Numerical Information Retrieval and Modeling for Small Droplet Samples

DOI

10.2991/icacsei.2013.168How to use a DOI?

Keywords

Information retrieval, Data analysis, Biomicrofluidics, Droplets, Modeling.

Abstract

Information retrieval is applied widely in modern digital world. Particularly in chemistry and life science, retrieval technology is used for raw data acquirement, analytical modeling and processing optimization. The complicated microdroplets fabrication can be facilitated through different retrievals. In this work, different information retrieval and analysis were performed through small samples. The linear model could depict general droplet size variation. Nonlinear item was found and then added in this model to ameliorate its effectiveness. The biomicrofluidic droplet variations, as complicated procedure, were described satisfactorily in the optimized nonlinear model. Neural Networks Modeling (NNM) was performed to train the small samples and finally the verification of NNM demonstrated its accuracy for small droplet samples.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - P. He
AU  - L. Xue
AU  - Y. Qi
AU  - L. Zhang
AU  - Y. Lu
PY  - 2013/08
DA  - 2013/08
TI  - Numerical Information Retrieval and Modeling for Small Droplet Samples
BT  - Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)
PB  - Atlantis Press
SP  - 697
EP  - 699
SN  - 1951-6851
UR  - https://doi.org/10.2991/icacsei.2013.168
DO  - 10.2991/icacsei.2013.168
ID  - He2013/08
ER  -