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Then, similarity between the retina image of test person and all retina images in dataset is determined.
The rigid transformation for optimal alignment of the target CT to the reference CT dataset is determined.
The tissue represented in each voxel of the volume dataset is determined by using predefined attenuation threshold levels and is assigned to a specific colour and opacity.
Finally, using a new similarity function, the similarity of each test image to each retina image of the dataset is determined.
Based on a defined threshold volume, each voxel within the dataset is determined to be either part or not part of the object of interest, thus defining the surface.
The numbers of surrogate parents in a dataset is determined by its size, its effective population size, level of relatedness amongst its individuals, the proportion of genotype errors allowed for, and the length of the CplusTs.
Similar(53)
The purpose of this dataset is determining which of the structure-based similarity measures is more accurate: the one that relies on superposition of the entire subunits, or the one that relies on the interaction interfaces only.
Each class in our dataset was determined by the positivity of arousal and valence ratings.
The number of occurrence of each of the 111 substructures in the actives and the inactives dataset was determined.
The final performance per dataset was determined by context configuration (random selection, missing values, imbalance dataset, outliers, and other machine learning strategies).
The most appropriate model of nucleotide substitution for each dataset was determined using jModelTest v0.1.1 [78].
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com