Abstract Modern enterprise AI systems increasingly operate across multiple authorized data sources, memories, applications, and tools. This creates a security problem that is not adequately described as conventional data theft. An AI workload may be individually authorized to read support records, engineering informati...
Sangam Das· Zenodo (CERN European Organi...· 0 citations
This comprehensive foundational curriculum module examines the cyber-physical systems architecture, state estimation theory, and feedback control loops of modern autonomous systems within the Prep4Uni open STEM curriculum. Core Thematic & Pedagogical Foundations: Systems-Level IDEF0 Functional Modeling: Deconstructs au...
Prep4Uni.Online· Zenodo (CERN European Organi...· 0 citations
Rooftop photovoltaic (PV) generation is a core contributor to zero-carbon parks, but the inverter fleets that produce it are often locked inside a manufacturer’s closed cloud, so the owner cannot freely access, aggregate or audit the data. This paper reports the design and ongoing field deployment of a vendor-independe...
In the context of psychological care for adolescents and safety monitoring for the elderly, traditional emotion monitoring devices face challenges such as low accuracy in single-modal recognition, cloud data leakage, and high hardware costs. This paper designs an emotion recognition system based on artificial intellige...
This study develops a defense-oriented framework for tactical edge-to-military data center workload migration for resilient c5i operations under d-dil conditions within an integrated military C5I environment. The research addresses the engineering problem of maintaining mission information advantage when physical infra...
M. Rizwan Yasin· Zenodo (CERN European Organi...· 0 citations
Paper I of the Guarino Infrastructure Dependency Metric (GIDM). First revision, 20 September 2026. DOI 10.5281/zenodo.22864280. Infrastructure fails in chains. The February 2021 freeze in Texas began at frozen wellheads, ran through load-shed gas processing plants, took 61,800 MW of generation offline, and ended in boi...
Brian Guarino· Zenodo (CERN European Organi...· 0 citations
This study examines real-time monitoring and automatic management of passenger flow on metropolitan escalators using artificial intelligence and computer vision technologies. The aim is to develop the conceptual foundations of an automatic hazard detection system based on deep learning algorithms (CNN, YOLO, transforme...
Humoyun Pardaboyev, Bakhodir Zaripov· Zenodo (CERN European Organi...· 0 citations
For four decades, deep artificial neural networks have relied on continuous vector spaces, dense floating-point General Matrix Multiplications (GEMM: hl+1 = σ(Wlhl + bl)), and gradient-based backpropagation. While effective in data centers, this paradigm incurs severe thermodynamic, memory bandwidth, and numerical stab...
A. Emre Cetin· Zenodo (CERN European Organi...· 0 citations
This paper develops the next foundational layer of the AASC formalism: the exact structure of admissibility once non-degenerate determinate construction has already incurred the kernel roles of Admissibility, Standing, Reference, and Irreversibility. Its central contribution is to distinguish three questions that are o...
Amos Jay Maley· Zenodo (CERN European Organi...· 0 citations
The common refinement of the icosahedral edge shell and its Galois shadow (the great-icosahedron chords) on the sphere is computed exactly: each visible edge crosses exactly one shadow edge, the shadow edges cross each other twenty times, and the refined sphere is the barycentric subdivision of the icosahedron — $V=62$...
Arber Gishto· Zenodo (CERN European Organi...· 2 citations
Integration of Internet of Things (IoT) and Edge Computing (EC) presents significant challenges, particularly in guaranteeing secure communication amid IoT devices and cloud systems formerly to data aggregation. Existing aggregation schemes often compromise on cost-effectiveness while struggling to preserve data integr...
R. T. Rajappa, P. S. Periyasamy, K. K. Kanagasabai· Peer-to-Peer Networking and...· 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
