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Although our SPECT/CT technique for patient-specific lung parenchyma mass estimation was shown to be accurate, it was only moderately precise.
The LPE estimation was shown to be powerful and effective in case of a small number of replicate arrays [ 73].
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Nonparametric additive regression models for genomic breeding value estimation were shown to estimate breeding values of individuals without phenotypic information with moderate to high accuracy.
Furthermore, the convergence path for PIC-MF with SAGE ML estimation is shown as a dashed line, and the receiver is estimated to converge in five iterations.
The accuracy of estimation is shown to be more accurate and robust than the commonly used single-layer diffusion model.
A unified designing approach for control as well for the state space variables estimation is shown.
The torque loss estimation is shown to capture the main loss effects.
The corresponding fatigue lifetime estimation is shown to be closer to clinical evidence.
Nonparametric spectral density estimation is shown to be self-calibrating and accurate when compared to several other time-domain approaches.
In addition, range obtained through interval estimation is shown to be more credible than certain results of other reliability models.
The inadequacy of the standard notions of detectability and observability to ascertain robust state estimation is shown.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com