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Using the compact finite difference method this problem can be recast as an ordinary differential equation initial value problem.
For in the ANN (Artificial Neural Networks) method, the training samples are difficult to generate, while combining the linear regression method with ANN method this problem can be solved perfectly.
Then, based on the dual decomposition method, this problem is decomposed into many subproblems, which can be solved independently in a parallel fashion at each source/link, and builds the Dual Decomposition based Optimal and Fair Congestion Control framework (D2OFC2) to coordinate their source allocation among flows.
As for the new method, this problem is solved by introducing external markers determined by contextual information.
We can find the best seam (the shortest path) via dynamic programming method, this problem can be common in graphs.
With our method, this problem is eliminated because the starting material is a CVD-grown single-crystalline 2D superlattice.
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In filter bank multicarrier (FBMC) methods, this problem is resolved, simply, by using filters with well-attenuated stopbands, [3].
Because of the limited number of therapeutic methods this problem is one of the most urgent challenges in biology and medicine [ 1– 3].
You will find condition variables to be the most useful synchronization method for this problem.
Dr. Srivastava's method sidesteps this problem by avoiding the stem cell stage.
One reliable method avoiding this problem is to excite the process to some extents intentionally.
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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