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  • 05.06. Methods  (2)
  • Frontiers  (1)
  • Wiley  (1)
  • Cell Press
  • 2020-2022  (2)
  • 1
    Publication Date: 2021-06-14
    Description: Southwestern Sicily is an area of infrequent seismic activity; however, some studies carried out in the archaeological Selinunte site suggest that, between the fourth century BC and the early Middle Ages, probably at least two earthquakes strucked this area with enough energy to damage and cause the collapse and kinematics of much of the architecture of Selinunte. Take into account that, in 2008, a noninvasive archaeological prospection and traditional data gathering methods along the Acropolis north fortifications were carried out. Following these first studies, after about 10 years, a new geophysical campaign was carried out. This second campaign benefited from the application of modern technologies for the acquisition and processing of the point cloud data on the northern part of the Acropolis, like terrestrial laser scanning and unmanned aerial vehicle photogrammetry. In this paper, we present the application of these techniques and a strategy for their integration for the 3D modelling of buildings and cultural heritages. We show how the integration of data acquired independently by these two techniques is an added value able to overcome the intrinsic limits of the individual techniques. The application to Selinunte's Acropolis allowed it to highlight and measure with high accuracy fractures, dislocation, inclinations of walls, depressions of some areas and other interesting observations, which may be important starting points for future investigations.
    Description: Published
    Description: 153-165
    Description: 2IT. Laboratori analitici e sperimentali
    Description: JCR Journal
    Keywords: 3D reconstruction ; archaeological survey ; digital elevation model ; Selinunte Archaeological Park ; terrestrial laser scanning ; unmanned aerial vehicle photogrammetry ; 05.04. Instrumentation and techniques of general interest ; 04.02. Exploration geophysics ; 05.02. Data dissemination ; 05.06. Methods
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2021-05-03
    Description: We present a skillful deep learning algorithm for supporting quality control of ocean temperature measurements, which we name SalaciaML according to Salacia the roman goddess of sea waters. Classical attempts to algorithmically support and partly automate the quality control of ocean data profiles are especially helpful for the gross errors in the data. Range filters, spike detection, and data distribution checks remove reliably the outliers and errors in the data, still wrong classifications occur. Various automated quality control procedures have been successfully implemented within the main international and EU marine data infrastructures (WOD, CMEMS, IQuOD, SDN) but their resulting data products are still containing data anomalies, bad data flagged as good and vice-versa. They also include visual inspection of suspicious measurements, which is a time consuming activity, especially if the number of suspicious data detected is large. A deep learning approach could highly improve our capabilities to quality assess big data collections and contemporary reducing the human effort. Our algorithm SalaciaML is meant to complement classical automated quality control procedures in supporting the time consuming visually inspection of data anomalies by quality control experts. As a first approach we applied the algorithm to a large dataset from the Mediterranean Sea. SalaciaML has been able to detect correctly more than 90% of all good and/or bad data in 11 out of 16 Mediterranean regions.
    Description: This project has received funding from the European Union Horizon 2020 and Seventh Framework Programmes under grant agreement number 730960 SeaDataCloud.
    Description: Published
    Description: 611742
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Keywords: 05.06. Methods
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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