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The experiments showing the advantages of the new method, with regard to both delay and precision, are described.
We also demonstrate the flexibility of the class discovery method with regard to standard resampling methodology such as jackknifing and noise perturbation.
In this study, seeding by using fibrin as a cell carrier is compared to the conventional static seeding method with regard to tissue development.
This is done to validate the method with regard to cavitation including complex cavitation phenomena responsible for higher order pressure pulses.
Numerical and experiment results demonstrate the efficacy of the proposed vectorization method with regard to computational speed in signal processing and high precision in the correlation algorithm.
Furthermore, the sensitivity of the method with regard to the damage degree, the static system, the damage position and the impact of temperature variation were analysed.
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The main advantages and disadvantages of each method with regards to emissions modelling are presented.
We focus on the VM cluster migration by exploring a more sophisticated method with regards to VM network configurations.
Here, we show the effectiveness of our CS compression method with regards to its new feature that motivated our study that is the ability of CS to be applicable on unstructured mesh data.
Further, it is compared experimentally with Bayesian and consonant approximation methods with regard to the error they make.
The aim of the study was to compare these 2 methods with regard to early mortality and long-term survival.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com