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Rail-Pillar Net:A 3D Detection Network for Railway Foreign Object Based on LiDAR

Computers, Materials & Continua 2024年第9期80卷 3819-3833页

作者： Fan Li Shuyao Zhang Jie Yang Zhicheng Feng Zhichao Chen School of Electrical Engineering and Automation Jiangxi University of Science and TechnologyGanzhou341000China Jiangxi Provincial Key Laboratory of Maglev Technology Ganzhou341000China School of Information Engineering Jiangxi University of Science and TechnologyGanzhou341000China

Aiming at the limitations of the existing railway foreign object detection methods based on two-dimensional(2D)images,such as short detection distance,strong influence of environment and lack of distance information,we propose Rail-PillarNet,a three-dimensional(3D)LIDAR(Light Detection and Ranging)railway foreign object detection method based on the improvement of ***,the parallel attention pillar encoder(PAPE)is designed to fully extract the features of the pillars and alleviate the problem of local fine-grained information loss in PointPillars pillars ***,a fine backbone network is designed to improve the feature extraction capability of the network by combining the coding characteristics of LIDAR point cloud feature and residual ***,the initial weight parameters of the model were optimised by the transfer learning training method to further improve *** experimental results on the OSDaR23 dataset show that the average accuracy of Rail-PillarNet reaches 58.51%,which is higher than most mainstream models,and the number of parameters is 5.49 *** with PointPillars,the accuracy of each target is improved by 10.94%,3.53%,16.96%and 19.90%,respectively,and the number of parameters only increases by 0.64M,which achieves a balance between the number of parameters and accuracy.

关键词： Railway foreign object light detection and ranging(LiDAR) 3D object detection PointPillars parallel attention mechanism transfer learning

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Method for measuring the low-frequency sound power from a complex sound source based on sound-field correction in a non-anechoic tank

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Chinese Physics B 2023年第5期32卷 504-519页

作者：徐宏哲李琪唐锐尚大晶 Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001China Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001China College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001China

Similar to air reverberation chambers, non-anechoic water tanks are important acoustic measurement devices that can be used to measure the sound power radiated from complex underwater sound sources using diffusion field theory. However,the problem of the poor applicability of low-frequency measurements in these tanks has not yet been solved. Therefore,we propose a low-frequency acoustic measurement method based on sound-field correction(SFC) in an enclosed space that effectively solves the problem of measuring the sound power from complex sound sources below the Schroeder cutoff frequency in a non-anechoic tank. Using normal mode theory, the transfer relationship between the mean-square sound pressure in an underwater enclosed space and the free-field sound power of the sound source is established, and this is regarded as a correction term for the sound field between this enclosed space and the free field. This correction term can be obtained based on previous measurements of a known sound source. This term can then be used to correct the mean-square sound pressure excited by any sound source to be tested in this enclosed space and equivalently obtain its free-field sound power. Experiments were carried out in a non-anechoic water tank(9.0 m × 3.1 m × 1.7 m) to confirm the validity of the SFC method. Through measurements with a spherical sound source(whose free-field radiation characteristics are known),the correction term of the sound field between this water tank and the free field was obtained. On this basis, the sound power radiated from a cylindrical shell model under the action of mechanical excitation was measured. The measurement results were found to have a maximum deviation of 2.9 d B from the free-field results. These results show that the SFC method has good applicability in the frequency band above the first-order resonant frequency in a non-anechoic tank. This greatly expands the potential low-frequency applications of non-anechoic tanks.

关键词： non-anechoic tank complex sound source sound-field correction low-frequency sound power

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BAYESIAN OPTIMISATION-BASED DYNAMIC CHANNEL PREDICTION FOR THE URLLC-ORIENTED UAV COMMUNICATION SYSTEM

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International Journal of Robotics and Automation 2025年第3期40卷 203-221页

作者： Zhang, Qiuyun Jiang, Hong Shi, Fanrong Deng, Liping Guo, Qiumei Luo, Ying Yan, Tingting School of Information Engineering Southwest University of Science and Technology Mianyang621010 China Peng Cheng Laboratory Shenzhen518055 China

The acquisition of real-time and accurate channel state information (CSI) is the foundation for achieving ultra-reliable and low-latency communication (URLLC). However, in high-speed mobile application scenarios, the wireless channel between the transmitter and receiver exhibits rapid changes and non-stationary characteristics. This makes obtaining CSI increasingly difficult, and conventional datadriven prediction models are difficult to adapt. Therefore, this paper proposes a new model-driven prediction framework to tackle the challenge. Specifically, we propose a new prediction framework based on Bayesian optimisation and long short-term memory (LSTM). This method continuously acquires and updates CSI data in real time, evaluates prediction accuracy, and optimises the model based on these evaluations. This iterative process allows the model to adapt to changes, leading to more accurate CSI predictions. To demonstrate the effectiveness of our forecasting framework, we designed a UAV operational context and conducted experiments on the UAV control channels. In comparing various data-driven models, including LSTM, gated recurrent unit (GRU), TCN, and recurrent neural network (RNN), the simulation outcomes revealed that our approach performed better on dynamic non-stationary UAV control channels. Our method, evaluated by mean squared error (MSE), shows superior performance over other prediction methods, reducing errors by 3.86% on average. © 2025 Acta Press. All rights reserved.

关键词： Recurrent neural networks

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Abnormal event detection in surveillance videos through LSTM auto-encoding and local minima assistance

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Discover Internet of Things 2025年第1期5卷 1-25页

作者： Sengonul, Erkan Samet, Refik Abu Al-Haija, Qasem Alqahtani, Ali Alsemmeari, Rayan A. Alghamdi, Bandar Alturki, Badraddin Alsulami, Abdulaziz A. Department of Computer Engineering Ankara University Ankara06100 Turkey Department of Cybersecurity Faculty of Computer & Information Technology Jordan University of Science and Technology PO Box 3030 Irbid22110 Jordan Department of Networks & Communications Engineering College of Computer Science & Information Systems Najran University Najran61441 Saudi Arabia Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia

Abnormal event detection in video surveillance is critical for security, traffic management, and industrial monitoring applications. This paper introduces an innovative methodology for anomaly detection in video data, encompassing three primary stages: preprocessing, feature learning, and anomaly detection. We employ background subtraction and noise reduction during preprocessing to refine the data. The feature-learning stage involves training an LSTM autoencoder to capture the essential features of normal video sequences. For anomaly detection, we map video data to a lower-dimensional space (latent code) and compare it against the distribution of codes from normal sequences. We determine regularity scores and identify local minima points exceeding a specified threshold while scrutinizing shadows between adjacent maxima to confirm and pinpoint anomalies. When tested on the CUHK Avenue and UMN datasets, our methodology demonstrated performance with AUCs of 93.8% and 94.1%, respectively, outperforming several baseline models. Our results show the high precision of our method that can detect anomalies, highlighting its potential advantages that it can achieve for enhancing systems of surveillance. © The Author(s) 2025.

关键词： Noise abatement

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Rational surface charge engineering of haloalkane dehalogenase for boosting the enzymatic performance in organic solvent solutions

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Chinese Journal of Chemical engineering 2024年第1期65卷 276-285页

作者： Yin Wu Yan Sun Department of Biochemical Engineering School of Chemical Engineering and Technology and Key Laboratory of Systems Bioengineering and Frontiers Science Center for Synthetic Biology(Ministry of Education)Tianjin UniversityTianjin 300350China

Biocatalysis in organic solvents(OSs)has numerous important applications,but native enzymes in OSs often exhibit limited catalytic ***,we proposed a computation-aided surface charge engineering strategy to improve the catalytic performance of haloalkane dehalogenase DhaA in OSs based on the energetic analysis of substrate binding to the DhaA *** variants with enhanced OS resistance were obtained by replacing negative charged residues on the surface with positive charged residue(Arg).Particularly,a four-substitution variant E16R/E93R/E121R/E257R exhibited the best catalytic performance(five-fold improvement in OS resistance and seven-fold half-life increase in 40%(vol)dimethylsulfoxide).As a result,the overall catalytic performance of the variant could be at least 26 times higher than the wild-type *** spectroscopy and molecular dynamics simulation studies revealed that the residue substitution mainly enhanced OS resistance from four aspects:(a)improved the overall structural stability,(b)increased the hydrophobicity of the local microenvironment around the catalytic triad,(c)enriched the hydrophobic substrate around the enzyme molecule,and(d)lowered the contact frequency between OS molecules and the catalytic *** findings validate that computationaided surface charge engineering is an effective and ingenious rational strategy for tailoring enzyme performance in OSs.

关键词： Surface charge engineering Organic solvent resistance Molecular dynamics simulation Haloalkane dehalogenase

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FDCPNet:feature discrimination and context propagation network for 3D shape representation

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 83-94页

作者： Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.

关键词： 3D shape representation Mesh model MeshNet Feature discrimination Context propagation

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Compact TE-pass polarizer based on lithium-niobate-on-insulator assisted by indium tin oxide and silicon nitride

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Chinese Physics B 2023年第6期32卷 284-289页

作者：刘家敏张德龙 Department of Opto-electronics and Information Engineering School of Precision Instruments and Opto-electronics EngineeringKey Laboratory of Optoelectronic Information Technology(Ministry of Education)and Key Laboratory of Micro-Opto-Electro-Mechanical Systems(MOEMS)Technology(Ministry of Education)Tianjin UniversityTianjin 300072China

An indium tin oxide(ITO) and silicon nitride(Si_(3)N_(4)) assisted compact TE-pass waveguide polarizer based on lithiumniobate-on-insulator is proposed and numerically *** properly designing the ITO and Si_(3)N_(4) assisted structure and utilizing the epsilon-near-zero effect of ITO,the TM mode is strongly confined in the ITO layer with extremely high loss,while the TE mode is hardly affected and passes through the waveguide with low *** simulation results show that the polarizer has an extinction ratio of 22.5 dB and an insertion loss of 0.8 dB at the wavelength of 1.55 μm,and has an operating bandwidth of about 125 nm(from 1540 nm to 1665 nm) for an extinction ratio of>20 dB and an insertion loss of<0.95 ***,the proposed device exhibits large fabrication *** notably,the device is compact,with a length of only 7.5 μm,and is appropriate for on-chip applications.

关键词： polarizer lithium-niobate-on-insulator integrated optics devices optical waveguide

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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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science China(information sciences) 2025年第2期68卷 89-102页

作者： Meiting SUN Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Institute of Artificial Intelligence

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder(RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

关键词： unsupervised feature selection fractal autoencoder correspondence neural network selection neural network redundancy regularization strategy

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Health monitoring by optical fiber sensing technology for rechargeable batteries

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escience 2024年第1期4卷 79-95页

作者： Yi Zhang Yanpeng Li Zezhou Guo Jianbo Li Xiaoyu Ge Qizhen Sun Zhijun Yan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhanHubei430074China Henan Key Laboratory of Laser and Opto-electric Information Technology School of Electrical and Information EngineeringZhengzhou UniversityZhengzhouHenan45001China

With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical ***,many traditional sensing technologies suffer from low sensitivity,large size,and electromagnetic interference problems,rendering them unusable in the harsh and complicated electrochemical environments of *** optical sensor is an alternative approach to realize multiple-parameter,multiple-point measurements ***,it has garnered significant *** analyzing these measured parameters,the state of interest can be decoded to monitor a battery's *** review summarizes current progress in optical sensing techniques for batteries with respect to various sensing parameters,discussing the current limitations of optical fiber sensors as well as directions for their future development.

关键词： Optical fiber sensing Rechargeable battery Real-time sensing Health monitoring

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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