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We demonstrate the effectiveness and robustness of the proposed method by presenting several clinical applications.
In this paper we consider a nonlocal elasticity theory defined by Eringen's integral model and introduce, for the first time, a boundary layer method by presenting the exponential basis functions (EBFs) for such a class of problems.
We demonstrate the accuracy of the method by presenting examples of two-fluid linear wave propagation, two-fluid linear eigenmodes of a tilting cylinder, and of a challenging nonlinear problem in two-fluid magnetic reconnection.
In this section, we illustrate the validity of the effectiveness of the proposed method by presenting the simulation results.
In Section 8, we illustrate the method by presenting two numerical examples with exact solutions and also one example without an exact solution.
The authors evaluate their method by presenting missed and false detections and by comparing the schooling behaviour as identified by manual annotation and automated annotation.
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PANAS-t and Emoticons DS used manually unlabeled Twitter data to validate their methods, by presenting evaluations of events in which some bias towards positivity and negativity would be expected.
We conclude with a discussion on both the theoretical and practical implications of our method and by presenting some relevant future research needs.
Section VI concludes the paper by summarizing the proposed methods and by presenting some perspectives.
This method is compared with two other similar methods: the Expected Conditional F-statistic method (ECF method) presented by Lai YL et al. [ 7] and the Detection of Altered Gene Associations method (DAGA method) proposed by Yoon SH et al. [ 9].
The image characteristics were analyzed by the image spectrum method and presented by the spectrum-frequency slope (S).
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