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Ag-integrated mixed metallic Co-Fe-Ni-Mn hydroxide composite as advanced electrode for high-performance hybrid supercapacitors

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Journal of Energy Chemistry 2024年第1期88卷 579-591,I0013页

作者： Anki Reddy Mule Bhimanaboina Ramulu Shaik Junied Arbaz Anand Kurakula Jae Su Yu department of electronics and information Convergence Engineering Institute for Wearable Convergence ElectronicsKyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea

Direct growth of redox-active noble metals and rational design of multifunctional electrochemical active materials play crucial roles in developing novel electrode materials for energy storage *** this regard,silver(Ag)has attracted great attention in the design of efficient *** by the house/building process,which means electing the right land,it lays a strong foundation and building essential columns for a complex ***,we report the construction of multifaceted heterostructure cobalt-iron hydroxide(CFOH)nanowires(NWs)@nickel cobalt manganese hydroxides and/or hydrate(NCMOH)nanosheets(NSs)on the Ag-deposited nickel foam and carbon cloth(i.e.,Ag/NF and Ag/CC)***,the formation and charge storage mechanism of Ag are described,and these contribute to good conductive and redox chemistry *** switching architectural integrity of metal and redox materials on metallic frames may significantly boost charge storage and rate performance with noticeable drop in *** as-fabricated Ag@CFOH@NCMOH/NF electrode delivered superior areal capacity value of 2081.9μA h cm^(-2)at 5 mA cm^(-2).Moreover,as-assembled hybrid cell based on NF(HC/NF)device exhibited remarkable areal capacity value of 1.82 mA h cm^(-2)at 5 mA cm^(-2)with excellent rate capability of 74.77%even at 70 mA cm^(-2)Furthermore,HC/NF device achieved maximum energy and power densities of 1.39 mW h cm^(-2)and 42.35 mW cm^(-2),*** verify practical applicability,both devices were also tested to serve as a self-charging station for various portable electronic devices.

关键词： Current collectors Redox-active silver Transition metal-hydroxides Electrochemical performance Hybrid supercapacitor

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

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Chinese Physics B 2024年第5期33卷 306-314页

作者：丁大为牛炎张红伟杨宗立王金王威王谋媛 School of electronics and information Engineering Anhui UniversityHefei 230601China

This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network(FRHNN),utilizing memristors for emulating neural *** study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams,Lyapunov exponents(LEs),and bifurcation ***,the parameter related firing behaviors are described through two-parameter bifurcation ***,local attraction basins reveal multi-stability phenomena related to initial ***,the proposed model is implemented on a microcomputer-based ARM platform,and the experimental results correspond to the numerical ***,the article explores the application of digital watermarking for medical images,illustrating its features of excellent imperceptibility,extensive key space,and robustness against attacks including noise and cropping.

关键词： fractional order memristors Rulkov neuron medical image watermarking

Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

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Chinese Journal of Aeronautics 2024年第1期37卷 287-299页

作者： Yu ZHANG Fanghui HUANG Xinyang DENG Mingda LI Wen JIANG School of electronics and information Northwestern Polytechnical UniversityXi’an 710129China

Recognizing target intent is crucial for making decisions on the ***,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition *** with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)*** target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain ***,the HIR model is utilized to recognize intent for a tested sample from uncertain ***,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested *** retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample *** simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

关键词： Causal effect analysis Hybrid intention recognition Intervention retrieval Target intention Uncertainty reasoning

Loyal wingman task execution for future aerial combat:A hierarchical prior-based reinforcement learning approach

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Chinese Journal of Aeronautics 2024年第5期37卷 462-481页

作者： Jiandong ZHANG Dinghan WANG Qiming YANG Zhuoyong SHI Longmeng JI Guoqing SHI Yong WU School of electronics and information Northwestern Polytechnical UniversityXi’an 710129China

In modern Beyond-Visual-Range(BVR)aerial combat,unmanned loyal wingmen are pivotal,yet their autonomous capabilities are *** study introduces an advanced control algorithm based on hierarchical reinforcement learning to enhance these capabilities for critical missions like target search,positioning,and relay *** on a dual-layer model,the algorithm’s lower layer manages basic aircraft maneuvers for optimal flight,while the upper layer processes battlefield dynamics,issuing precise navigational *** approach enables accurate navigation and effective reconnaissance for lead ***,our Hierarchical Prior-augmented Proximal Policy Optimization(HPE-PPO)algorithm employs a prior-based training,prior-free execution method,accelerating target positioning training and ensuring robust target *** paper also improves missile relay guidance and promotes the effective *** integrating this system with a human-piloted lead aircraft,this paper proposes a potent solution for cooperative aerial *** experiments demonstrate enhanced survivability and efficiency of loyal wingmen,marking a significant contribution to Unmanned Aerial Vehicles(UAV)formation control *** advancement is poised to drive substantial interest and progress in the related technological fields.

关键词： Beyond-visual-range Loyal wingmen Hierarchical prior-augmented proximal policy optimization Unmanned aerial vehicles Warfare

A novel Bayesian-based INS/GNSS integrated positioning method with both adaptability and robustness in urban environments

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Chinese Journal of Aeronautics 2024年第6期37卷 205-218页

作者： Zhe YANG Hongbo ZHAO School of electronics and information Engineering Beihang UniversityBeijing 100191China

Achieving higher accuracy positioning results in urban environments at a lower cost has been an important pursuit in areas such as autonomous driving and intelligent *** Inertial Navigation System and Global Navigation Satellite System(INS/GNSS)integrated navigation systems have been an important means of fulfilling the above quest due to the complementary error characteristics between INS and *** complex urban driving environment requires the system sufficiently adaptive to keep up with the time-varying measurement noise and sufficiently robust to cope with measurement outliers and prior ***,many efforts lack a balance between adaptability and *** this paper,a novel positioning method with both adaptability and robustness is proposed by coupling the Mahalanobis distance method,the Variational Bayesian method and the student’s t-distribution in one process(M-VBt method).This method is robust against non-Gaussian noise and priori uncertainties,plus adaptive against measurement noise uncertainty and time-varying *** field test results show that the M-VBt method(especially the Mahalanobis distance part)has significantly improved the system performance in the complex urban driving environment.

关键词： Urban environments Mahalanobis distance Adaptability Robustness Integrated navigation

Product quality prediction based on RBF optimized by firefly algorithm

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Journal of Systems Engineering and electronics 2024年第1期35卷 105-117页

作者： HAN Huihui WANG Jian CHEN Sen YAN Manting College of electronics and information Engineering Tongji UniversityShanghai 201804China

With the development of information technology,a large number of product quality data in the entire manufacturing process is accumulated,but it is not explored and used *** traditional product quality prediction models have many disadvantages,such as high complexity and low *** overcome the above problems,we propose an optimized data equalization method to pre-process dataset and design a simple but effective product quality prediction model:radial basis function model optimized by the firefly algorithm with Levy flight mechanism(RBFFALM).First,the new data equalization method is introduced to pre-process the dataset,which reduces the dimension of the data,removes redundant features,and improves the data *** the RBFFALFM is used to predict product *** expe riments conducted on real-world product quality datasets validate that the new model RBFFALFM combining with the new data pre-processing method outperforms other previous me thods on predicting product quality.

关键词： product quality prediction data pre-processing radial basis function swarm intelligence optimization algorithm

Client selection and resource scheduling in reliable federated learning for UA V-assisted vehicular networks

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Chinese Journal of Aeronautics 2024年第9期37卷 328-346页

作者： Hongbo ZHAO Liwei GENG Wenquan FENG ChangmingZHOU School of electronics and information Engineering Beihang UniversityBeijing 100191China

Federated Learning(FL),a promising deep learning paradigm extensively deployed in Vehicular Edge Computing Networks(VECN),allows a distributed approach to train datasets of nodes locally,e.g.,for mobile vehicles,and exchanges model parameters to obtain an accurate model without raw data ***,the existence of malicious vehicular nodes as well as the inherent heterogeneity of the vehicles hinders the attainment of accurate ***,the local model training and model parameter transmission during FL exert a notable energy burden on vehicles constrained in *** view of this,we investigate FL client selection and resource management problems in FL-enabled UAV-assisted Vehicular Networks(FLVN).We first devise a novel reputation-based client selection mechanism by integrating both data quality and computation capability metrics to enlist reliable high-performance ***,to fortify the FL reliability,we adopt the consortium blockchain to oversee the reputation informa-tion,which boasts tamper-proof and interference-resistant ***,we formulate the resource scheduling problem by jointly optimizing the computation capability,the transmission power,and the number of local training rounds,aiming to minimize the cost of clients while guaranteeing *** this end,we propose a reinforcement learning algorithm employing an asynchronous parallel network structure to achieve an optimized scheduling *** results show that our proposed client selection mechanism and scheduling algorithm can realize reliable FL with an accuracy of 0.96 and consistently outperform the baselines in terms of delay and energy consumption.

关键词： Federated learning Vehicular edge computing Resource management Reinforcement learning Optimization techniques

A whole-net cooperative positioning method based on CDGNSS and inter-vehicle ranging

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Chinese Journal of Aeronautics 2024年第2期37卷 401-416页

作者： Shan HU Hongbo ZHAO Chen ZHUANG School of electronics and information Engineering Beihang UniversityBeijing 100191China

Relative positioning is recognized as an important issue for vehicles in urban ***-vehicle Cooperative Positioning(CP)techniques which fuse the Global Navigation Satellite System(GNSS)and inter-vehicle ranging have attracted attention in improving the performance of baseline estimation between ***,current CP methods estimate the baselines separately and ignore the interactions among the positioning information of different *** interactions are called’information coupling’.In this work,we propose a new multivehicle precise CP framework using the coupled information in the network based on the Carrier Differential GNSS(CDGNSS)and inter-vehicle *** demonstrate the benefit of the coupled information by deriving the Cramer-Rao Lower Bound(CRLB)of the float estimation in *** fully use this coupled information,we propose a Whole-Net CP(WN-CP)method which consists of the Whole-Net Extended Kalman Filter(WN-EKF)as the float estimation filter,and the Partial Baseline Fixing(PBF)as the ambiguity resolution *** WN-EKF fuses the measurements of all baselines simultaneously to improve the performance of float estimation,and the PBF strategy fixes the ambiguities of the one baseline to be estimated,instead of full ambiguity resolution,to reduce the computation load of ambiguity *** tests involving four vehicles were conducted in urban *** results show that the proposed WN-CP method can achieve better performance and meanwhile maintain a low computation load compared to the existing methods.

关键词： GNSS Cooperative positioning Baseline Ambiguity resolution information coupling

Long Short-Term Memory Spiking Neural Networks for Classification of Snoring and Non-snoring Sound Events

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Chinese Journal of electronics 2024年第3期33卷 793-802页

作者： Rulin ZHANG Ruixue LI Jiakai LIANG Keqiang YUE Wenjun LI Yilin LI electronics and information College Hangzhou Dianzi University

Snoring is a widespread occurrence that impacts human sleep *** is also one of the earliest symptoms of many sleep *** is accurately detected,making further screening and diagnosis of sleep problems *** is frequently ignored because of its underrated and costly detection *** a result,this research offered an alternative method for snoring detection based on a long short-term memory based spiking neural network(LSTM-SNN) that is appropriate for large-scale home detection for *** designed acquisition equipment to collect the sleep recordings of 54 subjects and constructed the sleep sound database in the home *** Mel frequency cepstral coefficients(MFCCs) were extracted from these sound signals and encoded into spike trains by a threshold encoding *** were classified automatically as non-snoring or snoring sounds by our LSTM-SNN *** used the backpropagation algorithm based on an alternative gradient in the LSTM-SNN to complete the parameter *** categorization percentage reached an impressive 93.4%,accompanied by a remarkable 36.9% reduction in computer power compared to the regular LSTM model.

关键词： Costs Databases Computational modeling Backpropagation algorithms Sleep apnea Encoding Recording