Design of Mobile Intelligent Evaluation Algorithm in Physical Education Teaching

De-kun, Jiang; Memon, Fida Hussain

doi:10.1007/s11036-021-01818-1

Cited by 30 publications

(20 citation statements)

References 15 publications

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“…Layered architectures are very common in software architecture planning, and they are also a very important class of constructs. A hierarchical model can often have three main layers, roughly from bottom to top: the domain layer, the data access layer, and the representation layer [6], as shown in Figure 2. e role of each level is as follows.…”

Section: Design Of Sports Equipment Managementmentioning

confidence: 99%

“…Secondly, there is no fixed position of sports equipment manager in our unit, it is done by physical education teachers on a part-time basis, and each physical education teacher has classes to attend and teaching tasks to complete. In response to the above phenomenon, at least two teachers need to take turns to sit on duty to manage the assets and loan of physical education equipment, which increases the burden of teachers [6,7].…”

Section: Introductionmentioning

confidence: 99%

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Influence of Management Efficiency of Sports Equipment in Colleges and Universities Based on the Intelligent Optimization Method

Wang

2022

Scientific Programming

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China has always considered the improvement of youth physical quality as one of the key steps in the talent training program, and universities have always followed the national policy to change the quantity and quality of sports equipment. This study mainly focuses on the development of sports equipment management system in colleges and universities. By building a scientific sports equipment management system, the efficiency of sports equipment management process is improved and the difficulty of managers’ work is reduced. The construction of the sports equipment management system is a comprehensive information service platform created specifically for sports administrators. The main function is to help sports equipment administrators obtain information on equipment management, and it is an electronic system that can obtain the status of sports equipment use through certain instructions, providing an example for sports equipment management in China’s universities.

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Section: Design Of Sports Equipment Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of Management Efficiency of Sports Equipment in Colleges and Universities Based on the Intelligent Optimization Method

Wang

2022

Scientific Programming

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“…Furthermore, for the research progress of the training process of PE, Dekun et al (2021) [ 22 ] designed and researched the mobile intelligent evaluation algorithm in PE and designed a new mobile intelligent evaluation algorithm and applied it to the mobile intelligent evaluation of PE. The experimental results demonstrate that the proposed algorithm has a higher evaluation accuracy than the traditional mobile intelligent evaluation algorithm, and the evaluation accuracy can be maintained above 96%.…”

Section: Recent Related Workmentioning

confidence: 99%

Evaluation of the Physical Education Teaching and Training Efficiency by the Integration of Ideological and Political Courses with Lightweight Deep Learning

Zhang¹

2022

Computational Intelligence and Neuroscience

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The purpose is to improve the training effect of physical education (PE) based on the teaching concept of ideological and political courses. The research is supported by the lightweight deep learning (DL) model of the Internet of things (IoT). Through intelligent recognition and classification of human action and images, it discusses the PE and training scheme based on the lightweight DL model. In addition, by the optimization of the accelerated compression algorithm and the evaluation of the PE and training effect of the Openpose algorithm, an optimization model of the PE and training effect has been successfully established. The research data results indicate that after 120 iterations of the model, the system recognition accuracy of the convolutional neural network (CNN) algorithm can only be improved to about 75%, while the recognition accuracy of the Openpose algorithm can reach about 85%. Compared with the CNN algorithm under the same number of iterations, the recognition accuracy can be improved by 9.8%. In addition, when the number of nodes in the network layer is 60, the system delay time of the proposed Openpose algorithm is smaller. At this time, the system delay of the algorithm is only 10.8s. Compared with the CNN algorithm under the same conditions, the proposed algorithm can save at least 1.2s in system delay time. The advantage of the algorithm is that it can improve the efficiency of physical training and teaching, and this research has important reference significance for the digital and intelligent development of the teaching mode of PE.

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“…Then, the second section of this issue includes the other five papers, which focuses on the mobile information processing in real application, such as enterprise, automobile, education, as well as Architectural Engineering [12][13][14][15][16].…”

Section: Mobile Information Processing In Real Applicationmentioning

confidence: 99%

Profile of Intelligent Hybrid Information System in Mobile World

Liu

2022

Mobile Netw Appl

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Design of Mobile Intelligent Evaluation Algorithm in Physical Education Teaching

Cited by 30 publications

References 15 publications

Influence of Management Efficiency of Sports Equipment in Colleges and Universities Based on the Intelligent Optimization Method

Influence of Management Efficiency of Sports Equipment in Colleges and Universities Based on the Intelligent Optimization Method

Evaluation of the Physical Education Teaching and Training Efficiency by the Integration of Ideological and Political Courses with Lightweight Deep Learning

Profile of Intelligent Hybrid Information System in Mobile World

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