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Detect and attribute the extreme maize yield losses based on spatio-temporal deep learning

Fundamental Research 2023年第6期3卷 951-959页

作者： Renhai Zhong yue Zhu Xuhui wang Haifeng li Bin wang Fengqi You Luis F.Rodríguez Jingfeng Huang K.C.Ting Yibin Ying Tao lin College of Biosystems engineering and Food Science Zhejiang UniversityHangzhouZhejiang 310058China International Campus Zhejiang UniversityHainingZhejiang 314400China Sino-French institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing 100871China school of Geosciences and Info-Physics Central South UniversitySouth Lushan RoadChangsha 410000China NSW Department of Primary Industries Wagga Wagga Agricultural InstitutePine Gully Road Wagga WaggaNSW 2650Australia Robert Frederick Smith school of Chemical and Biomolecular engineering Cornell UniversityIthacaNY 14853USA Department of Agricultural and Biological engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA institute of Applied Remote Sensing and Information technology Zhejiang UniversityHangzhouZhejiang 310058China Key Laboratory of On Site Processing Equipment for Agricultural Products Ministry of Agriculture and Rural AffairsHangzhouZhejiang 310058China Key Laboratory of intelligent Equipment and robotics for Agriculture of Zhejiang Province HangzhouZhejiang 310058China

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food *** the data-driven deep learning approach has shown great capacity in predicting yield patterns,its capacity to detect and attribute the impacts of climatic extremes on yields remains *** this study,we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018,with a special focus on the extreme yield loss in *** found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018(R^(2)=0.81)and well reproduced the extreme yield anomalies in 2012(R^(2)=0.79).Further attribution analysis indicated that extreme heat stress was the major cause for yield loss,contributing to 72.5%of the yield loss,followed by anomalies of vapor pressure deficit(17.6%)and precipitation(10.8%).Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in *** results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

关键词： Crop yield estimation Deep Learning Long short-term memory Multi-task learning Extreme yield loss Attribution analysis

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Construction of Multilayer Porous Scaffold Based on Magnetically Guided Assembly of Microfiber

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Journal of Systems Science & Complexity 2018年第3期31卷 581-595页

作者： li Xingfu wang Huaping SHI Qing SUN Tao HUANG Qiang FUKUDA Toshio intelligent robotics institute School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing 100816 China Key Laboratory of intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper proposes a novel method of magnetically guided assembly to construct multi- layer porous scaffold for three-dimensional cell culture by apply magnetic microfibers. Microfibers are composed of biocompatible and biodegradable alginate solution with homogeneous magnetic nanopar- ticles, which are continuously spun from a microfluidic device by precise pressure control of the syringe pump. Magnetic nanoparticles enable the control of magnetic field on microfibers. Meanwhile, mag- netized device combining with a round permanent magnet are utilized to guide the distribution of spouted microfibers. The device is composed by pure iron wire arrays and wax, which stimulates pow- erful magnetic flux density and magnetic field gradients for the capture and assembly of microfibers. Thus, magnetic microfibers are spun on desired places of the magnetized device by motion control of the micromanipulation robot, and precise locations are adjusted by magnetic force couple with the assist of glass micropipette. Afterwards, microfibers are spatially organized by periodic magnetic force and crossed layer-by-layer to form micro-pore structure with both length and width of 650μm. Finally, the authors construct a multilayer microfiber-based scaffold with high porosity to provide a satisfactory environment for long-term cell culture. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Magnetically guided assembly magnetic microfiber magnetized device periodic magneticforce multilayer porous scaffold.

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An Isomerism Learning Model to Solve Time-Varying Problems Through intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng wang Bob Zhang Leyuan Fang Haisheng li the Department of Computer and Information Science University of MacaoMacao 999078China the school of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen institute of Artificial Intelligence and robotics for Society Shenzhen 518000 china Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the beijing Key Laboratory of Big Data technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the school of Computer Science and engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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A review of structures,verification,and calibration technologies of space robotic systems for on-orbit servicing

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Science china(Technological Sciences) 2021年第3期64卷 462-480页

作者： DING XiLun wang YeCong wang YaoBing XU Kun robotics institute Beihang UniversityBeijing 100191China beijing institute of Spacecraft System engineering Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and ApplicationsBeijing 100094China

Recently,with the rapid development of aerospace technology,an increasing number of spacecraft is being launched into ***,the demands for on-orbit servicing(OOS)missions are rapidly *** robotics is one of the most promising approaches for various OOS missions;thus,research on space robotics technologies for OOS has attracted increased attention from space agencies and universities *** this paper,we review the structures,ground verification,and onorbit kinematics calibration technologies of space robotic systems for ***,we systematically summarize the development of space robotic systems and OOS programs based on space ***,according to the structures and applications,these systems are divided into three categories:large space manipulators,humanoid space robots,and small space *** to the capture mechanisms adopted,the end-effectors are systematically ***,the ground verification facilities used to simulate a microgravity environment are summarized and ***,the on-orbit kinematics calibration technologies are discussed and analyzed compared with the kinematics calibration technologies of industrial manipulators with regard to four ***,the development trends of the structures,verification,and calibration technologies are discussed to extend this review work.

关键词： space robotic system on-orbit servicing large space manipulator humanoid space robot verification kinematics calibration

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General Kinetostatic Modeling and Deformation Analysis of a Two-Module Rod-Driven Continuum Robot with Friction Considered

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Chinese Journal of Mechanical engineering 2023年第3期36卷 110-122页

作者： Peiyi wang Xinhua Yang Xiangyang wang Sheng Guo school of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Guangdong Provincial Key Lab of robotics and intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518005China

Continuum robots actuated by flexible rods have large potential applications,such as detection and operation tasks in confined environments,since the push and pull actuation of flexible rods withstand tension and compressive force,and increase the structure's *** this paper,a generalized kinetostatics model for multi-module and multi-segment continuum robots considering the effect of friction based on the Cosserat rod theory is ***,the model is applied to a two-module rod-driven continuum robot with winding ropes to analyze its deformation and load *** different in-plane configurations under the external load term as S1,S2,C1,and C2 are *** a bending plane as an example,the tip deformation along thex-axis of these shapes is simulated and compared,which shows that the load capacity of C1 and C2 is generally larger than that of S1 and ***,the deformation experiments and simulations show that the maximum error ratio without external loads relative to the total length is no more than 3%,and it is no more than 4.7%under the external *** established kinetostatics model is proven sufficient to accurately analyze the rod-driven continuum robot with the consideration of internal friction.

关键词： Rod-driven continuum robot Kinetostatic model Cosserat rod theory Deformation and stiffness analysis

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Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

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Petroleum Science 2023年第2期20卷 1142-1154页

作者： yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China institutes for robotics and intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of technology ShenyangLiaoning 110870China school of Automation and Electrical engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

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A New Recursive Composite Adaptive Controller for Robot Manipulators

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Space(Science & technology) 2021年第1期2021卷 77-83页

作者： Jianfei li Yaobing wang Zhiyong liu Xin Jing Chengwei Hu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China beijing Key Laboratory of intelligent Space Robotic System technology and Applications Beijing Institute of Spacecraft System EngineeringBeijing 100094China State Key Laboratory of robotics and System Harbin Institute of TechnologyHarbin 150001China

In this paper,a new recursive implementation of composite adaptive control for robot manipulators is *** investigate the recursive composite adaptive algorithm and prove the stability directly based on the Newton-Euler equations in matrix form,which,to our knowledge,is the first result on this point in the *** proposed algorithm has an amount of computation O(n),which is less than any existing similar algorithms and can satisfy the computation need of the complicated multidegree *** manipulator of the Chinese Space Station is employed as a simulation example,and the results verify the effectiveness of this proposed recursive algorithm.

关键词： Robot manipulators robot

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Attention shifting during child-robot interaction:a preliminary clinical study for children with autism spectrum disorder

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信息与电子工程前沿：英文版 2019年第3期20卷 374-387页

作者： Guo-bin WAN Fu-hao DENG Zi-jian JIANG Sheng-zhao liN Cheng-lian ZHAO Bo-xun liU Gong CHEN Shen-hong CHEN Xiao-hong CAI Hao-bo wang li-ping li Ting YAN Jia-ming ZHANG Shenzhen Maternal&Child Healthcare Hospital institute of robotics and intelligent Manufacturing The Chinese University of Hong Kong(Shenzhen) school of Mechanical engineering Zhejiang University institute of Information engineering&technology Huaqiao University school of Information and Control engineering China University of Mining and Technology school of Mechanical and Electrical engineering Beijing Information Science and Technology University Shenzhen institutes of Advanced technology Chinese Academy of Sciences

There is an increasing need to introduce socially interactive robots as a means of assistance in autism spectrum disorder(ASD) treatment and rehabilitation, to improve the effectiveness of rehabilitation training and the diversification of treatment, and to alleviate the shortage of medical personnel in china's Mainland and other places in the world. In this preliminary clinical study, three different socially interactive robots with different appearances and functionalities were tested in therapy-like settings in four different rehabilitation facilities/institutions in Shenzhen, china. Seventy-four participants, including 52 children with ASD, whose processes of interacting with robots were recorded by three different cameras, all received a single-session three-robot intervention. Data were collected from not only the videos recorded, but also the questionnaires filled mostly by parents of the participants. Some insights from the preliminary results were obtained. These can contribute to the research on physical robo it design and evaluations on robots in therapy-like settings. First, when doing physical robot design, some preferential focus should be on aspects of appearances and functionalities. Second, attention analysis using algorithms such as estimation of the directions of gaze and head posture of a child in the video clips can be adopted to quantitatively measure the prosocial behaviors and actions(e.g., attention shifting from one particular robot to other robots) of the children. Third, observing and calculating the frequency of the time children spend on exploring/playing with the robots in the video clips can be adopted to qualitatively analyze such behaviors and actions. limitations of the present study are also presented.

关键词： Human-robot interaction Robot-enhanced therapy Socially interactive robots Robot-mediated intervention

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3D fully-enclosed triboelectric nanogenerator with bionic fish-like structure for harvesting hydrokinetic energy

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Nano Research 2022年第6期15卷 5098-5104页

作者： Zhaoxu Jing Jiacheng Zhang Jianlong wang Mingkang Zhu Xinxian wang Tinghai Cheng Jianyang Zhu Zhong lin wang beijing institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400China school of Mechatronic engineering Changchun University of TechnologyChangchunJilin 130012China institute of robotics and intelligent Systems Wuhan University of Science and TechnologyWuhanHubei 430081China CUSTech institute of technology WenzhouZhejiang 325024China school of Materials Science and engineering Georgia Institute of TechnologyAtlantaGA 30332-0245USA

The hydrokinetic energy of river current,as one of the essential and widespread renewable energies,is difficult to be harvested in low flow velocity and shallow water *** this work,a three-dimensional(3D)fully-enclosed triboelectric nanogenerator(FETENG)with bionic fish-like structure for harvesting hydrokinetic energy is reported,which is comprised of the triboelectric powergeneration unit,bionic fish-like structure and connection *** the bionic structure,the FE-TENG realizes zero head power generation in shallow water with low flow ***’s more,the effect of external excitations and bionic structures on the electrical performance are systematically studied in this *** FE-TENG can generate peak power density of 7 and 0.36 W/m^(3)respectively under the simulated swing state with frequency of 1.25 Hz and simulated river current with flow velocity of 0.81 m/*** practical applications,due to the 3D fully-enclosed design,the FE-TENG immersed in water for 35 days demonstrates excellent immersion durability with undiminished electrical ***,the work proposes an efficient method realizing zero head power generation,and provides a good candidate for long-term service in the river current.

关键词： hydrokinetic energy three-dimensional(3D)fully-enclosed design triboelectric nanogenerator bionic fish-like structure zero head power generation water immersion durability

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基于多尺度特征融合的功耗建模分析方法

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四川大学学报（自然科学版） 2024年第3期61卷 182-194页

作者：李想杨宁刘伟锋陈艾东张彦龙王硕周婧北京联合大学北京市信息服务工程重点实验室北京100101 中国科学院半导体研究所北京100085 北京联合大学机器人学院北京100101 北京联合大学多智能体系统研究中心北京100101 北京微电子技术研究所北京100076

在数字化浪潮推动下,5G和6G技术的快速发展正引领移动通信系统步入新阶段.先进的硬件设备和加密芯片为不断增长的数据处理需求和日益关注的安全保障提供了强有力的支持.在这一背景下,搭载现代密码技术的各类硬件设备逐渐演变为不可或缺... 详细信息

在数字化浪潮推动下,5G和6G技术的快速发展正引领移动通信系统步入新阶段.先进的硬件设备和加密芯片为不断增长的数据处理需求和日益关注的安全保障提供了强有力的支持.在这一背景下,搭载现代密码技术的各类硬件设备逐渐演变为不可或缺的生活基石.这些设备已经具备抵御传统密码分析的能力.近年来,学术界的研究重点之一是对设备在实际运行过程中产生的物理泄漏进行分析.这一领域被称为侧信道分析(Side-Channel Analysis,SCA).深度学习驱动的侧信道分析已被广泛认可为一种有效的方法,针对当前神经网络模型的功耗曲线数量需求大、鲁棒性差和收敛速度慢等问题,本文提出一种基于CNNbest的多尺度特征融合侧信道分析方法.首先,重构特征提取网络结构,以解决深层特征向量容易过度解释噪声细节的问题和模型过拟合问题.而后,使用滤波器阵列执行离散小波变换(Dis‐crete Wavelet Transform,DWT)分析方法构造多解析度时频,提升数据质量.最后,引入轻量级的结合通道空间的卷积块注意力模块(Convolutional Block Attention Module,CBAM),以提高功耗曲线关键特征的学习效率.实验结果表明,本文方法对侧信道分析所需的功耗曲线较原模型减少了88.27%,显著提高了分析性能,能够满足侧信道建模和分析的要求.

关键词：侧信道分析功耗分析多尺度特征融合离散小波变换注意力机制

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