972 resultados para Random processes
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A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.
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Public acceptance is consistently listed as having an enormous impact on the implementation and success of a congestion charge scheme. This paper investigates public acceptance of such a scheme in Australia. Surveys were conducted in Brisbane and Melbourne, the two fastest growing Australian cities. Using an ordered logit modeling approach, the survey data including stated preferences were analyzed to pinpoint the important factors influencing people’s attitudes to a congestion charge and, in turn, to their transport mode choices. To accommodate the nature of, and to account for the resulting heterogeneity of the panel data, random effects were considered in the models. As expected, this study found that the amount of the congestion charge and the financial benefits of implementing it have a significant influence on respondents’ support for the charge and on the likelihood of their taking a bus to city areas. However, respondents’ current primary transport mode for travelling to the city areas has a more pronounced impact. Meanwhile, respondents’ perceptions of the congestion charge’s role in protecting the environment by reducing vehicle emissions, and of the extent to which the charge would mean that they travelled less frequently to the city for shopping or entertainment, also have a significant impact on their level of support for its implementation. We also found and explained notable differences across two cities. Finally, findings from this study have been fully discussed in relation to the literature.
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This research project was a case study for managing and innovating an interdisciplinary practice: specifically across music, performance and contemporary art. Key works included painting/sound/video installation, experimental performance, electronic pop music, music video and electronic pop music performance. An idiosyncratic and transformative use of colour emerged as an underlying theme and strategy for cohesion. The project offers strategies for the challenges of interdisciplinary practice specifically addressing the limitations related to institutionalised value systems, aesthetic traditions and disciplinary languages.
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This thesis explored pathways to healing in men and women who experienced traumatic sexual abuse in childhood and considered themselves to be in a place of wellness. The thesis synthesises current knowledge in this area and has produced a number of models with direct implications for clinical practice. This unique work has also contributed to advancing theoretical understanding of healing following sexual assault.
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This study developed an understanding of hydrological processes within the Cressbrook Creek catchment of the upper Brisbane River, in particular for the alluvial aquifers. Those aquifers within the lower catchment are used for intensive irrigation, and have been impacted by long-term drought followed by flooding. The study utilised water chemistry, isotopic characters and hydraulic measurements to determine factors such as recharge, links between creeks and groundwater, and variations in water quality. The catchment-wide study will enable improved management of the local water resources.
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Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.
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Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.
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A well designed peer review process in higher education subjects can lead to more confident and reflective learners who become skilled at making independent judgements of their own and others’ work; essential requirements for successful lifelong learning. The challenge for educators is to ensure their students gain these important graduate attributes within the constraints of a range of internal and external tensions currently facing higher education systems, including, respectively, the realities of large undergraduate Accounting subjects, culturally diverse and time-poor academics and students, and increased calls for public accountability of the Higher Education sector by groups such as the OECD. Innovative curriculum and assessment design and collaborative technologies have the capacity to simultaneously provide some measure of relief from these internal and external tensions and to position students as responsible partners in their own learning. This chapter reports on a two phase implementation of an online peer review process as part of the assessment in a large, under-graduate, International Accounting class. Phase One did not include explicit reflective strategies within the process, and anonymous and voluntary student views served to clearly highlight that students were ‘confused’ and ‘hesitant’ about moving away from their own ideas; often mistrusting the conflicting advice received from multiple peer reviewers. A significant number of students also felt that they did not have the skills to constructively review the work of their peers. Phase Two consequently utilised the combined power of e-Technology, peer review feedback and carefully scaffolded and supported reflective practices from Ryan and Ryan’s Teaching and Assessing Reflective Learning (TARL) model (see Chap. 2). Students found the reflective skills support workshop introduced in Phase Two to be highly useful in maximising the benefits of the peer review process, with 83 % reporting it supported them in writing peer reviews, while 90 % of the respondents reporting the workshop supported them in utilising peer and staff feedback.
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In this study, the pedagogical decision-making processes of 21 Australian early childhood teachers working with children experiencing parental separation and divorce were examined. Transcripts from interviews and a focus group with teachers were analysed using grounded theory methodology. The findings showed that as teachers interacted with young children experiencing parental separation and divorce, they reported using strategic, reflexive pedagogical decision-making processes. These processes comprised five stages: (1) teachers constructing their knowledge; (2) teachers thinking about their knowledge; (3) teachers using decision-making schemas; (4) teachers taking action, and; (5) teachers monitoring action and evaluating. This understanding of teachers’ reflexive pedagogical decision-making is useful for identifying how teachers and educational leaders can support children experiencing parental separation and divorce or other life challenges.
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Although driver aggression has been identified as contributing to crashes, current understanding of the fundamental causes of the behaviour is poor. Two key reasons for this are evident. Firstly, existing research has been largely atheoretical, with no unifying conceptual framework guiding investigation. Secondly, emphasis on observable behaviours has resulted in limited knowledge of the underlying thought processes that motivate behaviour. Since driving is fundamentally a social situation, requiring drivers to interpret on-road events, insight regarding these perception and appraisal processes is paramount in advancing understanding of the underlying causes. Thus, the current study aimed to explore the cognitive appraisal processes involved in driver aggression, using a conceptual model founded on the General Aggression Model (Anderson & Bushman, 2002). The present results reflect the first of several studies testing this model. Participants completed 3 structured driving diaries to explore perceptions and cognitions. Thematic analysis of diaries identified several cognitive themes. The first, ‘driving etiquette’ concerned an implied code of awareness and consideration for other motorists, breaches of which were strongly associated with reports of anger and frustration. Such breaches were considered intentional; attributed to dispositional traits of another driver, and precipitated the second theme, ‘justified retaliation’. This theme showed that drivers view their aggressive behaviour as warranted, to convey criticism towards another motorist’s etiquette violation. However, the third theme, ‘superiority’ suggested that those refraining from an aggressive response were motivated by a desire to perceive themselves as ‘better’ than the offending motorists. Collectively, the themes indicate deep-seated and complex thought patterns underlying driver aggression, and suggest the behaviour will be challenging to modify. Implications of these themes in relation to the proposed model will be discussed, and continued research will explore these cognitive processes further, to examine their interaction with person-related factors.
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This pilot project investigated the existing practices and processes of Proficient, Highly Accomplished and Lead teachers in the interpretation, analysis and implementation of National Assessment Program – Literacy and Numeracy (NAPLAN) data. A qualitative case study approach was the chosen methodology, with nine teachers across a variety of school sectors interviewed. Themes and sub-themes were identified from the participants’ interview responses revealing the ways in which Queensland teachers work with NAPLAN data. The data illuminated that generally individual schools and teachers adopted their own ways of working with data, with approaches ranging from individual/ad hoc, to hierarchical or a whole school approach. Findings also revealed that data are the responsibility of various persons from within the school hierarchy; some working with the data electronically whilst others rely on manual manipulation. Manipulation of data is used for various purposes including tracking performance, value adding and targeting programmes for specific groups of students, for example the gifted and talented. Whilst all participants had knowledge of intervention programmes and how practice could be modified, there were large inconsistencies in knowledge and skills across schools. Some see the use of data as a mechanism for accountability, whilst others mention data with regards to changing the school culture and identifying best practice. Overall, the findings showed inconsistencies in approach to focus area 5.4. Recommendations therefore include a more national approach to the use of educational data.
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Purpose This paper seeks to investigate the conditions and processes affecting the operation and potential effectiveness of audit committees (ACs), with particular focus on the interaction between the AC, individuals from financial reporting and internal audit functions and the external auditors. Design/methodology/approach A case study approach is employed, based on direct engagement with participants in AC activities, including the AC chair, external auditors, internal auditors, and senior management. Findings The authors find that informal networks between AC participants condition the impact of the AC and that the most significant effects of the AC on governance outcomes occur outside the formal structures and processes. An AC has pervasive behavioural effects within the organization and may be used as a threat, an ally and an arbiter in bringing solutions to issues and conflicts. ACs are used in organizational politics, communication processes and power plays and also affect interpretations of events and cultural values. Research limitations/implications Further research on AC and governance processes is needed to develop better understanding of effectiveness. Longitudinal studies, focusing on the organizational and institutional context of AC operations, can examine how historical events in an organization and significant changes in the regulatory environment affect current structures and processes. Originality/value The case analysis highlights a number of significant factors which are not fully recognised either in theorizing the governance role of ACs or in the development of policy and regulations concerning ACs but which impinge on their governance contribution. They include the importance of informal processes around the AC; its influence on power relations between organizational participants; the relevance of the historical development of governance in an organization; and the possibility that the AC’s impact on governance may be greatest in non-routine situations.
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Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.