Sentence examples for estimation in conjunction with from inspiring English sources
Based on the principle of identifying distribution and trends (IDT) with time-varying moments, we employed the parametric weighted least squares (WLS) estimation in conjunction with the non-parametric discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD).
This prospective study presents the results of using serial tumour marker estimation in conjunction with contrast-enhanced CT of the chest, abdomen and pelvis in the follow-up of patients following liver resection for colorectal metastases.
So the enhanced algorithm is designed to combine the estimation results in conjunction with a selection strategy.
To improve the component structural analysis, a phenomenological lifetime estimation approach, in conjunction with a constitutive material model applied in a preceding Finite-Element analysis, for application on the casting materials Ni-resist D5S and GJV was developed and validated.
In normal tracking mode, with continuous flow of data packets, only small CFO and FTD values are expected, and it is enough to use only the estimation algorithms in conjunction with basic time domain compensation methods and some filtering to reduce the random variations of block-wise estimates.
Reconstruction of evolutionary relationships and estimation of divergence time in conjunction with traditional gonococcal surveillance data can assist in understanding the development, impact and public health importance of QRNG.
Specifically, shared weights strategy and a parameter-free correlation layer are exploited to carry out RGB-D-correlated objectness estimation and region-wise recognition in conjunction with RGB-specific and depth-specific procedures.
However, these image features cannot significantly improve the estimation accuracy of winter wheat LAI in conjunction with eight texture measures.
The main novelty in comparison with the above techniques is the use of independent component analysis in conjunction with uncertainty estimation and with a piecewise approach of transforming uncertainties to the feature domain of interest.
2) To address wind power uncertainty, POPF based on a three-point estimation method (3PEM) is introduced, which, in conjunction with the M-GEOPF model, yields a multi-period gas and electric system probabilistic optimal power flow (M-GEPOPF) model.
Though the moment method is not the optimal tool in statistical inference, as compared to maximum likelihood estimation for example, its controlled use in conjunction with the Anderson-Darling and Cramér-von Mises goodness-of-fit statistics remains a first choice in applications depending heavily on moments as the one considered in Hürlimann [41 43].
