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The model is validated experimentally with a number of part configurations with favorable results.
The model parameters related to the process time estimation of the lay-up procedure were analyzed and modified for different part configurations.
Fig. 3 Graph of the part configurations of our model.
Third, our model formulation is flexible enough to incorporate different features and part configurations, so other interaction classes can be easily trained.
(g) Flexibility Flexibility of a CNC turning centre relates to its ability to deal with the changing part configurations to allow variations in part assembly and process sequence, and changes in production volume and product design.
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Part configuration underlies the perceptual measures because it determines the shapes of objects to a large degree.
Labeling appears to follow the natural breaks of perception and behavior; consequently, part configuration also underlies communication measures.
We propose that part configuration underlies the various empirical operations of perception, behavior, and communication that converge at the basic level.
In order to determine an optimal process condition, major parameters (i.e., part configuration, blank configuration, and blank material) are explored.
The four-dimension (4D) is created by the predictable change in 3D printed part configuration over time as the result of shape-memory functionality.
The scoring for a part configuration in image I is given by: Sleft(boldsymbol{I},boldsymbol{l}right kern0.5em =kern0.5em {vartheta}_{boldsymbol{s}}left(sum limits_{iin V}{boldsymbol{w}}_icdot {phi}_ileft(boldsymbol{I},{boldsymbol{l}}_iright)right kern0.5em +kern0.5em sum limits_{ijin E}{boldsymbol{w}}_{ij}cdot psi left({boldsymbol{l}}_i-{boldsymbol{l}}_jright) (1).
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