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SSRN 2023年

作者： Ye, Lianxu Wu, Fan Xu, Ruixing Zhang, Di Lu, Juanjuan Wang, Chuanlong Dong, Anjiang Xu, Sichen Xue, Lejun Fan, Zixin Xu, Longjie Li, Kaifeng Li, Dong Kursumovic, Ahmed Zhao, Run Tang, Rujun Qiu, Lei Wang, Haiyan MacManus-Driscoll, Judith L. Jing, Qingshen Li, Weiwei Yang, Hao College of Physics MIIT Key Laboratory of Aerospace Information Materials and Physics Nanjing University of Aeronautics and Astronautics Nanjing211106 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China School of Microelectronics & Data Science Anhui University of Technology Maanshan243002 China School of Materials Engineering School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Jiangsu Key Laboratory of Thin Films School of Physical Science and Technology Soochow University Suzhou215006 China Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom James Watt School of Engineering University of Glasgow GlasgowG12 8LT United Kingdom State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing211106 China

Face masks are key personal protective equipment for reducing exposure to viruses and other environmental hazards such as air pollution. Integrating flexible and wearable sensors into face masks can provide valuable insights into personal and public health. The advantages that a breath-monitoring face mask requires, including multi-functional sensing ability and continuous, long-term dynamic breathing process monitoring, have been underdeveloped to date. Here, we design an effective human breath monitoring face mask based on a flexible La0.7Sr0.3MnO3 (LSMO)/Mica respiration sensor. The sensor’s capabilities and systematic measurements are investigated under two application scenes, namely clinical monitoring mode and daily monitoring mode, to monitor, recognise, and analyse different human breath status, i.e., cough, normal breath, and deep breath. This sensing system exhibits super-stability and multi-modal capabilities in continuous and long-time monitoring of the human breath. We determine that during monitoring human breath, thermal diffusion in LSMO is responsible for the change of resistance in flexible LSMO/Mica sensor. Both simulated and experimental results demonstrate good discernibility of the flexible LSMO/Mica sensor operating at different breath status. Our work opens a route for the design of novel flexible and wearable electronic devices. © 2023, The Authors. All rights reserved.

关键词： Mica

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2020 International Conference on computer Big Data and Artificial Intelligence, ICCBDAI 2020

作者： Li, Ni Peng, Manman Cao, Buwen Li, Kenli Li, Keqin College of Computer Science and Electric Engineering Hunan University Changsha Hunan410082 China College of Information and Electronic Engineering Yiyang Hunan413000 China Department of Computer Science State University of New York New PaltzNY12561 United States Engineering Research Center of Dong Ting Lake Regional Ecological Environment Intelligent Monitoring Disaster Prevention and Mitigation Hunan Yiyang413000 China Key Laboratory of City Computing and IoT Hunan City UniversityHunan Yiyang413000 China

Spectral clustering is one of the most popular clustering approaches. Despite its good performance and strong theoretical supports, it is limited to high complexity of the graph Laplacian similarity matrix construction and eigen-decomposition problems. Recently, deep learning has been successfully adopted in graph representation. In the paper, we jointly learn the manifold graph construction and non-linear low-dimension mapping of the graph. In addition, we theoretically proved that our model according with spectral clustering theory. Meanwhile, we use the proposed non-linear coders as the building blocks to formulate a deep structure to further refine features of layer wise fashion. Extensive experiments on clustering tasks demonstrate that our method performs well in terms of both clustering accuracy and normalized mutual information( NMI ). © Published under licence by IOP Publishing Ltd.

关键词： Deep learning

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An Ultra-compact Broadband TE-pass Nanofocusing Structure

An Ultra-compact Broadband TE-pass Nanofocusing Structure

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2020 Asia Communications and Photonics Conference, ACP 2020 and International Conference on Information Photonics and Optical Communications, IPOC 2020

作者： Zhu, Kejian Pengfei, Xu Sun, Pengfei Liu, Xingpeng Li, Haiou Zhou, Zhiping Nano-optoelectronics Frontier Center of Ministry of Education Peking University Beijing100871 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Department of Electronics Beijing100871 China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin China

We propose a broadband structure which integrates polarization and nanofocusing functions into a single device with 3.8x4 μm footprint. The bandwidth is over 200 nm with insert loss (IL) smaller than 1.68 dB. © ...

ISBN: (纸本)9781943580828

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Hero: On the Chaos When PATH Meets Modules

Hero: On the Chaos When PATH Meets Modules

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International Conference on Software Engineering (ICSE)

作者： Ying Wang Liang Qiao Chang Xu Yepang Liu Shing-Chi Cheung Na Meng Hai Yu Zhiliang Zhu Software College Northeastern University China State Key Laboratory for Novel Software Technology and Department of Computer Science and Technology Nanjing University China Southern University of Science and Technology China The Hong Kong University of Science and Technology China Virginia Tech USA

Ever since its first release in 2009, the Go programming language (Golang) has been well received by software communities. A major reason for its success is the powerful support of library-based development, where a Golang project can be conveniently built on top of other projects by referencing them as libraries. As Golang evolves, it recommends the use of a new library-referencing mode to overcome the limitations of the original one. While these two library modes are incompatible, both are supported by the Golang ecosystem. The heterogeneous use of library-referencing modes across Golang projects has caused numerous dependency management (DM) issues, incurring reference inconsistencies and even build failures. Motivated by the problem, we conducted an empirical study to characterize the DM issues, understand their root causes, and examine their fixing solutions. Based on our findings, we developed Hero, an automated technique to detect DM issues and suggest proper fixing solutions. We applied Hero to 19,000 popular Golang projects. The results showed that Hero achieved a high detection rate of 98.5% on a DM issue benchmark and found 2,422 new DM issues in 2,356 popular Golang projects. We reported 280 issues, among which 181 (64.6%) issues have been confirmed, and 160 of them (88.4%) have been fixed or are under fixing. Almost all the fixes have adopted our fixing suggestions.

关键词： Chaos computer languages Ecosystems Benchmark testing Libraries Software Software engineering

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Enhanced Population on Ionic Excited states by Synchronized Ionization and Multiphoton Resonance

arXiv

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arXiv 2023年

作者： Chen, Yewei Lei, Hongbin Wang, Quanjun Xie, Hongqiang Zhang, He Lu, Xu Zhang, Ning Huang, Shunlin Wu, Yuzhu Liu, Jianpeng Zhang, Qian Liu, Yi Zhao, Zengxiu Zhao, Jing Yao, Jinping State Key Laboratory of High Field Laser Physics Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Department of Physics National University of Defense Technology Changsha410073 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China School of Science East China University of Technology Nanchang330013 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China School of Microelectronics Shanghai University Shanghai200444 China

We study population distributions and lasing actions of N2+ drieen by femtosecond lasers with earious waeelengths, and uncoeer an efficient ionic excitation mechanism induced by synchronized ionization and multiphoton resonance. Our results show that the strongest N2+ lasing appears around 1000 nm pump waeelength. At the optimal waeelength, the pump-energy threshold for air lasing generation is reduced by fiee folds compared with that required by the preeious 800 nm pump laser. Simulations based on the ionization-coupling model indicate that although the Stark-assisted three-photon resonance can be satisfied within a broad pump waeelength range, the optimal pump waeelength arises when the dynamic three-photon resonance temporally synchronizes with the ionization injection. In this case, the ionic dipoles created at each half optical cycle haee the same phase. The dipole phase locking promotes the continuous population transfer from ionic ground state to the excited state, gieing rise to a dramatic increase of excited-state population. This work proeides new insight on the photoexcitation mechanism of ions in strong laser fields, and opens up a route for optimizing ionic radiations. Copyright © 2023, The Authors. All rights reserved.

关键词： Excited states

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Exchange-Torque-Triggered Fast Switching of Antiferromagnetic Domains

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Physical Review Letters 2022年第13期128卷 137201-137201页

作者： Jia Xu Jing Xia Xichao Zhang Chao Zhou Dong Shi Haoran Chen Tong Wu Qian Li Haifeng Ding Yan Zhou Yizheng Wu Department of Physics and State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China Institute of Physics Shaanxi University of Technology Hanzhong 723001 China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Guangdong 518172 China College of Physics and Electronic Engineering Sichuan Normal University Chengdu 610068 China Department of Electrical and Computer Engineering Shinshu University 4-17-1 Wakasato Nagano 380-8553 Japan National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei 230029 China National Laboratory of Solid State Microstructures Department of Physics Nanjing University Nanjing 210093 China Shanghai Research Center for Quantum Sciences Shanghai 201315 China

The antiferromagnet is considered to be a promising hosting material for the next generation of magnetic storage due to its high stability and stray-field-free property. Understanding the switching properties of the antiferromagnetic (AFM) domain state is critical for developing AFM spintronics. By utilizing the magneto-optical birefringence effect, we experimentally demonstrate the switching rate of the AFM domain can be enhanced by more than 2 orders of magnitude through applying an alternating square-wave field on a single crystalline Fe/CoO bilayer. The observed extraordinary speed can be much faster than that triggered by a constant field with the same amplitude. The effect can be understood as the efficient suppression of the pinning of AFM domain walls by the strong exchange torque triggered by the reversal of the Fe magnetization, as revealed by spin dynamics simulations. Our finding opens up new opportunities to design the antiferromagnet-based spintronic devices utilizing the ferromagnet-antiferromagnet heterostructure.

关键词： Antiferromagnetism Magnetic coupling Magnetization switching Magneto-optical effect Antiferromagnets Single crystal materials Surfaces Thin films Magnetization measurements Micromagnetic modeling Optical microscopy

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Optimal Landing of Tilt-rotor Aircraft after Engine Failure Considering Pilot Inherent Limitations

Optimal Landing of Tilt-rotor Aircraft after Engine Failure ...

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IEEE International Conference on Robotics and Biomimetics

作者： Xufei Yan Renliang Chen Shiqiang Zhu Anhuan Xie Jason Gu Research Center for Intelligent Robotics Zhejiang Lab Hangzhou 311100 China. Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu China Intelligent Robot Research Center Zhejiang Lab Hangzhou Zhejiang China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

An augmented longitudinal rigid-body model is developed with a set of algebra equations describing the controls in the cockpit and the differential equations describing the pilot inherent limitations. The landing procedure after one engine failure is formulated into a nonlinear optimal control problem. XV-15 tilt-rotor aircraft is taken as the sample for the demonstration of landing in one engine failure during short takeoff. The results show that the total power required, thrust coefficient, longitudinal flapping angle and optimal controls are more relatively gentle than the solutions without considering the pilot inherent limitations. Compared with the basic longitudinal rigid-body model, the optimal solutions involve more control information.

关键词： Atmospheric modeling Optimal control Rotors Mathematical models History Aircraft propulsion Aircraft

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Lightweight Trust Model with Machine Learning scheme for secure privacy in VANET

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Procedia computer science 2021年 194卷 45-59页

作者： Muhammad Haleem Junejo Ab Al-Hadi Ab Rahman Riaz Ahmed Shaikh Kamaludin Mohamad Yusof Dileep Kumar Imran Memon Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Skudai Johor Malaysia Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia State Key Laboratory of Industrial Control Technology College of Control Science & Engineering Zhejiang University Hangzhou china Department of computer science bahria university Karachi campus sindh Pakistan

A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.

关键词： VANET Trust Model Machine Learning

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用于监测锂离子电池膨胀的通过屈曲实现超过两百倍电流放大的摩擦纳米发电机（英文）

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science Bulletin 2025年第2期 148-152页

作者：张懋熠胡超胜张彤彤 Chris R.Bowen 李锐黄永安苏业旺王中林杨亚 Beijing Key Laboratory of Micro-Nano Energy and Sensor Center for High-Entropy Energy and Systems Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences State Key Laboratory of Nonlinear Mechanics Institute of Mechanics Chinese Academy of Sciences School of Engineering Science University of Chinese Academy of Sciences School of Nanoscience and Technology University of Chinese Academy of Sciences Department of Mechanical Engineering University of Bath State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology School of Material Science and Engineering Georgia Institute of Technology

Sensors deployed within the Internet of Things(Io T) require a stable and continuous electrical energy supply [1]. The traditional approach to provide an energy supply relies primarily on battery power, which has specific shortcomings; these include integration difficulties, the need for frequent charging or replacement, and environmental pollution associated with battery production and disposal. To solve the challenge of delivering an energy supply to sensors, researchers have designed self-powered sensors or have produced power for sensors by scavenging mechanical energy from the surrounding environment. Electromagnetic generators [2],piezoelectric generators [3] and triboelectric nanogenerators(TENGs) [4,5] are common approaches to scavenge mechanical energy. TENGs have been widely used in the development of self-powered sensors and the supply of electrical energy to sensors due to their high performance, low cost, and wide range of potential materials [6].

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Study on the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,with prediction of its tendency

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Journal of Biosafety and Biosecurity 2023年第1期5卷 39-44页

作者： Yao Bai Zhihang Peng Fengying Wei Zhen Jin Jinjie Wang Ximing Xu Xinyan Zhang Jun Xu Zixiong Ren Bulai Lu Zhaojun Wang Jianguo Xu Senzhong Huang Xi’an Center for Disease Control and Prevention Xi’an 710054ShaanxiChina Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjing 211166JiangsuChina School of Mathematics and Statistics Fuzhou UniversityFuzhou 350116FujianChina Complex Systems Research Center Key Discipline of Computer Science and Technology of“Double-First-Class”Project of Shanxi ProvinceShanxi UniversityTaiyuan 030006ShanxiChina Nankai Institute of Economics Binhai Development InstituteNankai UniversityTianjin 300071China Children’s Hospital of Chongqing Medical University Chongqing 400010China Jinzhou Center for Disease Control and Prevention Jinzhou 121000LiaoningChina School of Statistics and Data Science Nankai UniversityTianjin 300071China Suzhou Center for Disease Control and Prevention Suzhou 215004JiangsuChina State Key Laboratory of Communicable Disease Prevention and Control National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 102206China Institute of Public Health Nankai UniversityTianjin 300071China School of Statistics and Data Science ZhiYing Research Center for Health DataNankai UniversityTianjin 300071China

The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chinese Center for Disease Control and Prevention on February 1,*** kinds of reported data were used for model fitting:the daily numbers of positive nucleic acid tests and deaths,and the daily number of hospital beds taken by COVID-19 *** was estimated that the overall infection rate was 87.54%and the overall case fatality rate was 0.078%–0.116%(median 0.100%).Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023,induced by a slightly more infectious mutant strain,we predicted a possible large rebound between September and October 2023,with a peak demand of between 800,000 and 900,000 inpatient *** no such new outbreak was induced by other variants,then the current COVID-19 epidemic course in China's Mainland would remain under control until the end of ***,it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future,especially for the period between September and October 2023.

关键词： COVID-19 Epidemic Infection rate Case fatality rate Prediction

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