v1.0.7. Two faults in the cavity figure, both found on the page. The near lower corner of the box at the far end was missing, and with it about a sixth of the front lower edge. The two panels of that figure are each wider and taller than the drawing they hold, which is what lets a long flat cavity and a cone...

Tanvir Mahmud Mahim, M. Mosaddequr Rahman, Abu S. M. Mohsin · 0 citations
#edge computing Open access Sep 2026

A spatial dataset for identifying disadvantaged communities facing cumulative climate and economic burdens in the United States

Abstract The Climate and Economic Justice Screening Tool (CEJST) was developed by the U.S. federal government in 2021 to identify and support marginalized communities disproportionately impacted by climate change. This tool identifies disadvantaged communities based on the presence of low-income residents and one of ei...

Jayajit Chakraborty, Haylee Oyler, Kat Le et al. · 0 citations
#diffusion models Open access Sep 2026

Renaissance: The Sovereign Physical Intelligence via Resonance Plexus Framework

Technical White Paper v1.5 | Document ID: QN-RP-2026-V1.5 Affiliation: QuantNature Global (https://www.quantnature.com)Release Date: September 11, 2026 Executive Summary This white paper presents the Resonance Plexus (RP v1.5), a novel non-symbolic physical intelligence framework designed to overcome the structural bri...

QuantNature Global · 0 citations
#edge computing Open access Sep 2026

ROMS-Tools: Reproducible Preprocessing and Analysis for Regional Ocean Modeling with ROMS

Breaking Changes BoundaryForcing is now a wrapper over multiple constituent sources; the previous single-source class is available as BoundaryForcingSource. The wrapper takes the physics dataset as source plus a list of bgc_sources, exposes the constituent objects as .physics and .bgc (a list), and does not accept type...

Nora Loose, Tom Nicholas, ubbu36 et al. · 0 citations
#edge computing Open access Sep 2026

NSF Cybertraining 2026 Poster for OAC-2306184 by Tong Shu

With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. While this evolution has been largely supported by the rapid improvements in advanced GPU cyberinfrastructure, comprehensive training materials are generally...

Tong Shu · 0 citations
#edge computing Open access Sep 2026

NSF-Cybertraining-2026-Poster_OAC2306184_TongShu

With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. While this evolution has been largely supported by the rapid improvements in advanced GPU cyberinfrastructure, comprehensive training materials are generally...

Tong Shu · 0 citations
#edge computing Open access Sep 2026

CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure

With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. While this evolution has been largely supported by the rapid improvements in advanced GPU cyberinfrastructure, comprehensive training materials are generally...

Tong Shu · 0 citations
#edge computing Open access Sep 2026

Peer Review Report For: Chromatic Number of Bipolar Intuitionistic Fuzzy Graphs [version 1; peer review: 1 approved]

Background Bipolar intuitionistic fuzzy graphs (BIFGs) extend fuzzy graphs by assigning both positive and negative membership and non-membership degrees to vertices and edges, capturing more nuanced uncertainty. The chromatic number of a BIFG, unlike that of crisp graphs, depends on the interplay of these bipolar param...

Fikadu Tesgera Tolasa, V.N.Srinivasa Rao Repalle, Gamachu Adugna Ganati et al. · 0 citations
#edge computing Open access Sep 2026

NSF Cybertraining 2026 Poster for OAC 2306184 by Tong Shu

With the recent advancements in artificial intelligence, deep learning systems and applications have become a driving force in multiple transdisciplinary domains. While this evolution has been largely supported by the rapid improvements in advanced GPU cyberinfrastructure, comprehensive training materials are generally...

Tong Shu · 0 citations
#edge computing Open access Sep 2026

The Law of Action: Behavioural Choice on Three Axes, and Its Domain of Definition

Abstract Given the state of a subject and the state of the environment he is in, under what conditions does the question "what should be done next" have a determinate answer, and where does that answer lie. This paper gives a computable form and marks out its domain of definition. First, location on three axes. The sta...

Qinfu Li · 0 citations
#edge computing Open access Sep 2026

AV-IMAP (Agrivoltaic Irradiance Mapping and Analysis Platform): A Numerical Framework for Canopy-Top Irradiance Mapping and Edge-Effect Analysis in Finite Agrivoltaic Systems

The AV-IMAP Simulator is a MATLAB-based computational tool for evaluating solar irradiance and shading characteristics of agrivoltaic (AV) panel configurations. The model is developed to compute the spatial and temporal distribution of direct, diffuse, total ground irradiance beneath photovoltaic (PV) arrays, and AV an...

Saad Mahbub Chowdhury, Noor Mohammed Naushad, M. Ryyan Khan · 0 citations
#edge computing Open access Sep 2026

Technical White Paper: Super RTO Architecture for Resilient Infrastructure & AI Governance

Author: Yoko Hasebe (Iwakuni, Yamaguchi, Japan) Date: September 2026 Classification: Open Architecture Specification & Technical White Paper Abstract: Modern cyber-physical infrastructure—encompassing power grids, telecommunications, and distributed energy resources (DERs)—is increasingly interfacing with frontier AI i...

洋子 Hasebe · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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