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SPMNet: A Siamese Pyramid Mamba Network for Very-High-Resolution Remote Sensing Change Detection

IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Wang, Jiashu Song, Jinze Zhang, Hao Zhang, Zekai Ji, Yunlong Zhang, Wenyin Zhang, Jinglin Wang, Xing Linyi University School of Computer Science and Engineering Linyi276000 China Shandong University Department of Control Science and Engineering Jinan250061 China Linyi University School of Information Science and Engineering China

Very-High-Resolution (VHR) remote sensing images are characterized by extremely high spatial resolution, incorporating higher pixel density and larger image sizes, which pose challenges for existing methods to extract complex texture features. Furthermore, due to the wide-area and high-resolution imaging strategy, VHR change detection images suffer from a severe imbalance between change pixels and non-change pixels, increasing the difficulty of handling change detection tasks. To address these challenges, we introduced the Omnidirectional Selective Scan Module (OSSM), which has the capability to process long sequences. By integrating it with the lightweight Siamese Feature Pyramid Network (SFPN), we designed a hybrid CNN-Mamba backbone, referred to as SPMamba. This backbone captures both global and local information within bitemporal feature maps at each stage, enhancing the precision of texture feature extraction. Additionally, to integrate the semantic features from each branch in SPMamba and reduce noise interference from non-target change areas, we developed a Hybrid Fusion Module (HFM). The HFM consists of two fusion modules: the High-Low Channel Fusion Module (HLM) and the Bilateral Channel Fusion Module (BCM), which facilitates both feature-level and channel-level integration, enhancing the sensitivity of the model to subtle changes. Extensive experimental results demonstrate that SPMNet achieves the highest F1-score of 91.80%, 90.99%, and 96.04% on the WHU-CD, LEVIR-CD, and CDD-CD datasets, respectively, outperforming eleven state-of- the-art methods. Moreover, the effects of varying image sizes on model training are thoroughly analyzed. © 1980-2012 IEEE.

关键词： Change detection

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Multi-Source Data with Laplacian Eigenmaps and Denoising Autoencoder for Predicting Microbe-Disease Associations via Convolutional Neural Network

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Journal of computer science and Technology 2025年第2期40卷 588-604页

作者： Lei, Xiu-Juan Chen, Ya-Li Pan, Yi School of Computer Science Shaanxi Normal University Xi’an710119 China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Science Shenzhen518055 China

Identifying microbes associated with diseases is important for understanding the pathogenesis of diseases as well as for the diagnosis and treatment of diseases. In this article, we propose a method based on a multi-source association network to predict microbe-disease associations, named MMHN-MDA. First, a heterogeneous network of multi-molecule associations is constructed based on associations between microbes, diseases, drugs, and metabolites. Second, the graph embedding algorithm Laplacian eigenmaps is applied to the association network to learn the behavior features of microbe nodes and disease nodes. At the same time, the denoising autoencoder (DAE) is used to learn the attribute features of microbe nodes and disease nodes. Finally, attribute features and behavior features are combined to get the final embedding features of microbes and diseases, which are fed into the convolutional neural network (CNN) to predict the microbe-disease associations. Experimental results show that the proposed method is more effective than existing methods. In addition, case studies on bipolar disorder and schizophrenia demonstrate good predictive performance of the MMHN-MDA model, and further, the results suggest that gut microbes may influence host gene expression or compounds in the nervous system, such as neurotransmitters, or metabolites that alter the blood-brain barrier. © Institute of Computing Technology, Chinese Academy of sciences 2025.

关键词： Convolutional neural networks

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Evolving Multi-Access Edge Computing (MEC) for Diverse Ubiquitous Resources Utilization: A Survey

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Telecommunication Systems 2025年第2期88卷 1-41页

作者： Khattak, Muhammad Ilyas Yuan, Hui Khan, Ajmal Ahmad, Ayaz Ullah, Inam Ahmed, Manzoor School of Control Science and Engineering Shandong University Jinan Shandong Province China Communication and Information Research Center Sultan Qaboos University Muscat Oman Department of Electrical Engineering College of Engineering King Faisal University Al-Ahsa Saudi Arabia School of Computer Science and Technology Shandong Jianzhu University (SDJZU) Jinan China School of Computer and Information Science and AI Industrial Technology Research Hubei Engineering University Xiaogan China

The surge in smart device usage and the demand for high-throughput, low-latency mobile networks have accelerated the adoption of distributed smart applications and Collaborative Resource Management (CRM) techniques such as Multi-Access Edge Computing (MEC). With its ability to handle large data volumes, computational demands, scalability, and high energy consumption, MEC represents the next generation of Mobile Cloud Computing (MCC), addressing key challenges in emerging smart applications. MEC supports real-time, high-throughput, and energy-efficient techniques like task offloading and ultra-reliable low-latency communication (URLLC). However, as these techniques become more widespread, their diversity increases, leading to complexities that make them harder to understand and validate in different applications. This includes their use in areas like assistance for unmanned vehicles (UVs), autonomous driving, unmanned aerial vehicles (UAVs), high altitude platforms (HAPs), underwater unmanned vehicles (UUVs), satellite air-ground communication (SAGC), and other emerging systems that rely on Collaborative Resource Management (CRM). Although a number of review articles pertaining to MEC systems exist, we analyzed techniques beyond task offloading that explore MEC system applicability in diverse domains, including UUVs, vehicular edge computing, Re-configurable Intelligent Surfaces (RIS), Massive MIMO, autonomous driving, HAPs, and SAGC. From the perspective of these optimization techniques, this article highlights their role in shaping MEC’s evolution, focusing on parameters such as real-time response, energy efficiency, and other critical factors in task offloading processes. We also explored the role of Standard Development Organizations (SDOs), such as ETSI and IEEE, in advancing MEC systems. This included an analysis of offloading techniques based on their principles, features, and trade-offs, using key performance indicators (KPIs) for fair comparison, while ident

关键词： Computation offloading

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GCAT: Gated Convolutional Attention Transformer for Efficient Image Super-Resolution

GCAT: Gated Convolutional Attention Transformer for Efficien...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhijian Wu Kaiyi Feng Dingjiang Huang School of Data Science and Engineering East China Normal University Shanghai China School of Control and Computer Engineering North China Electric Power University Hebei China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recently, Transformer-based methods have achieved impressive performance in many computer vision tasks (e.g., image super-resolution (SR)) due to the advantages of long-range modeling. However, the computational cost requirement renders these methods unsuitable on resource-constrain devices, especially for image SR tasks involving high-resolution images. In this paper, we propose a concise and effective Gated Convolutional Attention Unit (GCAU) that uses cheap convolutional operations. Specifically, GCAU consists of Convolutional Transposed Attention (CTA) and Locally-enhanced Gating (LeG) in parallel. The former allows for efficient modeling of the global relational interactions by calculating cross-covariance across channels dimension, while the latter controls the information flow from the former directing the network to focus on more refined image attributes. Without bells and whistles, we present a simple SR Transformer GCAT by cascading the GCAUs. Extensive experimental results demonstrate that our GCAT achieves state-of-the-art performance among the existing efficient SR methods with significantly less complexity. Especially, GCAT is on average 5× faster than SwinIR-light with comparable performance.

关键词： Legged locomotion Performance evaluation computer vision Convolution Computational modeling Superresolution Logic gates Transformers Speech processing Signal resolution

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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Generation of n-dimensional complex chaotic system via parameter matrix configuration

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Chaos, Solitons and Fractals 2025年 197卷

作者： Yao, Jinhui Zhang, Yinxing Bao, Han Hua, Zhongyun School of Computer Science and Technology Harbin Institute of Technology Shenzhen Guangdong518055 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China

Complex chaotic systems can exhibit high chaotic complexity due to the presence of complex variables and complex parameters. Most research has focused on real chaotic systems, but complex chaotic systems remain relatively under-explored. To this end, this work presents an n-dimensional complex chaotic system (nD-CCS) generation method utilizing complex parametric Pascal matrices. Initially, these matrices are generated and subsequently utilized as the parameter matrices for constructing the nD chaotic systems. Theoretical analysis demonstrates that the proposed nD-CCS can exhibit chaotic behavior. Extensive experiments show that the nD-CCS possesses more robust chaotic performance than existing nD real chaotic systems. To demonstrate the effectiveness of our method, a four-dimensional complex chaotic map (4D-CCM) is generated and its chaotic behavior is analyzed. Furthermore, we develop a hardware platform to verify the 4D-CCM's implementation on hardware devices. We also design pseudorandom number generators (PRNGs) using the 4D-CCM and test their randomness against the NIST SP800-22 standard. The result indicates excellent randomness in the PRNGs. © 2025

关键词： computer peripheral equipment

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CASI: Context-aware Automatic Semantic Inference by fusing video and network traffic information in industrial control systems

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Information Fusion 2025年 122卷

作者： Hetu, Zheqiu Zhang, Zhenyong Wang, Mufeng Xv, Zidong Meng, Jie State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China State Key Laboratory of Industrial Control Technology and College of Control Science and Engineering Zhejiang University Hangzhou310027 China

The increasing adoption of Internet of Things devices in Industrial control Systems (ICS) has provided both attackers and security professionals with new perspectives on these traditionally safety-critical systems. Our observations reveal that video captured by field-deployed cameras contains process variables (PVs) essential for both ICS attack and defense. Based on this insight, we propose a Context-Aware Semantic Inference (CASI) method. CASI integrates video information from cameras with network traffic to infer the physical semantics of PVs in network packets, serving as a tactical tool for attackers or security professionals. A key advantage of CASI is its non-intrusive nature, deriving PVs location in the packets and semantics solely from video and network traffic without interacting with the runtime ICS, which is both covert and ensures the uninterrupted operation of the system. We constructed an ICS testbed using real devices to replicate a simplified industrial process, collecting traffic from 2 industrial protocols and creating 4 datasets. We evaluated CASI's precision and recall in detecting PVs within this context, comparing it with similar tools. Experimental results demonstrate that CASI achieves a recall rate of 1.00 in PV semantic extraction, significantly outperforming other tools. Furthermore, leveraging CASI-derived semantic information for data tampering attacks successfully disrupted monitoring and data acquisition programs, posing a severe security threat to the ICS. © 2025 Elsevier B.V.

关键词： Reverse engineering

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C4F6 Etching Characteristics for High-Aspect-Ratio Etching of SiO2 Films Using an Inductively Coupled Plasma Etching System With Low-Frequency Bias Power

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Plasma Processes and Polymers 2025年第0期

作者： Wei, Jiachen Woo, Byungjun Lee, DaeKug Jeong, Ki-Hyeok Kwon, Kwang-Ho Department of Control and Instrumentation Engineering Korea University-Sejong Campus Sejong Korea Republic of Department of Computer and Information Science Korea University-Sejong Campus Sejong Korea Republic of

In this study, the etching characteristics of C4F6 gas are investigated using inductively coupled plasma (ICP) etching equipment to apply a high-aspect-ratio etching process to SiO2. The use of a CF4 + C4F6 + He gas mixture in the ICP etching system provides a lower F atom density, a higher polymerization capacity with increasing C4F6 gas proportion, and better SiO2/amorphous carbon layer selectivity. With an increase in the C4F6 gas mixing ratio, the bowing phenomenon is alleviated, and a vertically etched profile is formed regardless of the source and bias power. The etching characteristics demonstrate that ICP etching using C4F6 gas is an excellent alternative to capacitively coupled plasma (CCP) etching for the development of next-generation high-aspect-ratio-contact etching processes. © 2025 Wiley-VCH GmbH.

关键词： Aspect ratio

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Geometric Reachability for Attitude control Systems via Contraction Theory

arXiv

引用

arXiv 2025年

作者： Xu, Chencheng Jafarpour, Saber Zhao, Chengcheng Shi, Zhiguo Chen, Jiming College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO United States College of Control Science and Engineering Zhejiang University Hangzhou China

In this paper, we present a geometric framework for the reachability analysis of attitude control systems. We model the attitude dynamics on the product manifold SO(3) × 3 and introduce a novel parametrized family of Riemannian metrics on this space. Using contraction theory on manifolds, we establish reliable upper bounds on the Riemannian distance between nearby trajectories of the attitude control systems. By combining these trajectory bounds with numerical simulations, we provide a simulation-based algorithm to over-approximate the reachable sets of attitude systems. We show that the search for optimal metrics for distance bounds can be efficiently performed using semidefinite programming. Additionally, we introduce a practical and effective representation of these over-approximations on manifolds, enabling their integration with existing Euclidean tools and software. Numerical experiments validate the effectiveness of the proposed approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Geometry

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Applying System Thinking to Learn from Accident of Modern Automatic control Systems

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Chinese Journal of Electronics 2025年第2期23卷 409-414页

作者： Ru Niu Yuan Cao Xiaocheng Ge Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronics and Information Engineering National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Department of Computer Science University of York York UK

Modern societies increasingly rely on automatic control systems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events, rather than a simple cause-effect chain. We take railway Train control systems (TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP - one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.

关键词： Sociotechnical systems Analytical models Systematics Railway accidents Transportation Medical services Rail transportation Systems thinking Research and development Accidents

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