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To the same degree, it is impossible to spatialize perception data in reason of the limited number of respondents for each area (between 16 and 24 respondents by community) as well as in reason of the experimentation method (face to face in the same room).
Based on these results, a statistical method, face centered central composite design (FCCCD) falling under response surface method (RSM) was employed for further enhancing the succinic acid production and to monitor the interactive effect of these parameters, which resulted in a twofold increase in yield (14.3 g L−1 in 48 h).
Attempts to evaluate the effectiveness of any phosphorylation prediction method face a two-fold difficulty.
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To discuss the perceived benefits of the proposed method, face-to-face and phone interviews were conducted with eleven actual domain experts.
Based on these results, a statistical method, face-centered central composite design (FCCCD) falling under RSM was employed for further enhancing the succinic acid production and to monitor the interactive effect of these parameters, which resulted in a more than 2-fold increase in yield (12.5 g L−1 in 24 h).
However, in the multilinear case, the method faces some challenges.
Nevertheless, every empirical method faces this issue due to the unavoidable dependency of data on a specific context.
When the considered flow is highly dissipative, this otherwise very attractive method faces a serious time-step limitation.
(2) The VCA method faces a similar difficulty with kernel method, that is, restriction on the scale of training set [7].
However, the bottom-up method faces a serious obstacle because the enormous nexus of Peircean ideas is difficult to unravel and separate.
However, as we will discuss later, this method faces the curse of dimensionality when the number of secondary users is large.
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