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All experiments are implemented by first optimizing the methods using the development data and then testing with fivefold cross-validation over the primary dataset.
This is done by first optimizing the parameters using AHP and then using VIKOR and TOPSIS with fuzzy logic to sum up the result.
Therefore, the nonconvex joint power allocation problem can be solved by first optimizing the relays' power coefficients with fixed, and then optimizing the sources' power coefficients while is fixed.
In this case, one could begin by first optimizing the likelihood based on the discrete Wright Fisher model over small values of N NN < 5000).
Taking the adult VNC as an example, we can make our algorithm more robust by first optimizing the skeleton of the main trunk (i.e. the horizontal domain in Fig. 8a) so that we can get a good estimation of the scale, position and the orientation of the VNC, and then optimizing the remaining domains/segments to complete the entire skeleton.
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We formulate a graph-augmented deformable (GD) model based on the geodesic shortest path, and produce satisfactory tracing by first optimizing a shortest path graph problem followed by refining a 3D deformable curve.
Because percent masking using k-mers depends on which absolute frequency threshold is used, we first optimized the threshold by comparing all ROC curves for absolute frequency thresholds between 0 and 4.0 at 0.1 increments.
We first optimized the KRAS test, by performing an accurate tissue-dissection step followed by pyrosequencing, a more sensitive method, and found further mutations in 12 (12.8%) cases.
We first optimized the LASL method (Figure 1) by reducing template contamination during shearing, and taking steps to minimize cloning biases, particularly for AT-rich templates.
In detail, it first optimizes the Q function in X by fixing Π.
In detail, it first optimizes the Q function in X and Y by fixing Π and Ω.
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