979 resultados para Leak locations


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Leakage in buried pipes is one of the main concerns for water companies due to the scarcity of potable water sources. Older metallic pipelines have been replaced by plastic pipes in such systems, which makes it more difficult to locate leaks using acoustics and vibration. This is mainly because of the high attenuation of leak signals caused by the damping in the pipe wall. To investigate acoustic methods in leak location in controlled conditions, a bespoke test rig was constructed in the UK. In this paper, data from this test-rig is used to discuss some issues that arise when using two contemporary correlators. Of particular interest, is the way in which a resonance in the system can have a profound effect on the estimate of the position of the leak depending on the way in which the leak noise signals are processed. © (2013) Trans Tech Publications.

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To determine the location of leaks in buried water pipes, acoustic methods are often used. These have proven to be very effective in metallic pipes but have been problematic in modern plastic pipes. In this paper the reason why this is so is discussed together with some measurements that were made on a bespoke test rig built by South Staffs Water plc. A particular problem is the estimate of the wavespeed. Tables are frequently used for this purpose, but these are often inaccurate and this means that a leak cannot be located accurately. An in-situ measure of the wavespeed is thus preferable. In this paper it is shown that there are significant issues in obtaining an accurate estimate of the wavespeed when a leak is present in the system. A method is proposed that overcomes some of these problems, which is discussed and is demonstrated using some data from the bespoke test-rig. © (2013) Trans Tech Publications.

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This paper discusses a successful application of the Acoustic Emission Technique (AET) for the detection and location of leak paths present on an inaccessible side of an end shield of a Pressurised Heavy Water Reactor (PHWR). The methodology was based on the fact that air- and water-leak AE signals have different characteristic features. Baseline data was generated from a sound end shield of a PHWR for characterising the background noise. A mock-up end shield system with saw-cut leak paths was used to verify the validity of the methodology. It was found that air-leak signals under pressurisation (as low as 3 psi) could be detected by frequency domain analysis. Signals due to air leaks from various locations of defective end shield were acquired and analysed. It was possible to detect and locate leak paths. The presence of detected leak paths was further confirmed by an alternative test.

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The role of networks and their contribution to sustaining and developing creative industries is well documented (Wittel 2001; Kong 2005; Pratt 2007). This article argues that although networks operate across geographical boundaries, particularly through the use of communication technologies, the majority of studies have focussed on the ways in which networks operate in a) specific inner-urban metropolitan regions or b) specific industries. Such studies are informed by the geographical mindset of creative city proponents such as Florida (2002) and Landry (2000) in which inner-urban precincts are seen as the prime location for creative industries activity, business development and opportunity. But what of those creative industries situated beyond the inner city? Evidence in Australia suggests there is increasing creative industries activity beyond the inner city, in outer-suburban and ex-urban areas (Gibson & Brennan-Horley 2006). This article identifies characteristics of creative industries networks in outer-suburban locations in Melbourne and Brisbane. It argues that supporting and sustaining creative industries networks in these locations may require different strategies than those applied to inner-city networks. The article thus contributes to the growing understanding of the cultural economic geography of creative industries.

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We investigated the relative importance of vision and proprioception in estimating target and hand locations in a dynamic environment. Subjects performed a position estimation task in which a target moved horizontally on a screen at a constant velocity and then disappeared. They were asked to estimate the position of the invisible target under two conditions: passively observing and manually tracking. The tracking trials included three visual conditions with a cursor representing the hand position: always visible, disappearing simultaneously with target disappearance, and always invisible. The target’s invisible displacement was systematically underestimated during passive observation. In active conditions, tracking with the visible cursor significantly decreased the extent of underestimation. Tracking of the invisible target became much more accurate under this condition and was not affected by cursor disappearance. In a second experiment, subjects were asked to judge the position of their unseen hand instead of the target during tracking movements. Invisible hand displacements were also underestimated when compared with the actual displacement. Continuous or brief presentation of the cursor reduced the extent of underestimation. These results suggest that vision–proprioception interactions are critical for representing exact target–hand spatial relationships, and that such sensorimotor representation of hand kinematics serves a cognitive function in predicting target position. We propose a hypothesis that the central nervous system can utilize information derived from proprioception and/or efference copy for sensorimotor prediction of dynamic target and hand positions, but that effective use of this information for conscious estimation requires that it be presented in a form that corresponds to that used for the estimations.

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In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

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The role of networks and their contribution to sustaining and developing creative industries is well documented (Wittel 2001; Kong 2005; Pratt 2007). This article argues that although networks operate across geographical boundaries, particularly through the use of communication technologies, the majority of studies have focussed on the ways in which networks operate in a) specific inner-urban metropolitan regions or b) specific industries. Such studies are informed by the geographical mindset of creative city proponents such as Florida (2002) and Landry (2000) in which inner-urban precincts are seen as the prime location for creative industries activity, business development and opportunity. But what of those creative industries situated beyond the inner city? Evidence in Australia suggests there is increasing creative industries activity beyond the inner city, in outer-suburban and ex-urban areas (Gibson & Brennan-Horley 2006). This article identifies characteristics of creative industries networks in outer-suburban locations in Melbourne and Brisbane. It argues that supporting and sustaining creative industries networks in these locations may require different strategies than those applied to inner-city networks. The article thus contributes to the growing understanding of the cultural economic geography of creative industries.

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The role of networks and their contribution to sustaining and developing creative industries is well documented (Wittel 2001, Kong 2005, Pratt, 2007). This article argues that although networks operate across geographical boundaries, particularly through the use of communication technologies, the majority of studies have focussed on the ways in which networks operate among creative industry workers located in a) specific inner-urban metropolitan regions or b) specific industries. Such studies are informed by the geographical mindset of creative city proponents such as Florida (2002) and Landry (2000) in which inner-urban precincts are seen as the prime location or ‘hub’ for creative industries activity, business development and opportunity. But what of those creative industries situated beyond the inner city? Evidence in Australia suggests that there is increasing creative industries activity beyond the inner city, in outer-suburban and ex-urban areas (Gibson and Brennan-Horley 2006). This article identifies features of networks operating two outer-suburban locations.

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Compass Points: The Locations, Landscapes and Coordinates of Identities' the Australasian Association for Theatre, Drama and Performance Studies (ADSA) Conference 2012 was held at Queensland University of Technology, July 3-6 2012. The Conference was sponsored by the Australasian Association for Theatre, Drama and Performance Studies (ADSA), Queensland University of Technology (QUT), Ian Potter Foundation, Arts Queensland, La Boite Theatre Company and Queensland Theatre Company. The papers selected for this collection represent a small sample of the scope, depth and diversity of scholarship presented at the conference - they cover a range of genres, cultures and contexts in contemporary performance making from autobiography, to playwrighting, to public space performance and beyond. The papers collected have been peer-reviewed to Australia’s Department of Education, Science and Training (DEST) standards - each has been subject to two blind reviews, followed by acceptance, rejection or revision, and editing of accepted papers - by colleagues from Australasia and overseas. The review process for the conference publication was separate from the review process for acceptance of abstracts for the actual conference presentations. The conference convenors, Bree Hadley and Caroline Heim, edited the collection, and would like to thank all those who gave their time to advise on the peer review process and act as reviewers - Tom Burvill, Christine Comans, Sean Edgecomb, Angela Campbell, Natalie Lazaroo, Jo Loth, Meg Mumford, Ulrike Garde, Laura Ginters, Andre Bastian, Sam Trubridge, Delyse Ryan, Georgia Seffrin, Gillian Arrighi, Rand Hazou, Rob Pensalfini, Sue Fenty-Studham, Mark Radvan, Rob Conkie, Kris Plummer, Lisa Warrington, Kate Flaherty, Bryoni Tresize, Janys Hayes, Lisa Warrington, Teresa Izzard, Kim Durban, Veronica Kelly, Adrian Keirnander, James Davenport, Julie Robson and others. We, and the authors, appreciate the rigour and care with which peers have approached the scholarship presented here. This collection was published in final form on July 3rd 2012, the first day of the ADSA Conference 2012.

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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

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Background: Gestational diabetes mellitus (GDM) is increasing, along with obesity and type 2 diabetes (T2DM), with Aboriginal and Torres Strait Islander people* in Australia particularly affected. GDM causes serious complications in pregnancy, birth, and the longer term, for both women and their infants. Women diagnosed with GDM have an eightfold risk of developing T2DM after pregnancy, compared with women who have not had GDM. Indigenous women have an even higher risk, at a younger age, and progress more quickly from GDM to T2DM, compared to non-Indigenous women. If left undetected and untreated, T2DM can lead to heart disease, stroke, renal disease, kidney failure, amputations and blindness. A GDM diagnosis offers a ‘window of opportunity’ for diabetes health interventions and it is vital that acceptable and effective prevention, treatment, and post-pregnancy care are provided. Low rates of post-pregnancy screening for T2DM are reported among non-Aboriginal women in Australia and among Indigenous women in other countries, however data for Aboriginal women are scarce. Breastfeeding, a healthy diet, and exercise can also help to prevent T2DM, and together with T2DM screening are recommended elements of ‘post-pregnancy care’ for women with GDM, This paper describes methods for a data linkage study to investigate rates of post-pregnancy care among women with GDM. Methods/Design: This retrospective cohort includes all women who gave birth at Cairns Base Hospital in Far North Queensland, Australia, from 2004 to 2010, coded as having GDM in the Cairns Base Hospital Clinical Coding system. Data linkage is being conducted with the Queensland Perinatal Data Collection, and three laboratories. Hospital medical records are being reviewed to validate the accuracy of GDM case ascertainment, and gather information on breastfeeding and provision of dietary advice. Multiple logistic regression is being used to compare post-pregnancy care between Aboriginal and non-Aboriginal women, while adjusting for other factors may impact on post-pregnancy care. Survival analysis is being used to estimate the rates of progression from GDM to T2DM. Discussion: There are challenges to collecting post-pregnancy data for women with GDM. However, research is urgently needed to ensure adequate post-pregnancy care is provided for women with GDM in Australia.

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Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

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In this work, 17-polychlorinated dibenzo-pdioxin/furan (PCDD/Fs) isomers were measured in ambient air at four urban sites in Seoul, Korea (from February to June 2009). The concentrations of their summed values RPCDD/Fs) across all four sites ranged from 1,947 (271 WHO05 TEQ) (Jong Ro) to 2,600 (349 WHO05 TEQ) fg/m3 (Yang Jae) with a mean of 2,125 ± 317) fg/m3 (292 WHO05 TEQ fg/m3). The sum values for the two isomer groups of RPCDD and RPCDF were 527 (30 WHO05 TEQ) and 1,598 (263 WHO05 TEQ) fg/m3, respectively. The concentration profile of individual species was dominated by the 2,3,4,7,8-PeCDF isomer, which contributed approximately 36 % of the RPCDD/Fs value. The observed temporal trends in PCDD/F concentrations were characterized by relative enhancement in the winter and spring. The relative contribution of different sources, when assessed by principal component analysis, is explained by the dominance of vehicular emissions along with coal (or gas) burning as the key source of ambient PCDD/Fs in the residential areas studied.

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Fatty acid methyl ester (FAME) profiles, together with Biolog substrate utilization patterns, were used in conjunction with measurements of other soil chemical and microbiological properties to describe differences in soil microbial communities induced by increased salinity and alkalinity in grass/legume pastures at three sites in SE South Australia. Total ester-linked FAMEs (EL-FAMEs) and phospholipid-linked FAMEs (PL-FAMEs), were also compared for their ability to detect differences between the soil microbial communities. The level of salinity and alkalinity in affected areas of the pastures showed seasonal variation, being greater in summer than in winter. At the time of sampling for the chemical and microbiological measurements (winter) only the affected soil at site 1 was significantly saline. The affected soils at all three sites had lower organic C and total N concentrations than the corresponding non-affected soils. At site 1 microbial biomass, CO 2-C respiration and the rate of cellulose decomposition was also lower in the affected soil compared to the non-affected soil. Biomarker fatty acids present in both the EL- and PL-FAME profiles indicated a lower ratio of fungal to bacterial fatty acids in the saline affected soil at site 1. Analysis of Biolog substrate utilization patterns indicated that the bacterial community in the affected soil at site 1 utilized fewer carbon substrates and had lower functional diversity than the corresponding community in the non-affected soil. In contrast, increased alkalinity, of major importance at sites 2 and 3, had no effect on microbial biomass, the rate of cellulose decomposition or functional diversity but was associated with significant differences in the relative amounts of several fatty acids in the PL-FAME profiles indicative of a shift towards a bacterial dominated community. Despite differences in the number and relative amounts of fatty acids detected, principal component analysis of the EL- and PL-FAME profiles were equally capable of separating the affected and non-affected soils at all three sites. Redundancy analysis of the FAME data showed that organic C, microbial biomass, electrical conductivity and bicarbonate-extractable P were significantly correlated with variation in the EL-FAME profiles, whereas pH, electrical conductivity, NH 4-N, CO 2-C respiration and the microbial quotient were significantly correlated with variation in the PL-FAME profiles. Redundancy analysis of the Biolog data indicated that cation exchange capacity and bicarbonate-extractable K were significantly correlated with the variation in Biolog substrate utilization patterns.

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We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.