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| 1 | Evaluation of a laying-hen tracking algorithm based on a hybrid support vector machine显示文摘Background: Behavior is an important indicator reflecting the welfare of animals. Manual analysis of video is the most commonly used method to study animal behavior. However, this approach is tedious and depends on a subjective judgment of the analysts. There is an urgent need for automatic identification of individual animals and automatic tracking is a fundamental part of the solution to this problem.Results: In this study, an algorithm based on a Hybrid Support Vector Machine(HSVM) was developed for the automated tracking of individual laying hens in a layer group. More than 500 h of video was conducted with laying hens raised under a floor system by using an experimental platform. The experimental results demonstrated that the HSVM tracker outperformed the Frag(fragment-based tracking method), the TLD(Tracking-Learning-Detection),the PLS(object tracking via partial least squares analysis), the Mean Shift Algorithm, and the Particle Filter Algorithm based on their overlap rate and the average overlap rate.Conclusions: The experimental results indicate that the HSVM tracker achieved better robustness and state-of-theart performance in its ability to track individual laying hens than the other algorithms tested. It has potential for use in monitoring animal behavior under practical rearing conditions. | Cheng Wang Hongqian Chen Xuebin Zhang Chaoying Meng | 2017 | Journal of Animal Science and Biotechnology2017，8，1： | 5 |
| 2 | Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms显示文摘Management of poultry farms in China mostly relies on manual labor.Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents,making it very difficult for data retrieve,processing and analysis.An integrated cloud-based data management system(CDMS)was proposed in this study,in which the asynchronous data transmission,distributed file system,and wireless network technology were used for information collection,management and sharing in large-scale egg production.The cloud-based platform can provide information technology infrastructures for different farms.The CDMS can also allocate the computing resources and storage space based on demand.A real-time data acquisition software was developed,which allowed farm management staff to submit reports through website or smartphone,enabled digitization of production data.The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center.All the valid historical data of poultry farms can be stored to the remote cloud data center,and then eliminates the need for large server clusters on the farms.Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide. | Chen Hongqian Hongwei Xin Teng Guanghui Meng Chaoying Du Xiaodong Mao Taotao Wang Cheng | 2016 | International Journal of Agricultural and Biological Engineering2016，9，4： | 3 |
| 3 | Comparison of Mastoscopic and Conventional Axillary Lymph Node Dissection in Breast Cancer: Long-term Results From a Randomized, Multicenter Trial显示文摘 | Chengyu Luo Wenbin Guo Jie Yang Qiuru Sun Wei Wei Suhua Wu Shubing Fang Qingliang Zeng Zhensheng Zhao Fanjie Meng Xuandong Huang Xianlan Zhang Ruihua Li Xiufeng Ma Chaoying Luo Yun Yang | 2012 | Mayo Clinic Proceedings2012，，12： | 1 |
| 4 | In-situ stress of coal reservoirs in the Zhengzhuang area of the southern Qinshui Basin and its effects on coalbed methane development显示文摘In-situ stress is a critical factor influencing the permeability of coal reservoirs and the production capacity of coalbed methane(CBM)wells.Accurate prediction of in-situ stress and investigation of its influence on coal reservoir permeability and production capacity are significant for CBM development.This study investigated the CBM development zone in the Zhengzhuang area of the Qinshui Basin.According to the low mechanical strength of coal reservoirs,this study derived a calculation model of the in-situ stress of coal reservoirs based on the multi-loop hydraulic fracturing method and analyzed the impacts of initial fractures on the calculated results.Moreover,by combining the data such as the in-situ stress,permeability,and drainage and recovery data of CBM wells,this study revealed the spatial distribution patterns of the current in-situ stress of the coal reservoirs and discussed the impacts of the insitu stress on the permeability and production capacity.The results are as follows.(1)Under given fracturing pressure,longer initial fractures are associated with higher calculated maximum horizontal principal stress values.Therefore,ignoring the effects of the initial fractures will cause the calculated values of the in-situ stress to be less than the actual values.(2)As the burial depth increases,the fracturing pressure,closure pressure,and the maximum and minimum horizontal principal stress of the coal reservoirs in the Zhengzhuang area constantly increase.The average gradients of the maximum and minimum horizontal principal stress are 3.17 MPa/100 m and 2.05 MPa/100 m,respectively.(3)Coal reservoir permeability is significantly controlled by the magnitude and state of the current in-situ stress.The coal reservoir permeability decreases exponentially with an increase in the effective principal stress.Moreover,a low lateral pressure coefficient(less than 1)is associated with minor horizontal compressive effects and high coal reservoir permeability.(4)Under similar conditions,such as resource endowments,CBM well capacity is higher in primary structural coal regions with moderate paleotectonic stress modification,low current in-situ stress,and lateral pressure coefficient of less than 1. | Peng Zhang Ya Meng Chaoying Liu Yuanling Guo Xiangbin Yan Lixue Cai Zhe Cheng | 2023 | Energy Geoscience2023，4，2： | 0 |
| 5 | Experimental Tests of Different Types of Flanges for Cryogenic Vacuum Seals显示文摘 | Meng Jun Luo Cheng Zhang Junhui Niu Zhiwei Nie Zengshen Hao Chaoying | 2011 | IMP & HIRFL Annual Report2011，，1： | 0 |
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