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Analysis of radiation diffusion of COVID-19 driven by social attributes

Chinese Physics B 2024年第1期33卷 773-779页

作者：年福忠杨晓晨师亚勇 Lanzhou University of Technology School of Computer&CommunicationLanzhou 730050China University of Science and Technology Beijing School of Computer&Communication EngineeringBeijing 100083China

This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was introduced in this paper, which took the gross domestic product(GDP) of each region as one of the factors that affect the spread speed of COVID-19 and studied the relationship between the GDP and the infection density of each region(China's Mainland, the United States, and EU countries). In addition, the geographic distance between regions was also considered in this method and the effect of geographic distance on the spread speed of COVID-19 was studied. Studies have shown that the probability of mutual infection of these two regions decreases with increasing geographic distance. Therefore, this paper proposed an epidemic disease spread index based on GDP and geographic distance to quantify the spread speed of COVID-19 in a region. The analysis results showed a strong correlation between the epidemic disease spread index in a region and the number of confirmed cases. This finding provides reasonable suggestions for the control of epidemics. Strengthening the control measures in regions with higher epidemic disease spread index can effectively control the spread of epidemics.

关键词： COVID-19 basic reproduction number gross domestic product(GDP) geographic distance cross-regional spread

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Robust style injection for person image synthesis

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CAAI Transactions on Intelligence technology 2025年第2期10卷 402-414页

作者： Yan Huang Jianjun Qian Shumin Zhu Jun Li Jian Yang School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingChina School of Fashion and Textiles The Hong Kong Polytechnic UniversityHong KongChina

Person Image Synthesis has been widely used in fashion with extensive application *** point of this task is how to synthesise person image from a single source image under arbitrary *** methods generate the person image with target pose well;however,they fail to preserve the fine style details of the source *** address this problem,a robust style injection(RSI)model is proposed,which is a coarse-to-fine framework to synthesise target the person *** develops a simple and efficient cross-attention based module to fuse the features of both source semantic styles and target pose for achieving the coarse aligned *** adaptive instance normalisation is employed to enhance the aligned features in conjunction with source semantic ***,source semantic styles are further injected into the positional normalisation scheme to avoid the fine style details erosion caused by massive *** training losses,optimal transport theory in the form of energy distance is introduced to constrain data distribution to refine the texture style ***,the authors’model is capable of editing the shape and texture of garments to the target style *** experiments demonstrate that the authors’RSI achieves better performance over the state-of-art methods.

关键词： computer vision image reconstruction virtual try‐on

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A secure double spectrum auction scheme

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Digital Communications and Networks 2024年第5期10卷 1415-1427页

作者： Jiaqi Wang Ning Lu Ziyang Gong Wenbo Shi Chang Choi School of Computer Science and Engineering Northeastern UniversityShenyang110004China School of Computer Science and Technology Xidian UniversityXi©anChina Dept.of Computer Engineering Gachon University1342Seongnam-daeroSujeong-guSeongnam-si13120G School of Computer and Communication Engineering Northeastern UniversityQinhuangdao066004China

With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of the electronic spectrum auction network environment,the security of spectrum auction can not be *** scholars focus on researching the security of the single-sided auctions,while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and *** begin to design the secure double spectrum auction mechanisms,in which two semi-honest agents are introduced to finish the spectrum auction *** these two agents may collude with each other or be bribed by buyers and sellers,which may create security risks,therefore,a secure double spectrum auction is proposed in this *** traditional secure double spectrum auctions,the spectrum auction server with Software Guard Extensions(SGX)component is used in this paper,which is an Ethereum blockchain platform that performs spectrum auctions.A secure double spectrum protocol is also designed,using SGX technology and cryptographic tools such as Paillier cryptosystem,stealth address technology and one-time ring signatures to well protect the private information of spectrum *** addition,the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification,and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum ***,security analysis and performance evaluation of our protocol are discussed.

关键词： Secure double spectrum auction SGX technology Privacy information Ethereum platform Verification

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Effect of silica on crystallization process of calcium ferrite:thermodynamic and kinetic analysis

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Journal of Iron and Steel Research International 2024年第12期31卷 2893-2902页

作者： Xu-chao Wang Cheng-yi Ding Xue-wei Lv Hong-ming Long Yu-xi Wu Feng Jiang Ren-de Chang Sheng Xue Qing-lin Chen Key Laboratory of Metallurgical Emission Reduction&Resources Recycling Anhui University of TechnologyMinistry of EducationMa’anshan243002AnhuiChina School of Metallurgical Engineering Anhui University of TechnologyMa’anshan243032AnhuiChina School of Materials Science and Engineering Chongqing UniversityChongqing400044China

SiO_(2)is the main component of gangue in sinters and a crucial constituent in the formation of the SiO_(2)–Fe_(2)O_(3)–Cao(SFC)*** non-isothermal crystallization kinetics of the SFC system were investigated using differential scanning *** crystallization process of SFC was studied under different cooling rates(5,10,15,and 20 K/min),and the crystalline phases and microstructures of the SFC crystals were verified through X-ray diffraction and scanning electron *** results indicate that when the SiO_(2)content is 2 wt.%,increasing the cooling rate promotes the precipitation of CaFe_(2)O_(4)(CF)in the SFC system,thereby inhibiting the precipitation of Ca_(2)Fe_(2)O_(5)(C_(2)F).In contrast to the Cao–Fe_(2)O_(3)(C–F)system,the addition of SiO_(2)does not alter the precipitation mechanisms of C_(2)F and *** further adding SiO_(2),the precipitation of Ca_(2)Sio_(4)(C_(2)S)significantly ***,the Cao content in the liquid phase *** leads to the crystallization process of the CF_(4)S(4 wt.%Sio_(2))system bypassing the precipitation of C_(2)F and directly forming CF and CaFe_(4)O_(7)(CF_(2)).In the case of the CF_(8)S(8 wt.%SiO_(2))system,the crystallization process skips the precipitation of C_(2)F and CF,directly yielding CF_(2).The crystallization process of both CF_(2)S(2 wt.%Sio_(2))and CF is similar,comprising two reaction *** Ozawa method was used to calculate the activation energy for the crystallization of C_(2)F and CF as-329 and-419 kJ/mol,*** using the Malek method reveals model functions for both stages.

关键词： Silica Calcium ferrite Sinter Cao–Fe_(2)O_(3)–SiO_(2) system Differential scanning calorimetry Crystallization

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Resource allocation for wireless networks based on enhanced Harris hawks optimisation algorithm

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International Journal of Security and Networks 2024年第4期19卷 178-187页

作者： Meng, Xianmeng Cai, Cuicui Tan, Linglong Wang, Qijian School of Electronics Engineering Anhui Xinhua University Hefei230088 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China School of Electronics and Information Engineering West Anhui University Lu’an237012 China

Efficient resource allocation is critical to improve the quality of service in wireless networks. The problem of resource allocation is usually non-convex and non-deterministic polynomial-hard. Meta-heuristic algorithms are widely used to solve non-convex optimisation problems due to their efficient execution and high iteration accuracy. The Harris hawk optimisation (HHO) algorithm has recently received attention as an effective approach for addressing various optimisation problems. However, the HHO algorithm is employed for resource allocation issues in WNs and suffers from early convergence and local optimal problems. To overcome these issues, we develop a novel enhanced HHO (EHHO) algorithm with low computational complexity and explore the performance of the EHHO in resource allocation. Firstly, we introduce the power allocation for secrecy rate maximisation and spectrum efficiency trade-off in wireless networks. Then, the fundamental of the basic HHO algorithm is described, and the EHHO algorithm is proposed with nonlinear control update and local search strategies. Finally, we demonstrate the remarkable capabilities of the EHHO in terms of the benchmark functions and resource allocation in wireless networks. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： energy efficiency enhanced Harris hawks optimisation algorithm meta-heuristic optimisation resource allocation secrecy rate spectral efficiency

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Overlapping community‐based particle swarm optimization algorithm for influence maximization in social networks

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CAAI Transactions on Intelligence technology 2023年第3期8卷 893-913页

作者： Lei Zhang Yutong Liu Haipeng Yang Fan Cheng Qi Liu Xingyi Zhang Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Intelligent Computing and Signal Processing of Ministry of EducationSchool of Computer Science and TechnologyAnhui UniversityHefeiChina School of Computer Science and Technology University of Science and Technology of ChinaHefeiChina

Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour *** the existing influence maximization methods,the community‐based ones can achieve a good balance between effectiveness and ***,this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping *** fact,many nodes in social networks are overlapping ones,which play more important role in influence *** this end,an overlapping community‐based particle swarm opti-mization algorithm named OCPSO for influence maximization in social networks,which can make full use of overlapping nodes,non‐overlapping nodes,and their interactive information is ***,an overlapping community detection algorithm is used to obtain the information of overlapping community structures,based on which three novel evolutionary strategies,such as initialisation,mutation,and local search are designed in OCPSO for better finding influential *** results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts(***,CMA‐IM,CIM,CDH‐SHRINK,CNCG,and CFIN).

关键词： computational intelligence data mining social network

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Robust federated contrastive recommender system against targeted model poisoning attack

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science China(Information sciences) 2025年第4期68卷 50-65页

作者： Wei YUAN Chaoqun YANG Liang QU Guanhua YE Quoc Viet Hung NGUYEN Hongzhi YIN School of Electrical Engineering and Computer Science The University of Queensland School of Information and Communication Technology Griffith University Deep Neural Computing Company Limited

Federated recommender systems(FedRecs) have garnered increasing attention recently, thanks to their privacypreserving benefits. However, the decentralized and open characteristics of current FedRecs present at least two ***, the performance of FedRecs is compromised due to highly sparse on-device data for each client. Second, the system's robustness is undermined by the vulnerability to model poisoning attacks launched by malicious users. In this paper, we introduce a novel contrastive learning framework designed to fully leverage the client's sparse data through embedding augmentation, referred to as CL4FedRec. Unlike previous contrastive learning approaches in FedRecs that necessitate clients to share their private parameters, our CL4FedRec aligns with the basic FedRec learning protocol, ensuring compatibility with most existing FedRec implementations. We then evaluate the robustness of FedRecs equipped with CL4FedRec by subjecting it to several state-of-the-art model poisoning attacks. Surprisingly, our observations reveal that contrastive learning tends to exacerbate the vulnerability of FedRecs to these attacks. This is attributed to the enhanced embedding uniformity, making the polluted target item embedding easily proximate to popular items. Based on this insight, we propose an enhanced and robust version of CL4FedRec(rCL4FedRec) by introducing a regularizer to maintain the distance among item embeddings with different popularity levels. Extensive experiments conducted on four commonly used recommendation datasets demonstrate that rCL4FedRec significantly enhances both the model's performance and the robustness of FedRecs.

关键词： federated recommender system contrastive learning model poisoning attack and defense

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Impact of asymptomatic infected individuals on epidemic transmission dynamics in multiplex networks with partial coupling

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Chinese Physics B 2024年第10期33卷 80-87页

作者： Xin Hu Jiaxing Chen Chengyi Xia School of Control Science and Engineering Tiangong UniversityTianjin 300387China School of Computer Science and Engineering Tianjin University of TechnologyTianjin 300384China School of Artificial Intelligence Tiangong UniversityTianjin 300387China

The theory of network science has attracted great interest of many researchers in the realm of biomathematics and public health,and numerous valuable epidemic models have been *** previous studies,it is common to set up a one-to-one correspondence between the nodes of a multi-layer network,ignoring the more complex situations in *** the present work,we explore this situation by setting up a partially coupled model of a two-layer network and investigating the impact of asymptomatic infected individuals on *** propose a self-discovery mechanism for asymptomatic infected individuals,taking into account situations such as nucleic acid testing in the community and individuals performing self-antigen testing during the *** these factors together,through the microscopic Markov chain approach(MMCA)and extensive Monte Carlo(MC)numerical simulations,we find that the greater the coupling between the networks,the more information dissemination is *** order to control the epidemics,more asymptomatic infected individuals should be made aware of their *** adoption of nucleic acid testing and individual adoption of antigenic self-testing can help to contain epidemic ***,the epidemic threshold of the proposed model is derived,and then miscellaneous factors affecting the epidemic threshold are also *** results are conducive to devising the prevention and control policies of pandemics.

关键词： asymptomatic infected individuals multi-layer networks partial interdependence

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Loop Subgraph-Level Greedy Mapping Algorithm for Grid Coarse-Grained Reconfigurable Array

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Tsinghua science and technology 2023年第2期28卷 330-343页

作者： Naijin Chen Fei Cheng Chenghao Han Jianhui Jiang Xiaoqing Wen School of Computer and Information Science Anhui Polytechnic UniversityWuhu 241000China School of Software Engineering Tongji UniversityShanghai 201804China Department of Computer Science and Networks Kyushu Institute of TechnologyFukuoka 820-8502Japan

To solve the problem of grid coarse-grained reconfigurable array task mapping under multiple constraints,we propose a Loop Subgraph-Level Greedy Mapping(LSLGM)algorithm using parallelism and processing element *** the constraint of a reconfigurable array,the LSLGM algorithm schedules node from a ready queue to the current reconfigurable cell array *** mapping a node,its successor’s indegree value will be dynamically *** its successor’s indegree is zero,it will be directly scheduled to the ready queue;otherwise,the predecessor must be dynamically *** the predecessor cannot be mapped,it will be scheduled to a blocking *** dynamically adjust the ready node scheduling order,the scheduling function is constructed by exploiting factors,such as node number,node level,and node *** with the loop subgraph-level mapping algorithm,experimental results show that the total cycles of the LSLGM algorithm decreases by an average of 33.0%(PEA44)and 33.9%(PEA_(7×7)).Compared with the epimorphism map algorithm,the total cycles of the LSLGM algorithm decrease by an average of 38.1%(PEA_(4×4))and 39.0%(PEA_(7×7)).The feasibility of LSLGM is verified.

关键词： Grid Coarse-Grained Reconfigurable Array(GCGRA) mapping loop subgraph scheduling

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Feature Enhancement and Offset Learning for Multi-Stage Human Pose Estimation 6

Feature Enhancement and Offset Learning for Multi-Stage Huma...

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6th International Conference on Communications, Information System and computer engineering, CISCE 2024

作者： Xie, Xuchao Chen, Yi Xu, Yinhao Gao, Teng School of Computer Science and Technology Anhui University Anhui China

ISBN: (纸本)9798350353174

Most of the existing studies have focused on human pose estimation at high resolution;however, research on low-resolution scenes has not yet received extensive attention. The quantization error associated with human pose estimation based on heat map regression increases as the resolution of the detected image decreases, thus seriously affecting the model's detection accuracy. Moreover, the low-resolution image itself loses much of the position information, thus increasing the difficulty of key point localization. Detection at low resolution has important applications in real-world environments and represents an urgent problem to be solved. In this paper, we propose a feature-enhanced offset learning model for human pose estimation based on the high-resolution network HRNet, effectively addressing the problem of quantization error arising from Gaussian heatmap encoding of key point location and addressing the problem of losing detailed information in low-resolution images. The model contains a multi-stage network that gradually obtains lower resolution features while maintaining the existing resolution features and improves the feature extraction capability of the backbone model by fusing different scale features. The extracted information can be enriched with positional information, semantic information, and channel context information by the feature enhancement module, thereby alleviating the problem of missing details due to the low-resolution images. This enhanced information is very important for the subsequent prediction of key points. The offset vector field-based model is used to find out the highest response point position of the heat map and take this position as a rough estimation. Subsequently, it regresses the heat map according to the offset vector to get the offset vector of the corresponding position. Finally, the final position prediction is obtained from the combination of the rough key point position and the offset vector, significantly mitigating

关键词： Vector quantization

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