يعرض 1 - 20 نتائج من 172 نتيجة بحث عن '(( significantly ((linear decrease) OR (mean decrease)) ) OR ( significant results decrease ))~', وقت الاستعلام: 0.44s تنقيح النتائج
  1. 1
  2. 2

    Baseline patient characteristics. حسب Oscar F. C. van den Bosch (22184246)

    منشور في 2025
    "…Their median baseline variabilities of respiratory rate and tidal volume were 0.19 (IQR: 0.16–0.25) and 0.23 (0.19–0.34), respectively. While mean respiratory rate was not affected, midazolam resulted in a significant decrease in both VRR (ß = −0.071, 95% CI: −0.120 to −0.021) and VTV (ß = −0.117, 95% CI: −0.170 to −0.062). …"
  3. 3
  4. 4
  5. 5

    Volitional control frequency and intensity in VH (Kapsner-Smith et al., 2025) حسب Mara R. Kapsner-Smith (22139315)

    منشور في 2025
    "…Group differences were tested with general linear models.</p><p dir="ltr"><b>Results: </b>No significant differences were found between people with and without HVDs on any of the measures. …"
  6. 6

    Fluctuation trend of the mean temperature index. حسب Chengyuan Hao (21615653)

    منشور في 2025
    "…Secondly, the daily minimum and maximum temperatures increased significantly, which were 0.395°C/10a and 0.200°C/10a respectively<b>—</b>less than the national mean. …"
  7. 7

    Variation curve of the mean temperature index. حسب Chengyuan Hao (21615653)

    منشور في 2025
    "…Secondly, the daily minimum and maximum temperatures increased significantly, which were 0.395°C/10a and 0.200°C/10a respectively<b>—</b>less than the national mean. …"
  8. 8

    Mann-Kendall test for the mean temperature index. حسب Chengyuan Hao (21615653)

    منشور في 2025
    "…Secondly, the daily minimum and maximum temperatures increased significantly, which were 0.395°C/10a and 0.200°C/10a respectively<b>—</b>less than the national mean. …"
  9. 9

    A summary of calibration standards (n = 3). حسب Ewa Paszkowska (21246702)

    منشور في 2025
    "…<div><p>Purpose</p><p>Statins are the most commonly used drugs worldwide. Besides a significant decrease in cardiovascular diseases (CVDs) risk, the use of statins is also connected with a broad beneficial pleiotropic effect. …"
  10. 10

    The observed MRM reactions. حسب Ewa Paszkowska (21246702)

    منشور في 2025
    "…<div><p>Purpose</p><p>Statins are the most commonly used drugs worldwide. Besides a significant decrease in cardiovascular diseases (CVDs) risk, the use of statins is also connected with a broad beneficial pleiotropic effect. …"
  11. 11

    Intra- and inter-day precision and accuracy. حسب Ewa Paszkowska (21246702)

    منشور في 2025
    "…<div><p>Purpose</p><p>Statins are the most commonly used drugs worldwide. Besides a significant decrease in cardiovascular diseases (CVDs) risk, the use of statins is also connected with a broad beneficial pleiotropic effect. …"
  12. 12
  13. 13

    Structure diagram of ensemble model. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  14. 14

    Fitting formula parameter table. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  15. 15

    Test plan. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  16. 16

    Fitting surface parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  17. 17

    Model generalisation validation error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  18. 18

    Empirical model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  19. 19

    Fitting curve parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  20. 20

    Test instrument. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"