Abstract
Streptococcus pneumoniae is a bacterial pathogen that causes many life-threatening diseases and an effective vaccine against this pa-thogen is still subject of research. These bacteria grow with low carbon dioxide production, which hinders the application of exhaust gas composition for on-line process monitoring. This work investigates the proposal of a committee of neural networks for identifying Streptococcus pneumoniae growth phases, to be used for on-line state inference. The committee results as well as the accuracy for predicting the culture phases are compared to the results of a unique neural network, for different input variables. The best configuration for the software was: a committee of three NN trained with two input attributes (optical density and mass of alkali solution), 200 epochs of training and log sigmoid as the activation function in the hidden layer as well as in the output layer.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bricks, L.F., Berezin, E.: Impact of pneumococcal conjugate vaccine on the prevention of invasive pneumococcal diseases. J. Pediatr (R. J.) 82(3 Suppl), S67–74 (2006)
Shuler, M.L., Kargi, F.: Bioprocess Engineering: Basic Concepts, 2nd edn. Prentice-Hall, Englewood Cliffs (2001)
Hoeprich, P.D.: Carbon-14 labeling of Diplococcus pneumoniae. J. Bacteriol. 69, 682–688 (1955)
Gonçalves, V.M., Zangirolami, T.C., Giordano, R.L.C., Raw, I., Tanizaki, M.M., Giordano, R.C.: Optimization of medium and culture conditions for capsular polysaccharide production by Streptococcus pneumoniae serotype 23F. Applied Microbiology and Biotechnology, Germany 59, 713–717 (2002)
Dische, Z., Shettles, B.: A specific color reaction of methylpentoses and a spectrophotometric micromethod for their determination. J. Biol. Chem. 175, 595–603 (1948)
Eilers, P.H.C.: A Perfect Smoother. Analytical Chemistry 75(14), 3631–3636 (2003)
Giordano, R.C., Bertini, J.R., Nicoletti, M.C., Giordano, R.L.C.: On-line filtering of CO 2 signals from a bioreactor gas outflow using a committee of constructive neural networks. Bioprocess and Biosystems Engineering (2007) (accepted for publication)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Horta, A.C.L., Zangirolami, T.C., do Carmo Nicoletti, M., Montera, L., Carmo, T.S., Gonçalves, V.M. (2008). An Empirical Investigation of the Use of a Neural Network Committee for Identifying the Streptococcus Pneumoniae Growth Phases in Batch Cultivations. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds) New Frontiers in Applied Artificial Intelligence. IEA/AIE 2008. Lecture Notes in Computer Science(), vol 5027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69052-8_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-69052-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69045-0
Online ISBN: 978-3-540-69052-8
eBook Packages: Computer ScienceComputer Science (R0)