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University of Groningen
Nijenborgh 9
9747 AG Groningen
The Netherlands

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2018

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  1. Kollenstart, M., Harmsma, E., Langius, E., Andrikopoulos, V., & Lazovik, A. (2018). Adaptive Provisioning of Heterogeneous Cloud Resources for Big Data Processing. Big Data and Cognitive Computing, 2, 15. https://doi.org/10.3390/bdcc2030015
  2. Saleh, S., Qadir, J., & Ilyas, M. U. (2018). Shedding Light on the Dark Corners of the Internet: A Survey of Tor Research. Journal of Network and Computer Applications, 114, 1–28. https://doi.org/10.1016/j.jnca.2018.04.002
  3. Groefsema, H., van Beest, N. R. T. P., & Aiello, M. (2018). A Formal Model for Compliance Verification of Service Compositions. Ieee Transactions on Services Computing, 11(3), 466–479. https://doi.org/10.1109/TSC.2016.2579621
  4. Haghshenas, K., Hashemi, M., & Nikoubin, T. (2018). Fast and Energy-Efficient CNFET Adders with CDM and Sensitivity-Based Device-Circuit Co-Optimization. IEEE Transactions on Nanotechnology, 17, 783–794. https://doi.org/10.1109/TNANO.2018.2834511
  5. Bessani, M., Ribeiro, R. R. M., Pagani, G. A., Aiello, M., & Maciel, C. D. (2018). Robustness of reconfigurable complex systems by a multi-agent simulation: Application on power distribution systems. 2018 Annual IEEE International Systems Conference (SysCon), 1–6. https://doi.org/10.1109/SYSCON.2018.8369553
  6. Saquicela Vı́ctor, Segarra, J., Ortiz, J., Tello, A., Espinoza, M., Lupercio Lucı́a, & Villazón-Terrazas, B. (2018). LOD-GF: an integral linked open data generation framework. Conference on Information Technologies and Communication of Ecuador, 283–300.
  7. Robles, P., Tello, A., Zúñiga-Prieto, M., & Solano-Quinde, L. (2018). Modeling 911 emergency events in Cuenca-Ecuador using geo-spatial data. International Conference on Technology Trends, 564–577.
  8. Bahnasy, M., Elbiaze, H., & Boughzala, B. (2018). Zero-queue ethernet congestion control protocol based on available bandwidth estimation. Journal of Network and Computer Applications, 105, 1–20.
  9. Santiago da Silva, J., Stimpfling, T., Luinaud, T., Fradj, B., & Boughzala, B. (2018). One for All, All for One: A Heterogeneous Data Plane for Flexible P4 Processing. ArXiv e-Prints, arXiv–1807.
  10. Düştegör, D., Sultana, N., Felemban, N., & Qahtani, D. A. (2018). A smarter electricity grid for the Eastern Province of Saudi Arabia: Perceptions and policy implications. Utilities Policy, 50. https://doi.org/10.1016/j.jup.2017.09.009
  11. Düştegör, D., Elhussein, M. A., Alghamdi, A., & Nagy, N. (2018). Learning behind glass walls: learning style and partition-room, is there a correlation? International Journal of Innovation Science. https://doi.org/10.1108/IJIS-09-2017-0100
  12. Elhussein, M. A., Düştegör, D., Nagy, N., & Alghamdi, A. K. H. (2018). The impact of digital technology on female students’ learning experience in partition-rooms: Conditioned by social context. IEEE Transactions on Education, 61(4). https://doi.org/10.1109/TE.2018.2840501
  13. Sameh, H., Aiman, K., & Düştegör, D. (2018). A remotely piloted aerial system for a faster processing of traffic collisions towards reducing the resulting road congestion. 2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017. https://doi.org/10.1109/IEEEGCC.2017.8447915
  14. Aiello, M. (2018). The Web Was Done by Amateurs: A Reflection on One of the Largest Collective Systems Ever Engineered. Springer.
  15. Aiello, M., Yang, Y., Zou, Y., & Zhang, L.-J. (Eds.). (2018). Artificial Intelligence and Mobile Services - AIMS 2018 (Vol. 10970). Springer. http://dx.doi.org/10.1007/978-3-319-94361-9
  16. Blaauw, F. J. (2018). The non-existent average individual: Automated personalization in psychopathology research by leveraging the capabilities of data science [PhD thesis, University of Groningen]. http://hdl.handle.net/11370/ab67f288-309b-4d23-adab-0df7c8bb1f26
  17. Bos, F. M., Blaauw, F. J., Snippe, E., van der Krieke, L., de Jonge, P., & Wichers, M. (2018). Exploring the emotional dynamics of subclinically depressed individuals with and without anhedonia: An experience sampling study. Journal of Affective Disorders, 228, 186–193. https://doi.org/https://doi.org/10.1016/j.jad.2017.12.017
  18. Fiorini, L., Aiello, M., Poli, D., & Pelacchi, P. (2018). Topological Considerations on the Use of Batteries to Enhance the Reliability of HV-Grids . Journal of Energy Storage , 18, 316–326. https://doi.org/https://doi.org/10.1016/j.est.2018.04.025
  19. Pratama, A. R., Widyawan, W., Lazovik, A., & Aiello, M. (2018). Multi-User Low Intrusive Occupancy Detection. Sensors, 18(3). https://doi.org/10.3390/s18030796
  20. Dijkhuis, T. B., Blaauw, F. J., van Ittersum, M. W., Velthuijsen, H., & Aiello, M. (2018). Personalized Physical Activity Coaching: A Machine Learning Approach. Sensors, 18(2). https://doi.org/10.3390/s18020623
  21. Sha, A., & Aiello, M. (2018). Topological Considerations on Decentralised Energy Exchange in the Smart Grid. Procedia Computer Science, 130, 720–727. https://doi.org/https://doi.org/10.1016/j.procs.2018.04.126
  22. Yousefi, M. H. N., & Goudarzi, M. (2018). A task-based greedy scheduling algorithm for minimizing energy of mapreduce jobs. Journal of Grid Computing, 16(4), 535–551.
  23. Fiorini, L., & Aiello, M. (2018). Household CO2-efficient energy management. Energy Informatics.
  24. Kalksma, M., Setz, B., Pratama, A. R., Georgievski, I., & Aiello, M. (2018). Mining Sequential Patterns for Appliance Usage Prediction. International Conference on Smart Cities and Green ICT Systems.