209 resultados para Shortest Path Length


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In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

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BACKGROUND: A long length of stay (LOS) in the emergency department (ED) associated with overcrowding has been found to adversely affect the quality of ED care. The objective of this study is to determine whether patients who speak a language other than English at home have a longer LOS in EDs compared to those whose speak only English at home. METHODS: A secondary data analysis of a Queensland state-wide hospital EDs dataset (Emergency Department Information System) was conducted for the period, 1 January 2008 to 31 December 2010. RESULTS: The interpreter requirement was the highest among Vietnamese speakers (23.1%) followed by Chinese (19.8%) and Arabic speakers (18.7%). There were significant differences in the distributions of the departure statuses among the language groups (Chi-squared=3236.88, P<0.001). Compared with English speakers, the Beta coeffi cient for the LOS in the EDs measured in minutes was among Vietnamese, 26.3 (95%CI: 22.1–30.5); Arabic, 10.3 (95%CI: 7.3–13.2); Spanish, 9.4 (95%CI: 7.1–11.7); Chinese, 8.6 (95%CI: 2.6–14.6); Hindi, 4.0 (95%CI: 2.2–5.7); Italian, 3.5 (95%CI: 1.6–5.4); and German, 2.7 (95%CI: 1.0–4.4). The fi nal regression model explained 17% of the variability in LOS. CONCLUSION: There is a close relationship between the language spoken at home and the LOS at EDs, indicating that language could be an important predictor of prolonged LOS in EDs and improving language services might reduce LOS and ease overcrowding in EDs in Queensland's public hospitals.

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This paper is concerned with the optimal path planning and initialization interval of one or two UAVs in presence of a constant wind. The method compares previous literature results on synchronization of UAVs along convex curves, path planning and sampling in 2D and extends it to 3D. This method can be applied to observe gas/particle emissions inside a control volume during sampling loops. The flight pattern is composed of two phases: a start-up interval and a sampling interval which is represented by a semi-circular path. The methods were tested in four complex model test cases in 2D and 3D as well as one simulated real world scenario in 2D and one in 3D.

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The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

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Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

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An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

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This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.

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Dear Editor We thank Dr Klek for his interest in our article and giving us the opportunity to clarify our study and share our thoughts. Our study looks at the prevalence of malnutrition in an acute tertiary hospital and tracked the outcomes prospectively.1 There are a number of reasons why we chose Subjective Global Assessment (SGA) to determine the nutritional status of patients. Firstly, we took the view that nutrition assessment tools should be used to determine nutrition status and diagnose presence and severity of malnutrition; whereas the purpose of nutrition screening tools are to identify individuals who are at risk of malnutrition. Nutritional assessment rather than screening should be used as the basis for planning and evaluating nutrition interventions for those diagnosed with malnutrition. Secondly, Subjective Global Assessment (SGA) has been well accepted and validated as an assessment tool to diagnose the presence and severity of malnutrition in clinical practice.2, 3 It has been used in many studies as a valid prognostic indicator of a range of nutritional and clinical outcomes.4, 5, 6 On the other hand, Malnutrition Universal Screening Tool (MUST)7 and Nutrition Risk Screening 2002 (NRS 2002)8 have been established as screening rather than assessment tools.

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It is well known that a broad range of ocular anatomical and physiological parameters undergo significant diurnal variation. However, the natural diurnal variations that occur in the length of the human eye (axial length) and their underlying causes have been less well studied. Improvements in optical methods for the measurement of ocular biometrics now allow more precise and comprehensive measurements of axial length to be performed than has previously been possible. Research from animal models also suggests a link between diurnal axial length variations and longer term myopic eye growth, and that retinal image defocus can disrupt these diurnal rhythms in axial length. This research programme has examined the diurnal variations in axial length in young normal eyes, the contributing components and the influence of optical stimuli on these changes. In the first experiment, the normal pattern and consistency of the diurnal variations in axial length were examined at 10 different times (5 measurements each day, at ~ 3-hour intervals from ~ 9 am to ~ 9 pm) over 2 consecutive days on 30 young adult subjects (15 myopes, 15 emmetropes). Additionally, variations in a range of other ocular biometric measurements such as choroidal thickness, intraocular pressure, and other ocular biometrics were also explored as potential factors that may be associated with the observed variations in axial length. To investigate the potential influence of refractive error on diurnal axial length variations, the differences in the magnitude and pattern of diurnal variations in axial length between the myopic and emmetropic subjects were examined. Axial length underwent significant diurnal variation that was consistently observed over the 2 consecutive days of measurements, with the longest axial length typically occurring during the day, and the shortest at night. Significant diurnal variations were also observed in choroidal thickness, IOP and other ocular biometrics (such as central corneal thickness, anterior chamber depth and vitreous chamber depth) of the eye. Diurnal variations in vitreous chamber depth, IOP (positive associations) and choroidal thickness (negative association) were all significantly correlated with the diurnal changes in axial length. Choroidal thickness was found to fluctuate approximately in antiphase to the axial length changes, with the average timing of the longest axial length coinciding with the thinnest choroid and vice versa. There were no significant differences in the ocular diurnal variations associated with refractive error. Given that the diurnal changes in axial length could be associated with the changes in the eye’s optical quality, whether the optical quality of the eye also undergoes diurnal variation in the same cohort of young adult myopes and emmetropes over 2 consecutive days was also examined. Significant diurnal variations were observed only in the best sphere refraction (power vector M) and in the spherical aberration of the eye over two consecutive days of testing. The changes in the eyes lower and higher order ocular optics were not significantly associated with the diurnal variations in axial length and the other measured ocular biometric parameters. No significant differences were observed in the magnitude and timing of diurnal variations in lower-order and higher-order optics associated with refractive error. Since the small natural fluctuations in the eye’s optical quality did not appear to be sufficient to influence the natural diurnal fluctuations in ocular biometric parameters, in the next experiment, the influence of monocular myopic defocus (+1.50 DS) upon the normal diurnal variations in axial length and choroidal thickness of young adult emmetropic human subjects (n=13) imposed over a 12 hour period was examined. A series of axial length and choroidal thickness measurements (collected at ~3 hourly intervals, with the first measurement at ~9 am and the final measurement at ~9 pm) were obtained over three consecutive days. The natural diurnal rhythms (Day 1, no defocus), diurnal rhythms with monocular myopic defocus (Day 2, +1.50 DS spectacle lens over the right eye), and the recovery from any defocus induced changes (Day 3, no defocus) were examined. Significant diurnal variations over the course of the day were observed in both axial length and choroidal thickness on each of the three measurement days. The introduction of monocular myopic defocus led to significant reductions in the mean amplitude of diurnal change, and phase shifts in the peak timing of the diurnal rhythms in axial length and choroidal thickness. These defocus induced changes were found to be transient in nature and returned to normal the day following removal of the defocus. To further investigate the influence of optical stimuli on human diurnal rhythms, in the final experiment, the influence of monocular hyperopic defocus on the normal diurnal rhythms in axial length and choroidal thickness was examined in young adult emmetropic subjects (n=15). Similar to the previous experiment, the natural diurnal rhythms (Day 1, no defocus), diurnal rhythms with monocular hyperopic defocus (Day 2, -2.00 DS spectacle lens over the right eye), and the recovery from any defocus induced changes (Day 3, no defocus) were examined over three consecutive days. Both axial length and choroidal thickness underwent significant diurnal variations on each of the three days. The introduction of monocular hyperopic defocus resulted in a significant increase in the amplitude of diurnal change, but no change in the peak timing of diurnal rhythms in both parameters. The ocular changes associated with hyperopic defocus returned to normal, the day following removal of the defocus. This research has shown that axial length undergoes significant diurnal variation in young adult human eyes, and has shown that the natural diurnal variations in choroidal thickness and IOP are significantly associated, and may underlie these diurnal fluctuations in axial length. This work also demonstrated for the first time that exposing young human eyes to monocular myopic and hyperopic defocus leads to a significant disruption in the normal diurnal rhythms of axial length and choroidal thickness. These changes in axial length with defocus may reflect underlying mechanisms in the human eye that are involved in the regulation of longer term eye growth.

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We predict here from first-principle calculations that finite-length (n,0) single walled carbon nanotubes (SWCNTs) with H-termination at the open ends displaying antiferromagnetic coupling when n is greater than 6. An opposite local gating effect of the spin states, i.e., half metallicity, is found under the influence of an external electric field along the direction of tube axis. Remarkably, boron doping of unpassivated SWCNTs at both zigzag edges is found to favor a ferromagnetic ground state, with the B-doped tubes displaying half-metallic behavior even in the absence of an electric field. Aside of the intrinsic interest of these results, an important avenue for development of CNT-based spintronic is suggested.

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This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal.

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Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

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The paper attempts to project the future trend of the gender wage gap in Australia up to 2031. The empirical analysis utilises the Income Distribution Survey (1996) together with Australian Bureau of Statistics (ABS) demographic projections. The methodology combines the ABS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. The analysis suggests that female relative pay will continue to rise up to 2031. However, gender wage convergence will be relatively slow, with a substantial gap remaining in 2031.

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Purpose – The paper attempts to project the future trend of the gender wage gap in Great Britain up to 2031. Design/methodology/approach – The empirical analysis utilises the British Household Panel Study Wave F together with Office for National Statistics (ONS) demographic projections. The methodology combines the ONS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. Findings – The analysis suggests that gender wage convergence will be slow, with little female progress by 2031 unless there is a large rise in returns to female experience. Originality/value – The paper has projected the pattern of male and female skill acquisition together with the associated trend in wages up to 2031.

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Objective To evaluate relative telomere length of female migraine patients. Background Migraine is a debilitating disorder affecting 6-28% of the population. Studies on the mechanisms of migraine have demonstrated genetic causes but the pathophysiology and subcellular effects of the disease remain poorly understood. Shortened telomere length is associated with age-related or chronic diseases, and induced stresses. Migraine attacks may impart significant stress on cellular function, thus this study investigates a correlation between shortening of telomeres and migraine. Methods Relative telomere length was measured using a previously described quantitative polymerase chain reaction method. A regression analysis was performed to assess differences in mean relative telomere length between migraine patients and healthy controls. Results The leukocyte telomeres of a cohort of 142 Caucasian female migraine subjects aged 18-77 years and 143 matched 17-77-year-old healthy control Caucasian women were examined.A significantly shorter relative telomere length was observed in the migraine group compared with the control group after adjusting for age and body mass index (P = .001). In addition, age of onset was observed to associate with the loss of relative telomere length, especially at early age of onset (<17 years old). No association was observed between relative telomere length and the severity and frequency of migraine attacks and the duration of migraine. Conclusion Telomeres are shorter in migraine patients and there is more variation in telomere length in migraine patients.