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Based on the architecture of ZigBee wireless sensor network (WSN) and the hierarchical modeling mechanism of OPENT, an enhanced ZigBee simulation model was studied to improve the MAC layer process model of IEEE 802.15.4 protocol provided by OPNET. The ZigBee Protocolcompatible network layer protocol, the routing algorithm, and the network layer process model based on an embedded routing function of OPNET were designed, which enhanced the scalability of ZigBee simulation system. And the enhanced ZigBee model optimized the number of router nodes needed for nodes access network, network control overheads, and end-to-end delay under different network scales.

In the big data environment, the key is the precise recommendation of learning resources to learners. The core is the indeep mining of learners' personalized demands. This study solves this problem by constructing learner personas. Primarily, collect web learning data of learners to cluster them. Then analyze the characteristics of learners to predict their learning intentions and knowledge blind spots. Based on it, generate a clear personalized learning path subsequently. Precise positioning, quickly finding out the learner's ability and quality shortcomings. And completing the accurate recommendation to learners. It will help learners establish a reasonable learning path, and provide more accurate service support. This study will provide a theoretical basis for carrying out big data precision services and meeting the personalized learning needs of learners.

With the development of vocational education, it is necessary to construct the pattern of lifelong learning. To push delivery learning resources and provide a learning environment, it is necessary to innovate in-service learning mode. According to the characteristics of the aerospace position, the capacity model was studied and proposed. Based on the ability model, the intelligent in-service learning model is studied and proposed to improve the precision service quality. From the angle of principle and learning process, this paper discusses the intelligent in-service learning mode of including the learning model based on knowledge map and the learning model based on seminar hall. The framework of the job knowledge map is constructed according to the post ability model which is based on professional knowledge, professional skills, and professional quality. The intelligent on-the-job learning model includes four elements: (i) learning platform, (ii) learning resources, (iii) learning methods, and (iv) learning evaluation. The learning portrait can record and visualize the information of learning, including content, activities, and effects.

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