The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.

This paper presents a simple approach for accurate determination of the resonant frequency of an elliptical microstrip patch printed on isotropic or anisotropic substrate materials. In this approach, some modifications are made to account for fringe fields, dispersion effects, and losses by calculating effective dimensions, effective permittivity of anisotropy in the layer, and effective loss tangent, respectively. The theoretical resonant frequency results are in very good agreement with the experimental results reported elsewhere. Numerical results show that the change in the resonant frequency of the antenna is due primarily to a small disturbance of the substrate’s nature. Then the effect of the uniaxial anisotropic materials is a significant parameter and most essential on the microstrip antenna characterization.