191 resultados para Random telegraph noise (RTN)


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Urban road traffic noise in cities is an ongoing and increasing problem across much of the world. Consequently a large amount of effort is expended in attempts to address this problem, especially in the area of acoustic design of buildings. Acoustic design policies developed by government authorities will typically focus on required transport noise reductions through a building façade to meet a specified internal noise levels. The significance of balcony acoustic treatments has been highlighted in recent decades yet this area has potentially been considered less important than the need for acoustic isolation of building facades. This paper outlines recent research that has been conducted in determining the significance of balcony acoustic treatments in mitigating urban road traffic noise. It summarizes recent literature, some of which focuses on technological advances in the knowledge of balcony acoustic design and some literature discusses the overall aims and benefits of balcony acoustic design. The aim of this paper is to promote the use of balcony acoustic design as a significant element in the overall solution towards mitigating road traffic noise in modern cities.

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Balcony acoustic treatments can mitigate the effects of community road traffic noise. To further investigate, a theoretical study into the effects of balcony acoustic treatment combinations on speech interference and transmission is conducted for various street geometries. Nine different balcony types are investigated using a combined specular and diffuse reflection computer model. Diffusion in the model is calculated using the radiosity technique. The balcony types include a standard balcony with or without a ceiling and with various combinations of parapet, ceiling absorption and ceiling shield. A total of 70 balcony and street geometrical configurations are analyzed with each balcony type, resulting in 630 scenarios. In each scenario the reverberation time, speech interference level (SIL) and speech transmission index (STI) are calculated. These indicators are compared to determine trends based on the effects of propagation path, inclusion of opposite buildings and difference with a reference position outside the balcony. The results demonstrate trends in SIL and STI with different balcony types. It is found that an acoustically treated balcony reduces speech interference. A parapet provides the largest improvement, followed by absorption on the ceiling. The largest reductions in speech interference arise when a combination of balcony acoustic treatments are applied.

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The work described in this technical report is part of an ongoing project to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the methods we use to remove background noise from spectrograms. It updates techniques previously described in Towsey and Planitz (2011), Technical report: acoustic analysis of the natural environment, downloadable from: http://eprints.qut.edu.au/41131/. It also describes noise removal from wave-forms, a technique not described in the above 2011 technical report.

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Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

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The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.

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Background Random Breath Testing (RBT) remains a central enforcement strategy to deter and apprehend drink drivers in Queensland (Australia). Despite this, there is little published research regarding the exact drink driving apprehension rates across the state as measured through RBT activities. Aims The aim of the current study was to examine the prevalence of apprehending drink drivers in urban versus rural areas. Methods The Queensland Police Service provided data relating to the number of RBT conducted and apprehensions for the period 1 January 2000 to 31 December 2011. Results In the period, 35,082,386 random breath tests (both mobile and stationary) were conducted in Queensland which resulted in 248,173 individuals being apprehended for drink driving offences. Overall drink driving apprehension rates appear to have decreased across time. Close examination of the data revealed that the highest proportion of drink driving apprehensions (when compared with RBT testing rates) was in the Northern and Far Northern regions of Queensland (e.g., rural areas). In contrast, the lowest proportions were observed within the two Brisbane metropolitan regions (e.g., urban areas). However, differences in enforcement styles across the urban and rural regions need to be considered. Discussion and conclusions The research presentation will further outline the major findings of the study in regards to maximising the efficiency of RBT operations both within urban and rural areas of Queensland, Australia.

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The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

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This thesis studied the source of instability in optical phase modulators used in high accuracy laser measurement systems. The nonlinear origin of the amplitude noise helped further reducing this instability in applications that rely on phase modulators to function. This outcome will have positive impacts on the development of new methods in the amplitude noise suppression.

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Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Residential balcony design influences speech interference levels caused by road traffic noise and a simplified design methodology is needed for optimising balcony acoustic treatments. This research comprehensively assesses speech interference levels and benefits of nine different balcony designs situated in urban street canyons through the use of a combined direct, specular reflection and diffuse reflection path theoretical model. This thesis outlines the theory, analysis and results that lead up to the presentation of a practical design guide which can be used to predict the acoustic effects of balcony geometry and acoustic treatments in streets with variable geometry and acoustic characteristics.

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The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.

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Our results demonstrate that photorefractive residual amplitude modulation (RAM) noise in electro-optic modulators (EOMs) can be reduced by modifying the incident beam intensity distribution. Here we report an order of magnitude reduction in RAM when beams with uniform intensity (flat-top) profiles, generated with an LCOS-SLM, are used instead of the usual fundamental Gaussian mode (TEM00). RAM arises from the photorefractive amplified scatter noise off the defects and impurities within the crystal. A reduction in RAM is observed with increasing intensity uniformity (flatness), which is attributed to a reduction in space charge field on the beam axis. The level of RAM reduction that can be achieved is physically limited by clipping at EOM apertures, with the observed results agreeing well with a simple model. These results are particularly important in applications where the reduction of residual amplitude modulation to 10^-6 is essential.

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In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations.

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There has been considerable recent work on the development of energy conserving one-step methods that are not symplectic. Here we extend these ideas to stochastic Hamiltonian problems with additive noise and show that there are classes of Runge-Kutta methods that are very effective in preserving the expectation of the Hamiltonian, but care has to be taken in how the Wiener increments are sampled at each timestep. Some numerical simulations illustrate the performance of these methods.