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This paper studies adaptive thinning strategies for approximating a large set of scattered data by piecewise linear functions over triangulated subsets.
In sheet metal forming applications, errors of formed parts due to springback can be compensated by offsetting tool surfaces, which are often defined by a set of scattered data points in FE forming simulation.
The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors.
How to reconstruct the scene (a visible surface) from a set of scattered, noisy and possibly sparse range data is a challenging problem in robotic navigation and computer graphics.
A mesh-free method does not require a mesh to discretize the domain of the problem under consideration, and the approximate solution is constructed entirely based on a set of scattered nodes.
Since the newly developed method is a meshless approach, it does not require any background mesh structure to obtain semi-discrete solutions of the problem under consideration, and the numerical solutions are constructed entirely based on a set of scattered nodes.
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Sisense provides a set of proprietary tools and features that enables cybersecurity companies to quickly analyze huge sets of scattered data.
For two sets of scattered point clouds, the curvature of each point is estimated by using the quadratic surface fitting method.
These sets of scattering waveform responses representing normal and damage conditions are transformed into a set of novelty indices that ultimately determine the true conditions of the tested structure.
Here, μ′ s was calculated for λ ∈ [400 – 900] nm in 50 nm increments with a2 = −1.0 (which is typical for tissue [ 22]) and a1 adjusted to calculate three different sets of scattering profiles, such that μ′ s (800nm) = [0.5,1.0,2.0] mm−1 respectively; this yielded 33 μ′ s values in total.
This set of scatter plots shows a pattern seen throughout the SAS responses, with full-semester and private school cohorts less dispersed overall than partial-semester and public school cohorts.
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