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A novel method for extracting and optimizing the complex permittivity of paper-based composites based on an artificial neural network model

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Science China Technological Sciences 2024年第10期67卷 3190-3204页

作者： XIA ChenBin SHEN JunYi LIAO ShaoWei WANG Yi HUANG ZhengSheng XUE Quan TANG Min LONG Jin HU Jian School of Light Industry and Engineering South China University of Technology School of electronic and Information Engineering South China University of Technology

Measuring the complex permittivity of ultrathin, flexible materials with a high loss tangent poses a substantial challenge with precision using conventional methods, and verifying the accuracy of test results remains difficult. In this study, we introduce a methodology based on a back-propagation artificial neural network(ANN) to extract the complex permittivity of paper-based composites(PBCs). PBCs are ultrathin and flexible materials exhibiting considerable complex permittivity and dielectric loss tangent. Given the absence of mature measurement methods for PBCs and a lack of sufficient data for ANN training, a mapping relationship is initially established between the complex permittivity of honeycomb-structured microwave-absorbing materials(HMAMs, composed of PBCs) and that of PBCs using simulated data. Leveraging the ANN model, the complex permittivity of PBCs can be extracted from that of HMAMs obtained using standard measurement. Subsequently, two published methods are cited to illustrate the accuracy and advancement of the results obtained using the proposed approach. Additionally, specific error analysis is conducted, attributing discrepancies to the conductivity of PBCs, the homogenization of HMAMs, and differences between the simulation model and actual objects. Finally, the proposed method is applied to optimize the cell length parameters of HMAMs for enhanced absorption performance. The conclusion discusses further improvements and areas for extended research.

关键词： paper-based composite honeycomb complex permittivity artificial neural networks inverse modeling

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Quantum Anomalous Hall Effect with Tunable Chern Numbers in High-Temperature 1T-PrN_(2) Monolayer

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Chinese Physics Letters 2024年第5期41卷 77-84页

作者：吴绪才李树宗司君山黄博张卫兵 Hunan Provincial Key Laboratory of Flexible electronic Materials Genome Engineering School of Physics and Electronic SciencesChangsha University of Science and TechnologyChangsha 410114China

Quantum anomalous Hall(QAH) insulators have highly potential applications in spintronic device. However,available candidates with tunable Chern numbers and high working temperature are quite rare. Here, we predict a 1T-PrN_(2) monolayer as a stable QAH insulator with high magnetic transition temperature of above 600 K and tunable high Chern numbers of C = ±3 from first-principles calculations. Without spin-orbit coupling(SOC),the 1T-PrN_(2) monolayer is predicted to be a p-state Dirac half metal with high Fermi velocity. Rich topological phases depending on magnetization directions can be found when the SOC is considered. The QAH effect with periodical changes of Chern number(±1) can be produced when the magnetic moment breaks all twofold rotational symmetries in the xy plane. The critical state can be identified as Weyl half semimetals. When the magnetization direction is parallel to the z-axis, the system exhibits high Chern number QAH effect with C = ±*** work provides a new material for exploring novel QAH effect and developing high-performance topological devices.

关键词： magnetization topological monolayer

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Rapid Energy Exchange between In Situ Formed Bromine Vacancies and CO_(2)Molecules Enhances CO_(2)Photoreduction

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Research 2024年第2期2023卷 763-771页

作者： Qin Ren Ye He Hong Wang Yanjuan Sun Fan Dong Research Center for Environmental and Energy Catalysis Institute of Fundamental and Frontier SciencesUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Resources and Environment University of Electronic Science and Technology of ChinaChengdu 611731China

Photocatalytic reduction of CO_(2)into fuels provides a prospective tactic for regulating the global carbon balance utilizing renewable solar ***,CO_(2)molecules are difficult to activate and reduce due to the thermodynamic stability and chemical *** this work,we develop a novel strategy to promote the adsorption and activation of CO_(2)molecules via the rapid energy exchange between the photoinduced Br vacancies and CO_(2)*** in situ continuous wave-electron paramagnetic resonance(cw-EPR)and pulsed EPR technologies,we observe that the spin-spin relaxation time(T_(2))of BiOBr is decreased by 198 ns during the CO_(2)photoreduction reaction,which is further confirmed by the broadened EPR *** result reveals that there is an energy exchange interaction between in situ formed Br vacancies and CO_(2)molecules,which promotes the formation of high-energy CO_(2)molecules to facilitate the subsequent reduction *** addition,theoretical calculations indicate that the bended CO_(2)adsorption configuration on the surface of BiOBr with Br vacancies caused the decrease of the lowest unoccupied molecular orbital of the CO_(2)molecule,which makes it easier for CO_(2)molecules to acquire electrons and get *** situ diffuse reflectance infrared Fourier transform spectroscopy further shows that the activated CO_(2)molecules are favorably converted to key intermediates of COOH*,resulting in a CO generation rate of 9.1μmol g^(-1)h^(-1)and a selectivity of 100%.This study elucidates the underlying mechanism of CO_(2)activation at active sites and deepens the understanding of CO_(2)photoreduction reaction.

关键词： reaction. adsorption activation

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Model Predictive Control based Motion Cueing Algorithm for Driving Simulator

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Journal of Systems Science and Systems Engineering 2024年第5期33卷 607-626页

作者： Ayesha Hameed Ali Soltani Sharif Abadi Andrzej Ordys Institute of Automatic Control and Robotics Warsaw University of TechnologyWarsawPoland Institute of electronic Systems Warsaw University of TechnologyWarsawPoland

Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, research and development of new vehicles and even for entertainment purposes. Driving simulators have been developed to reduce the cost of field studies, allow more flexible control over circumstances and measurements, and safely present hazardous conditions. The major challenge in a driving simulator is to reproduce realistic motions within hardware constraints. Motion Cueing Algorithm (MCA) guarantees a realistic motion perception in the simulator. However, the complex nature of the human perception system makes MCA implementation challenging. The present research aims to improve the performance of driving simulators by proposing and implementing the MCA algorithm as a control problem. The approach is realized using an actual vehicle model integrated with a detailed model of the human vestibular system, which accurately reproduces the driver’s perception. These perception motion signals are compared with simulated ones. A 2-DOF stabilized platform model is used to test the results from the two proposed control strategies, Proportional Integrator and Derivative (PID) and Model Predictive Control (MPC).

关键词： Driving simulator motion cueing algorithm control theory model predictive control PID

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Engineering tantalum nitride for efficient photoelectrochemical water splitting

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Science China Chemistry 2024年第7期67卷 2171-2180页

作者： Beibei Zhang Zeyu Fan Yanbo Li Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China

Photoelectrochemical(PEC)water splitting is a promising energy conversion strategy for directly converting solar energy into green hydrogen *** an efficient PEC device,finding an efficient photoanode material with a suitable band gap and favorable band-edge positions is *** nitride(Ta_(3)N_(5))meets these fundamental requirements,and its theoretical maximum solar-to-hydrogen(STH)conversion efficiency can reach 15.9%.Consequently,it has been widely applied as a photoanode material for the PEC oxygen evolution reaction(OER).However,severe bulk and interface charge recombination,along with sluggish water oxygen kinetics,seriously limits its STH conversion efficiency for PEC water ***,this feature article briefly reviews recent advances by our research group in improving the STH conversion efficiency of the Ta_(3)N_(5)photoanode using various strategies,including defect engineering,construction of a gradient band structure,interface engineering,and surface modification of self-healing OER *** to now,the obtained half-cell STH efficiency has exceeded 4%,providing a solid foundation for the development of tandem PEC devices for unbiased solar-driven overall water splitting toward practical application.

关键词： Photoelectrochemical water splitting tantalum nitride defect engineering interface engineering oxygen evolution cocatalyst

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Scale effect removal and range migration correction for hypersonic target coherent detection

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Journal of Systems Engineering and electronics 2024年第1期35卷 14-23页

作者： WU Shang SUN Zhi JIANG Xingtao ZHANG Haonan DENG Jiangyun LI Xiaolong CUI Guolong School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar ***,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual ***,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration *** eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation *** to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation *** last,this paper gives several simulations to assess the viability of ScLRT.

关键词： hypersonic target detection coherent integration(CI) scale effect(SE)removal range migration(RM)correction scaled location rotation transform(ScLRT)

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DLF-YOLOF:an improved YOLOF-based surface defect detection for steel plate

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Journal of Iron and Steel Research International 2024年第2期31卷 442-451页

作者： Guang-hu Liu Mao-xiang Chu Rong-fen Gong Ze-hao Zheng School of electronic and Information Engineering University of Science and Technology LiaoningAnshan114051LiaoningChina

Surface defects can affect the quality of steel *** methods based on computer vision are currently applied to surface defect detection of steel ***,their real-time performance and object detection of small defect are still *** improved object detection network based on You Only Look One-level Feature(YOLOF)is proposed to show excellent performance in surface defect detection of steel plate,called ***,the anchor-free detector is used to reduce the network ***,deformable convolution network and local spatial attention module are introduced into the feature extraction network to increase the contextual information in the feature ***,the soft non-maximum suppression is used to improve detection accuracy ***,data augmentation is performed for small defect objects during training to improve detection *** show the average precision and average precision for small objects are 42.7%and 33.5%at a detection speed of 62 frames per second on a single GPU,*** shows that DLF-YOLOF has excellent performance to meet the needs of industrial real-time detection.

关键词： Steel surface defects detection YOLOF Anchor-free detector Small object detection Real-time detection

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Electricity Theft Detection Method Based on Ensemble Learning and Prototype Learning

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 213-224页

作者： Xinwu Sun Jiaxiang Hu Zhenyuan Zhang Di Cao Qi Huang Zhe Chen Weihao Hu the School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengduChina Southwest University of Science and TechnologyChengduChina

With the development of advanced metering infrastructure(AMI),large amounts of electricity consumption data can be collected for electricity theft ***,the imbalance of electricity consumption data is violent,which makes the training of detection model *** this case,this paper proposes an electricity theft detection method based on ensemble learning and prototype learning,which has great performance on imbalanced dataset and abnormal data with different abnormal *** this paper,convolutional neural network(CNN)and long short-term memory(LSTM)are employed to obtain abstract feature from electricity consumption *** calculating the means of the abstract feature,the prototype per class is obtained,which is used to predict the labels of unknown *** the meanwhile,through training the network by different balanced subsets of training set,the prototype is *** with some mainstream methods including CNN,random forest(RF)and so on,the proposed method has been proved to effectively deal with the electricity theft detection when abnormal data only account for 2.5%and 1.25%of normal *** results show that the proposed method outperforms other state-of-the-art methods.

关键词： Electricity theft detection ensemble learning prototype learning imbalanced dataset deep learning abnormal level

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Analyzing topics in social media for improving digital twinning based product development

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Digital Communications and Networks 2024年第2期10卷 273-281页

作者： Wenyi Tang Ling Tian Xu Zheng Ke Yan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital *** work mines real-world consumer feedbacks through social media topics,which is significant to product *** specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a *** primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset ***,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse *** this end,this work combines deep learning and survival analysis to predict the prevalent time of *** propose a specialized deep survival model which consists of two *** first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network ***,a specific loss function different from regular survival models is proposed to achieve a more reasonable *** experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

关键词： Digital twinning Product development Topic analysis Social media

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Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng Kaili.Jiang Zhixing Zhou Yuxin Zhao Kailun Tian Haixin Yan Bin Tang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic *** methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative *** paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse *** results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

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