The dynamic nature of thermal processes means that predictive algorithms are an obvious choice for controlling processes of this type. Unfortunately, the product variability commonly found in real-world processes forces changes in the operating point. This, in turn, forces changes in the controller settings. Unfortunat...
G. Malanowski, Malgorzata Michalczyk, Tomasz Klopot· Advances in Science and Tech...· 0 citations
As Satellite Edge Computing (SEC) emerges as a computing backbone of 6 G IoT, its feasibility is threatened by frequent handovers that disrupt task continuity and cause deadline violations in AI-driven workloads. Conventional communication-centric handover strategies overlook the urgency of computational tasks, further...
Chuxing Fang, Changqiao Xu, Zitong Li et al.· IEEE Transactions on Mobile...· 0 citations
Large language models (LLMs) are increasingly deployed in edge computing environments to reduce latency and preserve privacy. However, their inference process presents fundamental challenges for resource-constrained IoT devices. LLM inference involves computationally asymmetric stages: parallelizable prompt processing...
Xingyu Feng, Huanqi Yang, Zhuangzhuang Chen et al.· IEEE Transactions on Mobile...· 0 citations
Blockchain-enabled mobile edge computing (MEC) must jointly optimize task offloading and consensus finality under highly heterogeneous AIoT devices, where latency/energy constraints and fairness-sensitive incentives coexist with time-varying validator reliability. We propose FE-CTDE, a unified framework that couples (1...
Libo Feng, Chen-Xi Wang, Zhenli He et al.· IEEE Transactions on Mobile...· 2 citations
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An efficient, balanced state discovery heuristic algorithm that will discover the nearest balanced state for any size of the graph network and approximate the frustration of the network is proposed.
Muhieddine Shebaro, Jelena Tešić· Journal of Computer Science· 1 citation
The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluat...
Jaswanth Garugu· International Journal for Re...· 0 citations
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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.
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