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Search Results (15)
  • Open Access


    Coverless Text Hiding Method Based on Improved Evaluation Index and One-Bit Embedding

    Ning Wu1,2, Yi Yang1,*, Lian Li1, Zhongliang Yang3, Poli Shang4, Weibo Ma5, Zhenru Liu5

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1035-1048, 2020, DOI:10.32604/cmes.2020.010450

    Abstract In the field of information hiding, text is less redundant, which leads to less space to hide information and challenging work for researchers. Based on the Markov chain model, this paper proposes an improved evaluation index and onebit embedding coverless text steganography method. In the steganography process, this method did not simply take the transition probability as the optimization basis of the steganography model, but combined it with the sentence length in the corresponding nodes in the model to gauge sentence quality. Based on this, only two optimal conjunctions of the current words are retained in the method to generate… More >

  • Open Access


    Solution of the Inverse Radiative Transfer Problem of Simultaneous Identification of the Optical Thickness and Space-Dependent Albedo Using Bayesian Inference

    D. C. Knupp1,2, A. J. Silva Neto3

    CMES-Computer Modeling in Engineering & Sciences, Vol.96, No.5, pp. 339-360, 2013, DOI:10.3970/cmes.2013.096.339

    Abstract Inverse radiative transfer problems in heterogeneous participating media applications include determining gas properties in combustion chambers, estimating environmental and atmospheric conditions, and remote sensing, among others. In recent papers the spatially variable single scattering albedo has been estimated by expanding this unknown function as a series of known functions, and then estimating the expansion coefficients with parameter estimation techniques. In the present work we assume that there is no prior information on the functional form of the unknown spatially variable albedo and, making use of the Bayesian approach, we propose the development of a posterior probability density, which is explored… More >

  • Open Access


    Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

    Lingling Xia1, Bo Song2,3, Zhengjun Jing4, Yurong Song5,*, Liang Zhang1

    CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 123-144, 2018, DOI:10.32604/cmc.2018.03738

    Abstract Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves. On the basis of Markov chains theory, a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment. Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence… More >

  • Open Access


    Modeling Intergranular Crack Propagation in Polycrystalline Materials

    M.A.Arafin1, J.A.Szpunar2

    CMC-Computers, Materials & Continua, Vol.14, No.2, pp. 125-140, 2009, DOI:10.3970/cmc.2009.014.125

    Abstract A novel microstructure, texture and grain boundary character based model has been proposed to simulate the intergranular crack propagation behavior in textured polycrystalline materials. The model utilizes the Voronoi algorithm and Monte Carlo simulations to construct the microstructure with desired grain shape factor, takes the texture description of the materials to assign the orientations of the grains, evaluates the grain boundary character based on the misorientation angle - axis calculated from the orientations of the neighboring grains, and takes into account the inclination of grain boundaries with respect to the external stress direction. Markov Chain theory has been applied to… More >

  • Open Access


    Convergence Properties of Genetic Algorithmsin a Wide Variety of Noisy Environments


    CMC-Computers, Materials & Continua, Vol.14, No.1, pp. 35-60, 2009, DOI:10.3970/cmc.2009.014.035

    Abstract Random noise perturbs objective functions in practical optimization problems, and genetic algorithms (GAs) have been proposed as an effective optimization tool for dealing with noisy objective functions. In this paper, we investigate GAs in a variety of noisy environments where fitness perturbation can occur in any form-for example, fitness evaluations can be concurrently disturbed by additive and multiplicative noise. We reveal the convergence properties of GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms in noisy environments. We compute the one-step transition probabilities of the Markov chain and show that the chain has… More >

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