55 resultados para Eun Yung

em Queensland University of Technology - ePrints Archive


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We propose a new password-based 3-party protocol with a formal security proof in the standard model. Under reasonable assumptions we show that our new protocol is more efficient than the recent protocol of Abdalla and Pointcheval (FC 2005), proven in the random oracle model. We also observe some limitations in the model due to Abdalla, Fouque and Pointcheval (PKC 2005) for proving security of such protocols.

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This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

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In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

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The field was the curation of cross-cultural new media/ digital media practices within large-scale exhibition practices in China. The context was improved understandings of the intertwining of the natural and the artificial with respect to landscape and culture, and their consequent effect on our contemporary globalised society. The research highlighted new languages of media art with respect to landscape and their particular underpinning dialects. The methodology was principally practice-led. --------- The research brought together over 60 practitioners from both local and diasporic Asian, European and Australian cultures for the first time within a Chinese exhibition context. Through pursuing a strong response to both cultural displacement and re-identification the research forged and documented an enduring commonality within difference – an agenda further concentrated through sensitivities surrounding that year’s Beijing’s Olympics. In contrast to the severe threats posed to the local dialects of many of the world’s spoken and written languages the ‘Vernacular Terrain’ project evidenced that many local creative ‘dialects’ of the environment-media art continuum had indeed survived and flourished. --------- The project was co-funded by the Beijing Film Academy, QUT Precincts, IDAProjects and Platform China Art Institute. A broad range of peer-reviewed grants was won including from the Australia China Council and the Australian Embassy in China. Through invitations from external curators much of the work then traveled to other venues including the Block Gallery at QUT and the outdoor screens at Federation Square, Melbourne. The Vernacular Terrain catalogue featured a comprehensive history of the IDA project from 2000 to 2008 alongside several major essays. Due to the reputation IDA Projects had established, the team were invited to curate a major exhibition showcasing fifty new media artists: The Vernacular Terrain, at the prestigious Songzhang Art Museum, Beijing in Dec 07-Jan 2008. The exhibition was designed for an extensive, newly opened gallery owned by one of China's most important art historians Li Xian Ting. This exhibition was not only this gallery’s inaugural non-Chinese curated show but also the Gallery’s first new media exhibition. It included important works by artists such as Peter Greenway, Michael Roulier, Maleonn and Cui Xuiwen. --------- Each artist was chosen both for a focus upon their own local environmental concerns as well as their specific forms of practice - that included virtual world design, interactive design, video art, real time and manipulated multiplayer gaming platforms and web 2.0 practices. This exhibition examined the interconnectivities of cultural dialogue on both a micro and macro scale; incorporating the local and the global, through display methods and design approaches that stitched these diverse practices into a spatial map of meanings and conversations. By examining the contexts of each artist’s practice in relationship to the specificity of their own local place and prevailing global contexts the exhibition sought to uncover a global vernacular. Through pursuing this concentrated anthropological direction the research identified key themes and concerns of a contextual language that was clearly underpinned by distinctive local ‘dialects’ thereby contributing to a profound sense of cross-cultural association. Through augmentation of existing discourse the exhibition confirmed the enduring relevance and influence of both localized and globalised languages of the landscape-technology continuum.

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Scaffolds manufactured from biological materials promise better clinical functionality, providing that characteristic features are preserved. Collagen, a prominent biopolymer, is used extensively for tissue engineering applications, because its signature biological and physico-chemical properties are retained in vitro preparations. We show here for the first time that the very properties that have established collagen as the leading natural biomaterial are lost when it is electro-spun into nano-fibres out of fluoroalcohols such as 1,1,1,3,3,3-hexafluoro-2-propanol or 2,2,2-trifluoroethanol. We further identify the use of fluoroalcohols as the major culprit in the process. The resultant nano-scaffolds lack the unique ultra-structural axial periodicity that confirms quarter-staggered supramolecular assemblies and the capacity to generate second harmonic signals, representing the typical crystalline triple-helical structure. They were also characterised by low denaturation temperatures, similar to those obtained from gelatin preparations ( p > 0.05). Likewise, circular dichroism spectra revealed extensive denaturation of the electro-spun collagen. Using pepsin digestion in combination with quantitative SDS-PAGE, we corroborate great losses of up to 99% of triple-helical collagen. In conclusion, electro-spinning of collagen out of fluoroalcohols effectively denatures this biopolymer, and thus appears to defeat its purpose, namely to create biomimetic scaffolds emulating the collagen structure and function of the extracellular matrix.

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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.