From the 1 of 14 linked papers with an AI index.
14 papers
Branching random walk in random environment
Xinxin Chen, Chenlin Gu, Zhiqi Zhao
We consider a branching random walk on \(\Z^d\) in a random environment given by Bernoulli site percolation with parameter \(p\in (0,1)\). In this model, each particle located at a…
OSNR/GSNR Prediction in Brownfield Links via a DLM-Anchored Hybrid Physics/ML Model
Agastya Raj, Venkata Virajit Garbhapu, Hiroyuki Ishihara +5
The paper proposes a hybrid physics‑based and machine‑learning model anchored by a digital line model (DLM) to accurately predict per‑channel power, OSNR, and GSNR in existing (bro…
Fully Unsupervised Detection of Physical Contacts on Subsea Cables via State-of-Polarization Monitoring
Agastya Raj, Alvaro Doval, Tian Tian +2
We present a fully unsupervised Fast-Slow DSVDD detector for continuous State-of-Polarization monitoring on a deployed subsea cable. Trained without event labels, it ranks all five…
DAS-AIS Association Patterns for Vessel Monitoring on an Operational Subsea Fibre Link
Tian Tian, Agastya Raj, Lara Flanagan +4
We present a case study on the Emerald Fibre Bridge Link, an operational subsea telecom cable connecting Dublin and North Wales, examining DAS vessel-related signatures jointly wit…
Sea-Scan: High-Accuracy, ML-based Dark Vessel Detection and Localisation via Weakly Supervised DAS Monitoring
Tian Tian, Agastya Raj, Lara Flanagan +2
We present an ML-based vessel detection and localization system, trained with weak supervision from imperfect AIS labels, that achieves a 97.8% detection rate at 1.98% false-trigge…
Deep Learning Based Multi-Step Channel Prediction for Adaptive Underwater Acoustic OFDM Systems
Tian Tian, Ying Zhang, Agastya Raj +2
We develop an adaptive OFDM framework for underwater acoustic communications based on PatchCSI-T, a Transformer-based multistep channel prediction model with feature-independent mo…