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

“…As a result, the improved model effectively increases signal recognition accuracy, enhances model robustness, and significantly reduces computational complexity while ensuring real-time signal processing for communication computing.…”

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

“…As a result, the improved model effectively increases signal recognition accuracy, enhances model robustness, and significantly reduces computational complexity while ensuring real-time signal processing for communication computing.…”

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

“…As a result, the improved model effectively increases signal recognition accuracy, enhances model robustness, and significantly reduces computational complexity while ensuring real-time signal processing for communication computing.…”

Autoencoder structure. by Li Yuan (102305)

“…As a result, the improved model effectively increases signal recognition accuracy, enhances model robustness, and significantly reduces computational complexity while ensuring real-time signal processing for communication computing.…”

Flow chart of research object screening. by Wenyao Xie (21567889)

“…</p><p>Conclusion</p><p>This study systematically reveals for the first time the association between male sex hormone levels and ALI and the moderating effect of cancer status. …”

Top predictive variables for KDIGO stage ≥ 3 identified by the final Random Forest model. by Julian Müller-Kühnle (22265248)

Algorithm training accuracy experiments. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Repeat the detection experiment. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Detection network structure with IRAU [34]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Ablation experiments of various block. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Kappa coefficients for different algorithms. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of ASPP+ block. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of attention gate block [31]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

DSC block and its application network structure. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of multi-scale residual block [30]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of IRAU and Res2Net+ block [22]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Study sample. by Nipaporn Butsing (19470003)

“…One increased National Institute of Health Stroke Scale (NIHSS) score decreased adjusted BI scores by 3.6.</p><p>Conclusion</p><p>The time after discharge, gender, stroke subtype, and stroke severity are significant factors affecting functional outcomes after a stroke. …”

Manuscript data. by Khalid A. Al-Gaadi (2826632)

“…Moreover, the total tomato fruit yield also decreased significantly at salinity-3 compared to salinity-1.…”

Baseline characteristics of participants. by Mei Zhou (269746)

“…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …”

The framework diagram of this study. by Mei Zhou (269746)

“…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …”