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< Page ,Total 13 >
Fast PageRank Computation Based on Network Decomposition and DAG Structure EI SCIE Scopus
期刊论文 | 2018 , 6 , 41760-41770 | IEEE ACCESS
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Abstract :

PageRank has been widely used for the problem of evaluating the importance of data in many applications, such as Web science, information systems, and social network analysis. As vast amounts of data generate, the development of efficient PageRank computation is a vibrant area of contemporary research. In this paper, we propose a fast PageRank computation method based on network decomposition and the structure of directed acyclic graph (DAG). A network decomposition technique is first introduced to decompose the original network into three parts, including a general sub-network and two sub-DAGs. Based on the acyclic characteristic, we demonstrate that these two sub-DAGs can be theoretically lumped into two single nodes by a similarity transformation. Then, the PageRank problem on the original network is transformed into a PageRank problem on a much smaller network, and the full PageRank vector can be easily recovered from the result of new problem. As the time taken by the estimation of PageRank is directly proportional to the network size, the proposed method achieves an improved time complexity and is more efficient as the size of two sub-DAGs increases. Experimental results on real data sets show that our method provides a significant speedup compared with existing alternatives.

Keyword :

link analysis DAG structure PageRank network decomposition

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GB/T 7714 Zhu, Zhibo , Peng, Qinke , Li, Zhi et al. Fast PageRank Computation Based on Network Decomposition and DAG Structure [J]. | IEEE ACCESS , 2018 , 6 : 41760-41770 .
MLA Zhu, Zhibo et al. "Fast PageRank Computation Based on Network Decomposition and DAG Structure" . | IEEE ACCESS 6 (2018) : 41760-41770 .
APA Zhu, Zhibo , Peng, Qinke , Li, Zhi , Guan, Xinyu , Muhammad, Owais . Fast PageRank Computation Based on Network Decomposition and DAG Structure . | IEEE ACCESS , 2018 , 6 , 41760-41770 .
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Analyzing and Detecting Money-Laundering Accounts in Online Social Networks SCIE Scopus
期刊论文 | 2018 , 32 (3) , 115-121 | IEEE NETWORK
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Abstract :

Virtual currency in OSNs plays an increasingly important role in supporting various financial activities such as currency exchange, online shopping, and paid games. Users usually purchase virtual currency using real currency. This fact motivates attackers to instrument an army of accounts to collect virtual currency unethically or illegally with no or very low cost and then launder the collected virtual money for massive profit. Such attacks not only introduce significant financial loss of victim users, but also harm the viability of the ecosystem. It is therefore of central importance to detect malicious OSN accounts that engage in laundering virtual currency. To this end, we extensively study the behavior of both malicious and benign accounts based on operation data collected from Tencent QQ, one of the largest OSNs in the world. Then, we devise multi-faceted features that characterize accounts from three aspects: account viability, transaction sequences, and spatial correlation among accounts. Finally, we propose a detection method by integrating these features using a statistical classifier, which can achieve a high detection rate of 94.2 percent at a very low false positive rate of 0.97 percent.

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GB/T 7714 Zhou, Yadong , Wang, Ximi , Zhang, Junjie et al. Analyzing and Detecting Money-Laundering Accounts in Online Social Networks [J]. | IEEE NETWORK , 2018 , 32 (3) : 115-121 .
MLA Zhou, Yadong et al. "Analyzing and Detecting Money-Laundering Accounts in Online Social Networks" . | IEEE NETWORK 32 . 3 (2018) : 115-121 .
APA Zhou, Yadong , Wang, Ximi , Zhang, Junjie , Zhang, Peng , Liu, Lili , Jin, Huan et al. Analyzing and Detecting Money-Laundering Accounts in Online Social Networks . | IEEE NETWORK , 2018 , 32 (3) , 115-121 .
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Two-step output feedback predictive control for Hammerstein systems with networked-induced time delays EI Scopus
期刊论文 | 2018 , 49 (13) , 2753-2762 | International Journal of Systems Science
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Abstract :

This paper is mainly concerned with the design problem of two-step model predictive control (MPC) for nonlinear systems represented by Hammerstein model, where the network-induced time delays exist between sensor to controller (S2C) and controller to actuator (C2A) links. We assume that the system state is not measurable, so the state observer is employed to estimate the state. The intermediate variable for the linear part of the system is calculated by minimising the quadratic performance function. The time-delay compensation algorithm of two-step output feedback predictive control (TSOFPC) for Hammerstein systems is presented and validated by a numerical example. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

Keyword :

Hammerstein model Network induced time delay Networked-induced time delay Output feedback Performance functions Predictive control Time delay compensation TWo-step model

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GB/T 7714 Wang, Jun , Ding, Baocang . Two-step output feedback predictive control for Hammerstein systems with networked-induced time delays [J]. | International Journal of Systems Science , 2018 , 49 (13) : 2753-2762 .
MLA Wang, Jun et al. "Two-step output feedback predictive control for Hammerstein systems with networked-induced time delays" . | International Journal of Systems Science 49 . 13 (2018) : 2753-2762 .
APA Wang, Jun , Ding, Baocang . Two-step output feedback predictive control for Hammerstein systems with networked-induced time delays . | International Journal of Systems Science , 2018 , 49 (13) , 2753-2762 .
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A Gaussian Estimation of Distribution Algorithm Using General Second-order Mixed Moment EI Scopus CSCD PKU
期刊论文 | 2018 , 44 (4) , 635-645 | Zidonghua Xuebao/Acta Automatica Sinica
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Abstract :

Traditional Gaussian estimation of distribution algorithms (GEDAs) are confronted with issues that variable variances decrease fast and the long axis of the probability density ellipsoid (PDE) tends to be perpendicular to the improvement direction of the objective function, leading to reduction of search efficiency of GEDA and premature convergence. To alleviate these issues, this paper proposes a novel GEDA based on the general second-order mixed moment. In each iteration, this algorithm first estimates an initial mean using weighted excellent samples, then shifts the mean along the improvement direction of the objective function and estimates the covariance matrix with the new mean as the center. Theoretical and numerical analysis results both show that this simple operation can adaptively adjust the location, size and long axis direction of PDE without increasing computation. As a consequence, the search efficiency of the algorithm is improved. Experiments are conducted on 14 benchmark functions. The resultant Cohen0s d effect size demonstrates that the proposed algorithm possesses stronger global optimization ability than traditional GEDA. And compared with some state-of-the-art particle swarm optimization and differential evolution algorithms, it can produce significantly superior solutions for 9 functions within the same function evaluation times. Copyright © 2018 Acta Automatica Sinica. All rights reserved.

Keyword :

Benchmark functions Differential evolution algorithms Estimation of distribution algorithms Objective functions Optimization ability Pre-mature convergences Probability densities Search efficiency

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GB/T 7714 Ren, Zhi-Gang , Liang, Yong-Sheng , Zhang, Ai-Min et al. A Gaussian Estimation of Distribution Algorithm Using General Second-order Mixed Moment [J]. | Zidonghua Xuebao/Acta Automatica Sinica , 2018 , 44 (4) : 635-645 .
MLA Ren, Zhi-Gang et al. "A Gaussian Estimation of Distribution Algorithm Using General Second-order Mixed Moment" . | Zidonghua Xuebao/Acta Automatica Sinica 44 . 4 (2018) : 635-645 .
APA Ren, Zhi-Gang , Liang, Yong-Sheng , Zhang, Ai-Min , Pang, Bei . A Gaussian Estimation of Distribution Algorithm Using General Second-order Mixed Moment . | Zidonghua Xuebao/Acta Automatica Sinica , 2018 , 44 (4) , 635-645 .
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Efficient Estimation of View Synthesis Distortion for Depth Coding Optimization EI Scopus
期刊论文 | 2018 | IEEE Transactions on Multimedia
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Abstract :

Depth coding in depth-based 3D video is unique in that its quality is measured by view synthesis distortion (VSD) rather than the depth distortion itself, which further complicates the coding optimization as the VSD is related to quality of both the associated depth and texture videos. In this paper, an efficient VSD estimation scheme is developed to measure the effect of depth errors on the VSD for a block given its depth distortion in mean-squared error. Unlike other relevant VSD models which involve computationally intensive parameter training or Fourier transform, the proposed scheme is free of parameter training while taking advantage of integer 4&#x00D7;4 discrete Cosine transform to replace Fourier transform, thus well saving computational cost and diminishing sensitivity to training dataset of video. The proposed scheme is then incorporated on the coding unit basis into the rate-distortion optimization for depth coding optimization, coupled with adapting quantization parameter accordingly to accommodate local effect of the depth errors on the VSD. Experimental results show that our solution obtains better results in depth coding than three testing solutions, on the platform of H.264/AVC reference software JM16.0. Benefiting from the efficiency of the VSD estimation, low coding complexity is obtained as well. The proposed solution is further evaluated on the reference software HTM13.0 of the latest 3D-HEVC standard, exhibiting better and comparable results compared against the HTM codec with the view synthesis optimization disabled and enabled, respectively. IEEE

Keyword :

3-D videos 3D-HEVC Depth coding H.264/AVC Rate-distortion optimization View synthesis

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GB/T 7714 Yang, Meng , Zhu, Ce , Lan, Xuguang et al. Efficient Estimation of View Synthesis Distortion for Depth Coding Optimization [J]. | IEEE Transactions on Multimedia , 2018 .
MLA Yang, Meng et al. "Efficient Estimation of View Synthesis Distortion for Depth Coding Optimization" . | IEEE Transactions on Multimedia (2018) .
APA Yang, Meng , Zhu, Ce , Lan, Xuguang , Zheng, Nanning . Efficient Estimation of View Synthesis Distortion for Depth Coding Optimization . | IEEE Transactions on Multimedia , 2018 .
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Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems EI Scopus
期刊论文 | 2018 | ISA Transactions
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Abstract :

This paper proposes an event-triggered distributed receding horizon control (DRHC) approach for the formation and tracking problems of homogeneous multi-agent systems. For each agent, an event-triggering condition, based on assumed predictive information of the neighbours, is derived from stability analysis. Considering the uncertain deviation between the assumed and true predictive information, we design a time-varying compatibility constraint for the individual optimization problem. In the event-triggered DRHC algorithm, each agent solves the optimization problem and communicates with its neighbours only when the event-triggering condition is satisfied, so the communication and computation burden are reduced. Moreover, guarantees for the recursive feasibility and asymptotic stability of the overall system are proved. A simulation example is provided to illustrate effectiveness of the proposed approach. © 2018 ISA

Keyword :

Compatibility constraint Computation burden Event-triggering Optimization problems Predictive information Receding horizon control Simulation example Stability analysis

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GB/T 7714 Yang, Yuanqing , Ding, Baocang . Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems [J]. | ISA Transactions , 2018 .
MLA Yang, Yuanqing et al. "Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems" . | ISA Transactions (2018) .
APA Yang, Yuanqing , Ding, Baocang . Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems . | ISA Transactions , 2018 .
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Dynamic Output Feedback Predictive Control with One Free Control Move for Takagi-Sugeno Model with Bounded Disturbance EI Scopus
期刊论文 | 2018 | IEEE Transactions on Fuzzy Systems
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Abstract :

In this paper, the fuzzy model predictive control for nonlinear system represented by a discrete-time Takagi-Sugeno model with norm-bounded disturbance is studied. An output feedback algorithm is proposed by parameterizing the infinite horizon control moves and estimated states into one free control move, one free estimated state followed by a dynamic output feedback law. Since the introduced free control move and free estimated state are decision variables, which bring more degrees of freedom for the optimization, larger feasibility region and better control performance can be achieved. By properly designing the constraints in optimization problem, the recursive feasibility is guaranteed, and the convergence of the closed-loop system to the neighborhood of the equilibrium is guaranteed. A numerical example is given to illustrate the effectiveness of the proposed algorithm. IEEE

Keyword :

Dynamic output feedback Free control free estimate state Fuzzy model predictive control Takagi-Sugeno modeling

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GB/T 7714 Hu, Jianchen , Ding, Bao-Cang . Dynamic Output Feedback Predictive Control with One Free Control Move for Takagi-Sugeno Model with Bounded Disturbance [J]. | IEEE Transactions on Fuzzy Systems , 2018 .
MLA Hu, Jianchen et al. "Dynamic Output Feedback Predictive Control with One Free Control Move for Takagi-Sugeno Model with Bounded Disturbance" . | IEEE Transactions on Fuzzy Systems (2018) .
APA Hu, Jianchen , Ding, Bao-Cang . Dynamic Output Feedback Predictive Control with One Free Control Move for Takagi-Sugeno Model with Bounded Disturbance . | IEEE Transactions on Fuzzy Systems , 2018 .
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From big data to knowledge: A spatio-temporal approach to malware detection EI SCIE Scopus
期刊论文 | 2018 , 74 , 167-183 | COMPUTERS & SECURITY
WoS CC Cited Count: 1 SCOPUS Cited Count: 1
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Abstract :

The deployment of endpoint protection has been gradually migrated from individual clients to remote cloud servers, which is termed as cloud based security service. The new paradigm of security defense produces a large amount of data and log files, and motivates data driven techniques for detecting malicious software. This paper conducts an empirical study on the log of a real cloud based security service to characterize the occurrence of executable files in end hosts, which concerns 124,782 benign and 113,305 malicious executable files occurred in 165,549,417 end hosts. The end hosts and the timestamps that an executable file occurs in provide insights into the distribution of software in wild from spatial and temporal perspectives, respectively. Meanwhile, we investigate the strategies behind the characterizations, and observe the preferential attachment process and the periodicity of file occurrence in end hosts. The observed different occurrence patterns of benign and malicious files in end hosts inspire us a new scalable approach to malware detection. We learn from the characterizations that, the associated files shared more spatial and temporal information in common are more likely to be same in their labels, either benign or malicious. Thus, we devise a graph based semi-supervised learning algorithm for real-time malware detection by taking into account the spatio-temporal information of the distribution of executable files. Experimental results demonstrate that our approach increases the performance on malware detection by 14.7% over previous techniques on average. (C) 2018 Elsevier Ltd. All rights reserved.

Keyword :

Content-agnostic Graph based semi-supervised learning File co-occurrence Malware detection Data-driven security analysis

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GB/T 7714 Mao, Weixuan , Cai, Zhongmin , Yang, Yuan et al. From big data to knowledge: A spatio-temporal approach to malware detection [J]. | COMPUTERS & SECURITY , 2018 , 74 : 167-183 .
MLA Mao, Weixuan et al. "From big data to knowledge: A spatio-temporal approach to malware detection" . | COMPUTERS & SECURITY 74 (2018) : 167-183 .
APA Mao, Weixuan , Cai, Zhongmin , Yang, Yuan , Shi, Xiaohong , Guan, Xiaohong . From big data to knowledge: A spatio-temporal approach to malware detection . | COMPUTERS & SECURITY , 2018 , 74 , 167-183 .
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Modeling Stock Price Dynamics With Fuzzy Opinion Networks EI SSCI SCIE Scopus
期刊论文 | 2017 , 25 (2) , 277-301 | IEEE TRANSACTIONS ON FUZZY SYSTEMS | IF: 8.415
WoS CC Cited Count: 3
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Abstract :

We propose a mathematical model for the word-of-mouth communications among stock investors through social networks and explore howthe changes of the investors' social networks influence the stock price dynamics and vice versa. An investor is modeled as a Gaussian fuzzy set (a fuzzy opinion) with the center and standard deviation as inputs and the fuzzy set itself as output. Investors are connected in the following fashion: the center input of an investor is taken as the average of the neighbors' outputs, where two investors are neighbors if their fuzzy opinions are close enough to each other, and the standard deviation (uncertainty) input is taken with local, global, or external reference schemes to model different scenarios of how investors define uncertainties. The centers and standard deviations of the fuzzy opinions are the expected prices and their uncertainties, respectively, that are used as inputs to the price dynamic equation. We prove that with the local reference scheme the investors converge to different groups in finite time, while with the global or external reference schemes all investors converge to a consensus within finite time and the consensus may change with time in the external reference case. We show how to model trend followers, contrarians, and manipulators within this mathematical framework and prove that the biggest enemy of a manipulator is the other manipulators. We perform Monte Carlo simulations to show how the model parameters influence the price dynamics, and we apply a modified version of the model to the daily closing prices of 15 top banking and real estate stocks in Hong Kong for the recent two years from December 5, 2013 to December 4, 2015 and discover that a sharp increase of the combined uncertainty is a reliable signal to predict the reversal of the current price trend.

Keyword :

Fuzzy opinion networks (FONs) investor social networks stock price dynamics

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GB/T 7714 Wang, Li-Xin . Modeling Stock Price Dynamics With Fuzzy Opinion Networks [J]. | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2017 , 25 (2) : 277-301 .
MLA Wang, Li-Xin . "Modeling Stock Price Dynamics With Fuzzy Opinion Networks" . | IEEE TRANSACTIONS ON FUZZY SYSTEMS 25 . 2 (2017) : 277-301 .
APA Wang, Li-Xin . Modeling Stock Price Dynamics With Fuzzy Opinion Networks . | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2017 , 25 (2) , 277-301 .
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A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems SCIE
期刊论文 | 2017 , 25 (3) , 693-706 | IEEE TRANSACTIONS ON FUZZY SYSTEMS | IF: 8.415
WoS CC Cited Count: 5
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Abstract :

We propose the concept of a conditional fuzzy set and prove that a type-2 fuzzy set is equivalent to a conditional fuzzy set. We show that both the conditional fuzzy sets and the type-2 fuzzy sets are fuzzy relations on the product space of the primary and secondary variables, and the difference is that the primary and secondary variables in the conditional fuzzy set framework are usually independent to each other, whereas in the type-2 fuzzy set framework, the secondary variable depends on the primary variable by definition. It is this dependence between the primary and secondary variables that makes the type-2 fuzzy sets a complex subject, while the conditional fuzzy sets do not have this built-in dependence and, thus, are much easier to analyze. With the fuzzy relation formulation, powerful tools in fuzzy set theory such as Zadeh's compositional rule of inference can be used to obtain the marginal fuzzy sets of the type-2 and conditional fuzzy sets, transforming the type-2 problems back to the conventional type-1 domain. With the help of the marginal fuzzy set concept, we show that a type-2 fuzzy logic system can be designed in the same way as designing a type-1 fuzzy logic system.

Keyword :

conditional fuzzy sets type-2 fuzzy logic systems (T2 FLSs) fuzzy relations Compositional rule of inference type-2 fuzzy sets (T2 FSs)

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GB/T 7714 Wang, Li-Xin . A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems [J]. | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2017 , 25 (3) : 693-706 .
MLA Wang, Li-Xin . "A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems" . | IEEE TRANSACTIONS ON FUZZY SYSTEMS 25 . 3 (2017) : 693-706 .
APA Wang, Li-Xin . A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems . | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2017 , 25 (3) , 693-706 .
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