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Chen et al. (1990) first deduced the critical force to cause helical buckling with the energy method and stated that critical helical buckling load was (sqrt 2) times the critical sinusoidal buckling load.
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They respected the fact that HCPs have to work with evidence-based methods and stated that they would be positive towards working with CAM when research-based evidence becomes available.
The integration is analyzed for its reliability by using the conventional fault tree method and state of the art dynamic flowgraph methodology.
In order to compare the computation time of the natural vector method and state-of-the-art methods ClustalW2, MUSCLE and MAFFT [14], [15], [16], we performed the test on two sets of sequences.
Table 2 shows the comparison between our method and state-of-the-art methods on the same 10-fold CV.
To test our method, we constructed a retinal video indirect ophthalmoscopy (VIO) image database from pediatric patients and compared the segmentations achieved by our method and state-of-the-art approaches to a human-drawn gold standard.
Data collection is based on experimental design and stated choice methods through an Internet survey.
These methods are applied to nonlinear reliability prediction when compared with physical model methods, which mainly include computational intelligence methods, statistical methods, and state space methods.
Experimental results show that our approach outperforms both baseline methods and state-of-the-art methods on various evaluation metrics.
In the previous sections, we have investigated the particle filtering methods and state estimation for networked systems, respectively.
Subsequent sections in this paper discuss some of the basic definitions, provide an overview of the various preprocessing methods and state-of-the-art data processing tools for multivariate analysis that are widely used in Raman and IR spectroscopy.
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