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One of the companies featured in the article, Drawbridge, applies statistical modeling to data from ad exchanges and Web publishers to determine that several devices belong to the same person.
By adopting this model-driven development process, we have automated the process from data modeling to data distribution.
By adopting this model-driven development process, we have automated the process from business modeling to data distribution and reduced the time taken to implement a new product.
Based on the guidelines, a model-driven development process has also been established to automate the process from business modeling to data distribution.
To explore the extent of this bias, we applied structural equation modeling to data from a prospective study of developmental methylmercury neurotoxicity in the Faroe Islands.
In a study conceptually more similar to the present study, Wellenius et al. (2003) applied multivariate regression modeling to data from multiple exposures of dogs to concentrated ambient air PM to identify an association between silicon and cardiac effects, but studied only the PM fraction of pollution and did not have data on speciated organic compounds.
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Data management of models is further supported by the capability to link models to data and vice versa simulated data to models.
The main limitation lies in conditioning such models to data.
The results of applying the model to data entry screens support the use of the model.
An easy-to-use graphical user interface for fitting the hierarchical model to data is available.
Manual and automatic approaches for converting data from the geological model to data for the FEM numerical model are proposed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com