Search alternatives:
larger decrease » marked decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
larger decrease » marked decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
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The Effect of Confinement on the Phase Behavior of <i>n</i>‑Pentane in Nanoporous Media: An Experimental Investigation at Varying Pore Sizes and Temperatures
Published 2025“…Capillary condensation pressures increase with pore size and temperature, but suppression of saturation pressure under confinement decreases at higher temperatures and larger pore sizes. …”
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2245
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2246
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2247
Comparison of absolute and relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
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2248
Rate of convergence for relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
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2249
Ultrafine Particulate Matter Exacerbates the Risk of Delayed Neural Differentiation: Modulation Role of METTL3-Mediated m<sup>6</sup>A Modification
Published 2025“…By employing <i>N</i>6-methyladenosine (m<sup>6</sup>A) methylated RNA immunoprecipitation sequencing and bioinformatics, we identified <i>Zic1</i> as a key target of PM<sub>0.1</sub>-induced developmental disturbances. …”
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2250
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2251
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2252
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2253
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2254
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2255
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Complexity comparison of different models.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2257
Dynamic window based median filtering algorithm.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2258
Flow of operation of improved KMA.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2259
Improved DAE based on LSTM.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2260
Autoencoder structure.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”