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Firstly, we adopt DF layer as feature instead of traditional Haar-like one to model the target thanks to the DF specificity and the landscape smoothness.
In particular we have reviewed and analysed the possibility of using the most popular colour and texture features used in object and texture recognition, to identify and model the target (person being followed).
In one model the target chemicals were incorporated in the lipids before their self-assembly, and in the other one they were applied on top of a preformed lipid membrane.
When evaluating the dynamic response of a structure subjected to a high explosive detonation, it is common to simplify both the target properties and the form of the blast pressure load – a standard approach is to model the target as an equivalent Single-Degree-of-Freedom (SDOF) system with the blast load idealised as a pulse which decays linearly with time.
With the improved visual attention model, the target detection module is suitable for the SAR image target detection.
The 2D scattering center model [18, 19] in the ISAR imaging and automatic target recognition (ATR) can model the target returns well.
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Traditional statistical methodology is used for feature extraction, and GMM modelling is used to model the targets under different weather backgrounds.
In our model, the targets form part of the 3D environment.
The translation between the source model and the target model needs some rules to match the elements modelled in UML to other elements, which compose the Petri net.
vD1 and TD1 are calculated from the model D1, the target model, and vD2 and TD2 are from D2, the layered model.
In [12], adaptation methods are used to transform the neutral model to the target model, requiring only small amounts of adaptation data.
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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