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It shows that the proposed method inherits the features of dithering fringe pattern and it has the advantage to be used for large range 3D shape measurement with wide fringe pattern.
Moreover, the proposed method inherits the spatial filtering capability and spectral accuracy of the Fourier spectrum-based modal curvature, which ensures the robustness of the modal curvature calculation in noisy conditions.
The method inherits the main advantage of the IGA-based shape optimization, i.e., the control points are used as design variables, thus the design model, analysis model and optimization model are uniformly described with the NURBS, providing easy communication between the three models and resulting in a smooth optimized boundary.
The superiority of SVMRank probably due to that such a ranking method inherits the maximum-margin characteristics of SVM.
The presented method inherits the spatial filtering capability and the spectral accuracy of the Fourier spectral modal curvature, and features an efficient modal curvature algorithm in absence of the periodic extension.
Furthermore, the use of the marginal likelihood means our method inherits the ease with which side information can be incorporated in probabilistic models.
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The approach is formulated as an optimization problem and then framed into the generalized patterns search method, inheriting the convergence properties, which are a novelty both in the control theory as well as in mathematics.
Not only does the proposed method inherit the attractive characteristics of the locality preserving projections in terms of exploiting the intrinsic manifold structure, it is also appealing in terms of significant reduction in both space complexity and time complexity.
Not only does this method inherit the quickness of BCM and the safety of LCM, but also the proposed prediction based BCM (PBCM) can be used to avoid moving obstacles in dynamic environments.
Simulations confirm that IVX-QR methods inherit the robust properties of QR.
The efficient methods inherit the cascading lower bounds introduced in UCR-DTW, a state-of-the-art method of similarity search in the static time series, to admissibly prune off unpromising subsequences.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com