Download e-book for iPad: Computer Information Systems and Industrial Management: 12th by Mieczysław A. Kłopotek (auth.), Khalid Saeed, Rituparna

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

ISBN-10: 3642409245

ISBN-13: 9783642409240

ISBN-10: 3642409253

ISBN-13: 9783642409257

This booklet constitutes the lawsuits of the twelfth IFIP TC eight overseas convention, CISIM 2013, held in Cracow, Poland, in September 2013. The forty four papers awarded during this quantity have been conscientiously reviewed and chosen from over 60 submissions. they're equipped in topical sections on biometric and biomedical purposes; development acceptance and picture processing; a number of facets of laptop safety, networking, algorithms, and commercial functions. The ebook additionally comprises complete papers of a keynote speech and the invited talk.

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Read or Download Computer Information Systems and Industrial Management: 12th IFIP TC8 International Conference, CISIM 2013, Krakow, Poland, September 25-27, 2013. Proceedings PDF

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Additional info 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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Early drift detection method. In: Fourth International Workshop on Knowledge Discovery from Data Streams (2006) 35. : Tracking recurrent concept drift in streaming data using ensemble classifiers. In: Proceedings of the Sixth International Conference on Machine Learning and Applications, ICMLA 2007, pp. 404–409. IEEE Computer Society, Washington, DC (2007) 36. : Exploiting context when learning to classify. B. ) ECML 1993. LNCS, vol. 667, pp. 402–407. Springer, Heidelberg (1993) 37. : Tracking context changes through meta-learning.

In these appliances the span between fingers is always the same due to used pegs and the hand is isolated from the background, so the taken photograph is of very good quality. In household, we can fix the camera and the contrastive mat on which we put hand. That method lacks pegs so the additional module correcting finger span is required. One can also solve that problem via constructing the appliance consisting of pane of glass and the camera. The hand should be put to the glass and the lens should be installed in a fixed distance to the pane.

Thus we have two samples of faulty and healthy data containing n1=1232 and n2=951 data items appropriately. Taking as a new feature the sum of all the 15 variables, Bartelmus and Zimroz [1] were able to classify – on the base of the proposed feature – about 80 % of all data vectors. To classify the remainder, they needed an external variable indicating for the actual load of the working excavator. The data were more thoroughly investigated in [17, 5, 18]. It appeared that the distribution of the variables is not Gaussian, the data contains a considerable number of outliers, moreover, the covariance structure in the two groups (faulty and healthy) is markedly different.

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Computer Information Systems and Industrial Management: 12th IFIP TC8 International Conference, CISIM 2013, Krakow, Poland, September 25-27, 2013. Proceedings by Mieczysław A. Kłopotek (auth.), Khalid Saeed, Rituparna Chaki, Agostino Cortesi, Sławomir Wierzchoń (eds.)


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