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Identifying Unsafe Behavior of Construction Workers: A Dynamic Approach Combining Skeleton Information and Spatiotemporal Features
Data Availability Statement:
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.Vision-based methods for action recognition are valuable for supervising construction workers’ unsafe behaviors. However, current monitoring methods have limitations in extracting dynamic information about workers. Identifying hazardous actions based on the spatiotemporal relationships between workers’ skeletal points remains a significant challenge in construction sites. This paper proposed an automated method for recognizing dynamic hazardous actions. The method used the OpenPose network to extract workers’ skeleton information from the video and applied a spatiotemporal graph convolutional network (ST-GCN) to analyze the dynamic spatiotemporal relationships between workers’ body skeletons, enabling automatic recognition of hazardous actions. A novel human partitioning strategy and nonlocal attention mechanism were designed to assign appropriate weight parameters to different joints involved in actions, thereby improving the recognition accuracy of complex construction actions. The enhanced model is called the attention module spatiotemporal graph convolutional network (AM-STGCN). The method achieved a test accuracy of 90.50% and 87.08% in typical work scenarios, namely high-altitude scaffolding scenes with close-up and far views, surpassing the performance of the original ST-GCN model. The high-accuracy test results demonstrate that the model can accurately identify workers’ hazardous actions. The newly proposed model is inferred to have promising application prospects and the potential to be applied in broader construction scenarios for on-site monitoring of hazardous actions.National Natural Science Foundation of China (Grant No. 72071097); MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No.20YJAZH034); Foundation of Jiangsu University (Grant No. SZCY-014)
Prevalence of soil transmitted nematodes on Nukufetau, a remote Pacific island in Tuvalu
BACKGROUND: The population of Nukufetau, a remote coral atoll island in Tuvalu in the Western Pacific, received annual mass drug administration (MDA) of diethylcarbamazine and albendazole under the Pacific Elimination of Lymphatic Filariasis program in 2001, 2002 and 2003, with the last MDA occurring six months before a cross-sectional survey of the whole population for soil transmitted helminths (STH). METHODS: A cross-sectional survey in May 2004 recruited 206 residents (35.2% of the population) who provided a single faecal sample that was preserved, concentrated and examined microscopically. RESULTS: Overall prevalence of STH was 69.9%; only hookworm and Trichuris trichiura were diagnosed. Trichuris was present in 68.4% with intensity of infection being light in 56.3%, medium in 11.7% and heavy in 0.5%. Hookworm occurred in 11.7% with intensity of infection 11.2% being light and medium in 0.5%. Twenty individuals (9.7%) had dual infections. The prevalence of Trichuris was constant across all ages while the prevalence of hookworm was significantly lower in residents below 30 years of age. In the age group 5–12 years comparison of results with a 2001 survey [1] suggested that the prevalence of STH has declined minimally, due to sustained high prevalence of Trichuris, while hookworm has declined dramatically from 34.4% to 1.6%. CONCLUSION: The results of this survey suggest that although the MDA appears to have reduced hookworm prevalence in residents below 30 years of age, there has been minimal effect on Trichuris prevalence. An integrated program to control STH is required