Recent advances in artificial intelligence (AI) and intelligent algorithms have promoted the shift of object detection from cloud-based processing to real-time local perception on edge devices. To address the challenges of scale variation, occlusion interference, complex backgrounds and limited edge computing resources...
Deprecated Python below 3.11 is compatibility, not support. The floor becomes 3.11 in 0.2.0 (3.10 reaches end of life in October 2026). Nothing changes within 0.1.x; CI keeps running on every version the package still declares. Fixed RetryPolicy.backoff_for no longer raises OverflowError past attempt ~1024. 2 ** attemp...
Fernando Aporta Franco· Zenodo (CERN European Organi...· 0 citations
The non-proprietary part of the reproducibility package of the paper: 191 computation logs, which contain the log sources of the computed values reported in the paper and also retain earlier and control runs; the 30 tables of the paper as comma-separated values; SHA-256 indexes of the logs; three checks that run on the...
Arkady Khorunzhenko, V. K. Gusyakov, V. P. Ilyin et al.· Zenodo (CERN European Organi...· 0 citations
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A Universal, Options-Free, One-Byte Market-State Primitive (v2 — with a hardened bond-volatility addendum) Randolph James Ferlic, M.D., and Kimberly Kate Ferlic (Fieldstone Analytics, LLC). Version 2, Zenodo, CC-BY 4.0. v1 DOI 10.5281/zenodo.22116173. Version 2 note. This version adds a short addendum that deepens the...
Randolph James Ferlic, Kimberly Kate Ferlic· Zenodo (CERN European Organi...· 0 citations
AbstractTT-DAV §23.14 found that its gauge-independent defect-insertion outer-loop holonomy, evaluated on a sample of 300 edge-pair configurations, is exactly determined in its SUPPORT by the §23.10 (k1,k2) transport class — class (1,4) configurations produce only {0°,120°,144°}, class (2,3) only {72°,144°} — butnot in...
Daniel Andrés Chillemi· Zenodo (CERN European Organi...· 0 citations
The theoretical framework developed in P1-P5 requires computational infrastructure to make ultrametric (p-adic) analysis accessible to experimentalists. We specify and deploy an ultrametric discovery engine — a Cloudflare Worker implementing 20 principles from the proven Ask QWAV production system. The Worker provides...
QNFO Research Agent, Rowan Brad Quni-Gudzinas· Zenodo (CERN European Organi...· 0 citations
This version introduces the expanded physical testbed dataset (>148,000 telemetry records across 66 independent hardware runs) executed on live ESP32 microcontroller nodes and a Raspberry Pi edge gateway. Version 5.0 validates the TinyOLAF closed-loop edge AI framework across nominal baselines, concurrent network conte...
Haranath Rakshit, Subhasis Banerjee, Avishek Nandi et al.· Zenodo (CERN European Organi...· 0 citations
Background: In computed tomography (CT), the spot geometry is one of the main sources of error in CT images. Since X-rays do not arise from a point source, artefacts are produced. In particular there is a penumbra effect, leading to poorly defined edges within a reconstructed volume. Penumbra models can be simulated gi...
Audrey Kueh, J. W. Warnett, Gregory J. Gibbons et al.· Warwick Research Archive Por...· 0 citations
Background: Chronic disease management, an ageing global population, and the aftermath of the COVID-19 pandemic have pushed real-time, continuous health monitoring from a research curiosity toward routine clinical practice. Artificial intelligence (AI), the Internet of Medical Things (IoMT), edge computing, and next-ge...
Modern Cyber-Physical Systems (CPS) demand high computational capability, strong security guarantees, and energy-aware operation, particularly in embedded, mobile, and autonomous platforms such as robotics, intelligent vehicles, and industrial controllers. Addressing these requirements calls for heterogeneous System-on...
With the rapid advancement and deep integration of the Internet of Things (IoT) and 5G technologies, mobile edge computing (MEC) has undertaken an increasingly important role in enhancing service quality. Leveraging their high mobility and flexible deployment, unmannedaerial vehicles (UAVs) extend MEC services to chall...
Zhao Tong, Shi-Yan Zhang, Jing Mei et al.· IEEE Transactions on Mobile...· 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
