967 resultados para Network Modelling


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Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically dicult to solve, since the state-space involved can be very large or even countably innite. Recently a nite state projection method (FSP) that truncates the state-space was suggested and shown to be eective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the nal time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger nal times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was rst demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is signicantly faster and extendable to larger biological models.

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Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such microcalibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, lane distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.

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Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.

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Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such micro-calibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, land distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.

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Traffic Simulation models tend to have their own data input and output formats. In an effort to standardise the input for traffic simulations, we introduce in this paper a set of data marts that aim to serve as a common interface between the necessaary data, stored in dedicated databases, and the swoftware packages, that require the input in a certain format. The data marts are developed based on real world objects (e.g. roads, traffic lights, controllers) rather than abstract models and hence contain all necessary information that can be transformed by the importing software package to their needs. The paper contains a full description of the data marts for network coding, simulation results, and scenario management, which have been discussed with industry partners to ensure sustainability.

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Models of word meaning, built from a corpus of text, have demonstrated success in emulating human performance on a number of cognitive tasks. Many of these models use geometric representations of words to store semantic associations between words. Often word order information is not captured in these models. The lack of structural information used by these models has been raised as a weakness when performing cognitive tasks. This paper presents an efficient tensor based approach to modelling word meaning that builds on recent attempts to encode word order information, while providing flexible methods for extracting task specific semantic information.

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How do humans respond to their social context? This question is becoming increasingly urgent in a society where democracy requires that the citizens of a country help to decide upon its policy directions, and yet those citizens frequently have very little knowledge of the complex issues that these policies seek to address. Frequently, we find that humans make their decisions more with reference to their social setting, than to the arguments of scientists, academics, and policy makers. It is broadly anticipated that the agent based modelling (ABM) of human behaviour will make it possible to treat such social effects, but we take the position here that a more sophisticated treatment of context will be required in many such models. While notions such as historical context (where the past history of an agent might affect its later actions) and situational context (where the agent will choose a different action in a different situation) abound in ABM scenarios, we will discuss a case of a potentially changing context, where social effects can have a strong influence upon the perceptions of a group of subjects. In particular, we shall discuss a recently reported case where a biased worm in an election debate led to significant distortions in the reports given by participants as to who won the debate (Davis et al 2011). Thus, participants in a different social context drew different conclusions about the perceived winner of the same debate, with associated significant differences among the two groups as to who they would vote for in the coming election. We extend this example to the problem of modelling the likely electoral responses of agents in the context of the climate change debate, and discuss the notion of interference between related questions that might be asked of an agent in a social simulation that was intended to simulate their likely responses. A modelling technology which could account for such strong social contextual effects would benefit regulatory bodies which need to navigate between multiple interests and concerns, and we shall present one viable avenue for constructing such a technology. A geometric approach will be presented, where the internal state of an agent is represented in a vector space, and their social context is naturally modelled as a set of basis states that are chosen with reference to the problem space.

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Popular wireless networks, such as IEEE 802.11/15/16, are not designed for real-time applications. Thus, supporting real-time quality of service (QoS) in wireless real-time control is challenging. This paper adopts the widely used IEEE 802.11, with the focus on its distributed coordination function (DCF), for soft-real-time control systems. The concept of the critical real-time traffic condition is introduced to characterize the marginal satisfaction of real-time requirements. Then, mathematical models are developed to describe the dynamics of DCF based real-time control networks with periodic traffic, a unique feature of control systems. Performance indices such as throughput and packet delay are evaluated using the developed models, particularly under the critical real-time traffic condition. Finally, the proposed modelling is applied to traffic rate control for cross-layer networked control system design.

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A general mistrust within the contactor and subcontractor companies has identified one of the significant barriers to derive benefits from true downstream supply chain integration. Using the general theory of trust in inter-organizational relations and conducting interviews, this research discusses factors that influence development of trust and cooperation in contractor subcontractor relationships in construction projects. System dynamics is the simulation method is selected in this theory-building effort, based on qualitative data collected from two projects of a construction company in Thailand. Performance, permeability and system based trust are found to make significant contributions toward parties trust level. Three strategic policies such as best value contracting, management of subcontractors as internal team and semi project partnering approach are recommended to stimulate the trust factors as well as cooperative long term relationship.

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Goldin (2003) and McDonald, Yanchar, and Osguthorpe (2005) have called for mathematics learning theory that reconciles the chasm between ideologies, and which may advance mathematics teaching and learning practice. This paper discusses the theoretical underpinnings of a recently completed PhD study that draws upon Poppers (1978) three-world model of knowledge as a lens through which to reconsider a variety of learning theories, including Piagets reflective abstraction. Based upon this consideration of theories, an alternative theoretical framework and complementary operational model was synthesised, the viability of which was demonstrated by its use to analyse the domain of early-number counting, addition and subtraction.

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Innovation is vital for the future of Australia.s internet economy. Innovations rely on businesses. ability to innovate. Businesses. ability to innovate relies on their employees. The more these individual end users engage in the internet economy, the better businesses. engagement will be. The less these individual end users engage, the less likely a business is to engage and innovate. This means, for the internet economy to function at its fullest potential, it is essential that individual Australians have the capacity to engage with it and participate in it. The Australian federal government is working to facilitate the internet economy through policies, legislation and practices that implement high-speed broadband. The National Broadband Network will be a vital tool for Australia.s internet economy. Its .chief importance is that it will provide faster internet access speeds that will facilitate access to internet services and content. However, an appropriate infrastructure and internet speed is only part of the picture. As the Organisation for Economic Co-operation and Development identified, appropriate government policies are also needed to ensure that vital services are more accessible by consumers. The thesis identifies essential theories and principles underpinning the internet economy and from which the concept of connectedness is developed. Connectedness is defined as the ability of end users to connect with internet content and services, other individuals and organisations, and government. That is, their ability to operate in the internet economy. The NBN will be vital in ensuring connectedness into the future. What is not currently addressed by existing access regimes is how to facilitate end user access capacity and participation. The thesis concludes by making recommendations to the federal government as to what the governing principles of the Australian internet economy should include in order to enable individual end user access capacity.

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A crucial contemporary policy question for governments across the globe is how to cope with international crime and terrorist networks. Many such dark networksthat is, networks that operate covertly and illegallydisplay a remarkable level of resilience when faced with shocks and attacks. Based on an in-depth study of three cases (MK, the armed wing of the African National Congress in South Africa during apartheid; FARC, the Marxist guerrilla movement in Colombia; and the Liberation Tigers of Tamil Eelam, LTTE, in Sri Lanka), we present a set of propositions to outline how shocks impact dark network characteristics (resources and legitimacy) and networked capabilities (replacing actors, linkages, balancing integration and differentiation) and how these in turn affect a dark network's resilience over time. We discuss the implications of our findings for policymakers.

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This paper presents a research frame which we have found useful in analyzing complex socio- technical situations. The research frame is based on aspects of actor-network theory: interressment, enrollment, points of passage and the trial of strength. Each of these aspects are described in turn, making clear their purpose in the overall research frame. Having established the research frame it is used to analyse two examples. First, the use of speech recognition technology is examined in two different contexts, showing how to apply the frame to compare and contrast current situations. Next, a current medical consultation context is described and the research frame is used to consider how it could change with innovative technology. In both examples, the research frame shows that the use of an artefact or technology must be considered together with the context in which it is used.

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This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Some of the core components of data modelling are addressed. A selection of results from the first data modelling activity implemented during the second year (2010; second grade) of a current longitudinal study are reported. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Reported here are children's abilities to identify diverse and complex attributes, sort and classify data in different ways, and create and interpret models to represent their data.

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