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This approach is based on combined terahertz (THz) spectra and ultrasonic velocity and the use of a least squares support vector machine (LS-SVM).
A dynamic program is designed to determine the value of the flexibility by making use of a least squares Monte Carlo simulation algorithm.
However, reporting on QTL with a marginal significance may be affected by analysis methods, and the use of a least squares regression method perhaps over representing putative QTL.
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In this article we solve the inverse reflector problem for a light source emitting a parallel light bundle and a target in the far-field of the reflector by use of a least-squares method.
Therefore, with the use of a least-squares criterion, the minimization problem in vector notation can be written as hat{Q}= arg underset{mathbf{Q}}{ min}left{{left[varDelta d-f(Q right]}^T{R}^{-1}left[varDelta d-f(Q right]right}, (7).
A March Dollase r value between 0.8 and 1.2 appears to be relatively harmless, and, when discovered, must of course be included in the refinement (as the use of a least-squares refinement requires that the model be complete, i.e. that the experimental data is described exactly by the model with the exception of the random noise).
To achieve that, we propose the use of a recursive least squares estimator whose parameters are updated in real time.
Using protein-stabilised oil-in-water model emulsions, the use of a partial least squares and a multi-linear regression approach for processing and analysis of time-domain NMR data is demonstrated, and benchmarked against the deployment of NIR spectroscopy.
It is based on the use of three-state and PID control, and on the use of a simple least-squares based identification technique.
This finding highlights the importance of good temperature control for the distillation assemblies and for the use of a larger, at least 10 ml, AgNO3 trap.
The other uses the notion of a Least Common Ancestor (LCA).
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