535 resultados para pretest probability
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The available wind power is stochastic and requires appropriate tools in the OPF model for economic and reliable power system operation. This paper exhibit the OPF formulation with factors involved in the intermittency of wind power. Weibull distribution is adopted to find the stochastic wind speed and power distribution. The reserve requirement is evaluated based on the wind distribution and risk of under/over estimation of the wind power. In addition, the Wind Energy Conversion System (WECS) is represented by Doubly Fed Induction Generator (DFIG) based wind farms. The reactive power capability for DFIG based wind farm is also analyzed. The study is performed on IEEE-30 bus system with wind farm located at different buses and with different wind profiles. Also the reactive power capacity to be installed in the wind farm to maintain a satisfactory voltage profile under the various wind flow scenario is demonstrated.
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In the course of history, a large number of politicians have been assassinated. To investigate this phenomenon, rational choice hypotheses are developed and tested using a large data set covering close to 100 countries over a period of 20 years. Several strategies, in addition to security measures, are shown to significantly reduce the probability of politicians being attacked or killed: extended institutional and governance quality, democracy, voice and accountability, a well-functioning system of law and order, decentralization via the division of power and federalism, larger cabinet size and a stronger civil society. There is also support for a contagion effect.
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With the advent of large-scale wind farms and their integration into electrical grids, more uncertainties, constraints and objectives must be considered in power system development. It is therefore necessary to introduce risk-control strategies into the planning of transmission systems connected with wind power generators. This paper presents a probability-based multi-objective model equipped with three risk-control strategies. The model is developed to evaluate and enhance the ability of the transmission system to protect against overload risks when wind power is integrated into the power system. The model involves: (i) defining the uncertainties associated with wind power generators with probability measures and calculating the probabilistic power flow with the combined use of cumulants and Gram-Charlier series; (ii) developing three risk-control strategies by specifying the smallest acceptable non-overload probability for each branch and the whole system, and specifying the non-overload margin for all branches in the whole system; (iii) formulating an overload risk index based on the non-overload probability and the non-overload margin defined; and (iv) developing a multi-objective transmission system expansion planning (TSEP) model with the objective functions composed of transmission investment and the overload risk index. The presented work represents a superior risk-control model for TSEP in terms of security, reliability and economy. The transmission expansion planning model with the three risk-control strategies demonstrates its feasibility in the case study using two typical power systems
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High Dynamic Range (HDR) imaging was used to collect luminance information at workstations in 2 open-plan office buildings in Queensland, Australia: one lit by skylights, vertical windows and electric light, and another by skylights and electric light. This paper compares illuminance and luminance data collected in these offices with occupant feedback to evaluate these open-plan environments based on available and emerging metrics for visual comfort and glare. This study highlights issues of daylighting quality and measurement specific to open plan spaces. The results demonstrate that overhead glare is a serious threat to user acceptance of skylights, and that electric and daylight integration and controls have a major impact on the perception of daylighting quality. With regards to measurement of visual comfort it was found that the Daylight Glare Probability (DGP) gave poor agreement with occupant reports of discomfort glare in open-plan spaces with skylights, and the CIE Glare Index (CGI) gave the best agreement. Horizontal and vertical illuminances gave no indication of visual comfort in these spaces.
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Glare indices have yet to be extensively tested in daylit open plan offices, as such there is no effective method to predict discomfort glare within these spaces. This study into discomfort glare in open plan green buildings targeted full-time employees, working under their everyday lighting conditions. Three green buildings in Brisbane were used for data collection, two were Green Star accredited and the other contained innovative daylighting strategies. Data were collected on full-time employees, mostly aged between 30 and 50 years, who broadly reflect the demographics of the wider working population in Australia. It was discovered 36 of the 64 respondents experienced discomfort from both electric and daylight sources at their workspace. The study used a specially tailored post-occupancy evaluation (POE) survey to help assess discomfort glare. Luminance maps extracted from High Dynamic Range (HDR) images were used to capture the luminous environment of the occupants. These were analysed using participant data and the program Evalglare. The physical results indicated no correlation with other developed glare metrics for daylight within these open plan green buildings, including the recently developed Daylight Glare Probability (DGP) Index. The strong influence of vertical illuminance, Ev in the DGP precludes the mostly contrast-based glare from windows observed in this investigation from forming a significant part of this index. Furthermore, critical assessment of the survey techniques used are considered. These will provide insight for further research into discomfort glare in the endeavour to fully develop a suitable glare metric.
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Traditional shading design principles guide the vertical and horizontal orientation of fins, louvres and awnings being applied to orthogonal planar façades. Due to doubly curved envelopes characterising many contemporary designs, these rules of thumb are now not always applicable. Operable blinds attempt to regulate the fluctuating luminance of daylight and aid in shading direct sunlight. Mostly they remain closed, as workers are commonly too preoccupied to continually adjust them so a reliance on electrically powered lights remains a preference. To remedy these problems, the idea of what it is to sustainable enclose space is reconsidered through the geometric and kinetic optimisation of a parametric skin, with sunlight responsive modules that regulate interior light levels. This research concludes with an optimised design and also defines some unique metrics to gauge the design’s performance in terms of, the amount of exterior unobstructed view, its ability to shade direct sunlight and, its daylight glare probability.
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Background Total hip arthroplasty (THA) is a commonly performed procedure and numbers are increasing with ageing populations. One of the most serious complications in THA are surgical site infections (SSIs), caused by pathogens entering the wound during the procedure. SSIs are associated with a substantial burden for health services, increased mortality and reduced functional outcomes in patients. Numerous approaches to preventing these infections exist but there is no gold standard in practice and the cost-effectiveness of alternate strategies is largely unknown. Objectives The aim of this project was to evaluate the cost-effectiveness of strategies claiming to reduce deep surgical site infections following total hip arthroplasty in Australia. The objectives were: 1. Identification of competing strategies or combinations of strategies that are clinically relevant to the control of SSI related to hip arthroplasty 2. Evidence synthesis and pooling of results to assess the volume and quality of evidence claiming to reduce the risk of SSI following total hip arthroplasty 3. Construction of an economic decision model incorporating cost and health outcomes for each of the identified strategies 4. Quantification of the effect of uncertainty in the model 5. Assessment of the value of perfect information among model parameters to inform future data collection Methods The literature relating to SSI in THA was reviewed, in particular to establish definitions of these concepts, understand mechanisms of aetiology and microbiology, risk factors, diagnosis and consequences as well as to give an overview of existing infection prevention measures. Published economic evaluations on this topic were also reviewed and limitations for Australian decision-makers identified. A Markov state-transition model was developed for the Australian context and subsequently validated by clinicians. The model was designed to capture key events related to deep SSI occurring within the first 12 months following primary THA. Relevant infection prevention measures were selected by reviewing clinical guideline recommendations combined with expert elicitation. Strategies selected for evaluation were the routine use of pre-operative antibiotic prophylaxis (AP) versus no use of antibiotic prophylaxis (No AP) or in combination with antibiotic-impregnated cement (AP & ABC) or laminar air operating rooms (AP & LOR). The best available evidence for clinical effect size and utility parameters was harvested from the medical literature using reproducible methods. Queensland hospital data were extracted to inform patients’ transitions between model health states and related costs captured in assigned treatment codes. Costs related to infection prevention were derived from reliable hospital records and expert opinion. Uncertainty of model input parameters was explored in probabilistic sensitivity analyses and scenario analyses and the value of perfect information was estimated. Results The cost-effectiveness analysis was performed from a health services perspective using a hypothetical cohort of 30,000 THA patients aged 65 years. The baseline rate of deep SSI was 0.96% within one year of a primary THA. The routine use of antibiotic prophylaxis (AP) was highly cost-effective and resulted in cost savings of over $1.6m whilst generating an extra 163 QALYs (without consideration of uncertainty). Deterministic and probabilistic analysis (considering uncertainty) identified antibiotic prophylaxis combined with antibiotic-impregnated cement (AP & ABC) to be the most cost-effective strategy. Using AP & ABC generated the highest net monetary benefit (NMB) and an incremental $3.1m NMB compared to only using antibiotic prophylaxis. There was a very low error probability that this strategy might not have the largest NMB (<5%). Not using antibiotic prophylaxis (No AP) or using both antibiotic prophylaxis combined with laminar air operating rooms (AP & LOR) resulted in worse health outcomes and higher costs. Sensitivity analyses showed that the model was sensitive to the initial cohort starting age and the additional costs of ABC but the best strategy did not change, even for extreme values. The cost-effectiveness improved for a higher proportion of cemented primary THAs and higher baseline rates of deep SSI. The value of perfect information indicated that no additional research is required to support the model conclusions. Conclusions Preventing deep SSI with antibiotic prophylaxis and antibiotic-impregnated cement has shown to improve health outcomes among hospitalised patients, save lives and enhance resource allocation. By implementing a more beneficial infection control strategy, scarce health care resources can be used more efficiently to the benefit of all members of society. The results of this project provide Australian policy makers with key information about how to efficiently manage risks of infection in THA.
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The standard approach to tax compliance applies the economics-of-crime methodology pioneered by Becker (1968): in its first application, due to Allingham and Sandmo (1972) it models the behaviour of agents as a decision involving a choice of the extent of their income to report to tax authorities, given a certain institutional environment, represented by parameters such as the probability of detection and penalties in the event the agent is caught. While this basic framework yields important insights on tax compliance behavior, it has some critical limitations. Specifically, it indicates a level of compliance that is significantly below what is observed in the data. This thesis revisits the original framework with a view towards addressing this issue, and examining the political economy implications of tax evasion for progressivity in the tax structure. The approach followed involves building a macroeconomic, dynamic equilibrium model for the purpose of examining these issues, by using a step-wise model building procedure starting with some very simple variations of the basic Allingham and Sandmo construct, which are eventually integrated to a dynamic general equilibrium overlapping generations framework with heterogeneous agents. One of the variations involves incorporating the Allingham and Sandmo construct into a two-period model of a small open economy of the type originally attributed to Fisher (1930). A further variation of this simple construct involves allowing agents to initially decide whether to evade taxes or not. In the event they decide to evade, the agents then have to decide the extent of income or wealth they wish to under-report. We find that the ‘evade or not’ assumption has strikingly different and more realistic implications for the extent of evasion, and demonstrate that it is a more appropriate modeling strategy in the context of macroeconomic models, which are essentially dynamic in nature, and involve consumption smoothing across time and across various states of nature. Specifically, since deciding to undertake tax evasion impacts on the consumption smoothing ability of the agent by creating two states of nature in which the agent is ‘caught’ or ‘not caught’, there is a possibility that their utility under certainty, when they choose not to evade, is higher than the expected utility obtained when they choose to evade. Furthermore, the simple two-period model incorporating an ‘evade or not’ choice can be used to demonstrate some strikingly different political economy implications relative to its Allingham and Sandmo counterpart. In variations of the two models that allow for voting on the tax parameter, we find that agents typically choose to vote for a high degree of progressivity by choosing the highest available tax rate from the menu of choices available to them. There is, however, a small range of inequality levels for which agents in the ‘evade or not’ model vote for a relatively low value of the tax rate. The final steps in the model building procedure involve grafting the two-period models with a political economy choice into a dynamic overlapping generations setting with more general, non-linear tax schedules and a ‘cost-of evasion’ function that is increasing in the extent of evasion. Results based on numerical simulations of these models show further improvement in the model’s ability to match empirically plausible levels of tax evasion. In addition, the differences between the political economy implications of the ‘evade or not’ version of the model and its Allingham and Sandmo counterpart are now very striking; there is now a large range of values of the inequality parameter for which agents in the ‘evade or not’ model vote for a low degree of progressivity. This is because, in the ‘evade or not’ version of the model, low values of the tax rate encourages a large number of agents to choose the ‘not-evade’ option, so that the redistributive mechanism is more ‘efficient’ relative to the situations in which tax rates are high. Some further implications of the models of this thesis relate to whether variations in the level of inequality, and parameters such as the probability of detection and penalties for tax evasion matter for the political economy results. We find that (i) the political economy outcomes for the tax rate are quite insensitive to changes in inequality, and (ii) the voting outcomes change in non-monotonic ways in response to changes in the probability of detection and penalty rates. Specifically, the model suggests that changes in inequality should not matter, although the political outcome for the tax rate for a given level of inequality is conditional on whether there is a large or small or large extent of evasion in the economy. We conclude that further theoretical research into macroeconomic models of tax evasion is required to identify the structural relationships underpinning the link between inequality and redistribution in the presence of tax evasion. The models of this thesis provide a necessary first step in that direction.
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Aims: To identify risk factors for major Adverse Events (AEs) and to develop a nomogram to predict the probability of such AEs in individual patients who have surgery for apparent early stage endometrial cancer. Methods: We used data from 753 patients who were randomized to either total laparoscopic hysterectomy or total abdominal hysterectomy in the LACE trial. Serious adverse events that prolonged hospital stay or postoperative adverse events (using common terminology criteria 3+, CTCAE V3) were considered major AEs. We analyzed pre-surgical characteristics that were associated with the risk of developing major AEs by multivariate logistic regression. We identified a parsimonious model by backward stepwise logistic regression. The six most significant or clinically important variables were included in the nomogram to predict the risk of major AEs within 6 weeks of surgery and the nomogram was internally validated. Results: Overall, 132 (17.5%) patients had at least one major AE. An open surgical approach (laparotomy), higher Charlson’s medical co-morbidities score, moderately differentiated tumours on curettings, higher baseline ECOG score, higher body mass index and low haemoglobin levels were associated with AE and were used in the nomogram. The bootstrap corrected concordance index of the nomogram was 0.63 and it showed good calibration. Conclusions: Six pre-surgical factors independently predicted the risk of major AEs. This research might form the basis to develop risk reduction strategies to minimize the risk of AEs among patients undergoing surgery for apparent early stage endometrial cancer.
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We analyzed mesopic rod and S-cone interactions in terms of their contributions to the blue-yellow opponent pathway. Stimuli were generated using a 4-primary colorimeter. Mixed rod and S-cone modulation thresholds (constant L-, M-cone excitation) were measured as a function of their phase difference. Modulation amplitude was equated using threshold units and contrast ratios. This study identified three interaction types: (1) A linear and antagonistic rod:S-cone interaction, (2) probability summation (3) and a previously unidentified mutual nonlinear reinforcement. Linear rod:S-cone interactions occur within the blue-yellow opponent pathway. Probability summation involves signaling by different post-receptoral pathways. The origin of the nonlinear reinforcement is possibly at the photoreceptors.
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We consider a joint relay selection and subcarrier allocation problem that minimizes the total system power for a multi-user, multi-relay and single source cooperative OFDM based two hop system. The system is constrained to all users having a specific subcarrier requirement (user fairness). However no specific fairness constraints for relays are considered. To ensure the optimum power allocation, the subcarriers in two hops are paired with each other. We obtain an optimal subcarrier allocation for the single user case using a similar method to what is described in [1] and modify the algorithm for multiuser scenario. Although the optimality is not achieved in multiuser case the probability of all users being served fairly is improved significantly with a relatively low cost trade off.
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Maize streak virus strain A (MSV-A), the causal agent of maize streak disease, is today one of the most serious biotic threats to African food security. Determining where MSV-A originated and how it spread transcontinentally could yield valuable insights into its historical emergence as a crop pathogen. Similarly, determining where the major extant MSV-A lineages arose could identify geographical hot spots of MSV evolution. Here, we use model-based phylogeographic analyses of 353 fully sequenced MSV-A isolates to reconstruct a plausible history of MSV-A movements over the past 150 years. We show that since the probable emergence of MSV-A in southern Africa around 1863, the virus spread transcontinentally at an average rate of 32.5 km/year (95% highest probability density interval, 15.6 to 51.6 km/year). Using distinctive patterns of nucleotide variation caused by 20 unique intra-MSV-A recombination events, we tentatively classified the MSV-A isolates into 24 easily discernible lineages. Despite many of these lineages displaying distinct geographical distributions, it is apparent that almost all have emerged within the past 4 decades from either southern or east-central Africa. Collectively, our results suggest that regular analysis of MSV-A genomes within these diversification hot spots could be used to monitor the emergence of future MSV-A lineages that could affect maize cultivation in Africa. © 2011, American Society for Microbiology.
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Although the relationship between socioeconomic status (SES) and health is well documented for developed countries, less evidence has been presented for developing countries. The aim of this paper is to analyse this relationship at the household level for Fiji, a developing country in the South Pacific, using original household survey data. To allow for the endogeneity of SES status in the household health production function, we utilize a simultaneous equation approach where estimates are achieved by full information maximum likelihood. By restricting our sample to one, relatively small island, and including area and district hospital effects, physical geography effects are unpacked from income effects. We measure SES, as permanent income which is constructed using principal components analysis. An alternative specification considers transitory household income. We find that a 1% increase in wealth (our measure of permanent income) would lead to a 15% decrease in the probability of an incapacitating illness occurring intra-household. Although the presence of a strong relationship indicates that relatively small improvements in SES status can significantly improve health at the household level, it is argued that the design of appropriate policy would also require an understanding of the various mechanisms through which the relationship operates.
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Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.
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This paper outlines existing matching diagnostics, which may be used for identifying invalid matches and estimating the probability of a correct match. In addition, it proposes a new diagnostic for error prediction which can be used with the rank and census transforms. Both the existing and the new diagnostics have been evaluated and compared for a number of test images. In each case, a confidence estimate was computed for every location of the disparity map, and disparities having a low confidence estimate removed from the disparity map. Collectively, these confidence estimates may be termed a confidence map. Such information would be useful for potential applications of stereo vision such as automation and navigation.