At present, the methods of learning the hidden variables of Bayesian network with known structure is mainly for Bayesian networks with discrete variables or Gaussian networks with continuous variables.

Hidden variable can summarize the information between variables,simplify network structure, and avoid data over-fitting.

To present an summary and overview of recent developments on binary image information hiding, and discuss some important issues of those techniques such as robustness and data hiding capacity.

Then the author give a proof of the hiding capacity under the condition of no attack,and discuss the characteristic of the model.

2D-shuffling of image DCT coefficients is introduced in the information hiding arithmetic in order to equalize the uneven distribution of hiding capacity and to mprove the arithmetic validity.

To alleviate the weakness of existed network covert channels in traffic concealing and proxy penetration,a new method of constructing covert channel based on BHO is proposed.

Object: Exploring the method of modeling latent variable nonlinear effect analysis in structural equation modeling and the technique of latent variable nonlinear effect analysis by SAS software.

exploring the method of modeling latent variable interaction effect analysis in structural equation modeling and the technique of latent variable interaction effect analysis by SAS software.

In this paper,SEM is applied to incorporate transition of instituion,which is a Latent Variable,to the analysis of the source of growth of the source of growth,which is conductive to recognize the real reasons of economic growth of China.