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A Review of Feature Selection and Its Methods

-92, 1992, pp. 104-110. 25. Liu, H., R. Setiono. A Probabilistic Approach to Feature Selection – A Filter Solution. – In: Proc. of 13th International Conference on Machine Learning, 1996, pp. 319-327. 26. Siedlecki, W., J. Sklansky. On Automatic Feature Selection. – Int. J. Pattern Recognit. Artif. Intell., Vol. 02 , Jun 1988, No 02, pp. 197-220. 27. Dy, J. G., C. E. Brodley. Feature Subset Selection and Order Identification for Unsupervised Learning. – In: Proc. of 17th Int. Conf. Mach. Learn ICML’00, 2000, pp. 247-254. 28. John, G. H., R

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Algebraic Methods for Traffic Flow Densities Estimation

Mediterrean Conference on Control and Automation (MED.07), 2007. 13. Papageorgiou, M. Traffic Control. Handbook of Transportation Science. Ch. 8. 2001. 14. Muño z, L., X. Su n, Su n, G. Gome s, R. Horowitz. Methodological Calibration of the Cell Transmission Model. - In: American Control Conference, ACC’04, 30 June-2 July 2004, 798-803. 15. Muño z, L., X. Su n, R. Horowitz, L. Alvare z. Traffic Density Estimation with the Cell Transmission Model. - In: American Control Conference, ACC’03

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Appropriate Number of Standard 2 × 2 Max Pooling Layers and Their Allocation in Convolutional Neural Networks for Diverse and Heterogeneous Datasets

:// [20] J. Li, D. Zhang, J. Zhang, J. Zhang, T. Li, Y. Xia, Q. Yan, and L. Xun, “Facial Expression Recognition with Faster R-CNN,” Procedia Computer Science, vol. 107, pp. 135-140, 2017. [21] S. Mukherjee, P. Niyogi, T. Poggio, and R. Rifkin, “Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization,” Advances in Computational Mathematics, vol. 25, no. 1-3, pp. 161-193, Jul. 2006. https

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Natural Language Generation and Semantic Technologies

English and the German Upper Model. Darmstadt, Germany, GMD/ Institute fur Integriente Publikation-and Informations Systeme, 1993. 25. Hovy, E. H., J. Lavid, E. Maier, V. Mittal, C. Paris. Employing Knowledge Resources in a New Text Planner Architecture. - In: R. Dale, E. Hovy, D. Rosner and O. Stock, Eds. Aspects of Automated Natural Language Generation, Berlin, Springer, 1992, 57-72. 26. Joshi, A. K. The Relevance of Tree Adjoining Grammar to Generation. - In: G. Kempen, Ed. Natural Language Generation: Recent Advances in Artificial Intelligence, Psychology, and

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Advanced Control of the Wood Thermal Treatment Processing

Russian). 25. Videlo v, H. Drying and Thermal Treatment of Wood. University of Forestry, 2003, Sofia (in Bulgarian). 26. Vigak, V. M. Optimal Control of Non-Stationary Temperature Regimes. Kiev, Naukova Dumka, 1979 (in Russian). 27. Watson, I. Applying Case-Based Reasoning: Techniques for Enterprise Systems. Morgan Kaufmann, SF, 1977. 28. Welz, C., B. Srinivasan, D. Bonvin. Combined On-Line and Run-to-Run Optimization of Batch Processes with Terminal Constraints. - In: Proc. of ADCHEM’03, 2004

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Evaluation of Payoff Matrices for Non-Cooperative Games via Processing Binary Expert Estimations

References [1] M. J. Osborne, An introduction to game theory, Oxford, UK: Oxford University Press, 2003. [2] N. Nisan, T. Roughgarden, É. Tardos and V. V. Vazirani, Algorithmic Game Theory, Cambridge, UK: Cambridge University Press, 2007. [3] J. Moon and T. Başar, “Minimax estimation with intermittent observations,” Automatica, vol. 62, 2015, pp. 122-133. [4] C. Dong, G. H. Huang, Y. P. Cai, and Y. Xu, “An

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Big Data Analysis of Home Healthcare Services

. [Online].Available: reportdownload-today/ Accessed: Feb. 18, 2016. [24] R. Kosara and J. Mackinlay, Storytelling: The Next Step for Visualization. 2016. [Online]. Available: [25] A. Knebel and S. J. Phillips, Eds., Home Health Care during an Influenza Pandemic: Issues and Resources. AHRQ Publication No. 08-0018. Rockville, MD: Agency for Healthcare Research and Quality, 2008.

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Grinding in Ball Mills: Modeling and Process Control

Grinding Circuit Control System. - In: 15th IFAC Triennial World Congress, Barcelona, Spain, 2002. 25. Hennart, S. L. A., W. J. Wildeboer, P. van Hee, G. M. H. Meesters. Identification of the Grinding Mechanisms and Their Origin in a Stirred Ball Mill Using Population Balances. - Chemical Engineering Science, Vol. 64 , 2009, 4123-4130. 26. Hodouin, D. Methods for Automatic Control, Observation, and Optimization in Mineral Processing Plants. - Journal of Process Control, Vol. 21 , 2011, 211-225. 27. Hodouin, D., S-L. Jamsa

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A Survey on Group Key Management Schemes

Communication. – ACM Computing Surveys, Vol. 35 , September 2003, pp. 309-329. 5. Chiou, G. H., W. T. Chen. Secure Broadcast Using Secure Lock. – IEEE Transactions on Software Engineering, Vol. 15 , August 1989, No 8, pp. 929-934. 6. Harney, H., C. Muckenhirn. Group Key Management Protocol (GKMP) Architecture, July 1997. – In: RFC 2093. 7. Harney, H., C. Muckenhirn. Group Key Management Protocol (GKMP) Specification, July 1997. – In: RFC 2094. 8. Wallner, D., E. Harder, R. Agee. Key Management for Multicast: Issues and Architecture. National Security

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Hybrid Generalised Additive Type-2 Fuzzy-Wavelet-Neural Network in Dynamic Data Mining

. [5] O. Nelles, Nonlinear System Identification. Berlin: Springer, 2001. [6] J.-S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. N.J.: Prentice Hall, 1997. [7] R.A. Aliev and B.G. Guirimov, Type-2 Fuzzy Neural Networks and Their Applications . Switzerland: Springer; 2014. [8] A.K. Alexandridis and A.D. Zapranis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification . John Wiley & Sons, 2014. ttp://

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