In this paper, a new technique called symbolic kernel Principal Component Analysis (KPCA) is explored to develop a model for face representation and recognition. The conventional kernel PCA method extracts single valued features from the original image space to represent face images. The proposed method reduces the dimensionality of original image space by representing the face images as symbol...

We introduce the notion of re-establishing trust in compromised systems, specifically looking at recovering from kernel-level rootkits. An attacker that has compromised a system will often install a set of tools, known as a rootkit, which will break trust in the system as well as serve the attacker with other functionalities. One type of rootkit is a kernel-level rootkit, which will patch runni...

This study developed a novel model, HGA-SVR, for type of kernel function and kernel parameter value optimization in support vector regression (SVR), which is then applied to forecast the maximum electrical daily load. A novel hybrid genetic algorithm (HGA) was adapted to search for the optimal type of kernel function and kernel parameter values of SVR to increase the accuracy of SVR. The propos...

The problem of development of the SVM classifier based on the modified particle swarm optimization has been considered. This algorithm carries out the simultaneous search of the kernel function type, values of the kernel function parameters and value of the regularization parameter for the SVM classifier. Such SVM classifier provides the high quality of data classification. The idea of particle...