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Hierarchical Sponge-Hydrogel Hybrid Structures with Robust Interfaces

Chinese Journal of Chemistry 2023年第20期41卷 2635-2640页

作者： Pei Zhang Guangda Chen Xingmei Chen Junfei Xing Yue Tao Ji Liu Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhenGuangdong518055 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhenGuangdong518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and TechnologyShenzhenGuangdong518055 China

Soft materials including elastomers and hydrogels are playing critical roles in a variety of fields,including bioelectrodes,batteries,supercapacitors,biomedical scaffolds,and solar vapor *** hydrophobic sponges(i.e.,mechanical robustness,elasticity and macroscopic porous structure)and hydrophilic hydrogels(i.e.,autonomous water absorption and transportation,biocompatibility)within one unit could readily combine the complementary characters from each component,making a number of future research directions and applications *** propose a simple yet effective strategy to construct sponge-hydrogel hybrid structures with robust hydrophobic-hydrophilic *** sponge scaffold imparts the sponges-hydrogel hybrids with desirable mechanical robustness,elasticity and macroscopic *** the other hand,the incorporated hydrogel component endows the hybrids with high water content(98 wt%hydrogel and 2 wt%sponge),superior compatibility,and nanoscale pores allowing for storage and transportation of various chemical and biological *** further demonstrate that the introduction of hydrophilic hydrogel components could effectively improve the liquid absorption capability,blood coagulation rate,hemostatic capacity and hemocompatibility,thus promising as hemostatic agents.

关键词： Sponge-hydrogel hybrid Interface Hierarchical Robustness Liquid absorption Gels Polymer Composites Materials science

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Improving the Interpretability Through Maximizing Mutual Information for EEG Emotion Recognition

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IEEE Transactions on Affective Computing 2025年第2期16卷 744-757页

作者： Yang, Hua Chen, C. L. Philip Chen, Bianna Zhang, Tong North Carolina State University Department of Computer Science RaleighNC27695 United States South China University of Technology Guangdong Provincial Key Laboratory of AI Large Model and Intelligent Cognition The School of Computer Science and Engineering Guangzhou510006 China Pazhou Lab Guangzhou510335 China Engineering Research Center of the Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human Guangzhou510335 China

Trustworthy Graph Neural Networks (GNNs) for EEG emotion recognition should identify emotions accurately and elucidate corresponding rationales. Current GNNs have achieved notable performance by dynamically modeling emotional connections between EEG channels. However, these GNNs lack interpretability due to the absence of explicit rationale behind their predictions. This paper conducts a comprehensive identification of important EEG channels to enhance the interpretability of EEG emotion recognition from the perspective of mutual information. Specifically, an Adjacency-Explainable Graph Neural Network (AEG) for ante-hoc interpretability is proposed to capture genuine EEG emotional connections, which gives a theoretical guarantee to remove spurious connections. Moreover, a Channel-wise Adaptive Class Activation Mapping Explainer (CACA) for post-hoc interpretability is developed to locate the EEG channels that contribute most to predictions. Experimental results on three datasets, i.e., SEED, SEED-IV, and DREAMER, prove that imbuing training processes with enhanced interpretability ensures significant performance improvements in emotion recognition. Quantitative comparisons of post-hoc interpretability also demonstrate the superiority of CACA. Furthermore, this paper illustrates two potential applications of the proposed methodologies, showing their broader utility and significance. © 2010-2012 IEEE.

关键词： Graph neural networks

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Few-Shot Object Detection Based on the Transformer and High-Resolution Network

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computers, Materials & Continua 2023年第2期74卷 3439-3454页

作者： Dengyong Zhang Huaijian Pu Feng Li Xiangling Ding Victor S.Sheng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411004China Department of Computer Science Texas Tech UniversityLubbock79409TXUSA

Now object detection based on deep learning tries different *** uses fewer data training networks to achieve the effect of large dataset ***,the existing methods usually do not achieve the balance between network parameters and training *** makes the information provided by a small amount of picture data insufficient to optimize model parameters,resulting in unsatisfactory detection *** improve the accuracy of few shot object detection,this paper proposes a network based on the transformer and high-resolution feature extraction(THR).High-resolution feature extractionmaintains the resolution representation of the *** and spatial attention are used to make the network focus on features that are more useful to the *** addition,the recently popular transformer is used to fuse the features of the existing *** compensates for the previous network failure by making full use of existing object *** on the Pascal VOC and MS-COCO datasets prove that the THR network has achieved better results than previous mainstream few shot object detection.

关键词： Object detection few shot object detection transformer high-resolution

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Ultra-large mode area multi-core orbital angular momentum transmission fiber designed by neural network and optimization algorithms

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Optoelectronics Letters 2023年第12期19卷 744-751页

作者： GU Zhiwei HUANG Wei ZHANG Ran FAN Junjie SONG Binbin Key Laboratory of Computer Vision and Systems(Ministry of Education) School of Computer Science and EngineeringTianjin University of TechnologyTianjin 300384China Engineering Research Center of Learning-Based Intelligent System(Ministry of Education) Tianjin University of TechnologyTianjin 300384China

A large mode area multi-core orbital angular momentum(OAM)transmission fiber is designed and optimized by neural network and optimization *** neural network model has been established first to predict the optical properties of multi-core OAM transmission fibers with high accuracy and speed,including mode area,nonlinear coefficient,purity,dispersion,and effective index *** the trained neural network model is combined with different particle swarm optimization(PSO)algorithms for automatic iterative optimization of multi-core structures *** to the structural advantages of multi-core fiber and the automatic optimization process,we designed a number of multi-core structures with high OAM mode purity(>95%)and ultra-large mode area(>3000µm^(2)),which is larger by more than an order of magnitude compared to the conventional ring-core OAM transmission fibers.

关键词： network fiber OAM

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A comparative study of data-driven battery capacity estimation based on partial charging curves

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Journal of Energy Chemistry 2024年第1期88卷 409-420,I0010页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Xianggong Zhang Enhu Li Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina Wuhan Institute of Marine Electric Propulsion China State Shipbuilding Corporation LimitedWuhan 430064HubeiChina Gresgying Digital Technology Ltd. Xi’an 710086ShaanxiChina

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

关键词： Lithium-ion battery Partial charging curves Capacity estimation Data-driven Sampling frequency

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intelligent Blind Source Separation technology Based on OTFS Modulation for LEO Satellite Communication

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China Communications 2022年第7期19卷 89-99页

作者： Chengjie Li Lidong Zhu Cheng Guo Tao Liu Zhen Zhang The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and Technology(Southwest Minzu University)Chengdu 610000China National Key Laboratory of Science and Technology on Communications(University of Electronic Science and Technology of China) Chengdu 610000China College of Computer Science(Sichuan University) Chengdu 610000China

In LEO(Low Earth Orbit)satellite communication system,the orbit height of the satellite is low,the transmission delay is short,the path loss is small,and the frequency multiplexing is more ***,it is an unavoidable technical problem of the significant Doppler effect caused by the interference between satellite networks and the high-speed movement of the satellite relative to the *** order to improve the target detection efficiency and system security of LEO satellite communication system,blind separation technology is an effective method to process the collision signals received by *** of the signal has good sparsity in Delay-Doppler domain,in order to improve the blind separation performance of LEO satellite communication system,orthogonal Time-Frequency space(OTFS)modulation is used to convert the sampled signal to Delay-Doppler *** clustering algorithm is used to classify the sparse signal,so as to separate the original mixed ***,the simulation results show that the method has a good separation effect,and can significantly improve the detection efficiency of system targets and the security of LEO satellite communication system network.

关键词： LEO Doppler effect Delay-Doppler domain OTFS DBSCAN clustering algorithm

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A Study of the 1+2 Partitioning Scheme of Fibrous Unitcell under Reduced-Order Homogenization Method with Analytical Influence Functions

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computer Modeling in Engineering & sciences 2025年第3期142卷 2893-2924页

作者： Shanqiao Huang Zifeng Yuan HEDPS Center for Applied Physics and Technology(CAPT)Department of Mechanics and Engineering ScienceCollege of EngineeringPeking UniversityBeijing100871China State Key Laboratory for Turbulence and Complex Systems Peking UniversityBeijing100871China

The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite *** the ROH framework,a partition-based unitcell structure at the mesoscale is utilized to give a mechanical state at the macro-scale quadrature point with pre-evaluated influence *** the past,the“1-phase,1-partition”rule was usually adopted in numerical analysis,where one constituent phase at the mesoscale formed one *** numerical cost then is significantly reduced by introducing an assumption that the mechanical responses are the same all the time at the same constituent,while it also introduces numerical *** study proposes a new partitioning method for fibrous unitcells under a reduced-order homogenization *** this method,the fiber phase remains 1 partition,but the matrix phase is divided into 2 partitions,which refers to the“12”partitioning *** elastic influence+functions are derived by introducing the elastic strain energy equivalence(Hill-Mandel condition).This research also obtains the analytical eigenstrain influence functions by alleviating the so-called“inclusion-locking”*** addition,a numerical approach to minimize the error of strain energy density is introduced to determine the partitioning of the matrix *** numerical examples are presented to compare the differences among direct numerical simulation(DNS),“11”,and“12”partitioning *** numerical simulations show improved++numerical accuracy by the“12”partitioning scheme.

关键词： Multiscale reduced-order homogenization influence tensors unitcell fibrous composite mate

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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Game Learning-Based Target Allocation of the UAV Confrontation System

Game Learning-Based Target Allocation of the UAV Confronta...

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International Conference on Guidance, Navigation and Control, ICGNC 2024

作者： Hu, Yaxu Zhang, Yanling Xiao, Feng Key Laboratory of Intelligent Bionic Unmanned Systems School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819622313

Previous studies on the UAV swarm air combat decision-making problem lack consideration of uncertainty, intense confrontation, and high dynamics of aerial combat scenarios. This paper delves into the target allocation decision problem of the UAV attack and defense confrontation in a dynamic aerial combat environment. First, a dynamic game model is proposed to adapt changes in combat resources and adversaries’ behavior throughout multi-stage game processes. Then, the corresponding Nash equilibrium is solved based on a game learning algorithm- the Q-Learning algorithm. Finally, we consider the case where the UAV destructive probability is unknown, an uncertainty model is designed for predicting the UAV destructive probability based on the fuzzy comprehensive evaluation method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fuzzy comprehensive evaluation game learning target allocation UAV swarm

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PACE: Reputation-Driven Hierarchical Incentive Mechanism for Trusted Healthcare Transactions in Model Marketplace

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IEEE Transactions on Consumer Electronics 2024年第1期71卷 1571-1583页

作者： Lu, Jianfeng Dou, Xiaochi Rathore, Bharati Jhaveri, Rutvij H. Seid, Abegaz Mohammed Erbad, Aiman Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Ministry of Education Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology China United Kingdom Pandit Deendayal Energy University Department of Computer Science and Engineering School of Technology India Hamad Bin Khalifa University College of Science and Engineering Doha Qatar Qatar University College of Engineering Doha Qatar

Federated learning-based model marketplaces have the potential to securely leverage healthcare data for efficient healthcare transactions. However, the willingness to participate in this marketplace is severely hindered by self-interested model sellers, who maximize their personal gains via distorting the quality of their models. To this end, we propose a rePutation-driven hierArchical inCentive mEchanism, called PACE, which combines contract cooperation and game pricing to motivate model sellers to be honest, thereby improving the sustainability of the model marketplace via two-layer cooperation. Specifically, at the training layer, we design a reward payment rule based on multidimensional contracts, while at the trading layer, we use a competitive market pricing game to develop the accuracy pricing rule. In particular, the above rules cleverly combine the fine-grained model sellers' reputations with the willingness of healthcare devices to indirectly affect the model sellers' utilities. Theoretically, we prove that PACE can effectively incentivize model sellers to truthfully report model quality while satisfying both individual rationality and incentive compatibility with a fairness guarantee. Experimental results conducted on four real-world datasets show that our PACE improves the global performance by up to 12.85% and reduces the global loss by at least 19.23% compared with the state-of-the-art baselines. © 1975-2011 IEEE.

关键词： Marketplaces

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