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Image reconstruction algorithm of compressed sensing based on neural dynamics

Journal of Information Hiding and Multimedia Signal Processing 2017年第3期8卷 623-631页

作者： Gan, Zhenhua Xiong, Baoping Zou, Fumin Liao, Lyuchao Du, Min College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China College of Electrical Engineering and Automation Fuzhou University No.2 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China Fujian Provincial Key Laboratory of Big Data Mining and Applications No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China Key Lab of Automotive Electronics and Electric Drive Technology of Fujian Province No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China

To improve the recovery performance of compressed sensing (CS) recon- struction, this paper proposed a CS reconstruction model based on neural dynamics optimization algorithm (NDOA) with l1-norm minimization, and applied it to the two- dimensional (2D) image signals to verify the reconstruction effectiveness. Experiments proved the NDOA had performed better in reconstruction than the orthogonal matching pursuit (OMP) and its improved algorithms considering its perfect recovery. When the compressed sampling rate is 0:875 for 64×64 Lena image, the application of NDOA would raise the peak signal to noise ratio (PSNR) by 3:6466dB while decrease the relative error (REOR) by 2:21% in comparison with OMP and SWOMP. It showed that the effective- ness of CS reconstruction of NDOA was evident. At the same time, the adoption of NDOA could realize real-time processing by parallel computing, which would effectively solve real-time problems such as image processing in the realm of high dimensional sparse signals. © 2017.

关键词： Compressed sensing

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Fabrication and magnetic properties of 4SC(NH_2)_2–Ni_(0.97)Cu_(0.03)Cl_2 single crystals

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Chinese Physics B 2015年第12期24卷 541-544页

作者：陈丽敏郭颖刘旭光解其云陶志阔谌静周玲玲刘春生 Key Laboratory of Radio Frequency and Micro-Nano Electronics of Jiangsu Province Jiangsu Key Laboratory of Big Data Analysis Technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Hefei National Laboratory for Physical Sciences at Microscale University of Science and Technology of China

Single crystals of 4SC（NH2）2–Ni1-xCux Cl2（x = 0.03）（Cu-DTN） containing spin S = 1/2 Cu^2＋and S = 1 Ni^2＋cations are synthesized by slow evaporation methods. Structural characterization demonstrates that the Cu-DTN is of a tetrahedral structure with lattice parameter c being 9.0995 A, which is 1.32% expansion compared with that of parent material DTN due to the larger radius of the Cu ion. Direct current（DC） susceptibility measurements show that both the antiferromagnetic exchange interaction at low temperature and the large anisotropy of susceptibilities are suppressed after doping the Cu ion, which could be related to the structural distortion and the increase of the super-exchange paths in Cu-DTN.

关键词： magnetic metal-doped magnetic materials susceptibility antiferromagnetic interaction

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Heat dissipation and information flow for delayed bistable Langevin systems near coherence resonance

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Physical Review E 2016年第5期94卷 052109-052109页

作者： Tiejun Xiao Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Synergetic Innovation Center of Scientific Big Data for Advanced Manufacturing Technology Guizhou Education University Guiyang 550018 People's Republic of China.

In this paper, stochastic thermodynamics of delayed bistable Langevin systems near coherence resonance is discussed. We calculate the heat dissipation rate and the information flow of a delayed bistable Langevin system under various noise intensities. Both the heat dissipation rate and the information flow are found to be bell-shaped functions of the noise intensity, which implies that coherence resonance manifests itself in the thermodynamic properties.

关键词： Brownian motion Classical statistical mechanics Nonequilibrium & irreversible thermodynamics Nonequilibrium statistical mechanics

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An attribute reduction framework for inconsistent decision tables from view of the boundary region

An attribute reduction framework for inconsistent decision t...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin Qian Yu-Hui Chang Ping Lv Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou China

ISBN: (纸本)9781509003914

Attribute reduction is one of the key issues for data preprocess in data mining. Many heuristic attribute reduction algorithms based on discernibility matrix have been proposed for inconsistent decision tables. However, these methods are usually computationally time-consuming. To address this issue, the derived consistent decision tables are defined for different definitions of relative reducts. The computations for different reducts of the original inconsistent decision tables are converted into the computations for their corresponding reducts of the derived consistent datasets. The relative discernibility object pair and the more optimal relative discernibility degree from view of the boundary region are designed to accelerate the attribute reduction process. An efficient attribute reduction framework using relative discernibility degree is proposed for large datasets. Experimental results show that our attribute reduction algorithms are effective and feasible for large inconsistent datasets.

关键词： Cybernetics Acceleration Time complexity Rough sets Heuristic algorithms data mining Algorithm design and analysis

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Utilizing Cat Swarm Optimization in Allocating the Sink Node in the Wireless Sensor Network Environment 3

Utilizing Cat Swarm Optimization in Allocating the Sink Node...

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3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

作者： Tsai, Pei-Wei Kong, Lingping Vaclav, Snasel Pan, Jeng-Shyang Istanda, Vaci Hu, Zhi-Yong College of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Department of Computer Science VSB Technical University of Ostrava Ostrava Czech Republic Council of Indigenous Peoples Executive Yuan New Taipei City Taiwan

ISBN: (纸本)9781509010936

A general wireless sensor network (WSN) is a system composed of a large number of sensor nodes. In the WSN system, all sensor nodes are responsible for sensing the interested events and transmitting the related information back to the sink node. The sink node acts like the brain of the whole WSN system for processing the collected data and giving control commands. The position of the sink node directly affects the data transmission efficiency and the distance from the terminal sensor node to the sink node. Thus, choosing the correct place to place the sink node in the whole network is a delicate work. In this paper, we propose a sink node placement method by proposing a newly designed object function and utilizing Cat Swarm Optimization (CSO) to find out the near best location for placing the sink node. The simulation results indicate that our proposed method presents good performance compared with the conventional Particle Swarm Optimization (PSO) algorithm in reducing the overall energy consumption and prolongs the lifetime of network in an efficient way. © 2016 IEEE.

关键词： Sensor nodes

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A characteristic-preserving steganographic method based on revision identifiers

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2016年第9期11卷 29-38页

作者： Xiang, Lingyun Sun, Caixia Liao, Niandong Wang, Weizheng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology ChangshaHunan Province410114 China School of Computer and Communication Engineering Changsha University of Science and Technology ChangshaHunan Province410114 China

Since the majority of the available steganographic schemes in OOXML format documents suffered the disadvantages of unsatisfactory anti-detection capability and security level, a characteristic-preserving steganographic method with high security is proposed in this paper. The proposed method embeds secret information by replacing the last three bytes of the values of the revision identifiers in the main document body of the OOXML format document, while preserving the normal characteristics of the document. Meanwhile, position marks are added to track the locations of the embedded information. In order to keep the internal data consistency of the document, the newly created values are added into other related parts. Experimental results show that the method not only possesses good imperceptibility and anti-detection capability, but also has high security and large embedding capacity. © 2016 SERSC.

关键词： Anti-detection Characteristic-preserving OOXML Revision identifier Steganography

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Swarm Intelligence Algorithm Inspired by Route Choice Behavior

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Journal of Bionic Engineering 2016年第4期13卷 669-678页

作者： Daxin Tian Junjie Hu Zhengguo Sheng Yunpeng Wang Jianming Ma Jian Wang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing 1 O0191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing 210096 China Department of Engineering and Design University of Sussex Brighton BN1 9RH UK The Texas Department of Transportation Austin TX78750 USA College of Computer Science and Technology Jilin University Changchun 130012 China

Travelers＇ route choice behavior, a dynamical learning process based on their own experience, traffic information, and influence of others, is a type of cooperation optimization and a constant day-to-day evolutionary process. Travelers adjust their route choices to choose the best route, minimizing travel time and distance, or maximizing expressway use. Because route choice behavior is based on human beings, the most intelligent animals in the world, this swarm behavior is expected to in- corporate more intelligence. Unlike existing research in route choice behavior, the influence of other travelers is considered for updating route choices on account of the reality, which makes the route choice behavior from individual to swarm. Anew swarm intelligence algorithm inspired by travelers＇ route choice behavior for solving mathematical optimization problems is introduced in this paper. A comparison of the results of experiments with those of the classical global Particle Swarm Optimization （PSO） algorithm demonstrates the efficacy of the Route Choice Behavior Algorithm （RCBA）. The novel algorithm provides a new approach to solving complex problems and new avenues for the study of route choice behavior.

关键词： swarm intelligence route choice behavior particle swarm optimization mathematical optimization

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Security improvement on a three party password based authenticated key exchange scheme using chaotic maps

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Journal of Information Hiding and Multimedia Signal Processing 2016年第6期7卷 1365-1372页

作者： Chen, Yu Chen, Chien-Ming Pan, Jeng-Shyang Wu, Tsu-Yang Liu, Shuai Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China Innovative Information Industry Research Center School of Computer Science and Technology Shenzhen Graduate School Harbin Institute of Technology Shenzhen518055 China

Recently, password based authenticated key exchange (or called PAKE for short) with chaotic maps has been received much attention for researchers. In 2013, Xie et al. proposed a three party PAKE scheme (based on chaotic maps). However, their scheme had been proved insecure by Lee et al. in 2015. In this paper, we first show that Xie et al.’s scheme is also vulnerable to a replay attack. To overcome this attack, we further propose an improvement based on their scheme. Finally, we demonstrate the security of our improvement with the BAN logic. © 2016.

关键词： Authentication

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Light trapping characteristics of glass substrate with hemisphere pit arrays in thin film Si solar cells

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Chinese Physics B 2015年第4期24卷 16-21页

作者：陈乐王庆康王阳培华黄堃沈向前 Key Laboratory for Thin Film and Micro-fabrication of the Ministry of Education Department of Microelectronics and NanoscienceShanghai Jiao Tong University College of Physical Science and Technology Engineering Guangxi Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University

In this paper, the light trapping characteristics of glass substrate with hemisphere pit （HP） arrays in thin film Si solar cells are theoretically studied via a numerical approach. It is found that the HP glass substrate has good antireflection properties. Its surface reflectance can be reduced by - 50% compared with planar glass. The HP arrays can make the unabsorbed light return to the absorbing layer of solar cells, and the ratio of second absorption approximately equals 30%. Thus, the glass substrate with the hemisphere pit arrays （HP glass） can effectively reduce the total reflectivity of a solar celt from 20% to 13%. The lip glass can also prolong the optical path length. The numerical results show that the total optical path length of the thin film Si solar cell covered with the HP glass increases from 2ω to 409. These results are basically consistent with the experimental results.

关键词： numerical approach light trapping hemispherical pit （HP） optical path length solar cells

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Analysis of volatilities and correlations for chinese stock markets

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Journal of Information Hiding and Multimedia Signal Processing 2016年第5期7卷 1110-1125页

作者： Zhang, Ji Lin Lai, Yong Zeng Tsai, Pei-Wei School of Mathematics and Physics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350108 China Department of Mathematics Wilfrid Laurier University 75 Universit Ave. E WaterlooONN2L 3C5 Canada College of Information Science and Engineering Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350108 China

In this paper, GARCH, EG ARCH and GJR models are used to fit the volatilities of stock returns for two markets in China, namely, the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE) in both the developing and the developed stages. We also compare the performance of the volatilities and the leverage effects both across and within the two markets. Furthermore, we use VAR model to detect the correlation between the targeted markets based on impulse response and variance decomposition analyses. The experimental results indicate that the markets are less volatile and positively skewed in the developing phase while these are more volatile and negatively skewed in the developed phase. Another finding is that one standard-deviation innovation impulses die out after 7 days in the targeted markets and the impact of the SSE on the SZSE is stronger than that of the SZSE on the SSE. © 2016, Ubiquitous International. All Rights Reserved.

关键词： Impulse response

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