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Statistical process control for AR(1) or non-Gaussian processes using wavelets coefficients
Cohen, A., Tiplica, T., & Kobi, A. (2015). Statistical process control for AR(1) or non-Gaussian processes using wavelets coefficients. 12th European Workshop on Advanced Control and Diagnosis (ACD 2015), 659. doi:10.1088/1742-6596/659/1/012043
Weighted wavelets coefficients for monitoring process mean
Cohen, A., Tiplica, T., & Kobi, A. (2016). Weighted wavelets coefficients for monitoring process mean. International Conference on Advances in Control and Optimization of Dynamical Systems Tiruchirappalli, India / IFAC-PapersOnline, 49(1), 819-813. doi:10.1016/j.ifacol.2016.03.159
Robot theatre to boost excitement, engagement, and expression (E3) of STEM
Das, A., Doelling, K., Sevil, H. E., & Greer, J. (2018). Robot theatre to boost excitement, engagement, and expression (E3) of STEM. Proceedings of The 12th International Multi-Conference on Society, Cybernetics and Informatics (IMSCI 2018), 76-81.
A rapid situational awareness development framework for heterogeneous manned-unmanned teams
Das, A., Kolaric, P., Lundberg, C., Doelling, K., Sevil, H. E., & Lewis, F. (2018). A rapid situational awareness development framework for heterogeneous manned-unmanned teams. NAECON 2018 - IEEE National Aerospace and Electronics Conference, 417-424. doi:10.1109/NAECON.2018.8556769
A mixed reality based hybrid swarm control architecture for manned-unmanned teaming (MUM-T)
Das, A. N., Doelling, K., Lundberg, C., Sevil, H. E., & Lewis, F. (2018). A mixed reality based hybrid swarm control architecture for manned-unmanned teaming (MUM-T). ASME 2017 International Mechanical Engineering Congress and Exposition; November 3–9, 2017; Tampa, Florida, USA, 14. doi:10.1115/IMECE2017-72076
Determining intruder aircraft position using series of stereoscopic 2-D images
Ramani, A., Sevil, H. E., & Dogan, A. (2017). Determining intruder aircraft position using series of stereoscopic 2-D images. 2017 International Conference on Unmanned Aircraft Systems (ICUAS) June 13-16, 2017, Miami, FL, USA, 902-911. doi:10.1109/ICUAS.2017.7991384
Robotic nursing assistants
Ghadge, A. M., Dalal, A. V., Lundberg, C. L., Sevil, H. E., Behan, D., & Popa, D. O. (2019). Robotic nursing assistants: Human temperature measurement case study. 32nd Florida Conference on Recent Advances in Robotics May 9-10, 2019, Florida Polytechnic University, Lakeland, Florida.
Error minimization and energy conservation by predicting data in Wireless Body Sensor Networks using artificial neural network and analysis of error
Mishra, A., Chakraborty, S., Li, H., & Agrawal, D. P. (2014). Error minimization and energy conservation by predicting data in Wireless Body Sensor Networks using artificial neural network and analysis of error. IEEE 11th Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, 2014. doi:10.1109/CCNC.2014.7056324
Continuous health condition monitoring by 24x7 sensing and transmission of physiological data using 5G cellular channels
Mishra, A., & Agrawal, D. P. (2015). Continuous health condition monitoring by 24x7 sensing and transmission of physiological data using 5G cellular channels. 2015 International Conference on Computing, Networking and Communications (ICNC), Garden Grove, CA, 2015. doi:10.1109/ICCNC.2015.7069410
Scheduling schemes for Interference Suppression in Healthcare Sensor Networks
Jamthe, A., Mishra, A., & Agrawal, D. P. (2014). Scheduling schemes for Interference Suppression in Healthcare Sensor Networks. 2014 IEEE International Conference on Communications (ICC), Sydney, NSW, 2014. doi:10.1109/ICC.2014.6883350
Towards UAV-based post-disaster damage detection and localization
Clevenger, A., De Sa Lowande, R., Sevil, H. E., & Mahyari, A. (2022). Towards UAV-based post-disaster damage detection and localization: Hurricane Sally case study. AIAA SCITECH 2022 Forum, January 3-7, 2022San Diego, CA & Virtual. doi:10.2514/6.2022-0788
Omni directional moving object detection and tracking with virtual reality feedback
Zirakchi, A., Lundberg, C. L., & Sevil, H. E. (2018). Omni directional moving object detection and tracking with virtual reality feedback. ASME 2017 Dynamic Systems and Control Conference; October 11–13, 2017; Tysons, Virginia, USA, 2. doi:10.1115/DSCC2017-5352
Monte Carlo linear solvers with non-diagonal splitting
Srinivasan, A. (2010). Monte Carlo linear solvers with non-diagonal splitting. Mathematics and Computers in Simulation, 80, 1133-1143. doi:10.1016/j.matcom.2009.03.010
Latency tolerance through parallelization of time in scientific applications
Srinivasan, A., & Chandra, N. (2004). Latency tolerance through parallelization of time in scientific applications. Proceedings of the 18th International Parallel and Distributed Processing Symposium (IPDPS’04), 112-123. doi:10.1109/IPDPS.2004.1303067
On the application of machine learning to classify sleep positions
Becker, B., & Alqudah, Y. A. (2020). On the application of machine learning to classify sleep positions. 2020 International Conference on Computational Science and Computational Intelligence (CSCI), 1087-1090. doi:10.1109/CSCI51800.2020.00202
On the development of a model-based embedded systems design laboratory course
Sababha, B. H., AlQaralleh, E. A., & Alqudah, Y. A. (2021). On the development of a model-based embedded systems design laboratory course. 2021 Innovation and New Trends in Engineering, Science and Technology Education Conference (IETSEC). doi:10.1109/IETSEC51476.2021.9440487
GPU-accelerated rapid planar region extraction for dynamic behaviors on legged robots
Mishra, B., Calvert, D., Bertrand, S., McCrory, S., Griffin, R., & Sevil, H. E. (2021). GPU-accelerated rapid planar region extraction for dynamic behaviors on legged robots. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8493-8499. doi:10.1109/IROS51168.2021.9636009
A distributed behavioral model for landmine detection robots
Bayram, C., Sevil, H. E., & Ozdemir, S. (2007). A distributed behavioral model for landmine detection robots, 172-176.
A VisualSfM based rapid 3-D modeling framework using swarm of UAVs
Lundberg, C. L., Sevil, H. E., & Das, A. (2018). A VisualSfM based rapid 3-D modeling framework using swarm of UAVs. International Conference on Unmanned Aircraft Systems (ICUAS 2018), 22-29.
Designing Wireless Sensor Networks: from theory to applications
Agrawal, D. P., & Mishra, A. (2011). Designing Wireless Sensor Networks: from theory to applications. Seventh IEEE Conference on Wireless Communication and Sensor Networks, Dec 5-9, 2011, Panna, India.

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