Our experiments indicate that the instability occurs when Γ > Γc = 0.58, which we indicate by vertical lines in Figure 7a,b.
Since F is closed and convex, problem (2.6) has a unique solution in F, which we indicate by (x^).
In the sequel, we indicate by MEP ( F 1, F 2, A ) the set of solutions of our mixed equilibrium problem.
If the GPU is faster than the 8 cores of the CPU we indicate by how much faster the GPU performs.
As a result, the depth of the N feature points is computed accurately and we indicate by p z,k the depth of the feature point k.
Given any Lebesgue measurable set (Vsubseteq {mathbf{R}}^{n}), we indicate by ({mathcal{L}}(V)) the family of all Lebesgue measurable subsets of V, and by (m_{n}) the n-dimensional Lebesgue measure in ({mathbf{R}}^{n}).
Given a fixed time interval [ t 0, t 1 ] and a point z ∈ R 2, we indicate by ζ ( ⋅, t 0, z ) the solution ζ ( t ) = ( x ( t ), y ( t ) ) of (2.2) satisfying the initial condition ζ ( t 0 ) = z.
cNote also that, with a slight abuse of notation, in (23) and (24), we indicate by ζ-1 the inverse of ζ z; σ) with respect to ζ, with the implicit assumption that σ is fixed.
We indicate by (F_{mathrm{in}}(r,t)) the potential corresponding to the flow of individuals within the system, i.e., those ones following suggestions from the smart system, and by (F_{mathrm{out}}(r,t)) the potential corresponding to the flow of individuals out of the system.
