892 resultados para Characterizing Network Traffic
Resumo:
A tunable decoupling and matching network (DMN) for a closely spaced two-element antenna array is presented. The DMN achieves perfect matching for the eigenmodes of the array and thus simultaneously isolates and matches the system ports while keeping the circuit small. Arrays of closely spaced wire and microstrip monopole pairs are used to demonstrate the proposed DMN. It is found that monopoles with different lengths can be used for the design frequency by using this DMN, which increases the design flexibility. This property also enables frequency tuning using the DMN only without having to change the length of the antennas. The proposed DMN uses only one varactor to achieve a tuning range of 18.8% with both return loss and isolation better than 10-dB when the spacing between the antenna is 0.05λ. When the spacing increases to 0.1λ, the simulated tuning range is more than 60%.
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This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a “toolbox” of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel-Machine Job-Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK-BIH-TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best-Insertion-Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints.
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The next-generation of service-oriented architecture (SOA) needs to scale for flexible service consumption, beyond organizational and application boundaries, into communities, ecosystems and business networks. In wider and, ultimately, global settings, new capabilities are needed so that business partners can efficiently and reliably enable, adapt and expose services. Those services can then be discovered, ordered, consumed, metered and paid for, through new applications and opportunities, driven by third-parties in the global “village”. This trend is already underway, in different ways, through different early adopter market segments. This paper proposes an architectural strategy for the provisioning and delivery of services in communities, ecosystems and business networks – a Service Delivery Framework (SDF). The SDF is intended to support multiple industries and deployments where a SOA platform is needed for collaborating partners and diverse consumers. Specifically, it is envisaged that the SDF allows providers to publish their services into network directories so that they can be repurposed, traded and consumed, and leveraging network utilities like B2B gateways and cloud hosting. To support these different facets of service delivery, the SDF extends the conventional service provider, service broker and service consumer of the Web Services Architecture to include service gateway, service hoster, service aggregator and service channel maker.
Resumo:
High Speed Rail (HSR) is rapidly gaining popularity worldwide as a safe and efficient transport option for long-distance travel. Designed to win market shares from air transport, HSR systems optimise their productivity between increasing speeds and station spacing to offer high quality service and gain ridership. Recent studies have investigated the effects that the deployment of HSR infrastructure has on spatial distribution and the economic development of cities and regions. Findings appear mostly positive at higher geographical scales, where HSR links connect major urban centres several hundred kilometres apart and already well positioned within a national or international context. Also, at the urban level, studies have shown regeneration and concentration effects around HSR station areas with positive returns on city’s image and economy. However, doubts persist on the effects of HSR at an intermediate scale, where the accessibility trade off on station spacing limits access to many small and medium agglomerations. Thereby, their ability to participate in the development opportunities facilitated by HSR infrastructure is significantly reduced. The locational advantages deriving from transport improvements appear contrasting especially in regions that tend to have a polycentric structure, where cities may present greater accessibility disparities between those served by HSR and those left behind. This thesis fits in this context where intermediate and regional cities do not directly enjoy the presence of an HSR station while having an existing or planned proximate HSR corridor. With the aim of understanding whether there might be a solution to this apparent incongruity, the research investigates strategies to integrate HSR accessibility at the regional level. While current literature recommends to commit with ancillary investments to the uplift of station areas and the renewal of feeder systems, I hypothesised the interoperability between the HSR and the conventional networks to explore the possibilities offered by mixed traffic and infrastructure sharing. Thus, I developed a methodology to quantify the exchange of benefits deriving from this synergistic interaction. In this way, it was possible to understand which level of service quality offered by alternative transit strategies best facilitates the distribution of accessibility benefits for areas far from actual HSR stations. Therefore, strategies were selected for their type of service capable of regional extensions and urban penetrations, while incorporating a combination of specific advantages (e.g. speed, sub-urbanity, capacity, frequency and automation) in order to emulate HSR quality with increasingly efficient services. The North-eastern Italian macro region was selected as case study to ground the research offering concurrently a peripheral polycentric metropolitan form, the presence of a planned HSR corridor with some portions of HSR infrastructure implementation, and the project to develop a suburban rail service extended regionally. Results show significant distributive potential, in terms of network effects produced in relation with HSR, in increasing proportions for all the strategies considered: a regional metro rail strategy (abbreviated RMR), a regional high speed rail strategy (abbreviated RHSR), a regional light rail transit (abbreviated LRT) strategy, and a non-stopping continuous railway system (abbreviated CRS) strategy. The provision of additional tools to value HSR infrastructure against its accessibility benefits and their regional distribution through alternative strategies beyond the actual HSR stations, would have great implications, both politically and technically, in moving towards new dimensions of HSR evaluation and development.
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The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.
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Road traffic noise affects the quality of life in the areas adjoining the road. The effect of traffic noise on people is wide ranging and may include sleep disturbance and negative impact on work efficiency. To address the problem of traffic noise, it is necessary to estimate the noise level. For this, a number of noise estimation models have been developed which can estimate noise at the receptor points, based on simple configuration of buildings. However, for a real world situation we have multiple buildings forming built-up area. In such a situation, it is almost impossible to consider multiple diffractions and reflections in sound propagation from the source to the receptor point. An engineering solution to such a real world problem is needed to estimate noise levels in built-up area.
Resumo:
Traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) pose a serious threat to human and ecosystem health when washed off into receiving water bodies by stormwater. Climate change influenced rainfall characteristics makes the estimation of these pollutants in stormwater quite complex. The research study discussed in the paper developed a prediction framework for such pollutants under the dynamic influence of climate change on rainfall characteristics. It was established through principal component analysis (PCA) that the intensity and durations of low to moderate rain events induced by climate change mainly affect the wash-off of SVOCs and NVOCs from urban roads. The study outcomes were able to overcome the limitations of stringent laboratory preparation of calibration matrices by extracting uncorrelated underlying factors in the data matrices through systematic application of PCA and factor analysis (FA). Based on the initial findings from PCA and FA, the framework incorporated orthogonal rotatable central composite experimental design to set up calibration matrices and partial least square regression to identify significant variables in predicting the target SVOCs and NVOCs in four particulate fractions ranging from >300-1 μm and one dissolved fraction of <1 μm. For the particulate fractions range >300-1 μm, similar distributions of predicted and observed concentrations of the target compounds from minimum to 75th percentile were achieved. The inter-event coefficient of variations for particulate fractions of >300-1 μm were 5% to 25%. The limited solubility of the target compounds in stormwater restricted the predictive capacity of the proposed method for the dissolved fraction of <1 μm.
Resumo:
Traffic related emissions have been recognised as one of the main sources of air pollutants. In the research study discussed in this paper, variability of atmospheric total suspended particulate matter (TSP), polycyclic aromatic hydrocarbons (PAH) and heavy metal (HM) concentrations with traffic and land use characteristics during weekdays and weekends were investigated. Data required for the study were collected from a range of sampling sites to ensure a wide mix of traffic and land use characteristics. The analysis undertaken confirmed that zinc has the highest concentration in the atmospheric phase during weekends as well as weekdays. Although the use of leaded gasoline was discontinued a decade ago, lead was the second most commonly detected heavy metal. This is attributed to the association of previously generated lead with roadside soil and re-suspension to the atmosphere. Soil related particles are the primary source of TSP and manganese to the atmosphere. The analysis further revealed that traffic sources are dominant in gas phase PAHs compared to the other sources during weekdays. Land use related sources become important contributors to atmospheric PAHs during weekends when traffic sources are at their minimal levels.
Resumo:
Just as telecommunications has played a key role in the global economy,1 high-speed broadband will have a significant role to play in the future of the digital economy. In particular high-speed broadband will have a role to play in the delivery of applications and services necessary for acquiring, and maintaining into the future Australia and Australians’ appropriate education level; community; health services, information provision and support; government services and engagement and participation by the public in the political process.
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This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.
Resumo:
Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.
Resumo:
The use of the internet for political purposes is not new; however, the introduction of social media tools has opened new avenues for political activists. In an era where social media has been credited as playing a critical role in the success of revolutions (Earl & Kimport, 2011; Papic & Noonan, 2011; Wooley, Limperos & 10 Beth, 2010), governments, law enforcement and intelligence agencies need to develop a deeper understanding of the broader capabilities of this emerging social and political environment. This can be achieved by increasing their online presence and through the application of proactive social media strategies to identify and manage potential threats. Analysis of current literature shows a gap 15 in the research regarding the connection between the theoretical understanding and practical implications of social media when exploited by political activists,and the efficacy of existing strategies designed to manage this growing challenge. This paper explores these issues by looking specifically at the use of three popular social media tools: Facebook; Twitter; and YouTube. Through the examination of 20 recent political protests in Iran, the UK and Egypt from 2009�2011, these case studies and research in the use of the three social media tools by political groups, the authors discuss inherent weaknesses in online political movements and discuss strategies for law enforcement and intelligence agencies to monitor these activities.
Resumo:
A practical method for the design of dual-band decoupling and matching networks (DMN) for two closely spaced antennas using discrete components is presented. The DMN reduces the port-to-port coupling and enhances the diversity of the antennas. By applying the DMN, the radiation efficiency can also be improved when one port is fed and the other port is match terminated. The proposed DMN works at two frequencies simultaneously without the need for any switch. As a proof of concept, a dual-band DMN for a pair of monopoles spaced 0.05λ apart is designed. The measured return loss and port isolation exceed 10 dB from 1.71 GHz to 1.76 GHz and from 2.27 GHz to 2.32 GHz.