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It is reported in the literature that almost 99%% of the mechanical faults have noticeable indicators in the form of vibration and acoustic signals [1].
The integration of a set of key sustainability indicators in the form of a composite index is essential for simplifying the evaluation of sustainability performance.
In the literature, most of the automatic fault detection uses the acoustic or vibration signal generated by the engines for fault detection and classification, as most of the mechanical faults have noticeable indicators in the form of vibration and acoustic signals [1].
Scores that used to determine each indicator criteria set to be 5 levels of severity include: 0 = no injuries; 1 = Light; 2 = mild; 3 = moderate; 4 = heavy; 5 = very heavy; 0 = no injuries; 1 = Light; 2 = mild; 3 = moderate; 4 = heavy; 5 = very heavy; For criteria and indicators in the form of numerical data injuries, the determination of the score is done by processing data in groups (Table 7).
It might be possible to develop indicators in the form of descriptive scales of the degree of utilisation.
For analysis, the mean value of duplicates generated indicators in the form of height-for-age (HAZ) and weight-for-height (WHZ) Z-scores.
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Since journal-based normalized citation metrics are increasingly being discussed in the scientometric literature, we have integrated such an indicator in the form of the J-factor.
A chamber indicator, in the form of a pin inside a tiny hole, is provided on the left side of the slide.
Thus, each symbol x m is associated with a set of indicator functions in the form of I m, i = { I m, k, i } k = 1, k ≠ i, k ≠ m N, where I m, k, i for k ≠ i, k ≠ m acts as a binary indicator function when node S i is the receiving node, while S k is the optimally selected node transmitting signal ym,k corresponding to symbol x m.
In practical terms the output of the model is provided to the user as original indicator values in the form of tables, bar diagrams corresponding to each aggregation step and a radar diagram representing the overall farm performance in the twelve sub-dimensions.
As Figure 6 shows, the absorbance of the unprotonated form of the indicator in TiO2-Pr-SO3H was weak as compared to the sample of the indicator in CCl4, which indicated that the indicator was partially in the form of [IH+].
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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