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Percolation theory-based exposure-path prevention for wireless sensor networks coverage in internet of things

IEEE Sensors Journal 2013年第10期13卷 3625-3636页

作者： Liu, Liang Zhang, Xi Ma, Huadong Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas AandM University College Station TX 77843 United States

Deriving the critical density to achieve region coverage for random sensor deployment is a fundamentally important problem in the area of Internet of Things (IoT). Most of the existing works on sensor coverage mainly concentrate on the full coverage models, which ensure that all points in the deployment region are covered at the expense of high complexity and cost. In contrast, many applications of IoT focus on the exposure-path prevention, which does not require full coverage sensor deployment, and instead it only needs the partial coverage, because the exposure paths are prevented as long as no moving objects or phenomena can go through a deployment region without being detected. Finally, we focus on the partial coverage by applying the percolation theory to solve the exposure path problem for the network of sensors in IoT. Most of the existing percolation-based schemes apply the continuum-percolation theory, which, however, suffers from the loose lower and upper bounds on the critical density. To overcome this problem, we propose a bond-percolation theory based scheme by mapping the exposure path problem into a bond percolation model. Using this model, we derive the critical densities for both omnidirectional sensor networks and directional sensor networks under random sensor deployment where sensors are deployed according to a two-dimensional Poisson process. The rigorous modeling/analyses and extensive simulations show that our proposed scheme can yield much tighter upper and lower bounds on the critical densities as compared with those generated by continuum-percolation. © 2001-2012 IEEE.

关键词： Wireless sensor networks

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Corrections to “Percolation Theory-Based Exposure-Path Prevention for Wireless Sensor Networks Coverage in Internet of Things” [Oct 13 3625-3636]

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IEEE Sensors Journal 2014年第3期14卷 926-926页

作者： Liang Liu Xi Zhang Huadong Ma Beijing University of Posts and Telecommunications Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing China Department of Electrical and Computer Engineering Networking and Information Systems Laboratory College Station TX USA

In the above paper (ibid., vol. 13, no. 10, pp. 3625-3636, Oct. 2013), Fig. 15 is incorrect. The correct Fig. 15 is presented here.

关键词： Wireless sensor networks Internet Stochastic processes

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Chiral Scars in Chaotic Dirac Fermion systems

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Physical Review Letters 2013年第6期110卷 064102-064102页

作者： Hongya Xu Liang Huang Ying-Cheng Lai Celso Grebogi Institute of Computational Physics and Complex Systems and Key Laboratory for Magnetism and Magnetic Materials of MOE Lanzhou University Lanzhou Gansu 730000 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen Aberdeen AB24 3UE United Kingdom Freiburg Institute for Advanced Studies University of Freiburg 79104 Freiburg Germany

Do relativistic quantum scars in classically chaotic systems possess unique features that are not shared by nonrelativistic quantum scars? We report a class of relativistic quantum scars in massless Dirac fermion systems whose phases return to the original values or acquire a 2π change only after circulating twice about some classical unstable periodic orbits. We name such scars chiral scars, the successful identification of which has been facilitated tremendously by our development of an analytic, conformal-mapping-based method to calculate an unprecedentedly large number of eigenstates with high accuracy. Our semiclassical theory indicates that the physical origin of chiral scars can be attributed to a combined effect of chirality intrinsic to massless Dirac fermions and the geometry of the underlying classical orbit.

关键词： FERMIONS LEPTONS (Nuclear physics) COMBINATORIAL dynamics SCHRODINGER equation QUANTUM interference

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Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

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Chinese Journal of Chemical engineering 2012年第6期20卷 1081-1088页

作者：曹政才邓积杰刘民王永吉 College of Information Science and Technology Beijing University of Chemical Technology Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University Tsinghua National Laboratory for Information Science and Technology State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

关键词： semiconductor manufacturing system bottleneck prediction adaptive network-based fuzzy inference system

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Identity Based Encryption and Biometric Authentication Scheme for Secure Data Access in Cloud Computing

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电子学报(英文版) 2012年第2期21卷 254-259页

作者： CHENG Hongbing RONG Chunming TAN Zhenghua ZENG Qingkai State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Department of Information Engineering Jiangsu City Vocation College Nanjing 210036 China Department of Electronic Engineering and Computer Science University of Stavanger 4036 Stavanger Norway Department of Electronic Systems Aalborg University Niels Jernes Vej 12 9220 Aalborg Denmark

Cloud computing will be a main informa- tion infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for cloud computing platform is a big challenge. In this paper, we propose a secure data access scheme based on identity-based encryption and biometric authentication for cloud computing. Firstly, we describe the security concern of cloud computing and then propose an integrated data access scheme for cloud computing, the procedure of the proposed scheme include parameter setup, key distribu- tion, feature template creation, cloud data processing and secure data access control. Finally, we compare the pro- posed scheme with other schemes through comprehensive analysis and simulation. The results show that the pro- posed data access scheme is feasible and secure for cloud computing.

关键词：计算安全数据访问身份验证生物识别加密信息基础设施地理分布数据中心

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Universal formalism of Fano resonance

Universal formalism of Fano resonance

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第十二届全国磁性理论会议

作者： Liang Huang Ying-Cheng Lai Hong-Gang Luo Celso Grebogi Beijing Computational Science Research Center Beijing 100084 China Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen Aberdeen AB24 3UE UK School of Electrical Computer and Energy EngineeringArizona State University Tempe Arizona 85287 USA School of Physical Science and Technology and Key Laboratory for Magnetism and Magnetic Materials of MOE Lanzhou University Lanzhou Gansu 730000 China

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Description for 3D images with histogram of gradients based on maximum directional derivative

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第4期6卷 15-23页

作者： Wang, Hu Zhang, Wensheng Liu, Jin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of software Engineering Computer School Wuhan University Wuhan 430072 China

The histogram of gradients for three-dimensional images (HOG3D) has been widely used to generate descriptors of local features for the matching of salient interest blobs between volumetric medical images. The distinctiveness of descriptors is essential to match similar patterns as well as differentiate different patterns. However, most methods for HOG3D are based on the unequal azimuth-elevation-angle division of the three-dimensional orientations, leading to the reduction of the distinctiveness. This paper presents a description method to extract distinctive descriptors by using a novel histogram of gradients based on the maximum directional derivative (HOG3DMAX). The three-dimensional orientations are divided equally into 24 homogeneous regions for the bins of gradient histogram to improve the distinctiveness. In addition, the interpolation of gradients is applied in HOG3DMAX according to the relatively simple form of the homogeneous regions in order to avoid harmful effects from boundary in images. Experiments were performed on three sets with different extents of similarity. The cluster analysis and classification accuracy were utilized to validate the proposed method. Compared with the commonly used azimuth-elevation based method, the new method shows lower intra-cluster pairwise distances relative to inter-cluster pairwise distances, and achieved 5% higher classification accuracy. The results indicate the improvement of distinctiveness by using equally divided regions and the interpolation of gradients. We conclude that the HOG3DMAX is an effective description method for three-dimensional images.

关键词： Cluster analysis

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An Embedded Co-AdaBoost and Its Application in Classification of software Document Relation

An Embedded Co-AdaBoost and Its Application in Classificatio...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jin Liu Juan Li Yuan Xie Jeff Lei Qiping Hu State Key Laboratory of Software Engineering Computer School Wuhan University China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation CAS China Department of Computer Science and Engineering University of Texas Arlington USA International School of Software Wuhan University China

To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.

关键词： Classification algorithms Training software Accuracy Partitioning algorithms software algorithms Convergence

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Irregular community discovery for cloud service improvement

Irregular community discovery for cloud service improvement

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作者： Liu, Jin Zhou, Jing Wang, Junfeng Zhang, Feng Liu, Fei State Key Lab. of Software Engineering Wuhan University Wuhan 430072 China Lab. of Complex Systems and Intelligence Science Institute of Automation CAS Beijing 100190 China State Key Lab. for Novel Software Technology Nanjing University Nanjing China School of Computer Science Communication University of China Beijing 100024 China Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100190 China College of Computer Science Sichuan University Chengdu 610064 China Software School Sun Yat-sen University Guangzhou 510006 China

Utility services provided by cloud computing rely on virtual customer communities forming spontaneously and evolving continuously. Clarifying the explicit boundaries of these communities is thus essential to the quality of utility services in cloud computing. Communities with overlapping features or prominent peripheral vertexes are usually typical irregular communities. Traditional community identification algorithms are limited in discovering irregular topological structures from CR networks, whereas these irregular shapes typically play an important role in finding prominent customers which are ignored in social CRM otherwise. We present a novel method of discovering irregular communities. It firstly finds and merges primitive maximal cliques and the irregular features of overlapping and prominent sparse vertices are further considered. An empirical case and a methodology comparison confirm the feasibility and efficiency of our approach. © 2012 Springer Science+Business Media, LLC.

关键词： Cloud computing

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Developing Objective SensitivityAnalysis of Periodic systems： Case Studies of Biological Oscillators

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自动化学报 2012年第7期38卷 1065-1073页

作者： LU Bao-Yun YUE Hong Key Laboratory of Complex Systems and Intelligence Science Institute of AutomationChinese Academy of SciencesBeijing 100190P.R.China College of Computer Science and Technology Henan Polytechnic UniversityJiaozuo 454000P.R.China Department of Electronic and Electrical Engineering University of StrathclydeGlasgowG11QEUK

Abstract Sensitivity analysis is a powerful tool in investigating the impact of parameter variations on the change of system behaviours quantitatively. For a periodic system, sensitivity analysis is a challenging problem since the standard sensitivity metrics grow unbounded when time tends to infinity. Objective sensitivity analyses using various oscillation features such as period, phase, amplitude, etc. are therefore needed to circumvent this problem. In this work, a new concept of basal state sensitivity is proposed based on which a phase sensitivity calculation is derived. The improved period sensitivity calculation following an existing algorithm using singular value decomposition (SVD) is also presented, which provides a simple calculation for the basal state sensitivity. These new sensitivity calculations are developed with the purpose to analyse biological oscillators since there is an increasing interest in understanding how oscillations occur and what the main controlling factors are following a growing experimental and computational evidence of oscillations in biological systems. The improved calculation of period sensitivity is shown to be consistent with the previous methods through a well studied circadian rhythm model. The calculation of new objective sensitivities are also testified by the same circadian rhythm model as well as an oscillatory signal transduction pathway model, which further illustrates the efficiency of this approach in handling complex biological oscillators in the presence of reaction conservations.

关键词：周期系统生物系统振荡器敏感性分析灵敏度指标案例开发信号转导通路

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