955 resultados para Ecological Modelling
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The purpose of this research is to assess daylight performance of buildings with climatic responsive envelopes with complex geometry that integrates shading devices in the façade. To this end two case studies are chosen due to their complex geometries and integrated daylight devices. The effect of different parameters of the daylight devices is analysed through Climate base daylight metrics.
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Electric walking draglines are physically large and powerful machines used in the mining industry. However with the addition of suitable sensors and a controller a dragline can be considered as a numerically controlled machine or robot which can then perform parts of the operating cycle automatically. This paper presents an analysis of the electromechanical system necessary precursor to automatic control
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This thesis is an ecological systems case study of an industry-school partnership. It examines a minerals and energy sector partnership with Queensland schools and explains the operational dynamics. In doing so, an original contribution to theory and practice was presented, together with implications for the impact of industry on education.
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Passenger flow simulations are an important tool for designing and managing airports. This thesis examines the different boarding strategies for the Boeing 777 and Airbus 380 aircraft in order to investigate their current performance and to determine minimum boarding times. The most optimal strategies have been discovered and new strategies that are more efficient are proposed. The methods presented offer reduced aircraft boarding times which plays an important role for reducing the overall aircraft Turn Time for an airline.
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The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when nonlinear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bárdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.
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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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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 symptoms of psychiatric illness are diverse, as are the causes of the illnesses that cause them. Yet, regardless of the heterogeneity of cause and presentation, a great deal of symptoms can be explained by the failure of a single perceptual function – the reprocessing of ecological perception. It is a central tenet of the ecological theory of perception that we perceive opportunities to act. It has also been found that perception automatically causes actions and thoughts to occur unless this primary action pathway is inhibited. Inhibition allows perceptions to be reprocessed into more appropriate alternative actions and thoughts. Reprocessing of this kind takes place over the entire frontal lobe and it renders action optional. Choice about what action to take (if any) is the basis for the feeling of autonomy and ultimately for the sense-of-self. When thoughts and actions occur automatically (without choice) they appear to originate outside of the self, thereby providing prima facie evidence for some of the bizarre delusions that define schizophrenia such as delusional misidentification, delusions of control and Cotard’s delusion. Automatic actions and thoughts are triggered by residual stimulation whenever reprocessing is insufficient to balance automatic excitatory cues (for whatever reason). These may not be noticed if they are neutral and therefore unimportant whereas actions and thoughts with a positive bias are desirable. Responses to negative stimulus, on the other hand, are always unwelcome, because the actions that are triggered will carry the negative bias. Automatic thoughts may include spontaneous positive feelings of love and joy, but automatic negative thoughts and visualisations are experienced as hallucinations. Not only do these feel like they emerge from elsewhere but they carry a negative bias (they are most commonly critical, rude and are irrationally paranoid). Automatic positive actions may include laughter and smiling and these are welcome. Automatic behaviours that carry a negative bias, however, are unwelcome and like hallucinations, occur without a sense of choice. These include crying, stereotypies, perseveration, ataxia, utilization and imitation behaviours and catatonia.
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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 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.