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A number of test problems have been generated to evaluate the performance of the proposed algorithm (non-dominated sorting genetic algorithm II (NSGA-II)) in comparison with ɛ-Constraint.
Vocabulary questions also have been generated to evaluate learners' knowledge of English in correct usage of different types of words, such as verbs (Sakaguchi et al. 2013), prepositions (Lee and Seneff 2007), and adjectives (Lin et al. 2007) in a given context.
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Time activity curves were generated to evaluate the uptake and secretion pattern.
A diabody without C-terminal cysteine was generated to evaluate the effect of the additional cysteine.
Two sets of benchmark instances were generated to evaluate the proposed algorithms.
For each figure, 250 random realization of different channel coefficients are generated to evaluate the average performance.
Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm.
Test cases with different job factors were generated to evaluate the algorithms and to demonstrate its strength.
A linear regression is generated to evaluate the correlation of Land Surface Temperature (LST) with the four vegetation indices.
In addition, tri4 and tri11 deletion mutants were generated to evaluate the roles of tri4 and tri11 in trichodermin biosynthesis, respectively.
In this study, tri4 and tri11 deletion mutants were generated to evaluate the roles of tri4 and tri11 in trichodermin biosynthesis.
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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