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  1. (, 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC))
    Machine learning has shown incredibly potential in many fields of application ranging from ChatGPT and Bard to Tesla’s autonomous vehicles. These ML models require vast amounts of data and communications overhead in order to be effective. In this paper we propose a communication-efficient time series forecasting model combining the most recent advancements in MetaFormer architecture implemented across a federated series of learning nodes. The time series prediction performance and communication overhead cost of the distributed model is compared against a similar centralized model and shown to have parity in performance while consuming much lower data rates during training. 
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    Accepted Manuscript Full Text Available
  2. ; ; ; ; ; ; ; ; ; ; et al (, Journal of Instrumentation)
    Abstract The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules.During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb -1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector.Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2.It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%.Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules. 
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    Full Text Available