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To that end, and drawing on a previous study which demonstrated the effectiveness and efficiency of the methods proposed [ 42], and employing the skills of a specialist librarian, we will employ three approaches: 1. Identifying seminal sources known to the research team and other experts in the field (e.g. via relevant networks and email lists).
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The effectiveness and efficiency of the method is demonstrated through experiments on artificial and public datasets.
Finally, the experiments on real-world data demonstrate the effectiveness and efficiency of the proposed method over baseline methods.
Finally, we verify the effectiveness and efficiency of the proposed methods through extensive experiments on real and synthetic datasets.
As a result, the feature selection method improves the effectiveness and efficiency of the classification method.
Comparisons with the pseudospectral method are conducted to verify the effectiveness and efficiency of the proposed method.
Finally, the effectiveness and efficiency of the proposed method are illustrated based on several study cases.
Extensive experimental results demonstrate the effectiveness and efficiency of the proposed method.
Finally, experiments are conducted to demonstrate the effectiveness and efficiency of the proposed method.
Several examples are considered to demonstrate the effectiveness and efficiency of the proposed method.
The experimental result demonstrates the effectiveness and efficiency of the proposed method.
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