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First step was performed with the following procedures: (1) the raw brain structural images (3D T1-FSPGR) (Fig. 1a) were normalized into MNI space, and the normalized T1 images were obtained (Fig. 1b), which were gray images while not probability images.
For each patient, the co-registered anatomical images and the demarcated lesion were normalized into MNI space using the unified normalization segmentation of SPM (http://www.fil.ion.ucl.ac.uk/spm) as shown in Fig. 3C.
(3) All images were normalized into Montreal Neurological Institute (MNI) stereotactic space with the normalized images modulated to correct volume changes by the Jacobian determinants.
All the samples were normalized into the size of 64 ×64 pixels and flipped horizontally.
All variables were normalized into -1+1 range and variable selection was performed with a hybrid selection algorithm (HSA).
Known abbreviations, numbers and special characters in Twitter messages were normalized into more suitable forms with a set of rules shown in Fig. 1.
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The database schema has been normalized into third normal form to avoid storage of data with logical inconsistencies.
Here, the energy consumed in movement is normalized into communication.
In this research, the available data have been normalized into the range of −1 to 1.
where α is a constant in the range [0, 1] and e Lab is normalized into the range [0, 1].
For informative purposes, the steps of the development process are formalized based on database ER-model, and the final design is normalized into 3NF.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com