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Bacteria in such a film are embedded in a polymer matrix, which makes them harder to kill than isolated individuals.
Here, we propose a modified estimator based on the QR decomposition for solving the multicolinearity problem of design matrix, which makes the data to be less distorted than the other methods.
This proposed scheme is comprised of pre-coder, efficient transformation scheme followed by adaptive Huffman encoding/decoding in conjunction with quantization of image matrix which makes overall compression system lossy in nature.
The proposed method combines backstepping methods and active control without having to calculate the Lyapunov exponents and the eigenvalues of the Jacobian matrix, which makes it simple and convenient.
Mechanism that iron-rich nanoparticles are uniformly captured in the matrix was described, which is that numerous nanoparticles follow Brownian motions and are engulfed in the solidified matrix which makes it possible to form uniformly distributed nanoparticles reinforced single crystal Cu-1wt.
For complex symbols, the pseudo-covariance matrix C u is generally equal to the zero matrix, which makes the matrix (boldsymbol {R}_{widetilde u}) of full rank.
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This ended up in the development of an observation matrix, which made the field notes more structured.
For each respondent, quotes related to each identified theme were entered into a matrix, which made it easier to see the similarities and discrepancies among themes.
These additional matrix variables decouple the Lyapunov and the system matrices, which makes the control design feasible.
It is the factoring of the interpolation matrices which makes it possible to apply the WENO methodology in the reconstruction used in the semi-Lagrangian update.
The obtained matrix inequality conditions can be transformed to linear matrix inequality ones with the introduction of some free matrices, which makes the analysis and design procedure simple and reliable.
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