Conventional artificial intelligence architectures built on discrete binary silicon transistors face severe thermal bottlenecks, memory walls, and statistical drift when scaled under edge execution constraints. Recent proposals for quantum wave-unit computing engines and atomic-scale 0.356nm Lab-Grown Diamond (LGD) mem...
David Niedzwiecki Jr· Zenodo (CERN European Organi...· 0 citations
Neural Signed Distance Fields (Neural SDFs) provide compact, continuous, and topologically flexible geometric representations for inverse rendering, generative 3D modeling, and scientific visualization. However, real-time ray casting through neural implicit volumes remains severely constrained by computational cost: un...
A. Emre Cetin· Zenodo (CERN European Organi...· 0 citations
Papers I to III of this series built the buffer group ΠB = Ta/Tx for the edge between two infrastructure nodes, tested it plant by plant on the February 2021 Texas chain, and priced its hours with a cost group ΠC = ca/(vCd), all on one event. This paper reads a second. Winter Storm Elliott, 22 to 26 December 2022, ran...
Brian Guarino· Zenodo (CERN European Organi...· 0 citations
Rubber pump tubing governs the volumetric accuracy of peristaltic infusion pumps, so deviations in inner diameter or wall thickness can alter the delivered dose. Automated optical inspection of such tubing is constrained by two coupled factors: the samples themselves vary geometrically, which injects nuisance variation...
Feng Wang, Yutian Wan, Yaoyao Li et al.· Scientific Reports· 0 citations
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This paper provides a unified and complete characterization of nucleons within the State-Relational Entropy (SRE) dynamic framework: nucleons are stable composite objects emerging from binary self-organizing networks on the tripartite Y-shaped coherent core, constrained by the two-state opening/closing of dormant edges...
Yue Lu· Zenodo (CERN European Organi...· 0 citations
This review critically appraises the literature on the convergence of Internet of Things (IoT) sensing, edge computing and time-series machine learning for precision irrigation, checking predictive soil-moisture forecasting, edge-deployed neural controllers and LoRaWAN telemetry directly against independently published...
Naziru Halilu· Zenodo (CERN European Organi...· 0 citations
This note places on record, before any comparison with data, the magnetic specific heat implied by the icosahedral cluster magnon spectrum, so that a later comparison with the published low-temperature specific heat of the ferromagnetic quasicrystal i-Au65Ga20Gd15 (TC=23 K) and the antiferromagnetic i-Au56In28.5Eu15.5...
Arber Gishto· Zenodo (CERN European Organi...· 2 citations
Background: IoT devices deployed in hospitals, factories, vehicles, and homes are largely unable to defend themselves. Limited compute and power budgets make running a local intrusion detector impractical, even as the traffic these devices generate grows increasingly attractive to attackers. DRL offers a practical alte...
Fuad S. Abu Owaimer, Wesam M. R. Ashour· Israa University Journal for...· 0 citations
The rapid expansion of IoT devices has resulted in a paradigm shift from centralized cloud computing models to highly distributed computing continua that incorporate IoT devices, edge gateways, fog nodes, regional cloudlets, and hyperscale cloud data centers. In this survey, we provide an overview of Edge-Fog-Cloud-IoT...
Patrick Effraim, Micheal Mensah, Bismark Budu· Journal of King Saud Univers...· 0 citations
Automated classification of acute psychological stress from non-invasive wearable electrocardiography (ECG) is a fundamental problem in physiological computing, affective state recognition, and wearable Internet of Medical Things (IoMT). A central barrier to cross-subject generalization is inter-individual baseline het...
Mukesh Yadav· Zenodo (CERN European Organi...· 0 citations
Unlocking WebAssembly: Boost Web App Performance & Security Today's web applications are becoming more like full-featured software platforms. They can process media, perform complex calculations, visualize large datasets, and deliver interactive experiences without requiring traditional desktop installation. With this...
Tina Campbell· Zenodo (CERN European Organi...· 0 citations
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.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026