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Some non-parametric topic models can automatically select the number of topics as part of the model training procedure itself.
On the other hand, various machine learning (ML) models can automatically infer efficient rules (input transformations) from annotated corpora reducing development and maintenance costs.
These models can automatically be derived from the reaction scheme and dynamic simulations can be performed by scanning parameters of the normalized models.
The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge.
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Based on the above information models, our framework can automatically compare the response time of services on different cloud resources and use appropriate cloud resources for offloading.
The proposed model can automatically satisfy the continuity of transverse shear stresses at interfaces.
The proposed model can automatically adapt for different materials experiencing different local failure modes.
The cracking information is not required for multiaxial fatigue analysis and the proposed model can automatically adapt for very different materials experiencing different failure modes.
The proposed model can automatically find the new clustering center with the updated sample data, and outperforms several algorithms in data processing for the OWS.
We demonstrate how a sequence model and asampling-based planner can influence each other to produceefficient plans and how such a model can automatically learnto take advantage of observations of the environment.
Since an expert compensator is designed to suppress the external disturbance, the proposed model can automatically update the optimal set-point value for the furnace temperature of each zone under the varying boundary conditions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com