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An indoor simulation experiment was conducted, followed by model recognition and identification of the friction model parameters based on the experimental data.
Thus, 1,4-NADH biomimetic model recognition by HLADH does not significantly depend on the presence of the ribose, pyrophosphate, or adenosine groups to provide chiral products.
Since the well-testing diagnostic plots are arranged nearly ordered in time, the well-testing model recognition could be considered as a time-series classification problem where different types of underlying reservoir models constitute different classes.
This paper presents the design, simulation, fabrication and characterization of a silicon hollow waveguide-based full-field absorbance biosensor and its application for the detection of hydrogen peroxidase (H2O2) using a peroxidase enzyme as a model recognition element.
All experiments are performed using Gaussian Mixture Model recognition system.
This method avoided model recognition and successfully separated season factors from the price change.
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Using pressure derivative data is advantageous for accurate reservoir model recognitions (Onur and Reynolds 2001).
The paper offers a new methodology for modelling, recognition and understanding of electroencephalography (EEG) spatio-temporal data measuring complex cognitive brain processes during mental tasks.
Finally, we are modelling recognition using a paradigm that some believe taps mostly 'familiarity' based, as opposed to context-dependent 'recollection' based recognition memory (Aggleton and Brown, 1999).
Applications to meshing, motion planning, visibility preprocessing, model-based recognition, molecular modeling, and geographical information systems will be used throughout to motivate the material.
A few examples include Markov models of recognition and recall, Markov models of logical and scientific reasoning, multinomial models of mathematical reasoning, and multinomial models of false recognition and recall.
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