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Mayr, et al. [58, 59, 60], combined the advantages of FDM and FEA to simulate the thermo-mechanical behavior of machine tools (shown in Figure 6).
In recent years, the numerical studies for evaluating the behavior of machine vibration foundation have been conducted, but the design using the approximate analytical solution [9] still has been made a lot in the practice.
However, in order to observe the exact behavior of machine, the Magnetic-Equivalent-Circuit (MEC) and nonlinear B H curve are proposed to provide an insight into the machine model and saturation effect respectively.
Motivation: In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions.
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To develop Markov model for the transient behavior of machining system described in the previous section, the state-dependent transition rates for all the system states are to be specified.
Nonetheless, there is a slightly better behavior of machine-learning on traits with a small number of genomic regions affecting the outcome of the trait.
By means of a mathematical model of the machine, the mechanical behavior of the machine itself and hence the range figures of possible projectiles are computed.
In human-machine systems, a user predicts the behavior of a machine using partial or abstracted information provided by a user-interface.
Universal machines do this by executing instructions that encode the behavior of the machine they simulate.
Notice that Leibniz's strategy here is to contrast the overt behavior of the machine, which might appear to be the product of conscious thought, with the way the machine operates internally.
In the new business model, the quality and behavior of a machine tool not only affect the quality of the parts it manufactures, but also affect the profits of the machine tool's manufacturer.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com