994 resultados para Critical Sensitivity


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Finite element analysis is a useful tool in understanding how the accommodation system of the eye works. Further to simpler FEA models that have been used hitherto, this paper describes a sensitivity study which aims to understand which parameters of the crystalline lens are key to developing an accurate model of the accommodation system. A number of lens models were created, allowing the mechanical properties, internal structure and outer geometry to be varied. These models were then spun about their axes, and the deformations determined. The results showed the mechanical properties are the critical parameters, with the internal structure secondary. Further research is needed to fully understand how the internal structure and properties interact to affect lens deformation.

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Contrast susceptibility is defined as the difference in visual acuity recorded for high and low contrast optotypes. Other researchers refer to this parameter as "normalised low contrast acuity". Pilot surveys have revealed that contrast susceptibility deficits are more strongly related to driving accident involvement than are deficits in high contrast visual acuity. It has been hypothesised that driving situation avoidance is purely based upon high contrast visual acuity. Hence, the relationship between high contrast visual acuity and accidents is masked by situation avoidance whilst drivers with contrast susceptibility deficits remain prone to accidents in poor visibility conditions. A national survey carried out to test this hypothesis provided no support for either the link between contrast susceptibility deficits and accidents involvement or the proposed hypothesis. Further, systematically worse contrast susceptibility scores emerged from vision screeners compared to wall mounted test charts. This discrepancy was not due to variations in test luminance or instrument myopia. Instead, optical imperfections inherent in vision screeners were considered to be responsible. Although contrast susceptibility is unlikely to provide a useful means of screening drivers' vision, previous research does provide support for its ability to detect visual deficits that may influence everyday tasks. In this respect, individual contrast susceptibility variations were found to reflect variations in the contrast sensitivity function - a parameter that provides a global estimate of human contrast sensitivity.

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This thesis studied the effect of (i) the number of grating components and (ii) parameter randomisation on root-mean-square (r.m.s.) contrast sensitivity and spatial integration. The effectiveness of spatial integration without external spatial noise depended on the number of equally spaced orientation components in the sum of gratings. The critical area marking the saturation of spatial integration was found to decrease when the number of components increased from 1 to 5-6 but increased again at 8-16 components. The critical area behaved similarly as a function of the number of grating components when stimuli consisted of 3, 6 or 16 components with different orientations and/or phases embedded in spatial noise. Spatial integration seemed to depend on the global Fourier structure of the stimulus. Spatial integration was similar for sums of two vertical cosine or sine gratings with various Michelson contrasts in noise. The critical area for a grating sum was found to be a sum of logarithmic critical areas for the component gratings weighted by their relative Michelson contrasts. The human visual system was modelled as a simple image processor where the visual stimuli is first low-pass filtered by the optical modulation transfer function of the human eye and secondly high-pass filtered, up to the spatial cut-off frequency determined by the lowest neural sampling density, by the neural modulation transfer function of the visual pathways. The internal noise is then added before signal interpretation occurs in the brain. The detection is mediated by a local spatially windowed matched filter. The model was extended to include complex stimuli and its applicability to the data was found to be successful. The shape of spatial integration function was similar for non-randomised and randomised simple and complex gratings. However, orientation and/or phase randomised reduced r.m.s contrast sensitivity by a factor of 2. The effect of parameter randomisation on spatial integration was modelled under the assumption that human observers change the observer strategy from cross-correlation (i.e., a matched filter) to auto-correlation detection when uncertainty is introduced to the task. The model described the data accurately.

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The aim of this work is to evaluate the SEE sensitivity of a multi-core processor having implemented ECC and parity in their cache memories. Two different application scenarios are studied. The first one configures the multi-core in Asymmetric Multi-Processing mode running a memory-bound application, whereas the second one uses the Symmetric Multi-Processsing mode running a CPU-bound application. The experiments were validated through radiation ground testing performed with 14 MeV neutrons on the Freescale P2041 multi-core manufactured in 45nm SOI technology. A deep analysis of the observed errors in cache memories was carried-out in order to reveal vulnerabilities in the cache protection mechanisms. Critical zones like tag addresses were affected during the experiments. In addition, the results show that the sensitivity strongly depends on the application and the multi-processsing mode used.

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BACKGROUND: Efficient effort expenditure to obtain rewards is critical for optimal goal-directed behavior and learning. Clinical observation suggests that individuals with autism spectrum disorders (ASD) may show dysregulated reward-based effort expenditure, but no behavioral study to date has assessed effort-based decision-making in ASD. METHODS: The current study compared a group of adults with ASD to a group of typically developing adults on the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of effort-based decision-making. In this task, participants were provided with the probability of receiving a monetary reward on a particular trial and asked to choose between either an "easy task" (less motoric effort) for a small, stable reward or a "hard task" (greater motoric effort) for a variable but consistently larger reward. RESULTS: Participants with ASD chose the hard task more frequently than did the control group, yet were less influenced by differences in reward value and probability than the control group. Additionally, effort-based decision-making was related to repetitive behavior symptoms across both groups. CONCLUSIONS: These results suggest that individuals with ASD may be more willing to expend effort to obtain a monetary reward regardless of the reward contingencies. More broadly, results suggest that behavioral choices may be less influenced by information about reward contingencies in individuals with ASD. This atypical pattern of effort-based decision-making may be relevant for understanding the heightened reward motivation for circumscribed interests in ASD.

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One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.

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This paper reports the thermomechanical sensitivity of bimaterial cantilevers over a mid-infrared (IR) spectral range (5-10 µm) that is critical both for chemical analysis via vibrational spectroscopy and for direct thermal detection in the 300-700 K range. Mechanical bending sensitivity and noise were measured and modeled for six commercially available microcantilevers, which consist of either an aluminum film on a silicon cantilever or a gold film on a silicon nitride cantilever. The spectral sensitivity of each cantilever was determined by recording cantilever deflection when illuminated with IR light from a monochromator. Rigorous modeling and systematic characterization of the optical system allowed for a quantitative estimate of IR energy incident upon the cantilever. Separately, spectral absorptance of the cantilever was measured using Fourier transform infrared (FT-IR) microscopy, which was compared with analytical models of radiation onto the cantilever and heat flow within the cantilever. The predictions of microcantilever thermomechanical bending sensitivity and noise agree well with measurements, resulting in a ranking of these cantilevers for their potential use in IR measurements.

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The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

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In this article, the author discusses how she applied autoethnography in a study of the design of hypermedia educational resources and shows how she addressed problematic issues related to autoethnographic legitimacy and representation. The study covered a 6-year period during which the practitioner’s perspective on the internal and external factors influencing the creation of three hypermedia CD-ROMs contributed to an emerging theory of design. The author highlights the interrelationship between perception and reality as vital to qualitative approaches and encourages researchers to investigate their reality more fully by practicing the art of autoethnography.