In dynamic continuous systems, such a value is observed over a time interval.
System performance measures for systems observed over a time interval of random duration are introduced.
We show that sensitivity derivatives of statistical quantities can be accurately estimated using a single, short trajectory (over a time interval of 20) on the Lorenz attractor.
Reliability is expressed in terms of the expected number of failures over a time interval by means of closed-form mathematical expressions which consider the structural degradation.
It represents trajectory, color and dimensions of a single moving object and the directional and topological relations among multiple objects over a time interval.
Both indicators are extended (based on the approach proposed by Cornell and collaborators) to estimate the reliability of a structure over a time interval.
Then, the time-variant reliability is approximated using Monte Carlo simulations of the Kriging model where system failures over a time interval are predicted by the instantaneous failure surface.
In a parallel study, it has been shown by comparison of successive TV-holography campaigns that murals in the convent of Müstair Switzerlandd) have progressively detached from their substrate over a time interval of 5 years (J Cult Herit 2009).
For example, we investigate the relation between trading activity – measured by the number of transactions NΔt – and the price change GΔt for a given stock, over a time interval [t, t+Δt].
To attain this objective, it is assumed that multiple groups of actuators are available with only one such actuator group being active over a time interval of fixed length while the remaining actuator groups are kept dormant.
Using this conceptual framework as a guide, we empirically quantify the relation between trading activity measured by the number of transactions N and the price change G t) for a given stock, over a time interval [t,t+Δt].
