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A high correlation between the samples is achieved by over-sampling.
The PSD shape of the 1/f generated noise samples is achieved from the ACFs of the noise samples generated with the fBm process.
The elevation in the trend apparently shows that the increase in number of aggregated samples is achieved at the minor cost of minimum packets transmission.
The generation of such samples is achieved through Markov Chain Monte Carlo (MCMC) simulations using a MCMC algorithm proposed by the authors.
Evidence for the invariance of the model across both samples is achieved when the constraint of parameters performed in testing the subsequent models does not worsen the fit indices.
Perfect reconstruction from fewer samples is achieved by a blind signal reconstruction algorithm which exploits ℓ p -norm (0 < p < 1) minimization instead of ℓ1 or ℓ1/ℓ2 mixed minimization that are commonly used in existing signal recovery schemes.
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And even before more perfect samples are achieved, lower-tech refinements to the questions asked could also improve results.
Diffraction pattern of samples were achieved by selected area electron diffraction (SAED).
The characterization of lignin samples was achieved by thermogravimetric analysis and FTIR.
Extraction of samples was achieved by vortexing three times with 20 mL of diethyl ether (basic extracts).
The statistical importance of differences between two experimental samples was achieved via two-tailed paired Student's t-tests.
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