Showing 1 - 20 results of 211 for search '(( significant increase decrease ) OR ( significant bins decrease ))~', query time: 0.50s Refine Results
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    Soil disturbance cross-sectional model. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    Test plan table. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    Gas jet subsoiling model. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    Schematic diagram of the airflow passage. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    Variation in soil penetration resistance. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    Supersonic gas jet subsoiler experiment. by Xia Li (14984)

    Published 2025
    “…Furthermore, the subsoiling effect was further improved as the working speed decreased and the frequency of air blasts increased, satisfying the subsoiling operation assessment standards. …”
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    R project including metadata update. by Frederik Stein (22146203)

    Published 2025
    “…<div><p>The increasing number of Barcode of Life Database (BOLD) records per species and genus leads to contradictory species assignments within Barcode Index Numbers (BINs), serving as identifiers for the BOLD ID engine. …”
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    Classes of errors and gaps in BOLD metadata. by Frederik Stein (22146203)

    Published 2025
    “…<div><p>The increasing number of Barcode of Life Database (BOLD) records per species and genus leads to contradictory species assignments within Barcode Index Numbers (BINs), serving as identifiers for the BOLD ID engine. …”
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    Evaluation results. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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    Dataset with steel insert. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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    Reference dataset. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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    Dataset with aluminium insert. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”