Fifty Years of Candidate Pulsar Selection - What next?

For fifty years astronomers have been searching for pulsar signals in observational data. Throughout this time the process of choosing detections worthy of investigation, so called candidate selection, has been effective, yielding thousands of pulsar discoveries. Yet in recent years technological advances have permitted the proliferation of pulsar-like candidates, straining our candidate selection capabilities, and ultimately reducing selection accuracy. To overcome such problems, we now apply intelligent machine learning tools. Whilst these have achieved success, candidate volumes continue to increase, and our methods have to evolve to keep pace with the change. This talk considers how to meet this challenge as a community.Comment: 4 pages, submitted: Proceedings of Pulsar Astrophysics: The Next Fifty Years, IAU Symposium 33

Copy detection in Chinese documents using Ferret

Peer reviewe

Feasibility of using S-191 infrared spectra for geological studies from space

There are no author-identified significant results in this report

Analytical procedure for determining random load acting on a spacecraft due to a primary random load acting on an exterior structure Quarterly report no. 2, 1 Sep. - 30 Nov. 1965

Sound and vibration transmission in OGO SPACECRAFT shroud syste

Hellinger Distance Trees for Imbalanced Streams

Classifiers trained on data sets possessing an imbalanced class distribution are known to exhibit poor generalisation performance. This is known as the imbalanced learning problem. The problem becomes particularly acute when we consider incremental classifiers operating on imbalanced data streams, especially when the learning objective is rare class identification. As accuracy may provide a misleading impression of performance on imbalanced data, existing stream classifiers based on accuracy can suffer poor minority class performance on imbalanced streams, with the result being low minority class recall rates. In this paper we address this deficiency by proposing the use of the Hellinger distance measure, as a very fast decision tree split criterion. We demonstrate that by using Hellinger a statistically significant improvement in recall rates on imbalanced data streams can be achieved, with an acceptable increase in the false positive rate.Comment: 6 Pages, 2 figures, to be published in Proceedings 22nd International Conference on Pattern Recognition (ICPR) 201

The prediction and measurement of sound radiated by structures

Theories regarding the radiation of sound are reviewed and the implementation in strategies for explaining or measuring the sound produced by practical strucutres are discussed. Particular attention is given to those aspects that relate to the determination of the relative amounts of sound generated by various parts of a machine or structure, which can be very useful information for noise reduction efforts

Electron Spin Resonance at the Level of 10000 Spins Using Low Impedance Superconducting Resonators

We report on electron spin resonance (ESR) measurements of phosphorus donors localized in a 200 square micron area below the inductive wire of a lumped element superconducting resonator. By combining quantum limited parametric amplification with a low impedance microwave resonator design we are able to detect around 20000 spins with a signal-to-noise ratio (SNR) of 1 in a single shot. The 150 Hz coupling strength between the resonator field and individual spins is significantly larger than the 1 - 10 Hz coupling rates obtained with typical coplanar waveguide resonator designs. Due to the larger coupling rate, we find that spin relaxation is dominated by radiative decay into the resonator and dependent upon the spin-resonator detuning, as predicted by Purcell

Reevaluation of the normative minerals of Sonora Pass rock standards - University of Nevada reports 7 and 12

Chemical analyses and normative minerals of Nevada mountain pass rock