244 resultados para foot placement variability


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This work presents an extended Joint Factor Analysis model including explicit modelling of unwanted within-session variability. The goals of the proposed extended JFA model are to improve verification performance with short utterances by compensating for the effects of limited or imbalanced phonetic coverage, and to produce a flexible JFA model that is effective over a wide range of utterance lengths without adjusting model parameters such as retraining session subspaces. Experimental results on the 2006 NIST SRE corpus demonstrate the flexibility of the proposed model by providing competitive results over a wide range of utterance lengths without retraining and also yielding modest improvements in a number of conditions over current state-of-the-art.

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The purpose of this study was to verify within- and between-day repeatability and variability in children's oxygen uptake (VO^sub 2^), gross economy (GE; VO^sub 2^ divided by speed) and heart rate (HR) during treadmill walking based on self-selected speed (SS). Fourteen children (10.1 ± 1.4 years) undertook three testing sessions over 2 days in which four walking speeds, including SS were tested. Within- and between-day repeatability were assessed using the Bland and Altman method, and coefficients of variability (CV) were determined for each child across exercise bouts and averaged to obtain a mean group CV value for VO^sub 2^, GE, and HR per speed. Repeated measures analysis of variance showed no statistically significant differences in within- or between-day CV for VO^sub 2^, GE, or HR at any speed. Repeatability within- and between-day for VO^sub 2^, GE, and HR for all speeds was verified. These results suggest that submaximal VO^sub 2^ during treadmill walking is stable and reproducible at a range of speeds based on children's SS.

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This paper explores an innovative model for work-integrated learning using a virtual paradigm – The Virtual Law Placement Unit at Queensland University of Technology (QUT) Australia. It builds upon the conceptual model previously explored at WACE 2007 and provides an account of the lessons learned from the pilot offering of the unit which was conducted and evaluated in 2008. ----- The Virtual Placement Unit offers students the opportunity to complete an authentic workplace task under the guidance of a real-life workplace supervisor, where student-student communication and student-supervisor communication is all conducted virtually (and potentially asynchronously) to create an engaging but flexible learning environment using a combination of Blackboard and SharePoint technologies. This virtual experience is pioneering in the sense that it enables law students to access an unprecedented range of law graduate destination workplaces and projects, including international and social justice placements, absent the constraints traditionally associated with arranging physical placements. ----- All aspects of this unit have been designed in conjunction with community partners with a view to balancing student learning objectives with community needs through co-operative education. This paper will also explore how the implementation of the project is serving to strengthen those partnerships with the wider community, simultaneously addressing the community engagement agenda of the University and enabling students to engage meaningfully with local, national and international community partners in the real world of work.

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The roles of weather variability and sunspots in the occurrence of cyanobacteria blooms, were investigated using cyanobacteria cell data collected from the Fred Haigh Dam, Queensland, Australia. Time series generalized linear model and classification and regression (CART) model were used in the analysis. Data on notified cell numbers of cyanobacteria and weather variables over the periods 2001 and 2005 were provided by the Australian Department of Natural Resources and Water, and Australian Bureau of Meteorology, respectively. The results indicate that monthly minimum temperature (relative risk [RR]: 1.13, 95% confidence interval [CI]: 1.02-1.25) and rainfall (RR: 1.11; 95% CI: 1.03-1.20) had a positive association, but relative humidity (RR: 0.94; 95% CI: 0.91-0.98) and wind speed (RR:0.90; 95% CI: 0.82-0.98) were negatively associated with the cyanobacterial numbers, after adjustment for seasonality and auto-correlation. The CART model showed that the cyanobacteria numbers were best described by an interaction between minimum temperature, relative humidity, and sunspot numbers. When minimum temperature exceeded 18%C and relative humidity was under 66%, the number of cyanobacterial cells rose by 2.15-fold. We conclude that the weather variability and sunspot activity may affect cyanobacterial blooms in dams.

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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

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Specialised support for student nurses making the transition to graduate nurse can be crucial to successful and smooth adjustment, and can create a path to positive and stable career experiences. This paper describes an enhanced model of final year nursing student placements which was trialled in 2006 at the Queensland University of Technology. The model involved collaboration with two major urban health services and resources were developed to support effective transition experiences. Ninety-two students, including 29 trial participants and 63 non-trial participants were assessed on preparedness for professional practice, before and after the trial semester. Results indicated an increase in preparedness across the entire sample, but students participating in the trial did not differ significantly in overall preparedness change from those who did not participate. Higher baseline preparedness in the trial group highlighted the possibility that proactive students who choose enrichment experiences tend to be likelier to gain benefit from such options than those who do not. Qualitative findings from focus groups conducted with 12 transition group students highlighted that one of the main beneficial aspects of the experience for students was the sense of belonging to a team that understood their learning needs and could work constructively with them.

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Objective: To conduct an audit of elective foot and ankle surgery in Queensland public hospitals and to compare the frequency of these procedures performed to other states and territories of Australia. ---------- Methods: ICD-10-AM data was used to extract elective foot and ankle procedures from the Data Services Unit of Queensland Health, and the Australian Institute of Health and Welfare between the years of 2000 and 2004. ---------- Results During the 4-year audit period 3846 primary procedures were performed during the 4-year period with a complication rate of 2.2% during the hospital admission period. Mean length of stay was 1.7 days. Post-operative infection rates were 0.26%. With the exception of Tasmania and the Northern Territory, Queensland performs the least number of elective foot and ankle procedures per capita per year in Australia. ---------- Conclusions This is the first reported audit of elective foot and ankle surgery for Queensland public hospitals. Complication rates cannot be directly compared to the literature as this data could only capture complications within hospital admission period. Fewer elective foot and ankle procedures were performed in Queensland public hospitals compared to all other mainland states of Australia during the data collection period.

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Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

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Product placement is a fast growing multi-billion dollar industry yet measures of its effectiveness, which influence the critical area of pricing, have been problematic. Past attempts to measure the effect of a placement, and therefore provide a basis for pricing of placements, have been confounded by the effect on consumers of multiple prior exposures of a brand name in all marketing communications. Virtual product placement offers certain advantages: as a tool to measure the effectiveness of product placements; assistance with the problem of lack of audience selectivity in traditional product placement; testing different audiences for brands and addressing a gap in the existing academic literature by focusing on the impact of product placement on recall and recognition of new brands.

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Cloud computing has become a main medium for Software as a Service (SaaS) hosting as it can provide the scalability a SaaS requires. One of the challenges in hosting the SaaS is the placement process where the placement has to consider SaaS interactions between its components and SaaS interactions with its data components. A previous research has tackled this problem using a classical genetic algorithm (GA) approach. This paper proposes a cooperative coevolutionary algorithm (CCEA) approach. The CCEA has been implemented and evaluated and the result has shown that the CCEA has produced higher quality solutions compared to the GA.

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In this paper, a new method called the extended voltage phasors approach (EVPA) is proposed for placement of FACTS controllers in power systems. While the voltage phasors approach (VPA) identifies only the critical paths from the voltage stability viewpoint, the proposed method additionally locates the critical buses/line segments. The results of EVPA are compared with the well-established line flow index (LFI) method for nine-bus, 39-bus, and 68-bus systems. It is shown that the EVPA provides accurate indication for the placement of FACTS controllers.