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Wearable ultrasensitive and rapid human physiological monitoring based on microfiber Sagnac interferometer

Science China(information Sciences) 2024年第3期67卷 281-290页

作者： Xin WANG Hongyou ZHOU Meihua CHEN Yongcheng HE Zhishen ZHANG Jiulin GAN Zhongmin YANG State key laboratory Luminescent Materials and Devices Institute of Optical Communication MaterialsSpecial Glass Fiber and Device Engineering Technology Research and Development Center of Guangdong ProvinceGuangdong Provincial Key Laboratory of Fiber Laser Materials and Applied TechniquesSouth China University of Technology Guangdong-Hong Kong-Macao Joint laboratory for intelligent Micro-Nano Optoelectronic technology Foshan University

High-sensitive and fast-responding flexible strain sensors are essential for the smart wearable devices that precisely and dynamically perceive the weak deformations induced by human physiological signals. Here, a flexible strain sensor via polydimethylsiloxane(PDMS)-encapsulated microfiber Sagnac interferometer was designed and prepared for monitoring the human pulse signals and sound vibrations. The sensor achieved a record-breaking sensitivity(gauge factor, GF = 9977) and an extremely low detection limit(0.00025%) due to the strong polarization-dependent coupling effect in the microfiber coupler and the polarization-mixing effect in the Sagnac loop. The relative intensity demodulation method also enabled a fast response time of 10 μs. The wearable pulse measurements were implemented by attaching this flexible strain sensor directly to human skin at various locations and the waveform details were accurately captured. Taking advantage of the ultra-high sensitivity and fast response performance of the prepared sensor, the real-time dynamic acquisition of the underwater weak signal, such as the hydro-acoustic waves with a wide range of 20 Hz–16.86 k Hz, has been demonstrated. These initial results pave the way for a new and innovative category of underwater wearable devices with rapid detection of human physiological signals and weak environmental vibrations.

关键词： flexible strain sensor microfiber Sagnac interferometer underwater detection

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Multi-Time-Scale Variational Mode Decomposition-Based Robust Fault Diagnosis of Railway Point Machines Under Multiple Noises

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Chinese Journal of Electronics 2024年第3期33卷 814-822页

作者： Junqi LIU Tao WEN Guo XIE Yuan CAO Clive Roberts Shaanxi key laboratory of Complex System Control and intelligent information Processing Xi'an University of Technology The School of Electronic and information Engineering Beijing Jiaotong University Birmingham Centre for Railway Research and Education University of Birmingham

The fault diagnosis of railway point machines(RPMs) has attracted the attention of engineers and *** have studies considered diverse noises along the *** fulfill this aspect,a multi-time-scale variational mode decomposition(MTSVMD) is proposed in this paper to realize the accurate and robust fault diagnosis of RPMs under multiple *** decomposes condition monitoring signals after coarse-grained processing in varying *** this manner,the information contained in the signal components at multiple time scales can construct a more abundant feature space than at a single *** the experimental validation,a random position,random type,random number,and random length(4R) noise-adding algorithm helps to verify the robustness of the *** adequate experimental results demoristrate the superiority of the proposed MTSVMD-based fault diagnosis.

关键词： Fault diagnosis Condition monitoring Noise Signal processing algorithms Aerospace electronics Rail transportation Robustness

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BEDiff: denoising diffusion probabilistic models for building extraction

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Optoelectronics Letters 2024年

作者： LEI Yanjing WANG Yuan CHAN Sixian HU Jie ZHOU Xiaolong ZHANG Hongkai College of Computer Science and technology zhejiang University of technology Hubei key laboratory of intelligent Vision Based monitoring for Hydroelectric Engineering The College of Computer and information China Three Gorges University key laboratory of intelligent Informatics for Safety & Emergency of zhejiang Province Wenzhou University The College of Electrical and information Engineering Quzhou University The School of Electronic and information Engineering Anhui Jianzhu University

Accurately identifying building distribution from remote sensing images with complex background information is challenging. The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds. Building on this concept， we propose a novel framework， BEDiff， which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion. Our approach begins with the design of Booster Guidance， a mechanism that extracts structural and semantic features from remote sensing images to serve as priors， thereby providing targeted guidance for the diffusion process. Additionally， we introduce a Cross-Feature Fusion Module (CFM) that bridges the semantic gap between different types of features， facilitating the integration of the attributes extracted by Booster Guidance into the diffusion process more effectively. Our proposed BEDiff marks the first application of diffusion models to the task of building extraction. Empirical evidence from extensive experiments on the Beijing Building Dataset demonstrates the superior performance of BEDiff， affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.

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A Self-sensing TSA-actuated Anthropomorphic Robot Hand

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Journal of Bionic Engineering 2024年第3期21卷 1174-1190页

作者： Chanchan Xu Shuai Dong Yifan Ma Jingwei Zhan Yucheng Wang Xiaojie Wang Institute of intelligent Machines Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei230031China CAS key laboratory of Mechanical Behavior and Design of Materials Department of Precision Machinery and Precision InstrumentationUniversity of Science and Technology of ChinaHefei230026China Institutes of Physical Science and information technology Anhui UniversityHefei230601China

This paper introduces a self-sensing anthropomorphic robot hand driven by Twisted String Actuators(TSAs).The use of TSAs provides several advantages such as muscle-like structures,high transmission ratios,large output forces,high efficiency,compactness,inherent compliance,and the ability to transmit power over ***,conventional sensors used in TSA-actuated robotic hands increase stiffness,mass,volume,and complexity,making feedback control *** address this issue,a novel self-sensing approach is proposed using strain-sensing string based on Conductive Polymer Composite(CPC).By measuring the resistance changes in the strain-sensing string,the bending angle of the robot hand's fingers can be estimated,enabling closed-loop control without external *** developed self-sensing anthropomorphic robot hand comprises a 3D-printed structure with five fingers,a palm,five self-sensing TSAs,and a 3D-printed *** studies validate the self-sensing properties of the TSA and the anthropomorphic robot ***,a real-time Virtual Reality(VR)monitoring system is implemented for visualizing and monitoring the robot hand's movements using its self-sensing *** research contributes valuable insights and advancements to the field of intelligent prosthetics and robotic end grippers.

关键词： Anthropomorphic robot hand Twisted string actuator Self-sensing Conductive polymer composite Virtual reality monitoring

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Flexible capacitive pressure sensor based on interdigital electrodes with porous microneedle arrays for physiological signal monitoring

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Nanotechnology and Precision Engineering 2024年第1期7卷 18-31页

作者： Jiahui Xu Minghao Wang Minyi Jin Siyan Shang Chuner Ni Yili Hu Xun Sun Jun Xu Bowen Ji Le Li Yuhua Cheng Gaofeng Wang School of Electronics&information MOE Engineering Research Center of Smart Microsensors and MicrosystemsHangzhou Dianzi UniversityHangzhou 310018China Wenzhou Institute of Hangzhou Dianzi University Wenzhou 310018China key laboratory of intelligent Operation and Maintenance technology&Equipment for Urban Rail Transit of zhejiang Province College of EngineeringInstitute of Precision Machinery and Smart StructureZhejiang Normal UniversityJinhua 321004China Institute of Guizhou Aerospace Measuring and Testing technology Guiyang 550009China Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518057China

Flexible pressure sensors have many potential applications in the monitoring of physiological signals because of their good biocompatibil-ity and ***,their relatively low sensitivity,linearity,and stability have hindered their large-scale commercial ***,aﬂexible capacitive pressure sensor based on an interdigital electrode structure with two porous microneedle arrays(MNAs)is *** porous substrate that constitutes the MNA is a mixed product of polydimethylsiloxane and *** to its porous and interdigital structure,the maximum sensitivity(0.07 kPa-1)of a porous MNA-based pressure sensor was found to be seven times higher than that of an imporous MNA pressure sensor,and it was much greater than that of aﬂat pressure sensor without a porous MNA ***-element analysis showed that the interdigital MNA structure can greatly increase the strain and improve the sensitivity of the *** addition,the porous MNA-based pressure sensor was found to have good stability over 1500 loading cycles as a result of its bilayer parylene-enhanced conductive electrode *** importantly,it was found that the sensor could accurately monitor the motion of aﬁnger,wrist joint,arm,face,abdomen,eye,and Adam’s ***,preliminary semantic recognition was achieved by monitoring the movement of the Adam’s ***,multiple pressure sensors were integrated into a 33 array to detect a spatial pressure distribu-×*** to the sensors reported in previous works,the interdigital electrode structure presented in this work improves sensitivity and stability by modifying the electrode layer rather than the dielectric layer.

关键词： Capacitive pressure sensor Microneedle array Porous PDMS Interdigital electrode

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Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

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Journal of Mountain Science 2024年第3期21卷 952-972页

作者： GUO Junqi XI Wenfei YANG Zhiquan SHI Zhengtao HUANG Guangcai YANG Zhengrong YANG Dongqing Faculty of Geography Yunnan Normal UniversityKunming 650500China key laboratory of Early Rapid Identification Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan ProvinceKunming 650093China Faculty of Public Safety and Emergency Management Kunming University of Science and TechnologyKunming 650093China key laboratory of Geological Disaster Risk Prevention and Control and Emergency Disaster Reduction of Ministry of Emergency Management of the People’s Republic of China Kunming University of Science and TechnologyKunming 650093China Guizhou Geological Survey Institute Guiyang 550081China College of Big Data and intelligent Engineering Southwest Forestry UniversityKunming 650224China

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and *** order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network *** SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and *** Reservoir area is selected as a case study for *** indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard ***,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,***,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation *** area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation ra

关键词： Baihetan SBAS-InSAR SSA-BP Landslide hazard susceptibility evaluation

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2SWUNet: small window SWinUNet based on tansformer for building extraction from high-resolution remote sensing images

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Optoelectronics Letters 2024年

作者： YU Jiamin CHAN Sixian LEI Yanjing WU Wei WANG Yuan ZHOU Xiaolong College of Computer Science and technology zhejiang University of technology key laboratory of Meteorological Disaster(KLME) Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of information Science& technology The College of Geographic information Modern Industry zhejiang University of technology College of Electrical and information Engineering Quzhou University

Models dedicated to building long-range dependencies often exhibit degraded performance when transferred to remote sensing images. Vision Transformers (ViTs) is a new paradigm in computer vision that uses multi-head self-attention rather than convolution as the main computational module， with global modeling capabilities. How-ever， its performance on small datasets is usually far inferior to that of convolutional neural networks (CNNs). In this work， we propose a Small Window SWinUNet (2SWUNet) for building extraction from high-resolution remote sensing images. Firstly， 2SWUNet is trained based on Swin Transformer by designing a fully symmetric encoder-decoder U-shaped architecture. Secondly， to construct a reasonable U-shaped architecture for building extraction from high-resolution remote sensing images， the different forms of patch expansion are explored to simulate up-sampling operations and recover feature map resolution. Then， the small window-based multi-head self-attention (W-MSA) is designed to reduce the computational and memory burden， which is more appropriate for the features of remote sensing images. Meanwhile， the pre-training mechanism is advanced to make up for the lack of decoder parameters. Finally， comparison experiments with other mainstream CNNs and ViTs validate the superiority of the proposed model.

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Method for the multi-view estimation of fish mass using a two-stage neural network with edge-sensitive module

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International Journal of Agricultural and Biological Engineering 2024年第3期17卷 222-229页

作者： Zeyu Jiao Yingjie Cai Qi Zhang Zhenyu Zhong Guangdong key laboratory of Modern Control technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China Department of Electronic Engineering The Chinese University of Hong KongHong Kong 999077China College of Economics and Management Northwest A&F UniversityYangling 712100ShaanxiChina

The estimation of fish mass is one of the most basic and important tasks in *** the mass of fish at different growth stages is of great significance for feeding,monitoring the health status of fish,and making breeding plans to increase *** existing estimation methods for fish mass often stay in the 2D plane,and it is difficult to obtain the 3D information on fish,which will lead to the *** solve this problem,a multi-view method was proposed to obtain the 3D information of fish and predict the mass of fish through a two-stage neural network with an edge-sensitive *** the first stage,the side-and downward-view images of the fish and some 3D information,such as side area,top area,length,deflection angle,and pitch angle,were captured to estimate the size of the fish through two vertically placed *** the area of the fish at different views was estimated accurately through the pre-trained image segmentation neural network with an edgesensitive *** the second stage,a fully connected neural network was constructed to regress the fish mass based on the 3D information obtained in the previous *** experimental results indicate that the proposed method can accurately estimate the fish mass and outperform the existing estimation methods.

关键词： fish mass multi-view estimation two-stage neural network edge-sensitive module image segmentation

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用于紫外线成像和无线报警的水凝胶基可伸缩、高稳定性和高性能的光电传感器

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Science China Materials 2024年第6期67卷 1926-1937页

作者：洪杰钊姚帝杰王浩丁琼玲罗艺冰于家豪张鹤曾令兴杨柏儒王冰陶凯吴进 State key laboratory of Optoelectronic Materials and Technologies and Guangdong Province key laboratory of Display Material and technology School of Electronics and Information TechnologySun Yat-sen UniversityGuangzhou 510275China Ministry of Education key laboratory of Micro and Nano Systems for Aerospace Northwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Northwestern Polytechnical UniversityShenzhen 518063China State key laboratory of Transducer technology Shanghai 200050China Guangdong provincial key laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing National Engineering Research Center of Novel Equipment for Polymer ProcessingKey Laboratory of Polymer Processing Engineering(SCUT)Ministry of EducationSouth China University of TechnologyGuangzhou 510641China Engineering Research Center of Polymer Green Recycling of Ministry of Education College of Environment and ResourcesFujian Normal UniversityFuzhou 350007China State key laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065China

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化... 详细信息

柔性可穿戴的紫外线探测器在个体紫外线暴露监测、智能仿生眼和军事领域受到广泛关注.然而,传统不可拉伸的材料和器件结构设计限制了设备在可动态变形的人体皮肤和非平面表面上的精确监测应用和稳定附着.在本研究中,我们提出了基于氧化铜/碳-水凝胶-氧化锌/碳的新型应变隔离异质结构的本征可拉伸(拉伸应变或弯曲高达150%)紫外线探测器,该探测器具有高灵敏度(开/关比为2100%)、高稳定性(大于4000次循环),以及快速响应和恢复时间(分别为1.5和4 s).值得注意的是,该探测器通过水凝胶桥在氧化铜/碳和氧化锌/碳电极之间引入的p-n结能带结构,以及离子导电水凝胶中I^(-)/I_(3)^(-)的电化学反应机制,显著提高了其载流子效率和紫外线响应强度.本文通过集成传感器与所设计的电路板,进一步开发了一种无线紫外线报警系统,用于紫外线强度超标警报.此外,本文还设计了一种光电传感器阵列,并将其用作视网膜假体,以实现对环境紫外线强度的实时监测和成像.本文基于水凝胶基异质结构为开发可穿戴、可拉伸的光电紫外线传感器单元和成像阵列提供了一种新的可行方法.

关键词： flexible hydrogel sensors stretchable UV sensors UV imaging array optoelectronic sensors wireless alarm

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In situ plasmonic & electrochemical fiber-optic sensor for multi-metal-ions detection

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Science China(information Sciences) 2024年第1期67卷 292-302页

作者： Xiaoling PENG Zhiyong YANG Bo PENG Zhi LI Zhicong REN Xicheng WANG Jiahai LI Zhencheng LI Liang CHEN Daotong YOU Kaiwei LI Jianqing LI Tuan GUO Institute of Photonics technology Jinan University School of Computer Science and Engineering Macau University of Science and Technology Institute for Environmental and Climate Research Jinan University key laboratory of Bionic Engineering of Ministry of Education Jilin University

High precision and high throughput detection of heavy metal ions is essential for water quality monitoring and ***,we propose a plasmonic & electrochemical dual-mode fiber sensing probe for label-free and real-time detection of multiple ions(Pb2+and Cu2+as examples).This sensor comprises a multimode fiber-single mode fiber reflection probe,the outer surface of which is coated with a gold nanofilm to excite the surface plasmon resonance(SPR) optically and simultaneously serves as an electrochemical working *** traditional electrochemical detection,the enrichment of ions cannot be detected in ***,by utilizing the plasmonic & electrochemical dual-mode detection method,various kinds of metal ions can be deposited onto the gold nanofilm and selectively oxidized during forward potential scanning,and the entire electrochemical process can be monitored by SPR *** experimentally demonstrate that the sensor can simultaneously detect Pb2+and Cu2+in a mixed solution in real-time,providing a linear response over the ion concentration range from 10-12to 10-7M and offering an excellent detection limit(1.69×10-14–5.49×10-13M).The proposed dual-mode fiber sensor has the benefits of remote sensing,compact footprint,and cost-effectiveness and shows excellent potential for water quality risk management in difficult-to-reach environments.

关键词： optical fiber sensor surface plasmon resonance electrochemical measurement ions detection water pollution

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