Showing 1 - 20 results of 134 for search '(( like ((step decrease) OR (nn decrease)) ) OR ( ai ((larger decrease) OR (marked decrease)) ))', query time: 0.36s Refine Results
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    Results of Multiple Linear Regression. by Benjamin S. Killen (22766029)

    Published 2025
    “…Walk ratio was decreased in the sloped gravel conditions. Cadence and step length changes explained 95–99% of the variance in gait speed changes across conditions with step length being more heavily weighted across conditions. …”
  15. 15

    Spatiotemporal Gait Parameters Across Terrains. by Benjamin S. Killen (22766029)

    Published 2025
    “…Walk ratio was decreased in the sloped gravel conditions. Cadence and step length changes explained 95–99% of the variance in gait speed changes across conditions with step length being more heavily weighted across conditions. …”
  16. 16

    Participant Demographic Information. by Benjamin S. Killen (22766029)

    Published 2025
    “…Walk ratio was decreased in the sloped gravel conditions. Cadence and step length changes explained 95–99% of the variance in gait speed changes across conditions with step length being more heavily weighted across conditions. …”
  17. 17

    Grouping codes according to drivers and themes. by Jennie Ochshorn (21300213)

    Published 2025
    “…All approaches offer an automated component as the first step (a mobile app) and either an in-person, virtual reality (VR), or video telehealth session as the second step. …”
  18. 18

    Intervention models and descriptions. by Jennie Ochshorn (21300213)

    Published 2025
    “…All approaches offer an automated component as the first step (a mobile app) and either an in-person, virtual reality (VR), or video telehealth session as the second step. …”
  19. 19

    Definitions of drivers and within context. by Jennie Ochshorn (21300213)

    Published 2025
    “…All approaches offer an automated component as the first step (a mobile app) and either an in-person, virtual reality (VR), or video telehealth session as the second step. …”
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    A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

    Published 2025
    “…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”