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24th International Conference on Algorithms and Architectures for Parallel processing, ICA3PP 2024

作者： Xu, Xiaofeng Zhang, Weisha Huang, Yuanyuan Lu, Hongyu Lu, Jiazhong School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China School of Foreign Languages University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9789819615247

The detection of fake news is not confined to a single domain, and due to domain transfer, the reliance on detection methods specific to a single domain becomes inadequate when dealing with multi-domain issues. When a multi-domain detection occurs, labels from one domain focus exclusively on the news characteristics of that particular domain, ignoring the possibility that part of the news may include functions from more than one domain. To address these challenges, we propose a multi-domain fake news detection model based on fuzzy rules, incorporating a fuzzy mechanism and an optimization module for fuzzy association rules. In this model, we first introduce a fuzzy mechanism that applies fuzzy processing to domains through neural networks, constructing fuzzy domain labels for each news domain. Subsequently, we incorporate fuzzy association rules to extract a broader range of sample features, thereby enhancing detection effectiveness. Experiments conducted on a fake news dataset demonstrate that our model achieves commendable detection performance with a relatively low training cost, reaching an F1 score of over 97.13% for sample detection. This model successfully overcomes the limitations of single-domain detection in fake news identification and improves the precision of feature extraction through fuzzy rules, showing superior performance in handling multi-domain fake news detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fake news detection fuzzy rules multi-domain social media

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Prediction of Distributed Photovoltaic Accommodation Capability Based on Ridge Regression 9th

Prediction of Distributed Photovoltaic Accommodation Capabil...

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9th Purple Mountain Form on Smart Grid Protection and control, PMF 2024

作者： Ji, Xingquan Zhang, Bowen Zhang, Yumin Sun, Pengkai Zhang, Xiaofeng Liu, Wei dong Shandong University of Science and Technology Qingdao266590 China Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250061 China Information and Communication Company State Grid Shandong Electric Power Company Jinan250013 China Qingdao Yihe Electric Group Co. Ltd. Qingdao266510 China

ISBN: (纸本)9789819616701

A prediction method of distributed photovoltaic accommodation capability is proposed based on ridge regression. First, the factors influencing the distributed photovoltaic accommodation capacity are analyzed, and the concept of the contribution degree of distributed photovoltaic accommodation is introduced. The gray relation analysis method is used to evaluate the correlation between different factors and distributed photovoltaic accommodation, and a model of factors affecting distributed photovoltaic accommodation is constructed. Then, a prediction model of distributed photovoltaic accommodation capability is established based on ridge regression. The factors with high photovoltaic accommodation contribution degrees are incorporated in the prediction model. The mapping relationship between the driving factors of distributed photovoltaic accommodation and the prediction model is derived, then the development strategies for future photovoltaic accommodation capacity are formulated. Finally, simulation is performed on the SPSSPRO platform, and the results show that the proposed method can predict the distributed photovoltaic accommodation capability accurately and provide strategic suggestions for improving future photovoltaic accommodation capacity. © State Grid Electric Power 2025.

关键词： Photovoltaics

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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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A New Dual-Population Evolutionary Algorithm Leveraging Objective-Constraint Relationships for Constrained Multi-Objective Optimization

SSRN

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SSRN 2025年

作者： Ye, Jialu Tan, Chaogui Xia, Yizhang Hou, Zhanglu Liu, Yuan Zou, Juan Hunan Engineering Research Center of intelligent System Optimization and Security Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Hunan National Applied Mathematics Center China Xiangtan University China

Population co-evolution strategies are widely used to handle constrained multi-objective optimization problems (CMOPs). However, existing coevolutionary algorithms oversimplify population collaboration and are rigid in evolving the auxiliary population, ignoring the importance of maintaining population diversity, especially for CMOPs with irregular feasible regions. To tackle this issue, we propose a new dual-population evolutionary algorithm, denoted as AACMO, which attempts to mine the relational features between the unconstrained Pareto front (UPF) and the constrained Pareto front (CPF) to better adapt to CMOPs with various constraints. Specifically, the method is categorized into two phases: a learning phase and an evolving phase. First, the main population (MP) aims to quickly learn the relationships between the UPF and the CPF by leveraging the advantages of different operators, namely, genetic algorithm operators and differential evolution operators, during the learning phase. Secondly, two auxiliary strategies are designed to collaborate with the MP during the evolving phase. These strategies are capable of employing a more effective co-evolution method to assist the MP in maintaining diversity, based on the degree of alignment between the learned UPF and CPF at the end of the learning phase. The effectiveness of AACMO is confirmed through comparative analysis with eight state-of-the-art algorithms across four CMOP benchmark suites. © 2025, The Authors. All rights reserved.

关键词： Optimization algorithms

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Single-Loop Deadbeat Predictive control Framework for Uncertain SPMSM Drives With Disturbance Observation

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IEEE Transactions on Transportation Electrification 2025年

作者： Jiang, Fuxi Wang, Siqi Guo, Yuhao Cheng, Zhe Ye, Jie Cheng, Shanmei Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology School of Optical and Electronic Information Wuhan430074 China

To mitigate the detrimental effects of parameter perturbations and external load torque on the accuracy of speed and current tracking control in surface-mounted permanent magnet synchronous motor (SPMSM) drive systems, while avoiding the complexities inherent in traditional speed-current series control architectures, this paper presents a single-loop deadbeat predictive control (SDPC) framework that incorporates online disturbance observation. The control input voltage vector is directly computed using an SDPC controller in conjunction with a set of discrete-time disturbance observers (DDOBs). This proposed methodology offers two notable advantages over existing research: (i) it substantially reduces the number of adjustable controller parameters, requiring only the tuning of the observer bandwidth and the speed scaling gain, which enhances its practicality for engineering applications;and (ii) the disturbance estimation and compensation mechanism utilizing DDOBs significantly improves the robustness of the SPMSM system. Furthermore, the SDPC framework ensures that the system maintains satisfactory transient and steady-state tracking performance in response to reference signals. Experimental comparisons validate both the effectiveness and superiority of the proposed method. © 2015 IEEE.

关键词： Permanent magnets

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LSU-NET: LIGHTWEIGHT AUTOMATIC ORGANS SEGMENTATION NETWORK FOR MEDICAL IMAGES

arXiv

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arXiv 2025年

作者： Ding, Yujie Teng, Shenghua Li, Zuoyong Chen, Xiao College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control School of Computer and Big Data Minjiang University Fuzhou350121 China

UNet and its variants have widespread applications in medical image segmentation. However, the substantial number of parameters and computational complexity of these models make them less suitable for use in clinical settings with limited computational resources. To address this limitation, we propose a novel Lightweight Shift U-Net (LSU-Net). We integrate the Light Conv Block and the Tokenized Shift Block in a lightweight manner, combining them with a dynamic weight multi-loss design for efficient dynamic weight allocation. The Light Conv Block effectively captures features with a low parameter count by combining standard convolutions with depthwise separable convolutions. The Tokenized Shift Block optimizes feature representation by shifting and capturing deep features through a combination of the Spatial Shift Block and depthwise separable convolutions. Dynamic adjustment of the loss weights at each layer approaches the optimal solution and enhances training stability. We validated LSU-Net on the UWMGI and MSD Colon datasets, and experimental results demonstrate that LSU-Net outperforms most state-of-the-art segmentation architectures. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolution

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Learning to Learn Transferable Generative Attack for Person Re-Identification

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IEEE Transactions on Image processing 2025年 PP卷 PP页

作者： Bian, Yuan Liu, Min Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning-based person re-identification (reid) models are widely employed in surveillance systems and inevitably inherit the vulnerability of deep networks to adversarial attacks. Existing attacks merely consider cross-dataset and cross-model transferability, ignoring the cross-test capability to perturb models trained in different domains. To powerfully examine the robustness of real-world re-id models, the Meta Transferable Generative Attack (MTGA) method is proposed, which adopts meta-learning optimization to promote the generative attacker producing highly transferable adversarial examples by learning comprehensively simulated transfer-based crossmodel&dataset&test black-box meta attack tasks. Specifically, cross-model&dataset black-box attack tasks are first mimicked by selecting different re-id models and datasets for meta-train and meta-test attack processes. As different models may focus on different feature regions, the Perturbation Random Erasing module is further devised to prevent the attacker from learning to only corrupt model-specific features. To boost the attacker learning to possess cross-test transferability, the Normalization Mix strategy is introduced to imitate diverse feature embedding spaces by mixing multi-domain statistics of target models. Extensive experiments show the superiority of MTGA, especially in cross-model&dataset and cross-model&dataset&test attacks, our MTGA outperforms the SOTA methods by 20.0% and 11.3% on mean mAP drop rate, respectively. © 1992-2012 IEEE.

关键词： Generative adversarial networks

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Event-triggered MPC Design for Distributed systems With Network Communications

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 240-250页

作者： Xiaoxiao Mi Shaoyuan Li Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University

This paper deals with the communication problem in the distributed system, considering the limited battery power in the wireless network and redundant transmission among nodes. We design an event-triggered model predictive control(ET-MPC) strategy to reduce the unnecessary communication while promising the system performance. On one hand, for a linear discrete time-invariant system, a triggering condition is derived based on the Lyapunov stability. Here, in order to further reduce the communication rate, we enforce a triggering condition only when the Lyapunov function will exceed its value at the last triggered time, but an average decrease is guaranteed. On the other hand, the feasibility is ensured by minimizing and optimizing the terminal constrained set between the maximal control invariant set and the target terminal set. Finally, we provide a simulation to verify the theoretical results. It's shown that the proposed strategy achieves a good trade-off between the closed-loop system performance and communication rate.

关键词： Event-triggered control Lyapunov stability model predictive control(MPC) terminal invariant set

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Performance-Aware control of Modular Batteries For Fast Frequency Response

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IEEE Transactions on Sustainable Energy 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Massachusetts Institute of Technology Lab for Information and Decision Systems CambridgeMA02139 United States

Modular batteries can be aggregated to deliver frequency regulation services for power grids. Although utilizing the idle capacity of battery modules is financially attractive, it remains challenging to consider the heterogeneous module-level characteristics such as dynamic operational efficiencies and battery degradation. In addition, real-time decision making within seconds is required to enable fast frequency response. In order to address these issues, this paper proposes a performance-aware scheduling approach for battery modules to deliver fast frequency response (FFR) support. In particular, the conduction loss and switching loss of battery packs as well as converters are captured within a mix-integer quadratic constrained program (MIQCP). The cycle-based aging model identifies the aging cost of battery modules during frequent cycling by introducing the aging subgradient calculation and linearization. Case studies based on real-world battery data show that the proposed scheduling approach can effectively reduce power loss cost by nearly 28%-57% and battery aging cost by 4%-15% compared to conventional methods, which can also enhance the SoC balance. © 2010-2012 IEEE.

关键词： Battery management systems

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Autonomous and Incentivized Wireless Connection for Robust Mobile Blockchain Network

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IEEE Transactions on Mobile Computing 2025年

作者： Wang, Weiyi Jiao, Yutao Chen, Jin Kang, Jiawen Xu, Yuhua Army Engineering University of Pla College of Communications Engineering Nanjing210007 China Guangdong University of Technology School of Automation Guangzhou510006 China Ministry of Education Key Laboratory of Intelligent Information Processing and System Integration of IoT Guangzhou510006 China

Blockchain has been widely implemented as a trusted platform. Previous works mainly focus on the computing capacity of devices while communication factors play a vital role in blockchain performance during dynamic wireless environments. High-speed movement causes frequent wireless connection interruptions and leads to severe performance degradation of blockchain. Besides, resource-constrained mobile devices are unwilling to selflessly contribute their energy and bandwidth for blockchain, hindering applications in dynamic mobile networks. This paper proposes a reverse auction mechanism to incentivize mobile devices to provide robust wireless connections. Devices submit their connection provision and expected rewards as bids. The mobile blockchain system uses smart contracts to autonomously execute the reverse auction to determine winners and allocate payments based on actual connections. We prove that the reverse auction mechanism is Individual Rationality (IR), Incentive Compatibility (IC), and Computational Efficiency (CE), and derive the approximation ratio 2σ of the mechanism. Extensive simulation results demonstrate that the proposed mechanism decreases up to half the energy and bandwidth consumption, but achieves a similar TPS and stale rate compared to the selfless scheme, where devices contribute all wireless connections for nothing in return. The proposed auction mechanism achieves more than 96% of the optimal social welfare. © 2002-2012 IEEE.

关键词： Dynamic mobile network incentive mechanism mobile blockchain reverse auction

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