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Heterogeneous interface enhanced polyurethane/MXene@Fe_(3)O_(4)composite elastomers for electromagnetic wave absorption and thermal conduction

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International Journal of Minerals,Metallurgy and Materials 2025年第3期32卷 728-737页

作者： Xin An Zhaoxu Sun Jiahui Shen Jiajia Zheng Aixi Sun Xiping Li Shaohua Jiang Yiming Chen Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology&Equipment of Zhejiang Province College of EngineeringZhejiang Normal UniversityJinhua 321004China Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources International Innovation Center for Forest Chemicals and MaterialsCollege of Materials Science and EngineeringNanjing Forestry UniversityNanjing 210037China

The development of high-performance functional composites has become a research hotspot in response to the hazards of over-heating and electromagnetic radiation in modern electronic ***,we grew magnetic Fe_(3)O_(4)particles in situ on the MXene layer to obtain an MXene@Fe_(3)O_(4)composite with rich heterogeneous *** to the unique heterostructure and the synergistic effects of multiple electromagnetic wave absorption mechanisms,the composite achieved a minimum reflection loss of-27.14 dB and an effect-ive absorption bandwidth of 2.05 GHz at an absorption thickness of 2 ***,the MXene@Fe_(3)O_(4)composite could be encapsu-lated in thermoplastic polyurethane(TPU)via thermal *** obtained composite elastomer exhibited a strong tensile strength,and its thermal diffusivity was 113%higher than that of pure *** additional mechanical properties and thermal conduction features render this composite elastomer an advanced electromagnetic absorber to adapt to the ever-changing environment for expanding practical applications.

关键词： composite elastomer MXene electromagnetic wave absorption thermal conduction

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Specific Emitter Identification Based on ACGAN and STFT 7

Specific Emitter Identification Based on ACGAN and STFT

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7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Wang, Bin Xie, Jun Wang, Feng The 38th Research Institute Of China Electronics Technology Group Corporation China Key Laboratory Of Aperture Array And Space Application China Key Laboratory Of Intelligent Information Processing Anhui Hefei230088 China School Of Computer And Information Hefei University Of Technology Hefei230601 China

ISBN: (纸本)9798350361445

Deep learning methodologies are gaining popularity for enhancing the efficiency of Specific Emitter Identification (SEI). Nevertheless, the lack of labeled datasets continues to pose a challenge in most non-cooperative scenarios for SEI. Addressing this challenge, a framework for SEI is proposed, leveraging Short-Time Fourier Transform (STFT) in conjunction with auxiliary classifier GAN(ACGAN). The Short-Time Fourier Transform of emitters is utilized as radio-frequency fingerprint for the emitters. The input latent layer is infused with label information to steer the training process of the Generative Adversarial Network. Through semi-supervised training, shared weight updates are implemented for the classification network. Experimental results demonstrate that our model can achieve superior or competitive performances in several datasets compared with the former models. © 2024 IEEE.

关键词： Deep learning

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Enhanced photo-driven ion pump through silver nanoparticles decorated graphene oxide membranes

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Nano Research 2022年第1期15卷 612-616页

作者： Yaping Feng Haoyu Dai Yi Zhang Jianjun Chen Fengxiang Chen Lei Jiang CAS Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology Engineering Research Center oj BeijingBeijing University of TechnologyBeijing 100124China Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China

Biology systems harvest solar energy to regulate ions and molecules precisely across cell membrane that is essential to maintain their life ***,artificial light-driven directional ion transport through graphene oxide membranes has been established,where the membrane converts light power into a transmembrane motive ***,we report a silver nanoparticles decorated graphene oxide membranes for enhanced photo-driven ionic *** light stimulated charge carrier dynamics,such as advanced light absorption efficiency,extended lifetime and efficient separation of photo-excited charge carriers,are account for the ion-driven force *** on metal nanoparticles decoration,the concept of the guest-interactions of plasmon-enhanced photo-driven ion transport in two-dimentional layered membranes will stimulate broad researches in sensing,energy storage and conversion and water treatment.

关键词： ion pump silver nanoparticles nanofluidics photocurrent

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Impedance Ice Sensor Capable of Self-Componsating Temperature Drift 16

Impedance Ice Sensor Capable of Self-Componsating Temperatur...

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16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023

作者： Gui, Kang Bai, Hongfei Liu, Ziyu Ge, Junfeng Ye, Lin School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Huazhong University of Science and Technology National Key Laboratory of Multispectral Information Intelligent Processing Technology Wuhan China

ISBN: (纸本)9798350327144

In order to further support the development of arrayed impedance-based icing detection technology, a temperature drift self-compensation method that does not depend on traditional temperature sensors is proposed for the ice thickness measurement error problem caused by temperature variation. The method achieves compensation by establishing a mapping relationship between relaxation time and temperature to calculate the temperature of the ice layer. A theoretical model to describe the temperature drift characteristics of complex dielectric constant based on the relaxation polarization principle is established, and the ice layer temperature calculation method is proposed on the basis of complex impedance measurement. The experimental results show that the method reduces the error of ice thickness measurement, and the root mean square error reaches 0.09 mm in ice cases below 4 mm, which is clearly better than the uncompensated results. © 2023 IEEE.

关键词： Thickness measurement

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High-Throughput and Energy-Efficient FPGA-Based Accelerator for All Adder Neural Networks

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IEEE Internet of Things Journal 2025年第12期12卷 20357-20376页

作者： Zhang, Ning Ni, Shuo Chen, Liang Wang, Tong Chen, He Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing100081 China

Neural networks have been extensively applied across various Internet of Things (IoT) applications, such as drone-and satellite-based remote sensing and autonomous driving. With the increasing resolution and amount of data captured by sensors, the demand for real-time response in IoT applications is markedly increasing. However, it is difficult for existing convolutional neural network (CNN) accelerators for IoT applications on field-programmable gate array (FPGA) platforms to achieve high throughput because of the inherent dense multiplication operations of CNNs, memory bandwidth limitations and inefficient mapping mechanisms. In this article, a high-throughput and energy-efficient all adder neural network (ANN) accelerator for IoT applications on FPGA platform is proposed to solve this problem. First, a series of hardware-oriented algorithm optimization methods are proposed to simplify the processing flow of ANN and further minimize its deployment overhead. Second, a novel hardware architecture based on the idea of near-memory computation (NMC) is proposed to eliminate off-chip memory access completely and accelerate the reconstructed ANN in the pipeline. Third, a set of quantitative analysis methods for the proposed accelerator is presented to balance throughput and energy consumption, allowing the accelerator to adapt to the varying demands of different IoT application scenarios. Extensive experimental results on the AMD-Xilinx VC709 board demonstrate that the proposed accelerator achieves state-of-the-art performance in terms of throughput, energy efficiency, and throughput efficiency. Moreover, experiments on the AMD-Xilinx KV260 board highlight the architecture's exceptional scalability and energy efficiency, enabling a balance between speed and power consumption tailored to the specific requirements of IoT application scenarios. © 2014 IEEE.

关键词： Convolutional neural networks

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Linear Extended State Observer-based Sliding Mode Control of Active Magnetic Bearing Systems 41

Linear Extended State Observer-based Sliding Mode Control of...

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第41届中国控制会议

作者： Ziheng Yu Yifeng Tang Bowen Xu Xiang Huang Hai-Tao Zhang School of Artificial Intelligence and Automation the Key Laboratory of Image Processing and Intelligent Controland the State Key Lab of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the last decades,as a typical nonlinear system,active magnetic bearings(AMB) system has been widely applied in manufacturing systems.A sliding mode control(SMC) scheme for the AMB system is proposed with the disturbance observation of the linear extended state observer(LESO) in this *** chattering of the AMB system has been reduced by LESO-SMC by at least 60%.Sufficient BIBO(bounded input-bounded output) stability conditions of the closed-loop AMB system governed by the proposed LESO-SMC are derived by Lyapunov ***,experiments are conducted to verify the effectiveness and superiority of the proposed LESO-SMC than conventional SMC.

关键词： Active magnetic bearing systems state observer sliding mode control chattering

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A Fast Clustering Based Evolutionary Algorithm for Super-Large-Scale Sparse Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 1048-1063页

作者： Ye Tian Yuandong Feng Xingyi Zhang Changyin Sun Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China School of Computer Science and Technology Anhui UniversityHefei 230601China School of Artificial Intelligence Anhui UniversityHefei 230601China School of Automation Southeast UniversityNanjing 210096China

During the last three decades,evolutionary algorithms(EAs)have shown superiority in solving complex optimization problems,especially those with multiple objectives and non-differentiable ***,due to the stochastic search strategies,the performance of most EAs deteriorates drastically when handling a large number of decision *** tackle the curse of dimensionality,this work proposes an efficient EA for solving super-large-scale multi-objective optimization problems with sparse optimal *** proposed algorithm estimates the sparse distribution of optimal solutions by optimizing a binary vector for each solution,and provides a fast clustering method to highly reduce the dimensionality of the search *** importantly,all the operations related to the decision variables only contain several matrix calculations,which can be directly accelerated by *** existing EAs are capable of handling fewer than 10000 real variables,the proposed algorithm is verified to be effective in handling 1000000 real ***,since the proposed algorithm handles the large number of variables via accelerated matrix calculations,its runtime can be reduced to less than 10%of the runtime of existing EAs.

关键词： Evolutionary computation fast clustering sparse multi-objective optimization super-large-scale optimization

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Extending generalized unsupervised manifold alignment

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Science China(Information Sciences) 2022年第7期65卷 139-156页

作者： Xiaoyi YIN Zhen CUI Hong CHANG Bingpeng MA Shiguang SHAN Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences School of Computer Science and Engineering Nanjing University of Science and Technology CAS Center for Excellence in Brain Science and Intelligence Technology

Building connections between different data sets is a fundamental task in machine learning and related application community. With proper manifold alignment, the correspondences between data sets will assist us with comprehensive study of data processes and analyses. Despite the several progresses in semi-supervised and unsupervised scenarios, potent manifold alignment methods in generalized and realistic circumstances remain in absence. Besides, theretofore unsupervised algorithms seldom prove themselves mathematically. In this paper, we devise an efficient method to properly solve the unsupervised manifold alignment problem and denominate it as extending generalized unsupervised manifold alignment(EGUMA)method. More specifically, an explicit relaxed integer programming method is adopted to solve the unsupervised manifold alignment problem, which reconciles three factors covering the updated local structure matching, the the feature comparability and geometric preservation. An additional effort is retained on extending the Frank Wolfe algorithm to tacking our optimization problem. Besides our previous endeavors we adopt a new strategy for neighborhood discovery in the manifolds. The main advantages over previous methods accommodate(1) simultaneous alignment and discovery of manifolds;(2) complete unsupervised learning structure without any prerequisite correspondence;(3) more concise local geometry for the embedding space;(4) efficient alternative optimization;(5) strict mathematical analysis on the convergence and efficiency issues. Experiments on real-world applications verify the high accuracy and efficiency of our proposed method.

关键词： unsupervised manifold alignment relaxed integer programming Frank Wolfe algorithm

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Resolving the sintering conundrum of high-rhenium tungsten alloys

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Journal of Materials Science & technology 2023年第35期166卷 78-85页

作者： Zhongyou Que Xingyu Li Lin Zhang Xuanhui Qu Zichen Wei Chenguang Guo Haishen Sun Mingli Qin Gang Chen Peinan Du Yanhao Dong Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China Science and Technology on Reactor Fuel and Materials Laboratory Nuclear Power Institute of ChinaChengdu 610213China State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

Tungsten-rhenium(W-Re)alloys with high-Re contents are the preferred refractory metal materials in many applications because of the improved ductility and processability over pure W and low-Re tung-sten ***,the sintering concurrently becomes increasingly more difficult with increasing Re *** we proposed that the sintering conundrum is caused by the lowered crystal symmetry and the wider dihedral angle distribution when body-center-cubic(BCC)W is alloyed with more hexagonal-close-packed(HCP)Re,which results in inefficient pore removal in the final stage *** showed that the conundrum can be resolved by pressureless two-step sintering(TSS)which suppresses acceler-ating final-stage grain growth,and our proposal is supported by the data of the critical densityρc that is required to start the second step for successful TSS at different W-Re *** ultrafine-grained W-Re alloys with∼300 nm average grain size and up to 25 wt%Re were successfully *** work demonstrates the unique opportunities offered by two-step sintering to advance the scientific understanding and technological practices in powder metallurgy and related fields.

关键词： W-Re alloys Two-step sintering Grain growth Ultrafine-grained materials

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Distributed Equally Surrounding Control for Multiple Unmanned Surface Vessels 41

Distributed Equally Surrounding Control for Multiple Unmanne...

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第41届中国控制会议

作者： Fu-Long Hu Chuan-Cong Tang Bin-Bin Hu Bowen Xu Hai-Tao Zhang School of Artificial Intelligence and Automation the Key Laboratory of Image Processing and Intelligent Controland the State Key Lab of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper proposes a distributed controller to equally surround a static target with multiple unmanned surface vessels(USVs).By utilizing the mutually repulsive method,the proposed controller addresses the equally surrounding problem,taking into account the influence of time-varying topologies,and the total number USVs which is a 'global information is not used in the *** asymptotic convergence of the closed-loop multi-USV system is guaranteed with rigorous ***,the effectiveness of the controller is verified by numerical simulations.

关键词： Equally surrounding unmanned surface vessels(USVs) multi-agent system

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