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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Jiayuan Du Guowei Zhang School of Cyber Science and Engineering Qufu Normal University Qufu China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

To alleviate the burden on the core network, edge computing has rapidly advanced to support distributed computing. However, as sensitive information is delegated to the edge layer closer to endpoints, the privacy protection challenges faced by edge nodes intensify while striving to deliver high-quality services. Existing studies predominantly rely on various encryption algorithms to safeguard privacy information, such as identity, location, and offloading routes privacy. Unfortunately, these approaches exhibit high overhead and often neglect the potential maliciousness of the nodes themselves. To address these issues, this paper introduces a lightweight edge node verification and protection strategy. This strategy not only verifies the reliability of edge nodes but also enables anonymized uploading of private information. Numerical simulation results demonstrate the superiority of this strategy over existing schemes, showcasing reduced computational overhead while achieving enhanced protection.

关键词： Seminars Privacy Numerical simulation Mathematical models Performance analysis Security Reliability

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Enhanced optical imaging and fluorescent labeling for visualizing drug molecules within living organisms

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Acta Pharmaceutica Sinica B 2024年第6期14卷 2428-2446页

作者： Ting Sun Huanxin Zhao Luyao Hu Xintian Shao Zhiyuan Lu Yuli Wang Peixue Ling Yubo Li Kewu Zeng Qixin Chen School of Pharmaceutical Sciences National Key Laboratory of Advanced Drug Delivery SystemMedical Science and Technology Innovation CenterShandong First Medical University&Shandong Academy of Medical SciencesJinan 250062China Departments of Diagnostic Radiology SurgeryChemical and Biomolecular Engineeringand Biomedical EngineeringYong Loo Lin School of Medicine and College of Design and EngineeringNational University of SingaporeSingapore 119074Singapore Institute of Biochemical and Biotechnological Drugs School of Pharmaceutical SciencesCheeloo College of MedicineShandong UniversityJinan 250012China Key Laboratory of Biopharmaceuticals Postdoctoral Scientific Research WorkstationShandong Academy of Pharmaceutical ScienceJinan 250098China State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical SciencesPeking UniversityBeijing 100191China School of Life Sciences Science and Technology Innovation CenterShandong First Medical University&Shandong Academy of Medical SciencesJinan 250062China School of Chinese Materia Medica Tianjin University of Traditional Chinese MedicineTianjin 301617China Tianjin Pharmaceutical DA REN TANG Group Corporation Limited Traditional Chinese Pharmacy Research Institute Tianjin 300457China Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemistry Engineering and TechnologyTianjin UniversityTianjin 300072China

The visualization of drugs in living systems has become key techniques in modern *** advancements in optical imaging technologies and molecular design strategies have revolutionized drug *** the subcellular level,super-resolution microscopy has allowed exploration of the molecular landscape within individual cells and the cellular response to *** beyond subcellular imaging,researchers have integrated multiple modes,like optical near-infrared II imaging,to study the complex spatiotemporal interactions between drugs and their *** combining these visualization approaches,researchers gain supplementary information on physiological parameters,metabolic activity,and tissue composition,leading to a comprehensive understanding of drug *** review focuses on cutting-edge technologies in drug visualization,particularly fluorescence imaging,and the main types of fluorescent molecules ***,we discuss current challenges and prospects in targeted drug research,emphasizing the importance of multidisciplinary cooperation in advancing drug *** the integration of advanced imaging technology and molecular design,drug visualization has the potential to redefine our understanding of pharmacology,enabling the analysis of drug micro-dynamics in subcellular environments from new perspectives and deepening pharmacological research to the levels of the cell and organelles.

关键词： Optical imaging Drug visualization Fluorophore labeling Therapeutics

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VCFGAN: A Two-stage Collaborative Filtering Framework based on Variational Autoencoders and Generative Adversarial Networks

VCFGAN: A Two-stage Collaborative Filtering Framework based ...

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Information Systems and computing Technology (ISCTech), International Conference on

作者： Zhiqiang Huang Jinzhong Li Xueyu Huang Junqi Liu School of Software Engineering Jiangxi University of Science and Technology Nanchang China College of Electronics and Information Engineering Jinggangshan University Ji’an China Ministry of Education Key Laboratory of Embedded System and Service Computing (Tongji University) Shanghai China

ISBN: (数字)9798350379860

ISBN: (纸本)9798350379877

Deep generative models, such as Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE), are widely used in collaborative filtering. They usually learn users’ preferences for items directly from a highly sparse user rating matrix (URM), and then recommend the top-N items to users. Due to the high sparsity of URM, GAN has limited ability to handle sparse data, while VAE’s encoder can extract features. Therefore, we propose a two-stage collaborative filtering framework based on variational autoencoders and generative adversarial networks, named VCFGAN. It first uses two VAEs to extract features from URM and side information (SI), and then uses the extracted latent vectors to train the GAN network. To evaluate the performance of our proposed VCFGAN model, some experiments are conducted on two real datasets, and the experimental results show that our model outperforms other representative models.

关键词： Training Collaborative filtering Autoencoders Generative adversarial networks Feature extraction Vectors Data mining Sparse matrices Recommender systems Information systems

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Comparing different spatial interpolation methods to predict the distribution of fishes:A case study of Coilia nasus in the Changjiang River Estuary

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Acta Oceanologica Sinica 2021年第8期40卷 119-132页

作者： Shaoyuan Pan Siquan Tian Xuefang Wang Libin Dai Chunxia Gao Jianfeng Tong College of Marine Sciences Shanghai Ocean UniversityShanghai 201306China National Distant-water Fisheries Engineering Research Center Shanghai 201306China Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources Ministry of EducationShanghai 201306China Key Laboratory of Oceanic Fisheries Exploitation Ministry of Agriculture and Rural AffairsShanghai 201306China Scientific Observing and Experimental Station of Oceanic Fishery Resources Ministry of Agriculture and Rural AffairsShanghai 201306China

Spatial-temporal distribution of marine fishes is strongly influenced by environmental *** obtain a more continuous distribution of these variables usually measured by stationary sampling designs,spatial interpolation methods(SIMs)is usually ***,different SIMs may obtain varied estimation values with significant differences,thus affecting the prediction of fish spatial *** this study,different SIMs were used to obtain continuous environmental variables(water depth,water temperature,salinity,dissolved oxygen(DO),p H,chlorophyll a and chemical oxygen demand(COD))in the Changjiang River Estuary(CRE),including inverse distance weighted(IDW)interpolation,ordinary Kriging(OK)(semivariogram model:exponential(OKE),Gaussian(OKG)and spherical(OKS))and radial basis function(RBF)(regularized spline function(RS)and tension spline function(TS)).The accuracy and effect of SIMs were cross-validated,and two-stage generalized additive model(GAM)was used to predict the distribution of Coilia nasus from 2012 to 2014 in *** and COD were removed before model prediction due to their autocorrelation coefficient based on variance inflation factors *** showed that the estimated values of environmental variables obtained by the different SIMs differed(i.e.,mean values,range etc.).Cross-validation revealed that the most suitable SIMs of water depth and chlorophyll a was IDW,water temperature and salinity was RS,and p H was ***,different interpolation results affected the predicted spatial distribution of Coilia nasus in the *** mean values of the predicted abundance were similar,but the differences between and among the maximum value were *** showed that different SIMs can affect estimated values of the environmental variables in the CRE(especially salinity).These variations further suggest that the most applicable SIMs to each variable will also ***,it is necessary to take these potential impacts into consideration when

关键词： the Changjiang River Estuary marine environmental factors spatial interpolation method Coilia nasus spatial distribution

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Replace2Self: Self-Supervised Denoising based on Voxel Replacing and Image Mixing for Diffusion MRI

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Wu, Linhai Wang, Lihui Deng, Zeyu Zhu, Yuemin Wei, Hongjiang Guizhou University Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education State Key Laboratory of Public Big Data College of Computer Science and Technology 550025 China Univ Lyon INSA Lyon CNRS Inserm CREATIS UMR 5220 LyonF-69621 France Shanghai Jiao Tong University School of Biomedical Engineering Shanghai200030 China

Low signal to noise ratio (SNR) remains one of the limitations of diffusion weighted (DW) imaging. How to suppress the influence of noise on the subsequent analysis about the tissue microstructure is still challenging. This work proposed a novel self-supervised learning model, Replace2Self, to effectively reduce spatial correlated noise in DW images. Specifically, a voxel replacement strategy based on similar block matching in Q-space was proposed to destroy the correlations of noise in DW image along one diffusion gradient direction. To alleviate the signal gap caused by the voxel replacement, an image mixing strategy based on complementary mask was designed to generate two different noisy DW images. After that, these two noisy DW images were taken as input, and the non-correlated noisy DWimage after voxel replacement was taken as learning target, a denoising network was trained for denoising. To promote the denoising performance, a complementary mask mixing consistency loss and an inverse replacement regularization loss were also proposed. Through the comparisons against several existing DW image denoising methods on extensive simulation data with different noise distributions, noise levels and b-values, as well as the acquisition datasets and the ablation experiments, we verified the effectiveness of the proposed method. Regardless of the noise distribution and noise level, the proposed method achieved the highest PSNR, which was at least 1.9% higher than the suboptimal method when the noise level reaches 10%. Furthermore, our method has superior generalization ability due to the use of the proposed strategies. © 2025 IEEE. All rights reserved.

关键词： Signal to noise ratio

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Hand medical monitoring system based on machine learning and optimal EMG feature set

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Personal and Ubiquitous computing 2023年第6期27卷 1991-2007页

作者： Yu, Mingchao Li, Gongfa Jiang, Du Jiang, Guozhang Tao, Bo Chen, Disi Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

Considering that serious hand function damage will greatly affect the daily life of patients, its recovery mainly depends on the regular inspection and manual training of medical staff, and medical monitoring based on bioelectric signals can largely replace manual re-examination as autonomous rehabilitation technology. So, for the rationality of feature selection and the diversity of classifier design in the gesture recognition process based on electromyography (EMG) signals, this paper proposes a hand medical monitoring system based on feature selection method of feature subset average recognition rate and optimal machine learning algorithm selection, which mainly depends on the prediction of hand movement. At the same time, since most experiments are conducted in different non-public proprietary databases, the comparison between various gesture recognition methods can only be analyzed to a certain extent. Therefore, this paper uses the DB1 dataset in the large publicly available NinaPro database and combines with presently well-known 11 time-domain (TD) features and 5 frequency domain (FD) features, then uses the support vector machine (SVM) classifier to comparative analysis total 136 feature combinations under various feature numbers. Under the premise of ensuring the overall recognition rate of electromyography gesture, this method will be able to reduce the number of features in feature set, according to the change of the average remove redundant features, and construct an optimal reduced EMG feature set. Finally, through the four common hand motion classifiers based on machine learning: SVM, back propagation neural network, linear discriminant analysis, and K-nearest neighbor, this paper tests and verifies the separability of the optimal reduced EMG feature set, and based on this, selects the optimal hand motion classifier to build the optimal hand motion recognition system, improve the hand medical monitoring system, and provide technical reference for the c

关键词： Discriminant analysis

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Fast Heterogeneous Multi-Problem Surrogates for Transfer Evolutionary Multiobjective Optimization

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Li, Hao Xiong, Pu Gong, Maoguo Qin, A.K. Wu, Yue Xing, Lining Key Laboratory of Collaborative Intelligence Systems Ministry of Education School of Electronic Engineering Xidian University Xi’an China Department of Computing Technologies Swinburne University of Technology Hawthorn Victoria Australia School of Computer Science and Technology Xidian University Xi’an China

Transfer evolutionary multiobjective optimization leverages the relevant knowledge from other source problems (distinct but possibly related) to assist the optimization of the target problem of interest. Multi-problem surrogates stack multiple source surrogates to reduce the number of function evaluations of the target expensive problem. The current multi-problem surrogates only considers several source problems and the source and target problems are assumed to be homogeneous. In order to address the above issues, this paper proposes fast heterogeneous multi-problem surrogates for transfer evolutionary multiobjective optimization with a large number of surrogates. First, an iterative surrogate selection strategy is designed to select the highly relevant surrogates from the large-scale surrogate pool to avoid negative transfer. Second, heterogeneous multi-problem surrogates are established to align the features of the source and target models. Finally, an adaptive k-fold cross-validation method is proposed to obtain the predicted values of the target model with low computational costs. Experiments on the multiobjective optimization benchmark problems and multiobjective neural architecture search problems have demonstrated that the proposed method is able to avoid negative transfer in the large-scale scenarios and reduce the computational costs. IEEE

关键词： Multiobjective optimization

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Cooperative and Competitive Multi-Agent Systems:From Optimization to Games

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 763-783页

作者： Jianrui Wang Yitian Hong Jiali Wang Jiapeng Xu Yang Tang Qing-Long Han Jürgen Kurths Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China Department of Electrical and Computer Engineering University of WindsorWindsorON N9B 3P4Canada IEEE School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia Potsdam Institute for Climate Impact Research 14473 Potsdam Institute of Physics Humboldt University of Berlin12489 BerlinGermany

Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation *** a multi-agent system,agents with a certain degree of autonomy generate complex interactions due to the correlation and coordination,which is manifested as cooperative/competitive *** survey focuses on multi-agent cooperative optimization and cooperative/non-cooperative *** from cooperative optimization,the studies on distributed optimization and federated optimization are *** survey mainly focuses on distributed online optimization and its application in privacy protection,and overviews federated optimization from the perspective of privacy protection ***,cooperative games and non-cooperative games are introduced to expand the cooperative optimization problems from two aspects of minimizing global costs and minimizing individual costs,***-agent cooperative and non-cooperative behaviors are modeled by games from both static and dynamic aspects,according to whether each player can make decisions based on the information of other ***,future directions for cooperative optimization,cooperative/non-cooperative games,and their applications are discussed.

关键词： Cooperative games counterfactual regret minimization distributed optimization federated optimization fictitious

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Enhancement for Versatile Video Coding in Vehicular Ad Hoc Network Scenarios

Enhancement for Versatile Video Coding in Vehicular Ad Hoc N...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Jiacheng Wu Jiaqi Zou Songlin Sun School of Information and Communication Engineering Beijing University of Posts and Telecommunications (BUPT) Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education China National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

Vehicular Ad hoc Network (VANET) allows infor-mation exchange between vehicles. In VANET, video is the most recommended medium for transmitting information. However, the characteristics of VANET and the requirements of video content in terms of quality have resulted in various challenges. Besides, the movements of vehicles introduce complex motions in videos, making them more difficult to compress. As a result, it is a challenging task to transmit as less bits of video streams as possible while maintaining their visual quality. Therefore, we analyze Affine Motion Estimation (AME), a new coding tool in the latest generation video coding standard H.266NV C. Subsequently, a fast algorithm is proposed to make it able to describe complex motions such as rotation, zoom, shear, etc but also with low complexity. Experimental results show that the algorithm reduces the encoding complexity of AME by 20.19% and the overall encoding complexity by 3.25% compared to anchor VTM21.0, with eligible coding performance loss under Random Access (RA) configurations.

关键词： Video coding Visualization Motion estimation Vehicular ad hoc networks Streaming media Feature extraction Encoding Complexity theory Streams Standards

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Silent Deception: Compromising Speech Processing Pipelines via Universal Adversarial Attacks on Voice Activity Detection

Silent Deception: Compromising Speech Processing Pipelines v...

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IEEE International Conference on Cloud computing and Big Data Analysis (ICCCBDA)

作者： Zeyu Xiao Timan Pa Dengpan Ye Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University China Internet Information Office of the 12th Division Xinjiang Production and Construction Corps China

ISBN: (数字)9798331530808

ISBN: (纸本)9798331530815

The pipelined speech system, encompassing Voice Activity Detection (VAD) and Automatic Speech Recognition (ASR), plays a crucial role in human-machine interactions within scenarios such as voice assistants. Recent studies have shown that universal adversarial perturbations (UAP) can cause ASR to generate non-sensical outputs, compromising the integrity and reliability of the entire speech processing pipeline. However, the VAD component preceding ASR has been overlooked. This paper introduces Silent Deception, a novel universal adversarial attack that effectively suppresses VAD activation. Our approach incorporates two key insights: a spectral feature preservation mechanism that helps mitigate the low SNR issue common in speech adversarial attacks, and an adaptive gradient balancing strategy that dynamically optimizes the ensemble of surrogate models. Comprehensive experiments demonstrate the effectiveness of our approach, achieving attack success rates of 87.93% and 30.85 % in white-box and black-box settings respectively. When targeting commercial ASR services with local VAD modules, our attack induces word error rates of 92.4 % and 61.23 % under white-box and black-box scenarios.

关键词： Voice activity detection Perturbation methods Pipelines Closed box Personal voice assistants Security Reliability Glass box Automatic speech recognition Signal to noise ratio

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