This page is devoted to show the supplementary materials for the paper entitled "A Pattern-based
Approach for Detecting Pneumatic Failures on Temporary Immersion Bioreactors" accepted as
regular paper in Sensors journal since 2019.
Temporary Immersion Bioreactors (TIBs) are widely used for increasing plant quality and plant
multiplication rates. These TIBs are actioned by mean of a pneumatic system. A failure in the
pneumatic system could produce severe damages into the TIB. As a consequence, the whole biological
process would be aborted, increasing the production cost. Therefore, an important task is to detect
failures on a temporary immersion bioreactor system. In this paper, we propose to approach this task
using a contrast pattern based classifier. We will show that our proposal, for detecting pneumatic
failures in a TIB, outperforms other approaches reported on in the literature. Also, we introduce a
new feature representationfor a new micropropagation pineapple database, which is used for detecting
four new types of pneumatic failures on TIBs. Finally, we provide the result of an in-depth analysis
of our experimental results; this analysis was carried out together with experts in both
biotechnology and pneumatic devices.
CD diagrams with a statistical comparison of the classification results and statistical results using Friedman's test (as a non-parametric test) and Shaffer static procedure (as a post-hoc procedure) [1]. The post hoc comparisons contain α = 0.05, α = 0.10, and adjusted p-values. ->
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[2] J. G. Moreno-Torres, J. A. Saez, and F. Herrera, “Study on the Impact of Partition-Induced Dataset Shift on k-Fold Cross-Validation,” Neural Networks Learn. Syst. IEEE Trans., vol. 23, no. 8, pp. 1304–1312, Aug. 2012.
[3] O. Loyola-González, Miguel Angel Medina-Pérez, José Fco. Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa, Raúl Monroy, Milton García-Borroto, PBC4cip: A new contrast pattern-based classifier for class imbalance problems, Knowledge-Based Systems, Volume 115, pp. 100-109, 2017.