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Advanced modeling of the absorption enhancement of black carbon particles in chamber experiments by considering the morphology and coating thickness

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Frontiers of Environmental science & Engineering 2024年第9期18卷 129-142页

作者： Xiaodong Wei Jianlin Hu Chao Liu Xiaodong Xie Junjie Yin Song Guo Min Hu Jianfei Peng Huijun Wang Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&TechnologyNanjing 210044China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory of Meteorological Disaster(Ministry of Education)Nanjing University of Information Science and TechnologyNanjing 210044China Nansen−Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China East China Air Traffic Management Bureau CAAC Shanghai 200335China State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution Control(IJRC)(Ministry of Education)College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Tianjin Key Laboratory of Urban Transport Emission Research&State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and EngineeringNankai UniversityTianjin 300071China

Measurements studies have shown that the absorption of radiation by black carbon(BC)increases as the particles ***,there are significant discrepancies between the measured and modeled absorption enhancement(E_(abs)),largely due to the simplifications used in modeling the mixing states and shape *** took advantage of chamber experiments on BC aging and developed an efficient method to resolve the particle shape based on the relationship between the coating fraction(ΔD_(ve)/D_(ve),0)and fractal dimension(D_(f)),which can also reflect the variations of D_(f)during the whole BC aging *** with externally and partly mixed states(0≤ΔD_(ve)/D_(ve),0≤0.5)can be considered to be uniformly distributed with the D_(f)values of 1.8–2.1,whereas the Df values are constrained in the range 2.2–2.8 for fully mixed states(ΔD_(ve)/D_(ve),0>0.5).The morphological parameters(i.e.,the effective density and the dynamic shape factor)were compared with the measured values to verify the simulated *** simulated mean deviations of morphological parameters were smaller than 8%for the method resolving the particle *** applying a realistic shape and refractive index,the mass absorption cross for fully mixed states can be improved by 11%compared with a simplified core–shell *** on our understanding of the influence of D_(f)andΔD_(ve)/D_(ve),0 on E_(abs),we propose a two-stage calibration equation to correct the E_(abs)values estimated by the core–shell model,which reduces the simulation error in the Mie calculation by 6%–14%.

关键词： Black carbon Mixing states Fractal dimension Dynamic shape factor Absorption enhancement

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An end-to-end instance segmentation method based on improved ConvNeXt V2

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International Journal of Wireless and Mobile Computing 2024年第4期26卷 384-392页

作者： Wang, Wenlu Sun, Ying Xu, Manman Bai, Dongxu Huang, Li Zou, Chunlong Chen, Baojia Tang, Dalai Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China College of Mechanical Engineering Hubei University of Automotive Technology Hubei Shiyan China Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance China Three Gorges University Hubei Yichang China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot China

In order to improve the efficiency of indoor mobile robots in locating and segmenting environmental instances, an instance segmentation method based on RTMDet is proposed. Firstly, the more powerful ConvNeXt V2 is used as the backbone network of the model, which improves the performance of the existing RTMDet model. Subsequently, NAS-FPN is used as a converged network to detect the network at any given time. Finally, AdamW is used as the model optimiser, which effectively solves the problem of excessive memory occupation when updating parameters and improves the performance of the model. The proposed method obtains the highest evaluation index in all cases. After training and testing on the Cityscapes data set, the recognition accuracy reaches 65.0%. © 2024 Inderscience Enterprises Ltd.

关键词： Statistical tests

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SHORT-TERM TRAFFIC FLOW FORECASTING USING ADAPTIVE ECHO STATE NETWORKS 10

SHORT-TERM TRAFFIC FLOW FORECASTING USING ADAPTIVE ECHO STAT...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Li, Zhouyang Wang, Weiye Li, Qing School of Automation Beijing Information Science & Technology University Beijing China Ministry of Education Key Laboratory of Modern Measurement & Control Technology Beijing China

ISBN: (纸本)9781837242672

In recent years, with the increase in vehicle volume, the traffic system has been inconvenienced. Therefore, the timeliness and accuracy of traffic flow prediction are crucial to the overall efficiency of the traffic system. Echo state network (ESN) has attracted extensive attention in the field of time series and traffic flow prediction due to its simple concept, low computational cost and simplicity. However, the traditional ESN model has certain limitations in terms of prediction accuracy and stability when facing complex and changeable traffic flow data. In order to solve this problem, this paper proposes an ESN prediction model combined with adaptive optimization. The simulated annealing algorithm is used to optimize the configuration of several important parameters of ESN, thereby improving the prediction performance and stability of the model. The experimental results show that the optimized ESN model is significantly better than the traditional ESN method in terms of prediction accuracy and stability. The monthly mean absolute percentage error (MAPE) is reduced from 10.05% to 6.6%, and the average error of each detector is reduced from 9.5% to 6.61%. This study proposes a more efficient and reliable method for short-term traffic flow prediction, which shows potential value in practical applications. © The Institution of Engineering & technology 2024.

关键词： Simulated annealing

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A Graph-Based Semi-Supervised Approach for Few-Shot Class-Incremental Modulation Classification

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China Communications 2024年第11期21卷 88-103页

作者： Zhou Xiaoyu Qi Peihan Liu Qi Ding Yuanlei Zheng Shilian Li Zan State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China The No.011 Research Center Science and Technology on Communication Information Security Control LaboratoryJiaxing 314033China

With the successive application of deep learning(DL)in classification tasks,the DL-based modulation classification method has become the preference for its state-of-the-art ***,once the DL recognition model is pre-trained with fixed classes,the pre-trained model tends to predict incorrect results when identifying incremental ***,the incremental classes are usually emergent without label information or only a few labeled samples of incremental classes can be *** this context,we propose a graphbased semi-supervised approach to address the fewshot classes-incremental(FSCI)modulation classification *** proposed method is a twostage learning method,specifically,a warm-up model is trained for classifying old classes and incremental classes,where the unlabeled samples of incremental classes are uniformly labeled with the same label to alleviate the damage of the class imbalance *** the warm-up model is regarded as a feature extractor for constructing a similar graph to connect labeled samples and unlabeled samples,and the label propagation algorithm is adopted to propagate the label information from labeled nodes to unlabeled nodes in the graph to achieve the purpose of incremental classes *** results prove that the proposed method is superior to other finetuning methods and retrain methods.

关键词： deep learning few-shot label propagation modulation classification semi-supervised learning

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Mainlobe DRFM Jamming Suppression via Blind Source Separation Using Tensor Decomposition 8

Mainlobe DRFM Jamming Suppression via Blind Source Separatio...

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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Dong, Luxin Wang, Bing Pan, Bunian Kong, Yukai Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Science and Technology on Electronic Information Control Laboratory Chengdu610036 China

ISBN: (纸本)9798350397932

This paper deals with the suppression problem of mainlobe digital radio frequency memory (DRFM) jamming especially for intra-pulse slice forwarding jamming for phased array radar. A novel mainlobe DRFM jamming suppression method resorting to blind source separation based on tensor decomposition (TD-BSS) is proposed to separate the target echo signal and jamming signal. Specifically, the received signals are reconstructed into higher-order tensor form. Further, the separating matrix optimization problem relying on tensor Canonical Polyadic (CP) decomposition principle is formulated and then solved by an enhanced line search alternating least square (ELS-ALS) algorithm. Finally, the performance of the proposed method is demonstrated through numerical simulations, showing its superior to suppress mainlobe DRFM jamming over the exiting method in terms of interrupted sampling and cyclic repeater jamming (ISCRJ) and chopping and interval (C&I) jamming. © 2023 IEEE.

关键词： Blind source separation

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RESEARCH ON AUTONOMOUS INTERVAL MAINTENANCE IN COLLABORATIVE FLIGHT OF UNMANNED AERIAL VEHICLES 10

RESEARCH ON AUTONOMOUS INTERVAL MAINTENANCE IN COLLABORATIVE...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Ling, Xing Wang, Weiye Li, Qing School of Automation Beijing Information Science & Technology University Beijing China Ministry of Education Key Laboratory of Modern Measurement & Control Technology Beijing China

ISBN: (纸本)9781837242672

This study investigates the use of the Vicsek model for maintaining autonomous intervals in the cooperative flight of unmanned aerial vehicles (UAVs). Although the Vicsek model effectively simulates group movement, it does not inherently maintain safe intervals between drones. To address this limitation, we propose an enhanced approach that incorporates a speed adaptive mechanism and a repulsive force mechanism. The speed adaptive mechanism dynamically adjusts the drone's speed based on its proximity to neighboring drones, slowing down when in close proximity and speeding up when further apart, thus preventing collisions. Additionally, the repulsive force mechanism ensures that drones maintain a safe distance from each other, even in high-density areas, thereby avoiding clustering and maintaining formation stability. Our simulation results indicate that drones equipped with these mechanisms achieve direction and speed consistency more rapidly, effectively avoid collisions in dense environments, and enhance overall movement speed and task execution efficiency. This approach provides a robust solution for autonomous interval maintenance in UAV swarms, ensuring safe and efficient collaborative operations in complex environments. The findings of this study contribute significantly to the field of UAV collaborative flight, offering practical implications for military reconnaissance, agricultural management, logistics, and disaster relief applications. © The Institution of Engineering & technology 2024.

关键词： Drones

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Optimal Formation Tracking of Second-Order Multi-Agent Systems Without Velocity Interactions 43

Optimal Formation Tracking of Second-Order Multi-Agent Syste...

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43rd Chinese control Conference, CCC 2024

作者： Cao, Xiao-Ying Yi, Jing-Wen Chai, Li Wuhan University of Science and Technology School of Information Science and Engineering Wuhan430081 China Zhejiang University State Key Laboratory of Industrial Control Technology Zhejiang310027 China

ISBN: (纸本)9789887581581

In this paper, we address the optimal formation tracking issue of second-order multi-agent systems without velocity interactions. Firstly, by employing model transformation, the formation tracking problem is converted into a consensus problem for the deviation system, and necessary and sufficient conditions to achieve the formation tracking are obtained. Then, by establishing the direct relationship among the convergence rate, control gains and the network topology, analytical expressions of optimal control gains and the fastest convergence rate are derived by using the Routh-Hurwitz criterion. Finally, the effectiveness of the proposed algorithm is verified through numerical simulations. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： control theory

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MMH-FE:AMulti-Precision and Multi-Sourced Heterogeneous Privacy-Preserving Neural Network Training Based on Functional Encryption

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Computers, Materials & Continua 2025年第3期82卷 5387-5405页

作者： Hao Li Kuan Shao Xin Wang Mufeng Wang Zhenyong Zhang The State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science CenterQilu University of Technology(Shandong Academy of Sciences)Jinan250014China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model ***,dishonest clouds may infer user data,resulting in user data *** schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing *** address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training ***,we design a multi-precision functional encryption computation based on Euclidean ***,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced ***,we conduct experiments on three *** results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.

关键词： Functional encryption multi-sourced heterogeneous data privacy preservation neural networks

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Overview of Technologies in Marine Robotics 1

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Shen, He Zeng, Jinxin Yang, Yixin School of Marine Science and Technology Northwestern Polytechnical University Shaanxi Xi’an710072 China Shaanxi Key Laboratory of Underwater Information Technology Shaanxi Xi’an710072 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Marine robotics is a fast-growing and important branch of robotics. Meanwhile, it is highly interdisciplinary and faces special challenges in the marine environment. This paper provides a systematic overview of core technologies in marine robotics. Building upon the operational "sense-think-act" paradigm, we put forward five clusters of technologies, including "sense", "think", "act", "system", and "interactions". These interconnected five clusters of technologies form a framework for readers to have a quick grasp of the technologies in marine robotics. Following this framework, special challenges and recent progress are also presented. Finally, future trends in addressing these special challenges are also brought to readers’ attention. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Robotics

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Experimental study on the effect of underwater multiple degradation links on optical signal transmission 23

Experimental study on the effect of underwater multiple degr...

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Proceedings of the 2023 6th International Conference on Artificial Intelligence and Pattern Recognition

作者： Jianlei Zhang Pengwei Zhang Yunzhou Zhu Yuxin Tian School of Electronic Engineering Xi'an University of Posts & Telecommunications China Science and Technology on Underwater Information and Control Laboratory China

ISBN: (纸本)9798400707674

This paper presents an experimental investigation of the impact of various environmental factors, including temperature, salinity, and air bubbles, on the transmission of optical signals. A reception model was established to capture the degradation of the optical signal as it passes through multiple links. The fading of optical signals passing through different channels was quantified and analyzed. The findings highlight the distinct impacts of temperature, salinity, and air bubbles on the propagation of optical signals. Additionally, the study reveals that turbulence intensity plays a pivotal role in influencing the variability of the normalized amplitude of the received signal.

关键词： Air Bubbles Ocean Turbulence underwater Wireless Optical Communication

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