The MDOCA algorithm could have important applications in the mathematical modeling of realistic Turing systems when experimental data are available.
It means that we derive the necessary condition of identifiable systems when such data are available.
These contributions comprise a bounded-error experimental design framework that can be applied to nonlinear continuous-time systems when few data measurements are available.
In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available.
"Our research indicates that portable navigation device users are more satisfied with their systems when the map data is up-to-date".
In addition, the present study shows the applicability of the electrical resistivity method for the understanding of hydrogeological systems when the well data are limited for a precise characterization.
These results stress the necessity to take into account reversibility, or at least to evaluate the potential consequences of neglecting this important property of metabolic systems, when integrating isotopic data into quantitative models.
Third, this paper describes findings from the initial months of the SARI surveillance system in China, when data quality was inconsistent.
Through extensive simulations, we validate our analytical results for the system when the data arrival and channel condition processes follow Bernoulli distribution.
