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      Sports Medical Image Modeling of Injury Prevention in Dance Learning and Sports Training

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          Abstract

          In order to effectively prevent injuries in dance learning and sports training, this paper proposes a method based on sports medical image modeling. This method solves the problem of injury prevention in dance learning by studying the association analysis algorithm, medical image information system, and CT technology and analyzing the role of data mining technology in the medical image information system. The experimental results show that the average prediction error of CT and US is about 5%, which can be considered that the model can predict accurately. The error of MR is as high as 28.2%, and the prediction is relatively inaccurate. Conclusion. the model can effectively prevent the injury in training.

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          Progress of zinc oxide‐based nanocomposites in the textile industry

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            A Secure, Energy- and SLA-Efficient (SESE) E-Healthcare Framework for Quickest Data Transmission Using Cyber-Physical System

            Due to advances in technology, research in healthcare using a cyber-physical system (CPS) opens innovative dimensions of services. In this paper, the authors propose an energy- and service-level agreement (SLA)-efficient cyber physical system for E-healthcare during data transmission services. Furthermore, the proposed phenomenon will be enhanced to ensure the security by detecting and eliminating the malicious devices/nodes involved during the communication process through advances in the ad hoc on-demand distance vector (AODV) protocol. The proposed framework addresses the two security threats, such as grey and black holes, that severely affect network services. Furthermore, the proposed framework used to find the different network metrics such as average qualifying service set (QSS) paths, mean hop and energy efficiency of the quickest path. The framework is simulated by calculating the above metrics in mutual cases i.e., without the contribution of malevolent nodes and with the contribution of malevolent nodes over service time, hop count and energy constraints. Further, variation of SLA and energy shows their expediency in the selection of efficient network metrics.
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              Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm

              The basic task of railway signal work is to ensure safe and smooth transportation, improve transportation capacity, and improve transportation conditions and quality. Since it carries important information and control technology; it must be characterized by high security and high reliability. To address the aforementioned issues, this study uses a nonlinear technique to provide high-precision real-time detection of frequency shift signal parameters, based on an investigation of the sources of spectrum leakage in the FFT transformation. It not only reduces the sampling time but also the computation time when compared to the nonlinear method. This paper presents a frequency shift track circuit parameter based on nonlinear algorithm, studies the application of frequency shift signal parameter detection based on nonlinear algorithm, and simulates it with MATLAB. The experimental results show that the errors of center frequency, low frequency, and frequency offset are distributed in the range of ±0.05 Hz, ±0.005 Hz and ±0.15 Hz, respectively, which meet the parameters of frequency shift signal. The algorithm can meet the requirement of technical indexes and shorten the sampling time, which provides a theoretical basis for the design of the real-time frequency shift signal parameter tester.
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                Author and article information

                Contributors
                Journal
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                SCANNING
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                Hindawi
                0161-0457
                1932-8745
                2022
                27 July 2022
                : 2022
                : 7027007
                Affiliations
                Liupanshui Normal University, Liupanshui, Guizhou 553004, China
                Author notes

                Academic Editor: Danilo Pelusi

                Author information
                https://orcid.org/0000-0001-6357-5942
                Article
                10.1155/2022/7027007
                9348966
                35950088
                d8ed9b9b-1a6f-4435-b468-958d460fce35
                Copyright © 2022 Renying Fei.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 June 2022
                : 9 July 2022
                : 16 July 2022
                Categories
                Research Article

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