996 resultados para Nutrient Network
Resumo:
The Chemistry Discipline Network was funded in mid-2011, with the aim of improving communication between chemistry academics in Australia. In our first year of operation, we have grown to over 100 members, established a web presence, and produced substantial mapping reports on chemistry teaching in Australia. We are now working on the definition of standards for a chemistry degree based on the Threshold Learning Outcomes published by the Learning and Teaching Academic Standards Project.
A hybrid simulation framework to assess the impact of renewable generators on a distribution network
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With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.
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In this paper a combined subtransmission and distribution reliability analysis of SEQEB’s outer suburban network is presented. The reliability analysis was carried out with a commercial software package which evaluates both energy and customer indices. Various reinforcement options were investigated to ascertain the impact they have on the reliability of supply seen by the customers. The customer and energy indices produced by the combined subtransmission and distribution reliability studies contributed to optimise capital expenditure to the most effective areas of the network.
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Given the paradigm of smart grid as the promising backbone for future network, this paper uses this paradigm to propose a new coordination approach for LV network based on distributed control algorithm. This approach divides the LV network into hierarchical communities where each community is controlled by a control agent. Different level of communication has been proposed for this structure to control the network in different operation modes.
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This paper presents a new approach for network upgrading to improve the penetration level of Small Scale Generators in residential feeders. In this paper, it is proposed that a common DC link can be added to LV network to alleviate the negative impact of increased export power on AC lines, allowing customers to inject their surplus power with no restrictions to the common DC link. In addition, it is shown that the proposed approach can be a pathway from current AC network to future DC network.
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NeSSi (network security simulator) is a novel network simulation tool which incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Its capabilities such as profile-based automated attack generation, traffic analysis and support for detection algorithm plug-ins allow it to be used for security research and evaluation purposes. NeSSi has been successfully used for testing intrusion detection algorithms, conducting network security analysis and developing overlay security frameworks. NeSSi is built upon the agent framework JIAC, resulting in a distributed and extensible architecture. In this paper, we provide an overview of the NeSSi architecture as well as its distinguishing features and briefly demonstrate its application to current security research projects.
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In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.
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Return side streams from anaerobic digesters and dewatering facilities at wastewater treatment plants (WWTPs) contribute a significant proportion of the total nitrogen load on a mainstream process. Similarly, significant phosphate loads are also recirculated in biological nutrient removal (BNR) wastewater treatment plants. Ion exchange using a new material, known by the name MesoLite, shows strong potential for the removal of ammonia from these side streams and an opportunity to concurrently reduce phosphate levels. A pilot plant was designed and operated for several months on an ammonia rich centrate from a dewatering centrifuge at the Oxley Creek WWTP, Brisbane, Australia. The system operated with a detention time in the order of one hour and was operated for between 12 and 24 hours prior to regeneration with a sodium rich solution. The same pilot plant was used to demonstrate removal of phosphate from an abattoir wastewater stream at similar flow rates. Using MesoLite materials, >90% reduction of ammonia was achieved in the centrate side stream. A full-scale process would reduce the total nitrogen load at the Oxley Creek WWTP by at least 18%. This reduction in nitrogen load consequently improves the TKN/COD ratio of the influent and enhances the nitrogen removal performance of the biological nutrient removal process.
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Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.
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Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.
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Nitrogen balance is increasingly used as an indicator of the environmental performance of agricultural sector in national, international, and global contexts. There are three main methods of accounting the national nitrogen balance: farm gate, soil surface, and soil system. OECD (2008) recently reported the nitrogen and phosphorus balances for member countries for the 1985 - 2004 period using the soil surface method. The farm gate and soil system methods were also used in some international projects. Some studies have provided the comparison among these methods and the conclusion is mixed. The motivation of this present paper was to combine these three methods to provide a more detailed auditing of the nitrogen balance and flows for national agricultural production. In addition, the present paper also provided a new strategy of using reliable international and national data sources to calculate nitrogen balance using the farm gate method. The empirical study focused on the nitrogen balance of OECD countries for the period from 1985 to 2003. The N surplus sent to the total environment of OECD surged dramatically in early 1980s, gradually decreased during 1990s but exhibited an increasing trends in early 2000s. The overall N efficiency however fluctuated without a clear increasing trend. The eco-environmental ranking shows that Australia and Ireland were the worst while Korea and Greece were the best.
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We present a virtual test bed for network security evaluation in mid-scale telecommunication networks. Migration from simulation scenarios towards the test bed is supported and enables researchers to evaluate experiments in a more realistic environment. We provide a comprehensive interface to manage, run and evaluate experiments. On basis of a concrete example we show how the proposed test bed can be utilized.
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As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.
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The existence of the Macroscopic Fundamental Diagram (MFD), which relates network space-mean density and flow, has been shown in urban networks under homogeneous traffic conditions. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. The key requirements for the well-defined MFD is the homogeneity of the area wide traffic condition, which is not universally expected in real world. For the practical application of the MFD concept, several researchers have identified the influencing factors for network homogeneity. However, they did not explicitly take drivers’ behaviour under real time information provision into account, which has a significant impact on the shape of the MFD. This research aims to demonstrate the impact of drivers’ route choice behaviour on network performance by employing the MFD as a measurement. A microscopic simulation is chosen as an experimental platform. By changing the ratio of en-route informed drivers and pre-trip informed drivers as well as by taking different route choice parameters, various scenarios are simulated in order to investigate how drivers’ adaptation to the traffic congestion influences the network performance and the MFD shape. This study confirmed and addressed the impact of information provision on the MFD shape and highlighted the significance of the route choice parameter setting as an influencing factor in the MFD analysis.
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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.