154 resultados para Battery chargers


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Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

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This paper presents a summary of the key findings of the TTF TPACK Survey developed and administered for the Teaching the Teachers for the Future (TTF) Project implemented in 2011. The TTF Project, funded by an Australian Government ICT Innovation Fund grant, involved all 39 Australian Higher Education Institutions which provide initial teacher education. TTF data collections were undertaken at the end of Semester 1 (T1) and at the end of Semester 2 (T2) in 2011. A total of 12881 participants completed the first survey (T1) and 5809 participants completed the second survey (T2). Groups of like-named items from the T1 survey were subject to a battery of complementary data analysis techniques. The psychometric properties of the four scales: Confidence - teacher items; Usefulness - teacher items; Confidence - student items; Usefulness- student items, were confirmed both at T1 and T2. Among the key findings summarised, at the national level, the scale: Confidence to use ICT as a teacher showed measurable growth across the whole scale from T1 to T2, and the scale: Confidence to facilitate student use of ICT also showed measurable growth across the whole scale from T1 to T2. Additional key TTF TPACK Survey findings are summarised.

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PURPOSE: To examine the basis of previous findings of an association between indices of driving safety and visual motion sensitivity and to examine whether this association could be explained by low-level changes in visual function. METHODS: 36 visually normal participants (aged 19 – 80 years), completed a battery of standard vision tests including visual acuity, contrast sensitivity and automated visual fields. and two tests of motion perception including sensitivity for movement of a drifting Gabor stimulus, and sensitivity for displacement in a random-dot kinematogram (Dmin). Participants also completed a hazard perception test (HPT) which measured participants’ response times to hazards embedded in video recordings of real world driving which has been shown to be linked to crash risk. RESULTS: Dmin for the random-dot stimulus ranged from -0.88 to -0.12 log minutes of arc, and the minimum drift rate for the Gabor stimulus ranged from 0.01 to 0.35 cycles per second. Both measures of motion sensitivity significantly predicted response times on the HPT. In addition, while the relationship involving the HPT and motion sensitivity for the random-dot kinematogram was partially explained by the other visual function measures, the relationship with sensitivity for detection of the drifting Gabor stimulus remained significant even after controlling for these variables. CONCLUSION: These findings suggest that motion perception plays an important role in the visual perception of driving-relevant hazards independent of other areas of visual function and should be further explored as a predictive test of driving safety. Future research should explore the causes of reduced motion perception in order to develop better interventions to improve road safety.

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A number of tests and test batteries are available for the prediction of older driver safety, but many of these have not been validated against standardized driving outcome measures. The aim of this study was to evaluate a series of previously described screening tests in terms of their ability to predict the potential for safe and unsafe driving. Participants included 79 community-dwelling older drivers (M=72.16 years, SD=5.46; range 65-88 years; 57 males and 22 females) who completed a previously validated multi-disciplinary driving assessment, a hazard perception test, a hazard change detection test and a battery of vision and cognitive tests. Participants also completed a standardized on-road driving assessment. The multi-disciplinary test battery had the highest predictive ability with a sensitivity of 80% and a specificity of 73%, followed by the hazard perception test which demonstrated a sensitivity of 75% and a specificity of 61%. These findings suggest that a relatively simple and practical battery of tests from a range of domains has the capacity to predict safe and unsafe driving in older adults.

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The Multidimensional Loss Scale: Initial Development and Psychometric Evaluation The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to measure loss in refugee populations. Researchers developed initial items of the Multidimensional Loss Scale to assess Experience of Loss Events and Loss Distress in a culturally sensitive manner across multiple domains (social, material, intra-personal and cultural). A sample of 70 recently settled Burmese adult refugees completed a battery of questionnaires, including new scale items. Analyses explored the scale’s factor structure, internal consistency, convergent validity and divergent validity. Principal Axis Factoring supported a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Chronbach’s Alphas indicated satisfactory internal consistency for Experience of Loss Events (.85) and Loss Distress (.92). Convergent and divergent validity of Loss Distress were supported by moderate correlations with interpersonal grief and trauma symptoms and weak correlations with depression and anxiety. The new scale was well received by people from refugee backgrounds and shows promise for application in future research and practice

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Brief self-report symptom checklists are often used to screen for postconcussional disorder (PCD) and posttraumatic stress disorder (PTSD) and are highly susceptible to symptom exaggeration. This study examined the utility of the five-item Mild Brain Injury Atypical Symptoms Scale (mBIAS) designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist–Civilian (PCL–C). Participants were 85 Australian undergraduate students who completed a battery of self-report measures under one of three experimental conditions: control (i.e., honest responding, n = 24), feign PCD (n = 29), and feign PTSD (n = 32). Measures were the mBIAS, NSI, PCL–C, Minnesota Multiphasic Personality Inventory–2, Restructured Form (MMPI–2–RF), and the Structured Inventory of Malingered Symptomatology (SIMS). Participants instructed to feign PTSD and PCD had significantly higher scores on the mBIAS, NSI, PCL–C, and MMPI–2–RF than did controls. Few differences were found between the feign PCD and feign PTSD groups, with the exception of scores on the NSI (feign PCD > feign PTSD) and PCL–C (feign PTSD > feign PCD). Optimal cutoff scores on the mBIAS of ≥8 and ≥6 were found to reflect “probable exaggeration” (sensitivity = .34; specificity = 1.0; positive predictive power, PPP = 1.0; negative predictive power, NPP = .74) and “possible exaggeration” (sensitivity = .72; specificity = .88; PPP = .76; NPP = .85), respectively. Findings provide preliminary support for the use of the mBIAS as a tool to detect symptom exaggeration when administering the NSI and PCL–C.

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GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behaviour through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.

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This paper describes an analysis of construction project bids to determine (a) the global distribution and (b) factors influencing the distribution of bids. The global distribution of bids was found, by using a battery of ll test statistics, to be approximated by a three-parameter log normal distribution. No global spread parameter was found. A multivariate analysis revealed the year of tender to be the major influencing factor. Consideration of the construction order, tender price and output indices lead to the conclusion that distributional spread reflected the degree of difference in pricing policies between bidders and the skewness of the distributions reflected the degree of competition. The paper concludes with a tentative model of the causal relationships between the factors and distributional characteristics involved.

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LiFePO4 is a commercially available battery material with good theoretical discharge capacity, excellent cycle life and increased safety compared with competing Li-ion chemistries. It has been the focus of considerable experimental and theoretical scrutiny in the past decade, resulting in LiFePO4 cathodes that perform well at high discharge rates. This scrutiny has raised several questions about the behaviour of LiFePO4 material during charge and discharge. In contrast to many other battery chemistries that intercalate homogeneously, LiFePO4 can phase-separate into highly and lowly lithiated phases, with intercalation proceeding by advancing an interface between these two phases. The main objective of this thesis is to construct mathematical models of LiFePO4 cathodes that can be validated against experimental discharge curves. This is in an attempt to understand some of the multi-scale dynamics of LiFePO4 cathodes that can be difficult to determine experimentally. The first section of this thesis constructs a three-scale mathematical model of LiFePO4 cathodes that uses a simple Stefan problem (which has been used previously in the literature) to describe the assumed phase-change. LiFePO4 crystals have been observed agglomerating in cathodes to form a porous collection of crystals and this morphology motivates the use of three size-scales in the model. The multi-scale model developed validates well against experimental data and this validated model is then used to examine the role of manufacturing parameters (including the agglomerate radius) on battery performance. The remainder of the thesis is concerned with investigating phase-field models as a replacement for the aforementioned Stefan problem. Phase-field models have recently been used in LiFePO4 and are a far more accurate representation of experimentally observed crystal-scale behaviour. They are based around the Cahn-Hilliard-reaction (CHR) IBVP, a fourth-order PDE with electrochemical (flux) boundary conditions that is very stiff and possesses multiple time and space scales. Numerical solutions to the CHR IBVP can be difficult to compute and hence a least-squares based Finite Volume Method (FVM) is developed for discretising both the full CHR IBVP and the more traditional Cahn-Hilliard IBVP. Phase-field models are subject to two main physicality constraints and the numerical scheme presented performs well under these constraints. This least-squares based FVM is then used to simulate the discharge of individual crystals of LiFePO4 in two dimensions. This discharge is subject to isotropic Li+ diffusion, based on experimental evidence that suggests the normally orthotropic transport of Li+ in LiFePO4 may become more isotropic in the presence of lattice defects. Numerical investigation shows that two-dimensional Li+ transport results in crystals that phase-separate, even at very high discharge rates. This is very different from results shown in the literature, where phase-separation in LiFePO4 crystals is suppressed during discharge with orthotropic Li+ transport. Finally, the three-scale cathodic model used at the beginning of the thesis is modified to simulate modern, high-rate LiFePO4 cathodes. High-rate cathodes typically do not contain (large) agglomerates and therefore a two-scale model is developed. The Stefan problem used previously is also replaced with the phase-field models examined in earlier chapters. The results from this model are then compared with experimental data and fit poorly, though a significant parameter regime could not be investigated numerically. Many-particle effects however, are evident in the simulated discharges, which match the conclusions of recent literature. These effects result in crystals that are subject to local currents very different from the discharge rate applied to the cathode, which impacts the phase-separating behaviour of the crystals and raises questions about the validity of using cathodic-scale experimental measurements in order to determine crystal-scale behaviour.

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The success or effectiveness for any aircraft design is a function of many trade-offs. Over the last 100 years of aircraft design these trade-offs have been optimized and dominant aircraft design philosophies have emerged. Pilotless aircraft (or uninhabited airborne systems, UAS) present new challenges in the optimization of their configuration. Recent developments in battery and motor technology have seen an upsurge in the utility and performance of electric powered aircraft. Thus, the opportunity to explore hybrid-electric aircraft powerplant configurations is compelling. This thesis considers the design of such a configuration from an overall propulsive, and energy efficiency perspective. A prototype system was constructed using a representative small UAS internal combustion engine (10cc methanol two-stroke) and a 600W brushless Direct current (BLDC) motor. These components were chosen to be representative of those that would be found on typical small UAS. The system was tested on a dynamometer in a wind-tunnel and the results show an improvement in overall propulsive efficiency of 17% when compared to a non-hybrid powerplant. In this case, the improvement results from the utilization of a larger propeller that the hybrid solution allows, which shows that general efficiency improvements are possible using hybrid configurations for aircraft propulsion. Additionally this approach provides new improvements in operational and mission flexibility (such as the provision of self-starting) which are outlined in the thesis. Specifically, the opportunity to use the windmilling propeller for energy regeneration was explored. It was found (in the prototype configuration) that significant power (60W) is recoverable in a steep dive, and although the efficiency of regeneration is low, the capability can allow several options for improved mission viability. The thesis concludes with the general statement that a hybrid powerplant improves the overall mission effectiveness and propulsive efficiency of small UAS.

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Class E Resonant Inverters are theoretically capable of delivering any power to a load and achieve 100% efficiency at any frequency of operation. In practice efficiency in the “high 90's” can be achieved into megahertz frequencies regardless of inverter output powers. The topology also allows the manipulation of output power through sub-optimal operation, with a negligible efficiency penalty. The 24W inverter discussed in this paper was specifically designed to harness the benefits, and discuss the shortcomings, of the Class E topology for use in the growing market for portable, battery powered lighting. It exhibits a peak recorded power efficiently of over 98%, and a conservatively measured efficiency of 95% across a range of dimming settings.

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PURPOSE We wanted to assess the effectiveness of a home-based physical activity program, the Depression in Late Life Intervention Trial of Exercise (DeLLITE), in improving function, quality of life, and mood in older people with depressive symptoms. METHODS We undertook a randomized controlled trial involving 193 people aged 75 years and older with depressive symptoms at enrollment who were recruited from primary health care practices in Auckland, New Zealand. Participants received either an individualized physical activity program or social visits to control for the contact time of the activity intervention delivered over 6 months. Primary outcome measures were function, a short physical performance battery comprising balance and mobility, and the Nottingham Extended Activities of Daily Living scale. Secondary outcome measures were quality of life, the Medical Outcomes Study 36-item short form, mood, Geriatric Depression Scale (GDS-15), physical activity, Auckland Heart Study Physical Activity Questionnaire, and self-report of falls. Repeated measures analyses tested the differential impact on outcomes over 12 months’ follow-up. RESULTS The mean age of the participants was 81 years, and 59% were women. All participants scored in the at–risk category on the depression screen, 53% had a Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases, Tenth Revision diagnosis of major depression or scored more than 4 on the GDS-15 at baseline, indicating moderate or severe depression. Almost all participants, 187 (97%), completed the trial. Overall there were no differences in the impact of the 2 interventions on outcomes. Mood and mental health related quality of life improved for both groups. CONCLUSION he DeLLITE activity program improved mood and quality of life for older people with depressive symptoms as much as the effect of social visits. Future social and activity interventions should be tested against a true usual care control.

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Energy policy is driving renewable energy deployment with most of the developed countries having some form of renewable energy portfolio standard and emissions reduction target. To deliver upon these ambitious targets, those renewable energy technologies that are commercially available, such as wind and solar, are being deployed, but inherently have issues with intermittency of supply. To overcome these issues, storage options will need to be introduced into the distribution network with benefits for both demand management and power systems quality. How this can be utilised most effectively within the distribution network will allow for an even greater proportion of our energy demand to be met through renewable resources and meet the aspirational targets set. The distribution network will become a network of smart-grids, but to work efficiently and effectively, power quality issues surrounding intermittency must be overcome, with storage being a major factor in this solution.

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This paper presents two efficiency models for the regenerative dynamometer to be built at the University of Queensland. The models incorporate an accurate accounting of the losses associated with the regenerative dynamometer and the battery modelling technique used. In addition to the models the cycle and instantaneous efficiencies were defined for a regenerative system that requires a desired torque output. The simulation of the models allowed the instantaneous and cycle efficiencies to be examined. The results show the intended dynamometer machine has significant efficiency draw backs but incorporating field winding control, the efficiency can be improved.

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The University of Queensland UltraCommuter project is the demonstration of an ultra-light weight, low drag, energy efficient and low polluting, electric commuter vehicle equipped with a 2.5m2 on-board solar array. A key goal of the project is to make the vehicle predominantly self-sufficient from solar power for normal driving purposes , so that it does not require charging or refuelling from off-board sources. This paper examines the technical feasibility of the solar-powered commuter vehicle concept, as it applies the UltraCommuter project. A parametric description of a solar-powered commuter vehicle is presented. Real solar insolation data is then used to predict the solar driving range for the UltraCommuter and this is compared to typical urban usage patterns for commuter vehicles in Queensland. A comparative analysis of annual greenhouse gas emissions from the vehicle is also presented. The results show that the UltraCommuter’s on-board solar array can provide substantial supplementation of the energy required for normal driving, powering 90% of annual travel needs for an average QLD passenger vehicle. The vehicle also has excellent potential to reduce annual greenhouse gas emissions from the private transport sector, achieving a 98% reduction in CO2 emissions when compared to the average QLD passenger vehicle. Lastly, the vehicle battery pack provides for tolerance to consecutive days of poor weather without resorting to grid charging, giving uninterrupted functionality to the user. These results hold great promise for the technical feasibility of the solar-powered commuter vehicle concept.