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1 C. Zhu, "Improved multi-kernel classification machine with Nyström approximation technique and Universum data," Neurocomputing, vol. 175A, pp. 610-634, 2016./ View Article
2 S. Chen, "Model-based analysis of user behaviors in medical cyber-physical systems," Ph.D. dissertation, University of Pennsylvania, PA, 2016./ View Article
3 T. Simpson and T. Dao, "WordNet-based semantic similarity measurement," 2016; http://www.codeproject.com/Articles/11835/WordNet-based-semantic-similarity-measurement./ View Article
4 X. Zhou, Q. Wan, W. Zhang, X. Xue, and Y. Wei, "Modelbased deep hand pose estimation," in Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, 2016./ View Article
5 S. Gattupalli, A. Ghaderi, and V. Athitsos, "Evaluation of deep learning based pose estimation for sign language," 2016; http://arxiv.org/pdf/1602.09065v3.pdf./ View Article
6 M. N. I. Qureshi, B. Min, H. J. Jo, and B. Lee, "Multiclass classification for the differential diagnosis on the ADHD subtypes using recursive feature elimination and hierarchical extreme learning machine: structural MRI study," PLoS One, vol. 11, no. 8, article no. e0160697, 2016./   DOI View Article
7 M. Nancel, D. Vogel, and E. Lank, "Clutching is not (necessarily) the enemy," in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea, 2015, pp. 4199-4202./ View Article
8 J. Nayak, B. Naik, and H. S. Behera, "Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014," in Computational Intelligence in Data Mining-Volume 2, New Delhi: Springer India, pp. 133-149, 2015./ View Article
9 A. A. Nasr, N. A. El-Bahnasawy, and A. El-Sayed, "Task scheduling algorithm for high performance heterogeneous distributed computing systems," International Journal of Computer Applications, vol. 110, no. 16, pp. 23-29, 2015./   DOI View Article
10 W. Zheng, L. Tang, and R. Sakellariou, "A priority-based scheduling heuristic to maximize parallelism of ready tasks for DAG applications," in Proceedings of 2015 15th IEEE/ ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), Shenzhen, China, 2015, pp. 596-605./ View Article