We remind that the notion of a solution of a boundary value problem was specified in part 1. Theorem 4.1.
(d) The assumptions specified in part (d) of Theorem 2.1 are satisfied for the feasible solution (tilde{mathcal {S}}) of (DI), (bar{phi }(a)> 0 Rightarrow a > 0), and the function (xi rightarrow Phi (xi,tilde{x},tilde{u},tilde{v},tilde{w})) is ((mathcal {F},beta,bar{phi },bar{rho },theta,m)) -quasisounivex at (tilde{x}).
The assumptions specified in part (a) of Theorem 2.1 are satisfied for the feasible solution (tilde{mathcal {S}}) of (DI), (bar{phi }(a)> 0 Rightarrow a > 0), and the function (xi rightarrow Phi (xi,tilde{x},tilde{u},tilde{v},tilde{w})) is strictly ((mathcal {F},beta,bar{phi },bar{rho },theta,m)) -pseudosounivex at (tilde{x}).
(b) The assumptions specified in part (b) of Theorem 2.1 are satisfied for the feasible solution (tilde{mathcal {S}}) of (DI), (bar{phi }(a)> 0 Rightarrow a > 0), and the function (xi rightarrow Phi (xi,tilde{x},tilde{u},tilde{v},tilde{w})) is ((mathcal {F},beta,bar{phi },bar{rho },theta,m)) -quasisounivex at (tilde{x}).
(c) The assumptions specified in part (c) of Theorem 2.1 are satisfied for the feasible solution (tilde{mathcal {S}}) of (DI), (bar{phi }(a)> 0 Rightarrow a > 0), and the function (xi rightarrow Phi (xi,tilde{x},tilde{u},tilde{v},tilde{w})) is ((mathcal {F},beta,bar{phi },bar{rho },theta,m)) -quasisounivex at (tilde{x}).
One possibility is to employ different wavelet filters as specified in Part 1 of the standard (e.g., user designed filters) and to vary the filters during decomposition, which is discussed to be used as key-dependency scheme in the following subsection.
The HBM specifies in part that before people will take action to change behavior they must "believe they are susceptible to the condition," that the condition "has serious consequences," and that by taking action they can "reduce risks" [ 83].
If an item is covered, the payment rate is specified in other parts of the law.
Control systems are typically specified in two parts: continuous and discrete.
Regression parameters were specified in two-part marginalized models for direct estimation of exposure effects on the overall mean count using maximum likelihood methods.
The LCR model is specified in two parts: (1) a model for the relationship between the latent classes and the observed indicators; (2) a regression model for the relationship between covariates and latent class membership [ 34].
