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A mixed multinomial logit model for each dataset was employed to examine the contributory factors.
Different from recent modeling studies, a soil dataset was employed with 200 samples of correlated soil hydraulic parameters for sandy soils.
Four days of datasets were employed to develop the model and one day of dataset was employed to test the prediction accuracy.
The train dataset was used to build/simulate the model and the test dataset was employed to evaluate the performance of the built model.
In order to facilitate the comparison and evaluation of multiple ortholog identification methods, this dataset was employed for all analyses (except as otherwise noted).
For this reason, the local investigator-assessed dataset was employed in our analysis.
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Various quality control methods, which are not annotated in the dataset, were employed to omit samples whose composition is believed to differ from the intended composition.
To verify the efficiency of the proposed model, a dataset from approximately 3 years of cycling capacity fading experiments of various formulations using several different materials provided by Contemporary Amperex Technology Limited (CATL), as well as a NASA dataset, are employed.
To overcome the lack of large training data, the handwritten images in MNIST dataset are employed to simulate the properties of long-rang infrared images including dim targets, background clutters and low contrast.
For upsampling a target size of 200% (number of instances) of the upsampled training dataset compared to the original dataset is employed.
The validation dataset is employed to validate the final model for accuracy and to predict the limiting velocity required to prevent sedimentation in sewer systems.
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