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A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第3期25卷 206-222页

作者： Junyuan ZHENG Caiyou ZHAO Duojia SHI Ping WANG Jian WANG Bolong JIANG Xi SHENG Key Laboratoryof High-speed Railway engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu 60031China School of Civil engineering Southwest Jiaotong UniversityChengdu 610031China 01 DYNA(Qingdao)Test&Data Co. Ltd.Qingdao 266000China Rail Transit digital Construction and Measurement Technology National engineering research center China Railway Design CorporationTianjin300308China Institute of Urban Smart Transportation&Safety Maintenance Shenzhen UniversityShenzhen 518060China

The extensive use of steel spring floating slab tracks has effectively addressed the challenge of alleviating the environmental vibrations induced by urban rail transit ***,under the combined action of train dynamic loads and complex environmental factors,problems,such as the fracture of steel spring vibration isolators and suspension vibrations induced by the uneven settlement of the base,often *** failure of isolator support stiffness is often hidden in its early stages and is challenging to identify by conventional detection *** the same time,it will aggravate the wheel-rail interaction,accelerate the deterioration of track structure,and even affect the driving *** study first establishes a detailed coupled train-floating slab track-foundation analytical *** the influence of the vibration isolator support stiffness failure on the dynamic indices of the floating slab track system response is analyzed.A set of defect identification methods that can detect the number of failed steel springs,severity of damage,and their location is ***,an intelligent monitoring system for support stiffness of floating slab track is built by combining the density-based spatial clustering of applications with noise algorithm and statistical data analysis and is applied to a rail line in southern *** a three-year monitoring campaign,a suspension failure and a fracture of a steel spring were each successfully detected and detailed failure information was *** investigation results were consistent with the damage identification *** repair,the track structure dynamic response returned to the average pre-damage level and further deterioration had been *** proposed damage identification methods and monitoring system provide an approach for intelligent identification of track structure support stiffness failures.

关键词： Floating slab track Support stiffness Detailed analytical model Failure identification Monitoring system

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology engineering research center of digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Image coding Image color analysis Quaternions Forensics Transform coding Color Feature extraction

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Weakly Supervised Network with Scribble-Supervised and Edge-Mask for Road Extraction from High-Resolution Remote Sensing Images

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Computers, Materials & Continua 2024年第4期79卷 549-562页

作者： Supeng Yu Fen Huang Chengcheng Fan College of Artificial Intelligence Nanjing Agricultural UniversityNanjing210095China Innovation Academy for Microsatellites of CAS Shanghai201210China Shanghai engineering center for Microsatellites Shanghai201210China Key Laboratory of Satellite digital Technology Shanghai201210China

Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.

关键词： Semantic segmentation road extraction weakly supervised learning scribble supervision remote sensing image

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A General simulation Method for Complex Deformation of Irregular-Shaped Origami Configurations

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Acta Mechanica Solida Sinica 2024年第1期37卷 90-98页

作者： Zhaochen Dong Yichao Zhu Xu Guo State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian 116023China

Most existing treatments for origami-folding simulations have focused on regular-shaped *** article aims to introduce a general strategy for simulating and analyzing the deformation process of irregular shapes by means of computational capabilities *** better simulate origami deformation with folding orders,the concept of plane follow-up is introduced to achieve automated computer simulation of complex folding patterns,thereby avoiding intersection and penetration between *** on the evaluation criteria such as the lowest storage energy with tightening and the fastest pace from tightening to unfolding,the optimal crease distribution patterns for four irregular(‘N’-,‘T’-,‘O’-,and‘P’-shaped)origami configurations are then presented under five *** the dimensions of the origami are fixed,it is discovered that simpler folding patterns lead to faster deformation of the origami *** the folding complexity is fixed,higher strain energy results in more rapid origami expansion.

关键词： Irregular-shaped origami Complex deformation Computer-aided origami design General simulation

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Dramatic Difference Between Cu_(20)H_(8)and Cu_(20)H_(9)Clusters in Catalysis

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CCS Chemistry 2024年第6期6卷 1581-1590页

作者： Chun-Yu Liu Tong-Yu Liu Zong-Jie Guan Song Wang Yuan-Yuan Dong Feng Hu De-en Jiang Quan-Ming Wang Department of Chemistry Engineering Research Center of Advanced Rare Earth Materials(Ministry of Education)Tsinghua UniversityBeijing 100084 Jiangsu engineering research Centre for digital Textile Inkjet Printing Key Laboratory of Eco-Textile Jiangnan UniversityMinistry of EducationWuxiJiangsu 214122 Department of Chemical and Biomolecular engineering Vanderbilt UniversityNashvilleTennessee 37235 Department of Chemistry Vanderbilt UniversityNashvilleTennessee 37235 College of Chemistry and Chemical engineering Hunan UniversityChangsha 410082 Hefei National research center for Physical Sciences at the Microscale School of Chemistry and Materials ScienceUniversity of Science and Technology of ChinaHefeiAnhui 230026

Sensitivity to structure and composition is very challenging to establish in nanocatalysis due to inadequate definition of structures that are very close in *** synthesized a pair of atomically precise copper clusters that are very close in composition,[Cu_(20)H_(9)(Tf-dpf)_(10)]·BF4(Cu_(20)H_(9))and[Cu_(20)H_(8)(Tf-dpf)_(10)]·(BF_(4))_(2)(Cu_(20)H_(8)),by using a pyridyl-functionalized flexible amidinate ligand,N,N′-di(5-trifluoromethyl-2-pyridyl)*** one-hydride difference in their composition leads to significant variation in geometric and electronic structures and,consequently,distinctly different optical and catalytic ***_(20)H_(8)exhibits 25 times higher catalytic activity than Cu_(20)H_(9)(96.7%vs 3.7%in yield)in the selective hydrogenation of anα,β-unsaturated aldehyde(cinnamaldehyde)to saturated aldehyde(3-phenylpropanal).Electrospray ionization mass spectrometry combined with density functional theory calculations reveal that the greater ease of dissociation of one Tf-dpf ligand compared to Cu_(20)H_(8)is the key to its higher *** work demonstrates a clear case of structure and composition sensitivity in nanocatalysis and that one hydride,out of∼330 atoms in the nanoclusters,can make a huge difference in the catalytic *** insights will be useful in the design and synthesis of atomically precise nanocatalysts.

关键词： copper cluster hydride amidinate ligand structural transformation hydrogenation catalysis

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Wild Gibbon Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1203-1233页

作者： Jia Guo JinWang Ke Yan Qiankun Zuo Ruiheng Li Zhou He Dong Wang Yuji Sato Hubei Key Laboratory of digital Finance Innovation Hubei University of EconomicsWuhan430205China School of Information engineering Hubei University of EconomicsWuhan430205China China Construction Third engineering Bureau Installation engineering Co. Ltd.Wuhan430074China Hubei Internet Finance Information engineering Technology research center Hubei University of EconomicsWuhan430205China College of Informatics Huazhong Agricultural UniversityWuhan430070China Faculty of Computer and Information Sciences Hosei UniversityTokyo184-8584Japan

Complex optimization problems hold broad significance across numerous fields and ***,as the dimensionality of such problems increases,issues like the curse of dimensionality and local optima trapping also *** address these challenges,this paper proposes a novel Wild Gibbon Optimization Algorithm(WGOA)based on an analysis of wild gibbon population *** two strategies:community search and community *** community search strategy facilitates information exchange between two gibbon families,generating multiple candidate solutions to enhance algorithm ***,the community competition strategy reselects leaders for the population after each iteration,thus enhancing algorithm *** assess the algorithm’s performance,CEC2017 and CEC2022 are chosen as test *** the CEC2017 test suite,WGOA secures first place in 10 *** the CEC2022 benchmark functions,WGOA obtained the first rank in 5 *** ultimate experimental findings demonstrate that theWildGibbonOptimization Algorithm outperforms others in tested *** underscores the strong robustness and stability of the gibbonalgorithm in tackling complex single-objective optimization problems.

关键词： Complex optimization wild gibbon optimization algorithm community search community competition

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Kinetically and thermodynamically expediting elementary steps via high-valence Cr-incorporated of nickel selenide for water electrolysis

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Nano research 2024年第3期17卷 1199-1208页

作者： Huafeng Fan Dongxu Jiao Jinchang Fan Dewen Wang Bilal Zaman Wei Zhang Lei Zhang Weitao Zheng Xiaoqiang Cui State Key Laboratory of Automotive simulation and Control School of Materials Science and EngineeringKey Laboratory of Automobile Materials of MOEJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsElectron Microscopy CenterJilin UniversityChangchun 130012China College of Chemistry Jilin UniversityChangchun 130012China

Designing high-performance electrocatalysts toward hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)is essential to reduce the activation barrier and optimize free adsorption energy of reactive ***,we report that incorporating high-valence Cr into NiSe_(2)(Cr_(x)Ni_(1-x)Se_(2))kinetically and thermodynamically expedites elementary steps of both HER and *** as-prepared Cr_(0.05)Ni_(0.95)Se_(2) catalyst displays excellent HER and OER activities,with low overpotentials of 89 and 272 mV at the current density of 10 mA·cm^(-2)(j10),respectively,and remains stable during operation for 30 h.A low cell voltage of only 1.59 V is required to drive j10 in alkaline *** situ Raman spectroscopy reveals that Cr incorporation facilitates the formation of NiOOH active species during the OER ***,theoretical explorations demonstrate that high-valence Cr incorporation efficiently accelerates water dissociation kinetics and improves H*adsorption during HER process,lowering the activation barrier of OER and optimizing the adsorption energy of oxygen-based intermediate,thus kinetically and thermodynamically enhancing the intrinsic performance of NiSe_(2) for over water *** strategy provides a new horizon to design transition metal based electrocatalysts in the clean energy field.

关键词： nickel selenide electrocatalytic water splitting high-valence Cr density functional theory(DFT)calculation

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Emergence mechanisms of group consensus in social networks

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Frontiers of engineering Management 2024年第2期11卷 362-368页

作者： Min WANG Zi-Ke ZHANG College of Media and International Culture Zhejiang UniversityHangzhou 310058China research center for digital Communication Zhejiang UniversityHangzhou 310058China

Reaching consensus within larger social network groups has emerged as a pivotal concern in the digital age of *** article redefines group consensus as the emergence of collective intelligence resulting from self-organizing actions and interactions of individuals within a social network *** our exploration of extant research on group consensus,we illuminate two frequently underestimated,yet noteworthy facets:Dynamism and *** contrast to the conventional perspective of consensus as a mere outcome,we perceive it as an ongoing,dynamic *** process encompasses self-organized communication and interaction among group members,collectively guiding the group towards cognitive convergence and viewpoint ***,it is imperative to redirect our focus from the outcomes of group interactions to an examination of the relationships and processes underpinning consensus formation,thus elucidating the mechanisms responsible for the generation of group *** amalgamation of cognitive contexts and accurate simplification of real-world scenarios for simulation and experimental analysis offers a pragmatic operational *** study contributes novel theoretical underpinnings and quantitative insights for establishing and sustaining group consensus within the realm of engineering management ***,it holds substantial importance for advancing the broader research landscape pertaining to social consensus.

关键词： group consensus social network collective intelligence

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Ferroelectric-controlled graphene plasmonic surfaces for all-optical neuromorphic vision

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Science China(Technological Sciences) 2024年第3期67卷 765-773页

作者： CHEN JianBo LIU Yu LI ShangDong LIN Lin LI YaDong HUANG Wen GUO JunXiong School of Electronic Information and Electrical engineering Institute for Advanced StudyChengdu UniversityChengdu 610106China School of Integrated Circuits Tsinghua UniversityBeijing 100084China School of Integrated Circuits(National Exemplary Schoolof Microelectronics) Universityof Electronic Science and Technologyof China Chengdu 610054China Jincheng research Institute of Opto-mechatronics Industry Jincheng 048000China Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems Jincheng 048000China engineering research center of digital Imaging and Display Ministry of EducationSoochow UniversitySuzhou 215006China

Artificial visual systems can recognize desired objects and information from complex environments, and are therefore highly desired for pattern recognition, object detection, and imaging applications. However, state-of-the-art artificial visual systems with high recognition performances that typically consist of electronic devices face the challenges of requiring huge storage space and high power consumption owing to redundant data. Here, we report a terahertz(THz) frequency-selective surface using a graphene split-ring resonator driven by ferroelectric polarization for efficient visual system applications. The downward polarization of the ferroelectric material offers an ultrahigh electrostatic field for doping p-type graphene with an anticipated Fermi level. By optimizing the geometric parameters of the devices and modulating the carrier behaviors of graphene, our plasmonic devices exhibit a tunable spectral response in a range of 1.7–6.0 THz with continuous transmission values. The alloptical neural network using graphene plasmonic surfaces designed in this study exhibited excellent performance in visual preprocessing and convolutional filtering and achieved an ultrahigh recognition accuracy of up to 99.3% in training the Modified National Institute of Standards and Technology(MNIST) handwritten digit dataset. These features demonstrate the great potential of graphene plasmonic devices for future smart artificial vision systems.

关键词： graphene plasmon ferroelectric frequency selective surface artificial vision system

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A Comparative Study of Machine Learning Models for Traffic Accident Severity Prediction on Rural Highways

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Journal of Traffic and Transportation engineering(English Edition) 2024年

作者： Fengxiang Guo Jingyang Li Feng Zhu Bijiang Tian Wenchen Yang School of Transportation Science and engineering， Harbin Institute of Technology Yunnan Key Laboratory of digital Communications National engineering research center for Efficient Maintenance， Safety and Durability of Roads and Bridges，Broadvision engineering Consultants Co.， Ltd Kunming Faculty of Transportation engineering， Kunming University of Science and Technology School of Civil and Environmental engineering， Nanyang Technological University

The use of machine learning models for analyzing Traffic Accident Severity (TAS) is increasingly common in safety assessment and traffic accident prevention. However， many existing studies have not fully considered the importance of feature engineering， model hyperparameter optimization， and training set proportions， all of which significantly affect the performance of these models. This study addresses the research gap by developing a TAS model using the Light Gradient Boosting Machine (LightGBM) and integrating two feature engineering methods (Random Forest (RF) and Principal Component Analysis (PCA)). Additionally， we compared the LightGBM with three other machine learning models: Support Vector Machine (SVM)， Binary Logistic Regression (BL)， and Deep Neural Network (DNN). This comparison evaluates the effectiveness of different machine learning approaches in classifying TAS， taking into account variations in feature engineering techniques and training set proportions. The case study examines rural highway accidents in Yunnan Province， China， focusing on three categories of factors influencing TAS: accident characteristics， traffic flow， and highway conditions. Moreover， the SHAP (SHapley Additive exPlanations) values were employed to identify the primary factors contributing to the accident severity. The results show that with the training set size of 80%， all four models achieve the highest predictive accuracy for severe accidents. Notably， the PCA+lightGBM combination model outperforms others in overall accident prediction accuracy and has the highest recall rate and F1 score for severe accidents. Comparing the four models under different feature inputs， the impact of feature selection on model performance is less significant than reducing the data heterogeneity. LightGBM and DNN are more susceptible to data heterogeneity， and improving data homogeneity markedly boosts the model’s performance. Through SHAP analysis， it is evident that the modes of transportati

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