Showing 1,921 - 1,940 results of 4,206 for search '(( significantly ((teer decrease) OR (mean decrease)) ) OR ( significantly linear decrease ))', query time: 0.40s Refine Results
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    A Comparison of Pediatric Prehospital Opioid Encounters and Social Vulnerability by Stephen Sandelich (19991783)

    Published 2024
    “…The analysis demonstrated that as socioeconomic status (SES) improves, the likelihood of opioid-related activations increases significantly supported by a significant negative linear trend (Estimate = −0.2971, SE = 0.1172, z = −2.54, <i>p</i> = 0.0112. …”
  17. 1937

    Complexity comparison of different models. by Li Yuan (102305)

    Published 2025
    “…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
  18. 1938

    Dynamic window based median filtering algorithm. by Li Yuan (102305)

    Published 2025
    “…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
  19. 1939

    Flow of operation of improved KMA. by Li Yuan (102305)

    Published 2025
    “…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
  20. 1940

    Improved DAE based on LSTM. by Li Yuan (102305)

    Published 2025
    “…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”