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In info-gap decision theory, the demand value of information is formulated with the robustness function.
Also, we show that the info-gap robustness function provides an attractive tool for adjudicating between conflicting objectives in multi-criteria design.
This paper discusses evaluation techniques of the robustness function of trusses, which is regarded as one of measures of structural robustness, under the uncertainties of member stiffnesses and external forces.
The robustness function (q,rc) is the immunity against failure: the greatest level of uncertainty which is consistent with always attaining no less than a specified critical level of reward.
A non-probabilistic concept of reliability based on the info-gap robustness function allows us to define the three main components of the uncertainty analysis: structural model, uncertainty model represented by info-gap models, and a performance criterion.
This may provide some clues for the global stability, robustness, function and synthetic network design.
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The lower bounds of the robustness functions are computed for various trusses under several uncertainty circumstances.
By using quadratic embedding of the uncertainty and the S-procedure, we formulate a quasiconvex optimization problem which provides lower bounds of the robustness functions.
Moreover, it has been hypothesized that proteins without a rigid structure achieve high robustness of function (despite essentially zero structural robustness) (Brown et al. 2002), flexibility of function for transient and specific interactions (Singh et al. 2007), and the ability to evolve through promiscuous functions (Wroe et al. 2007)—all of which contribute to higher evolvability.
Figure 7 Computation of the robustness in function of for different images and different number of cones.
Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices.
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