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booktitle = {2019 IEEE 5th World Forum on Internet of Things},
organization={IEEE},
keywords={feature extraction;feedforward neural nets;Internet of Things;mobile computing;pattern recognition;sensor fusion;low-power smart devices;TM system-on-module;sensor fusion algorithm;ARM Cortex M4F;inertial sensors;shock-aware segmentation;histogram feature extraction;Neblina's MPR framework;human fitness activity recognition;motion pattern recognition;Internet of Things;feedforward neural network;3D orientation tracking;power consumption;Histograms;Real-time systems;Motion segmentation;Hardware;Sports;Feature extraction;Microsoft Windows},
doi={10.1109/WF-IoT.2019.8767219}
}
@inproceedings{StreamDM,
author = {Bifet, Albert and Maniu, Silviu and Qian, Jianfeng and Tian, Guangjian and He, Cheng and Fan, Wei},
title = {{StreamDM: Advanced Data Mining in Spark Streaming}},
year = {2015},
isbn = {9781467384933},
publisher = {IEEE Computer Society},
address = {USA},
url = {https://doi.org/10.1109/ICDMW.2015.140},
doi = {10.1109/ICDMW.2015.140},
booktitle = {Proceedings of the 2015 IEEE International Conference on Data Mining Workshop},
pages = {1608–1611},
numpages = {4},
series = {ICDMW ’15}
}
@article{behzad2019,
title={{A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors}},
author={Dehghani, Akbar and Sarbishei, Omid and Glatard, Tristan and Shihab, Emad},
journal={Sensors},
volume={19},
number={22},
pages={5026},