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A new systematic way in order to obtain optimized fuzzy inference system for classification task is developed.
In this paper, an FES-assisted training strategy combined with impedance control for the lower limb rehabilitation robot is presented and the controller used to accomplish this task is developed, aiming to achieve two goals.
In this paper, a variation of the digit span task is developed which reliably induces rapid changes of cognitive load to generate task-evoked pupillary responses (TEPRs) associated with large, within-task load changes.
In particular, a high-priority task is developed using non-conventional sliding mode control to guarantee safe reference parameters imposed by the task, e.g., keeping a load at a desired orientation (to prevent spill out in the case of liquids, or to reduce undue stresses that may compromise fragile items).
Third, our methodology did not allow us to determine the influence of specific factors on residents' preferences, such as individual characteristics, complexity of the task or even the specific workplace context in which this task is developed.
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For a given concept C, the first task is developing a theory explaining the psychological processes responsible for intuitions about C (once those intuitions have been systematically collected and assessed).
The ANT task was developed by Fan et al. (2002).
For this investigation, an electronic version of the task was developed using Adobe Creator.
To investigate the neural systems supporting this ability, an fMRI picture sequencing task was developed.
An auditory version of the OSPAN task was developed for use in the vehicle by Watson and Strayer (2010).
In particular, two versions of the modified counting task were developed: one incorporating neutral words and the other affective words.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com