We emphasise the EMC spin effect as a problem of symmetry and discuss the renormalisation of the C = +1 axial tensor operators. This involves the generalisation of the Adler-BellJackiw anomaly to each of these operators. We find that the contribution of the axial anomaly to the spin dependent structure function g1(x,Q ) scales at O(αs). This means that the anomaly can be a large x effect in g1....

Algorithms for anomaly detection in IP networks have been developed and a real-time distributed platform for anomaly detection has been implemented. These algorithms automatically and adaptively detect “soft” network faults (performance degradations) in IP networks. These algorithms are implemented as a reliable and fully distributed real-time software platform called NSAD (Network/Service Anom...

Organizations have recently shown increased interest in database activity monitoring and anomaly detection techniques to safeguard their internal databases. Once an anomaly is detected, a response from the database is needed to contain the effects of the anomaly. However, the problem of issuing an appropriate response to a detected database anomaly has received little attention so far. In this ...

The problem of detecting an anomaly from a limited number of noisy tomographic projections is addressed from the statistical point of view. An unknown two (or three)-dimensional scene is composed of a background, considered as a nuisance parameter, with a possibly hidden anomaly. A parametric approach is proposed to reduce the lack of a priori information and an optimal test is designed. To dec...

Anomaly detection in networks is detection of deviations from what is considered to be normal. Performing anomaly detection is a learning approach to detect failures and intrusions in a network, intended to capture novel attacks. Anomaly Detection With fast Incremental Clustering (ADWICE) is an efficient algorithm to detect anomaly. But, since it uses distance based clustering mechanism it suff...

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses...

A collection is made of presently unexplained phenomena within our Solar system and in the universe. These phenomena are (i) the Pioneer anomaly, (ii) the flyby anomaly, (iii) the increase of the Astronomical Unit, (iv) the quadrupole and octupole anomaly, and (v) Dark Energy and (vi) Dark Matter. A new data analysis of the complete set of Pioneer data is announced in order to search for system...

I present the detailed behavior of phonon dispersion curves near momenta which span the electronic Fermi sea in a superconductor. I demonstrate that an anomaly, similar to the metallic Kohn anomaly, exists in a superconductor’s dispersion curves when the frequency of the phonon spanning the Fermi sea exceeds twice the superconducting energy gap. This anomaly occurs at approximately the same mom...

This work explores unsupervised anomaly detection within sequential, hierarchical data. We present a flexible framework for detecting, ranking and analyzing anomalies. The framework 1) allows users to incorporate complex, multidimensional, hierarchical data into the anomaly detection process; 2) uses an ensemble method that can incorporate multiple unsupervised anomaly detection algorithms and ...