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| 1 | Significance of vulnerability assessment in establishment of Hainan provincal disaster medical system显示文摘Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role.Given the limited transportation route from Hainan to the outside world,self-rescue is more important to Hainan Province than other provinces in China and it is therefore imperative to establish an independent, scientific as well as efficient provincal disaster medical system in Hainan.The regulatory role for vulnerability analysis/assessment has been demonstrated in establisment of disaster medical system in varoius countries and or regions.In this paper,we attempt to describe/propose how to adopt vulnerability assessment through mathematical modeling of major biophysical social vulnerability factors to establish an independent,scientific,effieicnt and comprehensive provincial disaster medical system in Hainan. | Min Li Chuanzhu Lu Wei Son Junhong Miao Yipeng Ding Longhe Li Leilei Zhang Nin Zhao Bijiang Hu Yunjun Zhang | 2011 | Asian Pacific Journal of Tropical Medicine2011，4，8： | 2 |
| 2 | Performance tests and hysteresis model of MRF-04K damper显示文摘 | Li Zhongxian Xu Longhe | 2005 | Journal of Structural Engineering ASCE2005，131，8： | 1 |
| 3 | Performance tests and hysteresis model of MRF-04K damper 显示文摘 | Li Zhongxian Xu Longhe | 2005 | Journal of Structural Engineering-ASCE2005，131，8： | 1 |
| 4 | Performance tests and hysteresis model of MRF-04K damper显示文摘 | Li Zhongxian Xu Longhe | 2005 | Journal of Structural Engineering-ASCE2005，131，8： | 1 |
| 5 | Semi-active multi-step predictive control of structures using MR dampers 显示文摘 | Xu Longhe Li Zhongxian | 2008 | Earthquake Engineering and Structural Dynamics2008，37，12： | 1 |
| 6 | Performance tests and hysteresis model of MRF-04K damper 显示文摘 | Li Zhongxian Xu Longhe | 2005 | Journal of Structural Engineering ASCE2005，131，8： | 1 |
| 7 | Novel tracking method for the drinking behavior trajectory of pigs显示文摘Identifying and tracking the drinking behavior of pigs is of great significance for welfare feeding and piggery management. Research on pigs’ drinking behavior not only needs to indicate whether the snout is in contact with the water fountain, but it also needs to establish whether the pig is drinking water and for how long. To solve target loss and identification errors, a novel method for tracking the drinking behavior of pigs based on L-K Pyramid Optical Flow (L-K OPT), Kernelized Correlation Filters (KCF), and DeepLabCut (DLC) was proposed. First, the feature model of the drinking behavior of a sow was established by L-K OPT. In addition, the water flow vector was used to determine whether the animal drank water and to demonstrate the details of the movements. Then, on the basis of the improved KCF, the relocation model of the sow’s snout was established to resolve the problem of tracking loss in the snout. Finally, the tracking model of piglets’ drinking behavior was established by DLC to build the mapping association between the pig’s snout and the drinking fountain. By using 200 episodes of drinking water videos (30-60 s each) to verify the method proposed in this study, the results are explained that 1) according to the two important drinking water indexes, the Down (−135°, −45°) direction feature and the V2 (>10 pixels) speed feature, the drinking time could be accurate to the frame level, with an error within 30 frames;2) The overlapping precision (OP) was 95%, the center location error (CLE) was 3 pixels, and the speed was 300 fps, which were all superior to other traditional algorithms;3) The optimal learning rate was 0.005, and the loss value was 0.0 002. The method proposed in this study realized accurate and automatic monitoring of the drinking behavior of pigs, which could provide reference for other animal behavior monitoring. | Chengqi Liu Haijian Ye Longhe Wang Shuhan Lu Lin Li | 2023 | International Journal of Agricultural and Biological Engineering2023，16，6： | 0 |
| 8 | Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF显示文摘The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs.Accordingly,this study proposed a novel approach for the skeleton extraction and pose estimation of piglets.First,an improved Zhang-Suen(ZS)thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons.Then,body nodes were extracted on the basis of the improved DeepLabCut(DLC)algorithm,and a part affinity field(PAF)was added to realize the connection of body nodes,and consequently,construct a database of pig behavior and postures.Finally,a support vector machine was used for pose matching to recognize the main behavior of piglets.In this study,14000 images of piglets with different types of behavior were used in posture recognition experiments.Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation,medial axis transformation,morphology refinement,and the traditional ZS algorithm.The node tracking accuracy reached 85.08%,and the pressure test could accurately detect up to 35 nodes of 5 pigs.The average accuracy of posture matching was 89.60%.This study not only realized the single-pixel extraction of piglets’skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets.Furthermore,this study established a database of pig posture behavior,which provides a reference for studying animal behavior identification and classification and anomaly detection. | Chengqi Liu Haijian Ye Shuhan Lu Zhan Tang Zhao Bai Lei Diao Longhe Wang Lin Li | 2023 | International Journal of Agricultural and Biological Engineering2023，16，3： | 0 |
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