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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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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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FEW SHOT FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON CSML 14

FEW SHOT FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON ...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2024

作者： Wu, Minghao Wu, Lifeng Information Engineering College Capital Normal University Beijing China Beijing Key Laboratory of Electronic System Reliability Technology Capital Normal University Beijing China

ISBN: (纸本)9781837242672

Currently, neural network models have seen widespread adoption in the sphere of fault diagnosis. In the training process of the model there are still problems such as high demand for training data and insufficient generalisation of the model under different working conditions. In order to solve the above problems, in this paper, an algorithm named Cosine Annealing-Sgd-Meta-Learning (CSML) is proposed, which combines the cosine annealing method with the principles of stochastic gradient descent meta-learning. The method uses the cosine annealing algorithm to adjust the learning rate in the outer loop so as to better help the meta-learning task to find the initialisation parameters. In the inner loop, the learning rate is updated using the SGD optimisation algorithm and a wide convolutional network is used to improve the model's ability to extract fault information from the meta-task under known operating conditions, and then the basic learner is updated. High diagnostic accuracy was obtained on the Western Reserve University bearing dataset, which verified its feasibility and effectiveness. © The Institution of engineering & technology 2024.

关键词： Stochastic systems

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Cascade Optimization Control of Unmanned Vehicle Path Tracking Under Harsh Driving Conditions

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Journal of Shanghai Jiaotong university(science) 2023年第1期28卷 114-125页

作者：黄迎港罗文广黄丹蓝红莉 School of Electrical and Information Engineering、Guangxi Key Laboratory of Auto Parts and Vehicle Technology Guangxi University of Science and TechnologyLiuzhou 545006GuangxiChina School of Mechanical and Automotive Engineering South China University of TechnologyGuangzhou 510641China

Under ultra-high-speed and harsh conditions,conventional control methods struggle to ensure the path tracking accuracy and driving stability of unmanned vehicles during the turning ***,this study proposes a cascade control to solve this *** on the new vehicle error model that considers vehicle tire sideslip and road curvature,the feedforward-parametric adaptive linear quadratic regulator(LQR)and proportional integral control-based speed-keeping controllers are used to compose the path-tracking cascade optimization controller for unmanned *** improve the adaptability of the unmanned vehicle path-tracking control under harsh driving conditions,the LQR controller parameters are automatically adjusted using a back-propagation neural network,in which the initial weights and thresholds are optimized using the improved grey wolf optimization algorithm according to the driving *** speed-keeping controller reduces the impact on the curve-tracking accuracy under nonlinear vehicle speed ***,a joint model of MATLAB/Simulink and CarSim was established,and simulations show that the proposed control method can achieve stable entry and exit curves at ultra-high speeds for unmanned *** strong wind and ice road conditions,the method exhibits a higher tracking accuracy and is more adaptive and robust to external interference in driving and variable curvature roads than methods such as the feedforward-LQR,preview and pure pursuit controls.

关键词： unmanned vehicles path tracking harsh driving conditions cascade control improved gray wolf optimization algorithm backpropagation neural network

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High Resolution Remote Sensing Image Segmentation Method with Improved DeepLabv3+

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Journal of Shanghai Jiaotong University (science) 2024年 1-11页

作者： Tao, Hongjie Li, Zhaofei Qi, Fei Chen, Jingjue Zhou, Hao School of Automation and Information Engineering Sichuan University of Science and Engineering Sichuan Yibin643002 China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Sichuan Yibin643002 China Chengdu Tianxun Microsatellite Technology Co. Ltd. Chengdu610200 China

In order to address the challenges associated with poor semantic segmentation results of classical semantic segmentation networks in high-resolution remote sensing images, limited performance in complex scenes, a large number of network parameters, and high training costs, this study proposes an efficient segmentation method for high-resolution remote sensing images based on an improved DeepLabv3+ approach. The method focuses on three key aspects: reducing the number of network parameters, minimizing computation volume, and enhancing performance. First, the proposed method replaces the original DeepLabv3+ backbone network Xception, which is computationally heavy, with the lighter MobileNetV2 network for feature extraction. This substitution helps reduce the number of network parameters while maintaining effective feature extraction. Second, a lightweight convolutional block attention module (CBAM) is added after the feature extraction module to enhance the network’s feature extraction capability. The inclusion of CBAM further reduces the number of network parameters. Last, coordinate attention is introduced after the shallow features obtained from the feature extraction module. This addition allows the network to focus more on relevant features in the image, while disregarding irrelevant background information. Experimental results demonstrate the effectiveness of the proposed method. In the segmentation task of the high-resolution image dataset, the method achieves a mean intersection over union (mIoU) of 75.33%. This result surpasses mainstream semantic segmentation networks such as SegNet, PSPNet, and U-Net by 12.49%, 3.16%, and 1.62% respectively. Furthermore, the proposed model has a relatively low number of network parameters, with only 6.02 × 106 parameters, and a computation volume of 26.45 GFLOPs. This balance between computational efficiency and segmentation accuracy makes the model highly valuable for edge computing applications. © Shanghai Jiao Tong Univ

关键词： Feature extraction

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Numerical Investigation of Jet Impingement Cooling with Supercritical Pressure Carbon Dioxide in a Multi-Layer Cold Plate during High Heat Flux

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Journal of Thermal science 2023年第1期32卷 237-253页

作者： WEN Yaming LI Yulong LI Jingqi YU Xin-Gang National Key Laboratory of Science and Technology on Aero Engines Aero-Thermodynamics&Collaborative Innovation Center for Advanced Aero-Engine School of Energy and Power EngineeringBeihang UniversityBeijing 100191China Beijing Institute of Spacecraft System Engineering Beijing 100094China

Jet impingement cooling with supercritical pressure carbon dioxide in a multi-layer cold plate during the heat flux of 400 W/cm_(2) is investigated *** generation and distribution of pseudocritical fluid with the high specific heat of supercritical pressure carbon dioxide and the mechanism of the heat transfer enhancement led by the high specific heat are *** a given nozzle diameter,the effects of the geometric parameters of a multi-layer cold plate such as the relative nozzle-to-plate distance,relative plate thickness,and relative upper fluid thickness on the average heat transfer coefficient are *** results show that the target surface is cooled effectively with supercritical pressure carbon dioxide jet impingement *** the radial distance is less than 6 mm,the maximum wall temperature is 368 K,which is 30 K lower than the maximum junction temperature for a silicon-based insulated gate bipolar transistor,a typical electronic power *** is a pseudocritical fluid layer near the target surface,where specific heat reaches above 34 kJ/(kg·K)*** drastic rise of the specific heat leads to obvious heat transfer *** a certain range,the local heat transfer coefficient and the specific heat are linearly correlated and Stanton number remains constant over this *** heat transfer coefficient is at a maximum when the relative nozzle-to-plate distance is *** the relative plate thickness increases from 0.5 to 3.5 or the relative upper fluid thickness increases from 0.5 to 2.5,the average heat transfer coefficient decreases monotonically.

关键词： high heat flux jet impingement cooling supercritical pressure carbon dioxide heat transfer enhancement

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Statistical Model on CRAFT

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Chinese Journal of Electronics 2022年第4期31卷 698-712页

作者： WANG Caibing GUO Hao YE Dingfeng WANG Ping State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Tianjin Aerospace Zhongwei Data System Technology Co. Ltd.

Many cryptanalytic techniques for symmetric-key primitives rely on specific statistical analysis to extract some secrete key information from a large number of known or chosen plaintext-ciphertext pairs. For example, there is a standard statistical model for differential cryptanalysis that determines the success probability and complexity of the attack given some predefined configurations of the attack. In this work, we investigate the differential attack proposed by Guo et al. at Fast Software Encryption Conference 2020 and find that in this attack, the statistical behavior of the counters for key candidates deviate from standard scenarios, where both the correct key and the correct key xor specific difference are expected to receive the largest number of votes. Based on this bimodal behavior, we give three different statistical models for truncated differential distinguisher on CRAFT(a cryptographic algorithm name) for bimodal phenomena. Then, we provide the formulas about the success probability and data complexity for different models under the condition of a fixed threshold value. Also, we verify the validity of our models for bimodal phenomena by experiments on round-reduced of the versions distinguishers on CRAFT. We find that the success probability of theory and experiment are close when we fix the data complexity and threshold value. Finally, we compare the three models using the mathematical tool Matlab and conclude that Model 3 has better performance.

关键词： standard statistical model statistical analysis secrete key information data complexity cryptanalytic techniques probability fast software encryption conference 2020 success probability differential attack plaintext-ciphertext pairs Data security bimodal phenomena Other topics in statistics symmetric-key primitives Cryptography cryptographic algorithm name cryptography CRAFT

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design 13

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Hong, Wenjing Chen, Cheng Zhu, Zexuan Tang, Ke Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350308365

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design. © 2024 IEEE.

关键词： Vaccines

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Stability of single-cavity dual-wavelength-comb fiber laser with significant difference of pulse characteristics 11

Stability of single-cavity dual-wavelength-comb fiber laser ...

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Quantum and Nonlinear Optics XI 2024

作者： Hu, Guoqing Chen, Luoyang Li, Hetian Chen, Guangwei Liao, Xiaochun Yan, Pengyu Li, Huiyu Zhang, Zhiyong Wu, Tengfei Qin, Ying Zhou, Zhehai Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science & Technology University Beijing100192 China Beijing Laboratory of Optical Fiber Sensing and System Beijing Information Science & Technology University Beijing100016 China Key Laboratory of Scattering and Radiation Beijing100854 China Changcheng Institute of Metrology & Measurement Beijing100095 China

ISBN: (纸本)9781510682207

We investigated a stable single-cavity dual-wavelength-comb fiber laser with significant difference of pulse characteristics. Switchable single/dual-wavelength pulses across 1530- and 1550-nm gain regions are obtained by adjusting the intracavity linear loss. In the dual-wavelength operation, the repetition rates fluctuate and drift in more than 145 Hz, while the standard deviation of the repetition rate difference is measured as 64 mHz in 1000-second monitoring. The passive mutual coherence between pulses is comparable or somewhat better than the reported one under the similar disturbance and monitoring condition. Meanwhile, the significant difference of dual-wavelength pulse characteristics, including spectral bandwidth, pulse energy and dispersion is observed and discussed. The qualified stability is also attributed to the significant pulse difference, which could suppress the nonlinear pulse interaction induced instability. These results provide further physical understanding of the construction of dual-wavelength-comb pulse fiber laser, showing the high potential to promote the performance improvement of dual-comb metrology such as dual-comb spectroscopy, and ranging. © 2024 SPIE. All rights reserved.

关键词： Pulse repetition rate

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Improving the ductility and toughness of nano-TiC/AZ61 composite by optimizing bimodal grain microstructure via extrusion speed

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Journal of Magnesium and Alloys 2024年第8期12卷 3264-3280页

作者： Lingling Fan Mingyang Zhou Wulve Lao Yuwenxi Zhang Hajo Dieringa Ying Zeng Yuanding Huang Gaofeng Quan Key Laboratory of Advanced Technologies of Materials Ministry of EducationChengdu 610031China School of Materials Science and Engineering Southwest Jiaotong UniversityChengdu 610031China Institute of Material and Process Design Helmholtz-Zentrum HereonGeesthacht 21502Germany Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu 610213China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China Institute of Metallic Biomaterials Helmholtz-Zentrum HereonGeesthacht 21502Germany

In this study,the nano-TiC/AZ61 composites with different heterogeneous bimodal grain(HBG)structures and uniform structure are obtained by regulating the extrusion *** effect of HBG structure on the mechanical properties of the composites is *** increasing ductility and toughening mechanism of HBG magnesium matrix composites are carefully *** the extrusion speed increases from 0.75 mm/s to 2.5 mm/s or 3.5 mm/s,the microstructure transforms from uniform to HBG *** with Uniform-0.75 mm/s composite,Heterogeneous-3.5 mm/s composite achieves a 116.7%increase in ductility in the plastic deformation stage and almost no reduction in ultimate tensile *** is mainly because the lower plastic deformation inhomogeneity and higher strain hardening due to hetero-deformation induced(HDI)***,Heterogeneous-3.5 mm/s composite achieves a 108.3%increase in toughness compared with the Uniform-0.75 mm/s *** is mainly because coarse grain(CG)bands can capture and blunt cracks,thereby increasing the energy dissipation for crack propagation and improving *** addition,the CG band of the Heterogeneous-3.5 mm/s composite with larger grain size and lower dislocation density is more conducive to obtaining higher strain hardening and superior blunting crack ***,the increased ductility and toughness of the Heterogeneous-3.5 mm/s composite is more significant than that Heterogeneous-2.5 mm/s composite.

关键词： Nano-TiC/AZ61 composite Extrusion speed Heterogeneous bimodal grain structure Increasing ductility mechanism Toughening mechanism

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