By Mieczysław A. Kłopotek (auth.), Khalid Saeed, Rituparna Chaki, Agostino Cortesi, Sławomir Wierzchoń (eds.)

This publication constitutes the court cases of the twelfth IFIP TC eight overseas convention, CISIM 2013, held in Cracow, Poland, in September 2013. The forty four papers provided during this quantity have been conscientiously reviewed and chosen from over 60 submissions. they're geared up in topical sections on biometric and biomedical functions; development popularity and photograph processing; quite a few features of computing device safety, networking, algorithms, and business functions. The booklet additionally comprises complete papers of a keynote speech and the invited talk.

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Additional resources for Computer Information Systems and Industrial Management: 12th IFIP TC8 International Conference, CISIM 2013, Krakow, Poland, September 25-27, 2013. Proceedings

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IEEE Trans. on Neural Networks 12(2), 181–202 (2001) 15. : Kernel Methods for Pattern Analysis. Cambridge University Press, UK (2004) 16. : Simple and interpretable discrimination. Comput. Stat. Data Anal. 53, 979–989 (2009) 17. : Investigation on spectral structure of gearbox vibration signals by principal component analysis for condition monitoring purposes. Journal of Physics: Conference Series 305(1), art. no. 012075 (2011) 18. : Multidimensional data analysis for condition monitoring: features selection and data classification.

5, 197–227 (1990) 15. : Boosting a weak learning algorithm by majority. Inf. Comput. 121, 256–285 (1995) 16. : An introduction to computational learning theory. MIT Press, Cambridge (1994) 17. : Queries and concept learning. Mach. Learn. 2, 319–342 (1988) 18. : Design of effective multiple classifier systems by clustering of classifiers. In: Proceedings of the 15th International Conference on Pattern Recognition, vol. 2, pp. 160–163 (2000) 19. : Complexity of classification problems and comparative advantages of combined classifiers.

N for each individual data vector from the learning sample (nlearn=600 ) and test sample (ntest = 1283). The obtained scores zi obtained now are analogous to the scores zi defined for the classical canonical discriminant analysis (see eq. (13)) however the obtained now (from spreadgda and plotgda) are projections from the non-linear mapping valid in F . They are shown in Figure 3. One may notice that the projections from the faulty and healthy data vectors are completely disjoint. 9938. 5 Discussion and Concluding Remarks Using real data gathered in field conditions we have investigated the usefulness of some primary discriminant functions in diagnosis of the faulty or healthy state of two planetary gearboxes.

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