As with all manufactured engineering products, castings can suffer from errors of shape and size.
Such a conclusion would require dynamic PET imaging over exceptionally long imaging times (>4.5 h), flawless co-registration of PET images, and voxel-by-voxel (to limit the influence of averaging and co-registration errors on shape of the TAC), for instance, using spectral analysis, a method that does not a priori assume a compartment model type [29].
Given the error and change of error of motion, shape and appearance models in the last prediction, these rules are used to determine the fuzzy membership degrees that can be used to substitute the association probabilities between the objects and the measurements (or detection responses).
To estimate the amount of measurement error for shape, we carried out Procrustes ANOVA [16] for a subsample of 72 flies for which two images of each wing were taken and each image was digitized twice.
This chapter describes the errors of form in different engineering shapes.
The ray-tracing results suggest that this resolution can be improved to be less than 10 μm by decreasing the size of mesh holes and the error of the mesh shape.
We compare our LM and other LMs with similar number of points in terms of shape approximation error and landmark detection error.
The focus of our analysis was to demonstrate the influence of three sources of error on the shape and interpretation of concussion injury risk curves: sampling variability associated with a rare event, concussion under-reporting, and sensor measurement error.
Longer waves are produced by errors in the path of the tool effecting cause of the departures from its intended shape, such as roundness errors, straightness errors, or even errors of form.
The proposed algorithms, based on propagation of error probabilities and shape of erroneous waveforms, are scalable to very large circuits.
