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Design of Intelligent Integration System for Online Curriculum Resources of Mechanical Engineering Specialty Based on Fuzzy Clustering

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e-Learning, e-Education, and Online Training (eLEOT 2023)

Abstract

The conventional intelligent integration system of online course resources for mechanical engineering majors mainly uses HDFS (Hadoop Distributed File System) distributed architecture to process resource integration signals, which is vulnerable to the impact of dynamic allocation of data resources, leading to some system functions being abnormal. Therefore, a new intelligent integration system of online course resources for mechanical engineering majors needs to be designed based on fuzzy clustering. In the hardware part, TMS320DM642 DSP processor and FPGA data memory are designed. In the software part, roles and resource integration permissions are divided based on fuzzy clustering, an online curriculum resource integration architecture model is constructed, and online curriculum resource integration function modules are designed, thus realizing the intelligent integration of online curriculum resources. The system test results show that each functional module of the designed online course resource integration system operates normally, proving that the designed resource intelligent integration system has good performance, reliability, certain application value, and has made certain contributions to reducing the difficulty of course resource sharing.

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Correspondence to Jinjian Chen .

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chen, J., Zhao, N. (2024). Design of Intelligent Integration System for Online Curriculum Resources of Mechanical Engineering Specialty Based on Fuzzy Clustering. In: Gui, G., Li, Y., Lin, Y. (eds) e-Learning, e-Education, and Online Training. eLEOT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 545. Springer, Cham. https://doi.org/10.1007/978-3-031-51471-5_1

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  • DOI: https://doi.org/10.1007/978-3-031-51471-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51470-8

  • Online ISBN: 978-3-031-51471-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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