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Furthermore, internal computing support, internal computing training, external computing support, external computing training, and external equipment accessibility have positive effects on perceived ease of use.
In addition, the results also partially support that perceived resources have impacts on online learning adoption: Perceived ease of use, internal computing support, internal computing training, and external computing support have positive effects on perceived usefulness.
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Swenson et al. suggested that the pVL measurement at week eight was a good indicator of treatment success, which is why we used it to compute training and test labels.
To compute the train-train and train-test kernel matrices, we used the parameter free Χ 2 kernel for all features.
Perhaps the most potent and universally recognised issue with the change to computing is training.
According to the problems in the program design course's practice, proposes the new practice mode based on the computing ability training.
In addition, each training image subtracts the mean RGB values computed on training set from each pixel.
For fMRI, we computed the training effects by subtracting the activity for Ziggerins (relative to object control) before training from that after training.
Before training, the first empirical moments of all regions in f l c l = 1 L f and the second empirical moments of all regions in g l c l = 1 L g are computed using training data.
In order to approximate the expectations by sample averages computed from training data, the side-information variable Y is discretized to Ŷ ∈ η 1, … η Y, where is a large enough positive integer.
Regression plots were computed for training, validation and testing databases.
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