797 resultados para Agent-based model


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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

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This thesis explored the potential of a multi-component and multi-disciplinary approach to obesity management using action research methodologies. A preliminary systems-based model for obesity management was developed based around four meta-components (client factors, practitioner factors, process factors and the environment) and two action theories (action research and action science).

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This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.

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Hand, Foot and Mouth Disease (HFMD) is a self-limiting viral disease that mainly affects infants and children. In contrast with other HFMD causing enteroviruses, Enterovirus71 (EV71) has commonly been associated with severe clinical manifestation leading to death. Currently, due to a lack in understanding of EV71 pathogenesis, there is no antiviral therapeutics for the treatment of HFMD patients. Therefore the need to better understand the mechanism of EV71 pathogenesis is warranted. We have previously reported a human colorectal adenocarcinoma cell line (HT29) based model to study the pathogenesis of EV71. Using this system, we showed that knockdown of DGCR8, an essential cofactor for microRNAs biogenesis resulted in a reduction of EV71 replication. We also demonstrated that there are miRNAs changes during EV71 pathogenesis and EV71 utilise host miRNAs to attenuate antiviral pathways during infection. Together, data from this study provide critical information on the role of miRNAs during EV71 infection.

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Reliability of carrier phase ambiguity resolution (AR) of an integer least-squares (ILS) problem depends on ambiguity success rate (ASR), which in practice can be well approximated by the success probability of integer bootstrapping solutions. With the current GPS constellation, sufficiently high ASR of geometry-based model can only be achievable at certain percentage of time. As a result, high reliability of AR cannot be assured by the single constellation. In the event of dual constellations system (DCS), for example, GPS and Beidou, which provide more satellites in view, users can expect significant performance benefits such as AR reliability and high precision positioning solutions. Simply using all the satellites in view for AR and positioning is a straightforward solution, but does not necessarily lead to high reliability as it is hoped. The paper presents an alternative approach that selects a subset of the visible satellites to achieve a higher reliability performance of the AR solutions in a multi-GNSS environment, instead of using all the satellites. Traditionally, satellite selection algorithms are mostly based on the position dilution of precision (PDOP) in order to meet accuracy requirements. In this contribution, some reliability criteria are introduced for GNSS satellite selection, and a novel satellite selection algorithm for reliable ambiguity resolution (SARA) is developed. The SARA algorithm allows receivers to select a subset of satellites for achieving high ASR such as above 0.99. Numerical results from a simulated dual constellation cases show that with the SARA procedure, the percentages of ASR values in excess of 0.99 and the percentages of ratio-test values passing the threshold 3 are both higher than those directly using all satellites in view, particularly in the case of dual-constellation, the percentages of ASRs (>0.99) and ratio-test values (>3) could be as high as 98.0 and 98.5 % respectively, compared to 18.1 and 25.0 % without satellite selection process. It is also worth noting that the implementation of SARA is simple and the computation time is low, which can be applied in most real-time data processing applications.

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We construct a two-scale mathematical model for modern, high-rate LiFePO4cathodes. We attempt to validate against experimental data using two forms of the phase-field model developed recently to represent the concentration of Li+ in nano-sized LiFePO4crystals. We also compare this with the shrinking-core based model we developed previously. Validating against high-rate experimental data, in which electronic and electrolytic resistances have been reduced is an excellent test of the validity of the crystal-scale model used to represent the phase-change that may occur in LiFePO4material. We obtain poor fits with the shrinking-core based model, even with fitting based on “effective” parameter values. Surprisingly, using the more sophisticated phase-field models on the crystal-scale results in poorer fits, though a significant parameter regime could not be investigated due to numerical difficulties. Separate to the fits obtained, using phase-field based models embedded in a two-scale cathodic model results in “many-particle” effects consistent with those reported recently.

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To prevent unauthorized access to protected trusted platform module (TPM) objects, authorization protocols, such as the object-specific authorization protocol (OSAP), have been introduced by the trusted computing group (TCG). By using OSAP, processes trying to gain access to the protected TPM objects need to prove their knowledge of relevant authorization data before access to the objects can be granted. Chen and Ryan’s 2009 analysis has demonstrated OSAP’s authentication vulnerability in sessions with shared authorization data. They also proposed the Session Key Authorization Protocol (SKAP) with fewer stages as an alternative to OSAP. Chen and Ryan’s analysis of SKAP using ProVerif proves the authentication property. The purpose of this paper was to examine the usefulness of Colored Petri Nets (CPN) and CPN Tools for security analysis. Using OSAP and SKAP as case studies, we construct intruder and authentication property models in CPN. CPN Tools is used to verify the authentication property using a Dolev–Yao-based model. Verification of the authentication property in both models using the state space tool produces results consistent with those of Chen and Ryan.

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Drying is a key processing techniques used in food engineering which demands continual developments on advanced analysis techniques in order to optimize the product and the process. In this regard, plant based materials are a frequent subject of interest where microstructural studies can provide a clearer understanding on the fundamental physical mechanisms involved. In this context, considering numerous challenges of using conventional numerical grid-based modelling techniques, a meshfree particle based model was developed to simulate extreme deformations of plant microstructure during drying. The proposed technique is based on a particle based meshfree method: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). A tissue model was developed by aggrading individual cells modelled with SPH-DEM coupled approach by initializing the cells as hexagons and aggregating them to form a tissue. The model also involves a middle lamella resembling real tissues. Using the model, different dried tissue states were simulated with different moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model is capable of simulating plant tissues at lower moisture contents which results in excessive shrinkage and cell wall wrinkling. Model predictions were compared with experimental findings and a fairly good agreement was observed both qualitatively and quantitatively.

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The business value of information technology (IT) is increasingly being cocreated by multiple parties, opening opportunities for new research initiatives. Previous studies on IT value cocreation mainly focus on analyzing sources of cocreated IT value, yet inadequately accommodating the influence of competition relationships in IT value cocreation activities. To fill the gap, this in-progress paper suggests an agent-based modeling (also simulation) approach to investigating potential influences of the dynamic interplay between cooperation and competition relationships in IT value cocreation settings. In particular, the research proposes a high-level conceptual framework to position general IT value cocreation processes. A relational network view is offered, aiming at decomposing and systemizing several typical cooperation and competition scenarios in practical IT value cocreation settings. The application of a simulation approach to analytical insights and to theory building is illustrated.

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Large scale solar plants are gaining recognition as potential energy sources for future. In this paper, the feasibility of using electric vehicles (EVs) to control a solar powered micro-grid is investigated in detail. The paper presents a PSCAD/EMTDC based model for the solar powered micro-grid with EVs. EVs are expected to have both the vehicle-to-grid (V2G) and grid-to-vehicle (G2V) capability, through which energy can either be injected into or extracted from the solar powered micro-grid to control its energy imbalance. Using the model, the behaviour of the micro-grid is investigated under a given load profile, and the results indicate that a minimum number of EVs are required to meet the energy imbalance and it is time dependent and influenced by various factors such as depth of charge, commuting profiles, reliability etc...

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This thesis positions practitioner research within the emerging discipline of fashion and disputes that practitioner knowledge of fashion is predominantly tacit. This research contributes to the understanding of practitioner knowledge and proposes an object based model of practitioner research as an alternative to existing practice-led methodologies. The thesis theorises fashion objects as a site of significant knowledge and argues their potential to record and communicate fashion knowledge and disseminate practice-led research.

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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

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The strategies and techniques that police officers employ are adaptations to the types of communities they serve and the law enforcement system of which they are part. Observations of policing in rural and urban areas of Australia indicate that, despite being part of a single state police service, officers develop working philosophies that are systematically adapted to the locations they serve. Bayley (1989) has observed that while crimes are policed in the city, people are policed in the country. Rural police officers often adopt a community-based model of policing in which officers become integrated into a community and establish compatible community relations. While this model can produce successful results, with integration into informal social networks providing police increased opportunities to solve crime, rural police regularly find themselves occupying competing roles of law enforcer and local resident. This chapter will outline how the organisation and structure of rural communities impacts upon policing, noting distinct issues associated with police work in rural settings. Before examining current aspects of rural policing, a brief discussion of the historical and cultural context of rural policing is provided.

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Using established strategic management and business model frameworks we map the evolution of universities in the context of their value proposition to students as consumers of their products. We argue that in the main universities over time have transitioned from a value-based business model through to an efficiency-based business model that for numerous reasons, is becoming rapidly unsustainable. We further argue that the future university business models would benefit with a reconfiguration towards a network value based model. This approach requires a revised set of perceived benefits, better aligned to the current and future expectations and an alternate approach to the delivery of those benefits to learner / consumers.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.