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Publications (2020)

Below is a list of CS@UCA faculty/student publications in 2020. The names of faculty members and students are displayed in bold and italics, respectively. For 2019 publications, please visit here.

Articles in Conference Proceedings

  • A. Alsharif and M. Nabil, 鈥淎 Blockchain-based Medical Data Marketplace with Trustless Fair Exchange and Access Control,鈥 in Proceedings of the 2020 IEEE Global Communications Conference, 2020.
  • S. J. Mousavirad, G. Schaefer, M. E. Celebi, H. Fang, and X. Liu, 鈥淐olour Quantisation Using Human Mental 海角社区 and Local Refinement,鈥 in Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3045鈥3050, 2020.
  • B. Cetinsaya, J. Dials, D. Demirel, T. Halic, S. De, M. Gromski, and D. Rex, 鈥淐omparison Study of Deep Learning Models for Colorectal Lesions Classification,鈥 in Proceedings of the 2020 the 4th International Conference on Information System and Data Mining, pp. 84鈥88, 2020.
  • B. Palmer, G. Sundberg, J. Dials, B. Karaman, D. Demirel, M. Abid, T. Halic, and S. Ahmadi, 鈥淎rthroscopic Tool Classification Using Deep Learning,鈥 in Proceedings of the 2020 the 4th International Conference on Information System and Data Mining, pp. 96鈥99, 2020.
  • J. Farmer, M. Tunc, D. Ahmadi, D. Demirel, T. Halic, S. Arikatla, S. Kockara, and S. Ahmadi, 鈥淰irtual Rotator Cuff Arthroscopic Skill Trainer: Results and Analysis of a Preliminary Subject Study,鈥 in Proceedings of the 2020 the 4th International Conference on Information System and Data Mining, pp. 139鈥143, 2020.
  • C. Hu and Z. H. Hu, 鈥淥n Statistics, Probability, and Entropy of Interval-Valued Datasets,鈥 in Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 407鈥421, 2020.
  • C. Hu and Z. H. Hu, 鈥淎 Computational Study on the Entropy of Interval-Valued Datasets from the Stock Market,鈥 in Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 422鈥435, 2020.
  • D. E. Kim, R. E. Hacisoftaoglu, and M. Karakaya, 鈥淥ptic Disc Localization in Retina Images Using Deep Learning Frameworks,鈥 in Proceedings of the Disruptive Technologies in Information Sciences IV, 1141904, 2020.
  • F. Rabiee, M. Kajouyan, N. Estiri, J. Fluech, M. Fazeli, and A. Patooghy, 鈥淓nduring Non-Volatile L1 Cache Using Low-Retention-Time STTRAM Cells,鈥 in Proceedings of the 2020 IEEE Computer Society Annual Symposium on VLSI, pp. 322鈥327, 2020.
  • T. Cheng, F. Coulibaly, A. Patooghy, and O. Kursun, 鈥淒ata-Triggered Approach for Real-Time Machine Learning in IoT Systems,鈥 in Proceedings of the 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, pp. 101鈥104, 2020.

Articles in Journals

  • M. Kamarei, A. Patooghy, A. Alsharif, and V. Hakami, 鈥淪iMple: A Unified Single and Multi-Path Routing Algorithm for Wireless Sensor Networks with Source Location Privacy,鈥 IEEE Access, vol. 8, pp. 33818鈥33829, 2020.
  • P. Shamsolmoali, M. E. Celebi, and R. Wang, 鈥淒eep Learning Approaches for Real-Time Image Super-Resolution,鈥 Neural Computing and Applications, vol. 32, no. 18, pp. 14519鈥14520, 2020.
  • P. Shamsolmoali, M. E. Celebi, and R. Wang, 鈥淎dvances in Deep Learning for Real-Time Image and Video Reconstruction and Processing,鈥 Journal of Real-Time Image Processing, vol. 17, no. 6, pp. 1883鈥1884, 2020.
  • S. Thompson, M. E. Celebi, and K. H. Buck, 鈥淔ast Color Quantization Using MacQueen鈥檚 K鈥慚eans Algorithm,鈥澛燡ournal of Real-Time Image Processing, vol. 17, no. 5, pp. 1609鈥1624, 2020.
  • A. R. Sadri, M. E. Celebi, N. Rahnavard, and S. E. Viswanath, 鈥淪parse Wavelet Networks,鈥 IEEE Signal Processing Letters, vol. 27, pp. 111鈥115, 2020.
  • S. Zhang, H. Zhou, D. Xu, M. E. Celebi, and T. Bouwmans, 鈥淚ntroduction to the Special Issue on Multimodal Machine Learning for Human Behavior Analysis,鈥 ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 16, no. 1s, pp. 1鈥2, 2020.
  • J. Palmer, V. S. Sheng, T. Atkison, and B. Chen, 鈥淐lassification on Grade, Price, and Region with Multi-Label and Multi-Target Methods in Wineinformatics,鈥 Big Data Mining and Analytics, vol. 3, no. 1, pp. 1鈥12, 2020.
  • Z. Dong, X. Guo, S. Rajana, and B. Chen, 鈥淯nderstanding 21st Century Bordeaux Wines from Wine Reviews Using Na茂ve Bayes Classifier,鈥 Beverages, vol. 6, no. 1, 5 pages, 2020.
  • D. Qi, E. Petrusa, U. Kruger, N. Milef, M. R. Abu-Nuwar, M. Haque, R. Lim, D. B Jones, M. Turkseven, D. Demirel, T. Halic, S. De, and N. Saillant, 鈥淪urgeons with Five or More Actual Cricothyrotomies Perform Significantly Better on a VR Simulator,鈥 Journal of Surgical Research, vol. 252, pp. 247鈥254, 2020.
  • J. Farmer, D. Demirel, R. Erol, D. Ahmadi, T. Halic, S. Kockara, V. S. Arikatla, K. Sexton, and S. Ahmadi, 鈥淪ystematic Approach for Content and Construct Validation: Case Studies for Arthroscopy and Laparoscopy,鈥 The International Journal of Medical Robotics and Computer Assisted Surgery, vol. 16, no. 4, e2105, 2020.
  • D. Demirel, B. Cetinsaya, T. Halic, S. Kockara, D. Reiners, S. Ahmadi, and S. Arikatla, 鈥淎 Partition-Based Optimization Model and Its Performance Benchmark for Generative Anatomy Modeling Language,鈥 Computers in Biology and Medicine, vol. 119, 103695, 2020.
  • S. Hegde, M. A. Gromski, T. Halic, M. Turkseven, Z. Xia, B. Cetinsaya, M. S. Sawhney, D. B. Jones, S. De, and C. D. Jackson, 鈥淓ndoscopic Submucosal Dissection: A Cognitive Task Analysis Framework Toward Training Design,鈥 Surgical Endoscopy, vol. 34, no. 2, pp. 728鈥741, 2020.
  • M. Karakaya and R. E. Hacisoftaoglu, 鈥淐omparison of Smartphone-Based Retinal Imaging Systems for Diabetic Retinopathy Detection Using Deep Learning,鈥 BMC Bioinformatics, vol. 21, article no. 259, 2020.
  • R. E. Hacisoftaoglu, M. Karakaya, and A. B. Sallam, 鈥淒eep Learning Frameworks for Diabetic Retinopathy Detection with Smartphone-Based Retinal Imaging Systems,鈥 Pattern Recognition Letters, vol. 135, pp. 409鈥417, 2020.
  • O. Kursun and A. Patooghy, 鈥淎n Embedded System for Collection and Real-time Classification of a Tactile Dataset,鈥 IEEE Access, vol. 8, pp. 97462鈥97473, 2020.
  • E. Taheri, M. Isakov, A. Patooghy, and M. A. Kinsy, 鈥淎ddressing a New Class of Reliability Threats in 3-D Network-on-Chips, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,鈥 vol. 39, no. 7, pp. 1358鈥1371, 2020.
  • M. Taherifard, M. Fazeli, and A. Patooghy, 鈥淪can-Based Attack Tolerance with Minimum Testability Loss: A Gate-Level Approach,鈥 IET Information Security, vol. 14, no. 4, pp. 459鈥469, 2020.
  • M. Kamarei, A. Patooghy, Z. Shahsavari, and M. J. Salehi, 鈥淟ifetime Expansion in WSNs Using Mobile Data Collector: A Learning Automata Approach,鈥 Journal of King Saud University-Computer and Information Sciences, vol. 32, no. 1, pp. 65鈥72, 2020.
  • D. Wang, Y. Sun, C. Zhu, W. Li, F. Dufaux, and J. Luo, 鈥淔ast Depth and Mode Decision in Intra Prediction for Quality SHVC,鈥 IEEE Transactions on Image Processing, vol. 29, pp. 6136鈥6150, 2020.
  • Y. Huang, D. Wang, Y. Sun, and B. Hang, 鈥淎 Fast Intra Coding Algorithm for HEVC by Jointly Utilizing Naive Bayesian and SVM,鈥 Multimedia Tools and Applications, vol. 79, no. 45, pp. 33957鈥33971, 2020.
  • D. Wang, Y. Sun, C. Zhu, W. Li and F. Dufaux, 鈥淔ast Depth and Inter Mode Prediction for Quality Scalable High Efficiency Video Coding,鈥 IEEE Transactions on Multimedia, vol. 22, no. 4, pp. 833鈥845, 2020.
  • Y. Zhou, L. Tian, C. Zhu, J. Xin, and Y. Sun, 鈥淰ideo Coding Optimization for Virtual Reality 360-Degree Source,鈥 IEEE Journal of Selected Topics in Signal Processing, vol. 14, no. 1, pp. 118鈥129, 2020.