696 resultados para correlation modelling
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This thesis targets on a challenging issue that is to enhance users' experience over massive and overloaded web information. The novel pattern-based topic model proposed in this thesis can generate high-quality multi-topic user interest models technically by incorporating statistical topic modelling and pattern mining. We have successfully applied the pattern-based topic model to both fields of information filtering and information retrieval. The success of the proposed model in finding the most relevant information to users mainly comes from its precisely semantic representations to represent documents and also accurate classification of the topics at both document level and collection level.
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This study is seeking to investigate the effect of non-thermal plasma technology in the abatement of particulate matter (PM) from the actual diesel exhaust. Ozone (O3) strongly promotes PM oxidation, the main product of which is carbon dioxide (CO2). PM oxidation into the less harmful product (CO2) is the main objective whiles the correlation between PM, O3 and CO2 is considered. A dielectric barrier discharge reactor has been designed with pulsed power technology to produce plasma inside the diesel exhaust. To characterise the system under varied conditions, a range of applied voltages from 11 kVPP to 21kVPP at repetition rates of 2.5, 5, 7.5 and 10 kHz, have been experimentally investigated. The results show that by increasing the applied voltage and repetition rate, higher discharge power and CO2 dissociation can be achieved. The PM removal efficiency of more than 50% has been achieved during the experiments and high concentrations of ozone on the order of a few hundreds of ppm have been observed at high discharge powers. Furthermore, O3, CO2 and PM concentrations at different plasma states have been analysed for time dependence. Based on this analysis, an inverse relationship between ozone concentration and PM removal has been found and the role of ozone in PM removal in plasma treatment of diesel exhaust has been highlighted.
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Building information modelling (BIM) radically changes the practices in architecture, engineering and construction (AEC) and creates new job opportunities. Many governments, such as the United Kingdom, have made BIM a mandatory requirement. This substantially drives the demand for a BIM-literate workforce. Universities are facing the challenge to incorporate BIM into their curricula and produce “BIM ready” graduates to meet the needs of the industry. Like other universities, Queensland University of Technology (QUT) is at the heart of this change and aspires to develop collaborative BIM education across AEC. Previous BIM education studies identify that inadequate BIM awareness of AEC academics is one of the challenges for developing a BIM curriculum and there is a dearth in the learning and teaching support for academics on BIM education. Equipping the AEC academics for a more BIM focused curriculum is all the while more important. This paper aims to leverage knowledge drawn from a Learning & Teaching project currently undertaken at QUT. Its specific objectives are to: 1) review the existing learning and teaching initiatives on BIM education; and 2) briefly describe the learning and teaching activities on collaborative BIM education at QUT. Significance of the paper lies on revealing the importance of building up the capacity of AEC academics for collaborative BIM education. The paper contributes to sparking the interests in better equipping AEC academics to understand what curriculum changes would assist in BIM uptake within the relevant courses to provide context for changes in units; and how the use of BIM can improve the understanding by students of the large amounts of professional knowledge they need to function effectively as graduates.
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Supervisory Control and Data Acquisition (SCADA) systems are one of the key foundations of smart grids. The Distributed Network Protocol version 3 (DNP3) is a standard SCADA protocol designed to facilitate communications in substations and smart grid nodes. The protocol is embedded with a security mechanism called Secure Authentication (DNP3-SA). This mechanism ensures that end-to-end communication security is provided in substations. This paper presents a formal model for the behavioural analysis of DNP3-SA using Coloured Petri Nets (CPN). Our DNP3-SA CPN model is capable of testing and verifying various attack scenarios: modification, replay and spoofing, combined complex attack and mitigation strategies. Using the model has revealed a previously unidentified flaw in the DNP3-SA protocol that can be exploited by an attacker that has access to the network interconnecting DNP3 devices. An attacker can launch a successful attack on an outstation without possessing the pre-shared keys by replaying a previously authenticated command with arbitrary parameters. We propose an update to the DNP3-SA protocol that removes the flaw and prevents such attacks. The update is validated and verified using our CPN model proving the effectiveness of the model and importance of the formal protocol analysis.
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Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: •Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. •Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. •Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.
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This paper deals with a finite element modelling method for thin layer mortared masonry systems. In this method, the mortar layers including the interfaces are represented using a zero thickness interface element and the masonry units are modelled using an elasto-plastic, damaging solid element. The interface element is formulated using two regimes; i) shear-tension and ii) shearcompression. In the shear-tension regime, the failure of joint is consiedered through an eliptical failure criteria and in shear-compression it is considered through Mohr Coulomb type failure criterion. An explicit integration scheme is used in an implicit finite element framework for the formulation of the interface element. The model is calibrated with an experimental dataset from thin layer mortared masonry prism subjected to uniaxial compression, a triplet subjected to shear loads a beam subjected to flexural loads and used to predict the response of thin layer mortared masonry wallettes under orthotropic loading. The model is found to simulate the behaviour of a thin layer mortated masonry shear wall tested under pre-compression and inplane shear quite adequately. The model is shown to reproduce the failure of masonry panels under uniform biaxial state of stresses.
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The importance of modelling correlation has long been recognised in the field of portfolio management, with largedimensional multivariate problems increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large-dimensional problems.We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm, however, the suitability of the constant conditional correlation model cannot be discounted, especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, while portfolio weight stability and relative economic value are also considered.
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Searching for efficient solid sorbents for CO2 adsorption and separation is important for developing emergent carbon reduction and natural gas purification technology. This work, for the first time, has investigated the adsorption of CO2 on newly experimentally realized cage-like B40 fullerene (Zhai et al., 2014) based on density functional theory calculations. We find that the adsorption of CO2 on B40 fullerene involves a relatively large energy barrier (1.21 eV), however this can be greatly decreased to 0.35 eV by introducing an extra electron. A practical way to realize negatively charged B40 fullerene is then proposed by encapsulating a Li atom into the B40 fullerene (Li@B40). Li@B40 is found to be highly stable and can significantly enhance both the thermodynamics and kinetics of CO2 adsorption, while the adsorptions of N2, CH4 and H2 on the Li@B40 fullerene remain weak in comparison. Since B40 fullerene has been successfully synthesized in a most recent experiment, our results highlight a new promising material for CO2 capture and separation for future experimental validation.
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This thesis develops comprehensive mathematical models for an advanced drying technology Intermittent Microwave Convective Drying (IMCD). The models provide an improved physical understanding of the heat and mass transport during the drying process, which will help to improve the quality of dried food and energy efficiency of the process, as well as will increase the ability of automation and optimization. The final model in this thesis represents the most comprehensive fundamental multiphase model for IMCD that considers 3D electromagnetics coupled with multiphase porous media transport processes. The 3D electromagnetics considers Maxwell's equation and multiphase transport model considers three different phases: solid matrix, liquid water and gas consisting water vapour and air. The multiphase transport includes pressure-driven flow, capillary diffusion, binary diffusion, and evaporation. The models developed in this thesis were validated with extensive experimental investigations.
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Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in literature by applying the Navigation Traffic Conflict Technique (NTCT) for measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Grounding on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.
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This study analysed whether a significant relationship exists between the torque and muscle thickness and pennation angle of the erector spinae muscle during a maximal isometric lumbar extension with the lumbar spine in neutral position. This was a cross-sectional study in which 46 healthy adults performed three repetitions for 5 s of maximal isometric lumbar extension with rests of 90 s. During the lumbar extensions, bilateral ultrasound images of the erector spinae muscle (to measure pennation angle and muscle thickness) and torque were acquired. Reliability test analysis calculating the internal consistency (Cronbach's alpha) of the measure, correlation between pennation angle, muscle thickness and torque extensions were examined. Through a linear regression the contribution of each independent variable (muscle thickness and pennation angle) to the variation of the dependent variable (torque) was calculated. The results of the reliability test were: 0.976–0.979 (pennation angle), 0.980–0.980 (muscle thickness) and 0.994 (torque). The results show that pennation angle and muscle thickness were significantly related to each other with a range between 0.295 and 0.762. In addition, multiple regression analysis showed that the two variables considered in this study explained 68% of the variance in the torque. Pennation angle and muscle thickness have a moderate impact on the variance exerted on the torque during a maximal isometric lumbar extension with the lumbar spine in neutral position.
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This paper describes recent updates to a milling train extraction model used to assess and predict the performance of a milling train. An extension was made to the milling unit model for the bagasse mills to replace the imbibition coefficient with crushing factor and mixing efficiency. New empirical relationships for reabsorption factor, imbibition coefficient, crushing factor, mixing efficiency and purity ratio were developed. The new empirical relationships were tested against factory measurements and previous model predictions. The updated model has been implemented in the SysCAD process modelling software. New additions to the model implementation include: a shredder model to assess or predict cane preparation, mill and shredder drives for power consumption and an updated imbibition control system to add allow water to be added to intermediate mills.
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The behavior of small molecules on a surface depends critically on both molecule–substrate and intermolecular interactions. We present here a detailed comparative investigation of 1,3,5-benzene tricarboxylic acid (trimesic acid, TMA) on two different surfaces: highly oriented pyrolytic graphite (HOPG) and single-layer graphene (SLG) grown on a polycrystalline Cu foil. On the basis of high-resolution scanning tunnelling microscopy (STM) images, we show that the epitaxy matrix for the hexagonal TMA chicken wire phase is identical on these two surfaces, and, using density functional theory (DFT) with a non-local van der Waals correlation contribution, we identify the most energetically favorable adsorption geometries. Simulated STM images based on these calculations suggest that the TMA lattice can stably adsorb on sites other than those identified to maximize binding interactions with the substrate. This is consistent with our net energy calculations that suggest that intermolecular interactions (TMA–TMA dimer bonding) are dominant over TMA–substrate interactions in stabilizing the system. STM images demonstrate the robustness of the TMA films on SLG, where the molecular network extends across the variable topography of the SLG substrates and remains intact after rinsing and drying the films. These results help to elucidate molecular behavior on SLG and suggest significant similarities between adsorption on HOPG and SLG.
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This study aimed to take existing anatomical models of pregnant women, currently used for radiation pro-tection and nuclear medicine dose calculations, and adapt them for use in the calculation of fetal dose from external beam radiotherapy (EBRT). The models investigated were ‘KATJA’, which was provided as an MCNPX geometry file, and ‘RPI-P6’, which was provided in a simple, voxelized bina-ry format. In-house code was developed, to convert both mod-els into an `egsphant’ format, suitable for use with DOSXYZnrc. The geometries and densities of the resulting phantoms were evaluated and found to accurately represent the source data. As an example of the use of the phantoms, the delivery of a cranial EBRT treatment was simulated using the BEAMnrc and DOSXYZnrc Monte Carlo codes and the likely out-of-field doses to the fetus in each model was calculated. The results of these calculations showed good agreement (with-in one standard deviation) between the doses calculated in KATJA and PRI-P6, despite substantial anatomical differ-ences between the two models. For a 36 Gy prescription dose to a 233.2 cm3 target in the right brain, the mean doses calcu-lated in a region of interest covering the entire uterus were 1.0 +/- 0.6 mSv for KATJA and 1.3 +/- 0.9 mSv for RPI-P6. This work is expected to lead to more comprehensive studies of EBRT treatment plan design and its effects on fetal dose in the future.
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Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.