Computer Information Systems and Industrial Management: 14th by Khalid Saeed, Wladyslaw Homenda

By Khalid Saeed, Wladyslaw Homenda

This e-book constitutes the court cases of the 14th IFIP TC eight overseas convention on machine details structures and business administration, CISIM 2015, held in Warsaw, Poland, in September 2015.
The forty seven papers provided during this quantity have been conscientiously reviewed and chosen from approximately eighty submissions. the most themes coated are biometrics, defense platforms, multimedia, class and clustering with purposes, and commercial management.

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Extra resources for Computer Information Systems and Industrial Management: 14th IFIP TC 8 International Conference, CISIM 2015, Warsaw, Poland, September 24-26, 2015, Proceedings

Example text

To answer these questions, one needs also data sample from a ’bad’ machine. The bad data sample should be provided as another data matrix with d columns containing values of the same variables as those measured for the ’good’ matrix B. A survey of methods and papers dealing with this question may be found, for example, in [1,5,6,8,10,13,21]. – For the problem: How to detect the fault possibly early? g. [11]. g. [3,18,20], and references therein. – Say, we have data only for a machine in good condition.

Thus, we expect better soft-computing- than human-based performance. This concerns both music genre and emotion recognition. During its early stages, MIR focus was on studies that allowed for searching for music information through QBH, Query-by-Humming/Singing/Whistling. Since singing or whistling is a natural ability of humans, humming to a microphone seemed to be the most convenient way to search for a given melody. Full representation of a non-polyphonic piece is often called ‘melody profile’.

These background notions are to be shortly reviewed with a focus on whether they need to be readdressed by MIR community. The aim of this paper is paper is two-fold. First of it discusses MIR-related research and background measures utilized in music services. Secondly, it is to answer a question concerning usage of soft computing versus statistics, namely: why and when each of them should be employed. Section 2 reviews state-of-the-art in MIR in the context of search-based analysis, while in Section 3 issues related parametrization and soft-computing-based approach to genre classification are shown.

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