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As the proposed modeling method provides machine-processability, platform-independence, and semantic interoperability to business process models, collaborative business can be performed more efficiently.
The strong correlation between wire deflection and overall machine extension indicates that the method provides a promising means of assessing fracture site motion.
The numerical method provides an inexpensive and time saving alternative to study the performance of machining before actual cutting operation.
This method provides a reference for the error identification of the non-orthogonal five-axis NC machine tool.
CT provided machine learning expertise and guided the study.
Designing prototypes, with anticipation of their eventual manufacture by machine methods, provided a way of exploring the forms and materials as well as the parts and wholes of products.
Contouring control is an effective method of providing precision machine tool control, and various such methods have been proposed to date.
Therefore, the proposed methods provide an effective path for machine tool volume positioning error calibration and compensation.
Data mining and machine learning methods provide an in silico counterpart building predictive models based on chemical structure features and other properties, and training sets of known bioactivities.
However, machine learning methods provide important accuracy measures that may help determine the number of features that are important.
Kernels methods provide a powerful framework which combines machine learning with graph theory techniques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com