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    Volume 1, Issue 1, IECE Transactions on Computer Science
    Volume 1, Issue 1, 2024
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    Jinchao Chen
    Jinchao Chen
    Northwestern Polytechnical University, China
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    IECE Transactions on Computer Science, 2024, Volume 1, Issue 1: 21-25

    Free to Read | Research Article | 17 November 2024
    Innovating Internet+ Education for College Student Members of the Communist Party of China in the Context of Major Public Health Emergency
    by
    IECE Author Hong Xiao 1 *
    1 School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
    * Corresponding Author: Hong Xiao, [email protected]
    DOI: https://doi.org/10.62762/TCS.2024.251125
    Received: 11 September 2024, Accepted: 05 November 2024, Published: 17 November 2024  
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    Abstract
    In the post-COVID-19 era, the education of Communist Party of China members among college students continues to face evolving challenges and opportunities. This paper examines the sustained integration of the Internet with Party member education in colleges as a means to maintain flexibility, enrich educational content, and enhance engagement. The "Internet + education" model, which gained prominence during the pandemic, remains a vital tool for overcoming spatial and temporal constraints in education. However, as the pandemic has subsided, new challenges have emerged, including the need to build high-quality online resources, ensure alignment between educational supply and student demand, and leverage advanced data analytics for continuous improvement. By addressing these areas, Party member education can adapt to the changing digital landscape and better meet the needs of college students. Our findings suggest that a strategic combination of well-developed online resources, personalized learning pathways, and data-driven strategies can modernize Party member education, offering valuable insights for policymakers and educators in a post-pandemic context.
    Keywords
    internal+
    MCPC education for college students
    network resources
    data analysis
    Funding
    internal+, MCPC education for college students, network resources, data analysis
    Cite This Article
    APA Style
    Xiao, H. (2024). Innovating Internet+ Education for College Student Members of the Communist Party of China in the Context of Major Public Health Emergency. IECE Transactions on Computer Science, 1(1), 21–25. https://doi.org/10.62762/TCS.2024.251125
    References
    1. Mengxia, W., & Guorui, Z. (2018). Discussion on the innovative path of Party Construction in Colleges and universities in the network era [J]. Journal of Higher Education, 7, 165-167.
      [Google Scholar]
    2. Wang, Y., Li, H., & Li, X. (2017). A case of on-chip memory subsystem design for low-power CNN accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37(10), 1971-1984.
      [Google Scholar]
    3. Chen, W., Wang, Y., Yang, S., Liu, C., & Zhang, L. (2020, March). You only search once: A fast automation framework for single-stage dnn/accelerator co-design. In 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1283-1286). IEEE.
      [Google Scholar]
    4. Liu, C., Chu, C., Xu, D., Wang, Y., Wang, Q., Li, H., ... & Cheng, K. T. (2021). HyCA: A hybrid computing architecture for fault-tolerant deep learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(10), 3400-3413.
      [Google Scholar]
    5. Xu, D., Chu, C., Wang, Q., Liu, C., Wang, Y., Zhang, L., ... & Cheng, K. T. (2020, October). A hybrid computing architecture for fault-tolerant deep learning accelerators. In 2020 IEEE 38th International Conference on Computer Design (ICCD) (pp. 478-485). IEEE.
      [Google Scholar]
    6. Wang, C., Wang, Y., Han, Y., Song, L., Quan, Z., Li, J., & Li, X. (2017, January). CNN-based object detection solutions for embedded heterogeneous multicore SoCs. In 2017 22nd Asia and South Pacific design automation conference (ASP-DAC) (pp. 105-110). IEEE.
      [Google Scholar]
    7. Liu, B., Chen, X., Wang, Y., Han, Y., Li, J., Xu, H., & Li, X. (2019, January). Addressing the issue of processing element under-utilization in general-purpose systolic deep learning accelerators. In Proceedings of the 24th Asia and South Pacific Design Automation Conference (pp. 733-738).
      [Google Scholar]
    8. Zhao, X., Wang, Y., Liu, C., Shi, C., Tu, K., & Zhang, L. (2020, July). BitPruner: Network pruning for bit-serial accelerators. In 2020 57th ACM/IEEE Design Automation Conference (DAC) (pp. 1-6). IEEE.
      [Google Scholar]
    9. Li, C., Wang, Y., Liu, C., Liang, S., Li, H., & Li, X. (2021). GLIST: Towards in-storage graph learning. In 2021 USENIX Annual Technical Conference (USENIX ATC 21) (pp. 225-238).
      [Google Scholar]
    10. Wu, B., Wang, C., Wang, Z., Wang, Y., Zhang, D., Liu, D., ... & Hu, X. S. (2020). Field-free 3T2SOT MRAM for non-volatile cache memories. IEEE Transactions on Circuits and Systems I: Regular Papers, 67(12), 4660-4669.
      [Google Scholar]
    11. Liang, S., Liu, C., Wang, Y., Li, H., & Li, X. (2020, November). Deepburning-gl: an automated framework for generating graph neural network accelerators. In Proceedings of the 39th International Conference on Computer-Aided Design (pp. 1-9).
      [Google Scholar]
    12. Xu, D., Zhu, Z., Liu, C., Wang, Y., Zhao, S., Zhang, L., ... & Cheng, K. T. (2021). Reliability evaluation and analysis of FPGA-based neural network acceleration system. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 29(3), 472-484.
      [Google Scholar]
    13. Wang Bin, Wa Qingwei, Xiao Lei. Research on the quality evaluation system of Party Construction in Colleges and Universities Based on modern quality management [J]. Heilongjiang Education(Theory & Practice). 2022, 5:1389-1392.
      [Google Scholar]
    14. Li Junhai, Lu Lifei. Research on the education of College Students’ Party members based on wechat public platform [J]. Journal of Higher Education,2020,32:189-192.
      [Google Scholar]
    15. Han Jinghua. Exploration on the practical path of smart party building in Colleges and universities from the perspective of ’Internet+ [J]. University Logistics Research, 2022,2:239-241.
      [Google Scholar]
    16. Zhong Jianhua, Zhong Qinxiang, Sui Shanshan, Duan Rui. Innovative thinking on the grass-roots party building in Colleges and Universities under the background of ’Internet +’ [J]. Industrial & Science Tribune, 2021,20(24):279-280.
      [Google Scholar]
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