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Digital Communications and Networks 2021年第2期7卷 170-177页

作者： Xu Yang hongyan xing Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Key Laboratory of Meteorological Detection and Information Processing Nanjing University of Information Science and TechnologyNanjing210044China

Data loss or distortion causes adverse effects on the accuracy and stability of the thunderstorm point charge *** solve this problem,we propose a data complementary method based on the atmospheric electric field apparatus array *** electric field component measurement model of the atmospheric electric field apparatus is established,and the orientation parameters of the thunderstorm point charge are *** on the mirror method,the thunderstorm point charge coordinates are obtained by using the potential distribution *** test the validity of the basic algorithm,the electric field component measurement error and the localization accuracy are *** the azimuth angle and the elevation angle,the localization parameters also include the distance from the apparatus to the thunderstorm *** on a primary electric field apparatus,we establish the array group of *** on this,the data measured by each apparatus is complementarily processed to regain the thunderstorm point charge *** results show that,compared with the radar map data,this method can accurately reflect the location of the thunderstorm point charge,and has a better localization ***,several observation results during thunderstorm weather have been presented.

关键词： Atmospheric electric field apparatus Array Thunderstorm point charge Data complementary

Influence of Residual Stress on the Dimensional Instability of 7075 Aluminum Cone-Shaped Shells

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稀有金属材料与工程 2009年第A3期38卷 91-94页

作者： Wang Qiucheng Zhao Zude Wang Yisi xing hongyan Kang Feng MOE Key Lab of Mechanical Manufacture ＆Automation Zhejiang University of Technology Hangzhou 310032 China No.59 institute of China Ordnance Industry Chongqing 400039 China

This paper dealt with the influence of residual stress on the dimensional instability of 7075 aluminum cone-shaped shells. Finite element method was introduced to calculate residual stress distributions in 7075 aluminum cone-shaped shells during conventional heat treatment (CHT) and deep cryogenic treatment (DCT). An example was given to demonstrate effects of deep cryogenic treatment (DCT) and conventional heat treatment (CHT) on dimensional instability. It is concluded that initial residual stresses have detrimental influence on the dimensional instability of 7075 aluminum cone-shaped shells.

关键词：残余应力铝合金有限元分析物理性能

Distributed Sea Clutter Denoising Algorithm Based on Variational Mode Decomposition

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Instrumentation 2020年第3期7卷 23-32页

作者： SUN Jiang xing hongyan WU Jiajia Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and TechnologyNanjing 210044 Jiangsu Key Laboratory of Meteorological Detection and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044

In order to improve the detection accuracy of chaotic small signal prediction models under the background of sea clutter,a distributed sea clutter denoising algorithm is proposed,on the basis of variational modal decomposition(VMD).The sea clutter signal is decomposed into variational modal functions(VMF)with different center bandwidths by means of *** analyzing the autocorrelation characteristics of the deco mposed signal,we perform instantaneous half-period(IHP)and wavelet threshold denoising processing on the high-frequency and low-frequency components respectively,and regain the sea clutter *** on LSSVM sea clutter prediction model,this research compares and analyzes the denoising effects of *** ment results show that,the RMSE after denoising is reduced by two orders of magnitude,approximating 0.00034,with an apparently better denoising effect,compared with the root mean square error(RMSE)of the prediction before denoising.

关键词： Sea Clutter Variational Modal Decomposition Autocorrelation Properties Instantaneous Half-Period

Positional cloning and characterization reveal the role of a miRNA precursor gene ZmLRT in the regulation of lateral root number and drought tolerance in maize

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Journal of Integrative Plant Biology 2023年第3期65卷 772-790页

作者： Ming Zhang Yanhong Chen hongyan xing Wensheng Ke Yunlu Shi Zhipeng Sui Ruibin Xu Lulu Gao Ganggang Guo Jiansheng Li Jiewen xing Yirong Zhang State Key Laboratory for Agrobiotechnology Key Laboratory of Crop Heterosis and Utilization(MOE)Key Laboratory of Crop Genetic ImprovementChina Agricultural UniversityBeijing 100193China Agronomy College of Shandong Agricultural University Taian 271018China Key L aboratory of Crop Germplasm Resources and Utilization(MARA) Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijing 100081China Center for Crop Functional Genomics and Molecular Breeding China Agricultural UniversityBeijing 100193China Yantai Science and Technology Innovation Promotion Center Yantai 264003China Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding Maize Research InstituteBeijing Academy of Agriculture and Forestry SciencesBeijing 100097China National Maize Improvement Center of China China Agricultural UniversityBeijing 100193China

Lateral roots play essential roles in drought tolerance in maize(Zea mays L.). However, the genetic basis for the variation in the number of lateral roots in maize remains elusive. Here, we identified a major quantitative trait locus(QTL),q LRT5-1, controlling lateral root number using a recombinant inbred population from a cross between the maize lines Zong3(with many lateral roots) and 87-1(with few lateral roots).Fine-mapping and functional analysis determined that the candidate gene for qLRT5-1,ZmLRT, expresses the primary transcript for the microRNA miR166a. ZmLRT was highly expressed in root tips and lateral root primordia,and knockout and overexpression of ZmLRT increased and decreased lateral root number,respectively. Compared with 87-1, the ZmLRT gene model of Zong3 lacked the second and third exons and contained a 14 bp deletion at the junction between the first exon and intron,which altered the splicing site. In addition,ZmLRT expression was significantly lower in Zong3 than in 87-1, which might be attributed to the insertions of a transposon and over large DNA fragments in the Zong3 ZmLRT promoter region. These mutations decreased the abundance of mature miR166a in Zong3, resulting in increased lateral roots at the seedling ***, miR166a post-transcriptionally repressed five development-related class-Ⅲ homeodomain-leucine zipper genes. Moreover,knockout of ZmLRT enhanced drought tolerance of maize seedlings. Our study furthers our understanding of the genetic basis of lateral root number variation in maize and highlights ZmLRT as a target for improving drought tolerance in maize.

关键词： drought tolerance lateral root number maize miRNA precursor QTL mapping

Hybrid Gaussian Network Intrusion Detection Method Based on CGAN and E-GraphSAGE

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Instrumentation 2024年第2期11卷 24-35页

作者： Xinyi Liang hongyan xing Wei Gu Tianhao Hou Zhiwei Ni Xinyi Wang School of Electronics Information Engineering Nanjing University of Information Science&TechnologyNanjing 210044

The rapid development of the Internet of Things(IoT)and modern information technology has led to the emergence of new types of *** poses a great potential danger to network ***,protecting against network attacks has become a pressing issue that requires urgent *** is crucial to find practical solutions to combat such malicious behavior.A network intrusion detection(NID)method,known as GMCE-GraphSAGE,was proposed to meet the detection demands of the current intricate network *** data is mapped into gaussian distribution,which helps to ensure that subsequent models can effectively learn the features of traffic *** conditional generative adversarial network(CGAN)can generate attack samples based on specified labels to create balanced traffic *** addition,we constructed a communication interaction graph based on the connection patterns of traffic *** E-GraphSAGE is designed to capture both the topology and edge features of the traffic *** it,global behavioral information is combined with traffic features,providing a solid foundation for classifying and *** on the UNSW-NB15 dataset demonstrate the great detection advantage of the proposed *** binary and multi-classification F1-score can achieve 99.36%and 89.29%,*** GMCE-GraphSAGE effectively improves the detection rate of minority class samples in the NID task.

关键词： network intrusion detection IoT deep learning

Frequency modulated weak signal detection based on stochastic resonance and genetic algorithm

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Instrumentation 2016年第1期3卷 41-49页

作者： xing hongyan LU Chunxia ZHANG Qiang Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology Key Laboratory of Meteorological Observation and Information Processing of Jiangsu Province Nanjing University of Information Science & Technology

Stochastic resonance system is subject to the restriction of small frequency parameter in weak signal detection,in order to solve this problem,a frequency modulated weak signal detection method based on stochastic resonance and genetic algorithm is presented in this paper. The frequency limit of stochastic resonance is eliminated by introducing carrier signal,which is multiplied with the measured signal to be injected in the stochastic resonance system,meanwhile,using genetic algorithm to optimize the carrier signal frequency,which determine the generated difference-frequency signal in the lowfrequency range,so as to achieve the stochastic resonance weak signal detection. Results showthat the proposed method is feasible and effective,which can significantly improve the output SNR of stochastic resonance,in addition,the system has the better self-adaptability,according to the operation result and output phenomenon,the unknown frequency of the signal to be measured can be obtained,so as to realize the weak signal detection of arbitrary frequency.

关键词： stochastic resonance two-dimension Duffing oscillator frequency modulated genetic algorithm

Adaptive stochastic resonance method for weak signal detection based on particle swarm optimization

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Instrumentation 2015年第2期2卷 3-10页

作者： xing hongyan ZHANG Qiang LU Chunxia Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology Key Laboratory of Meteorological Observation and Information Processing of Jiangsu Province Nanjing University of Information Science & Technology

In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability in the system of two-dimensional Duffing based on particle swarm ***,the influence of different parameters on the detection performance is analyzed *** correlation between parameter adjustment and stochastic resonance effect is also discussed and converted to the problem of multi-parameter ***,the experiments including typical system and sea clutter data are conducted to verify the effect of the proposed *** show that the proposed method is highly effective to detect weak signal from chaotic background,and enhance the output SNR greatly.

关键词： Adaptive stochastic resonance two-dimensional Duffing oscillator weak signal detection particle swarm optimization

基于Hilbert-Huang变换的QRS波检测算法研究

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仪器仪表学报 2009年第7期30卷 1469-1475页

作者：行鸿彦黄敏松南京信息工程大学电子与信息工程学院南京210044

心电图(ECG)被广泛应用于心脏疾病诊断,而ECG中QRS复合波的检测是对ECG进行处理和分析的基础。本文提出一种新的QRS复合波检测算法。该算法利用Hilbert-Huang变换(HHT)中的经验模式分解(EMD)将心电信号自适应地分解为一组称为内禀模态函... 详细信息

心电图(ECG)被广泛应用于心脏疾病诊断,而ECG中QRS复合波的检测是对ECG进行处理和分析的基础。本文提出一种新的QRS复合波检测算法。该算法利用Hilbert-Huang变换(HHT)中的经验模式分解(EMD)将心电信号自适应地分解为一组称为内禀模态函数(IMF)的波动模态成分。然后,结合软阈值去噪方法,构造出有利于QRS复合波检测的检测层,利用模极大值和QRS复合波特征点之间的对应关系,实现了对QRS复合波的检测。经MIT-BIH心率失常数据库验证,该算法对QRS复合波检测的平均准确率达到了99.34%,平均灵敏度为99.77%,平均阳性预测率为99.56%。

关键词： Hilbert—Huang变换经验模式分解 QRS复合波内禀模态函数

基于多旋翼无人机的正交式风压矢量分解测风法

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仪器仪表学报 2019年第10期40卷 200-207页

作者：侯天浩行鸿彦刘洋南京信息工程大学气象灾害预报预警与评估协同创新中心南京210044 南京信息工程大学江苏省气象探测与信息处理重点实验室南京210044

针对多旋翼无人机平台上的测风设备会受到旋翼扰流干扰的问题,基于伯努利方程提出了一种适用于多旋翼无人机的利用正交式风压矢量分解反演风速风向的算法,并通过设计感压腔的布局与结构进一步降低了旋翼扰流的影响。利用Space claim和Me... 详细信息

针对多旋翼无人机平台上的测风设备会受到旋翼扰流干扰的问题,基于伯努利方程提出了一种适用于多旋翼无人机的利用正交式风压矢量分解反演风速风向的算法,并通过设计感压腔的布局与结构进一步降低了旋翼扰流的影响。利用Space claim和Meshing软件建立测风模型,通过Fluent软件改变流场内气流的速度与方向,对该测风法在不同流场中进行了仿真研究。在实际测量中,当风速高于2 m/s时正交式风压矢量分解测风法的测风速误差均保持在10%以内,证明了该法可以有效降低旋翼扰流对测风的干扰,实现高精度测风。

关键词：多旋翼无人机测风风压流场整流罩

基于网络流量时空特征和自适应加权系数的异常流量检测方法

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电子与信息学报 2024年第6期46卷 2647-2654页

作者：顾伟行鸿彦侯天浩南京信息工程大学电子与信息工程学院南京210044

针对传统异常流量检测模型对流量数据时空特性利用率较低从而导致检测模型性能较差的问题,该文提出一种基于融合卷积神经网络(CNN)、多头挤压激励机制(MSE)和双向长短期记忆(BiLSTM)网络的异常流量检测方法MSECNN-BiLSTM。利用1维CNN挖... 详细信息

针对传统异常流量检测模型对流量数据时空特性利用率较低从而导致检测模型性能较差的问题,该文提出一种基于融合卷积神经网络(CNN)、多头挤压激励机制(MSE)和双向长短期记忆(BiLSTM)网络的异常流量检测方法MSECNN-BiLSTM。利用1维CNN挖掘空间尺度下的异常流量特征,并引入MSE,多角度自适应特征加权,强化模型全局特征的关联能力。将网络流量的特征输入BiLSTM,捕捉流量数据的时序依赖性,进一步建立网络流量在时间尺度上的关系模型。利用softmax分类器进行预测分类,实验结果验证了所提模型在异常流量检测领域的有效性。

关键词：异常流量检测卷积神经网络长短期记忆网络挤压激励机制