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To evaluate the performance of the proposed KMSM, a driver action dataset was established that included 10 tractor drivers and 5 types of action that denote inattention.
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A dataset was established of the minimal number of parameters that need be reported when calculating a drug-dosing regimen.
A protein dataset was established for the GB calculations (referred to as the GB dataset).
Thus, through sufficient sample training, the more effective SVR model of JLUBR-IRIS dataset was established.
Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions.
Subsequently, it is established that the KSOM framework should include the coefficient of variation of the datasets for determination of the number of map units, without considering it as a single value function of the sample data size.
A calibration dataset of points was established using stratified random sampling (n = 352,188).
The viability of the tool was established with different datasets.
The assignment of thresholds was studied among the datasets where a dose-response relationship was established.
ExCAPE-DB, a searchable open access database, was established for sharing the dataset.
From these studies, a dataset with 4,220 cases and 8,946 controls (Table 1) was established.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com