يعرض 1 - 20 نتائج من 48 نتيجة بحث عن '(( significant decrease decrease ) OR ( significant ((inter decrease) OR (mean decrease)) ))~', وقت الاستعلام: 0.40s تنقيح النتائج
  1. 1

    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. …"
  2. 2
  3. 3
  4. 4

    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. …"
  5. 5

    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. …"
  6. 6
  7. 7

    Sensitivity analysis for inter-shift subscale. حسب Rong Pi (21743379)

    منشور في 2025
    "…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …"
  8. 8

    Group-level narrow- and broad-band spectral changes after hemispherotomy reveal a marked EEG slowing of the isolated cortex, robust across patients. حسب Michele Angelo Colombo (22446342)

    منشور في 2025
    "…The shaded area indicates the bootstrapped 95% confidence interval for the geometric mean across participants. <b>(B)</b> The PSD in the Slow Delta band (0.5–2 Hz) was significantly larger in the disconnected (Discon) than in the contralateral (Contra) cortex, only in the session after surgery. …"
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13

    Characteristics of included studies. حسب Rong Pi (21743379)

    منشور في 2025
    "…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …"
  14. 14

    Sensitivity analysis for acute fatigue subscale. حسب Rong Pi (21743379)

    منشور في 2025
    "…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …"
  15. 15

    Factors related to nurses’ occupational fatigue. حسب Rong Pi (21743379)

    منشور في 2025
    "…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …"
  16. 16

    The overall framework of CARAFE. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"
  17. 17

    KPD-YOLOv7-GD network structure diagram. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"
  18. 18

    Comparison experiment of accuracy improvement. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"
  19. 19

    Comparison of different pruning rates. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"
  20. 20

    Comparison of experimental results at ablation. حسب Zhongjian Xie (4633099)

    منشور في 2025
    "…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"