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

Articles in Journals

  • M. Kamarei, A. Patooghy, A. Alsharif, and V. Hakami, “SiMple: A Unified Single and Multi-Path Routing Algorithm for Wireless Sensor Networks with Source Location Privacy,” IEEE Access, vol. 8, pp. 33818–33829, 2020.
  • P. Shamsolmoali, M. E. Celebi, and R. Wang, “Deep Learning Approaches for Real-Time Image Super-Resolution,” Neural Computing and Applications, vol. 32, no. 18, pp. 14519–14520, 2020.
  • P. Shamsolmoali, M. E. Celebi, and R. Wang, “Advances in Deep Learning for Real-Time Image and Video Reconstruction and Processing,” Journal of Real-Time Image Processing, vol. 17, no. 6, pp. 1883–1884, 2020.
  • S. Thompson, M. E. Celebi, and K. H. Buck, “Fast Color Quantization Using MacQueen’s K‑Means Algorithm,” Journal of Real-Time Image Processing, vol. 17, no. 5, pp. 1609–1624, 2020.
  • A. R. Sadri, M. E. Celebi, N. Rahnavard, and S. E. Viswanath, “Sparse Wavelet Networks,” IEEE Signal Processing Letters, vol. 27, pp. 111–115, 2020.
  • S. Zhang, H. Zhou, D. Xu, M. E. Celebi, and T. Bouwmans, “Introduction to the Special Issue on Multimodal Machine Learning for Human Behavior Analysis,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 16, no. 1s, pp. 1–2, 2020.
  • J. Palmer, V. S. Sheng, T. Atkison, and B. Chen, “Classification on Grade, Price, and Region with Multi-Label and Multi-Target Methods in Wineinformatics,” Big Data Mining and Analytics, vol. 3, no. 1, pp. 1–12, 2020.
  • Z. Dong, X. Guo, S. Rajana, and B. Chen, “Understanding 21st Century Bordeaux Wines from Wine Reviews Using Naïve Bayes Classifier,” 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, “Surgeons with Five or More Actual Cricothyrotomies Perform Significantly Better on a VR Simulator,” Journal of Surgical Research, vol. 252, pp. 247–254, 2020.
  • J. Farmer, D. Demirel, R. Erol, D. Ahmadi, T. Halic, S. Kockara, V. S. Arikatla, K. Sexton, and S. Ahmadi, “Systematic Approach for Content and Construct Validation: Case Studies for Arthroscopy and Laparoscopy,” 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, “A Partition-Based Optimization Model and Its Performance Benchmark for Generative Anatomy Modeling Language,” 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, “Endoscopic Submucosal Dissection: A Cognitive Task Analysis Framework Toward Training Design,” Surgical Endoscopy, vol. 34, no. 2, pp. 728–741, 2020.
  • M. Karakaya and R. E. Hacisoftaoglu, “Comparison of Smartphone-Based Retinal Imaging Systems for Diabetic Retinopathy Detection Using Deep Learning,” BMC Bioinformatics, vol. 21, article no. 259, 2020.
  • R. E. Hacisoftaoglu, M. Karakaya, and A. B.Sallam, “Deep Learning Frameworks for Diabetic Retinopathy Detection with Smartphone-Based Retinal Imaging Systems,” Pattern Recognition Letters, vol. 135, pp. 409–417, 2020.
  • O. Kursun and A. Patooghy, “An Embedded System for Collection and Real-time Classification of a Tactile Dataset,” IEEE Access, vol. 8, pp. 97462–97473, 2020.
  • E. Taheri, M. Isakov, A. Patooghy, and M. A. Kinsy, “Addressing a New Class of Reliability Threats in 3-D Network-on-Chips, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,” vol. 39, no. 7, pp. 1358–1371, 2020.
  • M. Taherifard, M. Fazeli, and A. Patooghy, “Scan-Based Attack Tolerance with Minimum Testability Loss: A Gate-Level Approach,” IET Information Security, vol. 14, no. 4, pp. 459–469, 2020.
  • M. Kamarei, A. Patooghy, Z. Shahsavari, and M. J. Salehi, “Lifetime Expansion in WSNs Using Mobile Data Collector: A Learning Automata Approach,” Journal of King Saud University-Computer and Information Sciences, vol. 32, no. 1, pp. 65–72, 2020.
  • D. Wang, Y. Sun, C. Zhu, W. Li, F. Dufaux, and J. Luo, “Fast Depth and Mode Decision in Intra Prediction for Quality SHVC,” IEEE Transactions on Image Processing, vol. 29, pp. 6136–6150, 2020.
  • Y. Huang, D. Wang, Y. Sun, and B. Hang, “A Fast Intra Coding Algorithm for HEVC by Jointly Utilizing Naive Bayesian and SVM,” Multimedia Tools and Applications, vol. 79, no. 45, pp. 33957–33971, 2020.
  • D. Wang, Y. Sun, C. Zhu, W. Li and F. Dufaux, “Fast Depth and Inter Mode Prediction for Quality Scalable High Efficiency Video Coding,” IEEE Transactions on Multimedia, vol. 22, no. 4, pp. 833–845, 2020.
  • Y. Zhou, L. Tian, C. Zhu, J. Xin, and Y. Sun, “Video Coding Optimization for Virtual Reality 360-Degree Source,” IEEE Journal of Selected Topics in Signal Processing, vol. 14, no. 1, pp. 118–129, 2020.