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Current proposals for conceptual multidimensional modelling focus on the design of static data warehouse structures, but few approaches model the queries which the data warehouse should support by means of OLAP (on-line analytical processing) tools.
Further, certain approaches model biological organisms and cognitive processes using algorithms.
Traditional approaches model consciousness as the outcome either of internal computational processes or of cognitive structures.
In the last decades, the long-term structural health monitoring of civil structures has been mainly performed using two approaches: model- and data-based.
Many existing prediction approaches model concurrent behaviour insufficiently and yield inaccurate results due to hard underlying assumptions.
These approaches model the cell as a 'topology of molecular action', as I will call it, and it involves concepts of spaces, surfaces and movements.
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The original methodology uses an iterative three-stage modeling approach: Model identification and model selection.
In this paper will be described transformation approaches model-to-model and model-to-text.
We make use of quantitative experimental approaches, modeling, and theory.
To overcome such problems of data-driven approaches, model-driven methods generally are able to estimate landmark positions - even for total occlusions - by using global context.
To test the different modeling approaches, models were built using the same training/test set data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com