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Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection

Big Data Mining and Analytics 2024年第1期7卷 1-11页

作者： Rong Pang Yan Yang Aiguo Huang Yan Liu Peng Zhang Guangwu Tang School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China China Merchants Chongqing Road Engineering Inspection Center Co. Ltd.Chongqing 400067China State Key Laboratory of Bridge Engineering Structural Dynamics Chongqing 400067China

Although the Faster Region-based Convolutional Neural Network(Faster R-CNN)model has obvious advantages in defect recognition,it still cannot overcome challenging problems,such as time-consuming,small targets,irregular shapes,and strong noise interference in bridge defect *** deal with these issues,this paper proposes a novel Multi-scale Feature Fusion(MFF)model for bridge appearance disease ***,the Faster R-CNN model adopts Region Of Interest(ROl)pooling,which omits the edge information of the target area,resulting in some missed detections and inaccuracies in both detecting and localizing bridge ***,this paper proposes an MFF based on regional feature Aggregation(MFF-A),which reduces the missed detection rate of bridge defect detection and improves the positioning accuracy of the target ***,the Faster R-CNN model is insensitive to small targets,irregular shapes,and strong noises in bridge defect detection,which results in a long training time and low recognition ***,a novel Lightweight MFF(namely MFF-L)model for bridge appearance defect detection using a lightweight network EfficientNetV2 and a feature pyramid network is proposed,which fuses multi-scale features to shorten the training speed and improve recognition ***,the effectiveness of the proposed method is evaluated on the bridge disease dataset and public computational fluid dynamic dataset.

关键词： defect detection Multi-scale Feature Fusion(MFF) Region Of Interest(ROl)alignment lightweight network

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Design and performance study of a dielectric-filled cavity beam current monitor for HUST-PTF

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Nuclear Science and Techniques 2023年第8期34卷 75-85页

作者： Ji-Qing Li Kuan-Jun Fan Zheng-Zheng Liu Jian Wang Qu-Shan Chen Jin-Feng Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074China The Institute of Scientific and Industrial Research Osaka University8-1 MihogaokaIbarakiOsaka 567-0047Japan

To guarantee the exact proton dose applied to patients and ensure treatment safety while disrupting and destroying tumor cells,it is essential to accurately monitor the proton beam current in real time during patient *** clinical treatment requires a proton beam current in the∼nA range,nondestructive beam current monitors(BCMs)are preferred to minimize the degradation of beam ***,this poses significant challenges in accurately monitoring such extremely low beam *** study proposes a cavity-type BCM equipped with a dielectric plate to reduce its dimensions and achieve sufficient measurement sensitivity for practical requirements.A prototype cavity BCM was fabricated,and off-line testing was performed using a metal wire to simulate the beam to study its *** the simulation and experi-mental results showed that the cavity BCM could measure ultralow proton beam currents with a resolution up to 0.03 nA.

关键词： Proton therapy Beam current Cavity BCM Nondestructive

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Numerical analysis of the performance of a three-bladed vertical-axis turbine with active pitch control using a coupled unsteady Reynolds-averaged Navier-Stokes and actuator line model

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Journal of Hydrodynamics 2023年第3期35卷 516-532页

作者： Rui-wen Zhao Angus C.W.Creech Ye Li Vengatesan Venugopal Alistair G.L.Borthwick Laboratory of Multi-function Towing Tank State Key Laboratory of Ocean EngineeringSchool of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Engineering and Physical Sciences Heriot-Watt UniversityEdinburghUK School of Engineering The University of EdinburghEdinburghUK School of Engineering Computing and MathematicsUniversity of PlymouthPlymouthUK

In this paper,we present a numerical model of a vertical-axis turbine(VAT)with active-pitch torque *** model is based upon the Wind and Tidal Turbine Embedded Simulator(WATTES)and WATTES-V turbine realisations in conjunction with the actuator line method(ALM),and uses OpenFOAM to solve the unsteady Reynolds-averaged Navier-Stokes(URANS)equations with two-equation k-εturbulence *** novel pitch-controlled system is based on an even pressure drop across the entire rotor to mitigate against dynamic stall at low tip speed *** numerical model is validated against experimental measurements and alternative numerical predictions of the hydrodynamic performance of a 1:6 scale UNH-RM2 hydrokinetic *** deploying the variable pitch mechanism exhibit improved turbine performance compared to measured data and fixed zero-pitch model ***-wake characteristics are investigated by examining the vorticity distribution near the *** pitch-controlled system is demonstrated to theoretically decrease turbulence generated by turbine rotations,mitigate the intensity of vortex shedding and size of detached vortices,and significantly enhance the performance of a vertical-axis hydrokinetic turbine for rated tip-speed ratios.

关键词： Vertical-axis turbine pitch control hydrodynamic performance unsteady Reynolds-averaged Navier-Stokes(URANS) numerical simulation

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Accelerating the cryo-EM structure determination in RELION on GPU cluster

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Frontiers of Computer Science 2022年第3期16卷 21-39页

作者： Xin YOU Hailong YANG Zhongzhi LUAN Depei QIAN Sino-German Joint Software Institute School of Computer Science and EngineeringBeihang UniversityBeijing 100191China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125

The cryo-electron microscopy(cryo-EM)is one of the most powerful technologies available today for structural *** RELION(Regularized Likelihood Optimization)implements a Bayesian algorithm for cryo-EM structure determination,which is one of the most widely used software in this *** researchers have devoted effort to improve the performance of RELION to satisfy the analysis for the ever-increasing volume of *** this paper,we focus on performance analysis of the most time-consuming computation steps in RELION and identify their performance bottlenecks for specific *** propose several performance optimization strategies to improve the overall performance of RELION,including optimization of expectation step,parallelization of maximization step,accelerating the computation of symmetries,and memory affinity *** experiment results show that our proposed optimizations achieve significant speedups of RELION across representative *** addition,we perform roofline model analysis to understand the effectiveness of our optimizations.

关键词： cryo-EM structure determination performance optimization GPU acceleration RELION

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Diverse nucleotide substitutions in rice base editing mediated by novel TadA variants

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Plant Communications 2024年第8期5卷 104-112页

作者： Man Yu Yongjie Kuang Chenyang Wang Xuemei Wu Shaofang Li Dawei Zhang Wenxian Sun Xueping Zhou Bin Ren Huanbin Zhou State Key Laboratory for Biology of Plant Diseases and Insect Pests Institute of Plant ProtectionChinese Academy of Agricultural SciencesBeijing 100193China Department of Plant Pathology China Agricultural UniversityBeijing 100193China Scientific Observing and Experimental Station of Crop Pests in Guilin Ministry of Agriculture and Rural AffairsGuilin 541399China Ministry of Education Key Laboratory for Bio-Resource and Eco-Environment College of Life ScienceState Key Laboratory of Hydraulics and Mountain River EngineeringSichuan UniversityChengdu 610064China State Key Laboratory of Vegetable Biobreeding National Engineering Research Center for VegetablesBeijing Vegetable Research CenterBeijing Academy of Agriculture and Forestry ScienceBeijing 100097China State Key Laboratory of Rice Biology Institute of BiotechnologyZhejiang UniversityHangzhou 310058China Key Laboratory of Gene Editing Technologies(Hainan) Ministry of Agricultural and Rural AffairsSanya 572024China

CRISPR-mediated base editors have been widely used to correct defective alleles and create novel alleles by artificial evolution for the rapid genetic improvement of *** editing capabilities of base editors strictly rely on the performance of various nucleotide modification *** with the welldeveloped adenine base editors(ABEs),cytosine base editors(CBEs)and dual base editors suffer from unstable editing efficiency and patterns at different genomic loci in rice,significantly limiting their ***,we comprehensively examined the base editing activities of multiple evolved TadA8e variants in *** found that both TadA-CDd and TadA-E27R/N46L achieved more robust C-to-T editing than previously reported hyperactive hAID*D,and TadA-CDd outperformed TadA-E27R/N46L.A C-to-G base editor(CGBE)engineered with TadA-CDd and OsUNG performed highly efficient C-to-G editing in rice compared with that of *** addition,a dual base editor constructed with a single protein,TadDE,enabled simultaneous,highly efficient C-to-T and A-to-G editing in ***,our results demonstrate that TadA8e derivatives improve both CBEs and dual base editors in rice,providing a powerful way to induce diverse nucleotide substitutions for plant genome editing.

关键词： CRISPR TadA variants cytosine base editing dual base editor rice

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Disentangling Ensemble Models on Adversarial Generalization in Image Classification 5

Disentangling Ensemble Models on Adversarial Generalization ...

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5th International Conference on Electronic engineering and Informatics, EEI 2023

作者： Li, Chenwei Pan, Mengyuan Yang, Bo Zhang, Hengwei Henan Key Laboratory of Information Security State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Guizhou University School of Chemistry and Chemical Engineering Guiyang China

ISBN: (纸本)9798350327076

Convolutional neural networks are widely used in computer vision and image processing. However, when the original input is added with manually imperceptible perturbations, these deep network models mostly tend to output incorrect predictions. The vulnerability of these models poses great threat to intelligent applications, and these manually imperceptible perturbations are called adversarial examples. Current baseline methods have achieved considerable white-box attack success rate, but black-box rate remains to be improved. To boost the adversarial generalization, ensemble models method is introduced to the process of generating adversarial examples. This paper proposes multiple ensemble strategies with baseline attack methods based on existing ensemble strategy used by former methods. Experiment on ImageNet dataset empirically verifies the optimal ensemble strategy on boosting adversarial generalization. © 2023 IEEE.

关键词： Image classification

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An Opposition-Based Learning Adaptive Chaotic Particle Swarm Optimization Algorithm

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Journal of Bionic engineering 2024年第6期21卷 3076-3097页

作者： Chongyang Jiao Kunjie Yu Qinglei Zhou State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering UniversityZhengzhou450001China Henan Information Engineering School Zhengzhou Vocational College of Industrial SafetyZhengzhou450000China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou450001China

To solve the shortcomings of Particle Swarm Optimization(PSO)algorithm,local optimization and slow convergence,an Opposition-based Learning Adaptive Chaotic PSO(LCPSO)algorithm was *** chaotic elite opposition-based learning process was applied to initialize the entire population,which enhanced the quality of the initial individuals and the population diversity,made the initial individuals distribute in the better quality areas,and accelerated the search efficiency of the *** inertia weights were adaptively customized during evolution in the light of the degree of premature convergence to balance the local and global search abilities of the algorithm,and the reverse search strategy was introduced to increase the chances of the algorithm escaping the local *** LCPSO algorithm is contrasted to other intelligent algorithms on 10 benchmark test functions with different characteristics,and the simulation experiments display that the proposed algorithm is superior to other intelligence algorithms in the global search ability,search accuracy and convergence *** addition,the robustness and effectiveness of the proposed algorithm are also verified by the simulation results of engineering design problems.

关键词： PSO Opposition-based learning Chaotic motion Inertia weight Intelligent algorithm

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Modeling time-dependent mechanical behavior of hard rock considering excavation-induced damage and complex 3D stress states

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Journal of Rock Mechanics and Geotechnical engineering 2024年第10期16卷 4046-4065页

作者： Peiyang Yu Xiuli Ding Peng-Zhi Pan Shuting Miao Zhaofeng Wang Shuling Huang Key Laboratory of Geotechnical Mechanics and Engineering of the Ministry of Water Resources Yangtze River Scientific Research InstituteWuhan430010China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China University of Chinese Academy of Sciences Beijing100049China Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences PotsdamGermany

To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is *** model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength *** proposed model is implemented in a self-developed numerical code,*** reliability of the model is validated through *** is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced *** time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the ***,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.

关键词： Hard rock Excavation damage Complex stress state Three-dimensional(3D)time-dependent model

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A Review of Few-Shot Network Traffic Classification Based on Deep Learning

A Review of Few-Shot Network Traffic Classification Based on...

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2023 International Conference on Mechatronics and Intelligent Control, ICMIC 2023

作者： Yang, Kai Wang, Ruo Nan Meng, Qi Meng, Long Qi, Zan Li, Xue Fei, Jin Long State Key Laboratory of Mathematical Engineering And Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (纸本)9781510668393

At present, deep learning has achieved excellent performance in the field of network traffic classification. However, deep learning relies on massive data-driven classification models. When the data set is small, it is usually hindered. In order to solve this problem, few-shot network traffic classification technology based on deep learning has been gradually studied. In this paper, we conducted a comprehensive survey to fully understand the few-shot traffic classification techniques. We first define the few-shot traffic classification problem. Based on how to solve the contradiction between the few-shot data set and the large number of parameters to be trained in the model, we classify the current few-shot traffic classification method based on deep learning from two perspectives: (1) Data augmentation method, which uses the method of expanding the data set to enhance the supervision experience. In this paper, the methods based on data enhancement are divided into two categories based on GAN and feature transformation.(2) Model-based methods. Model-based methods are divided into three categories: transfer learning, metric learning and meta-learning. And discuss the advantages and disadvantages of each classification method. Finally, the results are summarized and the future development direction of few-shot network traffic classification technology based on deep learning is prospected. © 2023 SPIE.

关键词： Deep learning

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A spatial-spectral classification framework for multispectral LiDAR

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地球空间信息科学学报（英文版） 2024年第5期27卷中插4,1460-1474页

作者： Shuo Shi Biwu Chen Sifu Bi Junkai Li Wei Gong Jia Sun Bowen Chen Lin Du Jian Yang Qian Xu Fei Wang Shalei Song State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Scientific Laboratory Shanghai Radio Equipment Research InstituteShanghaiChina Industry Development and Planning Institute NFGABeijingChina State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Electronic Information School Wuhan UniversityWuhanChina Faculty of Information Engineering China University of GeosciencesWuhanChina Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunmingChina Innovation Academy for Precision Measurement Science and Technology Chinese Academy of SciencesWuhanChina

Precise classification of Light Detection and Ranging(LiDAR)point cloud is a fundamental process in various applications,such as land cover mapping,forestry management,and autonomous *** to the lack of spectral information,the existing research on single wavelength LiDAR classification is *** information from images could address this limitation,but data fusion suffers from varying illumination conditions and the registration problem.A novel multi-spectral LiDAR successfully obtains spatial and spectral information as a brand-new data type,namely,multispectral point cloud,thereby improving classification ***,spa-tial and spectral information of multispectral LiDAR has been processed separately in previous studies,thereby possibly limiting the classification performance of multispectral *** explore the potential of this new data type,the current spatial-spectral classification framework for multispectral LiDAR that includes four steps:(1)neighborhood selection,(2)feature extraction and selection,(3)classification,and(4)label *** novel highlights were proposed in this spatial-spectral classification framework.(1)We improved the popular eigen entropy-based neighborhood selection by spectral angle match to extract a more precise neighborhood.(2)We evaluated the importance of geometric and spectral features to compare their contributions and selected the most important features to reduce feature redundancy.(3)We conducted spatial label smoothing by a conditional random field,accounting for the spatial and spectral informa-tion of the neighborhood *** proposed method demonstrated by a multispectral LiDAR with three channels:466 nm(blue),527 nm(green),and 628 nm(red).Experimental results demonstrate the effectiveness of the proposed spatial-spectral classification ***,this research takes advantages of the complementation of spatial and spectral infor-mation,which could benefit more precise neighbor

关键词： multispectral Light Detection and Ranging(LiDAR) point cloud classification neighborhood selection feature selection condition random field

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