1,386 research outputs found
Revised time-of-flight calculations for high-latitude geomagnetic pulsations using a realistic magnetospheric magnetic field model
We present a simple time-of-flight analysis of Alfvén pulsations standing on closed terrestrial magnetic field lines. The technique employed in this study in order to calculate the characteristic period of such oscillations builds upon earlier time-of-flight estimates via the implementation of a more recent magnetospheric magnetic field model. In this case the model employed is the Tsyganenko (1996) field model, which includes realistic magnetospheric currents and the consequences of the partial penetration of the interplanetary magnetic field into the dayside magnetopause. By employing a simple description of magnetospheric plasma density, we are therefore able to estimate the period of standing Alfvén waves on geomagnetic field lines over a significantly wider range of latitudes and magnetic local times than in previous studies. Furthermore, we investigate the influence of changing season and upstream interplanetary conditions upon the period of such pulsations. Finally, the eigenfrequencies of magnetic field lines computed by the time-of-flight technique are compared with corresponding numerical solutions to the wave equation and experimentally observed pulsations on geomagnetic field lines
An epigenetic role for noncoding RNAs and intragenic DNA methylation
A report on the Keystone Symposium 'Epigenetics: Regulation of Chromatin Structure in Development and Disease', Breckenridge, USA, 11-16 April 2007
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A robust sclera segmentation algorithm
Sclera segmentation is shown to be of significant importance for eye and iris biometrics. However, sclera segmentation has not been extensively researched as a separate topic, but mainly summarized as a component of a broader task. This paper proposes a novel sclera segmentation algorithm for colour images which operates at pixel-level. Exploring various colour spaces, the proposed approach is robust to image noise and different gaze directions. The algorithm’s robustness is enhanced by a two-stage classifier. At the first stage, a set of simple classifiers is employed, while at the second stage, a neural network classifier operates on the probabilities’ space generated by the classifiers at stage 1. The proposed method was ranked the 1st in Sclera Segmentation Benchmarking Competition 2015, part of BTAS 2015, with a precision of 95.05% corresponding to a recall of 94.56%
Day-to-day variability of midlatitude ionospheric currents due to magnetospheric and lower atmospheric forcing
As known from previous studies on the solar quiet (Sq) variation of the geomagnetic field, the strength and pattern of ionospheric dynamo currents change significantly from day to day. The present study investigates the relative importance of two sources that contribute to the day-to-day variability of the ionospheric currents at middle and low latitudes. One is high-latitude electric fields that are caused by magnetospheric convection, and the other is atmospheric waves from the lower atmosphere. Global ionospheric current systems, commonly known as Sq current systems, are simulated using the National Center for Atmospheric Research thermosphere-ionosphere-mesosphere-electrodynamics general circulation model. Simulations are run for 1–30 April 2010 with a constant solar energy input but with various combinations of high-latitude forcing and lower atmospheric forcing. The model well reproduces geomagnetic perturbations on the ground, when both forcings are taken into account. The contribution of high-latitude forcing to the total Sq current intensity (Jtotal) is generally smaller than the contribution of wave forcing from below 30 km, except during active periods (Kp≥4), when Jtotal is enhanced due to the leakage of high-latitude electric fields to lower latitudes. It is found that the penetration electric field drives ionospheric currents at middle and low latitudes not only on the dayside but also on the nightside, which has an appreciable effect on the Dst index. It is also found that quiet time day-to-day variability in Jtotal is dominated by symmetric-mode migrating diurnal and semidiurnal tidal winds at 45–60° latitude at ∼110 km
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Quality-based iris segmentation-level fusion
Iris localisation and segmentation are challenging and critical tasks in iris biometric recognition. Especially in non-cooperative and less ideal environments, their impact on overall system performance has been identified as a major issue. In order to avoid a propagation of system errors along the processing chain, this paper investigates iris fusion at segmentation-level prior to feature extraction and presents a framework for this task. A novel intelligent reference method for iris segmentation-level fusion is presented, which uses a learning-based approach predicting ground truth segmentation performance from quality indicators and model-based fusion to create combined
boundaries. The new technique is analysed with regard to its capability to combine segmentation results (pupillary
and limbic boundaries) of multiple segmentation algorithms. Results are validated on pairwise combinations of four open source iris segmentation algorithms with regard to the public CASIA and IITD iris databases illustrating the high versatility of the proposed method
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Segmentation-level fusion for iris recognition
This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms
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Towards anomaly detection for increased security in multibiometric systems: spoofing-resistant 1-median fusion eliminating outliers
Multibiometrics aims at improving biometric security in presence of spoofing attempts, but exposes a larger availability of points of attack. Standard fusion rules have been shown to be highly sensitive to spoofing attempts – even in case of a single fake instance only. This paper presents a novel spoofing-resistant fusion scheme proposing the detection and elimination of anomalous fusion input in an ensemble of evidence with liveness information. This approach aims at making multibiometric systems more resistant to presentation attacks by modeling the typical behaviour of human surveillance operators detecting anomalies as employed in many decision support systems. It is shown to improve security, while retaining the high accuracy level of standard fusion approaches on the latest Fingerprint Liveness Detection Competition (LivDet) 2013 dataset
How fast do white dwarfs accrete from their low mass companion stars?
Cataclysmic variables are a type of close, interacting binary system, with a white dwarf primary and an M dwarf donor star that is in contact with its Roche lobe. As such, the outer layers of the M dwarf are gradually accreted onto the white dwarf, driven by angular momentum loss. Mass transfer and angular momentum loss dominates the evolution of these systems. I characterise 15 new eclipsing cataclysmic variable stars, finding component masses and radii, and orbital separations by modelling their light curves in multiple filters. These characterisations conform to the results of previous similar works, tracking the canonical donor evolutionary sequence. I develop a method to infer mass loss and angular momentum loss rates from donor properties. Stars are inflated by mass loss, and by replicating a donor star with the stellar evolutionary code, MESA, I can infer the mass loss rate the star is subjected to and calculate the corresponding angular momentum loss rate. I apply this method to the newly extended sample of eclipse-modelled cataclysmic variables, and report my findings. The field of research around cataclysmic variables has struggled with an unknown contribution to angular momentum losses in the short period (< 2.5 hours) regime for some time. This is seen in population synthesis models and evolutionary models, though discriminating between differing explanations for these excess losses has been somewhat challenging. By comparing existing prescriptions for magnetic braking and consequential angular momentum loss (specifically, extra angular momentum loss resulting from successive nova eruptions) with observed mass loss and angular momentum loss rates, I present preliminary evidence in favour of nova eruptions being the dominant source of excess angular momentum losses. These findings are limited primarily by the poorly understood and poorly
characterised M dwarf mass-radius relationship, a problem likely to be mitigated with the release of Gaia DR3
A high-resolution model of the external and induced magnetic field at the Earth’s surface in the northern hemisphere
We describe a method of producing high-resolution models of the Earth’s combined external and induced magnetic field (EIMF) using the method of Empirical Orthogonal Functions (EOFs) applied to the SuperMAG archive of ground-based magnetometer data. EOFs partition the variance of a system into independent modes, allowing us to extract the spatiotemporal patterns of greatest dynamical importance without applying the a priori assumptions of other methods (such as spherical harmonic analysis, parameterised averaging, or multi-variate regression). We develop an approach based on that of Beckers and Rixen [2003] and use the EOF modes to infill missing data in a self-consistent manner. Applying our method to a north polar case study spanning February 2001 (chosen for its proximity to solar maximum and good data coverage), we demonstrate that 41.7% and 9.4% of variance is explained by the leading two modes, respectively describing the temporal variations of the Disturbance Polar types 2 and 1 (DP2 and DP1) patterns. A further 14.1% of variance is explained by four modes that describe separate aspects of the motion of the DP1 and DP2 systems. Thus, collectively over 65% of variance is described by the leading 6 modes and is attributable to DP1 and DP2. This attribution is based on inspection of the spatial morphology of the modes, and analysis of the temporal variation of the mode amplitudes with respect to solar wind measures and substorm occurrence. This study is primarily a demonstration of the technique and a prelude to a model spanning the full solar cycle
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