Skip to content

Category

edge computing

2,653 papers

#edge computing Open access Sep 2026

Technical Treatise on Morphological Quantum Medicine and Agronomy: An Inversion of Biological Paradigms via Bioresorbable Vogel-Spiral (N=55) Nanoprostheses and Topological Phase-Matching

This treatise introduces a non-invasive, universal quantum-biological framework designed to reverse structural macromolecular mutations and pathogens across human, veterinary, and agronomic systems through the deployment of temporary, bioresorbable inorganic nanoprostheses. Traditional quantum biology remains bottlenec...

Yaron Admon Hefetz · 0 citations
#edge computing Open access Sep 2026

Technical Treatise on Morphological Quantum Medicine and Agronomy: An Inversion of Biological Paradigms via Bioresorbable Vogel-Spiral (N=55) Nanoprostheses and Topological Phase-Matching

This treatise introduces a non-invasive, universal quantum-biological framework designed to reverse structural macromolecular mutations and pathogens across human, veterinary, and agronomic systems through the deployment of temporary, bioresorbable inorganic nanoprostheses. Traditional quantum biology remains bottlenec...

Yaron Admon Hefetz · 0 citations
#artificial intelligence Book Open access Sep 2026

KI - Quo vadis? Von ChatGPT über neuronale Netze zu neuromorpher KI

Praktisch nutzbare Künstliche Intelligenz entstand aus dem Bündnis kluger Köpfe mit den rechentechnischen Fähigkeiten Boolescher Automaten – natürliche Intelligenz dagegen aus Selbstorganisation und Evolution. Dieser zweite Weg rückt mit dem neuromorphen Rechnen zunehmend wieder in das Blickfeld von Wissenschaft und Pr...

Volker Kempe · 0 citations
#explainable ai Open access Sep 2026

Exact contextuality gaps for graphs up to eleven vertices: certified maximizers and the algebraic degrees of the landscape

New in v2.5. At eight vertices three independent enumerations — the per-graph file published with arXiv:2605.12828, the 2012 Amselem–Danielsen–López-Tarrida–Portillo database, and this sweep — give the same 498 graphs, identical as graph6 strings, with zero disagreement on the independence number across all 11 117 grap...

Artem Oktiabrev · 0 citations
#federated learning Open access Sep 2026

FedQS: asynchronous federated learning based on queue scheduling

An asynchronous framework named FedQS, which employs a multi-dimensional staleness evaluation mechanism that dynamically assesses updates by combining the similarity between local and global models with client latency metrics, and implements a decoupling solution via a queue scheduling algorithm to resolve the coupling...

Jia-Hui Zhou, Fang Li, Tian-Yu Shi et al. · 0 citations
#federated learning Open access Sep 2026

Joao Ferreira project done at ISCTE IoT Laboratory

João Carlos Amaro Ferreira (ISCTE-IUL, 16/07/2021), showcasing the research group's work in IoT, edge/fog computing, and data science. The group has expertise in edge/fog architectures (open-source and commercial platforms), IoT communications (short and long range, lightweight protocols such as MQTT/CoAP, V2X), and di...

João C. Ferreira · 0 citations
#federated learning Open access Sep 2026

Joao Ferreira project done at ISCTE IoT Laboratory

João Carlos Amaro Ferreira (ISCTE-IUL, 16/07/2021), showcasing the research group's work in IoT, edge/fog computing, and data science. The group has expertise in edge/fog architectures (open-source and commercial platforms), IoT communications (short and long range, lightweight protocols such as MQTT/CoAP, V2X), and di...

João C. Ferreira · 0 citations
#graph neural networks Open access Sep 2026

LibXSub: A Framework for Detecting Binary Third-Party Library Reuse Regions Based on Explanatory Subgraphs

Binary third-party library detection is a fundamental task in software composition analysis, vulnerability tracing, and software supply chain security. Existing approaches mainly rely on function-level matching or global similarity computation, while paying insufficient attention to region-level reuse structures formed...

Dan Yu, Lu Miao, Rong-Sheng Li et al. · 0 citations
#reinforcement learning Review Nov 2026

Moving target defense in 5G and beyond networks: A comprehensive survey and research directions

This paper presents a deployment-oriented survey of MTD for 5G, with special emphasis on learning-assisted designs that optimize what to mutate, when to mutate, and how to enforce mutation under slice-isolation, URLLC, and orchestration constraints.

Amir Javadpour, Forough Ja'fari, T. Taleb et al. · 0 citations
#edge computing Open access Sep 2026

A Five-Layer IoT-Big Data Architecture for Smart Wastewater Monitoring and Treatment: Design, Integration of Machine Learning, and Deployment Feasibility for Vietnam

ABSTRACT: Industrial and urban wastewater pollution constitutes a critical environmental challenge in Vietnam, where only approximately 12.5% of municipal wastewater currently undergoes adequate treatment before discharge. This paper proposes the Smart Wastewater Monitoring and Treatment (SWMT) framework, a five-layer...

Đỗ Gia Bảo, Nguyễn Tài Tiệp · 0 citations
#edge computing Open access Sep 2026

Phi-Coupled E8 Cascades Drive Hyperbolic Topological Quantum Computing — E8 Intelligence Research

Under the 132 Hz driving tone, the 240 E8 root vectors exhibit a phi‑symmetric eigenvalue flow that simultaneously creates two interlocking sets of topological edge modes on the {5,3,4} hyperbolic lattice. These edge modes lock into a hierarchical cascade where each level amplifies the next by the golden ratio, effecti...

Andrew Stewart Caldin · 0 citations

From tech blogs

See all →
Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.