References
- G. Manogaran and D. Lopez, "Health data analytics using scalable logistic regression with stochastic gradient descent," International Journal of Advanced Intelligence Paradigms, Vol.10, No.1-2, pp.118-132, 2018. https://doi.org/10.1504/IJAIP.2018.089494
- J.-W. Lee, H.-S. Lim, D.-W. Kim, S.-A. Shin, J. Kim, B. Yoo, and K.-H. Cho, "The development and implementation of stroke risk prediction model in National Health Insurance Service's personal health record," Computer Methods and Programs in Biomedicine, Vol.153, pp.253-257, 2018. https://doi.org/10.1016/j.cmpb.2017.10.007
- N. Bouri and S. Ravi, "Going mobile: how mobile personal health records can improve health care during emergencies," JMIR mHealth uHealth, Vol.2, No.1, e8, 2014. https://doi.org/10.2196/mhealth.3017
- N. Khozouie, F. Fotouhi-Ghazvini, and B. Minaei-Bidgoli, "Ontological MobiHealth system," Indonesian J. Elect. Eng. Comput. Sci., Vol.10, No.1, pp.309-319, 2018. https://doi.org/10.11591/ijeecs.v10.i1.pp309-319
- S. Huang, L. Li, H. Cai, B. Xu, G. Li, and L. Jiang, "A Configurable WoT Application Platform Based on Spatiotemporal Semantic Scenarios," IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol.49, No.1, pp.123-135, 2017. https://doi.org/10.1109/TSMC.2017.2753465
- L. Mainetti, V. Mighali, L. Patrono, and P. Rametta, "A novel Rule-based Semantic Architecture for IoT Building Automation Systems," Software, Telecommunications and Computer Networks (SoftCOM), pp.124-131, 2015.
- L. Pessoa, P. Fernandes, T. Castro, V. Alves, G. N. Rodrigues, and H. Carvalho, "Building reliable and maintainable Dynamic Software Product Lines: An investigation in the Body Sensor Network domain," Information and Software Technology, Vol.86, pp.54-70, 2017. https://doi.org/10.1016/j.infsof.2017.02.002
- J. G. Nalepa and S. Bobek, "Rule-based solution for context-aware reasoning on mobile devices," Computer Science and Information Systems, Vol.11, No.1, pp.171-193, 2014. https://doi.org/10.2298/CSIS130209002N
- N. Kolbe, A. Zaslavsky, S. Kubler, J. Robert, and Y. Le Traon, "Enriching a Situation Awareness Framework for IoT with Knowledge Base and Reasoning Components," In International and Interdisciplinary Conference on Modeling and Using Context, Springer, Cham, pp.41-54, 2017.
- Z. Bahramian, R. Ali Abbaspour, and C. Claramunt, "A cold start context-aware recommender system for tour planning using artificial neural network and case based reasoning," Mobile Information Systems, 2017.
- M. Shin, W. Paik, B. Kim, and S. Hwang, "An IoT Platform with Monitoring Robot Applying CNN-Based Context-Aware Learning," Sensors, Vol.19, No.11, pp.1-13, 2019. https://doi.org/10.1109/JSEN.2019.2925985
- L. Gomes, C., Ramos, A., Jozi, B., Serra, L., Paiva, and Z. Vale, "IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach," Future Internet, Vol.11, No.3, pp.58, 2019. https://doi.org/10.3390/fi11030058
- N. Polyzotis, S. Roy, S. E. Whang, and M. Zinkevich, "Data Management Challenges in Production Machine Learning," Proceedings of the 2017 ACM International Conference on Management of Data, ACM, pp.1723-1726, 2017.
- M. H. Kabir, M. R. Hoque, H. Seo, and S. H. Yang, "Machine learning based adaptive context-aware system for smart home environment," International Journal of Smart Home, Vol.9, No.11, pp.55-62, 2015.
- M. H., Kabir, M. R., Hoque, H., Seo, and S. H. Yang, "Boolean Control Network Based Modeling for Context-Aware System in Smart Home," International Journal of Smart Home, Vol.10, No.4, pp.65-76, 2016.
- B. Ospan, N. Khan, J. Augusto, M. Quinde, and K. Nurgaliyev, "Context aware virtual assistant with casebased conflict resolution in multi-user smart home environment," 2018 International Conference on Computing and Network Communications (CoCoNet), IEEE, pp.36-44, 2018.
- P. Jiang, J. Winkley, C. Zhao, R. Munnoch, G. Min, and L. T. Yang, "An intelligent information forwarder for healthcare big data systems with distributed wearable sensors," IEEE systems journal, Vol.10, No.3, pp.1147-1159, 2014. https://doi.org/10.1109/JSYST.2014.2308324
- O. Banos, R. Garcia, J. A. Holgado-Terriza, M. Damas, H. Pomares, I. Rojas, A. Saez, and C. Villalonga, "mHealthDroid: a novel framework for agile development of mobile health applications," International Workshop on Ambient Assisted Living, Springer, Cham, pp.91-98, 2014.
- T. Zoppi, A. Ceccarelli, and A. Bondavalli, "Contextawareness to improve anomaly detection in dynamic service oriented architectures," International Conference on Computer Safety, Reliability, and Security, Springer, Cham, pp.145-158, 2016.
- Y. Bai, H. Ji, Q. Han, J. Huang, and D. Qian, "MidCASE: a service oriented middleware enabling context awareness for smart environment," 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07), IEEE, pp.946-951, 2007.
- L. O. Colombo-Mendoza, R. Valencia-Garcia, A. Rodriguez- Gonzalez, G. Alor-Hernandez, and J. J. Samper-Zapater, "RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes," Expert Systems with Applications, Vol.42, No.3, pp.1202-1222, 2015. https://doi.org/10.1016/j.eswa.2014.09.016
- P. H. Wu, G. J. Hwang, and W. H. Tsai, "An expert systembased context-aware ubiquitous learning approach for conducting science learning activities," Journal of Educational Technology & Society, Vol.16, No. 4, pp.217-230, 2013.
- D. Galar, A. Thaduri, M. Catelani, and L. Ciani, "Context awareness for maintenance decision making: A diagnosis and prognosis approach," Measurement, pp.137-150, 2015.
- A. I. Wang, and Q. K. Ahmad, "Camf-context-aware machine learning framework for android," Proceedings of the International Conference on Software Engineering and Applications (SEA 2010), CA, USA, 2010.
- H. Eldardiry, K. Sricharan, J. Liu, J. Hanley, B. Price, O. Brdiczka, and E. Bart, "Multi-source fusion for anomaly detection: using across-domain and across-time peergroup consistency checks," JoWUA, Vol.5, No.2, pp.39-58, 2014.