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Each of the following subsections describes and compares the various methods used for each step.
This section, divided into two subsections, describes the optimized reputation system proposed for VDTNs focusing on its main features.
The next subsections describes the method used for the state-independent GMM training and the two different classes estimating of the state-dependent morphing functions.
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The following subsections describe this approach to feature detection.
The following subsections describe the preprocessing stages implemented.
The next subsections describe details of the developed device.
The following three subsections describe the objective definitions in detail.
The following subsections describe the datasets' properties in more detail.
The next subsections describe the components' functions in more detail.
The following subsections describe some task scheduling methods in WSN.
The following subsections describe the features considered in this study.
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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