402 resultados para Horizontal network
Resumo:
Most forms of tissue healing depend critically on revascularisation. In soft tissues and in vitro, mechanical stimuli have been shown to promote vessel-forming activity. However, in bone defects, increased interfragmentary motion impairs vascular regeneration. Because these effects seem contradictory, we aimed to determine whether a range of mechanical stimuli exists in which angiogenesis is favoured. A series of cyclic strain magnitudes were applied to a Matrigel-based “tube formation” assay and the total lengths of networks formed by human microvascular endothelial cells measured at 24 h. Network lengths were reduced at all strain levels, compared to unstretched controls. However, the levels of pro-angiogenic matrix metalloproteases-2 and -9 in the corresponding conditioned media were unchanged by strain, and vascular endothelial growth factor was uniformly elevated in stretched conditions. By repeating the assay with the addition of conditioned media from mesenchymal stem cells cultivated in similar conditions, paracrine stimuli were shown to increase network lengths, but not to alter the negative effect of cyclic stretching. Together, these results demonstrate that directly applied periodic strains can inhibit endothelial organisation in vitro, and suggest that this may be due to physical disruption rather than biochemical modulation. Most importantly, the results indicate that the straining of endothelial cells and their assembly into vascular-like structures must be studied simultaneously to adequately characterise the mechanical influence on vessel formation.
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From the perspective of network, a project team’s social capital consists of conduits network, and resource exchange network. Prior research intensively studies the effect of the structure of conduits network on the team’s 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 team’s knowledge network mediates the effect of various conduit networks on the team’s 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 organization’s social capital, and hence improve the organization’s performance.
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With the rise of ubiquitous computing in recent years, concepts of spatiality have become a significant topic of discussion in design and development of multimedia systems. This article investigates spatial practices at the intersection of youth, technology, and urban space in Seoul, and examines what the author calls ‘transyouth’: in the South Korean context, these people are between the ages of 18 and 24, situated on the delicate border between digital natives and immigrants in Prensky’s (2001) terms. In the first section, the article sets out the technosocial environment of contemporary Seoul. This is followed by a discussion of social networking processes derived from semi-structured interviews conducted in 2007-8 with Seoul transyouth about their ‘lived experiences of the city.’ Interviewees reported how they interact to play, work, and live with and within the city’s unique environment. The article develops a theme of how technosocial convergence (re)creates urban environments and argues for a need to consider such user-driven spatial recreation in designing cities as (ubiquitous) urban networks in recognition of its changing technosocial contours of connections. This is explored in three spaces of different scales: Cyworld as an online social networking space; cocoon housing – a form of individual residential space which is growing rapidly in many Korean cities – as a private living space; and u-City (ubiquitous City) as the future macro-space of Seoul.
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Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.
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Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more generally on GNSS (Global Navigation Satellite System) measurements to achieve centimeter-level accuracy positioning in real-time. Reference station placement is an important problem in the design and deployment of network RTK systems as it directly affects the quality of the positioning service and the cost of the network RTK systems. This paper identifies a new reference station placement for network RTK, namely QoS-aware regional network RTK reference station placement problem, and proposes an algorithm for the new reference station placement problem. The algorithm can always produce a reference station placement solution that completely covers the region of network RTK.
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The distribution network reliability can be increased if distributed generators (DGs) are allowed to operate in both grid-connected and islanded operations when the network has a high DG penetration level. However, the current utility regulations do not allow for the islanded operation. The arc faults are the one of the major issues preventing the islanded operation, since the arc will not extinguish if the DGs are not disconnected. In this paper, the effect of a converter interfaced DG on an arc fault is investigated by considering different control strategies for the converter. The foldback current control characteristic is proposed to a converter interfaced DG to achieve quick arc extinction and self-restoration without disconnecting the DG in the event of an arc fault. The results are validated through PSCAD/EMTDC simulations.
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Read through a focus on the remediation of personal photography in the Flickr photosharing website, in this essay I treat vernacular creativity as a field of cultural practice; one that that does not operate inside the institutions or cultural value systems of high culture or the commercial popular media, and yet draws on and is periodically appropriated by these other systems in dynamic and productive ways. Because of its porosity to commercial culture and art practice, this conceptual model of ‘vernacular creativity’ implies a historicised account of ‘ordinary’ or everyday creative practice that accounts for both continuity and change and avoids creating a nostalgic desire for the recuperation of an authentic folk culture. Moving beyond individual creative practice, the essay concludes by considering the unintended consequences of vernacular creativity practiced in online social networks: in particular, the idea of cultural citizenship.
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Real-Time Kinematic (RTK) positioning is a technique used to provide precise positioning services at centimetre accuracy level in the context of Global Navigation Satellite Systems (GNSS). While a Network-based RTK (N-RTK) system involves multiple continuously operating reference stations (CORS), the simplest form of a NRTK system is a single-base RTK. In Australia there are several NRTK services operating in different states and over 1000 single-base RTK systems to support precise positioning applications for surveying, mining, agriculture, and civil construction in regional areas. Additionally, future generation GNSS constellations, including modernised GPS, Galileo, GLONASS, and Compass, with multiple frequencies have been either developed or will become fully operational in the next decade. A trend of future development of RTK systems is to make use of various isolated operating network and single-base RTK systems and multiple GNSS constellations for extended service coverage and improved performance. Several computational challenges have been identified for future NRTK services including: • Multiple GNSS constellations and multiple frequencies • Large scale, wide area NRTK services with a network of networks • Complex computation algorithms and processes • Greater part of positioning processes shifting from user end to network centre with the ability to cope with hundreds of simultaneous users’ requests (reverse RTK) There are two major requirements for NRTK data processing based on the four challenges faced by future NRTK systems, expandable computing power and scalable data sharing/transferring capability. This research explores new approaches to address these future NRTK challenges and requirements using the Grid Computing facility, in particular for large data processing burdens and complex computation algorithms. A Grid Computing based NRTK framework is proposed in this research, which is a layered framework consisting of: 1) Client layer with the form of Grid portal; 2) Service layer; 3) Execution layer. The user’s request is passed through these layers, and scheduled to different Grid nodes in the network infrastructure. A proof-of-concept demonstration for the proposed framework is performed in a five-node Grid environment at QUT and also Grid Australia. The Networked Transport of RTCM via Internet Protocol (Ntrip) open source software is adopted to download real-time RTCM data from multiple reference stations through the Internet, followed by job scheduling and simplified RTK computing. The system performance has been analysed and the results have preliminarily demonstrated the concepts and functionality of the new NRTK framework based on Grid Computing, whilst some aspects of the performance of the system are yet to be improved in future work.
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This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.
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Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.
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The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.
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Reflective learning is vital for successful practice-led education such as animation, multimedia design and graphic design, and social network sites can accommodate various learning styles for effective reflective learning. In this paper, the researcher studies reflective learning through social network sites with two animation units. These units aim to provide students with an understanding of the tasks and workflows involved in the production of style sheets, character sheets and motion graphics for use in 3D productions for film and television and game design. In particular, an assessment in these units requires students to complete their online reflective journals throughout the semester. The reflective learning has been integrated within the unit design and students are encouraged to reflect weekly learning processes and outcomes. A survey evaluating for students’ learning experience was conducted, and its outcomes indicate that social network site based reflective learning will not be effective without considering students’ learning circumstances and designing peer-to-peer interactions.
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The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.
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Networks form a key part of the infrastructure of contemporary governance arrangements and, as such, are likely to continue for some time. Networks can take many forms and be formed for many reasons. Some networks have been explicitly designed to generate a collective response to an issue; some arise from a top down perspective through mandate or coercion; while others rely more heavily on interpersonal relations and doing the right thing. In this paper, these three different perspectives are referred to as the “3I”s: Instrumental, Institutional or Interpersonal. It is proposed that these underlying motivations will affect the process dynamics within the different types of networks in different ways and therefore influence the type of outcomes achieved. This proposition is tested through a number of case studies. An understanding of these differences will lead to more effective design, management and clearer expectations of what can be achieved through networks.
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As a consequence of the increased incidence of collaborative arrangements between firms, the competitive environment characterising many industries has undergone profound change. It is suggested that rivalry is not necessarily enacted by individual firms according to the traditional mechanisms of direct confrontation in factor and product markets, but rather as collaborative orchestration between a number of participants or network members. Strategic networks are recognised as sets of firms within an industry that exhibit denser strategic linkages among themselves than other firms within the same industry. Based on this, strategic networks are determined according to evidence of strategic alliances between firms comprising the industry. As a result, a single strategic network represents a group of firms closely linked according to collaborative ties. Arguably, the collective outcome of these strategic relationships engineered between firms suggest that the collaborative benefits attributed to interorganisational relationships require closer examination in respect to their propensity to influence rivalry in intraindustry environments. Derived in large from the social sciences, network theory allows for the micro and macro examination of the opportunities and constraints inherent in the structure of relationships in strategic networks, establishing a relational approach upon which the conduct and performance of firms can be more fully understood. Research to date has yet to empirically investigate the relationship between strategic networks and rivalry. The limited research that has been completed utilising a network rationale to investigate competitive patterns in contemporary industry environments has been characterised by a failure to directly measure rivalry. Further, this prior research has typically embedded investigation in industry settings dominated by technological or regulatory imperatives, such as the microprocessor and airline industries. These industries, due to the presence of such imperatives, are arguably more inclined to support the realisation of network rivalry, through subscription to prescribed technological standards (eg., microprocessor industry) or by being bound by regulatory constraints dictating operation within particular market segments (airline industry). In order to counter these weaknesses, the proposition guiding research - Are patterns of rivalry predicted by strategic network membership? – is embedded in the United States Light Vehicles Industry, an industry not dominated by technological or regulatory imperatives. Further, rivalry is directly measured and utilised in research, thus distinguishing this investigation from prior research efforts. The timeframe of investigation is 1993 – 1999, with all research data derived from secondary sources. Strategic networks were defined within the United States Light Vehicles Industry based on evidence of horizontal strategic relationships between firms comprising the industry. The measure of rivalry used to directly ascertain the competitive patterns of industry participants was derived from the traditional Herfindahl Index, modified to account for patterns of rivalry observed at the market segment level. Statistical analyses of the strategic network and rivalry constructs found little evidence to support the contention of network rivalry; indeed, greater levels of rivalry were observed between firms comprising the same strategic network than between firms participating in opposing network structures. Based on these results, patterns of rivalry evidenced in the United States Light Vehicle Industry over the period 1993 – 1999 were not found to be predicted by strategic network membership. The findings generated by this research are in contrast to current theorising in the strategic network – rivalry realm. In this respect, these findings are surprising. The relevance of industry type, in conjunction with prevailing network methodology, provides the basis upon which these findings are contemplated. Overall, this study raises some important questions in relation to the relevancy of the network rivalry rationale, establishing a fruitful avenue for further research.