522 resultados para flow modelling


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Popular wireless network standards, such as IEEE 802.11/15/16, are increasingly adopted in real-time control systems. However, they are not designed for real-time applications. Therefore, the performance of such wireless networks needs to be carefully evaluated before the systems are implemented and deployed. While efforts have been made to model general wireless networks with completely random traffic generation, there is a lack of theoretical investigations into the modelling of wireless networks with periodic real-time traffic. Considering the widely used IEEE 802.11 standard, with the focus on its distributed coordination function (DCF), for soft-real-time control applications, this paper develops an analytical Markov model to quantitatively evaluate the network quality-of-service (QoS) performance in periodic real-time traffic environments. Performance indices to be evaluated include throughput capacity, transmission delay and packet loss ratio, which are crucial for real-time QoS guarantee in real-time control applications. They are derived under the critical real-time traffic condition, which is formally defined in this paper to characterize the marginal satisfaction of real-time performance constraints.

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In this paper, a rate-based flow control scheme based upon per-VC virtual queuing is proposed for the Available Bit Rate (ABR) service in ATM. In this scheme, each VC in a shared buffer is assigned a virtual queue, which is a counter. To achieve a specific kind of fairness, an appropriate scheduler is applied to the virtual queues. Each VC's bottleneck rate (fair share) is derived from its virtual cell departure rate. This approach of deriving a VC's fair share is simple and accurate. By controlling each VC with respect to its virtual queue and queue build-up in the shared buffer, network congestion is avoided. The principle of the control scheme is first illustrated by max–min flow control, which is realised by scheduling the virtual queues in round-robin. Further application of the control scheme is demonstrated with the achievement of weighted fairness through weighted round robin scheduling. Simulation results show that with a simple computation, the proposed scheme achieves the desired fairness exactly and controls network congestion effectively.

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Extensive groundwater withdrawal has resulted in a severe seawater intrusion problem in the Gooburrum aquifers at Bundaberg, Queensland, Australia. Better management strategies can be implemented by understanding the seawater intrusion processes in those aquifers. To study the seawater intrusion process in the region, a two-dimensional density-dependent, saturated and unsaturated flow and transport computational model is used. The model consists of a coupled system of two non-linear partial differential equations. The first equation describes the flow of a variable-density fluid, and the second equation describes the transport of dissolved salt. A two-dimensional control volume finite element model is developed for simulating the seawater intrusion into the heterogeneous aquifer system at Gooburrum. The simulation results provide a realistic mechanism by which to study the convoluted transport phenomena evolving in this complex heterogeneous coastal aquifer.

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Real-world business processes are resource-intensive. In work environments human resources usually multitask, both human and non-human resources are typically shared between tasks, and multiple resources are sometimes necessary to undertake a single task. However, current Business Process Management Systems focus on task-resource allocation in terms of individual human resources only and lack support for a full spectrum of resource classes (e.g., human or non-human, application or non-application, individual or teamwork, schedulable or unschedulable) that could contribute to tasks within a business process. In this paper we develop a conceptual data model of resources that takes into account the various resource classes and their interactions. The resulting conceptual resource model is validated using a real-life healthcare scenario.

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Groundwater is increasingly recognised as an important yet vulnerable natural resource, and a key consideration in water cycle management. However, communication of sub-surface water system behaviour, as an important part of encouraging better water management, is visually difficult. Modern 3D visualisation techniques can be used to effectively communicate these complex behaviours to engage and inform community stakeholders. Most software developed for this purpose is expensive and requires specialist skills. The Groundwater Visualisation System (GVS) developed by QUT integrates a wide range of surface and sub-surface data, to produce a 3D visualisation of the behaviour, structure and connectivity of groundwater/surface water systems. Surface data (elevation, surface water, land use, vegetation and geology) and data collected from boreholes (bore locations and subsurface geology) are combined to visualise the nature, structure and connectivity of groundwater/surface water systems. Time-series data (water levels, groundwater quality, rainfall, stream flow and groundwater abstraction) is displayed as an animation within the 3D framework, or graphically, to show water system condition changes over time. GVS delivers an interactive, stand-alone 3D Visualisation product that can be used in a standard PC environment. No specialised training or modelling skills are required. The software has been used extensively in the SEQ region to inform and engage both water managers and the community alike. Examples will be given of GVS visualisations developed in areas where there have been community concerns around groundwater over-use and contamination.

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In a seminal data mining article, Leo Breiman [1] argued that to develop effective predictive classification and regression models, we need to move away from the sole dependency on statistical algorithms and embrace a wider toolkit of modeling algorithms that include data mining procedures. Nevertheless, many researchers still rely solely on statistical procedures when undertaking data modeling tasks; the sole reliance on these procedures has lead to the development of irrelevant theory and questionable research conclusions ([1], p.199). We will outline initiatives that the HPC & Research Support group is undertaking to engage researchers with data mining tools and techniques; including a new range of seminars, workshops, and one-on-one consultations covering data mining algorithms, the relationship between data mining and the research cycle, and limitations and problems with these new algorithms. Organisational limitations and restrictions to these initiatives are also discussed.

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Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.

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Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

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A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

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The multi-criteria decision making methods, Preference METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.

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The Tamborine Mt area is a popular residential and tourist area in the Gold Coast hinterland, SE Qld. The 15km2 area occurs on elevated remnant Tertiary Basalts of the Beechmont Group, which comprise a number of mappable flow units originally derived from the Tweed volcanic centre to the south. The older Albert Basalt (Tertiary), which underlies the Beechmont Basalt at the southern end of the investigation area, is thought to be derived from the Focal Peak volcanic centre to the south west. The Basalts contain a locally significant ‘un-declared’ groundwater resource, which is utilised by the Tamborine Mt community for: • domestic purposes to supplement rainwater tank supplies, • commercial scale horticulture and • commercial export off-Mountain for bottled water. There is no reticulated water supply, and all waste water is treated on-site through domestic scale WTPs. Rainforest and other riparian ecosystems that attract residents and tourist dollars to the area, are also reliant on the groundwater that discharges to springs and surface streams on and around the plateau. Issues regarding a lack of compiled groundwater information, groundwater contamination, and groundwater sustainability are being investigated by QUT, utilising funding provided by the Federal Government’s ‘Caring for our Country’ programme through SEQ Catchments Ltd. The objectives of the two year project, which started in April 2009, are to: • Characterise the nature and condition of groundwater / surface water systems in the Tamborine Mountain area in terms of the issues being raised; • Engage and build capacity within the community to source local knowledge, encourage participation, raise awareness and improve understanding of the impacts of land and water use; • Develop a stand-alone 3D Visualisation model for dissemination into the community and use as a communication tool.

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Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

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A simple mathematical model is presented to describe the cell separation process that plants undertake in order to deliberately shed organs. The focus here is on modelling the production of the enzyme polygalacturonase, which breaks down pectin that provides natural cell-to-cell adhesion in the localised abscission zone. A coupled system of three ordinary differential equations is given for a single cell, and then extended to hold for a layer of cells in the abscission zone. Simple observations are made based on the results of this preliminary model and, furthermore, a number of opportunities for applied mathematicians to make contributions in this subject area are discussed.

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Purpose - This paper seeks to examine the complex relationships between urban planning, infrastructure management, sustainable urban development, and to illustrate why there is an urgent need for local governments to develop a robust planning support system which integrates with advance urban computer modelling tools to facilitate better infrastructure management and improve knowledge sharing between the community, urban planners, engineers and decision makers. Design/methodology/approach - The methods used in this paper includes literature review and practical project case observations. Originality/value - This paper provides an insight of how the Brisbane's planning support system established by Brisbane City Council has significantly improved the effectiveness of urban planning, infrastructure management and community engagement through better knowledge management processes. Practical implications - This paper presents a practical framework for setting up a functional planning support system within local government. The integration of the Brisbane Urban Growth model, Virtual Brisbane and the Brisbane Economic Activity Monitoring (BEAM) database have proven initially successful to provide a dynamic platform to assist elected officials, planners and engineers to understand the limitations of the local environment, its urban systems and the planning implications on a city. With the Brisbane's planning support system, planners and decision makers are able to provide better planning outcomes, policy and infrastructure that adequately address the local needs and achieve sustainable spatial forms.

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A set of non-nested longitudinal models tested the relationships between personal and workplace resources, well-being and work engagement. The reciprocal model, trimmed of trivial paths had the best fit and parsimony. The model showed the strong influences of concurrent functioning, stability of variables over time and weaker reciprocal relationships between variables across time. Individuals with greater confidence in themselves and the future experience better work conditions and have greater well-being and work engagement. These day-to-day influences are equalled by the long term strength and stability of Individual Factors, Positive Workplace Factors, and Overall Well-Being. Whilst the reciprocal paths had only weak to mild effects, there was mutual reinforcement of Individual Factors and Overall Well-Being, with Positive Workplace Factors and Work Engagement counterbalancing each other, indicating a more complex relationship. Well-being, particularly, is anchored in the immediate and distant past and provides a robust stability to functioning into the future.