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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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Layer-dependent optical and dielectric properties of CdSe semiconductor colloidal quantum wells characterized by spectroscopic ellipsometry

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Journal of Semiconductors 2025年第4期46卷 46-53页

作者： Chenlin Wang Haixiao Zhao Xian Zhao Baoqing Sun Jie Lian Yuan Gao School of Information Science and Engineering Shandong UniversityQingdao 266237China Key Laboratory of Laser&Infrared System(Shandong University) Ministry of EducationShandong UniversityQingdao 266237China Center for Optics Research and Engineering(CORE) Shandong UniversityQingdao 266237China

Semiconductor colloidal quantum wells(CQWs)with atomic-precision layer thickness are rapidly gaining attention for next-generation optoelectronic applications due to their tunable optical and electronic *** this study,we investigate the dielectric and optical characteristics of CdSe CQWs with monolayer numbers ranging from 2 to 7,synthesized via thermal injection and atomic layer(c-ALD)deposition *** a combination of spectroscopic ellipsometry(SE)and first-principles calculations,we demonstrate the significant tunability of the bandgap,refractive index,and extinction coefficient,driven by quantum confinement *** results show a decrease in bandgap from 3.1 to 2.0 eV as the layer thickness ***,by employing a detailed analysis of the absorption spectra,accounting for exciton localization and asymmetric broadening,we precisely capture the relationship between monolayer number and exciton binding *** findings offer crucial insights for optimizing CdSe CQWs in optoelectronic device design by leveraging their layer-dependent properties.

关键词： CdSe CQWs bandgap spectroscopic ellipsometry monolayer number exciton binding energy

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Neural-based prescribed-time consensus control for multiagent systems via dynamic memory event-triggered mechanism

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Science China(Technological Sciences) 2025年第3期68卷 217-227页

作者： Xiaohong ZHENG Hui MA Qi ZHOU Hongyi LI School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Controland Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative ControlGuangdong University of TechnologyGuangzhou510006China School of Mathematics and Statistics Guangdong University of TechnologyGuangzhou510006China College of Electronic and Information Engineering and the Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest UniversityChongqing400715China

This work investigates the implementation of distributed prescribed-time neural network(NN)control for nonlinear multiagent systems(MASs)using a dynamic memory event-triggered mechanism(DMETM).First,it introduces a composite learning technique in NN *** method leverages the prediction error within the NN update law to enhance the accuracy of the unknown nonlinearity ***,by introducing a time-varying transformation,the study establishes a distributed prescribed-time control *** notable feature of this algorithm is its ability to predetermine the convergence time independently of initial conditions or control ***,the DMETM is established to reduce the actuation frequency of the *** the conventional memoryless dynamic event-triggered mechanism,the DMETM incorporates a memory term to further increase triggering *** a distributed estimator for the leader,the DMETM-based NN prescribed-time controller is designed in a fully distributed manner,which guarantees that all signals in the closed-loop system remain bounded within the prescribed ***,simulation results are presented to validate the effectiveness of the proposed algorithm.

关键词： consensus control composite learning control dynamic memory event-triggered control prescribed-time control multiagent systems(MASs)

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Experimental demonstration of D-band signals wireless transmission over 30 km

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Science China(Technological Sciences) 2025年第2期68卷 318-320页

作者： Yi WEI Xiongwei YANG Jianjun YU Xianming ZHAO Mingxu WANG Jingwen TAN Weiping LI Feng ZHAO Chengzhen BIAN Hansong MA Qinyi ZHANG Qiutong ZHANG Bing Zhang Wen ZHOU Kaihui WANG Sicong XU Jianguo YU State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves(MoE)and School of Information Science and TechnologyFudan UniversityShanghai 200433China Harbin Institute of Technology Harbin 150001China School of Automation Xi’an University of Posts and TelecommunicationsXi’an 710121China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Due to the rise of innovative technologies like artificial intelligence(AI),the Internet of Things(IoT),and telemedicine,the demand for internet traffic is rapidly *** order to achieve ultra-high-speed wireless communication,many researchers are directing their efforts towards the *** D-band,spanning the frequency band 110-170 GHz,has abundant spectrum resources and license-free characteristics[1,2].

关键词： IoT wireless band

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A Valuable and Low-Budget Process Scheme of Equivalized 1 nm Technology Node Based on 2D Materials

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Nano-Micro Letters 2025年第8期17卷 294-305页

作者： Yang Shen Zhejia Zhang Zhujun Yao Mengge Jin Jintian Gao Yuhan Zhao Wenzhong Bao Yabin Sun He Tian College of Integrated Circuit Science and Engineering Shanghai Key Laboratory of Multidimensional Information ProcessingEast China Normal UniversityShanghai 200241People’s Republic of China Institute of Microelectronics and Beijing National Research Center for Information Science and Technology(BNRist) Tsinghua UniversityBeijing 100084People’s Republic of China State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai 200433People’s Republic of China Shaoxin Laboratory Shaoxing 312000People’s Republic of China

Emerging two-dimensional(2D)semiconductors are among the most promising materials for ultra-scaled transistors due to their intrinsic atomic-level *** the stacking process advances,the complexity and cost of nanosheet field-effect transistors(NSFETs)and complementary FET(CFET)continue to *** 1 nm technology node is going to be based on Si-CFET process according to international roadmap for devices and systems(IRDS)(2022,https://***/),but not publicly confirmed,indicating that more possibilities still *** miniaturization advantage of 2D semiconductors motivates us to explore their potential for reducing process costs while matching the performance of next-generation nodes in terms of area,power consumption and *** this study,a comprehensive framework is built.A set of MoS2 NSFETs were designed and fabricated to extract the key parameters and *** then for benchmarking,the sizes of 2D-NSFET are scaled to a extent that both of the Si-CFET and 2D-NSFET have the same average device *** these conditions,the frequency of ultra-scaled 2D-NSFET is found to improve by 36%at a fixed power *** work verifies the feasibility of replacing silicon-based CFETs of 1 nm node with 2D-NSFETs and proposes a 2D technology solution for 1 nm nodes,i.e.,“2D eq 1 nm”*** the same time,thanks to the lower characteristic length of 2D semiconductors,the miniaturized 2D-NSFET achieves a 28%frequency increase at a fixed power ***,developing a standard cell library,these devices obtain a similar trend in 16-bit RISC-V *** work quantifies and highlights the advantages of 2D semiconductors in advanced nodes,offering new possibilities for the application of 2D semiconductors in high-speed and low-power integrated circuits.

关键词： Two-dimensional semiconductors 1 nm technology node Nanosheet field-effect transistors Complementary field-effect transistors Horizontal scaling

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Comparison of gap-filling methods for generating landsat-like land surface temperatures under all-weather conditions

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ISPRS Journal of Photogrammetry and Remote Sensing 2025年 225卷 113-130页

作者： Guo, Jiali Quan, Jinling Zhan, Wenfeng Wen, Zhongguan State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100190 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Jiangsu Nanjing210046 China College of Environmental Sciences and Engineering Peking University Beijing100871 China

Thermal infrared remote sensors provide cost-effective and widespread land surface temperatures (LSTs) but often with spatiotemporal gaps due to discrete sampling and synoptic disturbance, greatly limiting their reliability and application. Current gap-filling methods have been primarily developed and validated for medium- to low-resolution LSTs;however, with rising demand for spatiotemporally continuous, high-resolution (tens of meters like Landsat) LSTs across disciplines, there is an urgent need to assess these methods’ applicability and uncertainty at higher spatial resolutions under a unified framework. In this study, we apply eight typical and hybrid methods, including temporal interpolation, spatiotemporal interpolation, weight-based fusion, learning-based fusion, and four standard annual temperature cycle (ATC)-based hybrid reconstructions, to fill gaps in irregularly spaced Landsat series over Weishan, Huairou, and Yulin, China. These sites represent cropland in a sub-humid plain, forest in a sub-humid mountain region, and grassland in the semi-arid Loess Plateau. We evaluate their performance in terms of spatiotemporal pattern, statistical accuracy, sensitivity to input data quality and distribution, and adaptability to different synoptic and surface conditions based on cloudy Landsat data and in-situ measurements. Results reveal that the enhanced ATC (EATC) method is optimal among these methods, capturing all-weather spatiotemporal dynamics at the Landsat scale with superior accuracy and robustness under various input, cloud, and ground conditions. In addition, the ATC-based hybrid methods do not necessarily improve the statistical accuracy over their respective typical ones. This comprehensive evaluation provides valuable insights into the selection of appropriate gap-filling methods for generating Landsat-like LSTs under all-weather conditions and highlights the need for further advancements especially in addressing abrupt changes in land cover types an

关键词： Surface stress

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Temperature Self-Reference Gas Pressure Sensor Based on Intracavity Sensing of Fiber Ring Laser

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Journal of Lightwave Technology 2025年第9期43卷 4259-4265页

作者： Shi, Boya Huo, Xinjuan Wang, Shaona Niu, Pingjuan Tang, Longhuang Li, Hongmei Yao, Jianquan Shi, Jia Tiangong University Tianjin Key Laboratory of Optoelectronic Detection Technology and System School of Electronics and Information Engineering Tianjin300387 China China Academy of Engineering Physics Institute of Fluid Physics Mianyang621900 China Aero Engine Corporation of China Commercial Aircraft Engine Company Limited Shanghai200241 China Ministry of Education Tianjin University Key laboratory of Opto-Electronic Information Technology Tianjin300072 China

The temperature cross-sensitivity is always challenging for the design and application of fiber-optic gas pressure sensors. Here, a temperature self-reference gas pressure sensor based on intracavity sensing of fiber ring laser has been demonstrated. The Fabry-Perot interferometer and fiber Bragg grating are cascaded as reflection sensing head and coupled into a fiber ring laser. The Fabry-Perot interferometer shows high sensitivities of gas pressure and temperature because of its specific fiber micro cavity structure. The fiber Bragg grating has narrow-band filtering characteristics at a certain wavelength, which ensures the desired accuracy for intracavity sensing, and has good temperature response characteristics. In the temperature self-reference sensing system, the output wavelength of the fiber ring laser is only modulated by the sensor temperature, while the output intensity is simultaneously modulated by the sensor temperature and gas pressure. The sensing model of the temperature self-reference gas pressure sensor has been presented. The experiment verifies that the scheme can measure gas pressure and temperature simultaneously. The stability and measurement errors have been analyzed. The proposed sensing system provides a potential solution for solving temperature cross-sensitivity in gas pressure measurement and can be extensible to similar fiber-optic sensors. © 1983-2012 IEEE.

关键词： Fabry-Perot interferometers

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A pipelining task offloading strategy via delay-aware multi-agent reinforcement learning in Cybertwin-enabled 6G network

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Digital Communications and Networks 2025年第1期11卷 92-105页

作者： Haiwen Niu Luhan Wang Keliang Du Zhaoming Lu Xiangming Wen Yu Liu Beijing Laboratory of Advanced Information Networks Beijing Univ.of Posts&TelecomBeijing 100876China Beijing Key Lab of Network System Architecture and Convergence Beijing Univ.of Posts&TelecomBeijing 100876China School of Information and Communication Engineering Beijing Univ.of Posts&TelecomBeijing100876China

Cybertwin-enabled 6th Generation(6G)network is envisioned to support artificial intelligence-native management to meet changing demands of 6G ***-Agent Deep Reinforcement Learning(MADRL)technologies driven by Cybertwins have been proposed for adaptive task offloading ***,the existence of random transmission delay between Cybertwin-driven agents and underlying networks is not considered in related works,which destroys the standard Markov property and increases the decision reaction time to reduce the task offloading strategy *** order to address this problem,we propose a pipelining task offloading method to lower the decision reaction time and model it as a delay-aware Markov Decision Process(MDP).Then,we design a delay-aware MADRL algorithm to minimize the weighted sum of task execution latency and energy ***,the state space is augmented using the lastly-received state and historical actions to rebuild the Markov ***,Gate Transformer-XL is introduced to capture historical actions'importance and maintain the consistent input dimension dynamically changed due to random transmission ***,a sampling method and a new loss function with the difference between the current and target state value and the difference between real state-action value and augmented state-action value are designed to obtain state transition trajectories close to the real *** results demonstrate that the proposed methods are effective in reducing reaction time and improving the task offloading performance in the random-delay Cybertwin-enabled 6G networks.

关键词： Cybertwin Multi-Agent Deep Reinforcement Learning(MADRL) Task offloading Pipelining Delay-aware

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Highly integrated multiplexed microscopy system for integrated circuit failure analysis

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Optics Letters 2025年第9期50卷 2864-2867页

作者： Li, Haotian Liu, Junliang Fei, Cheng Dong, Yakui Li, Yongfu Yang, Shuolin Sun, Linshan Wang, Mengda Fan, Shuzhen Yang, Zhongming Zhao, Xian Shandong University Key Laboratory of Laser & Infrared System Ministry of Education Qingdao266237 China Shandong University Center for Optics Research and Engineering Qingdao266237 China Shandong University School of Information Science and Engineering Qingdao266237 China

In this paper, we present an optical multiplexing structure designed to develop a highly integrated, non-contact, non-destructive inspection system for integrated circuit failure analysis or semiconductor defect detection. This system comprises four subsystems: a bright-/dark-field microscope subsystem, an emission microscope subsystem, a laser confocal scanning microscope subsystem, and a fluorescence confocal microscope subsystem. The functionality of the system is verified and analyzed using avalanche photodetectors. The detection process involves sequential steps: locating the light-emitting devices, performing 3D imaging to assess damage, and comparing fluorescence lifetimes among the devices to analyze the failure mechanisms. This multimodal detection approach enables rapid and accurate identification of production issues, facilitating the tracing of root causes for failures. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Fluorescence

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Fuzzy Terminal Sliding-Mode Control With Adaptive Switching Gain

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IEEE Transactions on Fuzzy systems 2025年第5期33卷 1499-1509页

作者： Feng, Cheng-Cheng Sun, Hao-Yuan Han, Hong-Gui Du, Sheng-Li Beijing University of Technology School of Information Science and Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Laboratory for Smart Environmental Protection Engineering Research Center of Digital Community Ministry of Education Beijing Artificial Intelligence Institute Beijing100124 China

For complex dynamic systems, it is a great challenge to design an appropriate control strategy to achieve stable tracking control. To solve this problem, a fuzzy terminal sliding-mode control method with adaptive switching gain (FTSC-ASG) is designed to improve the control performance in this article. First, an adaptive interval type-2 fuzzy prediction model (AIT2-FPM) is designed to approximate the complex nonlinearity and parameter uncertainty. Specifically, the state prediction error evaluated by predictor is utilized to design the weight adaptive law to improve the accuracy of the AIT2-FPM. Second, a terminal sliding-mode controller is utilized to obtain control input of the system in a finite time. To suppress the chattering phenomenon, the switching gain is designed based on the output of AIT2-FPM and the changes of control input information can be utilized to evaluate the degree of chattering. Furthermore, a parameter adaptive strategy is designed to adjust the parameter of equivalent control law. Third, FTSC-ASG can achieve fast convergence of tracking error, and the finite time stability of FTSC-ASG is proven in detail. Finally, the simulation studies in the third-order nonlinear system and the inverted pendulum systems are given to evaluate the effectiveness of FTSC-ASG. © 1993-2012 IEEE.

关键词： Sliding mode control

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