Showing 141 - 160 results of 7,726 for search '(( significant progress decrease ) OR ( significant ((shape decrease) OR (we decrease)) ))', query time: 0.57s Refine Results
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    Model selection based on best fit. by Angelina Mageni Lutambi (22097223)

    Published 2025
    “…<div><p>Malaria remains a significant public health challenge, particularly among vulnerable populations in high-burden countries like Tanzania. …”
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    Descriptive data for the pBT-child dyads. by Madalina Ciobanu (2504683)

    Published 2025
    “…<div><p>Autism spectrum disorder (ASD) is a condition with growing prevalence that results in significant healthcare spending, reduced parent income, high levels of family stress, and decreased quality of life (QoL). …”
  16. 156

    CFQL-2 descriptive statistics. by Madalina Ciobanu (2504683)

    Published 2025
    “…<div><p>Autism spectrum disorder (ASD) is a condition with growing prevalence that results in significant healthcare spending, reduced parent income, high levels of family stress, and decreased quality of life (QoL). …”
  17. 157

    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. 158

    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.…”
  19. 159

    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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