345 resultados para expert elicited


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The bulk of the homicide research to date has focused on male offending, with little consideration given to women's offending and in particular, their constructions within the courtroom following a homicide-related charge. This thesis examines, in detail, nineteen homicide cases finalised in the Queensland Supreme Courts between 01/01/1997 and 31/12/2002, in order to document and discuss the various legal stories available to women who kill. Predominantly, two “stock stories” are available within the court. The first, presented by the defence, offers the accused woman a victimised position to occupy. Evidence of victimisation is made available through previous abuse, expert testimony from psychologists and psychiatrists, challenges to her mental health, or appeals to her emotional nature. The second stock story, presented by the prosecution, positions the accused woman as angry, full of revenge, calculating and self serving. Such a script is usually supported by witnesses, police evidence, and family members. This thesis examines these competing and contradictory scripts using thematic discourse analysis to examine the court transcripts in detail. It argues that the "truth" of the fatal incident is based on one of these two prevailing scripts. This research destabilises the dominant script of violent female offending in the feminist literature. Most research to date has focussed on explaining the circumstances in which women kill, concentrating attention on the victimisation of the violent offending woman and negating or de-prioritising any volition on her part. By analysing all transcripts of women whose trials were held within the specified period, this research is able to demonstrate the stories used to describe their complex offending, and draw attention to the anger and intent that can occur alongside the victimisation.

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This book explores the application of concepts of fiduciary duty or public trust in responding to the policy and governance challenges posed by policy problems that extend over multiple terms of government or even, as in the case of climate change, human generations. The volume brings together a range of perspectives including leading international thinkers on questions of fiduciary duty and public trust, Australia's most prominent judicial advocate for the application of fiduciary duty, top law scholars from several major universities, expert commentary from an influential climate policy think-tank and the views of long-serving highly respected past and present parliamentarians. The book presents a detailed examination of the nature and extent of fiduciary duty, looking at the example of Australia and having regard to developments in comparable jurisdictions. It identifies principles that could improve the accountability of political actors for their responses to major problems that may extend over multiple electoral cycles.

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Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

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Railway timetabling is an important process in train service provision as it matches the transportation demand with the infrastructure capacity while customer satisfaction is also considered. It is a multi-objective optimisation problem, in which a feasible solution, rather than the optimal one, is usually taken in practice because of the time constraint. The quality of services may suffer as a result. In a railway open market, timetabling usually involves rounds of negotiations among a number of self-interested and independent stakeholders and hence additional objectives and constraints are imposed on the timetabling problem. While the requirements of all stakeholders are taken into consideration simultaneously, the computation demand is inevitably immense. Intelligent solution-searching techniques provide a possible solution. This paper attempts to employ a particle swarm optimisation (PSO) approach to devise a railway timetable in an open market. The suitability and performance of PSO are studied on a multi-agent-based railway open-market negotiation simulation platform.

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This research-in-progress paper reports preliminary findings of a study that is designed to identify characteristics of an expert in the discipline of Information Systems (IS). The paper delivers a formative research model to depict characteristics of an expert with three additive constructs, using concepts derived from psychology, knowledge management and social-behaviour research. The paper then explores the formation and application ‘expertise’ using four investigative questions in the context of System Evaluations. Data have been gathered from 220 respondents representing three medium sized companies in India, using the SAP Enterprise Resource Planning system. The paper summarizes planned data analyses in construct validation, model testing and model application. A validated construct of expertise of IS will have a wide range of implications for research and practice.

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Secondary lower-limb lymphedema can develop following treatment for gynecological cancers, and has debilitating effects on quality of life (QoL). Lymphedema can limit mobility and ability to perform daily activities, and have adverse effects on psychological and social wellbeing. When assessing the effect of lymphedema treatment methods, the focus is on change in clinically measured lymphedema status, rather than QoL outcomes. Considering that treatment for lymphedema involves a significant and ongoing commitment from patients, it is essential to determine whether the benefits to patients outweigh the burden associated with treatment. This article summarizes the results of studies assessing the impact of lower-limb lymphedema on QoL in women with gynecological cancer, evaluates their methodologies and discusses limitations and priorities for future research.

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...the probabilistic computer simulation study by Dunham and colleagues evaluating the impact of different cervical spine management (CSM) strategies on tetraplegia and brain injury outcomes.1 Based on literature findings, expert opinion and with use of advances programming techniques the authors conclude that early collar removal without cervical spine magnetic resonance imaging (MRI) is a preferable CSM strategy for comatose, blunt trauma patients with extremity movement and a negative cervical spine computed tomography(CT) scan. Although we do not have the required expertise to comment on the applied statistical approach, we would like to comment on one of the medical assumptions raised by the authors, namely the likelihood of tetraplegia in this specific population....

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This paper describes the development and evaluation of a new instrument - the Clinician Suicide Risk Assessment Checklist (CSRAC). The instrument assesses the clinician's competency in three areas: clinical interviewing, assessment of specific suicide risk factors, and formulating a management plan. A draft checklist was constructed by integrating information from 1) literature review 2) expert clinician focus group and 3) consultation with experts. It was utilised in a simulated clinical scenario with clinician trainees and a trained actor in order to test for inter-rater agreement. Agreement was calculated and the checklist was re-drafted with the aim of maximising agreement. A second phase of simulated clinical scenarios was then conducted and inter-rater agreement was calculated for the revised checklist. In the first phase of the study, 18 of 35 items had inadequate inter-rater agreement (60%>), while in the second phase, using the revised version, only 3 of 39 items failed to achieve adequate inter-rater agreement. Further evidence of reliability and validity are required. Continued development of the CSRAC will be necessary before it can be utilised to assess the effectiveness of risk assessment training programs.

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The World Health Organization recommends that data on mortality in its member countries are collected utilising the Medical Certificate of Cause of Death published in the instruction volume of the ICD-10. However, investment in health information processes necessary to promote the use of this certificate and improve mortality information is lacking in many countries. An appeal for support to make improvements has been launched through the Health Metrics Network’s MOVE-IT strategy (Monitoring of Vital Events – Information Technology) [World Health Organization, 2011]. Despite this international spotlight on the need for capture of mortality data and in the use of the ICD-10 to code the data reported on such certificates, there is little cohesion in the way that certifiers of deaths receive instruction in how to complete the death certificate, which is the main source document for mortality statistics. Complete and accurate documentation of the immediate, underlying and contributory causes of death of the decedent on the death certificate is a requirement to produce standardised statistical information and to the ability to produce cause-specific mortality statistics that can be compared between populations and across time. This paper reports on a research project conducted to determine the efficacy and accessibility of the certification module of the WHO’s newly-developed web based training tool for coders and certifiers of deaths. Involving a population of medical students from the Fiji School of Medicine and a pre and post research design, the study entailed completion of death certificates based on vignettes before and after access to the training tool. The ability of the participants to complete the death certificates and analysis of the completeness and specificity of the ICD-10 coding of the reported causes of death were used to measure the effect of the students’ learning from the training tool. The quality of death certificate completion was assessed using a Quality Index before and after the participants accessed the training tool. In addition, the views of the participants about accessibility and use of the training tool were elicited using a supplementary questionnaire. The results of the study demonstrated improvement in the ability of the participants to complete death certificates completely and accurately according to best practice. The training tool was viewed very positively and its implementation in the curriculum for medical students was encouraged. Participants also recommended that interactive discussions to examine the certification exercises would be an advantage.

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Research on expertise, talent identification and development has tended to be mono-disciplinary, typically adopting geno-centric or environmentalist positions, with an overriding focus on operational issues. In this thesis, the validity of dualist positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise and talent development, a shift towards a multidisciplinary and integrative science focus is necessary, along with the development of a comprehensive multidisciplinary theoretical rationale. Dynamical systems theory is utilised as a multidisciplinary theoretical rationale for the succession of studies, capturing how multiple interacting constraints can shape the development of expert performers. Phase I of the research examines experiential knowledge of coaches and players on the development of fast bowling talent utilising qualitative research methodology. It provides insights into the developmental histories of expert fast bowlers, as well as coaching philosophies on the constraints of fast bowling expertise. Results suggest talent development programmes should eschew the notion of common optimal performance models and emphasize the individual nature of pathways to expertise. Coaching and talent development programmes should identify the range of interacting constraints that impinge on the performance potential of individual athletes, rather than evaluating current performance on physical tests referenced to group norms. Phase II of this research comprises three further studies that investigate several of the key components identified as important for fast bowling expertise, talent identification and development extrapolated from Phase I of this research. This multidisciplinary programme of work involves a comprehensive analysis of fast bowling performance in a cross-section of the Cricket Australia high performance pathways, from the junior, emerging and national elite fast bowling squads. Briefly, differences were found in trunk kinematics associated with the generation of ball speed across the three groups. These differences in release mechanics indicated the functional adaptations in movement patterns as bowlers’ physical and anatomical characteristics changed during maturation. Second to the generation of ball speed, the ability to produce a range of delivery types was highlighted as a key component of expertise in the qualitative phase. The ability of athletes to produce consistent results on different surfaces and in different environments has drawn attention to the challenge of measuring consistency and flexibility in skill assessments. Examination of fast bowlers in Phase II demonstrated that national bowlers can make adjustments to the accuracy of subsequent deliveries during performance of a cricket bowling skills test, and perform a range of delivery types with increased accuracy and consistency. Finally, variability in selected delivery stride ground reaction force components in fast bowling revealed the degenerate nature of this complex multi-articular skill where the same performance outcome can be achieved with unique movement strategies. Utilising qualitative and quantitative methodologies to examine fast bowling expertise, the importance of degeneracy and adaptability in fast bowling has been highlighted alongside learning design that promotes dynamic learning environments.

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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.

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In order to understand better the role of affect in learning about socio-scientificissues (SSI), this study investigated Year 12 students’ emotional arousal as they participated in an online writing-to-learn science project about the socio-scientific issue of biosecurity. Students wrote a series of hybridised scientific narratives, or BioStories, that integrate scientific information about biosecurity with narrative storylines, and uploaded these to a dedicated website. Throughout their participation in the project, students recorded their emotional responses to the various activities (N=50). Four case students were also video recorded during selected science lessons as they researched, composed and uploaded their BioStories for peer review. Analysis of these data, as well as interview data obtained from the case students, revealed that pride, strength, determination, interest and alertness were among the positive emotions most strongly elicited by the project. These emotions reflected students’ interest in learning about a new socio-scientific issue, and their enhanced feelings of self-efficacy in successfully writing hybridised scientific narratives in science. The results of this study suggest that the elicitation of positive emotional responses as students engage in hybridised writing about SSI with strong links to environmental education, such as biosecurity, can be valuable in engaging students in education for sustainability.

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This research examines why and how brand owners in China adopt and use mobile media in marketing campaigns to deliver co-creation brand experiences and build consumer relationships. China represents an interesting case to study as it has leapfrogged into the age of consumer society and mobile media adoption. As the largest mobile market globally, it has experienced the intensity of mobile technology diffusion; and with it the rise of mobile consumer culture and participatory culture. Further, the rising individualism and the socio-cultural heritage in collectivism serve as a structuring tension in how mobile media is leveraged in marketing to cater to consumers' desires for individuality and social interaction. First, through expert interviews guided by the technology-organization-environment (TOE) framework (Tornatzky & Fleischer, 1990) as well as integrating innovation diffusion theory (E. Rogers, 2003), this research attempts to fill the gap of theoretical application in mobile marketing adoption at the firm level in China, and unravel the adoption factors of mobile marketing by brand owners in China. In total, 27 semi-structured interviews were conducted with key industry informants from mobile agencies, traditional agencies, venture capital firms, mobile content and service providers, mobile portals, and marketing management at brand owners. Second, based on case studies in China, this research investigates the use of mobile marketing to facilitate innovative co-creation of brand experience to cater to both individualistic as well as collective tendencies and desires amongst Chinese consumers. Through multiple case studies of the campaigns conducted by Nokia, Clean & Clear, and The North Face, and informed by in-depth interviews and document analysis, this research analyses the role of mobile media in marketing campaigns along three dimensions: the role of mobile media in content generation and consumption, the centrality of mobile media as text, tools or platforms; and the interactive environment. Specifically, the cases are organized along the spectrum from user-generated content to corporate-generated content, mobile media's role from being supplementary to it being central, and from a virtual environment to a hybrid environment. Overall, these cases demonstrate how brand owners adapt mobile media as text, tools, platforms, and environments to deliver co-creation brand experiences exploiting both individualistic as well as collective tendencies and desires amongst Chinese consumers. This research contributes to the literature on firm adoption of mobile marketing, and the role of the mobile media in facilitating co-creation experiences for Chinese consumers. It develops a model of the technological, organizational and environmental factors influencing mobile marketing adoption by firms, and provides a model explaining the role of mobile media in facilitating brand experience co-creation. The findings also demonstrate that mobile media can be leveraged to facilitate co-creation brand experience to generate added value; and meanwhile cater to both the rising individualism and the deep-seated collectivism of Chinese consumers. Empirically, it assists industry practitioners in understanding the adoption of mobile marketing in China, especially those on the supply side in order to improve their offerings and propositions. It also assists brand owners and agencies in designing their mobile marketing strategies to build consumer relationships in China.