Nur Kelesoglu, MSc Eng. Email: Orcid ID: 0000-0002-0306-7281Position: research assisstantResearch groups Security, Modelling and Performance Evaluation Group Room: 117b Horizontal TabsPublications Biblio RSS Submitted 1. Kelesoglu, N., M. Halama, and A. Strzoda, "Enhancing LoRa-based Outdoor Localization Accuracy Using Machine Learning", IEEE Access, 2025, Submitted. 2. Kelesoglu, N., M. Halama, and A. Strzoda, "Enhancing LoRa-based Outdoor Localization Accuracy Using Machine Learning", IEEE Access, Submitted. 2025 3. Kelesoglu, N., Ł. Sobczak, P. Biernacki, J. Domańska, F. Ferrão, S. Mumtaz, and F. Tchuenbou-Magaia, Artificial Intelligence for Electronic-based Systems in Safety Applications, 02/2025. 2024 4. Nakip, M., N. Kelesoglu, and C. Güzeliş, "Fire Detection and Risk Assessment via Support Vector Regression with Flattening-Samples Based Augmented Regularization", Applied Soft Computing, vol. 164, 10/2024. 5. Kelesoglu, N., and Ł. Sobczak, "ZigBeeNet: Decrypted ZigBee IoT Network Traffic Dataset in Smart Home Environment", Applied Sciences, vol. 14, issue 23, 11/2024. 2023 6. Kelesoglu, N., K. Filus, and J. Domańska, "HierAct: a Hierarchical Model for Human Activity Recognition in Game-Like Educational Applications", 2023 IEEE International Conference on Big Data, Sorrento, Italy , IEEE, 01/2024, 2023. 2021 7. Saylam, A., R. Orhan Cikmazel, N. Kelesoglu, M. Nakip, and V. Rodoplu, "Energy-Efficient Indoor Positioning for Mobile Internet of Things Based on Artificial Intelligence", ASYU2021 : IEEE, 2021. (1.79 MB) 8. 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) Projectsiitis employee projects: 1. Leveraging AI for Generation Realistic Network Traffic: A Descriptive Input Approach (IITIS/BW/05/25, 2025 - 2025) 2. Zaawansowane narzędzie utrzymania i diagnostyki aplikacji dla Start-upów IT (FENG.01.01-IP.01-A0GV/24-00, 2025 - 2027)
