Using different calculation methods (i.e. thermionic emission (TE) model, Ohm's Law and Norde's method), these parameters were obtained from the current-voltage (I-V) data and compared with each other in various conditions.
For example, with the FD method, these parameters would be the amplitude of the time derivative of the time series that must be exceeded, a FD, and p FD, the length of time it exceeds it.
In the proposed method, these parameters are directly calculated using a nonlinear regression model from the observed head and foot points of a walking human instead of estimating vanishing line and points, which are extremely sensitive to noise in practice.
In our method, these parameters were optimized so that pathways that are fully annotated in the reference database, for instance KEGG, are ranked first with respect to predicted pathways (see details in Methods).
All theoretical methods have these parameters, which have to be taken into account when translating a method into a practical application.
Fine structure parameters were also generated using density functional methods, and these parameters matched well with the experimental ones.
Typical tasks of a river monitoring network design include the selection of the water quality parameters, selection of sampling and measurement methods for these parameters, identification of the locations of sampling stations and determination of the sampling frequencies.
A new quantitative measurement method for these parameters in the realm of the Axiomatic Theory is introduced in this article.
The new method detects these parameters in low computational time in a serial manner, which implies that it has an advantage to track not only linear but also nonlinear motion of GEO debris more easily than the previous methods.
