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SSRN 2023年

作者： Wang, Guangwei Cong, Chenhao Zheng, Xianbing Li, Hongjiang Wang, Xuhao Jiang, Fuhao Li, Rong Jin, Mingliang Zhang, Pengfei Li, Junru Zhang, Chuanwei Kim, SeHyun Li, Shandong Li, Xinlin College of Mechanical and Electrical Engineering Qingdao University Qingdao266071 China Yeungnam University Korea Republic of School of Chemical Engineering Konkuk University Seoul05029 Korea Republic of Shandong Zhongkang Guochuang Research Institute of Advanced Dyeing & Finishing Technology Co. Ltd China Institute for Future Shandong Key Laboratory of Industrial Control Technology Automation School of Qingdao University Qingdao266071 China University-Industry Joint Center for Ocean Observation and Broadband Communication China

Due to the rapidly growing health field, the use of electronic skin for real-time monitoring of human metrics can provide an important basis for the monitoring of human movement patterns. Wearable flexible strain sensors combined with Internet of Things technology (IoT) are the most important units in the electronic skin. However, most current resistive strain sensors have the same response to strain from all directions, and practical applications are usually limited by a single sensing function. In the present study, a method for the synthesis of Fe3O4/ carbon nanotube (CNT) nanocomposites has been proposed using ultrasound catalysis. In addition, the coupled involvement of an applied magnetic field and the internal friction of a high-viscosity ink (after blending into a highly concentrated ink) have also been used. The parallel alignment of CNT during the electrode preparation has then been optimized, which is here referred to as magnetic blading. The difference in sensitivity between parallel and perpendicular directions in the magnetically bladed electrodes became as large as 300%, and the resulting multifunctional sensor was able to detect both weak and large deformations. Thereby, the sensor showed the Gauge Factor of 25.9 and 0.56 in the strain range of 0 - 3.2 % and 5.8 – 17.4 %, respectively. A strain angle recognition was achieved by using the specific response of parallel arranged CNT to strain, which was based on the detection of the human joint motion and the recognition of acoustic signals. The real-time monitoring of the data was realized by a 4G transmission module, which provided a reference for the development of remote wireless tracking for human health monitoring. © 2023, The Authors. All rights reserved.

关键词： Carbon nanotubes

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A Miniaturised Camera-based Multi-Modal Tactile Sensor

A Miniaturised Camera-based Multi-Modal Tactile Sensor

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Kaspar Althoefer Yonggen Ling Wanlin Li Xinyuan Qian Wang Wei Lee Peng Qi The Centre for Advanced Robotics @ Queen Mary (ARQ) Queen Mary University of London London United Kingdom Tencent Robotics X Lab Shenzhen China Beijing Institute for General Artificial Intelligence (BIGAI) Beijing China The Department of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai China

In conjunction with huge recent progress in cam-era and computer vision technology, camera-based sensors have increasingly shown considerable promise in relation to tactile sensing. In comparison to competing technologies (be they resistive, capacitive or magnetic based), they offer super-high-resolution, while suffering from fewer wiring problems. The human tactile system is composed of various types of mechanoreceptors, each able to perceive and process distinct information such as force, pressure, texture, etc. Camera-based tactile sensors such as GelSight mainly focus on high-resolution geometric sensing on a flat surface, and their force measurement capabilities are limited by the hysteresis and non-linearity of the silicone material. In this paper, we present a miniaturised dome-shaped camera-based tactile sensor that allows accurate force and tactile sensing in a single coherent system. The key novelty of the sensor design is as follows. First, we demonstrate how to build a smooth silicone hemispheric sensing medium with uniform markers on its curved surface. Second, we enhance the illumination of the rounded silicone with diffused LEDs. Third, we construct a force-sensitive mechanical structure in a compact form factor with usage of springs to accurately perceive forces. Our multi-modal sensor is able to acquire tactile information from multi-axis forces, local force distribution, and contact geometry, all in real-time. We apply an end-to-end deep learning method to process all the information.

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Nonreciprocity in Cold Atoms Based on Electromagnetically Induced Transparency

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Physical Review Applied 2023年第1期20卷 014027-014027页

作者： Jian-Feng Li Yun-Fei Wang Pei-Sheng Huang Ke-Yu Su Yu-Qing Peng Shanchao Zhang Hui Yan Shi-Liang Zhu Key Laboratory of Atomic and Subatomic Structure and Quantum Control (Ministry of Education) South China Normal University Guangzhou 510006 China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials School of Physics and Telecommunication Engineering South China Normal University Guangzhou 510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Frontier Research Institute for Physics South China Normal University Guangzhou 510006 China Guangdong Provincial Engineering Technology Research Center for Quantum Precision Measurement South China Normal University Guangzhou 510006 China

Nonreciprocal quantum devices with low loss are indispensable in quantum information processing but challenging to be realized. Here we report an experiment to realize the nonreciprocal phase shift larger than π with low loss in a cavity-free and magnetic-free cold atomic ensemble based on electromagnetically induced transparency. Furthermore, a four-port all-optical circulator is demonstrated with an average isolation ratio of 22.25 dB and transmission of 0.94 for each channel. At its optimal working point, the circulator’s total isolation ratio reaches 63.47 dB, transmission reaches 0.86, and fidelity at about 0.99. Our work can advance further investigation of nonreciprocity with cold atoms in quantum information processing applications.

关键词： Cold atoms & matter waves Electromagnetically induced transparency Non-reciprocal transmission Quantum control Quantum information with atoms & light Atomic ensemble Devices Mach-Zehnder atom interferometry

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IR2Net: Information Restriction and Information Recovery for Accurate Binary Neural Networks

arXiv

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arXiv 2022年

作者： Xue, Ping Lu, Yang Chang, Jingfei Wei, Xing Wei, Zhen The School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China The School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China The Anhui Mine IOT and Security Monitoring Technology Key Laboratory Hefei230088 China The Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei University of Technology Hefei230009 China The Intelligent Manufacturing Institute of HeFei University of Technology Hefei230009 China

Weight and activation binarization can efficiently compress deep neural networks and accelerate model inference, but cause severe accuracy degradation. Existing optimization methods for binary neural networks (BNNs) focus on fitting full-precision networks to reduce quantization errors, and suffer from the trade-off between accuracy and computational complexity. In contrast, considering the limited learning ability and information loss caused by the limited representational capability of BNNs, we propose IR2Net to stimulate the potential of BNNs and improve the network accuracy by restricting the input information and recovering the feature information, including: 1) information restriction: for a BNN, by evaluating the learning ability on the input information, discarding some of the information it cannot focus on, and limiting the amount of input information to match its learning ability;2) information recovery: due to the information loss in forward propagation, the output feature information of the network is not enough to support accurate classification. By selecting some shallow feature maps with richer information, and fusing them with the final feature maps to recover the feature information. In addition, the computational cost is reduced by streamlining the information recovery method to strike a better trade-off between accuracy and efficiency. Experimental results demonstrate that our approach still achieves comparable accuracy even with ∼10x floating-point operations (FLOPs) reduction for ResNet-18. The models and code are available at https://***/pingxue-hfut/IR2Net. Copyright © 2022, The Authors. All rights reserved.

关键词： Recovery

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A Classification–Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

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Computer Modeling in engineering & Sciences 2020年第11期125卷 579-596页

作者： Xing Deng Haijian Shao Liang Shi Xia Wang Tongling Xie School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212003China School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212003China School of Information Science and Technology Nantong UniversityNantong226019China Department of Electrical and Computer Engineering National University of Singapore117583Singapore The People’s Hospital of RUGAO Nantong226500China

The Coronavirus Disease 2019(COVID-19)is wreaking havoc around the world,bring out that the enormous pressure on national health and medical staff *** of the most effective and critical steps in the fight against COVID-19,is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation *** this paper,five keras-related deep learning models:ResNet50,InceptionResNetV2,Xception,transfer learning and pre-trained VGGNet16 is applied to formulate an classification-detection approaches of *** benchmark methods SVM(Support Vector Machine),CNN(Conventional Neural Networks)are provided to compare with the classification-detection approaches based on the performance indicators,i.e.,precision,recall,F1 scores,confusion matrix,classification accuracy and three types of AUC(Area Under Curve).The highest classification accuracy derived by classification-detection based on 5857 Chest X-rays and 767 Chest CTs are respectively 84%and 75%,which shows that the keras-related deep learning approaches facilitate accurate and effective COVID-19-assisted detection.

关键词： COVID-19 detection deep learning transfer learning pre-trained models

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Deployment of NRF in the Docker and Kubernetes - Based NFV Platform 1

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Workshops of the 34th International Conference on Advanced Information Networking and Applications, WAINA 2020

作者： Huang, Di Xu, Zhan Tian, Zhigang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

ISBN: (数字)9783030440381

ISBN: (纸本)9783030440374

Network Function Virtualization (NFV) which is one of the core technologies plays an important role in reality. NFV permits using Virtual Network Functions (VNF) as software components on top of a virtualization system (i.e., Virtual Machines or Containers) hosted in a cloud, which makes network services and functions deployed in high flexibility and elasticity. Therefore, based on this design concept, in 5G core networks, NRF (Network Repository Function), which was implemented in a server, supports network function of registering and monitoring conditions. It achieves automatic management, selection, and scalability of network function services. In this paper, NRF is deployed in Docker and Kubernetes-based NFV platform in the form of JSON + HTTP/2.0 that supports service discovery function. The performance is tested on a hardware platform, including Network Function (NF) Register, NF Update and NF Deregister. From the testing data, we can find that the NRF in the Docker and Kubernetes-based NFV platform is better than only Docker implemented platform. © 2020, Springer Nature Switzerland AG.

关键词： Network function virtualization

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A Study of Discharge Cavity Optimization in Hollow-Cathode Electron Beam Source

SSRN

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SSRN 2023年

作者： He, Weiguo Huo, Weijie Duan, Xinxin Gu, Jun Zhu, Kangwu School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou310024 China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Taiji Laboratory for Gravitational Wave Universe Hangzhou310024 China Shanghai Aerospace Electronic Technology Institute Shanghai201109 China Shanghai SastSpace Technology Co. Ltd Shanghai201109 China Shanghai Aerospace Control Technology Institute Shanghai201109 China

Improving the high-voltage resistance of the discharge cavity is essential to enhancing the performance of the hollow-cathode electron source. In this work, a discharge cavity of the hollow-cathode electron beam source is designed and optimized by stacking and isolating the insulating sheets. The experimental results indicate that the optimized design not only improves the overall high-voltage resistance of the device but also improves the stability of the discharge. Meanwhile, it is found that when the amplitude of the discharge breakdown voltage is increased from 12 kV to 20 kV, the resistance of the discharge cavity varies within the range of 3.8–3.7 Ω, with a slight change in the amplitude, and the inductance decreases from 356 nH to 323.1 nH. The experimental study of the high-pressure gas discharge characteristics in the discharge cavity reveals that the change in gas pressure leads to a significant change in the discharge pattern, and compared with the glow discharge, the hollow-cathode discharge significantly improves the discharge current and shortens the breakdown time of the discharge. Under the same air pressure, the breakdown voltage of the discharge decreases and then increases with the increase in cathode cavity length. © 2023, The Authors. All rights reserved.

关键词： Glow discharges

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Lateral Trajectory Stabilization of an Articulated Truck during Reverse Driving Maneuvers 31

Lateral Trajectory Stabilization of an Articulated Truck dur...

引用

31st IEEE Intelligent Vehicles Symposium, IV 2020

作者： Kumar, Mohit Hildebrandt, Arne-Christoph Strauss, Peter Kraus, Sven Stiller, Christoph Zimmermann, Andreas Mobile Perception System Forschungszentrum Informatik Karlsruhe Germany Engineering Central Research Man Truck Bus SE. Munich Germany Institute of Measurement and Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

The stabilization of articulated truck i.e. truck-semitrailer is a complex problem due to the instable dynamics. In this paper, a lateral trajectory stabilization algorithm for reverse driving of truck-semitrailer is proposed. A cascade control is presented for lateral trajectory stabilization of truck-semitrailer. A high-level path tracking algorithm handles the path tracking of a virtual vehicle which is an equivalent model for the semitrailer. A low-level Linear Quadratic Regulator (LQR) stabilizes the hitch angle. The path tracking problem is formulated as a linear time-varying differential dynamic programming problem subjective to virtual vehicle dynamics in a receding horizon fashion. The virtual vehicle dynamics are defined by the single track kinematic vehicle model and the hitch angle dynamics is used for formulating the Linear Quadratic Regulator problem. The approach is demonstrated with replays of real-world path tracking scenarios on a full-scale truck-semitrailer prototype. © 2020 IEEE.

关键词： Stabilization

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Neutronic and Thermaldynamic Analysis on control Drum Failures Accident in Heat Pipe Cooled Reactors

SSRN

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SSRN 2023年

作者： Gao, Tianyu Zhou, Tao Huang, Dongli Xue, Chunhui Lu, Huaichang Tang, Jianyu Department of Nuclear Science and Technology School of Energy and Environment Southeast University Jiangsu Nanjing210096 China Institute of Nuclear Thermal-hydraulic Safety and Standardization Jiangsu Nanjing210096 China National Engineering Research Center of Large Power Generation Equipment Safety Operation and Intelligent Measurement and Control Southeast University Jiangsu Nanjing210096 China

This manuscript analyzed the reactor safety of a heat pipe cooled reactor, determining the accident severity in the control drum failure accidents, by calculating the reactivity insertion and radial power distribution with OpenMC, core temperature distribution and actual power density with COMSOL. In addition, this manuscript provides a universal control drum design scheme by changing the shape of the control drum. Results show that the conventional control drum structure has inherent safety characteristics in the case of single control drum failure. When multiple control drums fail, the maximum temperature of reactor core exceeds the designed upperbound, requiring the insertion of safety rod to emergency shut down. In order to reduce the impact of positive reactivity insertion and mitigate the severity of the accident, the control drum absorber and a part of reflector should be designed integratedly as the cylindrical control drums. © 2023, The Authors. All rights reserved.

关键词： Heat pipes

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Surface crack characterization using laser nonlinear ultrasonics based on the bispectrum

Surface crack characterization using laser nonlinear ultraso...

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作者： Liu, Hui Wang, Zhaoba Zheng, Bin National Key Lab for Electronic Measurement Technology North University of China Taiyuan030051 China School of Information and Communication Engineering North University of China Taiyuan030051 China School of Electrical and Control Engineering North University of China Taiyuan030051 China

Laser nonlinear wave modulation spectroscopy (LNWMS) has been used to detect nonlinear ultrasonic signatures caused by fatigue cracks in materials. The nonlinear feature extraction from the spectral plot plays a significant role in LNWMS. This paper uses the bispectrum to distinguish harmonically related signals which result from nonlinear interactions and to remove those which do not. A feature called bispectrum damage factor (BDF), which is defined as the ratio of the bispectrum peak difference value of the damage and intact signals to the bispectrum peak value of intact signals at frequencies F 1, F 2, is extracted from the bispectral plot to characterize the crack features. The basic premise of the proposed laser nonlinear wave modulation bispectrum (LNWMBS) is that this BDF value will vary regularly as the level of crack-induced nonlinearity increases. A finite element model and a noncontact laser ultrasonic system have been built for LNWMBS measurement. The simulation results show that the BDF value is sensitive to crack depth and angle, and is insensitive to crack length and detecting position. BDF values of reflected Rayleigh waves are positive and approximately linearly increase with an increase of the crack depths in the range of 0.1 λ ∼ 0.6 λ (λ is the corresponding wavelength of adopted frequency);meanwhile, the values of the transmitted waves are negative and decreasing. The BDF values are larger than the crack angle at 90° when they are less than 90°, which is beneficial for crack detection. The proposed LNWMBS technique has been successfully tested for detecting artificial sub-millimeter surface-breaking cracks in aluminum alloy plates and closed fatigue cracks of torque load simulator connection blocks. © 2020 IOP Publishing Ltd.

关键词： Finite element method

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