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A U-Net-like full convolutional pavement crack segmentation network based on multi-layer feature fusion

International Journal of Pavement engineering 2025年第1期26卷

作者： Jin Wang Zhigao Zeng Fengxiang Huang R. Simon Sherratt Osama Alfarraj Amr Tolba Jianming Zhang a School of Computer and Communication Engineering Changsha University of Science and Technology Changsha People's Republic of China a School of Computer and Communication Engineering Changsha University of Science and Technology Changsha People's Republic of Chinad Key Laboratory of Safety Control of Bridge Engineering Ministry of Education (Changsha University of Science and Technology) Changsha People's Republic of China b Department of Biomedical Engineering The University of Reading Reading UK c Computer Science Department Community College King Saud University Riyadh Saudi Arabia

ABSTRACTCracks are an important indicator of pavement health, and it is difficult to achieve pixel-level segmentation of small and thin cracks. The existing network often experiences false segmentation and missed segmentation. Accordingly, a novel end-to-end U-Net-like full convolutional crack segmentation network is constructed. First, we propose a multi-layer feature fusion module to aggregate the texture and semantic features at each stage of encoder, so that the network can find smaller and thinner crack. Second, we design a novel residual structure with a pointwise convolution. Each stage of the encoder and decoder incorporates a residual structure to facilitate the fusion of feature maps with different spatial dimensions. It can also prevent the gradient vanish in the network training process. Finally, we utilise the maximum unpooling to restore spatial structure in up-sampling, which exploits the indices of maximum feature value in down-sampling. Therefore, high-frequency information is better preserved to help accurately restore the details of crack edges. To verify the proposed network performance, experiments are carried out on four open datasets, the proposed network can achieve better performance among five classical networks.

关键词： Crack segmentation deep learning semantic segmentation pavement damage detection

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PenAAc-based interfacial passivation to reduce voltage loss and defect densities in lead-free perovskite solar cells

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Journal of Applied Physics 2025年第21期137卷

作者： Guo, Jun Liu, Yu Chen, Xinyao Cheng, Jin Zhao, Longjiang Li, Junming Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China Beijing Key Laboratory for Sensor School of Science Beijing Information Science and Technology University Beijing100101 China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China College of Engineering Qufu Normal University Rizhao276826 China

Tin-based perovskites are considered a promising alternative to lead-based perovskites due to their low toxicity and suitable optical bandgap. However, the defects and voltage loss issues severely limit their device performance. In this study, an interfacial passivation strategy based on pentylammonium acetate (PenAAc) was proposed in tin-based perovskite solar cells. The PenAAc-modified layer can effectively improve the perovskite film morphology, crystallinity, and hydrophobicity. Meanwhile, the introduction of the PenAAc layer can significantly inhibit carrier complexation and reduce the hysteresis effect in solar cells. By systematically analyzing the charge transport and compounding mechanisms, the PenAAc layer enhances the built-in electric field, improves the carrier separation and the carrier extraction efficiency, and reduces the defect density in the perovskite layer. The optimal tin-based perovskite solar cell achieved a power conversion efficiency of 7.0%. Moreover, the PenAAc-modified device maintained above 89% of its initial efficiency even after 1200 h storage in a nitrogen-filled glovebox. © 2025 Author(s).

关键词： Defect density

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Granger-Causality Mining in Atmospheric Visibility Based on Deep Learning 9th

Granger-Causality Mining in Atmospheric Visibility Based on ...

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9th International Conference on Frontier Computing, FC 2019

作者： Liu, Bo He, Xi Li, Jianqiang Qu, Guangzhi Lang, Jianlei Gu, Rentao Faculty of Information Technology School of Software Engineering Beijing University of Technology Beijing100124 China Computer Science and Engineering Department Oakland University RochesterMI48309 United States Key Laboratory of Beijing on Regional Air Pollution Control College of Environmental and Energy Engineering Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811532498

Causal relationship mining of multi-dimensional meteorological time series data can reveal the potential connection between visibility and other influencing factors, and it is meaningful in terms of environmental management, air pollution chasing, and haze control. However, because causality analysis based on statistical methods or traditional machine learning techniques cannot represent the complex relationship between visibility and its influencing factors, as an extension of traditional Granger-causality analysis, we propose a causality mining method based on the seq2seq-LSTM deep learning model. The method can profoundly reveal the hidden relationship between different features and visibility and the regular pattern of bad weather, which can provide theoretical support for air pollution control. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Time series

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Non-contact monitoring of heart rate variability using medical radar for the evaluation of dynamic changes in autonomic nervous activity during a head-up tilt test

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Journal of Medical engineering and technology 2019年第7期43卷 411-417页

作者： Sun, Guanghao Tanaka, Yosuke Kiyono, Ken Hashimoto, Kenichi Takase, Bonpei Liu, He Kirimoto, Tetsuo Matsui, Takemi Graduate School of Informatics and Engineering The University of Electro-Communications ChofuTokyo Japan Graduate School of System Design Tokyo Metropolitan University HinoTokyo Japan Division of Bioengineering Graduate School of Engineering Science Osaka University ToyonakaOsaka Japan Department of Intensive Care Medicine National Defense Medical College TokorozawaSaitama Japan Department of Measurement and Control Technology and Communication Engineering The Harbin University of Science and Technology Harbin China

Electrocardiography (ECG) is a mandatory standard for monitoring electrical activity of the heart in many clinical settings such as intensive care and emergency units. However, in situations wherein the skin is damaged, such as acute burn injuries, it is impossible to efficiently attach electrodes to the skin. In this study, we developed a non-contact cardiac monitoring system using a 24-GHz medical radar for directly measuring the beat-to-beat heart mechanical activity at a distance from a subject. The heart rate variability (HRV) was analysed using an autoregressive model (AR) from the measured beat-to-beat intervals during a head-up tilt test. To investigate the feasibility of the proposed system, we compared medical radar and ECG recording by using Lin’s correlation coefficient and Bland–Altman analysis, which showed a negligible mean difference from the substantial agreement of Lin’s correlation coefficient of 0.9 between the radar and ECG. The non-contact radar clearly monitored dynamic changes in HRV indices induced by the head-up tilt test. This type of non-contact HRV-sensing technique as an alternative approach has significant potential for advancing personal healthcare in both clinical and out-of-hospital settings. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Electrocardiography

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Recycling qubits for the generation of Bell nonlocality between independent sequential observers

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Physical Review A 2022年第2期105卷 022411-022411页

作者： Shuming Cheng Lijun Liu Travis J. Baker Michael J. W. Hall The Department of Control Science and Engineering Tongji University Shanghai 201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai 201804 China Institute for Advanced Study Tongji University Shanghai 200092 China College of Mathematics and Computer Science Shanxi Normal University Linfen 041000 China Centre for Quantum Computation and Communication Technology (Australian Research Council) Centre for Quantum Dynamics Griffith University Brisbane QLD 4111 Australia Department of Theoretical Physics Research School of Physics Australian National University Canberra ACT 0200 Australia

There is currently much interest in the recycling of entangled systems, for use in quantum information protocols by sequential observers. In this work, we study the sequential generation of Bell nonlocality via recycling one or both components of two-qubit states. We first give a description of two-valued qubit measurements in terms of measurement bias, strength, and reversibility, and derive useful tradeoff relations between them. Then, we derive one-sided monogamy relations for unbiased observables that strengthen the recent conjecture by Cheng et al. [Phys. Rev. A 104, L060201 (2021)] that if the first pair of observers violate Bell nonlocality then a subsequent independent pair cannot, and give semianalytic results for the best possible monogamy relation. We also extend the construction by Brown and Colbeck [Phys. Rev. Lett. 125, 090401 (2020)] to obtain (i) a broader class of two-qubit states that allow the recycling of one qubit by a given number of observers on one side and (ii) a scheme for generating Bell nonlocality between arbitrarily many independent observers on each side, via the two-sided recycling of multiqubit states. Our results are based on a formalism that is applicable to more general problems in recycling entanglement and hence is expected to aid progress in this field.

关键词： Nonlocality Quantum correlations in quantum information Quantum networks

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GPDP: Game-Enhanced Personalized Differentially Private Smart Community

GPDP: Game-Enhanced Personalized Differentially Private Smar...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and communications (GreenCom)

作者： Yuping Zhang Youyang Qu Longxiang Gao Bruce Gu Lei Cui Xuemeng Zhai School of Network & Communication Chendu Technological University Chendu Sichuan China School of Information Technology Deakin University Geelong VIC Australia College of Engineering and Science Victoria University Footscary VIC Australia Key Laboratory of Advanced Control and Intelligent Information System Taiyuan University of Science and Technology Taiyuan Shanxi China College of Engineering and Science University of Electronic Science and Technology of China Chengdu Sichuan China

ISBN: (纸本)9781665417631

Smart community, as a key component of Internet of Things (IoT), is experiencing fast booming, which significantly enhances residents' quality of life. Using fog computing to establish a smart community is an effective way to further develop smart and sustainable cities due to the reduction of bandwidth consumption and latency. However, privacy issues are emerging because the continuous attacks are putting sensitive information under great threats. Motivated by this, we propose a differentially private smart community model with personalized privacy protection. Differential privacy is deployed in a personalized way while a logarithmic function is leveraged to map data sensitivity to privacy protection level. Extensive evaluation results show the advantages of the proposed model from the perspective of the optimized trade-off between personalized privacy protection and data utility.

关键词： Differential privacy Privacy Sensitivity Smart cities Computational modeling Bandwidth Data models

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Adaptive neural network output-feedback tracking control for switched nonlinear ship maneuvering systems with time delays under arbitrary switching

Adaptive neural network output-feedback tracking control for...

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Chinese Automation Congress (CAC)

作者： Zhenhua Li Xiangxuan Ren Botao Dong Hong Chen Weidong Zhang SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya P. R. China Department of Automation Shanghai Jiao Tong University Shanghai P. R. China College of Mechatronics and Control Engineering Shenzhen University Shenzhen P. R. China School of Information and Communication Engineering Hainan University Haikou P. R. China

This paper focuses on the tracking control problem for switched nonlinear ship maneuvering time-delay systems with only a heading angle available by adaptive neural network (NN) output feedback. Using the backstepping method, an adaptive NN control mechanism is designed to solve the problem cooperated with the state observer. The uncertain terms of the system are approximated by NNs, and the state observer is designed to estimate the yaw rate and rudder angle. The unknown time delays are overcome by exploiting the common Lyapunov-Krasovskii functionals (CLKFs). Combined with error transformation, the proposed control method guarantees that i) all of the signals for the system are semi-global uniformly ultimately boundedness (SGUUB) under arbitrary switching; and, ii) the tracking error of system output keeps within a small neighborhood around the origin. The results of simulation results are shown to demonstrate the feasibility of the control strategy.

关键词： Adaptive systems Backstepping Delay effects Simulation Switches Artificial neural networks Observers

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Sensing With Random communication Signals

arXiv

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arXiv 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi National Mobile Communications Research Laboratory Southeast University Nanjing210096 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin10587 Germany Southern University of Science and Technology Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security and also The Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing211189 China

communication-centric Integrated Sensing and communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025, CC BY-SA.

关键词： Signaling

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Omnidirectional and Broadband Metamaterial Absorber Using Multilayer Graphene Ribbons 5

Omnidirectional and Broadband Metamaterial Absorber Using Mu...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Cai, Yijun Hang, Yanfen Cao, Le Zhou, Yuanguo School of Opto-electronic and Communication Engineering Xiamen University of Technology Xiamen361024 China College of Communication and Information Engineering Xi'An University of Science and Technology Xi'an710054 China College of Electric and Control Engineering Xi'An University of Science and Technology Xi'an710054 China

ISBN: (纸本)9781538671115

A broadband metamaterial absorber is proposed utilizing multilayer graphene ribbons sandwiched between dielectric layers. The absorption spectrum can be further widen by stacking graphene ribbons of different widths layer by layer. Moreover, the graphene-based absorber can tolerate a wide range of incident angles. Our study can be applied in the systems of sensing, communication and imaging. © 2019 IEEE.

关键词： Graphene

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A fluorescent fiber pH sensor for sensitive, wide-range detection using orange-emitting silicon quantum dots

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Analytica Chimica Acta 2025年 1368卷

作者： Dan Li Xiaolong Li Zijia Huang Tengteng Liu Mao Li Xiaoming Chen Na Li Yong Zhao School of Control Engineering Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Northeastern University at Qinhuangdao Qinhuangdao 066004 China Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices School of Optoelectronic Science and Engineering South China Normal University Guangzhou 510006 China College of Information Science and Engineering Northeastern University Shenyang 110819 China

pH value plays a vital role in biochemical analysis. To achieve online analysis, a new type of fluorescent fiber sensor has been developed for real-time, wide-range pH monitoring in biological and environmental fluids. The fluorescent fiber pH sensor was facilely created by immobilizing orange-emitting silicon quantum dots onto a tapered fiber probe through a photoinduced hydrogel polymerization technique. The sensor displays a specific response to pH variations, covering an extensive dynamic range from pH 3.0 to 12.0 with a resolution of 0.06/pH. Additionally, the sensor exhibited remarkable stability, repeatability, robustness, and reversibility. Especially, its high stability to ion strength and temperature fluctuations ensures reliable performance across various physiological and physical conditions. Furthermore, successful implementations of this sensor in detecting pH levels in real serum, artificial sweat and seawater samples further validate its accuracy, practicality and versatility. Overall, this sensor offers a practical and versatile tool for sensitive, real-time pH sensing in complex fluid environments, with great potential across multiple fields.

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