arXiv Machine Learning By Saeid Jamshidi, Omar Abdul Wahab, Rolando Herrero, Foutse Khomh

Securing Time Integrity in Energy IoT Against Clock Drift and Y2K38 Failures

Read the original on arXiv Machine Learning →

arXiv:2601. 23147v2 Announce Type: replace Abstract: The integrity of time in distributed Internet of Things (IoT) devices is crucial for reliable operation in energy cyber-physical systems, such as smart grids and microgrids.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Aug 11

An Explainable GNN Framework for Component-Level Anomaly Diagnosis

arXiv:2608. 09246v1 Announce Type: new Abstract: Industrial processes are complex systems composed of multiple interacting sensors that generate multivariate time series (MTS).

By Sena Ozgunay (IMT, ANITI, LAAS-DISCO, LAAS, Comue de Toulouse), Louise Trav\'e-Massuy\`es (LAAS-DISCO, Comue de Toulouse, ANITI), Jean-Michel Loubes (IMT, REGALIA), Raul Sena Ferreira (LAAS)