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Multi-soliton solutions, breather-like and bound-state solitons for complex modified Korteweg–de Vries equation in optical fibers

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Chinese Physics B 2024年第6期33卷 119-123页

作者：兰中周 School of computer Information management Inner Mongolia University of Finance and EconomicsHohhot 010070China

Under investigation in this paper is a complex modified Korteweg–de Vries(KdV) equation, which describes the propagation of short pulses in optical fibers. Bilinear forms and multi-soliton solutions are obtained through the Hirota method and symbolic computation. Breather-like and bound-state solitons are constructed in which the signs of the imaginary parts of the complex wave numbers and the initial separations of the two parallel solitons are important factors for the interaction patterns. The periodic structures and position-induced phase shift of some solutions are introduced.

关键词： complex modified KdV equation multi-soliton solutions breather-like bound-state

Research on Credit Regulation Mechanism of E-commerce Platform Based on Evolutionary Game Theory

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 330-359页

作者： Zeguo Qiu Yuchen Yin Yao Yuan Yunhao Chen School of computer and Information Engineering Harbin University of CommerceHarbin150028China School of management Harbin University of CommerceHarbin150028China

In the growing e-commerce industry,the problem of malicious business operations has become increasingly prominent,exposing many problems such as weak supervision of e-commerce platforms and no way for consumers to *** order to solve the problems of counterfeit and shoddy products on e-commerce platforms and promote the sustainable development of the e-commerce industry in China,this paper constructs a three-party evolutionary game model of e-commerce platforms,merchants,and consumers,investigates the influence of each influencing factor on each party’s strategy choice,and provides targeted suggestions to e-commerce platforms based on relevant ***,the impact of several important parameters on the equilibrium solution is discussed through sensitivity *** results show that:1)the smaller the cost difference between active and negative regulation,the more the e-commerce platform tends to active regulation strategy,but increasing fines for dishonest merchants and consumer complaints have little impact on the e-commerce platform;2)increasing consumer compensation,creating an honest business environment,and reducing the cost of honest business all help companies tend to operate in good faith;3)the only factor that affects the tendency of consumer complaint strategies is the cost of *** loss suffered by silence and the compensation given to consumers have little effect on consumers’tendency to complain *** results can provide theoretical guidance for participants to make useful strategic decisions in the e-commerce market.

关键词： Evolutionary game e-commerce data simulation

Do community responses influence OSS contributor retention? A survival analysis

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Science China(Information Sciences) 2024年第8期67卷 331-333页

作者： Zhe WANG Zhixing LI Yue YU School of Public Policy and management Tsinghua University College of computer National University of Defense Technology

Open source software(OSS) projects usually employ a community-based model, where geographically distributed developers from around the world collaborate online [1].With the rise of social coding sites like Git Hub, contributing to OSS projects has become easier and more accessible, motivating many developers to join the OSS community [2]. The continued submission of high-quality contributions from these community developers has led to numerous corrections, improvements, and innovations in many successful OSS projects [1, 2].

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A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

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computers, Materials & Continua 2024年第2期78卷 2787-2811页

作者： Ye Lu Tao Feng Chunyan Liu Wenbo Zhang School of computer&Communication Lanzhou University of TechnologyLanzhou730000China School of Economics&management Lanzhou University of TechnologyLanzhou730000China School of computer Science Baoji University of Arts and ScienceBaoji721000China

The Access control scheme is an effective method to protect user data *** access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized ***,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so *** paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution *** technology tracks the authorization of attribute private *** credit scoring method improves the Raft protocol in consensus ***,the interplanetary file system(IPFS)addresses the capacity deficit of *** the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file *** optimizes the data-sharing *** the same time,Proxy Re-Encryption(PRE)technology is used to update the access *** proposed scheme proved to be *** analysis and experimental results show that the proposed scheme has higher efficiency and more *** can meet the needs of medical institutions.

关键词： Blockchain access-control CP-ABE cloud health

Double integral-enhanced Zeroing neural network with linear noise rejection for time-varying matrix inverse

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 197-210页

作者： Bolin Liao Luyang Han Xinwei Cao Shuai Li Jianfeng Li College of computer Science and Engineering Jishou UniversityJishouChina School of management Shanghai UniversityShanghaiChina School of Engineering Swansea UniversitySwanseaUK

In engineering fields,time-varying matrix inversion(TVMI)issue is often *** neural network(ZNN)has been extensively employed to resolve the TVMI ***,the original ZNN(OZNN)and the integral-enhanced ZNN(IEZNN)usually fail to deal with the TVMI problem under unbounded noises,such as linear ***,a neural network model that can handle the TVMI under linear noise interference is urgently *** paper develops a double integral-enhanced ZNN(DIEZNN)model based on a novel integral-type design formula with inherent linear-noise ***,its convergence and robustness are verified by deriva-tion *** comparison and verification,the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise *** experi-ments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear *** general,the DIEZNN model is an innovative work and is proposed for the first ***,the errors of DIEZNN are always less than 1�10−3 under linear noises,whereas the error norms of OZNN and IEZNN models are not convergent to *** addition,these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN.

关键词： neural network real-time systems

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

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computers, Materials & Continua 2024年第6期79卷 4127-4148页

作者： Abdulelah Alwabel Chinmaya Kumar Swain Department of computer Sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of computer Science and Engineering Institute of Management and Information TechnologyCuttackBPUTOdishaIndia

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data ***,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud *** approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing *** approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of *** this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing *** consider four cost-types for application deployment:Computation,communication,energy consumption,and *** proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the *** extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art *** results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

关键词： Placement mechanism application module placement fog computing cloud computing genetic algorithm flamingo search algorithm

Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach

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computers, Materials & Continua 2024年第2期78卷 2557-2573页

作者： Dayu Xu Jiaming Lu Xuyao Zhang Hongtao Zhang College of Mathematics and computer Science Zhejiang A&F UniversityHangzhou311300China College of Economics and management Zhejiang A&F UniversityHangzhou311300China

Data stream clustering is integral to contemporary big data ***,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current *** paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the *** original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior *** the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further *** work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat *** arrival,this ensures that new data points interact solely with clusters in very close *** significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some *** apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA *** results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.

关键词： Data stream clustering TEDA KD-tree scapegoat tree

A Hybrid Air Quality Prediction Model Based on Empirical Mode Decomposition

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Tsinghua Science and Technology 2024年第1期29卷 99-111页

作者： Yuxuan Cao Difei Zhang Shaoqi Ding Weiyi Zhong Chao Yan School of computer Science Qufu Normal UniversityRizhao 276826China School of Mathematical Sciences Qufu Normal UniversityQufu 273165China School of computer Science Qufu Normal UniversityRizhao 270826China College of Economic and management Shandong University of Science and TechnologyQingdao 250307China

Air pollution is a severe environmental problem in urban *** air quality prediction can help governments and individuals make proper decisions to cope with potential air *** a classic time series forecasting model,the AutoRegressive Integrated Moving Average(ARIMA)has been widely adopted in air quality ***,because of the volatility of air quality and the lack of additional context information,i.e.,the spatial relationships among monitor stations,traditional ARIMA models suffer from unstable prediction *** some deep networks can achieve higher accuracy,a mass of training data,heavy computing,and time cost are *** this paper,we propose a hybrid model to simultaneously predict seven air pollution indicators from multiple monitoring *** proposed model consists of three components:(1)an extended ARIMA to predict matrix series of multiple air quality indicators from several adjacent monitoring stations;(2)the Empirical Mode Decomposition(EMD)to decompose the air quality time series data into multiple smooth sub-series;and(3)the truncated Singular Value Decomposition(SvD)to compress and denoise the expanded *** results on the public dataset show that our proposed model outperforms the state-of-art air quality forecasting models in both accuracy and time cost.

关键词： air quality prediction Empirical Mode Decomposition(EMD) Singular Value Decomposition(SVD) AutoRegressive Integrated Moving Average(ARIMA)

Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

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computers, Materials & Continua 2024年第4期79卷 695-712页

作者： Fangjun Luan Xuewen Mu Shuai Yuan Department of computer Technology School of Computer Science and EngineeringShenyang Jianzhu UniversityShenyang110168China Liaoning Province Big Data management and Analysis Laboratory of Urban Construction Shenyang Jianzhu UniversityShenyang110168China Shenyang Branch of National Special computer Engineering Technology Research Center Shenyang Jianzhu UniversityShenyang110168China

Online Signature Verification (OSV), as a personal identification technology, is widely used in various ***, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. Toaddress these issues, we propose a novel approach for online signature verification, using a one-dimensionalGhost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolutionwith a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residualstructure is introduced to leverage both self-attention and convolution mechanisms for capturing global featureinformation and extracting local information, effectively complementing whole and local signature features andmitigating the problem of insufficient feature extraction. Then, the Ghost-based Convolution and Self-Attention(ACG) block is proposed to simplify the common parts between convolution and self-attention using the Ghostmodule and employ feature transformation to obtain intermediate features, thus reducing computational ***, feature selection is performed using the random forestmethod, and the data is dimensionally reducedusing Principal Component Analysis (PCA). Finally, tests are implemented on the MCYT-100 datasets and theSVC-2004 Task2 datasets, and the equal error rates (EERs) for small-sample training using five genuine andforged signatures are 3.07% and 4.17%, respectively. The EERs for training with ten genuine and forged signaturesare 0.91% and 2.12% on the respective datasets. The experimental results illustrate that the proposed approacheffectively enhances the accuracy of online signature verification.

关键词： Online signature verification feature selection ACG block ghost-ACmix residual structure