825 resultados para DELAY
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Due to ever increasing climate instability, the number of natural disasters affecting society and communities is expected to increase globally in the future, which will result in a growing number of casualties and damage to property and infrastructure. Such damage poses crucial challenges for recovery of interdependent critical infrastructures. Post-disaster reconstruction is a complex undertaking as it is not only closely linked to the well-being and essential functioning of society, but also requires a large financial commitment. Management of critical infrastructure during post-disaster recovery needs to be underpinned by a holistic recognition that the recovery of each individual infrastructure system (e.g. energy, water, transport and information and communication technology) can be affected by the interdependencies that exist between these different systems. A fundamental characteristic of these interdependencies is that failure of one critical infrastructure system can result in the failure of other interdependent infrastructures, leading to a cascade of failures, which can impede post-disaster recovery and delay the subsequent reconstruction process. Consequently, there is a critical need for developing a holistic strategy to assess the influence of infrastructure interdependencies, and for incorporating these interdependencies into a post-disaster recovery strategy. This paper discusses four key dimensions of interdependencies that need to be considered in a post-disaster reconstruction planning. Using key concepts and sub-concepts derived from the notion of interdependency, the paper examines how critical infrastructure interdependencies affect the recovery processes of damaged infrastructures.
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Traffic law enforcement sanctions can impact on road user behaviour through general and specific deterrence mechanisms. The manner in which specific deterrence can influence recidivist behaviour can be conceptualised in different ways. While any reduction in speeding will have road safety benefits, the ways in which a ‘reduction’ is determined deserves greater methodological attention and has implications for countermeasure evaluation more generally. The primary aim of this research was to assess the specific deterrent impact of penalty increases for speeding offences in Queensland, Australia, in 2003 on two cohorts of drivers detected for speeding prior to and after the penalty changes were investigated. Since the literature is relatively silent on how to assess recidivism in the speeding context, the secondary research aim was to contribute to the literature regarding ways to conceptualise and measure specific deterrence in the speeding context. We propose a novel way of operationalising four measures which reflect different ways in which a specific deterrence effect could be conceptualised: (1) the proportion of offenders who re-offended in the follow up period; (2) the overall frequency of re-offending in the follow up period; (3) the length of delay to re-offence among those who re-offended; and (4) the average number of re-offences during the follow up period among those who re-offended. Consistent with expectations, results suggested an absolute deterrent effect of penalty changes, as evidenced by significant reductions in the proportion of drivers who re-offended and the overall frequency of re-offending, although effect sizes were small. Contrary to expectations, however, there was no evidence of a marginal specific deterrent effect among those who re-offended, with a significant reduction in the length of time to re-offence and no significant change in the average number of offences committed. Additional exploratory analyses investigating potential influences of the severity of the index offence, offence history, and method of detection revealed mixed results. Access to additional data from various sources suggested that the main findings were not influenced by changes in speed enforcement activity, public awareness of penalty changes, or driving exposure during the study period. Study limitations and recommendations for future research are discussed with a view to promoting more extensive evaluations of penalty changes and better understanding of how such changes may impact on motorists’ perceptions of enforcement and sanctions, as well as on recidivist behaviour.
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Automatic speech recognition from multiple distant micro- phones poses significant challenges because of noise and reverberations. The quality of speech acquisition may vary between microphones because of movements of speakers and channel distortions. This paper proposes a channel selection approach for selecting reliable channels based on selection criterion operating in the short-term modulation spectrum domain. The proposed approach quantifies the relative strength of speech from each microphone and speech obtained from beamforming modulations. The new technique is compared experimentally in the real reverb conditions in terms of perceptual evaluation of speech quality (PESQ) measures and word error rate (WER). Overall improvement in recognition rate is observed using delay-sum and superdirective beamformers compared to the case when the channel is selected randomly using circular microphone arrays.
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The importance of developing effective disaster management strategies has significantly grown as the world continues to be confronted with unprecedented disastrous events. Factors such as climate instability, recent urbanization along with rapid population growth in many cities around the world have unwittingly exacerbated the risks of potential disasters, leaving a large number of people and infrastructure exposed to new forms of threats from natural disasters such as flooding, cyclones, and earthquakes. With disasters on the rise, effective recovery planning of the built environment is becoming imperative as it is not only closely related to the well-being and essential functioning of society, but it also requires significant financial commitment. In the built environment context, post-disaster reconstruction focuses essentially on the repair and reconstruction of physical infrastructures. The reconstruction and rehabilitation efforts are generally performed in the form of collaborative partnerships that involve multiple organisations, enabling the restoration of interdependencies that exist between infrastructure systems such as energy, water (including wastewater), transport, and telecommunication systems. These interdependencies are major determinants of vulnerabilities and risks encountered by critical infrastructures and therefore have significant implications for post-disaster recovery. When disrupted by natural disasters, such interdependencies have the potential to promote the propagation of failures between critical infrastructures at various levels, and thus can have dire consequences on reconstruction activities. This paper outlines the results of a pilot study on how elements of infrastructure interdependencies have the potential to impede the post-disaster recovery effort. Using a set of unstructured interview questionnaires, plausible arguments provided by seven respondents revealed that during post-disaster recovery, critical infrastructures are mutually dependent on each other’s uninterrupted availability, both physically and through a host of information and communication technologies. Major disruption to their physical and cyber interdependencies could lead to cascading failures, which could delay the recovery effort. Thus, the existing interrelationship between critical infrastructures requires that the entire interconnected network be considered when managing reconstruction activities during the post-disaster recovery period.
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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.
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The window of opportunity is a concept critical to rheumatoid arthritis treatment. Early treatment changes the outcome of rheumatoid arthritis treatment, in that response rates are higher with earlier disease-modifying anti-rheumatic drug treatment and damage is substantially reduced. Axial spondyloarthritis is an inflammatory axial disease encompassing both nonradiographic axial spondyloarthritis and established ankylosing spondylitis. In axial spondyloarthritis, studies of magnetic resonance imaging as well as tumor necrosis factor inhibitor treatment and withdrawal studies all suggest that early effective suppression of inflammation has the potential to reduce radiographic damage. This potential would suggest that the concept of a window of opportunity is relevant not only to rheumatoid arthritis but also to axial spondyloarthritis. The challenge now remains to identify high-risk patients early and to commence treatment without delay. Developments in risk stratification include new classification criteria, identification of clinical risk factors, biomarkers, genetic associations, potential antibody associations and an ankylosing spondylitis-specific microbiome signature. Further research needs to focus on the evidence for early intervention and the early identification of high-risk individuals.
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Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq™ (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using annovar. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq™ exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq™ capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity.
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Linewidth measurement of a femtosecond laser direct-written distributed feedback (DFB) waveguide laser (WGL) is reported. The WGL was fabricated in Yb-doped phosphate glass using the femtosecond laser direct-write technique. The linewidth was measured using a loss-compensated recirculating delayed self-heterodyne interferometer. By recirculating the output signal in a 10.2-km fiber delay loop, the linewidth was measured to be 35.4±1.4 kHz at a delay time of 306 μs , which is comparable with that of narrow-linewidth fiber DFB lasers.
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The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Autonomous vehicles are able to share information about the local traffic state in real time, which could result in a better reaction to the mechanism of traffic jam formation. An upstream single-hop radio broadcast network can improve the perception of each cooperative driver within a specific radio range and hence the traffic stability. The impact of vehicle to vehicle cooperation on the onset of traffic congestion is investigated analytically and through simulation. A next generation simulation field dataset is used to calibrate the full velocity difference car-following model, and the MOBIL lane-changing model is implemented. The robustness of the calibration as well as the heterogeneity of the drivers is discussed. Assuming that congestion can be triggered either by the heterogeneity of drivers' behaviours or abnormal lane-changing behaviours, the calibrated car-following model is used to assess the impact of a microscopic cooperative law on egoistic lane-changing behaviours. The cooperative law can help reduce and delay traffic congestion and can have a positive effect on safety indicators.
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Purpose To determine neuroretinal function with multifocal electroretinogram (mfERG) in diabetic subjects without retinopathy. Methods Multifocal electroretinogram (mfERG) was performed in 18 eyes of 18 diabetic subjects without retinopathy and 17 eyes of 17 age and gender-matched healthy control participants. Among 18 diabetic subjects, two had type 1 and 16 had type 2 diabetes. MfERG responses were averaged by the retinal areas of six concentric rings and four quadrants, and 103 retinal locations; N1–P1 amplitude and P1-implicit time were analysed. Results Average mfERG N1–P1 amplitude (in nv/deg2) of 103 retinal locations was 56.3 ± 17.2 (mean ± SD) in type 1 diabetic subjects, 47.2 ± 9.3 in type 2 diabetic subjects and 71.5 ± 12.7 in controls. Average P1-implicit time (in ms) was 43.0 ± 1.3 in type 1 diabetic subjects, 43.9 ± 2.3 in type 2 diabetic subjects and 41.9 ± 2.1 in controls. There was significant reduction in average N1–P1 amplitude and delay in P1-implicit time in type 2 diabetic subjects in comparison to controls. mfERG amplitude did not show any significant correlation with diabetes duration and blood sugar level. However, implicit time showed a positive correlation with diabetes duration in type 2 diabetic subjects with diabetes duration ≥5 years. Conclusions This is the first study in a Nepalese population with diabetes using multifocal electroretinography. We present novel findings that mfERG N1–P1 amplitude is markedly reduced along with delay in P1-implicit time in type 2 diabetic subjects without retinopathy. These findings indicate that there might be significant dysfunction of inner retina before the development of diabetic retinopathy in the study population, which have higher prevalence of diabetes than the global estimate and uncontrolled blood sugar level.
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In this paper, we propose a new load distribution strategy called `send-and-receive' for scheduling divisible loads, in a linear network of processors with communication delay. This strategy is designed to optimally utilize the network resources and thereby minimizes the processing time of entire processing load. A closed-form expression for optimal size of load fractions and processing time are derived when the processing load originates at processor located in boundary and interior of the network. A condition on processor and link speed is also derived to ensure that the processors are continuously engaged in load distributions. This paper also presents a parallel implementation of `digital watermarking problem' on a personal computer-based Pentium Linear Network (PLN) topology. Experiments are carried out to study the performance of the proposed strategy and results are compared with other strategies found in literature.
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The effect of the magnetic field on the unsteady flow over a stretching surface in a rotating fluid has been studied. The unsteadiness in the flow field is due to the time-dependent variation of the velocity of the stretching surface and the angular velocity of the rotating fluid. The Navier-Stokes equations and the energy equation governing the flow and the heat transfer admit a self-similar solution if the velocity of the stretching surface and the angular velocity of the rotating fluid vary inversely as a linear function of time. The resulting system of ordinary differential equations is solved numerically using a shooting method. The rotation parameter causes flow reversal in the component of the velocity parallel to the strerching surface and the magnetic field tends to prevent or delay the flow reversal. The surface shear stresses dong the stretching surface and in the rotating direction increase with the rotation parameter, but the surface heat transfer decreases. On the other hand, the magnetic field increases the surface shear stress along the stretching surface, but reduces the surface shear stress in the rotating direction and the surface heat transfer. The effect of the unsteady parameter is more pronounced on the velocity profiles in the rotating direction and temperature profiles.
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We apply the method of multiple scales (MMS) to a well known model of regenerative cutting vibrations in the large delay regime. By ``large'' we mean the delay is much larger than the time scale of typical cutting tool oscillations. The MMS upto second order for such systems has been developed recently, and is applied here to study tool dynamics in the large delay regime. The second order analysis is found to be much more accurate than first order analysis. Numerical integration of the MMS slow flow is much faster than for the original equation, yet shows excellent accuracy. The main advantage of the present analysis is that infinite dimensional dynamics is retained in the slow flow, while the more usual center manifold reduction gives a planar phase space. Lower-dimensional dynamical features, such as Hopf bifurcations and families of periodic solutions, are also captured by the MMS. Finally, the strong sensitivity of the dynamics to small changes in parameter values is seen clearly.
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The restructuring of the crop agriculture industry over the past two decades has enabled patent holders to exclude, prevent and deter others from using certain research tools and delay or block further follow-on inventions
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This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.