965 resultados para LOCATION NETWORK WWLLN


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The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

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A technologically innovative study was undertaken across two suburbs in Brisbane, Australia, to assess socioeconomic differences in women's use of the local environment for work, recreation, and physical activity. Mothers from high and low socioeconomic suburbs were instructed to continue with usual daily routines, and to use mobile phone applications (Facebook Places, Twitter, and Foursquare) on their mobile phones to ‘check-in’ at each location and destination they reached during a one-week period. These smartphone applications are able to track travel logistics via built-in geographical information systems (GIS), which record participants’ points of latitude and longitude at each destination they reach. Location data were downloaded to Google Earth and excel for analysis. Women provided additional qualitative data via text regarding the reasons and social contexts of their travel. We analysed 2183 ‘check-ins’ for 54 women in this pilot study to gain quantitative, qualitative, and spatial data on human-environment interactions. Data was gathered on distances travelled, mode of transport, reason for travel, social context of travel, and categorised in terms of physical activity type – walking, running, sports, gym, cycling, or playing in the park. We found that the women in both suburbs had similar daily routines with the exception of physical activity. We identified 15% of ‘check-ins’ in the lower socioeconomic group as qualifying for the physical activity category, compared with 23% in the higher socioeconomic group. This was explained by more daily walking for transport (1.7kms to 0.2kms) and less car travel each week (28.km to 48.4kms) in the higher socioeconomic suburb. We ascertained insights regarding the socio-cultural influences on these differences via additional qualitative data. We discuss the benefits and limitations of using new technologies and Google Earth with implications for informing future physical and social aspects of urban design, and health promotion in socioeconomically diverse cities.

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GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behaviour through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.

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Strike-slip faults commonly display structurally complex areas of positive or negative topography. Understanding the development of such areas has important implications for earthquake studies and hydrocarbon exploration. Previous workers identified the key factors controlling the occurrence of both topographic modes and the related structural styles. Kinematic and stress boundary conditions are of first-order relevance. Surface mass transport and material properties affect fault network structure. Experiments demonstrate that dilatancy can generate positive topography even under simple-shear boundary conditions. Here, we use physical models with sand to show that the degree of compaction of the deformed rocks alone can determine the type of topography and related surface fault network structure in simple-shear settings. In our experiments, volume changes of ∼5% are sufficient to generate localized uplift or subsidence. We discuss scalability of model volume changes and fault network structure and show that our model fault zones satisfy geometrical similarity with natural flower structures. Our results imply that compaction may be an important factor in the development of topography and fault network structure along strike-slip faults in sedimentary basins.

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Purpose – The purpose of this paper is to contribute to the sociology-of-science type of accounting literature, addressing how accounting knowledge is established, advanced and extended. Design/methodology/approach – The research question is answered through the example of research into linkages between accounting and religion. Adopting an actor-network theory (ANT) approach, the paper follows the actors involved in the construction of accounting as an academic discipline through the controversies in which they engage to develop knowledge. Findings – The paper reveals that accounting knowledge is established, advanced and developed through the ongoing mobilisation of nonhumans (journals) who can enrol other humans and nonhumans. It shows that knowledge advancement, establishment and development is more contingent on network breadth than on research paradigms, which appear as side-effects of positioning vis-a-vis a community. Originality/value – The originality of this paper is twofold. First, ANT is applied to accounting knowledge, whereas the accounting literature applies it to the spread of management accounting ideas, methods and practices. Second, an original methodology for data collection is developed by inviting authors from the network to give a reflexive account of their writings at the time they joined the network. Well diffused in sociology and philosophy, such an approach is, albeit, original in accounting research.

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Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.

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This thesis explores how governance networks prioritise and engage with their stakeholders, by studying three exemplars of “Regional Road Group” governance networks in Queensland, Australia. In the context of managing regionally significant road works programs, stakeholder prioritisation is a complex activity which is unlikely to influence interactions with stakeholders outside of the network. However, stakeholder priority is more likely to influence stakeholder interactions within the networks themselves. Both stakeholder prioritisation and engagement are strongly influenced by the way that the networks are managed, and in particular network operating rules and continuing access to resources.

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Objective: Effective management of multi-resistant organisms is an important issue for hospitals both in Australia and overseas. This study investigates the utility of using Bayesian Network (BN) analysis to examine relationships between risk factors and colonization with Vancomycin Resistant Enterococcus (VRE). Design: Bayesian Network Analysis was performed using infection control data collected over a period of 36 months (2008-2010). Setting: Princess Alexandra Hospital (PAH), Brisbane. Outcome of interest: Number of new VRE Isolates Methods: A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). BN enables multiple interacting agents to be studied simultaneously. The initial BN model was constructed based on the infectious disease physician‟s expert knowledge and current literature. Continuous variables were dichotomised by using third quartile values of year 2008 data. BN was used to examine the probabilistic relationships between VRE isolates and risk factors; and to establish which factors were associated with an increased probability of a high number of VRE isolates. Software: Netica (version 4.16). Results: Preliminary analysis revealed that VRE transmission and VRE prevalence were the most influential factors in predicting a high number of VRE isolates. Interestingly, several factors (hand hygiene and cleaning) known through literature to be associated with VRE prevalence, did not appear to be as influential as expected in this BN model. Conclusions: This preliminary work has shown that Bayesian Network Analysis is a useful tool in examining clinical infection prevention issues, where there is often a web of factors that influence outcomes. This BN model can be restructured easily enabling various combinations of agents to be studied.

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The host location behaviour of foraging caterpillars has received little attention, despite the wealth of theoretical and empirical studies that have been directed at this behavioural trait in adult Lepidoptera. Here, we study caterpillars of the moth Heliothis punctifera Walker (Lepidoptera: Noctuidae), which inhabits the arid inland desert areas of Australia. Caterpillars of this species consume many flowerheads before completing development and can be observed moving across the sand in search of new hosts. Consequently, if host location behaviour favours attraction to certain plant species, it might be expected to influence the distribution and abundance of caterpillars in the field. We present field data showing that H. punctifera caterpillars are unevenly distributed throughout mixed patches of two of its host species, with a higher abundance on Senecio gregorii F. Muell., the annual yellow top, compared to Myriocephalus stuartii (F. Muell. & Sond.) Benth., the poached egg daisy (both Asteraceae). Using laboratory studies, we test whether this distribution may, in part, be due to host location behaviour of caterpillars. Our results show that caterpillars exhibit a preference for locating S. gregorii in their pre- and post-contact foraging behaviour. In addition, our results provide evidence that feeding history plays a role in host location behaviour in this insect. We propose that key features of the desert environment and the ecology of H. punctifera would favour adaptations to host location behaviour by immatures.

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This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

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In this work, ab initio spin-polarised Density Functional Theory (DFT) calculations are performed to study the interaction of a Ti atom with a NaAlH4(001) surface. We confirm that an interstitially located Ti atom in the NaAlH4 subsurface is the most energetically favoured configuration as recently reported (Chem. Comm. (17) 2006, 1822). On the NaAlH4(001) surface, the Ti atom is most stable when adsorbed between two sodium atoms with an AlH4 unit beneath. A Ti atom on top of an Al atom is also found to be an important structure at low temperatures. The diffusion of Ti from the Al-top site to the Na-bridging site has a low activation barrier of 0.20 eV and may be activated at the experimental temperatures (∼323 K). The diffusion of a Ti atom into the energetically favoured subsurface interstitial site occurs via the Na-bridging surface site and is essentially barrierless.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

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The use of intelligent transport systems is proliferating across the Australian road network, particularly on major freeways. New technology allows a greater range of signs and messages to be displayed to drivers. While there has been a long history of human factors analyses of signage, no evaluation has been conducted on this novel, sometimes dynamic, signage or potential interactions when co-located. The purpose of this driving simulator study was to investigate drivers’ behavioural changes and comprehension resulting from the co-location of Lane Use Management Systems with static signs and (Enhanced) Variable Message Signs on Queensland motorways. A section of motorway was simulated, and nine scenarios were developed which presented a combination of signage cases across levels of driving task complexity. Two higher-risk road user groups were targeted for this research on an advanced driving simulator: older (65+ years, N=21) and younger (18-22 years, N=20) drivers. Changes in sign co-location and task complexity had small effect on driver comprehension of the signs and vehicle dynamics variables, including difference with the posted speed limit, headway, standard deviation of lane keeping and brake jerks. However, increasing the amount of information provided to drivers at a given location (by co-locating several signs) increased participants’ gaze duration on the signs. With co-location of signs and without added task complexity, a single gaze was over 2s for more than half of the population tested for both groups, and up to 6 seconds for some individuals.

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Often voltage rise along low voltage (LV) networks limits their capacity to accommodate more renewable energy (RE) sources. This paper proposes a robust and effective approach to coordinate customers' resources and control voltage rise in LV networks, where photovoltaics (PVs) are considered as the RE sources. The proposed coordination algorithm includes both localized and distributed control strategies. The localized strategy determines the value of PV inverter active and reactive power, while the distributed strategy coordinates customers' energy storage units (ESUs). To verify the effectiveness of proposed approach, a typical residential LV network is used and simulated in the PSCAD-EMTC platform.

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This thesis examines the use of network governance in US airport transportation planning activities involving taxicab services for airport patrons. The research provides US airports with new insights whereby they can successfully engage with both transportation regulatory agencies and taxicab service providers in developing mutually agreeable policies that foster the development of supply-side taxicab service improvements. A mix of quantitative and qualitative research methods is used to unearth how US airports interact with these actors, and to identify attitudes held by airport staff in their engagements involving airport taxicab planning matters. The research may ultimately lead to the achievement of sustainable increases in the air passenger ground transportation modal share at US airports, resulting in both desirable long-term operational and environmental benefits for airport management, those involved with the provision of airport taxicab services, and the traveling public.