A stepwise category-learning task was designed to examine brain activation associated with invariance detection and variance inhibition during category induction (CI).
A systematic method of constructing hierarchical net models is described for their direct implementation such that the net is translated into the detailed net by stepwise refinements from the highest task specification level to the lowest machine control level.
The task of the stepwise procedure is to maximize an objective function the sensitivity.
The proposed approach considers three factors, including workflow, activity, and resource that significantly influence stepwise decompositions of a complex manufacturing task.
To assess whether clinical knee pain (i.e., average pain on most days of the month prior to enrolment) predicted variance in the location of peak activation in the motor cortex, independently of any variance explained by accuracy of performance of the force-matching task (log RMS error), stepwise multiple regression analysis was used.
Finally, tasks were often introduced in a stepwise manner, progressing from the easiest to the most difficult conditions, which might have had the effect of training the subjects by reinforcing simple sequences of behaviour generated through random processes [8], [12], [13], [27].
Upon receipt of the response the "do case" state is returned to the sequencer to allow advancement through the monitoring sections of the script ensuring proper stepwise alignment of all three scripts throughout the task.
Procedural tasks can best be trained using a stepwise approach, with the therapist modeling each step and providing verbal cues to guide the patient.
Industrial upgrading (IU), the stepwise development of manufacturing skills from simple to more complicated tasks, can be a highly effective approach for late entrants.
Post Hoc Stepwise Stepdown Multiple Comparisons were used to identify subsets of tasks with homogeneous characteristics, as described by Campbell and Skillings.
