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International Symposium on Computational Intelligence and Design, ISCID

作者： Junzhu Zhong Chungang Yan Wangyang Yu Peihai Zhao Mimi Wang The Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China Shaanxi Normal University Xi'an China

ISBN: (纸本)9781479970063

Due to the continued growth threat in Phishing, a kind of stable identity authentication method is highly needed based on individual characteristics just like browsing behaviors. Most of the existing researches focused on browsing behavior patterns of group users are used in personal recommendation, website structure optimization or web prediction. In order to ensure the validity of user identity and the security of e-commerce, we construct personalized user browsing behavior model based on ARM (Association Rule Mining) from Web usage log. We compare real-time browsing behaviors with history model to identify a user's real identity in Web pages accessed. According to the results of the experiments, for the illegal users, this method can attain 91.3% detection rate with below 10% false alarm rate. Thus, it can achieve high real-time and recognition efficiency.

关键词： Association rules Authentication Web pages Decision trees Real-time systems Classification algorithms

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A Method to Check Liveness of WS3PR 33

A Method to Check Liveness of WS3PR

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第三十三届中国控制会议

作者： WANG ShouGuang LIU Miao ZHOU MengChu WU WenHui IEEE School of Information & Electronic Engineering Zhejiang Gongshang University State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University School of Electro-Mechanical Engineering Xidian University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA

ISBN: (纸本)9781479947249

Petri nets are widely used to model flexible manufacturing systems(FMSs) because they can help analyze the properties and synthesize deadlock-free supervisory controllers of *** system of Simple Sequential Processes with Resources(WS3PR) is an important subclass of Petri nets that can well model many *** work first gives new algorithms to check liveness for a WS3 PR net via its subnet trees and *** the computation complexity for the proposed method is shown in this paper,to be polynomial under certain ***,sufficient conditions for deciding liveness of a WS3 PR are *** example is used to illustrate the results.

关键词： Liveness,flexible manufacturing system,deadlock,Petri net.

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A Petri Nets Based Approach for Detecting the Data Races and Deadlocks in OpenMP Program

A Petri Nets Based Approach for Detecting the Data Races and...

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2012 Third International Conference on Theoretical and Mathematical Foundations of Computer Science(ICTMF 2012)

作者： Yulong Xian Zhijun Ding Department of Computer Science and Technology Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

Because of OpenMP programs shielding the underlying parallel execution and scheduling details,data races and deadlocks are tend to occur during program ***,this paper puts forward the modeling method of OpenMP programs based on Petri *** flow of programs are modeled according to the semantics of program control statements and directives of OpenMP programs;Data flow of programs are modeled by abstracting read and write operations related to shared *** two detection algorithms of data race and deadlock for OpenMP program are given based on the coverability tree of Petri ***,corresponding software tool is designed and implemented,and an OpenMP program example of the dining philosophers problem is analyzed to indicate the effectiveness of this method and tools.

关键词： OpenMP, Data races, Deadlock, Static detection, Petri nets

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A fast restarting particle swarm optimizer

A fast restarting particle swarm optimizer

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Congress on Evolutionary Computation

作者： Junqi Zhang Xiong Zhu Wei Wang Jing Yao Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Particle swarm optimization (PSO) is a swarm intelligence technique that optimizes a problem by iterative exploration and exploitation in the search space. However, PSO cannot achieve the preservation of population diversity on solving multimodal optimization problems, and once the swarm falls into local convergence, it cannot jump out of the local trap. In order to solve this problem, this paper presents a fast restarting particle swarm optimization (FRPSO), which uses a novel restarting strategy based on a discrete finite-time particle swarm optimization (DFPSO). Taking advantage of frequently speeding up the swarm to converge along with a greater exploitation capability and then jumping out of the trap, this algorithm can preserve population diversity and provide a superior solution. The experiment performs on twenty-five benchmark functions which consists of single-model, multimodal and hybrid composition problems, the experimental result demonstrates that the performance of the proposed FRPSO algorithm is better than the other three representatives of the advanced PSO algorithm on most of these functions.

关键词： Particle swarm optimization Sociology Statistics Convergence Oscillators Algorithm design and analysis Benchmark testing

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Robust control reconfiguration of resource allocation systems with Petri nets and integer programming

Robust control reconfiguration of resource allocation system...

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作者： Li, Jun Zhou, Mengchu Guo, Tao Gan, Yahui Dai, Xianzhong Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing 210096 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system's state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them. © 2014 Elsevier Ltd. All rights reserved.

关键词： Integer programming

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Social incentive policies to engage commercial building occupants in demand response

Social incentive policies to engage commercial building occu...

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2014 IEEE International Conference on Automation Science and Engineering, CASE 2014

作者： Li, Sisi Deng, Kun Zhou, Meng Chu Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07012 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Coordinated Science Laboratory University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Occupants' comfort is the primary target in a building operation. However their efforts are often neglected and ruled out from traditional control strategies of energy-efficient building management systems. Occupant-engaged control strategies have recently attracted many research attentions and demonstrated great potentials for energy saving. With them, occupants' behavior is incorporated into the closed-loop control methods in which their initiatives actively contribute to building services and energy utility by explicitly expressing their preferences. This work proposes an occupant-engaged demand response (DR) strategy for building automation in which occupants are actively engaged to adapt their energy consumption in response to incentive opportunities designed by facility managers. A model-based study and a Nash-Equilibrium-based solution are provided to assist facility managers with the design of social incentive policies to promote occupant participation, along with the guarantee of lucrativeness for a DR event. © 2014 IEEE.

关键词： Energy efficiency

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A Self-Learning Clustering Algorithm Based on Clustering Coefficient

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8786卷 79-94页

作者： Zhong, Mingjie Ding, Zhijun Sun, Haichun Wang, Pengwei The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China Department of Computer Science University of Pisa Pisa56127 Italy

This paper presents a novel clustering algorithm based on clustering coefficient. It includes two steps: First, k-nearest-neighbor method and correlation convergence are employed for a preliminary clustering. Then, the results are further split and merged according to intra-class and inter-class concentration degree based on clustering coefficient. The proposed method takes correlation between each other in a cluster into account, thereby improving the weakness existed in previous methods that consider only the correlation with center or core data element. Experiments show that our algorithm performs better in clustering compact data elements as well as forming some irregular shape clusters. It is more suitable for applications with little prior knowledge, e.g. hotspots discovery. © Springer International Publishing Switzerland 2014.

关键词： Clustering algorithms

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An optimized Apriori algorithm based on sparse matrix for intrusion detection

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Open Cybernetics and systemics Journal 2014年第1期8卷 8-11页

作者： Zeng, Xiaohui Lv, Jingxiang Li, Jingzhong Luo, Wenlang Dept. of Computer Science and Technology Jinggangshan University Ji’an China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

The original Apriori algorithm is widely used in the intrusion detection field, but it may consume incredible computing resources in the process of handling network packets. We propose our optimized-Apriori algorithm which can greatly improves the algorithm efficiency by means of reducing the data storage space and the number of frequent item sets. We take full advantage of the characteristics of sparse matrix to save storage space and shorten the running time. The experimental results show that our optimized-Apriori algorithm can make a larger progress in saving the storage space of network data to be processed, even shortening nearly half of the data mining time in the process of intrusion detection. © Zeng et al.

关键词： Data mining

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Improvement of rotation matrix based differential limited feedback with DFT codebook and its application in CoMP environment

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Journal of Communications 2014年第6期9卷 498-505页

作者： Zhu, Yin Ji, Yusheng Wang, Ping Liu, Fuqiang Broadband Wireless Communications and Multimedia Laboratory Key Laboratory of Embedded System and Service Computing supported by Ministry of Education Tongji University Shanghai 201804 China National Institute of Informatics Tokyo Japan

Recently, exploiting the temporal correlation of slowly varied multiple input multiple output (MIMO) channels to further improve the system performance or the feedback efficient in MIMO wireless communication systems with limited feedback has been investigated in many papers. Among them, T. Kim et al. proposed a rotation matrix based differential feedback scheme which is shown to have good performance with regard to the system throughput for spatial multiplexing MIMO systems. Although the rotation matrix codebook and the precoding codebook in their scheme are optimally constructed, they are not fit for a practical system due to the structure constraints. In this paper, we propose to replace the optimal codebook in the rotation matrix based differential feedback scheme with discrete Fourier transform (DFT) structured codebook, and propose a search-based method to decrease the performance degradation induced by the un-optimality of the DFT codebook. In addition, the modified algorithm is also applied to a per-cell codebook based coordinated multi-point (CoMP) transmission system to verify its applicability to different MIMO scenarios. Simulation results show the effectiveness of our modified scheme. © 2014 Engineering and Technology Publishing.

关键词： Discrete Fourier transforms

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A comparative study of redundant feature detection based feature selection methods

A comparative study of redundant feature detection based fea...

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International Conference on Computer, Information and Telecommunication systems (CITS)

作者： Xue-Qiang Zeng Qian-Sheng Chen Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Computer Center Nanchang University Nanchang China

As a high dimensional problem, analysis of largescale data sets is a challenging task, where many weakly relevant or redundant features hurt generalization performance of classification models. In order to solve this problem, many effective feature selection methods have proposed to eliminate redundant features in recent years. However, the comparative performances of these redundant feature detection based methods have not been reported yet, which makes the choice of feature selection method relatively difficult for many real applications. The paper presents a novel comparative study of redundant feature detection based feature selection methods. Experiments on several benchmark data sets demonstrate the comparative performances of some state-of-the-arts methods. Based on the extensive empirical results, the minimum Redundancy-Maximum Relevance (mRMR) method has been found to be the best one among all compared feature selection models.

关键词： Breast Colon Lungs Redundancy

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