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.

Background The influence of sociocultural factors on human reliability within an open sociotechnical systems is highlighted. The design of such systems is enhanced by experience feedback. Methods The study was focused on a survey related to the observation of working cases, and by processing of incident/accident statistics and semistructured interviews in the qualitative part. In order to consolidate the study approach, we considered a schedule for the purpose of standard statistical measurements. We tried to be unbiased by supporting an exhaustive list of all worker categories including age, sex, educational level, prescribed task, accountability level, etc. The survey was reinforced by a schedule distributed to 300 workers belonging to two oil companies. This schedule comprises 30 items related to six main factors that influence human reliability. Results Qualitative observations and schedule data processing had shown that the sociocultural factors can negatively and positively influence operator behaviors. Conclusion The explored sociocultural factors influence the human reliability both in qualitative and quantitative manners. The proposed model shows how reliability can be enhanced by some measures such as experience feedback based on, for example, safety improvements, training, and information. With that is added the continuous systems improvements to improve sociocultural reality and to reduce negative behaviors.