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We present a unified approach to elections based on a conceptual model built using software patterns.
The regression model built using query (Q_G) can be scaled to be used for each user query.
The analysis is carried out using a 3D numerical model built using one-dimensional finite elements using ADINA software code.
We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone.
We expanded upon a previously designed model built using Arc ModelBuilder® to quantify photomicrographs and scanned images of thin sections.
Therefore a calibration method is proposed based on a Kriging surrogate model built using the uniform design approach.
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Models built using the averaging method avoid this complication.
Models built using the combined performed better than those developed from the Benchmark data set.
Linear or nonlinear latent variable models built using PLS are ideal for such a purpose.
Models built using ALAMO can enforce constraints on the response variables to incorporate first-principles knowledge.
This decision-making is based on models built using the CR learning capability, which is based on the environment information.
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