914 resultados para Neurally-adjusted ventilatory assist


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The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides the SME a complex and challenging operational context. The primary aim of this research was to identify the needs of SMEs in regional areas for mobile data technologies (MDT). In this study a distinction was drawn between those respondents who were full-adopters of technology, those who were partial-adopters and those who were non-adopters and these three segments articulated different needs and requirements for MDT. Overall the needs of regional SMEs for MDT can be conceptualised into three areas where the technology will assist business practices, communication, e-commerce and security.

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The technological environment in which contemporary small- and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides for the SME a complex and challenging operational context. The primary aim of this research was to identify the needs of SMEs in regional areas for mobile data technologies (MDT). In this study a distinction was drawn between those respondents who were full-adopters of technology, those who were partial-adopters, and those who were non-adopters and these three segments articulated different needs and requirements for MDT. Overall, the needs of regional SMEs for MDT can be conceptualised into three areas where the technology will assist business practices; communication, e-commerce and security

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Given that teachers have one of the most significant influences on the educational development of gifted students, reports of negative attitudes and beliefs in popular myths about giftedness are cause for concern. It is important to understand teachers’ attitudes and beliefs to implement effective training and educational practices to improve education for gifted students. This study explored the attitudes of Australian primary school teachers (N = 126) towards intellectually gifted children and their education at eight schools. These schools could be categorised into four different classifications in regards to their involvement in gifted education. Key findings include significant associations between teachers’ attitudes and their school classifications (p < .001), and their participation in gifted and talented education inservice training (p < .001). Findings from this study suggest that further teacher training and school-wide involvement in gifted education may assist in improving attitudes towards intellectually gifted children and their education.

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Over the past decade privatised capital city airports in Australia have planned developed a range of non aviation commercial and retail land uses on airport land. Many surrounding municipalities consider this development in conflict with existing regional land use planning. Conversely airport operators are alarmed at continued urban consolidation and encroachment of incompatible regional development. Land use planning within and surrounding Australian capital city airports does not support compatible and integrated land use. It is currently a fragmented process due to: 1) current legislative and policy frameworks; 2) competing stakeholder priorities and interests; and 3) inadequate coordination and disjointed decision-making. This paper will examine privatised Australian airport development and consider three case studies to detail the context of airport and regional land use planning. A series of stakeholder workshops have served to inform the procedural dynamics and relationships between airport and regional decision-making. This exploratory research will assist in informing the knowledge gaps between aviation, airport development and broader urban land use policy. This paper will provide recommendations to enhance approaches to land use planning for airports and adjacent metropolitan regions in Australia and overseas.

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The extent of poor project outcomes is a recurring issue for construction industries worldwide. One of the main causes of these and project failure seems to be the inability of contractors to provide a high level of service quality to the project team. In Malaysia, design failures have also been identified as a further contributory factor. To overcome this, different types of subjective performance measurement have been progressively developed. These approaches are typically concerned with client satisfaction, customer satisfaction, home buyer satisfaction and occupant satisfaction, but very seldom consider contractor satisfaction. This paper examines the implications of this, and what is involved in developing satisfaction measures based on contractor perception instead of the typical sole concern with client performance. As a result, other attributes such as participants’ performance, business performance, project performance, external factors and contractor characteristics are also examined. Several potential attributes are derived from interviews among Malaysian contractors, namely: performance (direct attributes) and contractor characteristics (indirect attributes) that possibly influence contractor satisfaction levels. These attributes are then developed to improve the existing conceptual framework. The developed framework is expected to help the project team in performing projects more efficiently, maintaining service quality and improving relationships between participants. In addition, the findings of the paper should assist contractors enhance competitiveness, improve their image and create more job opportunities in the future.

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Before the Global Financial Crisis many providers of finance had growth mandates and actively pursued development finance deals as a way of gaining higher returns on funds with regular capital turnover and re-investment possible. This was able to be achieved through high gearing and low presales in a strong market. As asset prices fell, loan covenants breached and memories of the 1990’s returned, banks rapidly adjusted their risk appetite via retraction of gearing and expansion of presale requirements. Early signs of loosening in bank credit policy are emerging, however parties seeking development finance are faced with a severely reduced number of institutions from which to source funding. The few institutions that are lending are filtering out only the best credit risks by way of constrictive credit conditions including: low loan to value ratios, the corresponding requirement to contribute high levels of equity, lack of support in non-prime locations and the requirement for only borrowers with well established track records. In this risk averse and capital constrained environment, the ability of developers to proceed with real estate developments is still being constrained by their inability to obtain project finance. This paper will examine the pre and post GFC development finance environment. It will identify the key lending criteria relevant to real estate development finance and will detail the related changes to credit policies over this period. The associated impact to real estate development projects will be presented, highlighting the significant constraint to supply that the inability to obtain finance poses.

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Calibration of movement tracking systems is a difficult problem faced by both animals and robots. The ability to continuously calibrate changing systems is essential for animals as they grow or are injured, and highly desirable for robot control or mapping systems due to the possibility of component wear, modification, damage and their deployment on varied robotic platforms. In this paper we use inspiration from the animal head direction tracking system to implement a self-calibrating, neurally-based robot orientation tracking system. Using real robot data we demonstrate how the system can remove tracking drift and learn to consistently track rotation over a large range of velocities. The neural tracking system provides the first steps towards a fully neural SLAM system with improved practical applicability through selftuning and adaptation.

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Background Colorectal cancer survivors may suffer from a range of ongoing psychosocial and physical problems that negatively impact on quality of life. This paper presents the study protocol for a novel telephone-delivered intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors. Methods/Design Approximately 350 recently diagnosed colorectal cancer survivors will be recruited through the Queensland Cancer Registry and randomised to the intervention or control condition. The intervention focuses on symptom management, lifestyle and psychosocial support to assist participants to make improvements in lifestyle factors (physical activity, healthy diet, weight management, and smoking cessation) and health outcomes. Participants will receive up to 11 telephone-delivered sessions over a 6 month period from a qualified health professional or 'health coach'. Data collection will occur at baseline (Time 1), post-intervention or six months follow-up (Time 2), and at 12 months follow-up for longer term effects (Time 3). Primary outcome measures will include physical activity, cancer-related fatigue and quality of life. A cost-effective analysis of the costs and outcomes for survivors in the intervention and control conditions will be conducted from the perspective of health care costs to the government. Discussion The study will provide valuable information about an innovative intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors.

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The aim of this chapter is to provide you with a basic understanding of epidemiology, and to introduce you to some of the epidemiological concepts and methods used by researchers and practitioners working in public health. It is hoped that you will recognise how the principles and practice of epidemiology help to provide information and insights that can be used to achieve better health outcomes for all. Epidemiology is fundamental to preventive medicine and public health policy. Rather than examine health and illness on an individual level, as clinicians do, epidemiologists focus on communities and population health issues. The word epidemiology is derived from the Greek epi (on, upon), demos (the people) and logos (the study of). Epidemiology, then, is the study of that which falls upon the people. Its aims are to describe health-related states or events, and through systematic examination of the available information, attempt to determine their causes. The ultimate goal is to contribute to prevention of disease and disability and to delay mortality. The primary question of epidemiology is: why do certain diseases affect particular population groups? Drawing upon statistics, the social and behavioural sciences, the biological sciences and medicine, epidemiologists collect and interpret information to assist in the prevention of new cases of disease, eradicate existing disease and prolong the lives of people who have disease.

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This thesis addresses computational challenges arising from Bayesian analysis of complex real-world problems. Many of the models and algorithms designed for such analysis are ‘hybrid’ in nature, in that they are a composition of components for which their individual properties may be easily described but the performance of the model or algorithm as a whole is less well understood. The aim of this research project is to after a better understanding of the performance of hybrid models and algorithms. The goal of this thesis is to analyse the computational aspects of hybrid models and hybrid algorithms in the Bayesian context. The first objective of the research focuses on computational aspects of hybrid models, notably a continuous finite mixture of t-distributions. In the mixture model, an inference of interest is the number of components, as this may relate to both the quality of model fit to data and the computational workload. The analysis of t-mixtures using Markov chain Monte Carlo (MCMC) is described and the model is compared to the Normal case based on the goodness of fit. Through simulation studies, it is demonstrated that the t-mixture model can be more flexible and more parsimonious in terms of number of components, particularly for skewed and heavytailed data. The study also reveals important computational issues associated with the use of t-mixtures, which have not been adequately considered in the literature. The second objective of the research focuses on computational aspects of hybrid algorithms for Bayesian analysis. Two approaches will be considered: a formal comparison of the performance of a range of hybrid algorithms and a theoretical investigation of the performance of one of these algorithms in high dimensions. For the first approach, the delayed rejection algorithm, the pinball sampler, the Metropolis adjusted Langevin algorithm, and the hybrid version of the population Monte Carlo (PMC) algorithm are selected as a set of examples of hybrid algorithms. Statistical literature shows how statistical efficiency is often the only criteria for an efficient algorithm. In this thesis the algorithms are also considered and compared from a more practical perspective. This extends to the study of how individual algorithms contribute to the overall efficiency of hybrid algorithms, and highlights weaknesses that may be introduced by the combination process of these components in a single algorithm. The second approach to considering computational aspects of hybrid algorithms involves an investigation of the performance of the PMC in high dimensions. It is well known that as a model becomes more complex, computation may become increasingly difficult in real time. In particular the importance sampling based algorithms, including the PMC, are known to be unstable in high dimensions. This thesis examines the PMC algorithm in a simplified setting, a single step of the general sampling, and explores a fundamental problem that occurs in applying importance sampling to a high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of the estimate under conditions on the importance function. Additionally, the exponential growth of the asymptotic variance with the dimension is demonstrated and we illustrates that the optimal covariance matrix for the importance function can be estimated in a special case.

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Purpose – One of the critical issues for change management, particularly in relation to the implementation of new technologies, is the existence of prior knowledge and established mental models which may hinder change efforts. Understanding unlearning and how it might assist during organizational change is a way to address this resistance. The purpose of this paper is to present research designed to identify specific factors that facilitate unlearning. Design/methodology/approach – Drawing together issues identified as potential influencers of unlearning, a survey questionnaire was developed and administered in an Australian corporation undergoing large-scale change due to the implementation of an enterprise information system. The results were analyzed to identify specific factors that impact on unlearning. Findings – Findings from this paper identify factors that hinder or help the unlearning process during times of change including understanding the need for change, the level of organizational support and training, assessment of the change, positive experience and informal support, the organization's history of change, individual's prior outlooks, and individuals' feelings and expectations. Research limitations/implications – The use of only one organization does not allow for comparisons between organizations of different sizes, cultures or industries and therefore extension of this research is recommended. Practical implications – For practitioners, this paper provides specific elements at both the level of individuals and the organization that need to be considered for optimal unlearning during times of change. Originality/value – Previous literature on unlearning has been predominantly conceptual and theoretical. These empirical findings serve to further an earlier model based on qualitative research into potential influencers of unlearning.

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Purpose: The purpose of this paper is to explore the role of cross-functional teams in the alignment between system effectiveness and operational effectiveness after the implementation of enterprise information systems (EIS). In addition, it aims to explore the contribution of cross-functional teams to improvement in operational performance. ---------- Design/methodology/approach: The research uses a combination of qualitative and quantitative methods, in a two-stage methodological approach, to investigate the influence of cross-functional teams on the alignment between system effectiveness and operational effectiveness and the impact of the stated alignment on the improvement in operational performance. ---------- Findings: Initial findings suggest that factors stemming from system effectiveness and the performance objectives stemming from operational effectiveness are important and significantly well correlated factors that promote the alignment between the effectiveness of technological implementation and the effectiveness of operations. In addition, confirmatory factor analysis has been used to find the structural relationships and provide explanations for the stated alignment and the contribution of cross-functional teams to the improvement in operational performance. ---------- Research limitations/implications: The principal limitation of this study is its small sample size. ---------- Practical implications: Cross-functional teams have been used by many organisations as a way of involving expertise from different functional areas in the implementation of innovative technologies. An appropriate use of the dimensions that emerged from this research, in the context of cross-functional teams, will assist organisations to properly utilise cross-functional teams with the aim of improving operational performance. ---------- Originality/value: The paper presents a new approach to measure the effectiveness of EIS implementation by adding new dimensions to measure it.

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Objectives: To evaluate the validity, reliability and responsiveness of EDC using the WOMAC® NRS 3.1 Index on Motorola V3 mobile phones. ---------- Methods: Patients with osteoarthritis (OA) undergoing primary unilateral hip or knee joint replacement surgery were assessed pre-operatively and 3-4 months post-operatively. Patients completed the WOMAC® Index in paper (p-WOMAC®) and electronic (m-WOMAC®) format in random order. ---------- Results: 24 men and 38 women with hip and knee OA participated and successfully completed the m-WOMAC® questionnaire. Pearson correlations between the summated total index scores for the p-WOMAC® and m-WOMAC® pre- and post-surgery were 0.98 and 0.99 (p<0.0001). There was no clinically important or statistically significant between-method difference in the adjusted total summated scores, pre- and post-surgery (adjusted mean difference = 4.44, p = 0.474 and 1.73, p = 0.781). Internal consistency estimates of m-WOMAC® reliability were 0.87 – 0.98. The m-WOMAC® detected clinically important, statistically significant (p<0.0001) improvements in pain, stiffness, function and total index score. ---------- Conclusions: Sixty-two patients with hip and knee OA successfully completed EDC by Motorola V3 mobile phone using the m-WOMAC® NRS3.1 Index; completion times averaging only 1-1.5 minutes longer than the p-WOMAC® Index. Data were successfully and securely transmitted from patients in Australia to a server in the USA. There was close agreement and no significant differences between m-WOMAC® and p-WOMAC® scores. This study confirms the validity, reliability and responsiveness of the Exco InTouch engineered, Java-based m-WOMAC® Index application. EDC with the m-WOMAC® Index provides unique opportunities for using quantitative measurement in clinical research and practice.

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Powerful brands create meaningful images in the minds of customers (Keller, 1993). A strong brand image and reputation enhances differentiation and has a positive influence on buying behaviour (Gordon et al., 1993; McEnally and de Chernatony, 1999). While the power of branding is widely acknowledged in consumer markets, the nature and importance of branding in industrial markets remains under-researched. Many business-to-business (B2B) strategists have claimed brand-building belongs in the consumer realm. They argue that industrial products do not need branding as it is confusing and adds little value to functional products (Collins, 1977; Lorge, 1998; Saunders and Watt, 1979). Others argue that branding and the concept of brand equity however are increasingly important in industrial markets, because it has been shown that what a brand means to a buyer can be a determining factor in deciding between industrial purchase alternatives (Aaker, 1991). In this context, it is critical for suppliers to initiate and sustain relationships due to the small number of potential customers (Ambler, 1995; Webster and Keller, 2004). To date however, there is no model available to assist B2B marketers in identifying and measuring brand equity. In this paper, we take a step in that direction by operationalising and empirically testing a prominent brand equity model in a B2B context. This makes not only a theoretical contribution by advancing branding research, but also addresses a managerial need for information that will assist in the assessment of industrial branding efforts.

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In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.