Information technology has widened itself over the last two decades and has become the axis of today’s global development, but this development also faces many problems among which DoS is one of the big problem. DoS presents a great threat to internet as an attacker sends a lots of requests to the victim, Such that the victim will not be able to entertain the legitimate user and the next stage ...

In this paper, we formulate image annotation as a Multi-correlation Learning to Rank (MLRank) problem, i.e., ranking the relevance of tags to an image considering the visual similarity and the semantic relevance. Unlike typical learning to rank algorithms, which assume that the ranking objects are independent, we attempt to rank relational data by exploring the consistency between “visual simil...

This chapter concerns rank tests for independence of two random variables. A form of locally most powerful test against particular alternative is derived and the most often used variants of this test are mentioned, namely the test of van der Waerden type, Spearman rank correlation coefficient, the quadrant test and the Kendall rank correlation coefficient, a member of non-linear rank statistics...

We study the problem of rank aggregation: given a set of ranked lists, we want to form a consensus ranking. Our main contribution is the derivation of a nonparametric estimator for rank aggregation based on multivariate extensions of Spearman’s ρ, which measures correlation between a set of ranked lists. Multivariate Spearman’s ρ is defined using copulas, and we show that the geometric mean of ...

Color has been shown to be useful in the context of texture classification. However, since under different illuminations color is not stable, color invariant descriptors should be defined when the illumination of the query is unknown. In this paper, we propose to characterize color textures by analyzing the rank correlation of color planes between pixels locally close to each other. Thus, consi...

A new statistic, defined as Ro(k) = s(k)/ -.Jsr+ ... + sE {s(k) denoting the k-th singular value of data matrix}, is proposed for assessing the significance of individual components in principal-components analysis (PCA). Ro was shown to be the correlation coefficient of the prediction from the k-th principal component to the original data. The common significance test on Ro was applied as a se...

Face recognition systems have to deal with the problem that not all variations of all persons can be enrolled. Rather, the variations of most persons must be modeled. Explicit modeling of different poses is awkward and time consuming. Here, we present a subsystem that builds a model of pose variation by keeping a model database of persons in both poses, additionally to the gallery of clients kn...

The nonparanormal model assumes that variables follow a multivariate normal distribution after a set of unknown monotone increasing transformations. It is a flexible generalization of the normal model but retains the nice interpretability of the latter. In this paper we propose a rank-based tapering estimator for estimating the correlation matrix in the nonparanormal model in which the variable...