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Non-interactive SM2 threshold signature scheme with identifiable abort

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Frontiers of computer science 2024年第1期18卷 171-185页

作者： Huiqiang liang Jianhua CHEN school of Mathematics and Statistics Wuhan UniversityWuhan 430072China

A threshold signature is a special digital signature in which the N-signer share the private key x and can construct a valid signature for any subset of the included t-signer,but less than t-signer cannot obtain any *** the breakthrough achievements of threshold ECDSA signature and threshold Schnorr signature,the existing threshold SM2 signature is still limited to two parties or based on the honest majority setting,there is no more effective solution for the multiparty *** make the SM2 signature have more flexible application scenarios,promote the application of the SM2 signature scheme in the blockchain system and secure cryptocurrency *** paper designs a non-interactive threshold SM2signature schemebasedon partially homomorphic encryption and zero-knowledge *** the last round requires the message input,so make our scheme non-interactive,and the pre-signing process takes 2 rounds of communication to complete after the key *** allow arbitrary threshold t

关键词： SM2 signature secure multi-party computation threshold signature UC-secure dishonest majority

HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

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computers, Materials & Continua 2024年第4期79卷 1089-1103页

作者： Wuyan liang Xiaolong Xu school of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210023China school of computer science Nanjing University of Posts and TelecommunicationsNanjing210023China

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input ***, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, *** specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

关键词： Gesture action recognition multi-dimensional attention pseudo-3D skeletal heatmap

The Boundary Element Method for Ordinary State-Based Peridynamics

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computer Modeling in Engineering & sciences 2024年第6期139卷 2807-2834页

作者： Xue liang Linjuan Wang State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of EngineeringPeking UniversityBeijing100871China CAPT-HEDPS and IFSA Collaborative Innovation Center of MoECollege of EngineeringPeking UniversityBeijing100871China school of Astronautics Beihang UniversityBeijing100191China

The peridynamics(PD),as a promising nonlocal continuum mechanics theory,shines in solving discontinuous *** to now,various numerical methods,such as the peridynamic mesh-free particlemethod(PD-MPM),peridynamic finite element method(PD-FEM),and peridynamic boundary element method(PD-BEM),have been ***-BEM,in particular,outperforms other methods by eliminating spurious boundary softening,efficiently handling infinite problems,and ensuring high computational ***,the existing PD-BEM is constructed exclusively for bond-based peridynamics(BBPD)with fixed Poisson’s ratio,limiting its applicability to crack propagation problems and scenarios involving infinite or semi-infinite *** this paper,we address these limitations by introducing the boundary element method(BEM)for ordinary state-based peridynamics(OSPD-BEM).Additionally,we present a crack propagationmodel embeddedwithin the framework ofOSPD-BEM to simulate crack *** validate the effectiveness of OSPD-BEM,we conduct four numerical examples:deformation under uniaxial loading,crack initiation in a double-notched specimen,wedge-splitting test,and threepoint bending *** results demonstrate the accuracy and efficiency of OSPD-BEM,highlighting its capability to successfully eliminate spurious boundary softening phenomena under varying Poisson’s ***,OSPDBEMsignificantly reduces computational time and exhibits greater consistencywith experimental results compared to PD-MPM.

关键词： Ordinary state-based peridynamics boundary element method crack propagation fracture toughness

A Secure-Efficient Data Collection Algorithm Based on Self-Adaptive Sensing Model in Mobile Internet of Vehicles

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China Communications 2016年第2期13卷 121-129页

作者： liang Wei RUAN Zhiqiang TANG Mingdong LI Peng Department of Software Engineering Xiamen University of TechnologyXiamenFujian361024China Department of computer science Minjiang UniversityFuzhouFujian 350108China school of computer science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of ***,other performance requirements such as life cycle of nodes,stability and security are not set as primary design *** makes data collection ability of vehicular nodes in real application environment *** considering the features of nodes in wireless IoV,such as large scales of deployment,volatility and low time delay,an efficient data collection algorithm is proposed for mobile vehicle network *** adaptive sensing model is designed to establish vehicular data collection *** protocol adopts group management in model *** vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding *** will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding *** addition,secure data collection between sensing nodes is undertaken as *** simulation and experiments show that the vehicular node can realize secure and real-time data ***,the proposed algorithm is superior in vehicular network life cycle,power consumption and reliability of data collection by comparing to other algorithms.

关键词： wireless vehicle network datacollection protocol network sensing chain self'-adaptive sensing sensing distance threshold.

Rotor Angle Stability Prediction Using Temporal and Topological Embedding Deep Neural Network Based on Grid-informed Adjacency Matrix

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 695-706页

作者： Peiyuan Sun Long Huo Xin Chen Siyuan liang the school of Electrical Engineering Xi’an Jiaotong UniversityXi’an 710049China the school of Electrical Engineering and the Center of Nanomaterials for Renewable EnergyState Key Laboratory of Electrical Insulation and Power EquipmentXi’an Jiaotong UniversityXi’an 710049China the Department of computer science and Engineering The Chinese University of Hong KongShatin999077Hong KongChina

Rotor angle stability(RAS)prediction is critically essential for maintaining normal operation of the interconnected synchronous machines in power *** wide deployment of phasor measurement units(PMUs)promotes the development of data-driven methods for RAS *** paper proposes a temporal and topological embedding deep neural network(TTEDNN)model to accurately and efficiently predict RAS by extracting the temporal and topological features from the PMU *** grid-informed adjacency matrix incorporates the structural and electrical parameter information of the power *** the small-signal RAS with disturbance under initial operating conditions and the transient RAS with short circuits on transmission lines are *** studies of the IEEE 39-bus and IEEE 300-bus power systems are used to test the performance,scalability,and robustness against measurement uncertainties of the TTEDNN *** show that the TTEDNN model performs best among existing deep learning ***,the superior transfer learning ability from small-signal RAS conditions to transient RAS conditions has been proved.

关键词： Rotor angle stability prediction topological embedding deep learning graph convolution network

Dynamics modeling and optimal control for multi-information diffusion in Social Internet of Things

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Digital Communications and Networks 2024年第3期10卷 655-665页

作者： Yaguang Lin Xiaoming Wang liang Wang Pengfei Wan school of computer science Shaanxi Normal UniversityXi'an710119China

As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share ***,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its *** this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this ***,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is *** this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control *** optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control ***,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.

关键词： Social Internet of Things Information diffusion Dynamics modeling Trend prediction Optimal control

Scattering-based hybrid network for facial attribute classification

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Frontiers of computer science 2024年第3期18卷 105-116页

作者： Na LIU Fan ZHANG liang CHANG Fuqing DUAN school of Artificial Intelligence Beijing Normal UniversityBeijing 100875China

Face attribute classification(FAC)is a high-profile problem in biometric verification and face *** recent research has been devoted to extracting more delicate image attribute features and exploiting the inter-attribute correlations,significant challenges still *** scattering transform(WST)is a promising non-learned feature *** has been shown to yield more discriminative representations and outperforms the learned representations in certain *** to the image classification task,WST can enhance subtle image texture information and create local deformation *** paper designs a scattering-based hybrid block,to incorporate frequency-domain(WST)and image-domain features in a channel attention manner(Squeezeand-Excitation,SE),termed WS-SE *** with CNN,WS-SE achieves a more efficient FAC performance and compensates for the model sensitivity of the small-scale affine *** addition,to further exploit the relationships among the attribute labels,we propose a learning strategy from a causal *** cause attributes defined using the causalityrelated information can be utilized to infer the effect attributes with a high confidence *** analysis experiments demonstrate the effectiveness of our model,and our hybrid model obtains state-of-the-art results in two public datasets.

关键词： wavelet scattering transform causality-related learning facial attribute classification

Distributed user pairing and effective computation offloading in aerial edge networks

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Chinese Journal of Aeronautics 2024年第4期37卷 378-390页

作者： Wei liang Shuhui WEN Lixin LI Jingjing CUI school of Electronics and Information Northwestern Polytechnical UniversityXi’an CN710072China The State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an CN710126China school of Electronics and computer science University of SouthamptonSouthampton SO167NSUK

Future Sixth-Generation (6G) mobile communication networks extremely require the global connectivity and the ground Base Stations (BSs) are difficult to develop in some specific areas,such as mountainous ***,the aerial networks are the key framework for the future communications,in which the aerial vehicle could act as the access ***,Mobile Edge Computing (MEC) is also essential to enhance the data processing capabilities of aerial *** this paper,we study a comprehensive communication-computation resource management problem for jointly optimizing user pairing,power and time allocation in the MEC aided Cognitive Radio (CR) aerial networks,namely CR-MEC aerial ***,this multilevel optimization problem could be decomposed into the user pairing and power allocation as well as time allocation *** the conceived CR-MEC aerial networks,we propose a User Pairing and Computation Offloading Management Algorithm (UPCOMA) based on three-sided matching theory,aiming to minimize the system’s energy *** the first step of UPCOMA,multiple Primary Users (PUs) and Cognitive Users (CUs) on the ground negotiate to each other with the suitable power allocation coefficients and construct the stable user ***,the stable user pairs would match to a high altitude platform who act as the base station,which is for appropriately allocating Transmission Time Slots (TSs) at the second step of ***,a hybrid offloading mode is proposed in our conceived networks in order to support ground users to offload their tasks adaptively according to their individual ***,the simulation results reveal that the relative performance of UPCOMA is close to that of the Brute-Force Search Algorithm (BFSA) with low ***,the hybrid offloading mode with less energy consumption supports much more ground user pairs to offload tasks compared to the binary mode.

关键词： Aerial edge computing Binary offloading Cognitive radio Hybrid offloading Resource management

Predicting Traffic Flow Using Dynamic Spatial-Temporal Graph Convolution Networks

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computers, Materials & Continua 2024年第3期78卷 4343-4361页

作者： Yunchang Liu Fei Wan Chengwu liang school of computer and Data science Henan University of Urban ConstructionPingdingshan467036China school of Electrical and Control Engineering Henan University of Urban ConstructionPingdingshan467036China

Traffic flow prediction plays a key role in the construction of intelligent transportation ***,due to its complex spatio-temporal dependence and its uncertainty,the research becomes very *** of the existing studies are based on graph neural networks that model traffic flow graphs and try to use fixed graph structure to deal with the relationship between ***,due to the time-varying spatial correlation of the traffic network,there is no fixed node relationship,and these methods cannot effectively integrate the temporal and spatial *** paper proposes a novel temporal-spatial dynamic graph convolutional network(TSADGCN).The dynamic time warping algorithm(DTW)is introduced to calculate the similarity of traffic flow sequence among network nodes in the time dimension,and the spatiotemporal graph of traffic flow is constructed to capture the spatiotemporal characteristics and dependencies of traffic *** combining graph attention network and time attention network,a spatiotemporal convolution block is constructed to capture spatiotemporal characteristics of traffic *** on open data sets PEMSD4 and PEMSD8 show that TSADGCN has higher prediction accuracy than well-known traffic flow prediction algorithms.

关键词： Intelligent transportation graph convolutional network traffic flow DTW algorithm attention mechanism