A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer syste...A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.展开更多
Bacterial fruit blotch caused by Acidovorax citrulli is a serious threat to cucurbit industry worldwide.The pathogen is seedtransmitted,so seed detection to prevent distribution of contaminated seed is crucial in dise...Bacterial fruit blotch caused by Acidovorax citrulli is a serious threat to cucurbit industry worldwide.The pathogen is seedtransmitted,so seed detection to prevent distribution of contaminated seed is crucial in disease management.In this study,we adapted a quantitative real-time PCR(qPCR)assay to droplet digital PCR(ddPCR)format for A.citrulli detection by optimizing reaction conditions.The performance of ddPCR in detecting A.citrulli pure culture,DNA,infested watermelon/melon seed and commercial seed samples were compared with multiplex PCR,qPCR,and dilution plating method.The lowest concentrations detected(LCD)by ddPCR reached up to 2 fg DNA,and 102 CFU mL–1 bacterial cells,which were ten times more sensitive than those of the qPCR.When testing artificially infested watermelon and melon seed,0.1%infestation level was detectable using ddPCR and dilution plating method.The 26 positive samples were identified in 201 commercial seed samples through ddPCR,which was the highest positive number among all the methods.High detection sensitivity achieved by ddPCR demonstrated a promising technique for improving seed-transmitted pathogen detection threshold in the future.展开更多
The establishment of highly sensitive diagnostic methods is critical in the early diagnosis and control of Zika virus(ZIKV)and in preventing serious neurological complications of ZIKV infection. In this study, we esta...The establishment of highly sensitive diagnostic methods is critical in the early diagnosis and control of Zika virus(ZIKV)and in preventing serious neurological complications of ZIKV infection. In this study, we established micro-droplet digital polymerase chain reaction(ddPCR) and real-time quantitative PCR(RT-qPCR) protocols for the detection of ZIKV based on the amplification of the NS5 gene. For the ZIKV standard plasmid, the RT-qPCR results showed that the cycle threshold(Ct) value was linear from 10~1 to 10~8 copy/l L, with a standard curve R^2 of 0.999 and amplification efficiency of 92.203%;however, a concentration as low as 1 copy/l L could not be detected. In comparison with RT-qPCR, the dd PCR method resulted in a linear range of 10~1–10~4 copy/l L and was able to detect concentrations as low as 1 copy/l L. Thus, for detecting ZIKV from clinical samples, RT-qPCR is a better choice for high-concentration samples(above 10~1 copy/l L),while ddPCR has excellent accuracy and sensitivity for low-concentration samples. These results indicate that the ddPCR method should be of considerable use in the early diagnosis, laboratory study, and monitoring of ZIKV.展开更多
Background:Intelligent monitoring of human action in production is an important step to help standardize production processes and construct a digital twin shop-floor rapidly.Human action has a significant impact on th...Background:Intelligent monitoring of human action in production is an important step to help standardize production processes and construct a digital twin shop-floor rapidly.Human action has a significant impact on the production safety and efficiency of a shop-floor,however,because of the high individual initiative of humans,it is difficult to realize real-time action detection in a digital twin shop-floor.Methods:We proposed a real-time detection approach for shop-floor production action.This approach used the sequence data of continuous human skeleton joints sequences as the input.We then reconstructed the Joint Classification-Regression Recurrent Neural Networks(JCR-RNN)based on Temporal Convolution Network(TCN)and Graph Convolution Network(GCN).We called this approach the Temporal Action Detection Net(TAD-Net),which realized real-time shop-floor production action detection.Results:The results of the verification experiment showed that our approach has achieved a high temporal positioning score,recognition speed,and accuracy when applied to the existing Online Action Detection(OAD)dataset and the Nanjing University of Science and Technology 3 Dimensions(NJUST3D)dataset.TAD-Net can meet the actual needs of the digital twin shop-floor.Conclusions:Our method has higher recognition accuracy,temporal positioning accuracy,and faster running speed than other mainstream network models,it can better meet actual application requirements,and has important research value and practical significance for standardizing shop-floor production processes,reducing production security risks,and contributing to the understanding of real-time production action.展开更多
A multiscale foreground detection method was developed to segment moving objects from a sta- tionary background. The algorithm is based on a fixed-mesh-based contour model, which starts at the bounding box of the di...A multiscale foreground detection method was developed to segment moving objects from a sta- tionary background. The algorithm is based on a fixed-mesh-based contour model, which starts at the bounding box of the difference map between an input image and its background and ends at a final contour. An adaptive algorithm was developed to calculate an appropriate energy threshold to control the contours to identify the foreground silhouettes. Experiments show that this method more successfully ignores the nega- tive influence of image noise to obtain an accurate foreground map than other foreground detection algo- rithms. Most shadow pixels are also eliminated by this method.展开更多
为了从环境中检测出相位量化数字射频存储器(Digital radio frequency memory,DRFM)欺骗干扰的存在,本文设计了一种能够在均匀环境中检测出噪声、干扰或回波信号的自适应检测器。检测过程分为两步:先由基于广义似然比检测(Generalized l...为了从环境中检测出相位量化数字射频存储器(Digital radio frequency memory,DRFM)欺骗干扰的存在,本文设计了一种能够在均匀环境中检测出噪声、干扰或回波信号的自适应检测器。检测过程分为两步:先由基于广义似然比检测(Generalized likelihood ratio test,GLRT)的自适应匹配滤波(Adaptive matched filter,AMF)检测器完成噪声和"信号"(滤波后的回波信号或干扰)的检测;再从回波信号和干扰导引矢量间的差异性出发重新设计检测器,以甄别回波信号或干扰。最后,通过理论推导和蒙特卡洛试验对检测器的性能进行分析和评估,并与透视检测器进行比较。仿真结果表明,在低相位量化位数和高信噪比的条件下,所设计的检测器能够正确检测出干扰信号的存在。展开更多
文摘A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.
基金supported by the the National Key Research and Development Program of China (2017YFD0201602)the National Natural Science Foundation of China (31401704)the Beijing Academy of Agriculture and Forestry Foundation, China (KJCX20180203)
文摘Bacterial fruit blotch caused by Acidovorax citrulli is a serious threat to cucurbit industry worldwide.The pathogen is seedtransmitted,so seed detection to prevent distribution of contaminated seed is crucial in disease management.In this study,we adapted a quantitative real-time PCR(qPCR)assay to droplet digital PCR(ddPCR)format for A.citrulli detection by optimizing reaction conditions.The performance of ddPCR in detecting A.citrulli pure culture,DNA,infested watermelon/melon seed and commercial seed samples were compared with multiplex PCR,qPCR,and dilution plating method.The lowest concentrations detected(LCD)by ddPCR reached up to 2 fg DNA,and 102 CFU mL–1 bacterial cells,which were ten times more sensitive than those of the qPCR.When testing artificially infested watermelon and melon seed,0.1%infestation level was detectable using ddPCR and dilution plating method.The 26 positive samples were identified in 201 commercial seed samples through ddPCR,which was the highest positive number among all the methods.High detection sensitivity achieved by ddPCR demonstrated a promising technique for improving seed-transmitted pathogen detection threshold in the future.
基金supported by the National Natural Science Foundation of China (Nos. 31470271 and 81730110)Guangzhou Science and Technology Program key projects (No. 201803040006)
文摘The establishment of highly sensitive diagnostic methods is critical in the early diagnosis and control of Zika virus(ZIKV)and in preventing serious neurological complications of ZIKV infection. In this study, we established micro-droplet digital polymerase chain reaction(ddPCR) and real-time quantitative PCR(RT-qPCR) protocols for the detection of ZIKV based on the amplification of the NS5 gene. For the ZIKV standard plasmid, the RT-qPCR results showed that the cycle threshold(Ct) value was linear from 10~1 to 10~8 copy/l L, with a standard curve R^2 of 0.999 and amplification efficiency of 92.203%;however, a concentration as low as 1 copy/l L could not be detected. In comparison with RT-qPCR, the dd PCR method resulted in a linear range of 10~1–10~4 copy/l L and was able to detect concentrations as low as 1 copy/l L. Thus, for detecting ZIKV from clinical samples, RT-qPCR is a better choice for high-concentration samples(above 10~1 copy/l L),while ddPCR has excellent accuracy and sensitivity for low-concentration samples. These results indicate that the ddPCR method should be of considerable use in the early diagnosis, laboratory study, and monitoring of ZIKV.
基金This work was supported by the National Key Research and Development Program,China(2020YFB1708400)the National Defense Fundamental Research Program,China(JCKY2020210B006,JCKY2017204B053)awarded to TL.
文摘Background:Intelligent monitoring of human action in production is an important step to help standardize production processes and construct a digital twin shop-floor rapidly.Human action has a significant impact on the production safety and efficiency of a shop-floor,however,because of the high individual initiative of humans,it is difficult to realize real-time action detection in a digital twin shop-floor.Methods:We proposed a real-time detection approach for shop-floor production action.This approach used the sequence data of continuous human skeleton joints sequences as the input.We then reconstructed the Joint Classification-Regression Recurrent Neural Networks(JCR-RNN)based on Temporal Convolution Network(TCN)and Graph Convolution Network(GCN).We called this approach the Temporal Action Detection Net(TAD-Net),which realized real-time shop-floor production action detection.Results:The results of the verification experiment showed that our approach has achieved a high temporal positioning score,recognition speed,and accuracy when applied to the existing Online Action Detection(OAD)dataset and the Nanjing University of Science and Technology 3 Dimensions(NJUST3D)dataset.TAD-Net can meet the actual needs of the digital twin shop-floor.Conclusions:Our method has higher recognition accuracy,temporal positioning accuracy,and faster running speed than other mainstream network models,it can better meet actual application requirements,and has important research value and practical significance for standardizing shop-floor production processes,reducing production security risks,and contributing to the understanding of real-time production action.
文摘A multiscale foreground detection method was developed to segment moving objects from a sta- tionary background. The algorithm is based on a fixed-mesh-based contour model, which starts at the bounding box of the difference map between an input image and its background and ends at a final contour. An adaptive algorithm was developed to calculate an appropriate energy threshold to control the contours to identify the foreground silhouettes. Experiments show that this method more successfully ignores the nega- tive influence of image noise to obtain an accurate foreground map than other foreground detection algo- rithms. Most shadow pixels are also eliminated by this method.
文摘为了从环境中检测出相位量化数字射频存储器(Digital radio frequency memory,DRFM)欺骗干扰的存在,本文设计了一种能够在均匀环境中检测出噪声、干扰或回波信号的自适应检测器。检测过程分为两步:先由基于广义似然比检测(Generalized likelihood ratio test,GLRT)的自适应匹配滤波(Adaptive matched filter,AMF)检测器完成噪声和"信号"(滤波后的回波信号或干扰)的检测;再从回波信号和干扰导引矢量间的差异性出发重新设计检测器,以甄别回波信号或干扰。最后,通过理论推导和蒙特卡洛试验对检测器的性能进行分析和评估,并与透视检测器进行比较。仿真结果表明,在低相位量化位数和高信噪比的条件下,所设计的检测器能够正确检测出干扰信号的存在。
