Search alternatives:
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
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781
Dataset with steel insert.
Published 2024“…It focuses on identifying and quantifying clinically significant materials in the presence of metal objects. …”
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782
Reference dataset.
Published 2024“…It focuses on identifying and quantifying clinically significant materials in the presence of metal objects. …”
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783
Dataset with aluminium insert.
Published 2024“…It focuses on identifying and quantifying clinically significant materials in the presence of metal objects. …”
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784
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785
LSTM model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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786
CNN model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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787
Ceramic bearings.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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788
Geometric contact arc length model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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789
Indentation fracture mechanics model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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790
Grinding particle cutting machining model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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791
Three stages of abrasive cutting process.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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792
CNN-LSTM action recognition process.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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793
Grid division diagram.
Published 2025“…Between the second and third sand-blocking fences, when the height of sand-blocking fence is 2.5m, the increase of wind speed is 13.87% lower than that of 2m height. The decrease is the largest, and sand particles are easy to deposit here in large quantities. …”
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794
Model calculation diagram.
Published 2025“…Between the second and third sand-blocking fences, when the height of sand-blocking fence is 2.5m, the increase of wind speed is 13.87% lower than that of 2m height. The decrease is the largest, and sand particles are easy to deposit here in large quantities. …”
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795
Grid independence verification.
Published 2025“…Between the second and third sand-blocking fences, when the height of sand-blocking fence is 2.5m, the increase of wind speed is 13.87% lower than that of 2m height. The decrease is the largest, and sand particles are easy to deposit here in large quantities. …”
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796
Differences in magnitude and velocity of decay of the different compartments of the viral reservoir.
Published 2025“…<p>A. The overall decrease in each fraction of the viral reservoir during the first year after ART initiation is expressed as the ratio of week 48 to baseline values. …”
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797
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798
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799
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800
Mean parameter values for the selected crops.
Published 2025“…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”