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Application Layer Multicast Model with Low Delay and High Stability

Journal of Donghua University(English Edition) 2023年第1期40卷 74-79页

作者：廖小飞宣益亮宿轩策李德敏 College of Information Sciences and Technology Donghua UniversityShanghai 201620China Engineering Research Center of Digitized Textile&Fashion Technology Ministry of EducationDonghua UniversityShanghai 201620China

As an alternative of Internet protocol(IP)multicast,application layer multicast(ALM)is widely used with the advantage of simplicity and ***,the existing problems of large transmission delay and poor stability limit the application and *** this article,to solve these problems,an ALM model based on node potential(NP)and topological index(TI)is *** proposed model considers the factors of node capability and node distance in constructing and maintaining multicast tree to reduce transmission delay and increase stability,and thus it improves the application level in real-time multimedia *** computer simulations prove that the proposed model reduces the ALM transmission delay,increases multicast tree stability effectively,and improves the ALM performance,and therefore it is suitable to apply in large-scale real-time multimedia environment.

关键词： application layer multicast(ALM) high stability low delay node potential(NP) topological index(TI)

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A multi-scale dual moving horizon estimation method for state of charge of lithium-ion battery

A multi-scale dual moving horizon estimation method for stat...

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第42届中国控制会议

作者： Jiacheng Wen Xin Cai Engineering Research Center of Digitized Textile & Apparel Technology Ministry of EducationCollege of Information Science and Technology Donghua University

For the battery management system(BMS), accurate state of charge(SOC) estimation plays an important role in enhancing efficiency and ensuring safety of battery. Considering the tradeoff between accuracy of SOC and computational complexity, this paper proposes a multi-scale dual moving horizon estimation(MHE) algorithm, which incorporates a SOC estimator and a model parameters estimator using different time scales. Firstly, the state-space models of the SOC and parameters are built on basis of the equivalent circuit model and parametric sensitivity analysis, respectively. Secondly, the estimation problem of the model parameters is transformed into an optimization problem solved in a larger time scale used for the update of the SOC. Thirdly, the estimation problem of the SOC is solved in a smaller time scale used for the update of the model parameters. Finally, simulation results show that this method can effectively enhance accuracy and reduce computational burden compared with the methods such as MHE and dual EKF. The effect of the MHE window size on the SOC estimation is also discussed.

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Modified dynamic event-triggered scaled formation control for multi-agent systems via a sparrow search algorithm based co-design algorithm

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Frontiers of Information technology & Electronic engineering 2024年第2期25卷 197-213页

作者： Yanping YANG Siyu MA Dawei LI Jinghui SUO College of Information Science and Technology Donghua UniversityShanghai201620China Engineering Research Center of Digitized Textile&Apparel Technology Donghua UniversityShanghai201620China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Information Science and TechnologyDonghua UniversityShanghai201620China

This paper is concerned with the scaled formation control problem for multi-agent systems(MASs)over fixed and switching ***,a modified resilient dynamic event-triggered(DET)mechanism involving an auxiliary dynamic variable(ADV)based on sampled data is *** the proposed DET mechanism,a random variable obeying the Bernoulli distribution is introduced to express the idle and busy situations of communication ***,the operation of absolute value is introduced into the triggering condition to effectively reduce the formation ***,a scaled formation control protocol with the proposed resilient DET mechanism is designed over fixed and switching *** scaled formation error system is modeled as a time-varying delay ***,several sufficient stability criteria are derived by constructing appropriate Lyapunov-Krasovskii functionals(LKFs).A co-design algorithm based on the sparrow search algorithm(SSA)is presented to design the control gains and triggering parameters ***,numerical simulations of multiple unmanned aerial vehicles(UAVs)are presented to validate the designed control method.

关键词： Scaled consensus Formation control Dynamic event-triggered scheme Switching topology

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Dual-strategy Pose Estimation Network Based on Mask-RCNN

Dual-strategy Pose Estimation Network Based on Mask-RCNN

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第42届中国控制会议

作者： Haoyu Han Fengkang Ying Zuowei Pang Huashan Liu College of Information Science and Technology Donghua University Engineering Research Center of Digitized Textile & Apparel Technology Ministry of Education

6D pose estimation from a given input image is a key technology in computer vision and robotics,which has been broadly leveraged in robot operations,autonomous driving,and augmented *** current mainstream methods fall into two main categories,either regressing the rotation and translation directly from the image or constructing a 2D-3D correspondence and then solving the poses indirectly via *** this work,we propose a 6 D pose estimation method:a Mask-RCNN-based dual-strategy pose estimation ***,it divides the pose into two parts,rotation and translation,and uses two different strategies of pose estimation networks to solve the translation and rotation of the object separately,so as to improve the estimation's accuracy and ***,a Mask-based loss function is proposed to update the network and make it increasingly accurate in calculating the coordinates,where the coordinate points of the predicted object region are extracted from the local image by the Mask-RCNN prediction on the object ***,experiments are conducted on the LINEMOD dataset to demonstrate the superiority of our *** method is highly applicable and accurate to handle pose estimation problems for untextured and occluded objects.

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Optimal Scheduling for Shared Energy Storage Users Considering Both Construction and Operation of the Shared Energy Storage Station

Optimal Scheduling for Shared Energy Storage Users Consideri...

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Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Qicheng Xu Yinghao Shan Xueyang Wu Ziping Wang College of Information Science and Technology Donghua University Shanghai China Engineering Research Center of Digitized Textile and Apparel Technology Ministry of Education Shanghai China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

Shared energy storage is an emerging energy storage system. Optimal scheduling can maximize the resources of shared ESSs, thereby improving economic efficiency. This paper explores the optimal scheduling of electricity consumption behavior among shared energy storage users. Mixed integer linear programming is used to establish the optimal scheduling model, which is divided into two phases: construction and operation of the ESS. The efficacy of the proposed model is further corroborated through the selection of three industrial users based in Jiangsu Province. The analysis demonstrates that optimal scheduling can effectively curtail electricity costs for the users.

关键词： Electrical engineering Costs Power demand Job shop scheduling Electricity Asia Optimal scheduling

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A Dual Stream Multimodal Alignment and Fusion Network for Classifying Short Videos

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Journal of Donghua University(English Edition) 2025年第1期42卷 88-95页

作者： ZHOU Ming WANG Tong College of Information Science and Technology Donghua UniversityShanghai 201620China Engineering Research Center of Digitized Textile&Apparel Technology Ministry of EducationDonghua UniversityShanghai 201620China

Video classification is an important task in video understanding and plays a pivotal role in intelligent monitoring of information *** existing methods do not consider the multimodal nature of the video,and the modality fusion approach tends to be too simple,often neglecting modality alignment before *** research introduces a novel dual stream multimodal alignment and fusion network named DMAFNet for classifying short *** network uses two unimodal encoder modules to extract features within modalities and exploits a multimodal encoder module to learn interaction between *** solve the modality alignment problem,contrastive learning is introduced between two unimodal encoder ***,masked language modeling(MLM)and video text matching(VTM)auxiliary tasks are introduced to improve the interaction between video frames and text modalities through backpropagation of loss *** experiments prove the efficiency of DMAFNet in multimodal video classification *** with other two mainstream baselines,DMAFNet achieves the best results on the 2022 WeChat Big Data Challenge dataset.

关键词： video classification multimodal fusion feature alignment

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Multi-Target Federated Backdoor Attack Based on Feature Aggregation

arXiv

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arXiv 2025年

作者： Hao, Lingguag Hao, Kuangrong Wei, Bing Tang, Xue-Song College of Information Science and Technology Donghua University Shanghai201620 China Engineering Research Center of Digitized Textile & Apparel Technology Ministry of Education Shanghai201620 China

Current federated backdoor attacks focus on collaboratively training backdoor triggers, where multiple compromised clients train their local trigger patches and then merge them into a global trigger during the inference phase. However, these methods require careful design of the shape and position of trigger patches and lack the feature interactions between trigger patches during training, resulting in poor backdoor attack success rates. Moreover, the pixels of the patches remain untruncated, thereby making abrupt areas in backdoor examples easily detectable by the detection algorithm. To this end, we propose a novel benchmark for the federated backdoor attack based on feature aggregation. Specifically, we align the dimensions of triggers with images, delimit the trigger’s pixel boundaries, and facilitate feature interaction among local triggers trained by each compromised client. Furthermore, leveraging the intra-class attack strategy, we propose the simultaneous generation of backdoor triggers for all target classes, significantly reducing the overall production time for triggers across all target classes and increasing the risk of the federated model being attacked. Experiments demonstrate that our method can not only bypass the detection of defense methods while patch-based methods fail, but also achieve a zero-shot backdoor attack with a success rate of 77.39%. To the best of our knowledge, our work is the first to implement such a zero-shot attack in federated learning. Finally, we evaluate attack performance by varying the trigger’s training factors, including poison location, ratio, pixel bound, and trigger training duration (local epochs and communication rounds). © 2025, CC BY.

关键词： Federated learning

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Arbitrary Clothing Style Transfer Based on Attention Mechanism 27th

Arbitrary Clothing Style Transfer Based on Attention Mechan...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Huang, Chen Zhang, Junjie Yuan, Hua School of Computer Science and Artificial Intelligence Wuhan Textile University Wuhan430200 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430073 China Wuhan Textile and Apparel Digital Engineering Technology Research Center School of Fashion Wuhan Textile University Wuhan430073 China

ISBN: (纸本)9783031781247

In recent years, style transfer has become increasingly prominent in various domains, especially fashion. As a tool for designers, clothing style transfer generates a wide array of styles, enabling rapid experimentation and fostering creative inspiration. However, current methods have poor performance in transferring textures and colors from style images to clothing, and commonly result in blurred boundaries between clothing and background. To address these challenges, an arbitrary style transfer algorithm for clothing is proposed, utilizing attention network and feature fusion for more effective and efficient style application. In this paper, the criss-cross attention network is incorporated to extract comprehensively global features and capture long-range dependencies, thus minimizing artifacts and enhancing texture transfer. Through a novel multi-level feature fusion approach, color transfer becomes more natural and coherent, closely aligning with the color palette of the style image. Additionally, semantic segmentation is employed to separate clothing from the background, preserving the original background and character. The experimental results show that the user preference of this paper’s algorithm is much higher than existing methods, and single 512×512 image style transfer takes only 0.314 s with real-time performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantic Segmentation

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Attention-Guided Sparse Adversarial Attacks with Gradient Dropout

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Journal of Donghua University(English Edition) 2024年第5期41卷 545-556页

作者： ZHAO Hongzhi HAO Lingguang HAO Kuangrong WEI Bing LIU Xiaoyan College of Information Science and Technology Donghua UniversityShanghai 201620China Engineering Research Center of Digitized Textile and Apparel Technology Ministry of EducationDonghua UniversityShanghai 201620China

Deep neural networks are extremely vulnerable to externalities from intentionally generated adversarial examples which are achieved by overlaying tiny noise on the clean ***,most existing transfer-based attack methods are chosen to add perturbations on each pixel of the original image with the same weight,resulting in redundant noise in the adversarial examples,which makes them easier to be *** this deliberation,a novel attentionguided sparse adversarial attack strategy with gradient dropout that can be readily incorporated with existing gradient-based methods is introduced to minimize the intensity and the scale of perturbations and ensure the effectiveness of adversarial examples at the same ***,in the gradient dropout phase,some relatively unimportant gradient information is randomly discarded to limit the intensity of the *** the attentionguided phase,the influence of each pixel on the model output is evaluated by using a soft mask-refined attention mechanism,and the perturbation of those pixels with smaller influence is limited to restrict the scale of the *** conducting thorough experiments on the NeurIPS 2017 adversarial dataset and the ILSVRC 2012 validation dataset,the proposed strategy holds the potential to significantly diminish the superfluous noise present in adversarial examples,all while keeping their attack efficacy *** instance,in attacks on adversarially trained models,upon the integration of the strategy,the average level of noise injected into images experiences a decline of 8.32%.However,the average attack success rate decreases by only 0.34%.Furthermore,the competence is possessed to substantially elevate the attack success rate by merely introducing a slight degree of perturbation.

关键词： deep neural network adversarial attack sparse adversarial attack adversarial transferability adversarial example

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Clothing Style Recommendation System based on Interactive Genetic Algorithm 17

Clothing Style Recommendation System based on Interactive Ge...

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17th textile Bioengineering and Informatics Symposium, TBIS 2024

作者： Sun, Kai Wu, Long Qi, Jing Ding, Jun-Tao Wang, Yue Zhang, Jun School of Apparel & Art Design Xi’an Polytechnic University Shaanxi Xi’an710048 China Shaanxi Research Center of Clothing Engineering and Technology Xi’an Polytechnic University Shaanxi Xi’an710048 China Shaanxi "Four Subjects and One Union" Clothing Intelligent Design and Manufacturing Engineering Technology Research Center Shaanxi Xi’an710048 China Wuhan Textile and Apparel Digital Engineering Technology Research Center Hubei Wuhan430073 China

ISBN: (纸本)9798331306809

Given consumers' increasing demand for personalized recommendations of clothing styles, this study proposes a recommendation system based on an interactive genetic algorithm for women's shirts. Using interactive genetic algorithm as the core, the system interacts with users through the interface to obtain preference information in real-time, and then integrates the user's implicit decision factors, such as emotions and preferences, into the system through the adaptive function and uses the genetic algorithm to optimize the recommendation results to meet the personalized needs of users. It can then be optimized based on user experience and feedback. © TBIS 2024.

关键词： Genetic algorithms

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