956 resultados para environmental modeling
Resumo:
Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.
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This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.
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CONTEXT AND OBJECTIVE: Suboptimal vitamin D status can be corrected by vitamin D supplementation, but individual responses to supplementation vary. We aimed to examine genetic and nongenetic determinants of change in serum 25-hydroxyvitamin D (25(OH)D) after supplementation. DESIGN AND PARTICIPANTS: We used data from a pilot randomized controlled trial in which 644 adults aged 60 to 84 years were randomly assigned to monthly doses of placebo, 30 000 IU, or 60 000 IU vitamin D3 for 12 months. Baseline characteristics were obtained from a self-administered questionnaire. Eighty-eight single-nucleotide polymorphisms (SNPs) in 41 candidate genes were genotyped using Sequenom MassArray technology. Serum 25(OH)D levels before and after the intervention were measured using the Diasorin Liaison platform immunoassay. We used linear regression models to examine associations between genetic and nongenetic factors and change in serum 25(OH)D levels. RESULTS: Supplement dose and baseline 25(OH)D level explained 24% of the variability in response to supplementation. Body mass index, self-reported health status, and ambient UV radiation made a small additional contribution. SNPs in CYP2R1, IRF4, MC1R, CYP27B1, VDR, TYRP1, MCM6, and HERC2 were associated with change in 25(OH)D level, although only CYP2R1 was significant after adjustment for multiple testing. Models including SNPs explained a similar proportion of variability in response to supplementation as models that included personal and environmental factors. CONCLUSION: Stepwise regression analyses suggest that genetic variability may be associated with response to supplementation, perhaps suggesting that some people might need higher doses to reach optimal 25(OH)D levels or that there is variability in the physiologically normal level of 25(OH)D.
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The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.
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In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.
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Nitrogen is an important nutrient that can impact the quality of aquatic environments when present in high concentration. Even though low concentration levels of ammonium-nitrogen have been observed in laboratory studies in bioretention basins, poor removal or even the production of nitrate-nitrogen within the filter is often recorded in such studies. Ten Perspex biofilter columns of 94 mm (internal diameter) were packed with a filter layer, transition layer and a gravel layer. While the filter layer was packed to a height of 800 mm, transition and gravel layers were packed to a composite height of 220 mm and operated with simulated stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. The columns were operated with different antecedent dry days (0 d to 21 d) and constant inflow concentration at a feed rate of 100 mL/min. Samples were collected from the outflow at different time intervals, between 2 min and 150 min from the start of outflow, and were tested for nitrate-nitrogen and total organic carbon. Washoff of organic carbon from the filter layer was observed to occur for 30 min of outflow. This indicated washoff of organic carbon from the filter itself. At the same time, a very low concentration of nitrate-nitrogen was recorded at the beginning of the outflow, indicating the effective removal of nitrate-nitrogen. We conclude that the removal of nitrate-nitrogen is insignificant during the wetting phase of a rainfall event and the process of denitrification is more pronounced during the drying phase of a rainfall event. Thus intermittent wetting and drying is crucial for the removal of nitrate-nitrogen in bioretention basins.
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Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.
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The type of contract model may have a significant influence on achieving project objectives, including environmental and climate change goals. This research investigates non-standard contract models impacting greenhouse gas emissions (GHG) in transport infrastructure construction in Australia. The research is based on the analysis of two case studies: an Early Contractor Involvement (ECI) contract and a Design and Construct (D&C) contract with GHG reduction requirements embedded in the contractor selection. Main findings support the use of ECIs for better integrating decisions made during the planning phase with the construction activities, and improve environmental outcomes while achieving financial and time savings. Key words: greenhouse gases reduction; road construction; contracting; ECI; D&C
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It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.
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Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem; the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.
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A multi-season 15N tracer recovery experiment was conducted on an Oxisol cropped with wheat, maize and sorghum to compare crop N recoveries of different fertilisation strategies and determine the main pathways of N losses that limit N recovery in these agroecosystems. In the wheat and maize seasons, 15N-labelled fertiliser was applied as conventional urea (CONV) and urea coated with a nitrification inhibitor (DMPP). In sorghum, the fate of 15N-labelled urea was monitored in this crop following a legume ley pasture (L70) or a grass ley pasture (G100). The fertiliser N applied to sorghum in the legume-cereal rotation was reduced (70 kg N ha−1) compared to the grass-cereal (100 kg N ha−1) to assess the availability of the N residual from the legume ley pasture. Average crop N recoveries were 73 % (CONV) and 77 % (DMPP) in wheat and 50 % (CONV) and 51 % (DMPP) in maize, while in sorghum were 71 % (L70) and 53 % (G100). Data gathered in this study indicate that the intrinsic physical and chemical conditions of Oxisols can be extremely effective in limiting N losses via deep leaching or denitrification. Elevated crop 15N recoveries can be therefore obtained in subtropical Oxisols using conventional urea while in these agroecosystems DMPP urea has no significant scope to increase fertiliser N recovery in the crop. Overall, introducing a legume phase to limit the fertiliser N requirements of the following cereal crop proved to be the most effective strategy to reduce N losses and increase fertiliser N recovery.
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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.
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Giving and Volunteering in Australia: literature review summarises the findings of a comprehensive literature search that identifies relevant research on giving and volunteering in Australia. The report comments on the strengths and weaknesses of the methods used and the lessons that can be learned for the development of a future research agenda. The report arranges the findings in separate sections under the headings government sources, industry sources, university/peer-reviewed sources and international comparative sources. We learned that in the last 25 years there has been a growing body of knowledge about the dimensions of giving and volunteering in Australia, but much of the available data is not easily comparable or collected at regular intervals.
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In the Australian fashion industry, few fashion brands have intervened in the design of their products or the systems around their product to tackle environmental pollution and waste. Instead, support of charities (whether social or environmental) has become conflated with sustainability in the eyes of the public. Thus it is difficult to assess with any accuracy fashion brands’ response to sustainability. This article aims to address this through proposing a categorization system to structure the various interventions that a company may make. This system is applied to two case studies, analysing campaigns that respond to environmental sustainability by two established Australian brands, Country Road and Billabong. The case studies demonstrate how the interventions employed by a company, at least in the Australian context, are carefully developed to align with their brand story, revealing the interplay between the intangible aspects of a brand’s positioning and the tangible, measurable impacts of their garments.