613 resultados para Expert system


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Expert elicitation is the process of determining what expert knowledge is relevant to support a quantitative analysis and then eliciting this information in a form that supports analysis or decision-making. The credibility of the overall analysis, therefore, relies on the credibility of the elicited knowledge. This, in turn, is determined by the rigor of the design and execution of the elicitation methodology, as well as by its clear communication to ensure transparency and repeatability. It is difficult to establish rigor when the elicitation methods are not documented, as often occurs in ecological research. In this chapter, we describe software that can be combined with a well-structured elicitation process to improve the rigor of expert elicitation and documentation of the results

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Specialisation in nursing enables a nurse to focus, in much greater depth, on the requisite knowledge and skills for providing patients with the best possible care. Nephrology nursing is one such area where specialisation has evolved. The characteristic focus of practice emerged as an important feature during a study into the process of expertise acquisition in nephrology nursing practice. Using grounded theory methodology, this study involved 6 non-expert and 11 expert nurses and took place in one renal unit in New South Wales. Nephrology nursing practice was observed for 103 hours, and this was immediately followed by semi-structured interviews. The characteristic of focus was conceptualised as the nurses' centre of attention or concentration while they were undertaking nursing activities. Focus ranged from inexperienced non-expert nurses concentrating predominantly on the immediate task at hand, experienced non-expert nurses who focussed on the medium term to expert nurses who viewed actions (and their possible consequences) more broadly and in the longer term. Of significance to nursing, is how nephrology nurses alter their focus of practice as they acquire and exercise their developing expertise in this specialty.

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This paper analyses the Australian Values Education Program (VEP) within the framework of late-classical political economy. using analytical methods from systemic functional linguistics and critical discourse analysis, we demonstrate that the VEP is an unwitting restatement of the principles of ideology as developed by the likes of Destutt de Tracy and the Young Hegelians. We conclude that the sudden shock of globalisation and the post-national cultures this has entailed is in many ways similar to the shock of formal nationalism that emerged in the late-Seventeenth and early- Eighteenth centuries. The overall result of the VEP for the Australian school system is a massive procedural burden that is unlikely to produce the results at which the program is aimed.

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Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

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The major purpose of Vehicular Ad Hoc Networks (VANETs) is to provide safety-related message access for motorists to react or make a life-critical decision for road safety enhancement. Accessing safety-related information through the use of VANET communications, therefore, must be protected, as motorists may make critical decisions in response to emergency situations in VANETs. If introducing security services into VANETs causes considerable transmission latency or processing delays, this would defeat the purpose of using VANETs to improve road safety. Current research in secure messaging for VANETs appears to focus on employing certificate-based Public Key Cryptosystem (PKC) to support security. The security overhead of such a scheme, however, creates a transmission delay and introduces a time-consuming verification process to VANET communications. This paper proposes an efficient public key management system for VANETs: the Public Key Registry (PKR) system. Not only does this paper demonstrate that the proposed PKR system can maintain security, but it also asserts that it can improve overall performance and scalability at a lower cost, compared to the certificate-based PKC scheme. It is believed that the proposed PKR system will create a new dimension to the key management and verification services for VANETs.

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Georgia’s ‘National Integrity Systems’ are the institutions, laws, procedures, practices and attitudes that encourage and support integrity in the exercise of power in modern Georgian society. Integrity systems function to ensure that power is exercised in a manner that is true to the values, purposes and duties for which that power is entrusted to, or held by, institutions and individual office-holders. This report presents the results of the Open Society Institute / Open Society – Georgia Foundation funded project Georgian National Integrity Systems Assessment (GNISA), conducted in 2005–2006 by Caucasus Institute for Peace, Democracy and Development, Transparency International Georgia, Georgian Young Lawyers Association, in close cooperation with Griffith University Institute for Ethics, Governance and Law (Australia), and Tiri Group (UK), into how different elements of integrity systems interact, which combinations of institutions and reforms make for a strong integrity system, and how Georgia’s integrity systems should evolve to ensure coherence, not chaos in the way public integrity is maintained. Nevertheless all participants of the research may not share some conclusions given in the GNISA report.

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This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the role of knowledge in expert practice. Using grounded theory methodology, the study involved 17 registered nurses who were practicing in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participants' observations and interviews. Having extensive nephrology nursing knowledge was a striking characteristic of a nursing expert. Expert nurses clearly relied on and utilized extensive nephrology nursing knowledge to practice. Of importance for nursing, the results of this study indicate that domain-specific knowledge is a crucial feature of expert practice.

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Expertise in nursing has been widely studied although there have been no previous studies into what constitutes expertise in nephrology (renal) nursing. This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, provides evidence of the characteristics and practices of non-expert nephrology nurses. Using the grounded theory method, the study took place in one renal unit in New South Wales, Australia, and involved six non-expert and 11 expert nurses. Sampling was purposive then theoretical. Simultaneous data collection and analysis using participant observation, review of nursing documentation and semistructured interviews was undertaken. The study revealed a three-stage skills-acquisitive process that was identified as non-expert, experienced non-expert and expert stages. Non-expert nurses showed superficial nephrology nursing knowledge and limited experience; they were acquiring basic nephrology nursing skills and possessed a narrow focus of practice.

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As the sustainability awareness rises globally, the construction industry is under increasing pressure to improve efficiency and project delivery. The implementation of Industrialised Building Systems (IBS), for which utility components are built offsite, has the potential of promoting sustainability deliverables. This can be achieved by better control of production environment, minimising construction waste, using efficient building material energy, and stabilising work conditions. As a unique building technology, IBS has not been effectively implemented in Malaysia. Possible reasons may include limited understanding among stakeholders on the IBS potential and its relevance to sustainability. This warrants studies on the sustainability issues of IBS design, construction, operation and maintenance, A framework is being developed through research to assess performance criteria related to sustainability, which should be considered during IBS design and application in the most consistent and systematic way. This paper discusses how these sustainability performance criteria are examined in a continuing research project and the processes conducive to implementing sustainable IBS in Malaysia. Existing tools, indicators and guidelines are reviewed, analysed and grouped according to characteristics and application. The research also hopes to produce guidelines for stakeholders to incorporate sustainability issues and concepts into IBS applications.

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In Malaysia, Industrialised Building Systems (IBS) are being promoted as a potential to enhance sustainability by the building industry and government. Known elsewhere as prefabricated construction, IBS employs a combination of ready-made components in the construction of buildings that promote quality of production, enhance simplification of construction processes and minimise on-site work. The components are manufactured in a factory either on or off site. They are then positioned and assembled into building structures. The unique characteristic of IBS has the potential to respond well to the sustainability challenge facing the construction industry. Despite the promises however, IBS has yet to be effectively implemented in Malaysia. There are often misconceptions among key stakeholders about IBS applications and some of the rating schemes fail to assess IBS towards sustainability deliverables. A holistic approach to improving IBS implementation is necessary to consider sustainability perceptions on IBS among key stakeholders. As IBS design is one of the most important development phases to incorporate sustainability requirements and expectations, a framework of embedding sustainability factors into IBS design is being developed through research. This paper presents an improved IBS design process focused on sustainability, showing where and how sustainability should be assessed to improve IBS construction. The framework being developed can provide guidance and decision making assistance to not only design consultants but all relevant stakeholders by integrating sustainability concepts into IBS applications. Outcome of the research will also provide a benchmark for developing countries in adopting prefabricated construction systems.

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The purpose of this preliminary study was to determine the relevance of the categorization of the load regime data to assess the functional output and usage of the prosthesis of lower limb amputees. The objectives were a) to introduce a categorization of load regime, b) to present some descriptors of each activity, and c) to report the results for a case. The load applied on the osseointegrated fixation of one transfemoral amputee was recorded using a portable kinetic system for 5 hours. The periods of directional locomotion, localized locomotion, and stationary loading occurred 44%, 34%, and 22% of recording time and each accounted for 51%, 38%, and 12% of the duration of the periods of activity, respectively. The absolute maximum force during directional locomotion, localized locomotion, and stationary loading was 19%, 15%, and 8% of the body weight on the anteroposterior axis, 20%, 19%, and 12% on the mediolateral axis, and 121%, 106%, and 99% on the long axis. A total of 2,783 gait cycles were recorded. Approximately 10% more gait cycles and 50% more of the total impulse than conventional analyses were identified. The proposed categorization and apparatus have the potential to complement conventional instruments, particularly for difficult cases.

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We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the “ideal” algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.