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

Research Article | 28 December 2023
1 Recruitment and Employment Office, Shaanxi Institute of International Trade & Commerce, Xi’an 712046, China
* Corresponding Author
Received: 16 September 2023, Accepted: 22 December 2023, Published: 28 December 2023  

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.

Graphical Abstract
Design and implementation of private college enrollment Management System based on B/S mode

Enrollment management system
SVG map
Online consultation
Statistical analysis

Cite This Article
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.


[1]Pei, K. (2020). Analysis and design of private college enrollment management information system. Marketing Industry (38), 161–163.

[2]Wang, B. (2022). Design of intelligent analysis system for enrollment data of private colleges based on olap. (8), 108–110.

[3]Li, F. (2020). Analysis of the recruitment publicity strategy of domestic private colleges in the era of new media. Think-tank (9), 2.

[4]Shi, Y. (2018). Research on the recruitment strategy of private colleges. Guide for Knowledge seeking (31), 1.

[5]Sun, Y. (2016). Research on the recruitment strategy of private colleges based on the vision of humanization and institutionalization. Central China Normal University.

[6]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.

[7]Chen, J., Du, C., Han, P., & Du, X. (2021). Real-time digital simulator for distributed systems. Simulation, 97 (5), 299–309.

[8]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.

[9]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.

[10]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.

[11]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.

[12]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.

[13]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.

[14]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.

[15]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.

[16]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.

[17]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.

[18]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.

Publisher's Note
IECE stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions
IECE or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Copyright © 2023 Institute of Emerging and Computer Engineers INC. All rights reserved.