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A nonlinear analytical model of the piezoelectric actuator including a ferroelectric-like behavior is built using a Preisach model of hysteresis.
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The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function.
The prediction model of release behaviors was built using a back-propagation (BP) neural network.
Two major steps compose this methodology: first, a simplified process model is built using a PIMS Plant Information and Management Systemm) database, which contains limited information about the process behavior.
Finally, a virtual environment is built using Virtools where customized Building Blocks are created to present interactive deformation behavior.
The tree is built using CLUSTALW and NJPLOT.
BioSunMS is built using Standard Widget Toolkit SWTT).
This model is built using economic and probability theory, coupled with multiple data sets on the health care use of Californians (Medical Expenditure Panel Survey), the behavior of employers (Employment Development Department and the California Employer Health Benefits Survey), and characteristics of California's population (the California Health Interview Survey).
Systems biology models of cell signaling and cellular behaviors have been built using several strategies.
All analyses will be built using the Mplus program and will be adjusted for possible confounding variables (behaviors at baseline and control variables).
Models were built using logistic regressions to assess the predictive value of attitudes toward gender equality on adolescents' sexual behavior, on experiences and on communication.
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