International Journal of Soft Computing

Year: 2018
Volume: 13
Issue: 5
Page No. 139 - 148

High Performance Complex Event Processing for Nuclear Reactor Simulation

Authors : Nehal Safwat, Sherihan Abuelenin and Ahmed Tolba

References

Bayer, V., S. Kunath, R. Niemeier and J. Horwege, 2018. Signal-Based metamodels for predictive reliability analysis and virtual testing. Adv. Sci. Technol. Eng. Syst. J., 3: 342-347.
CrossRef  |  Direct Link  |  

Bhadani, A.K. and D. Jothimani, 2016. Big Data: Challenges, Opportunities and Realities. In: Effective Big Data Management and Opportunities for Implementation, Kumar, S.M. and K.G. Dileep (Eds.). IGI Global, Pennsylvania, USA., ISBN:9781522501824, pp: 1-24.

Burgueno, L., J. Boubeta-Puig and A. Vallecillo, 2018. Formalizing complex event processing systems in Maude. IEEE. Access, 6: 23222-23241.
CrossRef  |  Direct Link  |  

Chan, J. and L.B. Moses, 2017. Making sense of big data for security. Br. J. Criminology, 57: 299-319.
CrossRef  |  Direct Link  |  

Chandrathilake, H.M.C., H.T.S. Hewawitharana, R.S. Jayawardana, A.D.D. Viduranga and H.D. Bandara et al., 2016. Reducing computational time of closed-loop weather monitoring: A complex event processing and machine learning based approach. Proceedings of the 2016 International Conference on Moratuwa Engineering Research Conference (MERCon), April 5-6, 2016, IEEE, Moratuwa, Sri Lanka, ISBN:978-1-5090-0644-1, pp: 78-83.

Clavel, M., F. Duran, S. Eker, P. Lincoln and N. Marti-Oliet et al., 2007. All about Maude-A High-Performance Logical Framework: How to Specify Program and Verify Systems in Rewriting Logic. Springer, Berlin, Germany, ISBN:978-3-540-71999-1, Pages: 802.

Cugola, G., A. Margara, M. Pezze and M. Pradella, 2015. Efficient analysis of event processing applications. Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems, June 29-July 03, 2015, ACM, New York, USA., ISBN:978-1-4503-3286-6, pp: 10-21.

Dayarathna, M. and S. Perera, 2018. Recent advancements in event processing. ACM. Comput. Surv. CSUR., 51: 1-36.
CrossRef  |  Direct Link  |  

Flouris, I., N. Giatrakos, A. Deligiannakis, M. Garofalakis and M. Kamp et al., 2017. Issues in complex event processing: Status and prospects in the big data era. J. Syst. Software, 127: 217-236.
CrossRef  |  Direct Link  |  

Gao, X., W. Li, M. Loomes and L. Wang, 2017. A fused deep learning architecture for viewpoint classification of echocardiography. Inf. Fusion, 36: 103-113.
CrossRef  |  Direct Link  |  

Grewal, D., Y. Bart, M. Spann and P.P. Zubcsek, 2016. Mobile advertising: A framework and research agenda. J. Interact. Marketing, 34: 3-14.
Direct Link  |  

Guo, Y., J. Rao, D. Cheng and X. Zhou, 2017. Ishuffle: Improving hadoop performance with shuffle-on-write. IEEE. Trans. Parallel Distrib. Syst., 28: 1649-1662.
CrossRef  |  Direct Link  |  

Itria, M.L., M. Kocsis-Magyar, A. Ceccarelli, P. Lollini and G. Giunta et al., 2017. Identification of critical situations via event processing and event trust analysis. Knowl. Inf. Syst., 52: 147-178.
CrossRef  |  Direct Link  |  

Jing, W., D. Tong, Y. Wang, J. Wang and Y. Liu et al., 2017. MaMR: High-Performance MapReduce programming model for material cloud applications. Comput. Phys. Commun., 211: 79-87.
CrossRef  |  Direct Link  |  

Jung, J.J., 2017. Computational collective intelligence with big data: Challenges and opportunities. Future Gener. Comp. Syst., 66: 87-88.
CrossRef  |  Direct Link  |  

Korber, M., N. Glombiewski and B. Seeger, 2018. TPStream: Low-Latency temporal pattern matching on event streams. Open Proc., 1: 313-324.
CrossRef  |  Direct Link  |  

Lugmayr, A., B. Stockleben, C. Scheib and M.A. Mailaparampil, 2017. Cognitive big data: Survey and review on big data research and its implications: What is really new in big data?. J. Knowl. Manage., 21: 197-212.
CrossRef  |  Direct Link  |  

Sandha, S.S., M. Kachuee and S. Darabi, 2017. Complex event processing of health data in real-time to predict heart failure risk and stress. Comput. Soc., 1707: 1-5.
Direct Link  |  

Storey, V.C. and I.Y. Song, 2017. Big data technologies and management: What conceptual modeling can do. Data Knowl. Eng., 108: 50-67.
CrossRef  |  Direct Link  |  

Tao, F., J. Cheng, Q. Qi, M. Zhang and H. Zhang et al., 2018. Digital twin-driven product design manufacturing and service with big data. Intl. J. Adv. Manuf. Technol., 94: 3563-3576.
CrossRef  |  Direct Link  |  

Terzi, D.S., R. Terzi and S. Sagiroglu, 2017. Big data analytics for network anomaly detection from netflow data. Proceedings of the 2017 International Conference on Computer Science and Engineering (UBMK), October 5-8, 2017, IEEE, Antalya, Turkey, ISBN:978-1-5386-0931-6, pp: 592-597.

Viegas, E., A. Santin, N. Neves, A. Bessani and V. Abreu, 2017. A resilient stream learning intrusion detection mechanism for real-time analysis of network traffic. Proceedings of the 2017 IEEE International Conference on Global Communications GLOBECOM 2017, December 4-8, 2017, IEEE, Singapore, Singapore, ISBN:978-1-5090-5020-8, pp: 1-6.

Wang, Y., L. Kung and T.A. Byrd, 2018. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technol. Forecasting Soc. Change, 126: 3-13.
CrossRef  |  Direct Link  |  

Williams, M.L., P. Burnap and L. Sloan, 2017. Crime sensing with big data: The affordances and limitations of using open-Source communications to estimate crime patterns. Br. J. Criminology, 57: 320-340.
CrossRef  |  Direct Link  |  

Zhuang, C., J. Liu and H. Xiong, 2018. Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Intl. J. Adv. Manuf. Technol., 96: 1149-1163.
CrossRef  |  Direct Link  |  

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved