Showing 1 - 20 results of 5,308 for search '(( auc ((largest decrease) OR (larger decrease)) ) OR ( _ ((cnn decrease) OR (mean decrease)) ))', query time: 0.38s Refine Results
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    CM-DWM-EC chart using 30% decrease in the mean for the E(KeV). by Shumaila Nisar (20114256)

    Published 2024
    “…<p>CM-DWM-EC chart using 30% decrease in the mean for the E(KeV).</p>…”
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    <b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

    Published 2025
    “…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”
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    CNN framework. by Sajid Mehmood (6689843)

    Published 2025
    “…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”
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    CNN frameworks. by Sajid Mehmood (6689843)

    Published 2025
    “…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”
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    Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest. by Helal El-Zaatari (20442243)

    Published 2025
    “…<p>Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest.…”
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