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Interestingly, critical illness has the potential to become a key testing ground and field of application for these emerging modeling techniques, given the increasing availability of point-of-care testing and the need for titrated interventions in this patient population.
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In addition, the building information modeling and parametric modeling techniques are given in detail followed by the topics of the development of the application program interface and graphical user interface.
Analytical and numerical results are presented, and an assessment of each of the four modelling techniques is given.
Finally, some recommendations on the interpretation of the results from different modeling types or approaches and potential advantages of certain modeling techniques in future studies are given.
This paper gives an overview and recent developments on the knowledge based neural modeling techniques in microwave modeling and design.
Consequently, guidelines are given on good practices for overcoming the intrinsic limitations of 1D beam concept modeling techniques.
Given the improvement in computation tools, it is also possible to conduct evaluation using modeling techniques, thereby significantly reducing experimental workload.
Modeling techniques such as latent class models provide information on both observer bias and whether observers have different thresholds at which they change the score given.
Comparisons among the modelling techniques are also given.
Two modeling techniques were used.
More details about the acoustic modeling techniques are given in the subsequent sections: HMM/GMM — We employ a conventional three-state left-to-right context-dependent HMM/GMM trained on acoustic parameters (MFCCs in the case of the baseline systems).
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