595 resultados para methods: analytical


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Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

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In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.

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The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow. Since the MFD represents the area-wide network traffic performance, studies on perimeter control strategies and network-wide traffic state estimation utilising the MFD concept have been reported. Most previous works have utilised data from fixed sensors, such as inductive loops, to estimate the MFD, which can cause biased estimation in urban networks due to queue spillovers at intersections. To overcome the limitation, recent literature reports the use of trajectory data obtained from probe vehicles. However, these studies have been conducted using simulated datasets; limited works have discussed the limitations of real datasets and their impact on the variable estimation. This study compares two methods for estimating traffic state variables of signalised arterial sections: a method based on cumulative vehicle counts (CUPRITE), and one based on vehicles’ trajectory from taxi Global Positioning System (GPS) log. The comparisons reveal some characteristics of taxi trajectory data available in Brisbane, Australia. The current trajectory data have limitations in quantity (i.e., the penetration rate), due to which the traffic state variables tend to be underestimated. Nevertheless, the trajectory-based method successfully captures the features of traffic states, which suggests that the trajectories from taxis can be a good estimator for the network-wide traffic states.

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One of the major impediments for the use of UAVs in civilian environment is the capability to replicate some of the functionality of safe manned aircraft operations. One critical aspect is emergency landing. Once the possible landing sites have been rated, a decision on the most suitable choice to land is required. This is a multi-criteria decision making (MCDM) problem which needs to take into account various factors in its selection of landing site. This report summarises relevant literature in MCDM in the context of emergency forced landing and proposes and compares two algorithms and methods for this task.

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The effects of fish density distribution and effort distribution on the overall catchability coefficient are examined. Emphasis is also on how aggregation and effort distribution interact to affect overall catch rate [catch per unit effort (cpue)]. In particular, it is proposed to evaluate three indices, the catchability index, the knowledge parameter, and the aggregation index, to describe the effectiveness of targeting and the effects on overall catchability in the stock area. Analytical expressions are provided so that these indices can easily be calculated. The average of the cpue calculated from small units where fishing is random is a better index for measuring the stock abundance. The overall cpue, the ratio of lumped catch and effort, together with the average cpue, can be used to assess the effectiveness of targeting. The proposed methods are applied to the commercial catch and effort data from the Australian northern prawn fishery. The indices are obtained assuming a power law for the effort distribution as an approximation of targeting during the fishing operation. Targeting increased catchability in some areas by 10%, which may have important implications on management advice.

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This thesis explores the feasibility of donor-receiver concept for joint replacement where cartilage-bone tissues can be taken from either human or other mammals and prepared scientifically for repairing focal joint defects in knees, hips and shoulders. The manufactured construct is immunologically inert and is capable of acting as a scaffold for engineering new cartilage-bone laminates when placed in the joint. Innovative manufacturing procedures and assessment techniques were developed for appraising this tissue-based scaffold. This research has demonstrated that tissue replacement technology can be applied in situations where blood vessels are absent such as in articular cartilage.

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The method of generalised estimating equations for regression modelling of clustered outcomes allows for specification of a working matrix that is intended to approximate the true correlation matrix of the observations. We investigate the asymptotic relative efficiency of the generalised estimating equation for the mean parameters when the correlation parameters are estimated by various methods. The asymptotic relative efficiency depends on three-features of the analysis, namely (i) the discrepancy between the working correlation structure and the unobservable true correlation structure, (ii) the method by which the correlation parameters are estimated and (iii) the 'design', by which we refer to both the structures of the predictor matrices within clusters and distribution of cluster sizes. Analytical and numerical studies of realistic data-analysis scenarios show that choice of working covariance model has a substantial impact on regression estimator efficiency. Protection against avoidable loss of efficiency associated with covariance misspecification is obtained when a 'Gaussian estimation' pseudolikelihood procedure is used with an AR(1) structure.

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Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used (using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.

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Perceiving students, science students especially, as mere consumers of facts and information belies the importance of a need to engage them with the principles underlying those facts and is counter-intuitive to the facilitation of knowledge and understanding. Traditional didactic lecture approaches need a re-think if student classroom engagement and active learning are to be valued over fact memorisation and fact recall. In our undergraduate biomedical science programs across Years 1, 2 and 3 in the Faculty of Health at QUT, we have developed an authentic learning model with an embedded suite of pedagogical strategies that foster classroom engagement and allow for active learning in the sub-discipline area of medical bacteriology. The suite of pedagogical tools we have developed have been designed to enable their translation, with appropriate fine-tuning, to most biomedical and allied health discipline teaching and learning contexts. Indeed, aspects of the pedagogy have been successfully translated to the nursing microbiology study stream at QUT. The aims underpinning the pedagogy are for our students to: (1) Connect scientific theory with scientific practice in a more direct and authentic way, (2) Construct factual knowledge and facilitate a deeper understanding, and (3) Develop and refine their higher order flexible thinking and problem solving skills, both semi-independently and independently. The mindset and role of the teaching staff is critical to this approach since for the strategy to be successful tertiary teachers need to abandon traditional instructional modalities based on one-way information delivery. Face-to-face classroom interactions between students and lecturer enable realisation of pedagogical aims (1), (2) and (3). The strategy we have adopted encourages teachers to view themselves more as expert guides in what is very much a student-focused process of scientific exploration and learning. Specific pedagogical strategies embedded in the authentic learning model we have developed include: (i) interactive lecture-tutorial hybrids or lectorials featuring teacher role-plays as well as class-level question-and-answer sessions, (ii) inclusion of “dry” laboratory activities during lectorials to prepare students for the wet laboratory to follow, (iii) real-world problem-solving exercises conducted during both lectorials and wet laboratory sessions, and (iv) designing class activities and formative assessments that probe a student’s higher order flexible thinking skills. Flexible thinking in this context encompasses analytical, critical, deductive, scientific and professional thinking modes. The strategic approach outlined above is designed to provide multiple opportunities for students to apply principles flexibly according to a given situation or context, to adapt methods of inquiry strategically, to go beyond mechanical application of formulaic approaches, and to as much as possible self-appraise their own thinking and problem solving. The pedagogical tools have been developed within both workplace (real world) and theoretical frameworks. The philosophical core of the pedagogy is a coherent pathway of teaching and learning which we, and many of our students, believe is more conducive to student engagement and active learning in the classroom. Qualitative and quantitative data derived from online and hardcopy evaluations, solicited and unsolicited student and graduate feedback, anecdotal evidence as well as peer review indicate that: (i) our students are engaging with the pedagogy, (ii) a constructivist, authentic-learning approach promotes active learning, and (iii) students are better prepared for workplace transition.

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A profluorescent nitroxide possessing an isoindoline nitroxide moiety linked to a perylene fluorophore was developed to monitor radical mediated degradation of melamine-formaldehyde crosslinked polyester coil coatings in an industry standard accelerated weathering tester. Trapping of polyester-derived radicals (most likely C-radicals) that are generated during polymer degradation leads to fluorescent closed-shell alkoxy amines, which was used to obtain time-dependent degradation profiles to assess the relative stability of different polyesters towards weathering. The nitroxide probe couples excellent thermal stability and satisfactory photostability with high sensitivity and enables detection of free radical damage in polyesters under conditions that mimic exposure to the environment on a time scale of hours rather than months or years required by other testing methods. There are indications that the profluorescent nitroxide undergoes partial photo-degradation in the absence of polymer-derived radicals. Unexpectedly, it was also found that UV-induced fragmentation of the NO–C bond in closed-shell alkoxy amines leads to regeneration of the profluorescent nitroxide and the respective C-radical. The maximum fluorescence intensity that could be achieved with a given probe concentration is therefore not only determined by the amount of polyester radicals formed during accelerated weathering, but also by the light-driven side reactions of the profluorescent nitroxide and the corresponding alkoxy amine radical trapping products. Studies to determine the optimum probe concentration in the polymer matrix revealed that aggregation and re-absorption effects lowered the fluorescence intensity at higher concentrations of the profluorescent nitroxide, but too low probe concentrations, where these effects would be avoided, were not sufficient to trap the amount of polyester radicals formed upon weathering. The optimized experimental conditions were used to assess the impact of temperature and UV irradiance on polymer degradation during accelerated weathering.