648 resultados para bayesian networks


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The institution the police force has been established to protect citizens and their property from harm and predatory opportunism. However, there have been occasions when the very people assigned to protect become part of the predatory force against society. Predatory policing occurs when the police use their powers to extort money in the form of bribes. While, the concept is receiving attention in Europe but there have not been any direct studies in Australia. To overcome this research deficit and determine the extent, if any, of predatory policing in Australia data is interrogated from four police corruption inquiries in the Australian states of Queensland, New South Wales, Victoria and Western Australia. In addition, it examines the role of the type of networks used by corrupt police officers. The synthesis and application of public corruption and network literatures to the predatory policing domain provides new and relevant insights to assist those responsible for the administration of our institutions of justice. The paper concludes with a framework, drawn from the first stage of the project, to assist in the conceptualisation and monitoring of this public problem.

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Isolation of a faulted segment, from either side of a fault, in a radial feeder that has several converter interfaced DGs is a challenging task when current sensing protective devices are employed. The protective device, even if it senses a downstream fault, may not operate if fault current level is low due to the current limiting operation of converters. In this paper, a new inverse type relay is introduced based on line admittance measurement to protect a distribution network, which has several converter interfaced DGs. The basic operation of this relay, its grading and reach settings are explained. Moreover a method is proposed to compensate the fault resistance such that the relay operation under this condition is reliable. Then designed relay performances are evaluated in a radial distribution network. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

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The innovation diffusion and knowledge management literature strongly supports the importance of communities of practice (COP) for enabling knowledge about how to use and adopt innovation initiatives. One of the most powerful tools for innovation diffusion is word-of-mouth wisdom from committed individuals who mentor and support each other. Close proximity for face-to-face interaction is highly effective, however, many organisations are geographically dispersed with projects being virtual linked sub-organisations using ICT to communicate. ICT has also introduced a useful facilitating technology for developing knowledge networks. This paper presents findings from a research program concentrating on ICT innovation diffusion in the Australian construction industry. One way in which ICT diffusion is taking place was found to be through within-company communities of practice. We undertook in-depth unstructured interviews with three of the major 10 to 15 contractors in Australia to discuss their ICT diffusion strategies. We discovered that in all three cases,within company networked communities of practice was a central strategy. Further, effective diffusion of ICT groupware tools can be critical in developing COP where they are geographically dispersed.

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Collaborative networks have come to form a large part of the public sectorâs strategy to address ongoing and often complex social problems. The relational power of networks, with its emphasis on trust, reciprocity and mutuality provides the mechanism to integrate previously dispersed and even competitive entities into a collective venture(Agranoff 2003; Agranoff and McGuire 2003; Mandell 1994; Mandell and Harrington 1999). It is argued that the refocusing of a single body of effort to a collective contributes to reducing duplication and overlap of services, maximizes increasingly scarce resources and contributes to solving intractable or 'wickedâproblems (Clarke and Stewart 1997). Given the current proliferation of collaborative networks and the fact that they are likely to continue for some time, concerns with the management and leadership of such arrangements for optimal outcomes are increasingly relevant. This is especially important for public sector managers who are used to working in a top-down, hierarchical manner. While the management of networks (Agranoff and McGuire 2001, 2003), including collaborative or complex networks (Kickert et al. 1997; Koppenjan and Klijn 2004), has been the subject of considerable attention, there has been much less explicit discussion on leadership approaches in this context. It is argued in this chapter that the traditional use of the terms â˜leaderâ or â˜leadershipâ does not apply to collaborative networks. There are no â˜followersâ in collaborative networks or supervisor-subordinate relations. Instead there are equal, horizontal relationships that are focused on delivering systems change. In this way the emergent organizational forms such as collaborative networks challenge older models of leadership. However despite the questionable relevance of old leadership styles to the contemporary work environment, no clear alternative has come along to take its place.

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Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

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Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

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Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.

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In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

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From the perspective of network, a project teamâs social capital consists of conduits network, and resource exchange network. Prior research intensively studies the effect of the structure of conduits network on the teamâs performance, assuming knowledge transfer is the causal mechanism linking conduits network to performance. This paper attempts to explore the interrelations between conduits network and knowledge network, and further distinguish the different influence between various conduit networks, and hypothesizes that a project teamâs knowledge network mediates the effect of various conduit networks on the teamâs performance. This research can enrich our knowledge of disparate influence of the various conduit networks on knowledge transfer, and imply some management practices to enhance the organizationâs social capital, and hence improve the organizationâs performance.

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This paper introduces friendwork as a new term in social networks studies. A friendwork is a network of friends. It is a specific case of an interpersonal social network. Naming this seemingly well known and familiar group of people as a friendwork facilitates its differentiation from the overall social network, while highlighting this subgroup's specific attributes and dynamics. The focus on one segment within social networks stimulates a wider discussion regarding the different subgroups within social networks. Other subgroups also discussed in this paper are: family dependent, work related, location based and virtual acquaintances networks. This discussion informs a larger study of social media, specifically addressing interactive communication modes that are in use within friendworks: direct (face-to-face) and mediated (mainly fixed telephone, internet and mobile phone). It explores the role of social media within friendworks while providing a communication perspective on social networks.

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The research on project learning has recognised the significance of knowledge transfer in project based organisations (PBOs). Effective knowledge transfer across projects avoids reinventions, enhances knowledge creation and saves lots of time that is crucial in project environment. In order to facilitate knowledge transfer, many PBOs have invested lots of financial and human resources to implement IT-based knowledge repository. However, some empirical studies found that employees would rather turn for knowledge to colleagues despite their ready access to IT-based knowledge repository. Therefore, it is apparent that social networks play a pivotal role in the knowledge transfer across projects. Some scholars attempt to explore the effect of network structure on knowledge transfer and performance, however, focused only on egocentric networks and the groupsâ internal social networks. It has been found that the projectâs external social network is also critical, in that the team members can not handle critical situations and accomplish the projects on time without the assistance and knowledge from external sources. To date, the influence of the structure of a project teamâs internal and external social networks on project performance, and the interrelation between both networks are barely known. In order to obtain such knowledge, this paper explores the interrelation between the structure of a project teamâs internal and external social networks, and their effect on the project teamâs performance. Data is gathered through survey questionnaire distributed online to respondents. Collected data is analysed applying social network analysis (SNA) tools and SPSS. The theoretical contribution of this paper is the knowledge of the interrelation between the structure of a project teamâs internal and external social networks and their influence on the project teamâs performance. The practical contribution lies in the guideline to be proposed for constructing the structure of project teamâs internal and external social networks.

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This paper presents a novel algorithm for the gateway placement problem in Backbone Wireless Mesh Networks (BWMNs). Different from existing algorithms, the new algorithm incrementally identifies gateways and assigns mesh routers to identified gateways. The new algorithm can guarantee to find a feasible gateway placement satisfying Quality-of-Service (QoS) constraints, including delay constraint, relay load constraint and gateway capacity constraint. Experimental results show that its performance is as good as that of the best of existing algorithms for the gateway placement problem. But, the new algorithm can be used for BWMNs that do not form one connected component, and it is easy to implement and use.

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Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.