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BRIEF RESEARCH REPORT article
Front. Phys.
Sec. Fusion Plasma Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1538107
This article is part of the Research Topic Visualizing Offline and Live Data with AI (VOLDA) Workshop first edition Princeton 11-13th June 2024 View all 6 articles
Automatic location of relevant time slices and patterns in both signals and video-movies: real-time and off-line visualization
Provisionally accepted- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain
Next generation nuclear fusion devices, (for instance ITER), will generate Pbytes of data. To gain knowledge about the nature of thermonuclear plasmas, an in depth analysis of such massive databases is required. Typically, to get statistical relevance in the study of the plasma properties, particular databases around specific plasma events are created. This means their location not only in discharges but also in the corresponding times. In this respect, visualization tools are essential. Of course, manual location of any relevant phenomenology by means of visual analysis is no longer valid. Instead, automatic software based methods are necessary. These methods have to be applied in both real-time and off-line not only for visualization purposes but also for data access. Candidates for their implementation are machine learning techniques.
Keywords: machine learning, visual data analysis, Intelligent data access, pattern recognition, Nuclear Fusion
Received: 02 Dec 2024; Accepted: 02 Apr 2025.
Copyright: © 2025 Vega and Castro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jesús Vega, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain
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