These examples allow one to validate the multiscale approach and to study the influence of different parameters on the passive damping of the structure.
The Dr. Oldroyd research on immediate and persistent response, for example, allows one to predict who to call and when to call, to dramatically improve contact and qualification rates.
For example, a queueing model allows one to incorporate randomness, which is inherent in the actual system, into the mathematical analysis.
For example, a formal model allows one to incorporate randomness in key parameters, such as arrivals of phone calls at a system.
Intrinsic motion and the associated quasi-periodic respiration and heart beats, for example, allow one means of gating such high speed pulsed systems.
For example, it allows one to model spatial (Perrinet and Masson 2007) or temporal (Montagnini et al. 2007) integration of information, using conditional independence assumptions.
For example, it allows one to identify sub-networks within the metabolic network that are linked with shared metabolites and are controlled by sets of independent fluxes.
For example, it allows one to determine how task demands (e.g., the instruction to process the identity and not the emotional expression of a face) modulate the connectivity between these regions (Friston et al. 2003).
For example, BRMA allows one to describe the bivariate relationship between endpoints [ 4, 5], model, test or make predictions from their association [ 7], and estimate some function of the two pooled endpoints, like β1 - β2 [ 10], β1 + β2 [ 5], or β1/ β2 [ 6].
For example, the theory allows one to determine a mathematical expression that relates average customer waiting time to the number of servers.
