This paper proposes an effective anomaly detection algorithm for forward-looking ground-penetrating radar (FLGPR). The challenges in detecting explosive hazards with FLGPR are that there are multiple types of targets buried at different depths in a highly-cluttered environment. A wide array of target and clutter signatures exist, which makes classifier design difficult. Recent work in this appl...

Using available kinematical data for a sub-sample of NLTT stars from the HIPPARCOS mission we confirm the existence of a previously reported local anomaly in the (u, v) plane: the mean motion u for our sample is largely positive (+20 km s −1). With the use of the newest global self-consistent numerical models of our Galaxy (Fux 1997), we show that a bar could be responsible for this observed ve...

I present the recent developments in a specific sub-field of chiral gauge theories on the lattice. This subfield pertains to the use of infinitely many fermi fields to describe a single chiral field. In this approach, both anomalous and anomaly free theories can be discussed in equal footing. It produces the correct anomaly in the continuum limit. It has the potential to describe fermion number...

We discuss the algebraic structure of the various BRST symmetries associated with topological Yang-Mills theory as a generalization of the BRS analysis developed for the non-Abelian anomaly in the local Yang-Mills theory. We show that our BRST algebra leads to an extended Russian formula and descent equations, which contains the descent equation of Yang-Mills theory as sub-relations. We propose...

Aortic regurgitation was the commonest functional anomaly among younger patients in a group of 63 individuals with a diagnosis of bicuspid aortic valve. With increasing age, a rise in the number with combined aortic valve disease and aortic stenosis was observed. Aortic dilatation was found in 65% of cases. Dilatation was independently associated with age and transvalvular aortic gradient.

In practical applications of classification, there are often varying costs associated with different types of misclassification (e.g. fraud detection, anomaly detection and medical diagnosis), motivating the need for the so-called ”cost-sensitive” classification. In this paper, we introduce a family of novel boosting methods for cost-sensitive classification by applying the theory of gradient b...