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Multi-scale persistent spatiotemporal transformer for long-term urban traffic flow prediction

Journal of electronic Science and Technology 2024年第1期22卷 53-69页

作者： Jia-Jun Zhong Yong Ma Xin-Zheng Niu Philippe Fournier-Viger Bing Wang Zu-kuan Wei School of computer Science and engineering University of Electronic Science and Technology of ChinaChengdu611731China College of computer Science&Software engineering Shenzhen UniversityShenzhen518060China School of computer Science Southwest Petroleum UniversityChengdu610500China

Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel *** improve prediction accuracy,a crucial issue is how to model spatiotemporal dependency in urban traffic *** recent years,many studies have adopted spatiotemporal neural networks to extract key information from traffic ***,most models ignore the semantic spatial similarity between long-distance areas when mining spatial *** also ignore the impact of predicted time steps on the next unpredicted time step for making long-term ***,these models lack a comprehensive data embedding process to represent complex spatiotemporal *** paper proposes a multi-scale persistent spatiotemporal transformer(MSPSTT)model to perform accurate long-term traffic flow prediction in *** adopts an encoder-decoder structure and incorporates temporal,periodic,and spatial features to fully embed urban traffic data to address these *** model consists of a spatiotemporal encoder and a spatiotemporal decoder,which rely on temporal,geospatial,and semantic space multi-head attention modules to dynamically extract temporal,geospatial,and semantic *** spatiotemporal decoder combines the context information provided by the encoder,integrates the predicted time step information,and is iteratively updated to learn the correlation between different time steps in the broader time range to improve the model’s accuracy for long-term *** on four public transportation datasets demonstrate that MSPSTT outperforms the existing models by up to 9.5%on three common metrics.

关键词： Graph neural network Multi-head attention mechanism Spatio-temporal dependency Traffic flow prediction

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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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A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles

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computers, Materials & Continua 2024年第7期80卷 567-585页

作者： Feng Zhao Hongtao Ding Chunhai Li Zhaoyu Su Guoling Liang Changsong Yang Guangxi engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China School of Information and Communication Guilin University of Electronic TechnologyGuilin541004China School of computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the ***,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain *** such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication ***,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency *** mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for *** scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree *** divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and ***,we evaluate the performance of *** results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

关键词： Blockchain cross-domain authentication internet of vehicle zero-knowledge proof

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Convolutional neural network adaptation and optimization method in SIMT computing mode

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The Journal of China Universities of Posts and Telecommunications 2024年第2期31卷 105-112页

作者： Feng Zhenfu Zhang Yaying Yang Lele Xing Lidong School of electronic engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

For studying and optimizing the performance of general-purpose computing on graphics processing units(GPGPU)based on single instruction multiple threads(SIMT)processor about the neural network application,this work contributes a self-developed SIMT processor named Pomelo and correlated assembly *** parallel mechanism of SIMT computing mode and self-developed Pomelo processor is briefly introduced.A common convolutional neural network(CNN)is built to verify the compatibility and functionality of the Pomelo *** computing flow with task level and hardware level optimization is adopted on the Pomelo processor.A specific algorithm for organizing a Z-shaped memory structure is developed,which addresses reducing memory access in mass data computing *** the above-combined adaptation and optimization strategy,the experimental result demonstrates that reducing memory access in SIMT computing mode plays a crucial role in improving performance.A 6.52 times performance is achieved on the 4 processing elements case.

关键词： parallel computing single instruction multiple threads(SIMT) convolutional neural network(CNN) memory optimization

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Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

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computers, Materials & Continua 2024年第2期78卷 1977-1993页

作者： Zhiqing Dong Zhao Zhang Hongyan Zhou Xuebo Chen School of computer Science and Software engineering University of Science and Technology LiaoningAnshan114051China School of electronic and Information engineering University of Science and Technology LiaoningAnshan114051China

With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicated on 2D compressed sensing(CS)and the hyperchaotic ***,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong ***,the processed images are con-currently encrypted and compressed using 2D *** them,chaotic sequences replace traditional random measurement matrices to increase the system’s ***,the processed images are re-encrypted using a combination of permutation and diffusion *** addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct *** with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational ***,it has better *** experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.

关键词： Image encryption image compression hyperchaotic system compressed sensing

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Decision Aid Model for Private-owned Electric Vehicles Participating in Frequency Regulation Ancillary Service Market

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 621-629页

作者： Liwei Wang Yingyun Sun Haotian Wang Pengfei Zhao Muhammad Safwan Jaffar School of Electrical and electronic engineering North China Electric Power UniversityBeijing 102206China

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles(EVs) in participating in frequency regulation ancillary service market(FRASM), a decision aid model(DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode(BM), unidirectional charging mode(UCM), and bidirectional charging/discharging mode(BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use(TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

关键词： Electric vehicle(EV) frequency regulation decision aid model(DAM) utility maximization battery wear cost

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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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Design of digital calibration based on variable step size of sub-binary SAR ADC

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The Journal of China Universities of Posts and Telecommunications 2024年第2期31卷 62-71页

作者： Liu Wei Zhao Yanke Shang Shiguang School of electronic engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size digital calibration was *** least mean square(LMS)calibration algorithm was employed with a ramp signal used as the calibration *** errors,extracted under injected disturbances,underwent iterative training to optimize weight *** address the trade-off between conversion accuracy and speed caused by a fixed step size,a novel variable step size algorithm tailored for SAR ADC calibration was *** core circuit and layout of the SAR ADC were implemented using the Taiwan Semiconductor Manufacturing Company(TSMC)0.35μm complementary metal-oxide-semiconductor(CMOS)commercial *** of the SAR ADC calibration algorithm was conducted using Simulink,demonstrating quick convergence and meeting conversion accuracy requirements compared to fixed step size *** results indicated that the convergence speed of the LMS digital calibration algorithm with variable step size was approximately eight times faster than that with a fixed step size,also yielding a lower mean square error(MSE).After calibration,the simulation results for the SAR ADC exhibited an effective number of bit(ENOB)of 11.79 bit and a signal-to-noise and distortion ratio(SNDR)of 72.72 dB,signifying a notable enhancement in the SAR ADC performance.

关键词： successive approximation register analog-to-digital converter(SAR ADC) variable step size digital calibration disturbance technique

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Sintering of phosphor-glass composites goes ultrafast

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Science China Materials 2024年第8期67卷 2711-2712页

作者： Xiaoyong Huang College of electronic Information and Optical engineering Taiyuan University of TechnologyTaiyuan 030024China

Nowadays,with the rapid technological progress of high-quality lightings and high-end displays,high-power white light-emitting diodes(WLEDs)and high-brightness white laser diodes(WLDs)featuring with high energy density excitation,high output power and high device stability have been extensively investigated and regarded as the new-generation solid-state light sources[1–6].

关键词： diodes WLED white

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