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Quantum Generative Adversarial Network: A Survey

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Computers, Materials & Continua 2020年第7期64卷 401-438页

作者： Tong Li Shibin Zhang jinyue xia School of Cybersecurity Chengdu University of Information TechnologyChengdu610225China International Business Machines Corporation New York14201USA

Generative adversarial network(GAN)is one of the most promising methods for unsupervised learning in recent *** works via adversarial training concept and has shown excellent performance in the fields image synthesis,image super-resolution,video generation,image translation,*** with classical algorithms,quantum algorithms have their unique advantages in dealing with complex tasks,quantum machine learning(QML)is one of the most promising quantum algorithms with the rapid development of quantum ***,Quantum generative adversarial network(QGAN)has shown the potential exponential quantum speedups in terms of ***,QGAN also exhibits some problems,such as barren plateaus,unstable gradient,model collapse,absent complete scientific evaluation system,*** to improve the theory of QGAN and apply it that have attracted some *** this paper,we comprehensively and deeply review recently proposed GAN and QAGN models and their applications,and we discuss the existing problems and future research trends of QGAN.

关键词： Quantum machine learning generative adversarial network quantum generative adversarial network mode collapse

Review of Access Control Model

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Journal of Cyber Security 2019年第1期1卷 43-50页

作者： Zhengtao Liu Wen Gu jinyue xia School of Computer Science and Engineering Sanjiang UniversityNanjing210012China International Business Machines Corporation(IBM) New YorkUSA

Access control is one of the core problems in data management *** this paper,the system requirements were described in three aspects:the traditional access control model,the access control model in the Internet era and the access control model in the cloud computing ***,the corresponding major models were listed and their characteristics and problems were ***,the development trend of the corresponding model was proposed.

关键词： Access control RBAC ABAC cloud computing

Correlation Analysis between Economic Growth and Environmental Quality

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Computer Systems Science & Engineering 2022年第4期41卷 127-140页

作者： Baiqing Zhou Na Li Duan Lu jinyue xia Huzhou Vocational&Technical College Huzhou313000China International Business Machines Corporation(IBM) New YorkNYUSA

With the rapid development of the economy,China’s environment has been damaged severely,which has attracted much attention from scholars and the local *** concept of green development has been an underlying trend since 2012,and it is of great signiﬁcance to explore the relationship between economic growth and environmental *** is a prefecture-level city under the jurisdiction of Zhejiang Province,and it is one of the 27 cities in the central area of the Yangtze River *** recent years,this city develops well not only in economic development but also in maintaining a green *** the paper,the back propagation neural network is used to evaluate the local environmental ***,the panel model is exploited to analyze the relationship between economic growth and environmental *** the data presented in the paper range from the year 2008 to *** analysis indicates that the evaluation value of environmental quality,the emissions of industrial SO2,and waste water exhibit an inverted U-shaped relationship with economic *** for the regression results,the inﬂection point of income in the environmental Kuznets curve of the model which takes the evaluation value of the environmental quality as a dependent variable is higher than that of the model which takes the SO2 emission as an independent *** research result would help the local government to take appropriate countermeasures to improve the environment and economy.

关键词： Economic growth environmental quality BP neural network environmental Kuznets curve

A Temporal Multi-Tenant RBAC Model for Collaborative Cloud Services

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Computers, Materials & Continua 2020年第5期63卷 861-871页

作者： Zhengtao Liu Yi Ying Yaqin Peng jinyue xia School of Computer Science and Engineering Sanjiang UniversityNanjing210012China International Business Machines Corporation New YorkUSA

Multi-tenant collaboration brings the challenge to access control in cloud computing *** on the multi-tenant role-based access control(MT-RBAC)model,a Temporal MT-RBAC(TMT-RBAC)model for collaborative cloud services is *** adds the time constraint between trusted tenants,including usable role time constraint based on both calendar and interval *** shows that the new model strengthens the presentation ability of MT-RBAC model,achieves the finer-grained access control,reduces the management costs and enhances the security of multi-tenant collaboration in cloud computing environment.

关键词： Cloud computing multi-tenant collaboration access control temporal

An Improved Algorithm for Mining Correlation Item Pairs

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Computers, Materials & Continua 2020年第10期65卷 337-354页

作者： Tao Li Yongzhen Ren Yongjun Ren jinyue xia College of Electronic and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China College of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China International Business Machines Corporation(IBM) New YorkUSA

Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher *** the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association *** view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori *** can dig item sets with low-support but *** the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be *** paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search *** greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the *** with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation *** it improves the mining efficiency and accuracy.

关键词： Interestingness item pairs positive correlation association rules redundancy

A Multi-Tenant Usage Access Model for Cloud Computing

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Computers, Materials & Continua 2020年第8期64卷 1233-1245页

作者： Zhengtao Liu Yun Yang Wen Gu jinyue xia School of Computer Science and Engineering Sanjiang UniversityNanjing210012China International Business Machines Corporation(IBM) New YorkUSA

Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared *** offers tremendous advantages for enterprises and service *** is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a *** realize access control in a multi-tenant cloud computing environment,this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among *** model consists of three sub-models,which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application *** an established trust relation in MT-UCON(Multi-tenant Usage Access Control),the trustee can precisely authorize cross-tenant accesses to the trustor’s resources consistent with constraints over the trust relation and other components designated by the *** addition,the security of the model is analyzed by an information flow *** model adapts to the characteristics of a dynamic and open multi-tenant cloud computing environment and achieves fine-grained access control within and between tenants.

关键词： Multi-tenant usage access control model cloud computing

Ground Nephogram Recognition Algorithm Based on Selective Neural Network Ensemble

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Computers, Materials & Continua 2020年第5期63卷 621-631页

作者： Tao Li xiang Li Yongjun Ren jinyue xia College of Electronic and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China College of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China International Business Machines Corporation(IBM) New YorkUSA

In view of the low accuracy of traditional ground nephogram recognition model,the authors put forward a k-means algorithm-acquired neural network ensemble method,which takes BP neural network ensemble model as the basis,uses k-means algorithm to choose the individual neural networks with partial diversities for integration,and builds the cloud form classification *** simulation experiments on ground nephogram samples,the results show that the algorithm proposed in the article can effectively improve the Classification accuracy of ground nephogram recognition in comparison with applying single BP neural network and traditional BP AdaBoost ensemble algorithm on classification of ground nephogram.

关键词： Cloud shape k-means BP neural network adaboost

A Mixed Method for Feature Extraction Based on Resonance Filtering

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Intelligent Automation & Soft Computing 2023年第3期35卷 3141-3154页

作者： xia Zhang Wei Lu Youwei Ding Yihua Song jinyue xia School of Artificial Intelligence and Information Technology Nanjing University of Chinese MedicineNanjing210023China School of Artificial Intelligence Nanjing Vocational College of Information TechnologyNanjing210023China School of Automation Nanjing University of Information Science and Technology210044China International Business Machines Corporation(IBM) NY10504USA

Machine learning tasks such as image classiﬁcation need to select the features that can describe the image *** image has individual features and common features,and they are *** only the individual features of the image are emphasized,the neural network is prone to overﬁ*** only the common features of images are emphasized,neural networks will not be able to adapt to diversiﬁed learning *** order to better integrate individual features and common features,based on skeleton and edge individual features extraction,this paper designed a mixed feature extraction method based on reso-nanceﬁltering,named resonance *** layer is in front of the neural network input layer,using K3M algorithm to extract image skeleton,using the Canny algorithm to extract image border,using resonanceﬁltering to reconstruct training image byﬁltering image noise,through the common features of the images in the training set and efﬁcient expression of individual characteristics to improve the efﬁciency of feature extraction of neural network,so as to improve the accuracy of neural network *** the fully connected neural net-work and LeNet-5 neural networks for example,the experiment on handwritten digits database shows that the proposed mixed feature extraction method can improve the accuracy of training whileﬁltering out part of image noise data.

关键词： Deep learning feature extraction resonanceﬁltering image reconstruction

Quantum Fuzzy Support Vector Machine for Binary Classification

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Computer Systems Science & Engineering 2023年第6期45卷 2783-2794页

作者： Xi Huang Shibin Zhang Chen Lin jinyue xia School of Cybersecurity Chengdu University of Information TechnologyChengdu610225China Sichuan Key Laboratory of Advanced Cryptography and System Security Chengdu610225China International Business Machines Corporation(IBM) New York14201USA

In the objective world,how to deal with the complexity and uncertainty of big data efficiently and accurately has become the premise and key to machine *** support vector machine(FSVM)not only deals with the classifi-cation problems for training samples with fuzzy information,but also assigns a fuzzy membership degree to each training sample,allowing different training samples to contribute differently in predicting an optimal hyperplane to separate two classes with maximum margin,reducing the effect of outliers and noise,Quantum computing has super parallel computing capabilities and holds the pro-mise of faster algorithmic processing of ***,FSVM and quantum com-puting are incapable of dealing with the complexity and uncertainty of big data in an efficient and accurate *** paper research and propose an efficient and accurate quantum fuzzy support vector machine(QFSVM)algorithm based on the fact that quantum computing can efficiently process large amounts of data and FSVM is easy to deal with the complexity and uncertainty *** central idea of the proposed algorithm is to use the quantum algorithm for solving linear systems of equations(HHL algorithm)and the least-squares method to solve the quadratic programming problem in the *** proposed algorithm can deter-mine whether a sample belongs to the positive or negative class while also achiev-ing a good generalization ***,this paper applies QFSVM to handwritten character recognition and demonstrates that QFSVM can be run on quantum computers,and achieve accurate classification of handwritten *** compared to FSVM,QFSVM’s computational complexity decreases expo-nentially with the number of training samples.

关键词： Quantum fuzzy support vector machine(QFSVM) fuzzy support vector machine(FSVM) quantum computing