Design and Implementation of Private College Enrollment Management System Based on B/S Mode

Junhua Bai

doi:10.62762/TIOT.2023.550445

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Volume 1, Issue 1, IECE Transactions on Internet of Things

Volume 1, Issue 1, 2023

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Jinchao Chen

Northwestern Polytechnical University,China

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IECE Transactions on Internet of Things, 2023, Volume 1, Issue 1: 30-35

Free to Read | Research Article | 28 December 2023

Design and Implementation of Private College Enrollment Management System Based on B/S Mode

Junhua Bai 1 *

1 Recruitment and Employment Office, Shaanxi Institute of International Trade & Commerce, Xi’an 712046, China

* Corresponding Author: Junhua Bai, [email protected]

DOI: https://doi.org/10.62762/TIOT.2023.550445

Received: 16 September 2023, Accepted: 22 December 2023, Published: 28 December 2023

Cited by: 1 (Source: Web of Science) , 1 (Source: Google Scholar)

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Abstract

This system, combining with recruitment service characteristics of private college, adopts B/S pattern design for private colleges enrollment management system. The system includes PC terminal and mobile terminal access, realizing the display of SVG-based map, fully considering the convenience and friendly interactive interface of the system mobile terminal access, providing online consultation, registration, enrollment, payment, data statistical analysis and other functions, improving the efficiency and accuracy of enrollment data processing, so as to realize the information management of school enrollment. After the test, it meets the needs of enrollment management.

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Keywords

Enrollment management system

SVG map

Online consultation

Statistical analysis

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APA Style

Junhua Bai (2023). Design and implementation of privatecollege enrollment Management System based on B/S mode.IECE Transactions on Internet of Things, 1(1), 30–35. https://doi.org/10.62762/TIOT.2023.550445

References

Pei, K. (2020). Analysis and design of private college enrollment management information system. Marketing Industry (38), 161–163.
[Google Scholar]
Wang, B. (2022). Design of intelligent analysis system for enrollment data of private colleges based on olap. (8), 108–110.
[Google Scholar]
Li, F. (2020). Analysis of the recruitment publicity strategy of domestic private colleges in the era of new media. Think-tank (9), 2.
[Google Scholar]
Shi, Y. (2018). Research on the recruitment strategy of private colleges. Guide for Knowledge seeking (31), 1.
[Google Scholar]
Sun, Y. (2016). Research on the recruitment strategy of private colleges based on the vision of humanization and institutionalization. Central China Normal University.
[Google Scholar]
Li, X. (2020). Reform and innovation strategy of private college enrollment based on internet era – taking a university in foshan as an example. (1), 296.
[Google Scholar]
Chen, J., Du, C., Han, P., & Du, X. (2021). Real-time digital simulator for distributed systems. Simulation, 97 (5), 299–309.
[Google Scholar]
Yang, R. (2021). Innovative thinking on the recruitment publicity strategy of private colleges under the background of higher vocational enrollment expansion. Academy (17), 42-444.
[Google Scholar]
Liu, M., Cheng, L., Gu, Y., Wang, Y., Liu, Q., & O’Connor, N. E. (2021). MPC-CSAS: Multi-party computation for real-time privacy-preserving speed advisory systems. IEEE Transactions on Intelligent Transportation Systems, 23(6), 5887-5893.
[Google Scholar]
Zhang, X., Cui, L., Shen, W., Zeng, J., Du, L., He, H., & Cheng, L. (2023). File processing security detection in multi-cloud environments: a process mining approach. Journal of Cloud Computing, 12(1), 100.
[Google Scholar]
Liu, C., Zeng, Q., Cheng, L., Duan, H., Zhou, M., & Cheng, J. (2021). Privacy-preserving behavioral correctness verification of cross-organizational workflow with task synchronization patterns. IEEE Transactions on Automation Science and Engineering, 18(3), 1037-1048.
[Google Scholar]
Li, J., Li, J., Xie, C., Liang, Y., Qu, K., Cheng, L., & Zhao, Z. (2023). PipCKG-BS: A Method to Build Cybersecurity Knowledge Graph for Blockchain Systems via the Pipeline Approach. Journal of Circuits, Systems and Computers, 2350274.
[Google Scholar]
Li, S., Li, J., Pei, J., Wu, S., Wang, S., & Cheng, L. (2023). Eco-CSAS: A Safe and Eco-Friendly Speed Advisory System for Autonomous Vehicle Platoon Using Consortium Blockchain. IEEE Transactions on Intelligent Transportation Systems.
[Google Scholar]
Chen, X., Yu, Q., Dai, S., Sun, P., Tang, H., & Cheng, L. (2023). Deep Reinforcement Learning for Efficient IoT Data Compression in Smart Railroad Management. IEEE Internet of Things Journal.
[Google Scholar]
Wang, Y., Wang, Y., Shi, C., Cheng, L., Li, H. and Li, X., (2020). An edge 3D CNN accelerator for low-power activity recognition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40(5), pp.918-930.
[Google Scholar]
Cheng, L., Wang, Y., Liu, Q., Epema, D. H., Liu, C., Mao, Y., & Murphy, J. (2021). Network-aware locality scheduling for distributed data operators in data centers. IEEE Transactions on Parallel and Distributed Systems, 32(6), 1494-1510.
[Google Scholar]
Liu, J., Shen, H., Chi, H., Narman, H. S., Yang, Y., Cheng, L., & Chung, W. (2021). A low-cost multi-failure resilient replication scheme for high-data availability in cloud storage. IEEE/ACM Transactions on Networking, 29(4), 1436-1451.
[Google Scholar]
Chen, X., Cheng, L., Liu, C., Liu, Q., Liu, J., Mao, Y., & Murphy, J. (2020). A WOA-based optimization approach for task scheduling in cloud computing systems. IEEE Systems Journal, 14(3), 3117-3128.
[Google Scholar]

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