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Cloud Learning Community of Engineering Drawing

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Smart Computing and Communication (SmartCom 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10135))

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Abstract

General online teaching system cannot afford the huge information data exchange, held back in the modern teaching method and technology support. This paper aims at establishing the structure of the cloud learning community on big data. The Oracle server on cloud computing is selected to provide the data processing support. Based on the investigation on the students’ browse online and the homework completion situation, the existing teaching resource is integrated, and the frame work of the cloud learning community on big data is established to improve the communication and integration. Cloud platform layers and the key data processing technology are analyzed. The cloud learning community can match the data processing technology and expose the students in the advanced cloud teaching stimulate the study enthusiasm.

This work was supported by grants from National Major Special Project of Oil and Gas “Study and Promotion of the Self-Adaptive Control Technology of Drainage Based on Shaft Flow Field” (2016ZX05042003-001); National Major Special Project of Oil and Gas “Key Equipment Development of Integrated Development of Three Kind of Unconventional gas in One Well” (2016ZX05066004-002); “Fundamental Research Funds for the Central Universities” (16CX02004A); NSFC (51174224).

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References

  1. Gai, K., Qiu, M., Zhao, H., Tao, L., Zong, Z.: Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing. J. Netw. Comput. Appl. 59, 46–54 (2015)

    Article  Google Scholar 

  2. Gai, K., Qiu, M., Zhao, H.: Cost-aware multimedia data allocation for heterogeneous memory using genetic algorithm in cloud computing. IEEE Trans. Cloud Comput. 99, 1–11 (2016)

    Article  Google Scholar 

  3. Gai, K., Qiu, M., Chen, M., Zhao, H.: SA-EAST: security-aware efficient data transmission for ITS in mobile heterogeneous cloud computing. ACM Trans. Embed. Comput. Syst. PP, 1 (2016)

    Google Scholar 

  4. Li, Y., Gai, K., Ming, Z., Zhao, H., Qiu, M.: Intercrossed access control for secure financial services on multimedia big data in cloud systems. ACM Trans. Multimed. Comput. Commun. Appl. 12(4s), 67 (2016)

    Google Scholar 

  5. Li, Y., Gai, K., Qiu, L., Qiu, M., Zhao, H.: Intelligent cryptography approach for secure distributed big data storage in cloud computing. Inf. Sci. PP(99), 1 (2016)

    Google Scholar 

  6. Gai, K., Qiu, M., Zhao, H.: Security-aware efficient mass distributed storage approach for cloud systems in big data. In: The 2nd IEEE International Conference on Big Data Security on Cloud, pp. 140–145, New York, USA (2016)

    Google Scholar 

  7. Gai, K., Li, S.: Towards cloud computing: a literature review on cloud computing and its development trends. In: 2012 Fourth International Conference on Multimedia Information Networking and Security, pp. 142–146, Nanjing, China (2012)

    Google Scholar 

  8. Gai, K., Qiu, M., Thuraisingham, B., Tao, L.: Proactive attribute-based secure data schema for mobile cloud in financial industry. In: The IEEE International Symposium on Big Data Security on Cloud; 17th IEEE International Conference on High Performance Computing and Communications, pp. 1332–1337, New York, USA (2015)

    Google Scholar 

  9. Gai, K., Du, Z., Qiu, M., Zhao, H.: Efficiency-aware workload optimizations of heterogenous cloud computing for capacity planning in financial industry. In: The 2nd IEEE International Conference on Cyber Security and Cloud Computing, pp. 1–6. IEEE, New York, USA (2015)

    Google Scholar 

  10. Qiu, M., Zhong, M., Li, J., Gai, K., Zong, Z.: Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans. Comput. 64(12), 3528–3540 (2015)

    Article  MathSciNet  Google Scholar 

  11. Yin, H., Gai, K.: An empirical study on preprocessing high-dimensional class-imbalanced data for classification. In: The IEEE International Symposium on Big Data Security on Cloud, pp. 1314–1319, New York, USA (2015)

    Google Scholar 

  12. Gai, K., Qiu, M., Chen, L., Liu, M.: Electronic health record error prevention approach using ontology in big data. In: 17th IEEE International Conference on High Performance Computing and Communications, pp. 752–757, New York, USA (2015)

    Google Scholar 

  13. Ma, L., Tao, L., Zhong, Y., Gai, K., RuleSN: research and application of social network access control model. In: IEEE International Conference on Intelligent Data and Security, pp. 418–423, New York, USA (2016)

    Google Scholar 

  14. Gai, K., Qiu, M., Zhao, H., Xiong, J.: Privacy-aware adaptive data encryption strategy of big data in cloud computing. In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), The 2nd IEEE International Conference of Scalable and Smart Cloud (SSC 2016), pp. 273–278. IEEE, Beijing, China (2016)

    Google Scholar 

  15. Gai, K., Qiu, M., Zhao, H., Liu, M.: Energy-aware optimal task assignment for mobile heterogeneous embedded systems in cloud computing. In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), pp. 198–203. IEEE, Beijing, China, (2016)

    Google Scholar 

  16. Gai, K., Steenkamp, A.: A feasibility study of Platform-as-a-Service using cloud computing for a global service organization. J. Inf. Syst. Appl. Res. 7, 28–42 (2014)

    Google Scholar 

  17. Gai, K., Steenkamp, A.: Feasibility of a Platform-as-a-Service implementation using cloud computing for a global service organization. In: Proceedings of the Conference for Information Systems Applied Research ISSN, vol. 2167, p. 1508 (2013)

    Google Scholar 

  18. Gai, K., Qiu, M., Zhao, H., Dai, W.: Anti-counterfeit schema using monte carlo simulation for e-commerce in cloud systems. In: The 2nd IEEE International Conference on Cyber Security and Cloud Computing, pp. 74–79. IEEE, New York, USA (2015)

    Google Scholar 

  19. Hoi, S., Wang, J., Zhao, P.: Libol: a library for online learning algorithms. J. Mach. Learn. Res. 15(1), 495–499 (2014)

    MATH  Google Scholar 

  20. Steenkamp, A., Alawdah, A., Almasri, O., Gai, K., Khattab, N., Swaby, C., Abaas, R.: Teaching case enterprise architecture specification case study. J. Inf. Syst. Educ. 24(2), 105 (2013)

    Google Scholar 

  21. Agrawal, D., Das, S., El Abbadi, A.: Big data, cloud computing: current state and future opportunities. In: Proceedings of the 14th International Conference on Extending Database Technology, pp. 530–533. ACM (2011)

    Google Scholar 

  22. Demirkan, H., Delen, D.: Leveraging the capabilities of service-oriented decision support systems: putting analytics and big data in cloud. Decis. Support Syst. 55(1), 412–421 (2013)

    Article  Google Scholar 

  23. Yin, H., Gai, K., Wang, Z.: A classification algorithm based on ensemble feature selections for imbalanced-class dataset. In: The 2nd IEEE International Conference on High Performance and Smart Computing, pp. 245–249, New York, USA (2016)

    Google Scholar 

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Authors and Affiliations

  1. College of Mechanical and Electronic Engineering, China University of Petroleum (East China), Qingdao, 266555, Shandong, China

    Fenna Zhang, Yaoguang Qi, Long Pan, Yong Yang, Hao Zhang & Yao Yao

Authors
  1. Fenna Zhang
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  2. Yaoguang Qi
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  3. Long Pan
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  4. Yong Yang
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  5. Hao Zhang
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  6. Yao Yao
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Correspondence to Fenna Zhang .

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Editors and Affiliations

  1. Pace University, New York, New York, USA

    Meikang Qiu

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Zhang, F., Qi, Y., Pan, L., Yang, Y., Zhang, H., Yao, Y. (2017). Cloud Learning Community of Engineering Drawing. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2016. Lecture Notes in Computer Science(), vol 10135. Springer, Cham. https://doi.org/10.1007/978-3-319-52015-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-52015-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52014-8

  • Online ISBN: 978-3-319-52015-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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