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Volumn 41, Issue 4, 2014, Pages 74-77

Modeling and analytics for cyber-Physical systems in the age of big data

Author keywords

[No Author keywords available]

Indexed keywords

BIG DATA; EMBEDDED SYSTEMS;

EID: 84902509359     PISSN: 01635999     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2627534.2627558     Document Type: Article
Times cited : (44)

References (20)
  • 5
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    • The rise of industrial big data
    • The Rise of Industrial Big Data. GE whitepaper. http://www.ge-ip.com/ library/detail/13170/.
    • GE Whitepaper.
  • 6
    • 0141725660 scopus 로고    scopus 로고
    • The pragmatics of model-Driven development
    • B. Selic. The pragmatics of model-driven development. IEEE Software, 20 (5), 2003.
    • (2003) IEEE Software , vol.20 , pp. 5
    • Selic, B.1
  • 8
    • 77956210503 scopus 로고    scopus 로고
    • Multiple kernel learning for heterogeneous anomaly detection: Algorithm and aviation safety case study
    • S. Das, B. L. Matthews, A. N. Srivastava, and N. C. Oza. Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study. In KDD, 2010.
    • (2010) KDD
    • Das, S.1    Matthews, B.L.2    Srivastava, A.N.3    Oza, N.C.4
  • 10
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I. Guyon. An introduction to variable and feature selection. Journal of Machine Learning Research, 3:1157-1182, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 1157-1182
    • Guyon, I.1
  • 14
    • 84902515566 scopus 로고    scopus 로고
    • Switched and piecewise nonlinear hybrid system identification
    • F. Lauer and G. Bloch. Switched and PieceWise Nonlinear Hybrid System Identification. In HSCC, 2008.
    • (2008) HSCC
    • Lauer, F.1    Bloch, G.2
  • 15
    • 84876763091 scopus 로고    scopus 로고
    • Learning nonlinear hybrid systems: From sparse optimization to support vector regression
    • V. L. Le, F. Lauer, L. Bako, and G. Bloch. Learning Nonlinear Hybrid Systems: From Sparse Optimization to Support Vector Regression. In HSCC, 2013.
    • (2013) HSCC
    • Le, V.L.1    Lauer, F.2    Bako, L.3    Bloch, G.4
  • 16
    • 85076636929 scopus 로고    scopus 로고
    • Structured comparative analysis of system logs to diagnose performance problems
    • K. Nagaraj, C. Killian, and J. Neville. Structured Comparative Analysis of System Logs to Diagnose Performance Problems. In Proceedings of the NSDI, 2012.
    • (2012) Proceedings of the NSDI
    • Nagaraj, K.1    Killian, C.2    Neville, J.3
  • 19
    • 84902527594 scopus 로고    scopus 로고
    • Large scale estimation in cyberphysical systems using streaming data: A case study with smartphone traces
    • 1212.3393v1
    • T. Hunter and T. Das and M. Zaharia and P. Addeel and A. M. Bayen. Large Scale Estimation in Cyberphysical Systems using Streaming Data: a Case Study with Smartphone Traces. arXiv.org, 1212.3393v1, 2012.
    • (2012) ArXiv.org
    • Hunter, T.1    Das, T.2    Zaharia, M.3    Addeel, P.4    Bayen, A.M.5
  • 20
    • 84874722652 scopus 로고    scopus 로고
    • Discretized streams: An efficient and fault-Tolerant model for stream processing on large clusters
    • M. Zaharia, T. Das, H. Li, S. Shenker, and I. Stoica. Discretized streams: an efficient and fault-tolerant model for stream processing on large clusters. In HotCloud, 2010.
    • (2010) HotCloud
    • Zaharia, M.1    Das, T.2    Li, H.3    Shenker, S.4    Stoica, I.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.