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A Model Predictive Control (MPC) approach is used to track the optimal position profile.
Based on these measurements, we developed a model for needle insertion and withdrawal that can be used to generate a 1-DOF force versus position profile that can be experienced by a user operating a haptic device.
The position profile illustrates how cells are associated and distributed at different stages of the spermatogenic cycle.
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Using the k-means algorithm, we further classify individuals into k clusters based on the motif position profiles.
Overall, 468 speed profiles and 468 lateral position profiles were plotted to obtain the descriptive variables of the driver behavior during the interaction with the cyclist.
Within this scenario, the present paper reports a method for reducing the total energy consumption of pick-and-place manipulators for given TCP position profiles.
In this manner, the robot work cycle can be energetically optimized also when the TCP position profiles have been already defined on the basis of technological constraints and/or design choices aimed at guaranteeing manufacturing process efficacy/robustness.
The entire data analysis of eye position profiles was performed on the basis of single trials.
Eye position profiles were low-pass filtered at 40 Hz, eye velocity profiles at 10 Hz (Butterworth, first order).
The nucleosome positioning profile was generated as described [ 51].
The resulting combined profile was wavelet-smoothed to generate the final nucleosome positioning profile.
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