480 resultados para Modified Super-Time-Stepping


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A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.

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OBJECTIVE: Childhood-onset type 1 diabetes is associated with neurocognitive deficits, but there is limited evidence to date regarding associated neuroanatomical brain changes and their relationship to illness variables such as age at disease onset. This report examines age-related changes in volume and T2 relaxation time (a fundamental parameter of magnetic resonance imaging that reflects tissue health) across the whole brain. RESEARCH DESIGN AND METHODS: Type 1 diabetes, N = 79 (mean age 20.32 ± 4.24 years), and healthy control participants, N = 50 (mean age 20.53 ± 3.60 years). There were no substantial group differences on socioeconomic status, sex ratio, or intelligence quotient. RESULTS: Regression analyses revealed a negative correlation between age and brain changes, with decreasing gray matter volume and T2 relaxation time with age in multiple brain regions in the type 1 diabetes group. In comparison, the age-related decline in the control group was small. Examination of the interaction of group and age confirmed a group difference (type 1 diabetes vs. control) in the relationship between age and brain volume/T2 relaxation time. CONCLUSIONS: We demonstrated an interaction between age and group in predicting brain volumes and T2 relaxation time such that there was a decline in these outcomes in type 1 diabetic participants that was much less evident in control subjects. Findings suggest the neurodevelopmental pathways of youth with type 1 diabetes have diverged from those of their healthy peers by late adolescence and early adulthood but the explanation for this phenomenon remains to be clarified.

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Part-time employment presents a conundrum in that it facilitates work-life priorities, while also, compared to equivalent full-time roles, attracting penalties such as diminished career prospects and lower commensurate remuneration. Recently, some promising theoretical developments in the job/work design literature suggest that consideration of work design may redress some of the penalties associated with part-time work. Adopting the framework of the Elaborated Model of Work Design by Parker and colleagues (2001), we examined this possibility through interviews with part-time professional service employees and their supervisors. The findings revealed that in organizations characterised by cultural norms of extended working hours and a singular-focused commitment to work, part-time roles were often inadequately re-designed when adapted from full-time arrangements. The findings also demonstrated that certain work design characteristics (e.g. predictability of work-flow, interdependencies with co-workers) render some roles more suitable for part-time arrangements than others. The research provides insights into gaps between policy objectives and outcomes associated with part-time work, challenges assumptions about the limitations of part-time roles, and suggests re-design strategies for more effective part-time arrangements.

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An improved scaling analysis and direct numerical simulations are performed for the unsteady natural convection boundary layer adjacent to a downward facing inclined plate with uniform heat flux. The development of the thermal or viscous boundary layers may be classified into three distinct stages: a start-up stage, a transitional stage and a steady stage, which can be clearly identified in the analytical as well as the numerical results. Previous scaling shows that the existing scaling laws of the boundary layer thickness, velocity and steady state time scale for the natural convection flow on a heated plate of uniform heat flux provide a very poor prediction of the Prandtl number dependency of the flow. However, those scalings perform very well with Rayleigh number and aspect ratio dependency. In this study, a modified Prandtl number scaling is developed using a triple layer integral approach for Pr > 1. It is seen that in comparison to the direct numerical simulations, the modified scaling performs considerably better than the previous scaling.

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The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

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The article discusses evidence that time prevented many students from showing what they could do in the 2010 Year 7 and 9 NAPLAN numeracy tests. In addition to analysing the available data, the article discusses some NAPLAN numeracy questions that contribute to this problem. It is suggested that schools should investigate whether time limitation is a problem for their own students. The article discusses the implications of these findings for teachers preparing students for NAPLAN tests and for the developers of the tests.

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Genetically modified or engineered foods are produced from rapidly expanding technologies that have sparked international debates and concerns about health and safety. These concerns focus on the potential dangers to human health, the risks of genetic pollution, and the demise of alternative farming techniques as well as biopiracy and economic exploitation by large private corporations. This article discusses the findings of the world's first Royal Commission on Genetic Modification conducted in New Zealand and reveals that there are potential social, ecological and economic risks created by genetically modified foods that require closer criminological scrutiny. As contemporary criminological discourses continue to push new boundaries in areas of crimes of the economy, environmental pollution, risk management, governance and globalization, the potential concerns posed by genetically modified foods creates fertile ground for criminological scholarship and activism.

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Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

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Several studies of the surface effect on bending properties of a nanowire (NW) have been conducted. However, these analyses are mainly based on theoretical predictions, and there is seldom integration study in combination between theoretical predictions and simulation results. Thus, based on the molecular dynamics (MD) simulation and different modified beam theories, a comprehensive theoretical and numerical study for bending properties of nanowires considering surface/intrinsic stress effects and axial extension effect is conducted in this work. The discussion begins from the Euler-Bernoulli beam theory and Timoshenko beam theory augmented with surface effect. It is found that when the NW possesses a relatively small cross-sectional size, these two theories cannot accurately interpret the true surface effect. The incorporation of axial extension effect into Euler-Bernoulli beam theory provides a nonlinear solution that agrees with the nonlinear-elastic experimental and MD results. However, it is still found inaccurate when the NW cross-sectional size is relatively small. Such inaccuracy is also observed for the Euler-Bernoulli beam theory augmented with both contributions from surface effect and axial extension effect. A comprehensive model for completely considering influences from surface stress, intrinsic stress, and axial extension is then proposed, which leads to good agreement with MD simulation results. It is thus concluded that, for NWs with a relatively small cross-sectional size, a simple consideration of surface stress effect is inappropriate, and a comprehensive consideration of the intrinsic stress effect is required.

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This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

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The concept of local accumulation time (LAT) was introduced by Berezhkovskii and coworkers in 2010–2011 to give a finite measure of the time required for the transient solution of a reaction–diffusion equation to approach the steady–state solution (Biophys J. 99, L59 (2010); Phys Rev E. 83, 051906 (2011)). Such a measure is referred to as a critical time. Here, we show that LAT is, in fact, identical to the concept of mean action time (MAT) that was first introduced by McNabb in 1991 (IMA J Appl Math. 47, 193 (1991)). Although McNabb’s initial argument was motivated by considering the mean particle lifetime (MPLT) for a linear death process, he applied the ideas to study diffusion. We extend the work of these authors by deriving expressions for the MAT for a general one–dimensional linear advection–diffusion–reaction problem. Using a combination of continuum and discrete approaches, we show that MAT and MPLT are equivalent for certain uniform–to-uniform transitions; these results provide a practical interpretation for MAT, by directly linking the stochastic microscopic processes to a meaningful macroscopic timescale. We find that for more general transitions, the equivalence between MAT and MPLT does not hold. Unlike other critical time definitions, we show that it is possible to evaluate the MAT without solving the underlying partial differential equation (pde). This makes MAT a simple and attractive quantity for practical situations. Finally, our work explores the accuracy of certain approximations derived using the MAT, showing that useful approximations for nonlinear kinetic processes can be obtained, again without treating the governing pde directly.

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Driver response (reaction) time (tr) of the second queuing vehicle is generally longer than other vehicles at signalized intersections. Though this phenomenon was revealed in 1972, the above factor is still ignored in conventional departure models. This paper highlights the need for quantitative measurements and analysis of queuing vehicle performance in spontaneous discharge pattern because it can improve microsimulation. Video recording from major cities in Australia plus twenty two sets of vehicle trajectories extracted from the Next Generation Simulation (NGSIM) Peachtree Street Dataset have been analyzed to better understand queuing vehicle performance in the discharge process. Findings from this research will alleviate driver response time and also can be used for the calibration of the microscopic traffic simulation model.

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This paper presents the benefits and issues related to travel time prediction on urban network. Travel time information quantifies congestion and is perhaps the most important network performance measure. Travel time prediction has been an active area of research for the last five decades. The activities related to ITS have increased the attention of researchers for better and accurate real-time prediction of travel time. Majority of the literature on travel time prediction is applicable to freeways where, under non-incident conditions, traffic flow is not affected by external factors such as traffic control signals and opposing traffic flows. On urban environment the problem is more complicated due to conflicting areas (intersections), mid-link sources and sinks etc. and needs to be addressed.