The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

The biometric identification method is a current research hotspot in the pattern recognition field. Due to the advantages of electrocardiogram (ECG) signals, which are difficult to replicate and easy to obtain, ECG-based identity identification has become a new direction in biometric recognition research. In order to improve the accuracy of ECG signal identification, this paper proposes an ECG identification method based on a multi-scale wavelet transform combined with the unscented Kalman filter (WT-UKF) algorithm and the improved particle swarm optimization-support vector machine (IPSO-SVM). First, the WT-UKF algorithm can effectively eliminate the noise components and preserve the characteristics of ECG signals when denoising the ECG data. Then, the wavelet positioning method is used to detect the feature points of the denoised signals, and the obtained feature points are combined with multiple feature vectors to characterize the ECG signals, thus reducing the data dimension in identity identification. Finally, SVM is used for ECG signal identification, and the improved particle swarm optimization (IPSO) algorithm is used for parameter optimization in SVM. According to the analysis of simulation experiments, compared with the traditional WT denoising, the WT-UKF method proposed in this paper improves the accuracy of feature point detection and increases the final recognition rate by 1.5%. The highest recognition accuracy of a single individual in the entire ECG identification system achieves 100%, and the average recognition accuracy can reach 95.17%.

Applying resource bricolage theory to the city integration of new-generation migrant workers in China.

New-generation migrant workers in Chinese cities are struggling with a lack of urban resources, such as capital, skills, and relationships. To cope with the pressure of these resource constraints, new-generation migrant workers obtain urban development opportunities through resource bricolage. Based on a questionnaire survey of 365 new-generation migrant workers, we used a multiple regression analysis to study the mechanism underlying the effects of resource bricolage on the city integration of new-generation migrant workers. There were four findings: (1) resource bricolage had a significant positive effect on career growth and city integration; (2) career growth had a mediation effect on the relationship between resource bricolage and city integration; (3) environmental dynamism had a positive moderating effect on the relationship between resource bricolage and city integration for new-generation migrant workers; and (4) resource bricolage and environmental dynamism had a moderating effect on city integration through the mediation effect of career growth. The results suggest that resource bricolage promotes the career growth of new-generation migrant workers and further promotes their city integration, and that the environmental dynamism faced by workers is the external condition for promoting integration through resource bricolage. The study emphasizes the importance of resource bricolage in new-generation migrant workers' city integration.