Focus-score weighted super-resolution for uncooperative iris recognition at a distance and on the move

Uncooperative iris identification systems at a distance and on the move often suffer from poor resolution and poor focus of the captured iris images. The lack of pixel resolution and well-focused images significantly degrades the iris recognition performance. This paper proposes a new approach to incorporate the focus score into a reconstruction-based super-resolution process to generate a high resolution iris image from a low resolution and focus inconsistent video sequence of an eye. A reconstruction-based technique, which can incorporate middle and high frequency components from multiple low resolution frames into one desired super-resolved frame without introducing false high frequency components, is used. A new focus assessment approach is proposed for uncooperative iris at a distance and on the move to improve performance for variations in lighting, size and occlusion. A novel fusion scheme is then proposed to incorporate the proposed focus score into the super-resolution process. The experiments conducted on the The Multiple Biometric Grand Challenge portal database shows that our proposed approach achieves an EER of 2.1%, outperforming the existing state-of-the-art averaging signal-level fusion approach by 19.2% and the robust mean super-resolution approach by 8.7%.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

The Heavy Vehicle Study : a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models

The health of tollbooth workers is seriously threatened by long-term exposure to polluted air from vehicle exhausts. Using traffic data collected at a toll plaza, vehicle movements were simulated by a system dynamics model with different traffic volumes and toll collection procedures. This allowed the average travel time of vehicles to be calculated. A three-dimension Computational Fluid Dynamics (CFD) model was used with a k–ε turbulence model to simulate pollutant dispersion at the toll plaza for different traffic volumes and toll collection procedures. It was shown that pollutant concentration around tollbooths increases as traffic volume increases. Whether traffic volume is low or high (1500 vehicles/h or 2500 vehicles/h), pollutant concentration decreases if electronic toll collection (ETC) is adopted. In addition, pollutant concentration around tollbooths decreases as the proportion of ETC-equipped vehicles increases. However, if the proportion of ETC-equipped vehicles is very low and the traffic volume is not heavy, then pollutant concentration increases as the number of ETC lanes increases.

Channel plasmon-polariton modes in V grooves filled with dielectric

We investigated the effect of dielectric filling in a V groove on the propagation parameters of channel plasmon-polariton (CPP) modes. In particular, existence conditions and critical groove angles, mode localization, field structure, dispersion, and propagation distances of CPP modes are analyzed as functions of dielectric permittivity inside the groove. It is demonstrated that increasing dielectric permittivity in the groove results in a rapid increase of mode localization near the tip of the groove and increase of both the critical angles that determine a range of groove angles for which CPP modes can exist. Detailed analysis of the field structure has demonstrated that the maximum of the field in a CPP mode is typically reached at a small distance from the tip of the groove. The effect of rounded tip is also investigated.

Adhesion and dispersion of salmeterol xinofoate from lactose interactive mixtures for inhalation - can surface roughness of carriers determine performance

The objective was to understand the influence of the surface roughness of lactose carriers on the adhesion and dispersion of salmeterol xinafoate (SX) from interactive mixtures. The surface roughness of lactose carriers was determined by confocal microscopy. Particle images and adhesion forces between SX and lactose particles were determined by Atomic Force Microscopy. The dispersion of SX (2.5%) from interactive mixtures with lactose was determined using a twin-stage impinger (TSI) with a Rotahaler® at an airflow rate of 60L/min. SX was analysed using a validated HPLC assay. The RMS Rq of lactose carriers ranged from 0.93-2.84μm, the Fine Particle Fraction (FPF) of SX ranged between 4 and 24 percent and average adhesion force between a SX and lactose particles ranged between 49 and 134 nN. No direct correlation was observed between the RMS Rq of lactose carriers and either the FPF of SX for the interactive mixtures or the adhesion force of a SX on the lactose particles; however, the presence of fine lactose associated with the carrier surface increased the FPF of SX. Dispersion through direct SX detachment from the carrier surface was not consistent with the poor correlations described and was more likely to occur through complex particulate interactions involving fine lactose.

Effects of magnesium stearate on the efficient dispersion of salbutamol sulphate from carrier-based dry powder inhaler formulations

Dry powder inhaler (DPI) formulations is one of the most useful aerosol preparations in which drugs may be formulated as carrier-based interactive mixtures with micronised drug particles (<5 μm) adhered onto the surface of large inert carriers (lactose powders). The addition of magnesium stearate (MgSt) (1-3), was found to increase dispersion of various drugs from DPI formulations. Recently, some active compounds coated with 5% (wt/wt) MgSt using the mechanofusion method showed significant improvements in aerosolization behavior due to the reduction in intrinsic cohesion force (4). Application of MgSt in powder formulations is not new; however, no studies demonstrated the minimum threshold level for this excipient in efficient aerosolization of drug powders from the interactive mixtures. Therefore, this study investigated the role of MgSt concentration on the efficient dispersion of salbutamol sulphate (SS) from DPI formulations.

Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move

Less cooperative iris identification systems at a distance and on the move often suffers from poor resolution. The lack of pixel resolution significantly degrades the iris recognition performance. Super-resolution has been considered to enhance resolution of iris images. This paper proposes a pixelwise super-resolution technique to reconstruct a high resolution iris image from a video sequence of an eye. A novel fusion approach is proposed to incorporate information details from multiple frames using robust mean. Experiments on the MBGC NIR portal database show the validity of the proposed approach in comparison with other resolution enhancement techniques.

Employer-based support for registered nurses undertaking postgraduate study via distance education

Previous literature has focused on the need for support of undergraduate nursing students during clinical placements. Little is known about the support provided by employers for registered nurses (RNs) who pursue further education. This study sought to identify and describe the types, levels and perceived need for support in the workplace for RNs as they undertake further postgraduate nursing study by distance education (DE).Using an exploratory descriptive design a self-report questionnaire was distributed to a convenient sample of 270 RNs working in one acute care public hospital in Tasmania, Australia.92 questionnaires (response rate 34%) were returned with 26 (28%) reporting being currently enrolled in further study by DE and a further 50 (54)% of RNs planning future study. Results revealed that 100% of participants with a Masters degree completed this by DE. There were differences between the support sought by RNs to that offered by employers, and 16 (34%) who had done or were currently doing DE study, received no support to undertake DE. There was an overwhelming desire by RNs for support; 87 (94%), with a majority believing some support should be mandatory 76 (83%).This study may encourage employers to introduce structured support systems that will actively assist nurses to pursue further study. © 2010.

Pseudoseeds : investigating long-distance, ocean seed dispersal with wireless sensors

Recent theoretical research has shown that ocean currents and wind interact to disperse seeds over long distances among isolated landmasses. Dispersal of seeds among isolated oceanic islands, by birds, oceans and man, is a well-known phenomenon, and many widespread island plants have traits that facilitate this process. Crucially, however, there have been no mechanistic vector-based models of long-distance dispersal for seeds among isolated oceanic islands based on empirical data. Here, we propose a plan to develop seed analogues, or pseudoseeds, fitted with wireless sensor technology that will enable high-fidelity tracking as they disperse across the ocean. The pseudoseeds will be precisely designed to mimic actual seed buoyancy and morphology enabling realistic and accurate, vector-based dispersal models of ocean seed dispersal over vast geographic scales.