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2nd International Conference on Artificial Intelligence, Systems and Network Security, AISNS 2024

作者： Wan, Qin Ning, Shunxing Xu, Pin Li, Zhi Hunan Institute of Engineering Hunan Xiangtan China National Engineering Research Center for Robot Visual Perception and Control Technology Hunan Changsha China

ISBN: (纸本)9798400711237

This paper proposes a vision-based formation control method for multi-robot systems in the absence of inter-robot communication, employing a leader-follower scheme with a single Kinect camera as the sole sensor. By utilizing a pose estimation algorithm based on RGBD images, the relative position and orientation of the leader are captured. An anticipated formation shape aligned in the same movement direction is generated using a dipole vector field, ensuring formation stability. To address the limited field of view of the Kinect camera, an auxiliary system is designed to transform visibility constraints into input constraints, enabling effective control under non-communicative conditions. Simulation and experimental results demonstrate that the proposed method achieves real-time and robust formation control despite visibility limitations, simplifying the system architecture and enhancing practicality. © 2024 Copyright held by the owner/author(s).

关键词： Mobile robots

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A Nonlinear Input-Output-Based Model for Medium-Term Macroeconomic Risks Analysis for a Restructuring Economy with Limited Capacities 15th

A Nonlinear Input-Output-Based Model for Medium-Term Macroe...

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15th International Conference on Optimization and Applications, OPTIMA 2024

作者： Obrosova, Nataliia Spiridonov, Alexander Federal Research Center Computer Science and Control of the Russian Academy of Sciences 40 Vavilov st. Moscow119333 Russia

ISBN: (纸本)9783031791185

Nowadays global shifts in supply networks state the problem of building of new mathematical models to analyze medium-term macroeconomic risks of local economies in view of important economic restrictions and substitution of production factors. The methods are most importantly for catching-up economies with high rates of economic growth. In the paper we suggest the nonlinear generalization of Leontief Input-Output approach which supposes the possibility of inputs substitution in a production network in conditions of industrial capacity limitations. We state and investigate the competitive equilibrium evaluation problem in the space of intersectoral cash flows and prices as a pair of Young dual convex optimization problems. In the case of CES production we have an explicit solution that gives the equilibrium point of the problem, which includes the dependence on shadow prices which are the result of capacities lack. Based on official statistics we discuss the model application to evaluation of inflation risks in fast developing Kazakhstan economy. In terms of the model we analyze inflation risks caused by the possible lack of infrastructure services in scenario conditions based on the official macroeconomic forecast of Kazakhstan. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Inflation

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Convolution Algorithm for Evaluation of Probabilistic Characteristics of Resource Loss Systems with Signals 27th

Convolution Algorithm for Evaluation of Probabilistic Char...

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27th International Conference on Distributed Computer and Communication Networks, DCCN 2024

作者： Maslov, A.R. Sopin, E.S. Shorgin, S.Ya. Moscow Russia Institute of Informatics Problems Federal Research Center Computer Science and Control of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031808524

Resource loss systems (ReLS) with signals, in which arrival of a signal triggers resource reallocation of a customer, are often used in the performance analysis of the contemporary mobile networks, especially those that utilize high-frequency bands. An analytical solution for the stationary distribution of such systems is not obtained yet. Approximate calculation methods utilize the stationary distribution of ReLS without signals at the departure instants. In the paper, we develop an efficient convolution algorithm for evaluation of the probability metrics at the departure instants. In the case study, we demonstrate the effectiveness of the proposed algorithm in terms of execution time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Markov chains

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Composite intelligent learning-based tracking control for discrete-time repetitive process

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ISA Transactions 2025年 160卷 122-130页

作者： Yang, Rongni Hao, Jianqiang Shi, Peng Rudas, Imre J. School of Control Science and Engineering Shandong University Jinan Shandong250061 China School of Electrical and Mechanical Engineering University of Adelaide AdelaideSA5005 Australia Research and Innovation Centre Óbuda University BudapestH-1034 Hungary

In this work, a new composite iterative learning control (ILC) algorithm for the tracking issue of a class of discrete-time systems that operate repetitively over a finite time duration is developed. Particularly, the proposed intelligent learning process consists of two phases to achieve an enhanced tracking performance: the gain-adaptive iterative learning control (GAILC) phase and the sliding mode iterative learning control (SMILC) phase, respectively. Moreover, the switching of the two phases is determined by the tracking error. For GAILC phase, a prediction of tracking error based adaptive gain sequence is adopted to achieve a fast convergence in tracking error. For SMILC phase, an appropriate sliding surface function in the iteration domain is established, and then a novel SMILC law with a fractional power term is presented to achieve a high tracking precision. Finally, comparative simulations including a DC motor example are provided to validate the effectiveness and advantage of the proposed ILC strategy. © 2025 International Society of Automation

关键词： DC motors

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The Client-Level GAN-Based Data Reconstruction Attack and Defense in Clustered Federated Learning 18th

The Client-Level GAN-Based Data Reconstruction Attack and D...

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Wu, Han Shi, Lei Ye, Junyu Fan, Yuqi Lv, Zengwei School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

ISBN: (纸本)9783031714634

Clustered Federated Learning (CFL) is an innovative architecture that effectively tackles the challenge of data heterogeneity in Federated Learning (FL). However, such a setup also introduces vulnerabilities that can be exploited by attackers to execute more severe attacks. This paper compares the efficacy of data reconstruction attacks utilizing Generative Adversarial Nets (GANs) in FL and CFL, respectively. It also proposes a general client-level data reconstruction attack scheme whose key is in that the attackers can eavesdrop the victim’s partial uploaded parameters. Experimental results demonstrate that the sample data generated in this kind of attack within the scenario of CFL exhibit a higher degree of similarity with the targeted data compared to FL. And it is observed that the attacks involving eavesdropping in CFL perform more effectively with a client-level attack accuracy. In addition, we design a lightweight and adaptive local differential privacy (LDP) mechanism to defend against this kind of attack. In this method, under the premise that the differential privacy budget decreases as the number of training round adds, each client dynamically adjusts the probability of adding differential privacy noise and the size of DP’s parameters according to the training accuracy and the resemblance to the reconstructed data generated by attackers. Our defense method can effectively alleviate the loss of training accuracy for each client caused by the accumulation of the differential privacy budget while ensuring the defense effect, and it also reduces clients’ computational burden. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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Infrared image and circular polarization image processing methods for high-concentration scattering environments

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Applied Optics 2025年第12期64卷 3140-3149页

作者： Zhao, Dengke Wei, Yongqing Hong, Lu Xia, Haojie Huang, Liang Zhang, Jin School of Instrument Science and Opto-electronics Engineering Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Measuring Theory and Precision Instrument Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

In high-concentration scattering media, low contrast often obscures the surface details and textures of target objects. This paper proposes a method to enhance imaging quality under such conditions using polarization imaging theory. The method involves image registration, estimation of environmental transmittance, calculation of the degree of polarization and polarization difference intensity, and application of the CLAHE method to improve detail visibility and obtain de-scattered images. Finally, a weighted adaptive wavelet transform based on edge detection fuses the de-scattered and infrared images. Experimental results show that the proposed method outperforms traditional approaches, particularly in high-concentration scattering environments, offering insights into combining infrared and polarized imaging for challenging scenarios. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Circular polarization

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The State-of-the-Art in Catalyst Performance Evaluation for Automobile Emission control in China

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Emission control science and Technology 2025年第1期11卷 1-18页

作者： Liu, Xi Shao, Yuankai Wang, Maoxuan Dong, Anqi Liu, Yatao Ren, Xiaoning Li, Kaixiang Zhou, Bingjie Zhu, Weikang Wu, Hanming Li, Zhenguo National Engineering Laboratory for Mobile Source Emission Control Technology China Automotive Technology & Research Center Co. Ltd Tianjin300300 China

Emission control catalysts are the primary means of mitigating automobile exhaust pollution, and diverse catalysts have been developed, including TWC, MOC, ASC, DOC, NDC, and others. To further decrease vehicle emissions and enhance overall air quality, continuous upgrades of these catalysts are necessary. The methodologies and standards for evaluating the performance of automobile emission control catalysts are pivotal for their technological advancement. While various countries have issued regulations outlining test items, procedures, and evaluation indicators for engine bench and whole-vehicle emission assessments, no universally recognized evaluation methods or protocols exist for laboratory simulation evaluations of catalyst performance. This paper initially introduces the technical pathways for emission control in vehicles using diverse fuels. Subsequently, it comprehensively reviews the activity and lifespan evaluation methods for emission control catalysts across three levels: laboratory simulation, engine bench, and whole-vehicle evaluations, providing relevant evaluation standards for reference. It elaborates on laboratory simulation evaluation techniques, test conditions, and performance indicators for different catalysts, analyzes catalyst deactivation mechanisms, and summarizes research advancements in durability evaluation methods. Lastly, the paper prospects the future focus of research on performance evaluation methodologies for automobile emission control catalysts. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Emission control

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Exploiting neonatal host-bifidobacteria interactions to promote intestinal pathogen tolerance and barrier function:Bifidobacterium longum *** outperforms Bifidobacterium adolescentis in anti-Salmonella activity and maintenance of intestinal hom

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Food science and Human Wellness 2025年第4期14卷 1343-1359页

作者： Chunxiu Lin Shunhe Wang Min Guo Wentian Li Jiayin Qiu Yonghua Zhou Hao Zhang Wei Chen Gang Wang State Key Laboratory of Food Science and Resources Jiangnan UniversityWuxi 214122China School of Food Science and Technology Jiangnan UniversityWuxi 214122China Key Laboratory of National Health Commission on Parasitic Disease Control and Prevention Jiangsu Provincial Key Laboratory on Parasite and Vector Control TechnologyJiangsu Institute of Parasitic DiseasesWuxi 214064China National Engineering Research Center for Functional Food Jiangnan UniversityWuxi 214122China Wuxi Translational Medicine Research Center and Jiangsu Translational Medicine Research Institute Wuxi Branch Wuxi 214122China (Yangzhou)Institute of Food Biotechnology Jiangnan UniversityYangzhou 225004China

Bifidobacterium longum *** and Bifidobacterium adolescentis play important roles in the guts of infants and adolescents,*** this study,using a neonatal rat model,we compared the protective effects of these 2 bifidobacterial species against Salmonella *** results demonstrated that *** *** was more effective than *** in alleviating the severity of infection in newborn rats exposed to Salmonella enterica serovar Typhimurium strain *** *** attenuated intestinal inflammation and mucosal damage induced by Salmonella infection,as well as protecting intestinal nerves and intestinal barrier function through TLR4/My D88 *** *** also displayed the potential to modulate gut metabolites by promoting the biosynthesis of unsaturated fatty acids(arachidonic acid,eicosapentaenoic acid andα-linolenic acid)and purine metabolism(guanine,adenine,inosine and adenosine),thereby regulating metabolic ***,the benefits of *** *** were also observed in the liver,spleen and brain,improving nerve reflexes and suppressing ***,these findings provide novel insights into the prevention and treatment of gutrelated diseases in newborns,highlighting the potentially significant role of *** *** in clinical applications.

关键词： Salmonella infection Bifidobacterium longum subsp.infantis Bifidobacterium adolescentis Newborn Intestinal inflammation

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Anti-Interference High-Speed Modulation Decoder for Quantum Key Distribution

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Chinese Physics Letters 2025年第1期42卷 34-39页

作者： Hua-Xing Xu Shao-Hua Wang Chang-Lei Wang Ping Zhang National Engineering Research Center for Public Safety Risk Perception and Control by Big Data China Academic of Electronics and Information TechnologyBeijing 100041China CETC Academy of Electronics and Information Technology Group Co. Ltd.Beijing 100041China

Quantum key distribution is increasingly transitioning toward network applications,necessitating advancements in system performance,including photonic integration for compact designs,enhanced stability against environmental disturbances,higher key rates,and improved *** this letter,we propose an orthogonal polarization exchange reflector Michelson interferometer model to address quantum channel disturbances caused by environmental *** on this model,we designed a Sagnac reflector-Michelson interferometer decoder and verified its performance through an interference *** interference fringe visibility exceeded 98%across all four coding phases at 625 *** results indicate that the decoder effectively mitigates environmental interference while supporting high-speed modulation *** addition,the proposed anti-interference decoder,which does not rely on magneto-optical devices,is well-suited for photonic integration,aligning with the development trajectory for next-generation quantum communication devices.

关键词： decoder interferometer polarization

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A Method for Abnormal Detection and Poisoned Data Recovery in Clustered Federated Learning 18th

A Method for Abnormal Detection and Poisoned Data Recovery...

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Chen, Yingying Shi, Lei Xu, Hao Ye, Junyu Xu, Juan School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

ISBN: (纸本)9783031714665

Clustered Federated Learning (CFL), as a type of Federated Learning (FL) paradigm, divides the clients into multiple clusters through the clustering process and trains them within the clusters, thus improving the overall model training accuracy. But the clustering process is also the weak link, which can lead to the failure of the whole model training if it is interfered or destroyed by the attacker. In this paper, we study the attack methods and defense strategies for attackers to implement data poisoning by tampering with client data, resulting in overall clustering failure. Our defense approach is designed to identify anomalous clients and recover their poisoned data. In order to resist the malicious behavior of attackers, we propose a dual-threshold pixel difference and watermark authentication defense method for detecting the presence of anomalous clients. The method can accurately identify the abnormal fluctuations in the data and effectively screen out the abnormal clients. Meanwhile, we propose a self-embedding watermarking defense algorithm based on shuffling idea for recovering poisoned data. Among them, our self-embedding watermarking algorithm not only accurately locates and recovers the tampered region of the image, but also improves the watermark security to prevent attackers from cracking it easily. Simulation results show that our proposed algorithm can accurately identify the abnormal client and recover the data. Even if the client’s data is massively tampered with, we can recover the tampered data images with high quality and ensure that the CFL clustering is not corrupted. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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