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    Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

    Published 2025-01-01
    “…Anomaly prediction in time series is crucial for ensuring the stability and security of data centers, especially in scientific contexts such as INFN-CNAF, the National Center for Research and Development in Information and Communication Technology of the National Institute for Nuclear Physics. At INFN-CNAF, large volumes of heterogeneous data critical to international experiments are managed using dedicated monitoring systems. …”
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    Non-Destructive Testing by Magnetic Noise Method of the Quality of Heat Treatment of Steel Samples Obtained by Additive Technology by V. N. Busko, A. P. Kren, G. A. Lanzman

    Published 2022-10-01
    “…Compared to the hardness measurement method, which is mainly associated with phase-structural changes, the magnetic noise method due to selectivity to other controlled parameters is additionally sensitive to cast samples (at the same time the microstructures of cast and normalized three-dimensional samples are close to each other according to X-ray data).The magnetic noise method can be used as one of the physical methods for evaluation the quality and control of the heat treatment of 3D samples at the manufacturing stage when testing their types and modes, as well as sorting samples.…”
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