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2. Nakip, M., and E. Gelenbe, "Randomization of Data Generation Times Improves Performance of Predictive IoT Networks", 7th IEEE World Forum on the Internet of Things, New Orleans, Louisiana, USA, IEEE, 2021.  (968.83 KB)
6. Çakan, E., A. Şahin, M. Nakip, and V. Rodoplu, "Multi-Layer Perceptron Decomposition Architecture for Mobile IoT Indoor Positioning", 7th IEEE World Forum on the Internet of Things: IEEE, 2021.  (262.85 KB)
7. Nakip, M., and E. Gelenbe, "MIRAI Botnet Attack Detection with Auto-Associative Dense Random Neural Network", 2021 IEEE Global Communications Conference, Barcelona, IEEE, 7-11 Dec 2021.  (857.52 KB)
8. Gelenbe, E., M. Nakip, D. Marek, and T. Czachórski, "Diffusion Analysis Improves Scalability of IoTNetworks to Mitigate the Massive Access Problem", 2021 Mascots: 29th International Symposium on the Modelling, Analysis and Simulation of Computer and Telecommunication Systems, Houston, Texas, USA, IEEE, 11/2021.  (1.99 MB)
11. Saylam, A., N. Kelesoglu, R. Orhan Cikmazel, M. Nakip, and V. Rodoplu, "Dynamic Positioning Interval Based On Reciprocal Forecasting Error (DPI-RFE) Algorithm for Energy-Efficient Mobile IoT Indoor Positioning", International Conference on Computer, Information and Telecommunication Systems (CITS), Istanbul, Turkey, IEEE, 2021.  (364.76 KB)
12. Nakip, M., A. Asut, C. Kocabıyık, and C. Güzeliş, "A Smart Home Demand Response System based on Artificial Neural Networks Augmented with Constraint Satisfaction Heuristic", 13th INTERNATIONAL CONFERENCE on ELECTRICAL and ELECTRONICS ENGINEERING (ELECO), Bursa, Turkey, IEEE, 2021.  (387.52 KB)