By Yanglv Ling
These complaints of the 2014 Pacific-Asia Workshop on Computational Intelligence in commercial software (CIIA 2014) comprise eighty one peer-reviewed papers. the themes lined within the e-book contain: (1) desktop Intelligence, (2) software of computing device technological know-how and verbal exchange, (3) business Engineering, Product layout and production, (4) Automation and regulate, info know-how and MEMS.
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Additional resources for Computational intelligence in industrial application : proceedings of the 2014 Pacific-Asia Workshop on Computer Science in Industrial Application (CIIA, December 8-9, 2014, Singapore)
Lou, T. & J. Tang (2013). Mining structural hole spanners through information diffusion in social networks. In Proceedings of the 22nd international conference on World Wide Web, pp. 825–836. International World Wide Web Conferences Steering Committee. , J. Guan, & Y. Zhao (2008). Bringing pagerank to the citation analysis. Information Processing & Management 44(2), 800–810. Meng, Q. & P. J. Kennedy (2013). Discovering influential authors in heterogeneous academic networks by a co-ranking method.
In this way, students have more chance to analyze, explore and solve problems actively, and then have the knowledge internalized. 1 Generativity of teaching resources With the change of educational subjects, the providers of learning resources have changed. indd 29 04/04/15 3:35 PM according to his experience. In as age of big data, however, the teacher takes not only the role of “teacher” in a traditional meaning, but also the role of analyst. Data collection and learning analytics, can free teachers from the traditional teaching.
Tasks inserted barrier gate into need to wait until all tasks within the super-step to finish for interactive m ∑ | oldCenters[ i ][ j ] − newCenter[i ][ j ] | j= 0 13. If the deviation is acceptable, then return else update the old Center[i] to new Center[i]; 14. peer. Reopen Input (); //point back to the initial data and proceed the next iteration. 15. Write the clustering results into output file. Key means cluster id(start from 0) and value is the data object 16. 87GHz. 0. We test and evaluate the algorithm on different kinds of datasets .