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An analytical method for computation of the deviation is developed.
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Using the height variation along the periphery of objects present in the data, a method based on standard deviation was developed to distinguish between tree and building.
Although one-half standard deviation was developed as an anchor for health-related quality of life, for CAARS-Inv:SV and CGI-ADHD-S standardized differences, the same one-half standard deviation was used as a reference.
A method of finding scanner parameters that provides least point deviations is developed using least squares.
In the simulation, a mathematical model considering the particular deviations is developed and then the characteristic diagrams are prepared for every deviation and every three-axis control motion.
In the present work, a new subspace decomposition approach of fault deviations is developed in the context of principal component analysis (PCA) based monitoring system for fault diagnosis via reconstruction.
A linear alignment procedure for the expected range of deviations was developed for the correction of small random deviations in flow velocity and MCC temperatures and was validated using a gas mixture of analytes with a range of retention times.
An optimal linear discrete-time deviation controller is developed.
A new heuristic algorithm, i.e., the minimum deviation algorithm, is developed to solve the problems.
Combining dynamic train regulation and passenger flow control, a dynamic optimisation problem that minimises the timetable and the headway deviations for metro lines is developed.
A mathematical prediction model for estimating the standard deviation of the final surface is developed in terms of the above scanning parameters using response surface methodology (RS M.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com