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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Chen, Huimin Liu, Chenguang He, Zhibo Zhang, Guoqing Han, Bing State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430063 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China Navigation College Dalian Maritime University Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China National Engineering Research Center of Ship & Shipping Control System Shanghai200134 China

ISBN: (纸本)9789819639601

The paper presents a ship motion planning method that adjusts the attractive and repulsive gain parameters of the artificial potential field (APF) algorithm using the deep deterministic policy gradient (DDPG) algorithm, to address the challenges of parameter design and limited adaptability of traditional APF algorithms. This approach leverages the speed advantage of the APF planning algorithm and the exploration capability of the DDPG reinforcement learning algorithm. By optimizing the parameters of APF with DDPG, the local optima problem can be alleviated in complex obstacle environments. Simulation results demonstrate that the proposed motion planning algorithm can generate reasonable trajectories and exhibit strong adaptability in complex obstacle scenarios. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Motion planning

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A q-Axis Current Injection Open-Circuit Fault-Tolerant Control for AFE Rectifiers in DC Marine Integrated Power systems

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IEEE Transactions on Transportation Electrification 2025年

作者： Yao, Yuhao Huang, Wentao Li, Ran Liu, Jianzhe Zhang, Yuyang Senkov, Aleksey Li, Canbing Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Ship Integrated Power System Shanghai200240 China Marine Design and Research Institute of China Shanghai200011 China China Power Complete Equipment Co. Ltd Beijing100080 China Saint-Petersburg State Marine Technical University Saint Petersburg190008 Russia

The DC marine integrated power system uses the active front end (AFE) rectifiers widely to stabilize the DC bus voltage. However, AFE rectifiers are vulnerable to switch open-circuit faults, which challenge the stability and reliability of the system. Many existing works have been devoted to studying the fault-tolerant control (FTC) of rectifiers, but the adopted space vector replacement and additional control modules only compensate the vector synthesis partly which reduces the ability to control the DC voltage. This paper proposes a q-axis current injection FTC method that enables the converter to operate normally and reduce the DC voltage ripple. The space vector model considering the coupling of control and electrical vectors is established to determine the fault deviation and affected space sectors. The faulty active vectors are reactivated by changing the q-axis current. The modified modulation is the faulty zero vector replacement realized by changing the turn-on time of each switch. The distorted reference voltage vector can be effectively revised with the q-axis current injection and the space vector fault-tolerant modulation. Hardware-in-the-loop (HIL) testing and experimental results verify that the DC voltage ripple is less than 1% under single switch faults with the proposed method. Compared to the existing fault-tolerant control methods, such as projection compensation and zero vector replacement, the DC voltage ripple with the proposed method can be reduced by 33%89% without compromising the fault recovery time. © 2015 IEEE.

关键词： Vectors

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Vector Field-Guided Circumnavigation for an Unmanned Surface Vehicle With Boundary and Obstacle Constraints

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IEEE Transactions on Emerging Topics in computing 2025年

作者： Wu, Nailong Wang, Jigang Wang, Yueying He, Shuping Donghua University College of Information Science and Technology Shanghai201620 China Donghua University Engineering Research Center of Digitized Textile & Apparel Technology Ministry of Education Shanghai201620 China Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electrical Engineering and Automation Hefei230601 China

This article aims to tackle the challenge of rapid target circumnavigation by unmanned surface vehicles (USVs) under boundary and obstacle constraints through leveraging an emerging computing architecture specifically tailored for unmanned systems. Owing to the underactuation of USV dynamic systems and the presence of various time-varying surface disturbances, attaining rapid and accurate position control along with maneuverability poses a significant challenge to USVs. Therefore, when an USV maneuvers around a target in a confined search area with obstacles, it is essential for the guidance law to consider collision risks and environmental disturbances. This paper proposes a modified Lyapunov vector field with heading deviation compensation to circle the target in complex search regions. The vector field is designed to increase the radial velocity of the USV and accelerate convergence towards the target circle during the pursuit phase. By combining the proposed Lyapunov vector field with a boundary vector field, the USV can swiftly avoid boundaries and dynamic obstacles and then continue circling the target. The proposed computing architecture extends the application scope of the target circumnavigation to practical water surface environments, which is validated by extensive simulations and rigorous experiments. © 2025 IEEE.

关键词： Unmanned surface vehicles

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CESFusion: Cross-Frequency Enhanced Spatial-Spectral Fusion Network for Hyperspectral and Multispectral Image Fusion

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Zhang, Haozheng Yang, Yanhong Li, Chaoyang Lu, Yanjie Zhang, Guodao Chen, Shengyong School of Computer Science and Engineering Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin300384 China Engineering Research Center of Learning- Based Intelligent System Ministry of Education Key Laboratory of Computer Vision and Systems School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China Institute of Intelligent Media Computing Hangzhou Dianzi University Hangzhou310018 China

The fusion of hyperspectral and multispectral images involves integrating high spectral resolution hyperspectral image (HSI) and high spatial resolution multispectral image (MSI) to generate a HSI with high spatial and spectral resolution (HR-HSI). Existing HSI-MSI fusion methods primarily focus on information fusion within the spatial domain;however, few solutions have explored the employment of frequency analysis to enhance spatial resolution, limiting their capability for global perception. In this paper, we propose an efficient and novel paradigm for HSI-MSI fusion through the cross-frequency enhanced spatial-spectral fusion network, named CESFusion, exploring the complementary fusion of information between the spatial and frequency domains. Specifically, we first present the cross-frequency domain fusion module (CFFM) to perform global analysis through the Fourier transform and effectively integrate and enhance the frequency domain information from both HSI and MSI. Subsequently, we propose the spectral modeling module (SpeMM) based on state space model (SMM) to capture long-range spectral dependencies with linear complexity, and integrate it with the spatial residual block-based module (SRM) for joint spatial-spectral feature extraction. Finally, to enable sufficient interaction between the spatial and frequency domains, we adopt the cross-domain interaction module (CDIM), capturing and integrating complementary information from both domains. Moreover, a frequency-based loss function is purposely designed to further improve the restoration of global information. Extensive experiments conducted on both synthetic and real datasets demonstrate the superiority of our CESFusion, as evidenced by both quantitative and qualitative evaluation results. © 2025 IEEE.

关键词： Image fusion

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Insights into the X-shaped fissure propagation and interaction mechanisms of rock specimens: 3D printing experiments and DEM simulations

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Case Studies in Construction Materials 2025年 22卷

作者： Sun, Yiqing Huang, Wei Gan, Lei Shen, Zhenzhong Zhang, Hongwei Zhang, Wenbing Intelligent Transportation System Research Center Southeast University Nanjing211189 China Nanjing211100 China The National Key Laboratory of Water Disaster Prevention Hohai University Nanjing210024 China College of Ocean Science and Engineering Shanghai Maritime University Shanghai201306 China

X-shaped fissures are prevalent in natural rocks and significantly influence rock mass stability, yet their interaction and propagation mechanisms remain inadequately studied. This research fabricated rock-like specimens with single and double X-shaped fissures using sand 3D printing technology. Uniaxial compression tests were conducted, and the crack propagation process was analyzed via the DIC method. DEM simulations were also performed to explore the fracture mechanisms. In single X-shaped fissure specimens, crack growth is affected by the inclination angle, with Wing crack (WC) being a dominant propagation mode, and Anti-wing crack (AWC) emerging as the angle increases. In double X-shaped fissure specimens, complex fissure interactions lead to intricate crack propagation, forming through-going main cracks and elaborate crack networks, with Interaction crack (IC) being a notable feature. The stress-strain curves vary with fissure configurations. Specimens with difficult crack propagation generally have higher strength. These findings enhance the understanding of X-shaped fissure fracture mechanisms and offer crucial references for rock engineering design, construction, and stable operation. © 2025 The Authors

关键词： Crack propagation

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Efficient Resource Allocation in computing Power Networks Considering Similar Task Merging: A Lyapunov Optimization-Based DRL Approach

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IEEE Internet of Things Journal 2025年

作者： Jia, Zhonghai Xue, Junxiao Shi, Lei Li, Jie He, Mengyang Zhejiang Lab Research Center for Space Computing System Hangzhou310000 China Zhengzhou University School of Cyber Science and Engineering Zhengzhou450002 China SongShan Laboratory Zhengzhou450040 China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Key Laboratory of Trusted Data Circulation and Governance Web3 Shanghai China

The cloud-edge-terminal architecture relies on hierarchy for resource allocation but lacks global optimization. The computing power network (CPN) introduces a new distributed computing paradigm, integrating cross-domain, heterogeneous resources for global scheduling. However, most CPN research focuses on task optimization during resource allocation, while neglecting the similarity of random tasks before the allocation stage. Additionally, fragmented CPN resources and complex task demands pose challenges to global load balancing. This paper proposes a deep reinforcement learning framework with task merging and congestion avoidance for on-demand resource allocation. Specifically, a low-complexity similar task merging algorithm reduces redundant resource consumption during task preprocessing. In task offloading, the principal neighborhood aggregated graph neural network captures CPN's intricate features. Lyapunov optimization, integrated into a multi-threaded training framework, minimizes resource backlog congestion. A carefully designed reward function balances multiple objectives, enhancing computing resource utilization efficiency and ensuring system stability. Theoretical analysis shows that with control parameter V, the trade-off between resource utilization efficiency and system stability follows the relationship O(1/V), O(V). Extensive experiments demonstrate a 33.5% improvement in resource utilization efficiency and a 62.7% increase in task offloading success rates with respect to those in state-of-the-art algorithms. The proposed algorithm exhibits robustness and effectiveness, particularly in high-load and real network topologies. © 2014 IEEE.

关键词： computing power

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Analysis and Design of Application-Layer Rateless Codes Based on Reliability and Latency Trade-Off

Analysis and Design of Application-Layer Rateless Codes Base...

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IEEE Conference on Wireless Communications and Networking

作者： Haobo Huang Yusun Fu Junpeng Yin Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

With the Internet of Things (IoT) playing an increasingly crucial role in connecting diverse devices, applications have different requirements for communication and various evaluation metrics have emerged, such as Age of Information (AoI) and estimation error. Considering the fundamental trade-off between reliability and latency of the communication system, the relationship among reliability, latency, AoI and estimation error is complex. This paper proposes a remote state observation system with application-layer rateless codes to explore above relationships, addressing how to design the system for optimal performance based on varying requirements by adjusting coding parameters. By emphasizing flexible and adaptable coding strategies, we aim to convey the idea that the error-correction codes can be designed to optimize the communication system for diverse practical metrics. It is different from the traditional designs that focus on approaching the Shannon limit.

关键词： Measurement Estimation error Correlation Communication systems Reliability engineering Information age Error correction codes Internet of Things Channel coding State estimation

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Electrochemical activated ZnMn2O4 with Al doping for boosting high-capacity and long-term stable Zn ion storage

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Journal of Energy Storage 2025年 122卷

作者： Xu, Shusheng Xiong, Haichao Wang, Zhaozhao Ma, Hui Sun, Xuecheng Wang, Peiqingfeng Zhu, Jiaqing Shi, Xue-Rong School of Materials Science and Engineering Shanghai University of Engineering Science Shanghai201620 China School of Mechanical and Automotive Engineering Shanghai University of Engineering Science Shanghai201620 China Microelectronic Research & Development Center School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Shanghai Key Laboratory of Automotive Intelligent Network Interaction Chip and System The School of Microelectronics Shanghai University Shanghai200444 China State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences P.O. Box 165 Shanxi Taiyuan030001 China

Although spinel ZnMn2O4 (ZMO) is of great promise as a cathode material for Zn ion storage, the limited capacity and poor stability significantly hinders its practical applications. In this work, with Mn-BTC as the precursor, Al-doped ZnMn2O4 (AZMO) micro-spheres with an incorporated carbon skeleton were prepared by a two-step process involving low-temperature calcination and electrochemical activation. AZMO micro-spheres with hollow structures effectively shortens ion diffusion pathways and provides abundant active sites for Zn2+ storage during the electrochemical reactions. Meanwhile, Al doping leads to strong Al[sbnd]O bonds in ZMO framework, which not only prevents the structure transformation and Mn dissolution, but also optimizes the ion states and the band gap of the AZMO cathode. As a result, the synthesized AZMO cathode exhibits a larger reversible specific capacity of 526 mAh g−1 (0.1 A g−1) and better cycling stability (81.76 % capacity retention after 2000 cycles at 2 A g−1) than the original ZMO. Furthermore, coin-type and soft-packed Zn ion batteries (ZIBs) based on the AZMO cathode were also assembled with excellent electrochemical properties, demonstrating the great potential for energy storage and flexible electronic applications. © 2025 Elsevier Ltd

关键词： Boron carbide

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Air Pollution Monitoring By Integrating Local and Global Information in Self-Adaptive Multiscale Transform Domain

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IEEE Transactions on Multimedia 2025年

作者： Gu, Ke Liu, Yuchen Liu, Hongyan Liu, Bo Qiao, Junfei Lin, Weisi Zhang, Wenjun Beijing University of Technology School of Information Science and Technology Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Massey University School of Mathematical and Computational Sciences New Zealand Nanyang Technological University College of Computing and Data Science Singapore Shanghai Jiao Tong University Institute of Image Communication and Information Processing Shanghai China

As the deadliest form of pollution, air pollution had a prolonged severe damage to the human health and life safety of nearly 99% of the world's population. Facing to the problem that billions of tons of pollutants discharged into the air per year by industrial activities, this paper proposed a novel image-based air pollution monitor (IAPM) by incorporating local and global information in the self-adaptive multiscale transform domain, so as to achieve the timely and effective leakage detection of typical air pollutants from a single image. To be specific, this paper first developed a screen-shaped module according to two significant findings in visual neuroscience, which include the high sensitivity of human eyes to horizontal and vertical stimuli and the center-surround inhibition, by designing and fusing the square module, horizontal strip module and vertical strip module parallelly for simulating the behaviour of human eyes to extract local features. Second, the learnable weights and proportional mapping were applied to incorporate the screen-shaped module and lightweight vision transformer as backbone, towards more richly exploiting and fusing local and global information just as the way a brain perceives external stimuli. Third, a new self-adaptive multiscale transform domain method was devised based on two motivations from the visual characteristics of multiscale perception and the brain characteristics of self-adaptive domain transform to modify the backbone by using the operations of pooling and pointwise convolution. Extensive experiments implemented on the datasets of carbon particulate matters and ethylene leakage confirmed the superior monitoring performance of the proposed IAPM model beyond the state-of-the-art (SOTA) peers by an accuracy gain of about 4%. Furthermore, the proposed IAPM model only required 0.089 GFLOPs and 0.15 million model parameters, remarkably outperforming SOTA competitors in computational efficiency and storage resources. © 1999-2

关键词： Information leakage

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Replace2Self: Self-Supervised Denoising based on Voxel Replacing and Image Mixing for Diffusion MRI

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Wu, Linhai Wang, Lihui Deng, Zeyu Zhu, Yuemin Wei, Hongjiang Guizhou University Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education State Key Laboratory of Public Big Data College of Computer Science and Technology 550025 China Univ Lyon INSA Lyon CNRS Inserm CREATIS UMR 5220 LyonF-69621 France Shanghai Jiao Tong University School of Biomedical Engineering Shanghai200030 China

Low signal to noise ratio (SNR) remains one of the limitations of diffusion weighted (DW) imaging. How to suppress the influence of noise on the subsequent analysis about the tissue microstructure is still challenging. This work proposed a novel self-supervised learning model, Replace2Self, to effectively reduce spatial correlated noise in DW images. Specifically, a voxel replacement strategy based on similar block matching in Q-space was proposed to destroy the correlations of noise in DW image along one diffusion gradient direction. To alleviate the signal gap caused by the voxel replacement, an image mixing strategy based on complementary mask was designed to generate two different noisy DW images. After that, these two noisy DW images were taken as input, and the non-correlated noisy DWimage after voxel replacement was taken as learning target, a denoising network was trained for denoising. To promote the denoising performance, a complementary mask mixing consistency loss and an inverse replacement regularization loss were also proposed. Through the comparisons against several existing DW image denoising methods on extensive simulation data with different noise distributions, noise levels and b-values, as well as the acquisition datasets and the ablation experiments, we verified the effectiveness of the proposed method. Regardless of the noise distribution and noise level, the proposed method achieved the highest PSNR, which was at least 1.9% higher than the suboptimal method when the noise level reaches 10%. Furthermore, our method has superior generalization ability due to the use of the proposed strategies. © 2025 IEEE. All rights reserved.

关键词： Signal to noise ratio

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