Your English writing platform
Discover LudwigSuggestions(1)
Exact(13)
Tables 9 and 10 list the total criteria relation matrix and total dimensions relation matrix separately.
Having determined the relationship structure of all dimensions and criteria, the total criteria relation matrix was normalized according to Eq. (9), and Table 12 shows the normalized result.
(3) and (4), and the total criteria relation matrix T c and total dimensions relation matrix T d are derived by Eqs.
Based on above T c, the total dimensions relation matrix T d is generated from total criteria matrix by Eq. (6), where ( {t}_d^{ij} ) is the average of elements of matrix ( {T}_c^{ij} ).
The normalized total criteria relation matrix was weighted by the normalized total dimensions matrix to obtain an originally weighted super-matrix by Eq. (11), and the matrix was then transposed to get the weighted super-matrix using Eq. (12).
As the total criteria relation matrix and total dimensions relation matrix capture the effects and influences of elements, and there is no empty cell in the matrix, all elements both influence and be influenced by other elements.
Similar(47)
A positive linear trend was found for criterion A6 ("gambles again after losing," P = 0.050) and for the means for the DSM-total criteria (P = 0.038).
Differences between non-VGA and VGA achieved moderate effect sizes for the SOGS-total score and the DSM-total criteria, and the other pairwise comparison achieved a low effect size.
Figure 1 shows the path diagram and the standardized coefficients of the SEM developed to evaluate the mediating role of the ADHD total score in the relationship between novelty seeking (TCI-R NS-score) and gambling severity (DSM-total criteria).
Patients' age was negatively related to ADHD symptoms (the youngest patients obtained the highest ADHD scores; B = −0.128, SE =.054, z = −2.37, and p =.018), but age did not show a direct effect in relation to the DSM-total criteria (B = −0.015, SE =.053, z = −0.28, and p =.777).
The proposed algorithms are applied to the no-idle permutation flowshop scheduling (NIPFS) problem with the makespan and total flowtime criteria.
Write better and faster with AI suggestions while staying true to your unique style.
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