Sentence examples for trials domain from inspiring English sources

Yet, the use of workflow modeling in the clinical trials domain is less well established [5].

This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML.

Hence, the need for standardization applies to both the use of a single modeling language, as well as a standard representation to extend the modeling schema into the clinical trials domain.

In this work, we have demonstrated how such framework can be applied to the clinical trials domain.

The control law is obtained as the solution of the bounded data uncertainty (BDU) least squares problem, using the bounded model uncertainty in the trial domain.

Since we compute the uncertainty bound, rather than assuming its value in the trial domain, we reduce the conservatism of the robust design.

The resulting one step linear matrix inequality based design produces a stabilizing feedback controller in the time domain and a feedforward controller that guarantees convergence in the trial-to-trial domain.

Efficient solutions, with the linear complexity in the size of the trial length, are presented for both the BDU least squares problem and for the computation of the uncertainty bounds in the trial domain.

The uncertainty bounds in the trial domain are directly obtained from the bounds on the model uncertainties of the local sample to sample LTI or LTV models, using the randomized algorithm.

Starting from the model uncertainty of the local sample to sample LTI or LTV models, and using the randomized algorithm, we compute the bound on the model uncertainty of the ILC system representation in the trial domain (lifted ILC).

This paper considers the problem of designing an iterative learning control law for discrete linear systems using repetitive process stability theory The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain.