A full characterization of the encoding map should explain how an amino acid sequence determines an input contact vector.
In ordered to discriminate between models by determining an input, which results in the largest difference in the outputs of the models we wished to determine the optimal input frequency.
Using a Bode plot showing the response of the difference of the outputs to a sinusoidal input with fixed amplitude, we determined an input frequency (in terms of frequency of 100 μM amplitude ligand application) in order to discriminate best between the remaining two models.
The simulation of the hypothetical models is embedded in a nonlinear optimization problem to determine an optimal input sequence that maximizes model dissimilarity.
Without it, an adversary is able to determine a user input, with increasing accuracy when more outputs become available.
Optimal experiment design for system identification involves determining an optimal input that is used to perturb the system so that the resulting input-output data is maximally informative.
Captchas (completely automated public Turing test to tell computers and humans apart) are designed to determine whether an input to a web page - commenting on a blog post, or signing up for an online service - actually comes from a human or a computer (probably programmed to post advertisements or other junk).
For example, finite state machines cannot determine whether an input string consists of some As followed by the same number of Bs.
riboPicker uses query sequence coverage, alignment identity and minimum alignment length thresholds to determine if an input sequence is an rRNA-like sequence or not.
In the neural network based forward mapping, mould properties are expressed as the functions of input parameters, whereas attempts can also be made to determine an appropriate set of input parameters, to ensure a set of desired properties, in reverse mapping.
In this paper, a hybrid optimization technique is used by combining Taguchi grey relational analysis (TGRA) and response surface methodology (RS M to determine an optimal combination of input process parameters, such as the number of sheets, the tool diameter, the feed rate, the spindle speed and the vertical step depth, required to obtain favorable responses.
