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Based on our investigation, we recommend a PAPR optimization interval of around four symbols for SC-FDMA based systems while for OFDM DL systems a slightly larger interval may be selected if associated PAPR reduction is acceptable.
The result of Kalman filter is the optimal closed solution for linear systems, while for nonlinear systems, it is very difficult or even impossible to get an accurate optimal solution.
The yield- and the large strain response is captured well for the soft-particle filled systems while, for the hard-particles at increased filler loadings, the predictions are less accurate.
For the Hollywood movies, results are obtained both from the baseline TMM13 and the ICIP15 movie summarization systems, while for the five travel documentaries and GWW, we use the extended ICIP15 system; where GWW#1 shows AUC results obtained when GWW was trained on the movies and GWW#2 shows results when the training was performed on all data.
In the case of the pure solvents, the lowest values of the objective function have been obtained using the simulated annealing technique in six out of the seven studied systems, while for the electrolyte solutions the method results in the lowest values in nine systems out of 11; in the other systems the local methods have resulted in lower values of the objective function.
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Cases would move more smoothly through the system while, for example, assuring fairer debt-collection proceedings, which are often dominated by lawyers for collection companies.
This emphasizes the applicability of this approach in real-time applications where the 16PF traits need to be evaluated ad hoc, as the need for controlled scenarios is only vital when training the system, while for testing, we can use video recordings acquired in totally random scenarios.
The quantitative comparison of the fuzzy-evolutionary controller to the LQR controller has been given for one example system, while for the other two systems (for which there are no analytical solutions) the value of the objective function has been provided for future reference.
The best operating conditions of the Fast-SAGD1 process were an injector producer spacing of 9 m, injection pressure of 6409 kPa, steam injection rate of 610 m3/d, subcool 6 °C for the SAGD system; while for the CSS well, injection pressure of 8333 kPa and a steam injection rate of 1007 m3/d.
Titrations of PDCzm and slr1192 were performed in the initial system, while for titration of other components, 4 mg/l PDCzm and 6 mg/l slr1192 were added to the reaction as introduced below.
Nearly 20% of the S. paradoxus strains tested failed to receive a top mark in the scoring system while for S. cerevisiae this was less than 10%, and also reflected in the higher average overall score for S. cerevisiae of 2.5 ± 1.4 compared with 2.1 ± 1.4 for S. paradoxus.
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