Rail defect detection is crucial to rail operations safety. Addressing the problem of high false alarm rates and missed detection rates in rail defect detection, this paper proposes a deep learning method using B-scan image recognition of rail defects with an improved YOLO (you only look once) V3 algorithm. Specifically, the developed model can automatically position a box in B-scan images and recognize EFBWs (electric flash butt welds), normal bolt holes, BHBs (bolt hole breaks), and SSCs (shells, spalling, or corrugation). First, the network structure of the YOLO V3 model is modified to enlarge the receptive field of the model, thus improving the detection accuracy of the model for small-scale objects. Second, B-scan image data are analyzed and standardized. Third, the initial training parameters of the improved YOLO V3 model are adjusted. Finally, the experiments are performed on 453 B-scan images as the test data set. Results show that the B-scan image recognition model based on the improved YOLO V3 algorithm reached high performance in its precision. Additionally, the detection accuracy and efficiency are improved compared with the original model and the final mean average precision can reach 87.41%.

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Information security noncompliance behaviour of employees within an organization is one of the primary reasons for the high frequency of information security incidents. The issue of information security compliance behaviour has attracted attention and importance. The information came from a poll of 525 Chinese civil officials. This study identified variables through empirical analysis that can forecast extra-role information security policies (ISP) compliance behaviours. Structural equation model (SEM) was established and the data was analysed by SmartPLS (Partial Least Square). The findings demonstrated a substantial relationship between peers' behaviour and extra-role ISP compliance by employees and the company information security atmosphere. Additionally, it was discovered that both the relationship between peer behaviour and extra-role behaviour and the relationship between the information security climate and extrarole behaviour were being mediated by employees' ISP compliance intention and response efficacy. Practical implications are discussed in conclusion.

Work stress not only is a series results of physical, psychological and behavior on individuals, but also influence job satisfaction. In this paper, we propose the research model to explore the relationship between work stress and job satisfaction of the employees of Japanese-investment companies in China. By using SPSS software, the following results are obtained: (1) The whole work stress of the employees of Japanese companies in China is in a little low level, the main stressors of employee of Japanese companies in China are the stress of career development and organizational mechanism and style. (2) The whole job satisfaction is in a low level, the main factor of unsatisfactory is compensation and benefits. (3) There is negative correlation between work stress and other factors except work itself. Based on the research findings and the cross-cultural management characteristics of Japanese companies, corresponding managerial implications are put forward.