Design and Implementation of Intelligent Sports Training System for College Students' Mental Health Education

Wang, Ting; Park, Jinkyung

doi:10.3389/fpsyg.2021.634978

Cited by 53 publications

(34 citation statements)

References 27 publications

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“…While traditional sports are one-way streamlined, AI sports project is a client-side sports intelligence system that can verify DEMO, systematize various dynamics, and support technical capability transformation. e intelligent sports system realizes terminal inference of the mobile phone through the deep inference engine [12]. Information response and dynamic corrections are made by identifying and analyzing postures and dynamics, sports track, and dynamic angles, and then, the modular combination of technical capabilities is carried out.…”

Section: Core Concept Definition Andmentioning

confidence: 99%

[Retracted] Design and Research of the AI Badminton Model Based on the Deep Learning Neural Network

Chen

2022

Journal of Mathematics

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In view of the fact that it is difficult for existing algorithms to identify the movements of a player in an accurate way, this paper puts forward an artificial intelligence (AI) motion model on the basis of the deep learning neural network instruction set architecture (ISA). Firstly, a mobile neural network (MNN) inference engine was utilized to create a new AI sports project-side intelligent practice model. Under this model, a movement can be segmented into a series of decomposition movements, which are recognized and judged separately for the purpose of measuring the entire movement. In order to test its feasibility, the study compares the MNN inference engine with the traditional reasoning engine in terms of their algorithmic capabilities and compares the results obtained through this algorithm and traditional online motion app. Research shows that, in the MNN of the AI sports project proposed in this paper, the datasets of action recognition exceed the results of other inference engines, characterized by lightweight, high performance, and accessibility. Research also demonstrates that the AI sports project model can adapt to the needs of sports projects with a variety of themes and improve the accuracy of movement recognition details.

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Section: Core Concept Definition Andmentioning

confidence: 99%

[Retracted] Design and Research of the AI Badminton Model Based on the Deep Learning Neural Network

Chen

2022

Journal of Mathematics

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“…Lecture teaching is a way of teaching students directly by teachers, which is widely used in college classroom teaching. With the advancement of the new curriculum teaching concept, lecture-based teaching is called inculcation teaching or cramming teaching, and independent, cooperative, and inquiry-based teaching methods are advocated in the new curriculum ( Wang and Park, 2021 ). However, in lecturing teaching, teachers can transform complex and profound textbook knowledge into superficial or concrete knowledge that can be understood by students, and eliminate students’ mystery and confusion in learning entrepreneurial knowledge.…”

Section: Entrepreneurship Education and Students’ Entrepreneurial Psychologymentioning

confidence: 99%

The Impact of Young Entrepreneurs’ Network Entrepreneurship Education and Management System Innovation on Students’ Entrepreneurial Psychology

2021

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The purpose of the study is to solve the problems existing in entrepreneurship education and management under computer technology. The teaching content of entrepreneurship education in colleges and universities is proposed. Since entrepreneurship education is practical, the auxiliary mechanism of entrepreneurship education also needs to be highly integrated with entrepreneurship practice. First, the network entrepreneurship teaching and management system is constructed, and students’ entrepreneurial creativity, communication ability, leadership ability, and qualities are taken as the research object. Second, the traditional teaching method, case study method, and scene simulation method are used to analyze and discuss the influence of the entrepreneurial teaching mode, entrepreneurial experience, and entrepreneurial ability on students’ entrepreneurial psychology. Finally, the questionnaire survey is used to conduct the relative sample t-test (Student’s t-test), and the influence of three teaching methods on students’ learning effects is analyzed. The influence of the three teaching methods on students’ entrepreneurial psychological states is further analyzed by the statistical method. The experimental results show that the test result of the scene simulation method and the traditional teaching method is 0.584, the test result of the scene simulation method and the case study method is 0.842, and the test result of the case study method and the traditional teaching method is 0.595. This shows that the scene simulation method has a significant impact on students’ entrepreneurial psychology and their entrepreneurial ability. In addition, students’ cognition of professional status significantly affects their entrepreneurial psychology and attitudes, and the correlation coefficient is 0.576. Therefore, it is suggested that colleges and universities should adopt the scene simulation method to improve the teaching quality of entrepreneurship education and strengthen students’ cognition of professional status and their entrepreneurial practice.

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“…The discussion of DL technology focuses on the discussion of related social science issues and only stays on the method of use, such as the prediction of academic performance [ 17 ]. The application research of DL technology in teaching is mainly focused on the application of social science master's thesis online examination and other education systems [ 18 ]. Researchers proposed a DL-based target detection algorithm and designed an online examination abnormal behavior detection system.…”

Section: Introductionmentioning

confidence: 99%

Online Course Model of Social and Political Education Using Deep Learning

Zhang

Gao

2022

Computational Intelligence and Neuroscience

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This study aims to improve the social and political literacy of college students. Social and Political Education (SPE) is studied for undergraduates. Firstly, the background of the subject research is introduced. The face recognition module is built based on deep convolutional neural network (DCNN). The sociopolitical situation of the study subjects is analyzed through a questionnaire. Secondly, a model of the learning process is constructed. Finally, the SPE online course learning platform is constructed. Empirical studies are divided into experimental and control groups. The findings show that all model assumptions are valid. There is a significant structural relationship between the influencing factors of the SPE learning process of college students in the study area. The students selected as research objects lack innovation and critical thinking in the learning process and have certain deficiencies in innovative thinking and critical thinking. The questionnaire has good reliability and validity. The predicted data of the designed platform are compared with the predicted data of the control group. Social science competencies by gender are compared. The results showed little difference in the effectiveness of students using other methods for sociopolitical learning. The data of the experimental group before and after the test are quite different, indicating that the designed experimental platform has played a certain positive role. There are significant differences in the posttest data between the experimental group and the control group, indicating that the constructed online course learning model has a positive impact on students’ innovative thinking and critical thinking. Women’s learning motivation and transfer learning ability are stronger than those of men. The constructed model has certain feasibility for the learning of SPE online courses with face recognition module. These contents provide a reference for the reform of social and political courses.

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Design and Implementation of Intelligent Sports Training System for College Students' Mental Health Education

Cited by 53 publications

References 27 publications

[Retracted] Design and Research of the AI Badminton Model Based on the Deep Learning Neural Network

[Retracted] Design and Research of the AI Badminton Model Based on the Deep Learning Neural Network

The Impact of Young Entrepreneurs’ Network Entrepreneurship Education and Management System Innovation on Students’ Entrepreneurial Psychology

Online Course Model of Social and Political Education Using Deep Learning

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