Showing 101 - 120 results of 2,283 for search '(( significantly larger decrease ) OR ( significant ((shape decrease) OR (small decrease)) ))', query time: 0.67s Refine Results
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    Actual measurement of shape errors. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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    Technical properties of tested UASs. by Marc Roswag (20598443)

    Published 2025
    “…Our results support this hypothesis, because multicopter flights have a highly significant negative impact on bat activity levels with a medium effect size, particularly for the Myotini (<i>P</i> < 0.001, <i>d</i><sub><i>m</i></sub> = 0.54) and Nyctaloid group (<i>P</i> < 0.001, <i>d</i><sub><i>n</i></sub> = 0.55) and a small effect size for the Pipistrelloid group (<i>P</i> < 0.001, <i>d</i><sub><i>p</i></sub> = 0.36). …”
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    Comprehensive prediction process of shape errors. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  18. 118

    Shape error manual calculation process. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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    Shape error measurement results statistics. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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