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To improve the quality of education in higher vocational colleges and universities, it is necessary to reform and innovate their education management mode, and education can truly promote social development only by promoting the harmonious development of personality. This paper constructs a personalized education management and top talent cultivation model based on the framework of multiple intelligences theory and establishes an evaluation index system to assess its implementation effect. The hierarchical analysis method is used to determine the weights of the indicators, and then the implementation effect of the management and cultivation model is assessed through the multilevel gray comprehensive evaluation method. The evaluation of the implementation effect of the higher vocational colleges and universities found that the average score of the implementation effect evaluation of the four higher vocational colleges and universities is between 3.94 and 4.59 points, which is at a high level, indicating that the implementation effect of personalized education management and top talent cultivation model is better. It is also found that students in higher vocational colleges and universities are more satisfied with the teaching method, management method, curriculum, and cultivation objectives. The model improvement suggestions put forward in this paper from the perspective of students provide valuable references for educational administrators and teachers of higher vocational colleges and universities so that students in higher vocational colleges and universities can achieve the desired effect of cultivating top-notch talents.

In terms of spectrum reuse and lifetime prolongation, the energy‐harvesting cognitive radio networks (EH‐CRNs) have been a hot issue in the wireless networking research community. While satisfying the minimal throughput demand of primary users (PUs), it is aimed to maximize the throughput of secondary users (SUs) in the EH‐CRN with multiple SUs. Specifically, the problem of secondary throughput maximization (STM) is first formulated as a non‐linear optimization problem, then its convexity is proven, and finally an efficient algorithm is proposed that jointly uses the Fibonacci search method and equal interval search method to obtain the optimal time allocation among primary transmitter (PT)'s energy transfer and each SU's packet transmission, and the optimal transmit power of PT. Furthermore, for the scenarios where the circuit power is negligible, the convex problem is first proven, and a more efficient algorithm is presented for the problem of STM. Simulation results demonstrate that, with the increase of the minimal throughput demand of PUs, the reduction rate of the maximal secondary throughput increases. [ABSTRACT FROM AUTHOR]

With the increasing attention on environmental issues, green scheduling in manufacturing industries has become a hot research topic. As a typical scheduling problem, the flexible job-shop scheduling problem (FJSP) has received increasing attention, but research on the FJSP considering set-up and transportation times simultaneously is still rare. To address the energy-efficient FJSP with sequence-dependent set-up and transportation times to minimize makespan and total energy consumption, a multi-objective mixed-integer linear programming model of the problem is formulated and an effective novel heuristic method (NHM) is proposed. To enhance the convergence and distribution of the NHM, three strategies—population initialization, greedy iterative decoding and local intensification—are designed. The performance of the NHM is demonstrated by comparison with three algorithms through 48 instances. The results show that the NHM can obtain a scheduling scheme with lower makespan and total energy consumption than those of the comparison algorithms. [ABSTRACT FROM AUTHOR]