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The proposed workflow makes use of two separate model correction procedures.
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With respect to the data of the present study it seems as if the component model fitted better, since the results of the correction procedures was quite analogous for simulated and real data.
Nevertheless, further research is necessary to evaluate systematically the performance of different correction procedures (i.e. component models, regression approaches), since the discussion about that topic has not been settled.
A general method, based on original measured data sets and statistical modeling, was developed for simulating the impact of various correction procedures when using different analytical instruments.
The generalization of this approach has also been applied in the modeling of complex physical phenomena and in the understanding of correction procedures and manipulations in economic problems (Luenberger [1975]; Sengupta [1997]).
Imaging correction procedures and data fitting lead to satisfactory experimental results according to the theoretical model.
These procedures are deployed in a synergistic manner to provide mutually corroborating evidence for model correction.
We first present the model correction in a general form, involving both external correction and internal correction.
The aim was to compare two acquisition techniques and various correction procedures.
Extensive measurements are presented, and the different correction procedures are analysed with regard to their repeatability.
The multiplicative and additive correction procedures are implemented using multi-level solution techniques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com