Showing 6,141 - 6,160 results of 18,439 for search 'significantly ((((((less decrease) OR (largest decrease))) OR (mean decrease))) OR (a decrease))', query time: 0.64s Refine Results
  1. 6141

    Dimensions of FSW Tool. by Shaheer Ahmed Khan (17797647)

    Published 2025
    “…The joint efficiency of polymer is significantly improved as a result of the effective heat distribution and fusion during the welding. …”
  2. 6142

    Fabricated Fixture with labelled view. by Shaheer Ahmed Khan (17797647)

    Published 2025
    “…The joint efficiency of polymer is significantly improved as a result of the effective heat distribution and fusion during the welding. …”
  3. 6143

    Dog-bone specimens after tensile testing. by Shaheer Ahmed Khan (17797647)

    Published 2025
    “…The joint efficiency of polymer is significantly improved as a result of the effective heat distribution and fusion during the welding. …”
  4. 6144

    Dog-bone specimens before tensile testing. by Shaheer Ahmed Khan (17797647)

    Published 2025
    “…The joint efficiency of polymer is significantly improved as a result of the effective heat distribution and fusion during the welding. …”
  5. 6145

    Experimental run of FSW on CNC milling machine. by Shaheer Ahmed Khan (17797647)

    Published 2025
    “…The joint efficiency of polymer is significantly improved as a result of the effective heat distribution and fusion during the welding. …”
  6. 6146

    Scheme of the SiTFarm tool–farm to sector level. by Jure Brečko (20314959)

    Published 2024
    “…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”
  7. 6147

    S1 File - by Jure Brečko (20314959)

    Published 2024
    “…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”
  8. 6148

    GHG emissions in TAHs. by Jure Brečko (20314959)

    Published 2024
    “…However, the variability is significant, with a coefficient of variation 0.74. Only 25% of farms exceeded 17.15 €/h, while 25% did not surpass 4.46 €/h. …”
  9. 6149

    Variation law of UCS. by Wenyu Lv (20139458)

    Published 2025
    “…Notably, the attenuation constant λ follows a monotonically decreasing pattern with increasing loading rate. …”
  10. 6150

    Detail of the personalized-enhanced GCN. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  11. 6151

    Enhanced multi-component module. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  12. 6152

    The architecture of the TCBiL. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  13. 6153

    Detail of the encoder. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  14. 6154

    Detail of the Fourier transform. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  15. 6155

    Detail of the decoder. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  16. 6156

    Encoder-decoder architecture. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  17. 6157

    Dataset description. by Yuanming Ding (12842858)

    Published 2025
    “…The model achieves a significant enhancement in prediction accuracy through the introduction of the attention-based Personalized-enhanced Fusion Graph Convolutional Network (aPFGCN) and the Temporal Convolutional Bidirectional Long Short-Term Memory (TCBiL) module. …”
  18. 6158

    Study design. by Moazzam Tanveer (20775814)

    Published 2025
    “…<div><p>Background</p><p>Childhood obesity poses a significant public health challenge, yet effective school-based physical activity (PA) interventions remain scarce, especially in Pakistan. …”
  19. 6159

    Prevaelnce of different pathogens by location. by Amete Mihret Teshale (12072758)

    Published 2025
    “…<div><p>Diarrheal illness remains a major global health challenge, causing millions of deaths annually. …”
  20. 6160

    Frontier Analysis Based on ASDR and SDI. by Guanghui Yu (423945)

    Published 2025
    “…<div><p>Background and Objectives</p><p>Hypertension is a major risk factor for aortic aneurysm (AA), but the global, regional, and national patterns of its related disease burden are not well studied. …”