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Artificial Intelligence Meets Flexible Sensors:Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

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Nano-Micro Letters 2024年第1期16卷 235-273页

作者： Tianming Sun Bin Feng Jinpeng Huo yu Xiao Wengan Wang Jin Peng Zehua Li Chengjie Du wenxian Wang Guisheng Zou Lei Liu Department of Mechanical Engineering State Key Laboratory of Tribology in Advanced EquipmentKey Laboratory for Advanced Manufacturing by Materials Processing TechnologyMinistry of Education of PR ChinaTsinghua UniversityBeijing 100084People’s Republic of China College of Materials Science and Engineering Shanxi ProvinceTaiyuan University of TechnologyTaiyuan 030024People’s Republic of China

The recent wave of the artificial intelligence(AI)revolution has aroused unprecedented interest in the intelligentialize of human society.As an essential component that bridges the physical world and digital signals,flexible sensors are evolving from a single sensing element to a smarter system,which is capable of highly efficient acquisition,analysis,and even perception of vast,multifaceted data.While challenging from a manual perspective,the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm(machine learning)and the framework(artificial synapses)level.This review presents the recent progress of the emerging AI-driven,intelligent flexible sensing systems.The basic concept of machine learning and artificial synapses are introduced.The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed,which significantly advances the applications such as flexible sensory systems,soft/humanoid robotics,and human activity monitoring.As two of the most profound innovations in the twenty-first century,the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

关键词： Flexible electronics Wearable electronics Neuromorphic Memristor Deep learning

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M2C-GVIO:motion manifold constraint aided GNSS-visual-inertial odometry for ground vehicles

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Satellite Navigation 2023年第1期4卷 77-91,I0003页

作者： Tong Hua Ling Pei Tao Li Jie Yin Guoqing Liu wenxian yu Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong UniversityShanghaiChina

Visual-Inertial Odometry(VIO)has been developed from Simultaneous Localization and Mapping(SLAM)as a lowcost and versatile sensor fusion approach and attracted increasing attention in ground vehicle positioning.However,VIOs usually have the degraded performance in challenging environments and degenerated motion scenarios.In this paper,we propose a ground vehicle-based VIO algorithm based on the Multi-State Constraint Kalman Filter(MSCKF)framework.Based on a unifed motion manifold assumption,we derive the measurement model of manifold constraints,including velocity,rotation,and translation constraints.Then we present a robust flter-based algorithm dedicated to ground vehicles,whose key is the real-time manifold noise estimation and adaptive measurement update.Besides,GNSS position measurements are loosely coupled into our approach,where the transformation between GNSS and VIO frame is optimized online.Finally,we theoretically analyze the system observability matrix and observability measures.Our algorithm is tested on both the simulation test and public datasets including Brno Urban dataset and Kaist Urban dataset.We compare the performance of our algorithm with classical VIO algorithms(MSCKF,VINS-Mono,R-VIO,ORB_SLAM3)and GVIO algorithms(GNSS-MSCKF,VINS-Fusion).The results demonstrate that our algorithm is more robust than other compared algorithms,showing a competitive position accuracy and computational efciency.

关键词： Sensor fusion Visual-inertial odometry Motion manifold constraint

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Circulate shifted OFDM chirp waveform diversity design with digital beamforming for MIMO SAR

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Science China(Information Sciences) 2017年第10期60卷 217-228页

作者： Shangwen LIU Zenghui ZHANG wenxian yu Shanghai Key Laboratory of Intelligent Sensing and Recognition Shanghai Jiao Tong University

Waveform diversity design has always been the key to multiple-input multiple-output(MIMO)synthetic aperture radar(SAR) systems, and it is known that synthetic integral side lobe ratio(SISLR) is a more optimal indicator than the integral side lobe ratio(ISLR) to evaluate the orthogonality between different MIMO SAR waveforms. This paper presents proof that it is difficult to obtain the SISLR of an existing waveform such that it is sufficiently low to achieve high SNR for SAR imaging. Thus, it is necessary to find a way to separate these MIMO SAR waveforms in other domains, for example, a spatial domain by digital beamforming(DBF). Learning from Krieger’s idea of short-term shift-orthogonal waveforms and using joint time-frequency transforms(Gabor transform) to prove that for most existing SAR waveforms cyclic shift is a good operation with which to generate short-term shift-orthogonal waveforms. This paper presents the designs of four circulate shifted OFDM chirp waveforms, which have a much lower SISLR and retain all the advantages of the classical chirp waveform such as a large time-bandwidth product, constant amplitude, implementation simplicity, and good Doppler tolerance.

关键词： MIMO SAR Gabor transform cyclic shift OFDM chirp waveform synthetic integral side lobe ratio(SISLR)

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阵元位置互质的线性阵列:阵列校正和波束形成

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电子与信息学报 2024年第1期46卷 240-248页

作者：梁梦薇何劲舒汀郁文贤上海交通大学电子信息与电气工程学院上海200240

该文研究了阵元位置互质的线性阵列(CLA)的阵列校正和波束形成问题。在假设CLA天线单元部分校准的条件下,基于同时干扰定位与阵列校正(SILAC)技术,设计了一种适用于CLA的阵列校正和波束形成方法:CLA-SILAC-INCM算法。从理论上分析证明了... 详细信息

该文研究了阵元位置互质的线性阵列(CLA)的阵列校正和波束形成问题。在假设CLA天线单元部分校准的条件下,基于同时干扰定位与阵列校正(SILAC)技术,设计了一种适用于CLA的阵列校正和波束形成方法:CLA-SILAC-INCM算法。从理论上分析证明了,当CLA中包含有L_c≥3个完全校准的天线单元,使用SILAC技术可以高精度无模糊地实现干扰源角度和阵列天线幅相误差估计,并在此基础上完成干扰噪声协方差矩阵(INCM)重建和波束形成最优权向量构造。通过仿真实验验证了,提出的CLA-SILAC-INCM算法具有比其他常用算法更好的性能,尤其是信噪比接近干噪比时,CLA-SILAC-INCM算法的优势更为明显。

关键词：稀疏阵列自适应波束形成阵列校正

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A coupled convolutional neural network for small and densely clustered ship detection in SAR images

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Science China(Information Sciences) 2019年第4期62卷 111-126页

作者： Juanping ZHAO Weiwei GUO Zenghui ZHANG wenxian yu Shanghai Key Laboratory of Intelligent Sensing and Recognition School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University

Ship detection from synthetic aperture radar(SAR) imagery plays a significant role in global marine surveillance. However, a desirable performance is rarely achieved when detecting small and densely clustered ship targets, and this problem is difficult to solve. Recently, convolutional neural networks(CNNs)have shown strong detection power in computer vision and are flexible in complex background conditions,whereas traditional methods have limited ability. However, CNNs struggle to detect small targets and densely clustered ones that exist widely in many SAR images. To address this problem while preserving the good properties for complex background conditions, we develop a coupled CNN for small and densely clustered SAR ship detection. The proposed method mainly consists of two subnetworks: an exhaustive ship proposal network(ESPN) for ship-like region generation from multiple layers with multiple receptive fields, and an accurate ship discrimination network(ASDN) for false alarm elimination by referring to the context information of each proposal generated by ESPN. The motivation in ESPN is to generate as many ship proposals as possible, and in ASDN, the goal is to obtain the final results accurately. Experiments are evaluated on two data sets. One is collected from 60 wide-swath Sentinel-1 images and the other is from20 GaoF en-3(GF-3) images. Both data sets contain many ships that are small and densely clustered. The quantitative comparison results illustrate the clear improvements of the new method in terms of average precision(AP) and F 1 score by 0.4028 and 0.3045 for the Sentinel-1 data set compared with the multi-step constant false alarm rate(CFAR-MS) method. The values are verified as 0.2033 and 0.1522 for the GF-3 data set. In addition, the new method is demonstrated to be more efficient than CFAR-MS.

关键词： SAR image ship detection CNN exhaustive ship proposal network(ESPN) accurate ship discrimination network(ASDN)

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Collaborative visual SLAM for multiple agents:A brief survey

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Virtual Reality & Intelligent Hardware 2019年第5期1卷 461-482页

作者： Danping ZOU Ping TAN wenxian yu Shanghai Key Laboratory of Navigation and Location-Based Services Shanghai Key Laboratory of Intelligent Sensing and RecognitionShanghai Jiao Tong UniversityShanghai 200240China School of Computing Science Simon Fraser UniversityBurnaby V5A 1S6Canada

This article presents a brief survey to visual simultaneous localization and mapping (SLAM) systems applied to multiple independently moving agents, such as a team of ground or aerial vehicles, a group of users holding augmented or virtual reality devices. Such visual SLAM system, name as collaborative visual SLAM, is different from a typical visual SLAM deployed on a single agent in that information is exchanged or shared among different agents to achieve better robustness, efficiency, and accuracy. We review the representative works on this topic proposed in the past ten years and describe the key components involved in designing such a system including collaborative pose estimation and mapping tasks, as well as the emerging topic of decentralized architecture. We believe this brief survey could be helpful to someone who are working on this topic or developing multi-agent applications, particularly micro-aerial vehicle swarm or collaborative augmented/virtual reality.

关键词： Visual SLAM Multiple agent UAV swarm Collaborative AR/VR

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α-地中海贫血基因检测临床遗传咨询专家共识

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中华医学遗传学杂志 2024年第6期41卷 669-676页

作者：席惠刘沁刘静余雯贤吴学东常清贤湖南省妇幼保健院/国家卫健委出生缺陷研究与预防重点实验室湖南省妇幼保健院南方医科大学南方医院广州510515

α-地中海贫血是由α珠蛋白基因变异所导致的小细胞低色素性贫血,是我国南方地区最常见的单基因遗传病之一。基于血液学表型的群体携带者筛查模式在α地贫高发地区已取得了较大的成效。随着基因检测费用的不断下降,以及地贫基因携带者... 详细信息

α-地中海贫血是由α珠蛋白基因变异所导致的小细胞低色素性贫血,是我国南方地区最常见的单基因遗传病之一。基于血液学表型的群体携带者筛查模式在α地贫高发地区已取得了较大的成效。随着基因检测费用的不断下降,以及地贫基因携带者筛查的广泛开展,越来越多的α地贫基因变异类型被发现,为临床遗传咨询带来了较大的挑战。本文从α地贫基因检测临床遗传咨询的角度,对α-地贫基因检测前后咨询需要重点关注的内容进行了探讨,并达成了本专家共识,旨在为临床医师提供规范化的遗传咨询指导意见。

关键词： α-地中海贫血基因检测遗传咨询

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Discovery of orthorhombic perovskite oxides with low thermal conductivity by first-principles calculations

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Journal of Advanced Ceramics 2022年第10期11卷 1596-1603页

作者： yuchen LIU Kaili CHU yu ZHOU Yiran LI wenxian LI Bin LIU Institute for Advanced Ceramics School of Materials Science and EngineeringHarbin Institute of TechnologyHarbin 150080China School of Materials Science and Engineering Shanghai UniversityShanghai 200444China School of Materials Science and Engineering University of New South WalesSydney 2052Australia

Orthorhombic perovskite oxides are studied by high-throughput first-principles calculations to explore new thermal barrier coating(TBC)materials with low thermal conductivities.The mechanical and thermal properties are predicted for 160 orthorhombic perovskite oxides.The average atomic volume is identified as a possible predictor of the thermal conductivity for the perovskite oxides,as it has a good correlation with the thermal conductivity.Five compounds,i.e.,LaTmO_(3),LaErO_(3),LaHoO_(3),SrCeO_(3),and SrPrO_(3),having thermal conductivities under 1 W·m^(-1)·K^(-1) and good damage tolerance,are proposed as novel TBC materials.The obtained data are expected to inspire the design of perovskite oxide-based TBC materials and also support their future functionality investigations.

关键词： first-principles calculations perovskite oxide thermal conductivity mechanical property

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Rotor综合征患儿4例的临床特征及遗传学分析

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中华医学遗传学杂志 2024年第6期41卷 715-719页

作者：谭艳芳欧阳文献姜涛唐莲张慧于莹覃小梅李双杰湖南省儿童医院肝病科长沙410007

目的:探讨4例Rotor综合征患儿SLCO1B1/SLCO1B3基因的变异特点,为临床诊疗和遗传咨询提供依据。方法:以2019年1月至2022年1月湖南省儿童医院肝病科收治的4例患儿作为研究对象,对其进行家系全外显子组测序分析,并用凝胶电泳法对长散布元件... 详细信息

目的:探讨4例Rotor综合征患儿SLCO1B1/SLCO1B3基因的变异特点,为临床诊疗和遗传咨询提供依据。方法:以2019年1月至2022年1月湖南省儿童医院肝病科收治的4例患儿作为研究对象,对其进行家系全外显子组测序分析,并用凝胶电泳法对长散布元件-1(LINE-1)插入变异进行验证。结果:4例患儿均表现为皮肤及巩膜黄染。基因检测提示其SLCO1B1基因存在3处变异,分别为c.1738C>T(p.R580*)、c.757C>T(p.R253*)以及c.1622A>C(p.Q541P);SLCO1B3基因存在2处变异,分别为c.481+22insLINE-1及c.1747+1G>A。3例患儿携带SLCO1B1/SLCO1B3基因纯合变异,1例携带复合杂合变异。Sanger测序证实了上述变异的存在,凝胶电泳实验证实4例患儿均携带SLCO1B3基因第6内含子约6 kb的LINE-1插入变异。结论:4例Rotor综合征患儿均由SLCO1B1/SLCO1B3基因的变异所致。SLCO1B3基因LINE-1插入变异可能是中国Rotor患者中常见的变异类型。

关键词： Rotor综合征 SLCO1B1基因 OATP家族长散布元件-1

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Trap Spoofing Algorithm for Target Using GNSS/INS-Integrated Navigation System Based on Prior Error Compensation

Trap Spoofing Algorithm for Target Using GNSS/INS-Integrated...

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第十三届中国卫星导航年会

作者： Jianyu Pan Lei Chen Xin Chen wenxian yu Shanghai Key Laboratory of Navigation and Location Based Services School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Beijing institute of tracking and telecommunication technology

Black flights of unauthorized unmanned aerial vehicle（UAV） have occurred frequently in recent years, threatening public safety. UAV mainly uses GNSS（Global Navigation Satellite System）/INS（Inertial Navigation System） integrated navigation for positioning. Due to the weakness of GNSS signal, spoofing UAV is possible. Some scholars have conducted researches on the spoofing of targets with integrated navigation, but these studies all use radar to obtain the target’s position, speed and acceleration in real time. This method has high technical complexity and expensive cost. To solve this problem, this research proposes a trap spoofing algorithm for target using GNSS/INS-integrated navigation system based on prior error compensation. By setting a spoofing trap in a certain area of the target path, when the target moves within the trap range, it will be trapped in designated areas by spoofing signals. Finally, this paper verifies the feasibility of the trap spoofing algorithm through simulation experiments.

关键词： GNSS spoofing GNSS/INS integrated navigation Trap spoofing

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