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Construction of Big Data Technology Training Environment for Vocational Education Based on Edge Computing Technology

Author: Libiao Cui Academic Editor: Xin NingAuthors Info & Claims
Published: 01 January 2022 Publication History

Abstract

With the rapid growth of the BD (big data) industry, many universities are focusing their professional development and expansion efforts on cultivating talent in related industries as well as building and developing big data disciplines. The BD technical training platform of vocational education based on IPE (Integration of Production and Education) is built in this paper, and the agreement signing, process management, effectiveness evaluation, big data analysis, and statistics of the integration of production and education are realized using edge computing technology, providing a solution for the informatization development of the integration of production and education. The access sequence was discovered among some knowledge points, as well as the sequence of knowledge points frequently viewed by students, and the teaching platform adjusts the content of web pages based on these rules to better provide personalized services for users.

References

[1]
Y. Xin, X. Zuo, and Q. Huang, “Research on the construction of seamless learning platform based on open education,” Asian Association of Open Universities Journal, vol. 13, no. 1, pp. 88–99, 2018.
[2]
W. G. Wu and L. Y. Gao, “Parameter optimization of a stability-training platform’s 4-PSS/PS parallel mechanism based on training ability evaluation index and PSO algorithm,” Mechanical Engineering, vol. 31, no. 1, pp. 1–11, 2018.
[3]
J. F. Shen, C. D. Ye, and Y. X. Zhu, “Research on externality economic evaluation of China’s education and training industry based on cognitive perspective,” Cognitive Systems Research, vol. 52, no. DEC., pp. 571–578, 2018.
[4]
J. Kong, C. Yang, J. Wang, X. Wang, M. Zuo, X. Jin, and S. Lin, “Deep-stacking network approach by multisource data mining for hazardous risk identification in IoT-based intelligent food management systems,” Computational Intelligence and Neuroscience, vol. 2021, 16 pages, 2021.
[5]
A. Barari, M. de Sales Guerra Tsuzuki, Y. Cohen, and M. Macchi, “Editorial: Intelligent manufacturing systems towards industry 4.0 era,” Journal of Intelligent Manufacturing, vol. 32, no. 7, pp. 1793–1796, 2021.
[6]
R. H. Tsaih, B. S. Kuo, T. H. Lin, and C. C. Hsu, “The use of big data analytics to predict the foreign exchange rate based on public media: a machine-learning experiment,” It Professional, vol. 20, no. 2, pp. 34–41, 2018.
[7]
E. Olshannikova, A. Ometov, Y. Koucheryavy, and T. Olsson, “Visualizing big data with augmented and virtual reality: challenges and research agenda,” Journal of Big Data, vol. 2, no. 1, pp. 1–27, 2015.
[8]
L. Huang, C. Wu, and B. Wang, “Challenges, opportunities and paradigm of applying big data to production safety management: From a theoretical perspective,” Journal of Cleaner Production, vol. 231, no. SEP.10, pp. 592–599, 2019.
[9]
P. Jovanovic, S. Nadal, O. Romero, A. Abelló, and B. Bilalli, “Quarry: a user-centered big data integration platform,” Information Systems Frontiers, vol. 23, no. 1, pp. 9–33, 2021.
[10]
L. Zhu and F. Li, “Agricultural data sharing and sustainable development of ecosystem based on block chain,” Journal of Cleaner Production, vol. 315, article 127869, 2021.
[11]
Z. Shi and W. Gang, “Integration of big-data ERP and business analytics (BA),” The Journal of High Technology Management Research, vol. 29, no. 2, pp. 141–150, 2018.
[12]
W. Jiang, “An intelligent supply chain information collaboration model based on internet of things and big data,” IEEE Access, vol. 7, pp. 58324–58335, 2019.
[13]
J. Yang, J. Wen, B. Jiang, and H. Wang, “Blockchain-based sharing and tamper-proof framework of big data networking,” IEEE Network, vol. 34, no. 4, pp. 62–67, 2020.
[14]
P. Gong, Y. Cao, B. Cai, and K. Li, “Multi-information location data fusion system of railway signal based on cloud computing,” Future Generation Computer Systems, vol. 88, pp. 594–598, 2018.
[15]
V. Vennila and A. R. Kannan, “Hybrid parallel linguistic fuzzy rules with canopy MapReduce for big data classification in cloud,” International Journal of Fuzzy Systems, vol. 21, no. 3, pp. 809–822, 2019.
[16]
X. Fan, R. Xu, L. Cao, and Y. Song, “Learning nonparametric relational models by conjugately incorporating node information in a network,” IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 589–599, 2017.
[17]
J. Li, “A survey of new E-government and its security technologies,” Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, vol. 52, no. 10, pp. 1370–1381, 2018.
[18]
R. Bogue, “Cloud robotics: a review of technologies, developments and applications,” Industrial Robot, vol. 44, no. 1, pp. 1–5, 2017.
[19]
Q. Wang, X. Cui, Y. Li, and F. Ye, “Performance enhancement of a USV INS/CNS/DVL integration navigation system based on an adaptive information sharing factor federated filter,” Sensors, vol. 17, no. 2, p. 239, 2017.
[20]
P. Lin and Y. Chen, “Network security situation assessment based on text sim hash in BD environment,” International Journal of Network Security, vol. 21, no. 4, pp. 699–708, 2019.
[21]
Y. Liu, C. Yang, and Q. Sun, “Thresholds based image extraction schemes in BD environment in intelligent traffic management,” IEEE Transactions on Intelligent Transportation Systems, vol. 99, pp. 1–9, 2020.
[22]
H. Wang, S. Ma, and H. N. Dai, “A rhombic dodecahedron topology for human-centric banking big data,” IEEE Transactions on Computational Social Systems, vol. 6, no. 5, pp. 1095–1105, 2019.
[23]
H. Yu, H. Dai, G. Tian, Y. Xie, B. Wu, Y. Zhu, H. Li, and H. Wu, “Big-data-based power battery recycling for new energy vehicles: information sharing platform and intelligent transportation optimization,” Access, vol. 8, pp. 99605–99623, 2020.
[24]
I. Vakilinia and S. Sengupta, “Fair and private rewarding in a coalitional game of cybersecurity information sharing,” IET Information Security, vol. 13, no. 6, pp. 530–540, 2019.

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cover image Wireless Communications & Mobile Computing
Wireless Communications & Mobile Computing  Volume 2022, Issue
2022
25330 pages
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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John Wiley and Sons Ltd.

United Kingdom

Publication History

Published: 01 January 2022

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