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Some new bistable transition fronts with changing shape

Mathematische Annalen 2025年 1-54页

作者： Guo, Hongjun Wang, Kelei School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications (Ministry of Education) Institute for Advanced Study Tongji University Shanghai China School of Mathematics and Statistics Wuhan University Wuhan China

We construct entire solutions of bistable reaction-diffusion equations by mixing finite planar fronts, which form a finite-dimensional manifold. These entire solutions are generalized traveling fronts, that is, transition fronts. We also show their uniqueness and stability. Furthermore, we prove that transition fronts with level sets having finite facets are determined by finite planar fronts and they are in the class of entire solutions constructed by us.

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WiViPose: A Video-aided Wi-Fi Framework for Environment-Independent 3D Human Pose Estimation

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IEEE Transactions on Multimedia 2025年

作者： Zhang, Lei Ning, Haoran Tang, Jiaxin Chen, Zhenxiang Zhong, Yaping Han, Yahong Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Advanced Network Technology and Application Tianjin300050 China Key Laboratory of Computing Power Network and Information Security Ministry of Education China University of Jinan Shandong Provincial Key Laboratory of Ubiquitous Intelligent Computing the School of Information Science and Engineering Jinan250022 China Wuhan Sports University Sports Big-data Research Center Wuhan430079 China Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Machine Learning Tianjin300350 China

The inherent complexity of Wi-Fi signals makes video-aided Wi-Fi 3D pose estimation difficult. The challenges include the limited generalizability of the task across diverse environments, its significant signal heterogeneity, and its inadequate ability to analyze local and geometric information. To overcome these challenges, we introduce WiViPose, a video-aided Wi-Fi framework for 3D pose estimation, which attains enhanced cross-environment generalization through cross-layer optimization. Bilinear temporal-spectral fusion (BTSF) is initially used to fuse the time-domain and frequency-domain features derived from Wi-Fi. Video features are derived from a multiresolution convolutional pose machine and enhanced by local self-attention. Cross-modality data fusion is facilitated through an attention-based transformer, with the process further refined under a supervisory mechanism. WiViPose demonstrates effectiveness by achieving an average percentage of correct keypoints (PCK)@50 of 91.01% across three typical indoor environments. © 2025 IEEE.

关键词： Frequency domain analysis

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Innovative Application of Project Integration Technology in the Teaching Mode of Engineering Drawing Course 24

Innovative Application of Project Integration Technology in ...

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7th International Conference on Educational Technology Management, ICETM 2024

作者： Zhang, Runfeng Ming, Yankun Zhang, Guobin Liu, Zhenzhong Wu, Jianguo Tang, Yuxin National Demonstration Center for Exerimenta Mechanica and Electrica Engineering Education Lianin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin Tianjin China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin University of Technology Tianjin Tianjin China

ISBN: (纸本)9798400717468

Taking underwater robots project as an example, this paper discusses the innovation of the teaching mode of engineering drawing courses under the guidance of a project. The traditional engineering drawing course often lacks the link of practice and project application, which leads to the lack of students’ understanding and application ability of the course content. Therefore, this study proposes a teaching mode based on project guidance. By using underwater robots as teaching cases, theoretical knowledge and practical application are combined to promote the cultivation of students’ comprehensive abilities. This paper first reviews the research progress in related fields, then introduces the design and implementation methods of the teaching mode in detail, and analyzes the actual effect of the model through the underwater robot case. The results show that the teaching mode of engineering drawing courses under the guidance of the project has a positive impact on students’ learning interest, practical ability and teamwork ability. The results of this study will provide practical and feasible solutions for the innovation of the teaching mode of engineering drawing courses, and also provide a reference for the reform of undergraduate teaching mode in the construction of "New Engineering Education". © 2024 Copyright held by the owner/author(s).

关键词： Students

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RobNODDI: Robust NODDI Parameter Estimation with Adaptive Sampling Under Continuous Representation

RobNODDI: Robust NODDI Parameter Estimation with Adaptive S...

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15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2024

作者： Xiao, Taohui Cheng, Jian Fan, Wenxin Yang, Jing Li, Cheng Dong, Enqing Wang, Shanshan School of Mechanical Electrical and Information Engineering Shandong University Weihai264209 China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Peng Cheng Laboratory Guangdong Shenzhen China

ISBN: (纸本)9783031869198

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-based methods perform parameter estimation through diffusion magnetic resonance imaging (dMRI) with a small number of diffusion gradients. These methods speed up parameter estimation and improve accuracy. However, the diffusion directions used by most existing deep learning models during testing needs to be strictly consistent with the diffusion directions during training. This results in poor generalization and robustness of deep learning models in dMRI parameter estimation. In this work, we first verify that the parameter estimation performance of current mainstream methods will significantly decrease when the testing diffusion directions and the training diffusion directions are inconsistent. A robust NODDI parameter estimation method with adaptive sampling under continuous representation (RobNODDI) is proposed. Furthermore, long short-term memory (LSTM) units and fully connected layers are selected to learn continuous representation signals. To this end, we use a total of 100 subjects to conduct experiments based on the Human Connectome Project (HCP) dataset, of which 60 are used for training, 20 are used for validation, and 20 are used for testing. The test results indicate that RobNODDI improves the generalization performance and robustness of the deep learning model, enhancing the stability and flexibility of deep learning NODDI parameter estimatimation applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Family of Mutually Uncorrelated Codes for DNA Storage Address design

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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A Stable RTK/MEMS-IMU Tightly-Coupled Algorithm under Differential Corrections Outage

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IEEE Transactions on Vehicular Technology 2025年

作者： Bian, Yougang Cao, Shipeng Wang, Guangcai Qin, Xiaohui Hu, Manjiang Qin, Hongmao Hunan University State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University Wuxi Intelligent Control Research Institute Wuxi214115 China

The GNSS-RTK and MEMS-IMU integrated navigation system is a commonly used high-precision, low-cost solution for outdoor positioning. However, the significant measurement error of MEMS-IMU can rapidly lead to divergence in navigation state predictions based on inertial error propagation models. To overcome this limitation and enhance accuracy, maintaining the continuity of RTK measurement information is crucial. Nevertheless, due to the instability of wireless transmission links and communication equipment, or disruptions in base station observations, differential corrections often experience outages, resulting in a decline in measurement information quality and affecting the accuracy of integrated navigation. Therefore, this paper proposes a stable RTK/MEMS-IMU tightly coupled algorithm. During outages of differential corrections, the proposed algorithm utilizes historical differential corrections from the base station along with real-time rover station information to construct a stable double-difference carrier phase vector. This approach ensures the stability of measurement information and enhances positioning accuracy. Simulation results have verified the effectiveness of this method, and land tests have demonstrated that, compared to the traditional RTK/MEMS-IMU tightly coupled algorithm, the position and velocity accuracy of this algorithm during outages of differential corrections have been improved by 29.5% and 18.4%, respectively. © 1967-2012 IEEE.

关键词： Base stations

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design and testing research of LiDAR for detecting atmospheric turbulence

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Optoelectronics Letters 2025年第3期21卷 172-176页

作者： QIU Duoyang LI Xianyang YANG Hao ZHU Xiaomeng FANG Zhiyuan XU Xiang School of Advanced Manufacturing Engineering Hefei UniversityHefei230601China Anhui Provincial Engineering Technology Research Center of Intelligent Vehicle Control and Integrated Design Technology Hefei UniversityHefei230601China Science Island Branch of Graduate School University of Science and Technology of ChinaHefei230026China School of Mechanical and Energy Engineering Ningbo Tech UniversityNingbo315100China Key Laboratory of Atmospheric Optics Anhui Institute of Optics and Fine MechanicsChinese Academy of SciencesHefei230031China

Atmospheric turbulence is an important parameter affecting laser atmospheric *** paper reports on a self-developed atmospheric turbulence detection Li DAR system(scanning differential image motion Li DAR(DIM-Li DAR)system).By designing and simulating the optical system of atmospheric turbulence detection Li DAR,the basic optical imaging accuracy has been determined.

关键词： li dar designing simulating optical system lidar scanning differential image motion lidar differential image motion laser atmospheric transmissionthis atmospheric turbulence atmospheric turbulence detection li darthe

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Target-background feature blocks and aberrance repressed correlation filters for real-time UAV tracking

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Signal, Image and Video Processing 2025年第7期19卷 1-11页

作者： Jia, Yunwei Liu, Bo Liu, Zhenzhong Wang, Tianyang Yv, Kaiying Wang, Shuo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

In recent years, Unmanned Aerial Vehicle (UAV) tracking technology has been widely applied in fields such as agriculture and aviation. However, due to limitations in UAV computational resources and battery life, deep learning-based tracking algorithms are difficult to deploy directly. Therefore, efficient and robust tracking methods based on Discriminative Correlation Filters (DCF) have become the mainstream for UAV tracking. The traditional DCF method updates the model with a fixed step size, making it prone to contamination, while the boundary effect further limits its tracking capability. To address the issue of model contamination, an appearance model update and masking mechanism was designed, introducing feature confidence and overall confidence thresholds to evaluate the quality of features and images. Features and images with poor quality are masked, and the learning rate is reduced to prevent model contamination. This paper proposes the Target-Background Feature Block and Aberrance Repressed Correlation Filter (TBFBARCF), which introduces target and background regularization terms into the spatial filter to mitigate boundary effects and incorporates an aberrance repression regularization term into the temporal aberrance repressed filter to reduce response map aberrance. The two filters mutually constrain each other and are jointly trained. Experiments conducted on three challenging datasets, OTB100, UAV123, and UAVDT, demonstrate that the TBFBARCF tracker outperforms 11 other DCF-based trackers. Its average precision and average success rate reach 0.756 and 0.62, respectively, and it operates at a speed of 36.6 frames per second (FPS) on a CPU platform. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Drones

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A novel ECT image reconstruction method based on the deblurring diffusion model

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Flow Measurement and Instrumentation 2025年 104卷

作者： Liu, Yan-Dong Wu, Xin-Jie Liu, Shi-Xing Wang, Yi-Fan Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Liaoning Dalian116622 China School of Software Engineering Dalian University Liaoning Dalian116622 China College of Physics Liaoning University Liaoning Shenyang110036 China School of Information Science and Engineering Shenyang University of Technology Liaoning Shenyang110870 China

To address the challenge of low reconstruction accuracy in Electrical Capacitance Tomography (ECT) images, we propose an imaging method based on a deblurring diffusion model, transforming the image reconstruction into image generation. In cases where the noise type affecting the ECT image reconstruction cannot be determined, inspired by the cold diffusion model, we use an alpha kernel instead of Gaussian noise to perform the image blurring process. During the deblurring process, we utilize the U-Net as the backbone network and incorporated the Linear Attention module to improve imaging accuracy. Additionally, recognizing the similarity between image error metrics and the Dice function, we integrate the Dice function into the loss. Simulation experiments demonstrate that the image errors and correlation coefficients using the proposed method outperform those achieved with the LBP, Tikhonov, Landweber, and classic CNNs. Finally, we deploy the proposed algorithm to the actual ECT system. © 2025 Elsevier Ltd

关键词： Image denoising

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Enhanced corrosion resistance of laser powder bed fusion 316L stainless steel by modifying the microstructure through heat treatment

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Journal of Materials Research and Technology 2025年 36卷 7158-7171页

作者： Cuiling Zhao Yuchao Bai Qi Yan Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robots Harbin Institute of Technology Shenzhen 518055 China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Harbin Institute of Technology Shenzhen 518055 China School of Robotics and Advanced Manufacture Harbin Institute of Technology Shenzhen 518055 China Department of Mechanical Engineering College of Design and Engineering National University of Singapore Singapore 117575 Singapore

This study aims to investigate the microstructural evolution of laser powder bed fusion (LPBF) 316L stainless steel during heat treatment and its effect on corrosion resistance through microstructural characterization and corrosion testing. The results show that the as-built LPBF samples featured melt pool boundaries, cellular structures, a few nano-sized manganese silicate particles and irregular grains with strong fiber texture <101>, which are retained after heat treatment at 450 °C. With temperature increase to 850 °C, a σ phase rich in Cr, Mo, and S elements was formed. Subsequently, after heat treatment at 1100 °C, melt boundary disappears and large square grains similar to the cast counterparts appear. Electrochemical tests demonstrate that the corrosion resistance of LPBF samples surpasses the cast samples heat treated at 1100 °C. In addition, annealing at or below 1100 °C will reduce the corrosion resistance of LPBF samples due to the formation of hazardous precipitates. However, after heat treatment at 1300 °C, the best corrosion resistance was obtained due to the diffusion of Cr, Mo and S elements into the matrix and homogeneous microstructure. This study provides a method for effectively improving the corrosion resistance of LPBF 316L stainless steel and understanding the corresponding corrosion mechanism.

关键词： Laser powder bed fusion Corrosion behaviour Heat treatment 316L stainless steel Microstructure

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