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Additionally, Figures 8 and 9 show that the scheduling order and the number of iterations affect the system performance.
The proposed model can not only assess how design iterations affect the duration, but also evaluate the idle durations of the design participants to support the assignment of design tasks.
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We investigate how the number of reconstruction iterations affects the EF estimation in a high signal, no background phantom setup.
The convergence rate also affects the practical value of the method (e.g., a system with a tight constraint on decoding delay) and the number of iterations affects the performance.
As can be seen, the number of iterations affects the accuracy of solution very much for noise levels lower than σ = 25, i.e., the larger the number of iterations, the better the denoising result; and again we get the conclusion that our proposed method outperforms K-SVD much more for noise levels lower than σ = 25 as demonstrated in Section 4.2.
The number of iterations discarded as burnin varied across runs, but was determined by plotting the traces of μ and κ; iterations affected by the starting value of the parameter were discarded.
In addition, the probable number of iterations that affect the attenuation corrected image was calculated.
Therefore, the accuracy of the first iteration would highly affect the PIC performance as error propagation occurs when incorrect information imports.
Different decoding strategies in the first iteration does not affect the performance much, and the performance is not very sensitive to hard or soft feedback either.
However, in LS procedure, the result of the previous iteration does not affect the b that is computed.
Several conditions affect the iterations.
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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