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Automatic model generation by compositional modeling is not sufficient for automatic explanation generation in education.
Therefore, this research aims to develop a framework for fully-automated building model generation by integrating data-driven and model-driven methods using LiDAR datasets.
This study focuses on the improvement of automatic DTM (Digital Terrain Model) generation by using the stereo pair images of high-resolution satellite data.
In both cases the time spent in the 3D model generation by means of videogrammetry results much lower and the process is completely automatic requiring no post-processing or filtering work.
The second stage was the topological model generation by combining all the pooled genes and their interactions from all available interaction databases.
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As far as we know, this is the first study to use robust modeling techniques for model generation, followed by external validation to generate and validate symptom-based predictive models of endometriosis in a large prospectively recruited cohort of women across different countries and ethnicities.
As shown in Table 4, the total model generation time by the traditional approach is 51 h, while the proposed semi-automated approach only uses 21 h.
Finally, the illustrative case shows that using the proposed semi-automated approach can reduce the 4D/5D BIM model generation time by 58.8% compared with the traditional method.
To illustrate the model generation process by example, consider a model with quality λ = 20 and consisting of n = 100 active compounds on a total of N = 10,000 compounds.
In the first two it is demonstrated, how the sensor may support compact model generation of packages by measuring the time dependence of the heat flux leaving the package on a certain surface, and by enabling the direct measurement of the thermal transfer admittance parameters of packages.
We present a bipartite Boolean modelling approach supported by automatic model generation, simulation and visualisation in the rxncon software.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com