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Simulation and experimental results show that, when the arc length increments are kept small enough near the sharp corners, the ATE method attains high accuracy and robust computation.
Furthermore, simulations from real Population Reference Sample genotype data show that our method attains high accuracy in localizing recent ancestors of admixed individuals in Europe (an average of 550 km from their true location for localization of two ancestries in Europe, four generations ago).
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Through simulations, we demonstrate the FRF method attains higher or comparable accuracy over commonly used support vector machine based methods under various disease models.
This method attained high similarity indices.
With the semiautomatic segmentation by the experienced neurologist for comparison, this automatic method attained high similarity indices.
The proposed method attained high agreement with the semiautomatic method, with similarity index 89.9 ± 6.5%, in detecting cerebral infarct lesions from 22 acute stroke patients.
With regard to the reliability of the questionnaire, both internal consistency and two halves reliability methods attain higher values than the accepted standard minima [ 49] with respect to the total score and also to the individual subscales.
The results show that our method attains a high rate of correct selection of the most well-suited algorithm for the particular scene.
Both qualitative and quantitative comparisons yield good agreements of results, indicating that the HES approach with the flux-splitting method attains a high computational accuracy.
Comparing these complexes to manually curated ones, we show that our method attains very high specificity and sensitivity levels (∼ 80%), outperforming current approaches for protein complex inference.
Thus, the golden ratio-based method attains a higher recognition rate and is more robust.
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