Abstract
AI-native sixth-generation (6G) infrastructure will increasingly execute network, commercial and public-service actions through autonomous agents distributed across terminals, edges and clouds. Yet a conventional digital signature can authenticate a message without proving that the message was produced under a...
Murali Krishna Pasupuleti· International Journal of Aca...· 0 citations
Every finite bipartite simple graph occurs as a vertex-induced unrooted subgraph of the principal graph of an irreducible finite-depth inclusion of hyperfinite type II1 factors. For part sizes m and n, an explicit neighborhood-multiplicity parameter q gives index q3^n, with q at most m+1, and depth at most four. The se...
Alper Ferudun· Zenodo (CERN European Organi...· 0 citations
Abstract This dataset and software repository presents the formal implementation and theoretical framework of the Slot-Based Technical Taxonomy Model (N-Slot Engine). Evolving from a baseline 3-slot architecture (Header + Core + Modifier), this framework introduces deterministic 6-slot and 9-slot positional grammar sch...
Donald Sobaski· Zenodo (CERN European Organi...· 0 citations
Abstract This dataset and software repository presents the formal implementation and theoretical framework of the Slot-Based Technical Taxonomy Model (N-Slot Engine). Evolving from a baseline 3-slot architecture (Header + Core + Modifier), this framework introduces deterministic 6-slot and 9-slot positional grammar sch...
Donald Sobaski· Zenodo (CERN European Organi...· 0 citations
Every finite bipartite simple graph occurs as a vertex-induced unrooted subgraph of the principal graph of an irreducible finite-depth inclusion of hyperfinite type II1 factors. For part sizes m and n, an explicit neighborhood-multiplicity parameter q gives index q3^n, with q at most m+1, and depth at most four. The se...
Alper Ferudun· Zenodo (CERN European Organi...· 0 citations
To address governance bottlenecks such as data silos and fragmented monitoring in the implementation of the "Ten Networks" strategy in Xinjiang's Kezhou Prefecture, and to facilitate digital transformation in border regions, this paper conducts research on multi-network data integration, geographic information mapping,...
Qianfang Lei, Zhenghui Yang, Yahong Zhang· Third International Conferen...· 0 citations
The convergence of artificial intelligence (AI) and the Internet of Things (IoT) is increasing interest in how intelligence is distributed across cloud, edge, fog, and device layers. This study maps the 2020-2026 development of cloud-linked AI-IoT research using Scopus metadata. The reported Scopus query required AI or...
Osman Diriye Hussein, Adam Muhudin, Mohamed Abdirahman Addow et al.· Zenodo (CERN European Organi...· 0 citations
Special emphasis is placed on the concept of explainable AI, human in the loop decision making, risk based asset prioritization and ongoing model validation as ways to provide public accountability and reliability in critical infrastructure sectors.
Marjan Sultana Nuha· Journal of Artificial Intell...· 0 citations
Abstract: Climate-resilient smart cities require sensing infrastructures that can detect weak, rapidly evolving environmental signals, infer actionable risk locally, and remain trustworthy under both cyber disruption and emerging quantum threats. This paper develops a model-based architecture for Quantum-Secure Photoni...
Murali Krishna Pasupuleti· International Journal of Aca...· 0 citations
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
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.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
