Optical Turbulence Measurements and Models for Mount John University Observatory

Site measurements were collected at Mount John University Observatory in 2005 and 2007 using a purpose-built scintillation detection and ranging system. $C_n^2(h)$ profiling indicates a weak layer located at 12 - 14 km above sea level and strong low altitude turbulence extending up to 5 km. During calm weather conditions, an additional layer was detected at 6 - 8 km above sea level. $V(h)$ profiling suggests that tropopause layer velocities are nominally 12 - 30 m/s, and near-ground velocities range between 2 -- 20 m/s, dependent on weather. Little seasonal variation was detected in either $C_n^2(h)$ and $V(h)$ profiles. The average coherence length, $r_0$, was found to be $7 \pm 1$ cm for the full profile at a wavelength of 589 nm. The average isoplanatic angle, $\theta_0$, was $1.0 \pm 0.1$ arcsec. The mean turbulence altitude, $\bar{h_0}$, was found to be $2.0\pm0.7$ km above sea level. No average in the Greenwood frequency, $f_G$, could be established due to the gaps present in the \vw\s profiles obtained. A modified Hufnagel-Valley model was developed to describe the $C_n^2(h)$ profiles at Mount John, which estimates $r_0$ at 6 cm and $\theta_0$ at 0.9 arcsec. A series of $V(h)$ models were developed, based on the Greenwood wind model with an additional peak located at low altitudes. Using the $C_n^2(h)$ model and the suggested $V(h)$ model for moderate ground wind speeds, $f_G$ is estimated at 79 Hz.Comment: 14 pages; accepted for publication in PAS

Factors affecting consistency and accuracy in identifying modern macroperforate planktonic foraminifera

Planktonic foraminifera are widely used in biostratigraphic, palaeoceanographic and evolutionary studies, but the strength of many study conclusions could be weakened if taxonomic identifications are not reproducible by different workers. In this study, to assess the relative importance of a range of possible reasons for among-worker disagreement in identification, 100 specimens of 26 species of macroperforate planktonic foraminifera were selected from a core-top site in the subtropical Pacific Ocean. Twenty-three scientists at different career stages – including some with only a few days experience of planktonic foraminifera – were asked to identify each specimen to species level, and to indicate their confidence in each identification. The participants were provided with a species list and had access to additional reference materials. We use generalised linear mixed-effects models to test the relevance of three sets of factors in identification accuracy: participant-level characteristics (including experience), species-level characteristics (including a participant’s knowledge of the species) and specimen-level characteristics (size, confidence in identification). The 19 less experienced scientists achieve a median accuracy of 57 %, which rises to 75 % for specimens they are confident in. For the 4 most experienced participants, overall accuracy is 79 %, rising to 93 % when they are confident. To obtain maximum comparability and ease of analysis, everyone used a standard microscope with only 35× magnification, and each specimen was studied in isolation. Consequently, these data provide a lower limit for an estimate of consistency. Importantly, participants could largely predict whether their identifications were correct or incorrect: their own assessments of specimen-level confidence and of their previous knowledge of species concepts were the strongest predictors of accuracy

Detection/estimation of the modulus of a vector. Application to point source detection in polarization data

Given a set of images, whose pixel values can be considered as the components of a vector, it is interesting to estimate the modulus of such a vector in some localised areas corresponding to a compact signal. For instance, the detection/estimation of a polarized signal in compact sources immersed in a background is relevant in some fields like astrophysics. We develop two different techniques, one based on the Neyman-Pearson lemma, the Neyman-Pearson filter (NPF), and another based on prefiltering-before-fusion, the filtered fusion (FF), to deal with the problem of detection of the source and estimation of the polarization given two or three images corresponding to the different components of polarization (two for linear polarization, three including circular polarization). For the case of linear polarization, we have performed numerical simulations on two-dimensional patches to test these filters following two different approaches (a blind and a non-blind detection), considering extragalactic point sources immersed in cosmic microwave background (CMB) and non-stationary noise with the conditions of the 70 GHz \emph{Planck} channel. The FF outperforms the NPF, especially for low fluxes. We can detect with the FF extragalactic sources in a high noise zone with fluxes >= (0.42,0.36) Jy for (blind/non-blind) detection and in a low noise zone with fluxes >= (0.22,0.18) Jy for (blind/non-blind) detection with low errors in the estimated flux and position.Comment: 11 pages, 5 figure

An adaptive stereo basis method for convolutive blind audio source separation

NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [71, 10-12, June 2008] DOI:neucom.2007.08.02