Suggestions(5)
Exact(5)
In Section 3, we explain the test material used together with the details of the similarity metrics we defined.
For this analysis, we use the set of motivation and ability metrics we defined and calculated these metrics, considering the complete activity of each user.
Therefore, considering the metrics we defined in this work and based on both controlled experiments, TTR 1.2 is a better option if we need to consider higher strengths (5, 6).
We can explain this better performance of TTR 1.2 due to the fact that it no longer generates, at the beginning, the matrix of t-tuples but rather the algorithm works on a t-tuple by t-tuple creation and reallocation into M. Considering the metrics we defined in this work and based on both controlled experiments, TTR 1.2 is a better option if we need to consider higher strengths (5, 6).
To calculate performance metrics, we defined annotations that represented genotype differences between 454 and Sanger platforms [11] but modified to take heteroplasmy into account for mtDNA analysis (Table S3).
Similar(55)
As the transition metric is the ratio between two consecutive averaged metrics, we define the difference metric.
To validate these metrics, we define Efforts Deviation Index that captures the difficulty level of the change implementation process.
In this paper, we firstly summarise the set of metrics we have defined to measure the understandability (a quality subcharacteristic) of conceptual models for DWs, and present their theoretical validation to assure their correct definition.
As indicated in the figure, the different period metrics we employed (defined in the methods) were applied to both the exploratory and confirmatory approaches.
So, we must first define pairwise-molecular metrics before we define multiple molecule methods.
We defined novel metrics to be able to uncover clusters of different sizes in programs, and also to relate programs in terms of their degree of clusterization.
More suggestions(15)
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