Local Correlation Methods

An approximation to the many-body London dispersion energy in molecular systems is expressed as a functional of the occupied orbitals only. The method is based on the local-RPA theory. The occupied orbitals are localized molecular orbitals and the virtual space is described by projected oscillator orbitals, i.e. functions obtained by multiplying occupied localized orbitals with solid spherical harmonic polynomials having their origin at the orbital centroids. Since we are interested in the long-range part of the correlation energy, responsible for dispersion forces, the electron repulsion is approximated by its multipolar expansion. This procedure leads to a fully non-empirical long-range correlation energy expression. Molecular dispersion coefficients calculated from determinant wave functions obtained by a range-separated hybrid method reproduce experimental values with less than 15% error.

Genetic algorithm is used to perform variable selection to determine the ranges of wavelengths in NIR spectral data suitable to be used as predictors in multivariate calibration model via partial least squares. The NIR spectral data consists of three components of active substances, namely human serum albumin (HSA), γ-globulin and glucose. The wavelength selection is able to improve the calibration model by selecting the wavelengths that contains information or correlated with the concentration of substances, while others non-chosen wavelengths, which contribute no information or contain noises, are excluded from the calibration model. © 2005 IEEE.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1616633

This paper proposes to manage data structures manipulated by the proposed correlation function based on a new concept called Multi-violation Detectors (MvD). The MvD-based correlation function manipulates events based on metrics that evaluate them. The detection and the correlation processes are managed using a MLP(Muli-Layer Perceptron)-like network architecture. The manipulated data structures in the MLP-like network mainly include attacks, metrics and MvD values. To add more efficiency to the implemented processes, these values are managed through a structured database where an SQL-like language for MvD retrieval is introduced. The proposed approach is based on a relational calculus. Therefore, its completeness is mathematically proved.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4231056&tag=1

To expose the existence of hidden message, this paper presents a steganalysis method for LSB (Least signifycant bit) matching steganography in wav audio based on multiorder Markov feature. Noise sequences are extracted respectively based on two methods of local correlation and 5/3 wavelet de-noising, and then the correlation of noise sequence is quantified as multi-order Markov feature vectors. Based on the extracted feature vectors, a steganography detector based on support vector machine (SVM) is trained to identify whether the wav audio file carries hidden data. Experimental results show that detection accuracy can reach more than 80% even when the embedding rate is only 10%, which is far better than other method.