Analysis and design of a web-based decision support system for choosing higher education studies

The vocational orientation of the youngsters who are about to enter, study, or have recently graduated at higher education (HE) institutions, and linking HE with labor market are two research areas which have not been investigated extensively in Balkan countries. Job (or occupational) profiles, among other tools used in vocational orientation, provide standardized and digitized descriptions of different professions. This article focuses on the analysis and the design of a web-based decision support system (DSS) to assist its users in getting thoroughly informed about HE studies in Greece, and eventually in choosing their vocational prospects. Apart from reviewingthe related previous research work and relevant web-based systems, we present the main elements of the system's analysis and its design, the extensions that could lead to even more powerful systems, and conclusions about the advantages, limitations and practical application of the DSS. © 2014 Yugoslav Journal of Operations Research

Rigid and non-rigid 3D motion estimation from multiview image sequence

Multiviewimagesequenc proccwim has been thefocfi ofcfiVxBFw*jfiO attention inrecVx literature. This paper presents anefficjhw tecjhw*j forobjecxFw*jO rigid and non-rigid 3D motion estimation,applicion to problems ocoblems in multiviewimagesequenc cquen applicwimage MorespecOxj/w*fi a neural network is formed for the estimation of the rigid 3D motion ofeac objec in thescwfiE using initially estimated 2D motion veconw conwFhfixxw* toeac ccfiB view. Non-linear error minimizationtecmizati are adopted for neural network weight update. Furthermore, a novelteclwhfiB is also proposed for the estimation of thelocj non-rigid deformations, based on the multiviewcfixEF geometry. Experimental results using bothstereoscw*fi andtrinochw* crino setups illustrate and evaluate the proposed scosed r 2002 Elsevier Scvier B.V. All rights reserved

Weight compensated motion estimation for facial deformation analysis

Investigation of the motion performed by a person's face while speaking is the target of this paper. Methods and results of the studied facial motions are presented and rigid and non-rigid motion are analyzed. In order to extract only facial deformation independent from head pose, we use a new and simple approach for separating rigid and non-rigid motion called Weight Cornpensated Motion Estimation (WCME). This approach weights the data points according to their influence to the desired motion model. A synthetic test as well as real data, are used to demonstrate the performance of this approach. We also present results in the field of facial deformation analysis and used basis shapes as description form. These results can be used for recognition purposes by adding temporal changes to the overall process or adding natural deformations other than at the given database