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The ResNet model is then combined with the volume-of-fluid (VOF) method to integrate the description of the local conductivity (electronic and ionic) in the prediction of electrochemical performance.
Program development was part of the next step of Intervention Mapping (step 4), but because of comprehensibility and readability of this paper we decided to integrate the description of the program outline in the methods and strategies section.
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This method relies on integrating the description of the functional architecture with a formal network description and using that formal network description to provide access to analysis generation technologies.
A complete formulation of the computational features of the model, summarizing and integrating the description given in this section, is reported in Appendix A. The neural network model of the left-perisylvian language cortex described in the previous section was used to simulate brain processes of early language acquisition.
Then, a third resource may integrate the shape description vector produced in step two with clinical, demographic or genetic patient data to allow for such multispectral analysis of the patient and organ of interest.
In this paper, we efficiently integrate the LWDF methodology with hardware description languages (HDLs), and we apply this HDL-integrated form of the methodology to develop efficient methods for low power DSP hardware implementation.
Other models integrate the glucose HbA1c relationship into a description of drug pharmacokinetics and pharmacodynamics based on clinical data, which offers a framework for prediction of HbA1c based on clinical trial data.
Nonlinear mixed‐effect modeling (NLME) enables variability among individuals to be integrated into the description of any given process.
This description helps to integrate the key marketing and entrepreneurship concepts.
If the knowledge graph has page descriptions, we can integrate the semantic relatedness (we adopt cosine similarity between the context of an entity and the input document in our experiments) and the prior probability to decide the correct mapping.
It also attempts to integrate the various estimates into a more comprehensive description of the epidemiology.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com