912 resultados para nodes and links


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An application of image processing techniques to recognition of hand-drawn circuit diagrams is presented. The scanned image of a diagram is pre-processed to remove noise and converted to bilevel. Morphological operations are applied to obtain a clean, connected representation using thinned lines. The diagram comprises of nodes, connections and components. Nodes and components are segmented using appropriate thresholds on a spatially varying object pixel density. Connection paths are traced using a pixel-stack. Nodes are classified using syntactic analysis. Components are classified using a combination of invariant moments, scalar pixel-distribution features, and vector relationships between straight lines in polygonal representations. A node recognition accuracy of 82% and a component recognition accuracy of 86% was achieved on a database comprising 107 nodes and 449 components. This recogniser can be used for layout “beautification” or to generate input code for circuit analysis and simulation packages

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To facilitate the implementation of workflows, enterprise and workflow system vendors typically provide workflow templates for their software. Each of these templates depicts a variant of how the software supports a certain business process, allowing the user to save the effort of creating models and links to system components from scratch by selecting and activating the appropriate template. A combination of the strengths from different templates is however only achievable by manually adapting the templates which is cumbersome. We therefore suggest in this paper to combine different workflow templates into a single configurable workflow template. Using the workflow modeling language of SAP’s WebFlow engine, we show how such a configurable workflow modeling language can be created by identifying the configurable elements in the original language. Requirements imposed on configurations inhibit invalid configurations. Based on a default configuration such configurable templates can be used as easy as the traditional templates. The suggested approach is also applicable to other workflow modeling languages

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A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

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longitudinal study of data modelling across grades 1-3. The activity engaged children in designing, implementing, and analysing a survey about their new playground. 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. The core components of data modelling addressed here are children’s structuring and representing of data, with a focus on their display of metarepresentational competence (diSessa, 2004). Such competence includes students’ abilities to invent or design a variety of new representations, explain their creations, understand the role they play, and critique and compare the adequacy of representations. Reported here are the ways in which the children structured and represented their data, the metarepresentational competence displayed, and links between their metarepresentational competence and conceptual competence.

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Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

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Strong regulatory pressure and rising public awareness on environmental issues will continue to influence the market demand for sustainable housing for years to come. Despite this potential, the voluntary uptake rate of sustainable practices is not as high as expected within the new built housing industry. This is in contrast to the influx of emerging building technologies, new materials and innovative designs as showcased in office buildings and exemplar homes worldwide. One of the possible reasons for this under-performance is that key stakeholders such as developers, builders and consumers do not fully understand and appreciate the related challenges, risks and opportunities of pursuing sustainability. Therefore, in their professional and business activities, they may not be able to see the tangible and mutual benefits that sustainable housing may bring. This research investigates the multiple challenges to achieving benefits (CABs) from sustainable housing development, and links these factors to the characteristics of key stakeholders in the housing supply chain. It begins with a comparative survey study among seven stakeholder groups in the Australian housing industry, in order to examine the importance and interrelationships of CABs. In-depth interviews then further explore the survey findings with a focus on stakeholder diversity, which leads to the identification of 12 critical mutual-benefit factors and their interrelationship. Based on such a platform, a mutual-benefit framework is developed with the aid of Interpretive Structure Modelling, to identify the patterns of stakeholder benefit materialisation, suggest the priority of critical factors and provide related stakeholder-specific action guidelines for sustainable housing implementation. The study concludes with a case study of two real-life housing projects to test the application of the mutual-benefit framework for improvement. This framework will lead to a shared value of sustainability among stakeholders and improved stakeholder collaboration, which in turn help to break the "circle of blame" for the current under-performance of sustainable housing implementation.

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Food in schools is typically understood from a biomedical perspective. At practical, ideational and material levels, whether addressed pedagogically or bureaucratically, food in schools is generally considered from a natural sciences perspective. This perspective manifests as the bioenergetic principle of energy in versus energy out and appears in policy focused on issues such as obesity and physical activity. Despite the considerable literature on the sociology of food and eating, little is understood about food in schools from a sociological perspective. This oversight of one of the most fundamental requirements of the human condition--namely, food--should be of concern for educators. Investigating food through a political economy lens means understanding food in schools as part of broader economic, political, social and cultural conditions. Hence, a political economy of food and schooling is concerned with the formation of ideas about food relative to political, economic, and cultural ideologies in social practice. From a critical sociology study of food messages students receive in the primary school curriculum, this paper reports on some of the official food messages of an Australian state's education policy, as a case to highlight the current political economy of food in Australia. It examines the role of the corporate food industry in the formation of Australian food policy and how that policy created artefacts infused with competing messages. The paper highlights how food and nutrition policy moved from solely a health concern to incorporate an economic dimension and links that shift with the quality of food available in Queensland schools.

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Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

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This research develops a new framework to be used as a tool for analysing and designing walkable communities. The literature review recognises the work of other researchers combining their findings with the theory of activity nodes and considers how a framework may be used on a more global basis. The methodology develops a set of criteria through the analysis of noted successful case studies and this is then tested against an area with very low walking rates in Brisbane, Australia. Results of the study suggest that as well as the accepted criteria of connectivity, accessibility, safety, security, and path quality further criteria in the form or planning hierarchy, activity nodes and climate mitigation could be added to allow the framework to cover a broader context. Of particular note is the development of the nodal approach, which allows simple and effective analysis of existing conditions, and may also prove effective as a tool for planning and design of walkable communities.

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Chlamydia pneumoniae commonly causes respiratory tract infections in children, and epidemiological investigations strongly link infection to the pathogenesis of asthma. The immune system in early life is immature and may not respond appropriately to pathogens. Toll-like receptor (TLR)2 and 4 are regarded as the primary pattern recognition receptors that sense bacteria, however their contribution to innate and adaptive immunity in early life remains poorly defined. We investigated the role of TLR2 and 4 in the induction of immune responses to Chlamydia muridarum respiratory infection, in neonatal wild-type (Wt) or TLR2-deficient (−/−), 4−/− or 2/4−/− BALB/c mice. Wt mice had moderate disease and infection. TLR2−/− mice had more severe disease and more intense and prolonged infection compared to other groups. TLR4−/− mice were asymptomatic. TLR2/4−/− mice had severe early disease and persistent infection, which resolved thereafter consistent with the absence of symptoms in TLR4−/− mice. Wt mice mounted robust innate and adaptive responses with an influx of natural killer (NK) cells, neutrophils, myeloid (mDCs) and plasmacytoid (pDCs) dendritic cells, and activated CD4+ and CD8+ T-cells into the lungs. Wt mice also had effective production of interferon (IFN)γ in the lymph nodes and lung, and proliferation of lymph node T-cells. TLR2−/− mice had more intense and persistent innate (particularly neutrophil) and adaptive cell responses and IL-17 expression in the lung, however IFNγ responses and T-cell proliferation were reduced. TLR2/4−/− mice had reduced innate and adaptive responses. Most importantly, neutrophil phagocytosis was impaired in the absence of TLR2. Thus, TLR2 expression, particularly on neutrophils, is required for effective control of Chlamydia respiratory infection in early life. Loss of control of infection leads to enhanced but ineffective TLR4-mediated inflammatory responses that prolong disease symptoms. This indicates that TLR2 agonists may be beneficial in the treatment of early life Chlamydia infections and associated diseases.

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"This book systematically explores and clarifies the complexities of Austrealian Constitutional law and provides valuable critical analysis suitable for students, academics and government departments." -- book cover "Constitutional Law examines the foundational principles and concepts of this area of law. Written by practicing lawyers and lecturers in the subject, this book aims to provide an accessible yet comprehensive introductory text for Australian students. In eight parts this book systematically explores and clarifies the complexities of Australian Constitutional law and provides valuable critical analysis suitable for students, academics and government departments. An excellent resource for law students, Constitutional Law provides visual summaries in the form of flow charts, and each chapter includes key concepts and end-of-chapter discussion questions, further reading and useful websites and links. It also introduces students to key examinable areas, legal style essays, problems and assessment." -- publisher website

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Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

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In this paper we describe cooperative control algorithms for robots and sensor nodes in an underwater environment. Cooperative navigation is defined as the ability of a coupled system of autonomous robots to pool their resources to achieve long-distance navigation and a larger controllability space. Other types of useful cooperation in underwater environments include: exchange of information such as data download and retasking; cooperative localization and tracking; and physical connection (docking) for tasks such as deployment of underwater sensor networks, collection of nodes and rescue of damaged robots. We present experimental results obtained with an underwater system that consists of two very different robots and a number of sensor network modules. We present the hardware and software architecture of this underwater system. We then describe various interactions between the robots and sensor nodes and between the two robots, including cooperative navigation. Finally, we describe our experiments with this underwater system and present data.

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This paper examines the rise in the politicisation of Islam in Malaysia and links it to the othering of the Malaysian Malay. It is my argument that both were “conquering” tools of Malaysia’s “Father of Modernisation”, Mahathir Mohamad, devised to win the support of the Malay Muslim majority in Malaysia. The many awards bestowed on Mahathir obscure the fact that he was instrumental in the systematic erosion of the power and roles of state institutions, especially at the Federal government level. This includes the significant loss of the independence of the Malaysian judiciary. Whilst per capita income in Malaysia may well have increased eight times under his 22-year leadership, this paper asks why is it that the majority of the Malays remain the largest number among the poor and the more disenfranchised of ethnicities in the country? Why have Malay and Muslim women suffered such a rapid decreasing ability to access justice? This paper examines existing research on the social and political changes Malaysia has experienced with Islamisation and under Mahathir’s rule, as well as studies on Malayness, Malay nationalism and Muslim Malay identity formation. The paper elaborates the othering of a majority people, the Malays in Malaysia, and how this othering has brought forth a fast-growing political power in the name of a supremacist Islam, a puritanical Sunni and Malay Islam. Specific events in the rise and rule of Mahathir as Malaysia’s then Prime Minister are reviewed, such as the banning of The Malay Dilemma, and the split in the United Malays National Organisation (UMNO) in 1987. Also examined is the varying emphasis between Muslim and race, and how during Mahathir’s rule, that strong misogynist and patriarchal attitudes took hold in Malay Muslim consciousness, a colonising consciousness that is othering the perceived cultural and genetic “impurities” within the Malay.

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Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.