820 resultados para CASE SERIES


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Sri Lanka has one of the highest rates of natural disasters and violent conflicts in the world. Yet there is a lack of research on its unique socio-cultural characteristics that determine an individual's cognitive and behavioural responses to distressing encounters. This study extends Goh, Sawang and Oei's (2010) revised transactional model to examine the cognitive and behavioural processes of occupational stress experience in the collectivistic society of Sri Lanka. A time series survey was used to measure the participant's stress-coping process. Using the revised transactional model and path analysis, a unique Sri Lankan model is identified that provides theoretical insights on the revised transactional model, and sheds light on socio-cultural dimensions of occupational stress and coping, thus equipping practitioners with a sound theoretical basis for the development of stress management programs in the workplace.

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Retirement villages are regarded as a viable accommodation option for the ever increasing ageing population in Australia. This paper aims to identify sustainability features and practices adopted in retirement villages and associated benefits to improve the life quality of older people. A case study of an existing retirement village 10kms from Brisbane CBD was conducted involving a series of interviews with the village managers and residents together with documents relating to the village's operations and activities. The environmentally friendly features that were incorporated into the development mainly include green design for the site and floor plan and waste management in daily operation. More importantly, a variety of facilities are provided to strengthen the social engagement and interactions among the residents. Additionally, different daily services are provided to assist independent living and improve the health conditions of residents. Also, the relatively low vacancy rate in this village indicates that these sustainability features offer good value of money for the residents. The paper provides a first look at sustainable retirement villages in terms of triple bottom line sustainability with emphasis on social aspects, reveals the importance in maintaining an appropriate balance, and provides examples of how this can be achieved in practice.

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Introduction The presentation of pulmonary embolism to the emergency department (ED) can prove challenging because of the myriad of potential disease processes that mimic its signs and symptoms. The incidence of pulmonary embolism and indeed the mortality associated with it is relatively high. Early diagnosis and treatment is crucial in off-setting the potential deleterious effects associated with this condition. The aim of this article is to present a nursing case review of a patient presenting to the ED with a diagnosis of pulmonary embolism. Method We chose to use a case review to highlight the nursing and medical care that was provided for a patient who presented to the emergency department acutely with dyspnoea, chest pain and pyrexia. The use of case reviews are useful in reporting unusual or rare cases and this format is typically seen more in medicine than in nursing. They can naturally take one of two formats—a single case report or a series of case reports; in this case we opted to report on a single case. Discussion The gentleman in question was an ambulance admissionto the ED with a three day history of chest pain, shortness of breath and one episode of syncope which brought him to the ED. Over the course of his admission a variety of treatment modalities were used successfully to alleviate the problem. More notable from a nursing perspective was the use of diagnostic tools as an interpretation to guide his care and provide a platform from which a deeper understanding and appreciation of the intricacies the critically ill patient often presents. Conclusion We found the use of case review very enlightening in understanding the disease process and the decision-making that accompanies this. Whilst our patient was successfully rehabilitated home, we learnt a lot from the experience which has been most beneficial in supporting our understanding of pulmonary embolism.

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Mocombe and Tomlin’s Language, Literacy, and Pedagogy in Postindustrial Societies: The Case of Black Academic Underachievement is part of the Routledge Research in Education series. The purpose of the work is to set out a theoretical framework for understanding the black/white academic achievement gap in the age of globalisation and post-industrialism. The authors use each chapter to develop an explanation for the persistent black/white academic achievement gap, by theorising that the gap is an epiphenomenon of global capitalist, post-industrial structures, reinforced by education as an apparatus of the system...

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If you had to argue for the merits of one Australian book, one piece of writing, what would it be? Welcome to our occasional series in which our authors make the case for a work of their choosing. See the end of this article for information on how to get involved. The late Johnny Warren – also known as Captain Socceroo – was a legend of Australian football. He is fondly remembered as a player, coach, administrator, writer and broadcaster, and the award for the best player in the A-League is named the Johnny Warren Medal. And yet his 2002 biography Sheilas, Wogs and Poofters, an Incomplete Biography of Johnny Warren and Soccer in Australia, which he co-wrote with Andy Harper and Josh Whittington, seems eternally destined to raise eyebrows...

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Background Qualitative research is increasingly being recognised as a vital aspect of primary healthcare research. Teaching and learning how to conduct qualitative research is especially important for general practitioners and other clinicians in the professional educational setting. This article examines a case study of postgraduate professional education in qualitative research for clinicians, for the purpose of enabling a robust discussion around teaching and learning in medicine and the health sciences. Method A series of three workshops was delivered for primary healthcare academics. The workshops were evaluated using a quantitative survey and qualitative free-text responses to enable descriptive analyses. Results Participants found qualitative philosophy and theory the most difficult areas to engage with, and learning qualitative coding and analysis was considered the easiest to learn. Discussion Key elements for successful teaching were identified, including the use of adult learning principles, the value of an experienced facilitator and an awareness of the impact of clinical subcultures on learning.

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Public private partnerships (PPPs) have been adopted widely to provide public facilities and services. According to the PPP agreement, PPP projects would be transferred to the public sector. However, problems related to the subsequent management of ongoing PPP projects have not been studied thoroughly. Residual value risk (RVR) can occur if the public sector cannot obtain the project in the desired conditions as required in the agreement when a project is being transferred. RVR has been identified as an important risk in PPPs and has greatly influenced the outputs of the projects. In order to further observe the change of residual value (RV) during the process of PPP projects and to reveal the internal mechanism for reducing the RVR, a comparative case study of two PPP projects in mainland China and Hong Kong was conducted. Based on the case study, different factors leading to RVR and a series of key risk indicators (KRIs) were identified. The comparison demonstrates that RVR is an important risk that could influence the success of PPP projects. The cumulative effects during the concession period can play significant roles in the occurrence of RVR. Additionally, the cumulative effects in different cases can make the RVR different because of different stakeholders’ efforts on the projects and ways to treat RVR. Finally, alternatives for the public sector to treat RVR were proposed. The findings of this research can reduce RVR and improve the performance of PPP projects.

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This paper investigates several competing procedures for computing the prices of vanilla European options, such as puts, calls and binaries, in which the underlying model has a characteristic function that is known in semi-closed form. The algorithms investigated here are the half-range Fourier cosine series, the half-range Fourier sine series and the full-range Fourier series. Their performance is assessed in simulation experiments in which an analytical solution is available and also for a simple affine model of stochastic volatility in which there is no closed-form solution. The results suggest that the half-range sine series approximation is the least effective of the three proposed algorithms. It is rather more difficult to distinguish between the performance of the halfrange cosine series and the full-range Fourier series. However there are two clear differences. First, when the interval over which the density is approximated is relatively large, the full-range Fourier series is at least as good as the half-range Fourier cosine series, and outperforms the latter in pricing out-of-the-money call options, in particular with maturities of three months or less. Second, the computational time required by the half-range Fourier cosine series is uniformly longer than that required by the full-range Fourier series for an interval of fixed length. Taken together,these two conclusions make a case for pricing options using a full-range range Fourier series as opposed to a half-range Fourier cosine series if a large number of options are to be priced in as short a time as possible.

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This report summarises the findings of a case study on Queensland’s New Generation Rollingstock (NGR) Project carried out as part of SBEnrc Project 2.34 Driving Whole-of-life Efficiencies through BIM and Procurement. This case study is one of three exemplar projects studied in order to leverage academic research in defining indicators for measuring tangible and intangible benefits of Building Information Modelling (BIM) across a project’s life-cycle in infrastructure and buildings. The NGR is an AUD 4.4 billion project carried out under an Availability Payment Public-Private Partnership (PPP) between the Queensland Government and the Bomabardier-led QTECTIC consortium comprising Bombardier Transportation, John Laing, ITOCHU Corporation and Aberdeen Infrastructure Investments. BIM has been deployed on the project from conceptual stages to drive both design and the currently ongoing construction at the Wulkuraka Project Site. This case study sourced information from a series of semi-structured interviews covering a cross-section of key stakeholders on the project. The present research identified 25 benefits gained from implementing BIM processes and tools. Some of the most prominent benefits were those leading to improved outcomes and higher customer satisfaction such as improved communications, data and information management, and coordination. There were also a number of expected benefits for future phases such as: • Improved decision making through the use of BIM for managing assets • Improved models through BIM maturity • Better utilisation of BIM for procurement on similar future projects • New capacity to specify the content of BIM models within contracts There were also three benefits that were expected to have been achieved but were not realised on the NGR project. These were higher construction information quality levels, better alignment in design teams as well as project teams, and capability improvements in measuring the impact of BIM on construction safety. This report includes individual profiles describing each benefit as well as the tools and processes that enabled them. Four key BIM metrics were found to be currently in use and six more were identified as potential metrics for the future. This case study also provides insights into challenges associated with implementing BIM on a project of the size and complexity of the NGR. Procurement aspects and lessons learned for managers are also highlighted, including a list of recommendations for developing a framework to assess the benefits of BIM across the project life-cycle.

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Road traffic accidents are a large problem everywhere in the world. However, regional differences in traffic safety between countries are considerable. For example, traffic safety records are much worse in Southern Europe and the Middle East than in Northern and Western Europe. Despite the large regional differences in traffic safety, factors contributing to different accident risk figures in different countries and regions have remained largely unstudied. The general aim of this study was to investigate regional differences in traffic safety between Southern European/Middle Eastern (i.e., Greece, Iran, Turkey) and Northern/Western European (i.e., Finland, Great Britain, The Netherlands) countries and to identify factors related to these differences. We conducted seven sub-studies in which I applied a traffic culture framework, including a multi-level approach, to traffic safety. We used aggregated level data (national statistics), surveys among drivers, and data on traffic accidents and fatalities in the analyses. In the first study, we investigated the influence of macro level factors (i.e., economic, societal, and cultural) on traffic safety across countries. The results showed that a high GNP per capita and conservatism correlated with a low number of traffic fatalities, whereas a high degree of uncertainty avoidance, neuroticism, and egalitarianism correlated with a high number of traffic fatalities. In the second, third, and fourth studies, we examined whether the conceptualisation of road user characteristics (i.e., driver behaviour and performance) varied across traffic cultures and how these factors determined overall safety, and the differences between countries in traffic safety. The results showed that the factorial agreement for driver behaviour (i.e., aggressive driving) and performance (i.e., safety skills) was unsatisfactory in Greece, Iran, and Turkey, where the lack of social tolerance and interpersonal aggressive violations seem to be important characteristics of driving. In addition, we found that driver behaviour (i.e., aggressive violations and errors) mediated the relationship between culture/country and accidents. Besides, drivers from "dangerous" Southern European countries and Iran scored higher on aggressive violations and errors than did drivers from "safe" Northern European countries. However, "speeding" appeared to be a "pan-cultural" problem in traffic. Similarly, aggressive driving seems largely depend on road users' interactions and drivers' interpretation (i.e., cognitive biases) of the behaviour of others in every country involved in the study. Moreover, in all countries, a risky general driving style was mostly related to being young and male. The results of the fifth and sixth studies showed that among young Turkish drivers, gender stereotypes (i.e., masculinity and femininity) greatly influence driver behaviour and performance. Feminine drivers were safety-oriented whereas masculine drivers were skill-oriented and risky drivers. Since everyday driving tasks involve not only erroneous (i.e., risky or dangerous driving) or correct performance (i.e., normal habitual driving), but also "positive" driver behaviours, we developed a reliable scale for measuring "positive" driver behaviours among Turkish drivers in the seventh study. Consequently, I revised Reason's model [Reason, J. T., 1990. Human error. Cambridge University Press: New York] of aberrant driver behaviour to represent a general driving style, including all possible intentional behaviours in traffic while evaluating the differences between countries in traffic safety. The results emphasise the importance of economic, societal and cultural factors, general driving style and skills, which are related to exposure, cognitive biases as well as age, sex, and gender, in differences between countries in traffic safety.

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Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

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This paper investigates the long- and short-run relationships between energy consumption and economic growth in Australia using the bound testing and the ARDL approach. The analytical framework utilized in this paper includes both production and demand side models and a unified model comprising both production and demand side variables. The energy-GDP relationships are investigated at aggregate as well as several disaggregated energy categories, such as coal, oil, gas and electricity. The possibilities of one or more structural break(s) in the data series are examined by applying the recent advances in techniques. We find that the results of the cointegration tests could be affected by the structural break(s) in the data. It is, therefore, crucial to incorporate the information on structural break(s) in the subsequent modelling and inferences. Moreover, neither the production side nor the demand side framework alone can provide sufficient information to draw an ultimate conclusion on the cointegration and causal direction between energy and output. When alternative frameworks and structural break(s) in time series are explored properly, strong evidence of a bidirectional relationship between energy and output can be observed. The finding is true at both the aggregate and the disaggregate levels of energy consumption.

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In this paper we examine the effect of technology on economic growth in Zimbabwe over the period 1975–2014 whilst accounting for structural breaks. We use the extended Cobb–Douglas type Solow (Q J Econ 70(1):65–94, 1956) framework and the ARDL bounds procedure to examine cointegration and short run and long run effects. Using unit root tests, we note that structural changes in Zimbabwe are generally marked by the period 1982 onwards. We find that mobile technology has a positive short-run (0.09 %) and long-run (0.08 %) impact on the output per capita. The structural changes post-1982 periods show positive impact in the short-run (0.06) and the long-run (0.09), whereas the coefficient of trend in the short-run (−0.03) and the long-run (−0.04) is negative. The Granger non-causality test shows a unidirectional causality from capital stock (investment) per capita to output per capita and a bi-directional causality between mobile cellular technology and output per capita. The plausible reasons for estimated magnitude effects and the direction of causality are explained for policy deliberation.

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This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

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This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.