345 resultados para Akiba ben Joseph, Alphabet of.


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This article examines the place of Australian and local content regulation in the new media policy framework proposed by the Convergence Review. It outlines the history of Australian content regulation and the existing policy framework, before going on to detail some of the debates around Australian content during the Review. The final section analyses the relevant recommendations in the Convergence Review Final Report, and highlights some issues and problems that may arise in the new framework.

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In recent years, de-regulation in the airline industry and the introduction of low-cost carriers have conspired to produce significant changes in the airport landscape. From an airport operator’s perspective, one of the most notable has been the shift of capital revenue from traditional airline sources (through exclusive use, long term lease arrangements) to passengers (by way of fees collected from ticket sales). As a result of these developments, passengers have become recognized as major stakeholders who have the power to influence airport profitability. This link between passenger satisfaction and profitability has generated industry wide interest in the “passenger experience”. In this paper, we define the factors which influence passenger experience, namely (a) artifacts, (b) services and (c) the terminal building, and explore the challenges that exist in the current approaches to terminal design. On the basis of these insights, we propose a conceptual model of passenger experience, and motivate its use as a framework for further research into improving terminal design from a passenger oriented perspective.

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Airports are vital sources of income to a country and city. Airports are often understood from a management perspective, rather than a passenger perspective. As passengers are a vital customer of airports, a passenger perspective can provide a novel approach in understanding and improving the airport experience. This paper focuses on the study of passenger experiences at airports. This research is built on recent investigations of passenger discretionary activities in airports by the authors, which have provided a new perspective on understanding the airport experience. The research reported in this paper involves field studies at three Australian airports. Seventy one people who had impending travel were recruited to take part in the field study. Data collection methods included video-recorded observation and post-travel interviews. Observations were coded and a list of activities performed was developed. These activities were then classified into an activity taxonomy, depending on the activity location and context. The study demonstrates that there is a wide range of activities performed by passengers as they navigate through the airport. The emerging activity taxonomy consists of eight categories. They include: (i) processing (ii) preparatory (iii) consumptive (iv) social (v) entertainment (vi) passive (vii) queuing and (viii) moving. The research provides a novel perspective to understand the experience of passenger at international airports. It has been applied in airports to improve passenger processing and reduce waiting times. The significance of the taxonomy lies in its potential application to airport terminal design and how it can be utilised to understand and improve the passenger experience.

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Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

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Diabetes is one of the greatest public health challenges to face Australia. It is already Australia’s leading cause of kidney failure, blindness (in those under 60 years) and lower limb amputation, and causes significant cardiovascular disease. Australia’s diabetes amputation rate is one of the worst in the developed world, and appears to have significantly increased in the last decade, whereas some other diabetes complication rates appear to have decreased. This paper aims to compare the national burden of disease for the four major diabetes-related complications and the availability of government funding to combat these complications, in order to determine where diabetes foot disease ranks in Australia. Our review of relevant national literature indicates foot disease ranks second overall in burden of disease and last in evidenced-based government funding to combat these diabetes complications. This suggests public funding to address foot disease in Australia is disproportionately low when compared to funding dedicated to other diabetes complications. There is ample evidence that appropriate government funding of evidence-based care improves all diabetes complication outcomes and reduces overall costs. Numerous diverse Australian peak bodies have now recommended similar diabetes foot evidence-based strategies that have reduced diabetes amputation rates and associated costs in other developed nations. It would seem intuitive that “it’s time” to fund these evidence-based strategies for diabetes foot disease in Australia as well.

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This paper studies time integration methods for large stiff systems of ordinary differential equations (ODEs) of the form u'(t) = g(u(t)). For such problems, implicit methods generally outperform explicit methods, since the time step is usually less restricted by stability constraints. Recently, however, explicit so-called exponential integrators have become popular for stiff problems due to their favourable stability properties. These methods use matrix-vector products involving exponential-like functions of the Jacobian matrix, which can be approximated using Krylov subspace methods that require only matrix-vector products with the Jacobian. In this paper, we implement exponential integrators of second, third and fourth order and demonstrate that they are competitive with well-established approaches based on the backward differentiation formulas and a preconditioned Newton-Krylov solution strategy.

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This paper presents an experimental study on the vibration signal patterns associated with a simulated piston slap test of a four-cylinder diesel engine. It is found that a simulated worn-off piston results in an increase in vibration RMS peak amplitudes associated with the major mechanical events of the corresponding cylinder (i.e., inlet and exhaust valve closing and combustion of Cylinder 1). This then led to an increase of overall vibration amplitude of the time domain statistical features such as RMS, Crest Factor, Skewness and Kurtosis in all loading conditions. The simulated worn-off piston not only increased the impact amplitude of piston slap during the engine combustion, it also produced a distinct impulse response during the air induction stroke of the cylinder attributing to an increase of lateral impact force as a result of piston reciprocating motion and the increased clearance between the worn-off piston and the cylinder. The unique signal patterns of piston slap disclosed in this paper can be utilized to assist in the development of condition monitoring tools for automated diagnosis of similar diesel engine faults in practical applications.

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Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.

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Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

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One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

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Knowing, measuring and understanding media audiences have become a multi-billion dollar business. But the convention that underpins that business, audience ratings, is in crisis. Rating the Audience is the first book to show why and how audience ratings research became a convention, an agreement, and the first to interrogate the ways that agreement is now under threat. Taking a historical approach, the book looks at the evolution of audience ratings and the survey industry. It goes on to analyse today's media environment, looking at the role of the internet and the increased difficulties it presents for measuring audiences. The book covers all the major players and controversies, such as Facebook's privacy rulings and Google's alliance with Nielsen. Offering the first real comparative study, it will be critical for media students and professionals.

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Typical flow fields in a stormwater gross pollutant trap (GPT) with blocked retaining screens were experimentally captured and visualised. Particle image velocimetry (PIV) software was used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. A technique was developed to apply the Image Based Flow Visualization (IBFV) algorithm to the experimental raw dataset generated by the PIV software. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding gross pollutant capture and retention within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate specific areas and identify the flow features within the GPT.

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This article discusses the production history and social context of the 1981 Australian film, The Killing of Angel Street, directed by Donald Crombie. The article is Part 21 in a series on the National Film and Sound Archive's Kodak/Atlab Cinema Collection.

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This chapter reviews aspects of the challenge of reviewing and reforming Indonesian practice within state asset management law and policy specifically related to public housing, public buildings, parklands, and vacant land. A critical issue in beginning this review is how Indonesia currently conceptualizes the notion of asset governance and how this meaning is embodied in recent changes in law and policy and importantly in options for future change. This chapter discusses the potential complexities uniquely Indonesian characteristics such as decentralisation and regional autonomy regime, political history, and bureaucratic culture.

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An important component of current models for interstellar and circumstellar evolution is the infrared (IR)spectral data collected from stellar outflows around oxygen-rich stars and from the general interstellar medium [1]. IR spectra from these celestial bodies are usually interpreted as showing the general properties of sub-micron sized silicate grains [2]. Two major features at 10 and 20 microns are reasonably attributed to amorphous olivine or pyroxene (e.g. Mg2Si04 or MgSi03) on the basis of comparisons with natural standards and vapor condensed silicates [3-6]. In an attempt to define crystallisation rates for spectrally amorphous condensates, Nuth and Donn [5] annealed experimentally produced amorphous magnesium silicate smokes at 1000K. On analysing these smokes at various annealing times, Nuth and Donn [5] showed that changes in crystallinity measured by bulk X-ray diffraction occured at longer annealing times (days) than changes measured by IR spectra (a few hours). To better define the onset of crystallinity in these magnesium silicates, we have examined each annealed product using a JEOL 1OOCX analytical electron microscope (AEM). In addition, the development of chemical diversity with annealing has been monitored using energy dispersive spectroscopy of individual grains from areas <20nm in diameter. Furthermore, the crystallisation kinetics of these smokes under ambient, room temperature conditions have been examined using bulk and fourier transform infrared (FTIR)spectra.