894 resultados para comparative methods


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This study investigates facework (communicative) strategies of Sri Lankans working in Australia and compares them with strategies used by Australians of European origin working in Australia. The study also explores the values of those Sri Lankans as a reflection of their facework, and how Sri Lankans have adjusted their facework to the Australian culture. The study used a survey questionnaire and interviewed Sri Lankans working in Australia for this investigation. The survey questionnaire was used to understand the facework similarities and difference between the Sri Lankans and Australians as explained in Oetzel and Ting-Toomey’s Face Negotiation Model. The survey revealed that Sri Lankans are higher in interdependent self construal, self face concern and other face concern than the Australians. Nonetheless, Sri Lankans are similar to the Australians in other facework strategies. The interviews clarified that Sri Lankans do not change their values by living in Australia, yet they make some changes to how they do things.

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Cytogenetic and loss of heterozygosity (LOH) studies have long indicated the presence of a tumor suppressor gene (TSG) on 9p involved in the development of melanoma. Although LOH at 9p has been reported in approximately 60% of melanoma tumors, only 5-10% of these tumors have been shown to carry CDKN2A mutations, raising the possibility that another TSG involved in melanoma maps to chromosome 9p. To investigate this possibility, a panel of 37 melanomas derived from 35 individuals was analyzed for CDKN2A mutations by single-strand conformation polymorphism analysis and sequencing. The melanoma samples were then typed for 15 markers that map to 9p13-24 to investigate LOH trends in this region. In those tumors demonstrating retention of heterozygosity at markers flanking CDKN2A and LOH on one or both sides of the gene, multiplex microsatellite PCR was performed to rule out homozygous deletion of the region encompassing CDKN2A. CDKN2A mutations were found in tumors from 5 patients [5 (14%) of 35], 4 of which demonstrated LOH across the entire region examined. The remaining tumor with no observed LOH carried two point mutations, one on each allele. Although LOH was identified at one or more markers in 22 (59%) of 37 melanoma tumors corresponding to 20 (57%) of 35 individuals, only 11 tumors from 9 individuals [9 (26%) of 35] demonstrated LOH at D9S942 and D9S1748 the markers closest to CDKN2A. Of the remaining 11 tumors with LOH 9 demonstrated LOH at two or more contiguous markers either centromeric and/or telomeric to CDKN2A while retaining heterozygosity at several markers adjacent to CDKN2A. Multiplex PCR revealed one tumor carried a homozygous deletion extending from D9S1748 to the IFN-alpha locus. In the remaining eight tumors, multiplex PCR demonstrated that the observed heterozygosity was not attributable to homozygous deletion and stromal contamination at D9S1748, D9S942, or D9S974, as measured by comparative amplification strengths, which indicates that retention of heterozygosity with flanking LOH does not always indicate a homozygous deletion. This report supports the conclusions of previous studies that a least two TSGs involved in melanoma development in addition to CDKN2A may reside on chromosome 9p.

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As English increasingly becomes one of the most commonly spoken languages in the world today for a variety of economic, social and cultural reasons, education is impacted by globalisation, the internationalisation of universities and the diversity of learners in classrooms. The challenge for educators is to find more effective ways of teaching English language so that students are better able to create meaning and communicate in the target language as well as to transform knowledge and understanding into relevant skills for a rapidly changing world. This research focuses broadly on English language education underpinned by social constructivist principles informing communicative language teaching and in particular, interactive peer learning approaches. An intervention of interactive peer-based learning in two case study contexts of English as Foreign Language (EFL) undergraduates in a Turkish university and English as Second Language (ESL) undergraduates in an Australian university investigates what students gain from the intervention. Methodology utilising qualitative data gathered from student reflective logs, focus group interviews and researcher field notes emphasises student voice. The cross case comparative study indicates that interactive peer-based learning enhances a range of learning outcomes for both cohorts including engagement, communicative competence, diagnostic feedback as well as assisting development of inclusive social relationships, civic skills, confidence and self efficacy. The learning outcomes facilitate better adaptation to a new learning environment and culture. An iterative instructional matrix tool is a useful product of the research for first year university experiences, teacher training, raising awareness of diversity, building learning communities, and differentiating the curriculum. The study demonstrates that English language learners can experience positive impact through peer-based learning and thus holds an influential key for Australian universities and higher education.

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Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

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This paper gives a modification of a class of stochastic Runge–Kutta methods proposed in a paper by Komori (2007). The slight modification can reduce the computational costs of the methods significantly.

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In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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We consider time-space fractional reaction diffusion equations in two dimensions. This equation is obtained from the standard reaction diffusion equation by replacing the first order time derivative with the Caputo fractional derivative, and the second order space derivatives with the fractional Laplacian. Using the matrix transfer technique proposed by Ilic, Liu, Turner and Anh [Fract. Calc. Appl. Anal., 9:333--349, 2006] and the numerical solution strategy used by Yang, Turner, Liu, and Ilic [SIAM J. Scientific Computing, 33:1159--1180, 2011], the solution of the time-space fractional reaction diffusion equations in two dimensions can be written in terms of a matrix function vector product $f(A)b$ at each time step, where $A$ is an approximate matrix representation of the standard Laplacian. We use the finite volume method over unstructured triangular meshes to generate the matrix $A$, which is therefore non-symmetric. However, the standard Lanczos method for approximating $f(A)b$ requires that $A$ is symmetric. We propose a simple and novel transformation in which the standard Lanczos method is still applicable to find $f(A)b$, despite the loss of symmetry. Numerical results are presented to verify the accuracy and efficiency of our newly proposed numerical solution strategy.

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In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

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Microbial pollution in water periodically affects human health in Australia, particularly in times of drought and flood. There is an increasing need for the control of waterborn microbial pathogens. Methods, allowing the determination of the origin of faecal contamination in water, are generally referred to as Microbial Source Tracking (MST). Various approaches have been evaluated as indicatorsof microbial pathogens in water samples, including detection of different microorganisms and various host-specific markers. However, until today there have been no universal MST methods that could reliably determine the source (human or animal) of faecal contamination. Therefore, the use of multiple approaches is frequently advised. MST is currently recognised as a research tool, rather than something to be included in routine practices. The main focus of this research was to develop novel and universally applicable methods to meet the demands for MST methods in routine testing of water samples. Escherichia coli was chosen initially as the object organism for our studies as, historically and globally, it is the standard indicator of microbial contamination in water. In this thesis, three approaches are described: single nucleotide polymorphism (SNP) genotyping, clustered regularly interspaced short palindromic repeats (CRISPR) screening using high resolution melt analysis (HRMA) methods and phage detection development based on CRISPR types. The advantage of the combination SNP genotyping and CRISPR genes has been discussed in this study. For the first time, a highly discriminatory single nucleotide polymorphism interrogation of E. coli population was applied to identify the host-specific cluster. Six human and one animal-specific SNP profile were revealed. SNP genotyping was successfully applied in the field investigations of the Coomera watershed, South-East Queensland, Australia. Four human profiles [11], [29], [32] and [45] and animal specific SNP profile [7] were detected in water. Two human-specific profiles [29] and [11] were found to be prevalent in the samples over a time period of years. The rainfall (24 and 72 hours), tide height and time, general land use (rural, suburban), seasons, distance from the river mouth and salinity show a lack of relashionship with the diversity of SNP profiles present in the Coomera watershed (p values > 0.05). Nevertheless, SNP genotyping method is able to identify and distinquish between human- and non-human specific E. coli isolates in water sources within one day. In some samples, only mixed profiles were detected. To further investigate host-specificity in these mixed profiles CRISPR screening protocol was developed, to be used on the set of E. coli, previously analysed for SNP profiles. CRISPR loci, which are the pattern of previous DNA coliphages attacks, were considered to be a promising tool for detecting host-specific markers in E. coli. Spacers in CRISPR loci could also reveal the dynamics of virulence in E. coli as well in other pathogens in water. Despite the fact that host-specificity was not observed in the set of E. coli analysed, CRISPR alleles were shown to be useful in detection of the geographical site of sources. HRMA allows determination of ‘different’ and ‘same’ CRISPR alleles and can be introduced in water monitoring as a cost-effective and rapid method. Overall, we show that the identified human specific SNP profiles [11], [29], [32] and [45] can be useful as marker genotypes globally for identification of human faecal contamination in water. Developed in the current study, the SNP typing approach can be used in water monitoring laboratories as an inexpensive, high-throughput and easy adapted protocol. The unique approach based on E. coli spacers for the search for unknown phage was developed to examine the host-specifity in phage sequences. Preliminary experiments on the recombinant plasmids showed the possibility of using this method for recovering phage sequences. Future studies will determine the host-specificity of DNA phage genotyping as soon as first reliable sequences can be acquired. No doubt, only implication of multiple approaches in MST will allow identification of the character of microbial contamination with higher confidence and readability.

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The United States Supreme Court has handed down a once in a generation patent law decision that will have important ramifications for the patentability of non-physical methods, both internationally and in Australia. In Bilski v Kappos, the Supreme Court considered whether an invention must either be tied to a machine or apparatus, or transform an article into a different state or thing to be patentable. It also considered for the first time whether business methods are patentable subject matter. The decision will be of particular interest to practitioners who followed the litigation in Grant v Commissioner of Patents, a Federal Court decision in which a Brisbane-based inventor was denied a patent over a method of protecting an asset from the claims of creditors.

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Background: It is predicted that China will have the largest number of cases of dementia in the world by 2025 (Ferri et al., 2005). Research has demonstrated that caring for family members with dementia can be a long-term, burdensome activity resulting in physical and emotional distress and impairment (Pinquart & Sorensen, 2003b). The establishment of family caregiver supportive services in China can be considered urgent; and the knowledge of the caregiving experience and related influencing factors is necessary to inform such services. Nevertheless, in the context of rapid demographic and socioeconomic change, the impact of caregiving for rural and urban Chinese adult-child caregivers may be different, and different needs in supportive services may therefore be expected. Objectives: The aims of this research were 1) to examine the potential differences existing in the caregiving experience between rural and urban adult-child caregivers caring for parents with dementia in China; and 2) to examine the potential differences existing in the influencing factors of the caregiving experience for rural as compared with urban adult-child caregivers caring for parents with dementia in China. Based on the literature review and Kramer.s (1997) caregiver adaptation model, six concepts and their relationships of caregiving experience were studied: severity of the care receivers. dementia, caregivers. appraisal of role strain and role gain, negative and positive well-being outcomes, and health related quality of life. Furthermore, four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) were studied respectively. Methods: A cross-sectional, comparative design was used to achieve the aims of the study. A questionnaire, which was designed based on the literature review and on Kramer.s (1997) caregiver adaptation model, was completed by 401 adult-child caregivers caring for their parents with dementia from the mental health outpatient departments in five hospitals in the Yunnan province, P.R. China. Structural equation modelling (SEM) was employed as the main statistical technique for data analyses. Other statistical techniques (e.g., t-tests and Chi-Square tests) were also conducted to compare the demographic characteristics and the measured variables between rural and urban groups. Results: For the first research aim, the results indicated that urban adult-child caregivers in China experienced significantly greater strain and negative well-being outcomes than their rural peers; whereas, the difference on the appraisal of role gain and positive outcomes was nonsignificant between the two groups. The results also indicated that the amounts of severity of care receivers. dementia and caregivers. health related quality of life do not have the same meanings between the two groups. Thus, the levels of these two concepts were not comparable between the rural and urban groups in this study. Moreover, the results also demonstrated that the negative direct effect of gain on negative outcomes in urban caregivers was stronger than that in rural caregivers, suggesting that the urban caregivers tended to use appraisal of role gain to protect themselves from negative well-being outcomes to a greater extent. In addition, the unexplained variance in strain in the urban group was significantly more than that in the rural group, suggesting that there were other unmeasured variables besides the severity of care receivers. dementia which would predict strain in urban caregivers compared with their rural peers. For the second research aim, the results demonstrated that rural adult-child caregivers reported a significantly higher level of filial piety and more social support than their urban counterparts, although the two groups did not significantly differ on the levels of their resilience and personal mastery. Furthermore, although the mediation effects of these four influencing factors on both positive and negative aspects remained constant across rural and urban adult-child caregivers, urban caregivers tended to be more effective in using personal mastery to protect themselves from role strain than rural caregivers, which in turn protects them more from the negative well-being outcomes than was the case with their rural peers. Conclusions: The study extends the application of Kramer.s caregiving adaptation process model (Kramer, 1997) to a sample of adult-child caregivers in China by demonstrating that both positive and negative aspects of caregiving may impact on the caregiver.s health related quality of life, suggesting that both aspects should be targeted in supportive interventions for Chinese family caregivers. Moreover, by demonstrating partial mediation effects, the study provides four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) as specific targets for clinical interventions. Furthermore, the study found evidence that urban adult-child caregivers had more negative but similar positive experience compared to their rural peers, suggesting that the establishment of supportive services for urban caregivers may be more urgent at present stage in China. Additionally, since urban caregivers tended to use appraisal of role gain and personal mastery to protect themselves from negative well-being outcomes than rural caregivers to a greater extend, interventions targeting utility of gain or/and personal mastery to decrease negative outcomes might be more effective in urban caregivers than in rural caregivers. On the other hand, as cultural expectations and expression of filial piety tend to be more traditional in rural areas, interventions targeting filial piety could be more effective among rural caregivers. Last but not least, as rural adult-child caregivers have more existing natural social support than their urban counterparts, mobilising existing natural social support resources may be more beneficial for rural caregivers, whereas, formal supports (e.g., counselling services, support groups and adult day care centres) should be enhanced for urban caregivers.

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Corrosion is a common phenomenon and critical aspects of steel structural application. It affects the daily design, inspection and maintenance in structural engineering, especially for the heavy and complex industrial applications, where the steel structures are subjected to hash corrosive environments in combination of high working stress condition and often in open field and/or under high temperature production environments. In the paper, it presents the actual engineering application of advanced finite element methods in the predication of the structural integrity and robustness at a designed service life for the furnaces of alumina production, which was operated in the high temperature, corrosive environments and rotating with high working stress condition.

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Six sigma has proven itself as a major quality initiative in the last two decades. It is a philosophy which provides a systematic approach to applying numerous tools in the framework of several quality improvement methodologies. The most widely used six sigma methodology is DMAIC, which is best suited for improving existing processes. In order to build quality into the product or service, a proactive approach like Design for Six Sigma (DFSS) is required. This paper provides an overview of DFSS, product innovation, and service innovation. The emphasis is on comparing how DFSS is applied differently in product and service innovation. This paper contributes by analysing the existing literature on DFSS in product and service innovation. The major findings are that the DFSS approach in services and products can be differentiated along the following three dimensions: methodology, characteristics, and technology.

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The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.