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In this section, we implement the LWOM on the FPDE stated in Eq. (9).
In this section, we implement the proposed algorithm using MATLAB (The MathWorks, Inc., Natick, MA, USA) and present simulation results to illustrate its performance.
In this section, we implement the proposed method on hardware system and show its high beamforming efficiency from our experiment result.
In this section, we implement the regression filter on six sample images, as shown in Section 3.2, to determine the neighborhood radius d value needed to achieve good denoising results.
The whole THS procedure is depicted in detail in Algorithm 2. In order to evaluate the performance and effectiveness of our proposed approaches (BHS and THS) to the power optimization problem, in this section we implement the blocking island paradigm and two heuristic schemes in the DCNSim simulator [36].
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As described in the Method section, we implemented the clustering algorithm of Haigh et al. [15] to select a diverse set of reference shapes.
In this section, we implement LAPM to the nonlinear fractional Riccati differential equations.
In this section we implement Principal Component Analysis to reduce the number of variables representing non-cognitive skills.
In this section, we implement three alternative tests to assess threats to the internal validity of our results.
In this section, we implement performance analysis characterization for Hadoop K-means iteration using AMD Interlagos platform.
In this section, we implement a k-means clustering algorithm by using (M phi -distance M phi -distance
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com