Local Correlation Methods

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

Tying the synthetic trace to the actual seismic trace at the well location is a labor-intensive task that relies on the interpreter's experience and the similarity metric used. The traditional seismic to well tie suffers from subjectivity by visually matching major events and using global crosscorrelation to measure the quality of that tying. We compared two automatic techniques that will decrease the subjectivity in the entire process. First, we evaluated the dynamic time warping method, and then, we used the local similarity attribute based on regularized shaping filters. These two methods produced a guided stretching and squeezing process to find the best match between the two signals. We explored the proposed methods using real well log examples and compared to the manual method, showing promising results with both semiautomatic approaches.

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.

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