Research on Track Fastener Service Status Detection Based on Improved Yolov4 Model

As an important part of railway lines, the healthy service status of track fasteners was very important to ensure the safety of trains. The application of deep learning algorithms was becoming an important method to realize its state detection. However, there was often a deficiency that the detection accuracy and calculation speed of model were difficult to balance, when the traditional deep learning model is used to detect the service state of track fasteners. Targeting this issue, an improved Yolov4 model for detecting the service status of track fasteners was proposed. Firstly, the Mixup data augmentation technology was introduced into Yolov4 model to enhance the generalization ability of model. Secondly, the MobileNet-V2 lightweight network was employed in lieu of the CSPDarknet53 network as the backbone, thereby reducing the number of algorithm parameters and improving the model’s computational efficiency. Finally, the SE attention mechanism was incorporated to boost the importance of rail fastener identification by emphasizing relevant image features, ensuring that the network’s focus was primarily on the fasteners being inspected. The algorithm achieved both high precision and high speed operation of the rail fastener service state detection, while realizing the lightweight of model. The experimental results revealed that, the MAP value of the rail fastener service state detection algorithm based on the improved Yolov4 model reaches 83.2%, which is 2.83% higher than that of the traditional Yolov4 model, and the calculation speed was improved by 67.39%. Compared with the traditional Yolov4 model, the proposed method achieved the collaborative optimization of detection accuracy and calculation speed.

The current status of community mental health services in three northern areas of China

Objective:This study investigated and discussed the current status of community mental health service in three northern areas of China(Beijing,Harbin,and Karamay)in an effort to improve the community mental health services in China.Methods:In this study 176 residents from communities of the three northern areas of China were involved and divided into 18 groups.The study was conducted according to a self-prepared structured interview outline.Results:The analysis was conducted based on the following four perspectives:1.commu-nity residents’understanding of the mental health problems and how they treated psychiatric patients;2.community residents’access to and application of mental health information;3.com-munity residents’attitude to accept mental health services and the factors influencing community residents to seek help from mental health services;and 4.community residents’attitude and will-ingness to participate in the activities of community mental health services.Conclusion:Based on the investigation and analysis regarding the current status of the com-munity mental health services in three northern areas of China,it is concluded that the residents do not have s clear and complete understanding of mental health.The characteristics of mental health services had a regional correlation.Currently,the mental health services do not work effectively,and the residents are somewhat passive in obtaining information about mental health.Community mental health services should be offered according to different individual needs of the residents and the actual situations of each region.