Anomaly detection in spatial time series is a challenging problem with numerous potential applications. A comprehensive anomaly detection approach not only should be able to detect and identify the emerging anomalies, but it also has to characterize the essence of these anomalies by visualizing the structures revealed within data in a way, which is understandable to the end-user. In this study,...

A summary is given of the present status of the theory and experiment of the anomalous magnetic moment of the muon. A difference between predicted and measured values is an indication of physics beyond the Standard Model. A new experimental measurement has produced a value which differs from a recent Standard Model prediction by about 1.6 standard deviations. When first announced, the discrepan...

CLASSIFYING MALICIOUS WINDOWS EXECUTABLES USING ANOMALY BASED DETECTION by Ronak Sutaria A malicious executable is broadly defined as any program or piece of code designed to cause damage to a system or the information it contains, or to prevent the system from being used in a normal manner. A generic term used to describe any kind of malicious software is Malware, which includes Viruses, Worms...

​—Google uses continuous streams of data from industry partners in order to deliver accurate results to users. Unexpected drops in traffic can be an indication of an underlying issue and may be an early warning that remedial action may be necessary. Detecting such drops is non-trivial because streams are variable and noisy, with roughly regular spikes (in many different shapes) in traffic data....

We show, that SN1987A can serve as an astrophysical laboratory for testing the viability of the assertion that a new massive neutral fermion is implied by the KARMEN data. We show that a wide range of the parameters characterizing the proposed particle is ruled out by the above constraints making this interpretation very unlikely.

Anomaly detection in big data is a key problem in the big data analytics domain. In this paper, the definitions of anomaly detection and big data were presented. Due to the sampling and storage burden and the inadequacy of privacy protection of anomaly detection based on uncompressed data, compressive sensing theory was introduced and used in the anomaly detection algorithm. The anomaly detecti...

We examine the Weyl anomaly for a four-dimensional z = 3 Lifshitz scalar coupled to Hořava’s theory of anisotropic gravity. We find a one-loop break-down of scale-invariance at second order in the gravitational background.