Clarkson University

About: Clarkson University is a education organization based out in Potsdam, New York, United States. It is known for research contribution in the topics: Particle & Turbulence. The organization has 4414 authors who have published 10009 publications receiving 305356 citations. The organization is also known as: Thomas S. Clarkson Memorial School of Technology & Thomas S. Clarkson Memorial College of Technology.

Applications of a commercially available current conveyor

Abstract: It is demonstrated that a commercially available integrated circuit, the AD844 from Analog Devices, implements a current conveyor.

Structural properties of scale‐free networks

Abstract: Many networks have been reported recently to follow a scalefre degree distribution in which the fraction of sites having k connections follows a power law: P (k) = k . In this chapter we study the structural properties of such networks. We show that the average distance between sites in scale-free networks is much smaller than that in regular random networks, and bears an interesting dependence on the degree exponent . We study percolation in scale-free networks and show that in the regime 2 < < 3 the networks are resilient to random breakdown and the percolation transition occurs only in the limit of extreme dilution. On the other hand, attack of the most highly connected nodes easily disru pt the nets. We compute the percolation critical exponents and find that percolation in sca le-free networks is non-universal, i.e. depends on and different from the mean-field behavior in dimensions d 6. Finally, we suggest a novel and efficient method for immunization agains t the spread of diseases in social networks, or the spread of viruses and worms in computer netw orks.

On Techniques for Angle Compensation in Nonideal Iris Recognition

Abstract: The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word ldquononidealrdquo is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.