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For practical computation, let us sample spectral reflectance at N wavelengths in the visible range 400 to 700 nm.
The spectra were corrected for instrumental broadening to obtain the intrinsic diamond peak widths [20, 21]. Figure 3b shows a sample spectral simulation.
Or, (b), the atomic filter or some components of our setup (e.g.: laser, optical fiber, sample) spectral shifts the scattered light far enough away from the laser wavelength that it cannot be blocked.
When both are present in a patient's sample, spectral peaks from each species are observed in the same spectrum.
If autopeaks appear at the waveband that not associated with the analyte of interest or any known interferent compositions, a conclusion that the instrumental drift have not been corrected in the sample spectral data can be drawn.
Even if the autopeaks also show at the waveband that belonging to glucose, it's absolutely essential to correct the background from the sample spectral data because of faint spectral variations caused by glucose concentration changes and the severe impact of the background drift.
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Figure 9 One sample spectral-face and the first 10 spectral eigenfaces.
On contrary to classical color spaces, we treat the R, G, and B components as a sampled spectral signal.
Although the tremolite bands are weak in spectra of these samples, spectral features near 2.32 and 2.39 μm could be detected by CRISM if tremolite is present on the martian surface.
Unlike the classical color spaces that treat the R, G, and B (RGB) components of a pixel's color as independent elements, the proposed color space treats RGB as a sampled spectral signal, called a RGB signal.
Kennard-Stone algorithm is based on spectral distance measure and selects a set of samples having a uniform distribution over the predictor space and hence comprises all the sources of variation found in the recorded samples spectral library (Kennard and Stone 1969).
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CEO of Professional Science Editing for Scientists @ prosciediting.com