962 resultados para Alleyn, Edward, 1566-1626.
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Understanding the link between tectonic-driven extensional faulting and volcanism is crucial from a hazard perspective in active volcanic environments, while ancient volcanic successions provide records on how volcanic eruption styles, compositions, magnitudes and frequencies can change in response to extension timing, distribution and intensity. This study draws on intimate relationships of volcanism and extension preserved in the Sierra Madre Occidental (SMO) and Gulf of California (GoC) regions of western Mexico. Here, a major Oligocene rhyolitic ignimbrite “flare-up” (>300,000 km3) switched to a dominantly bimodal and mixed effusive-explosive volcanic phase in the Early Miocene (~100,000 km3), associated with distributed extension and opening of numerous grabens. Rhyolitic dome fields were emplaced along graben edges and at intersections of cross-graben and graben-parallel structures during early stages of graben development. Concomitant with this change in rhyolite eruption style was a change in crustal source as revealed by zircon chronochemistry with rapid rates of rhyolite magma generation due to remelting of mid- to upper crustal, highly differentiated igneous rocks emplaced during earlier SMO magmatism. Extension became more focused ~18 Ma resulting in volcanic activity being localised along the site of GoC opening. This localised volcanism (known as the Comondú “arc”) was dominantly effusive and andesite-dacite in composition. This compositional change resulted from increased mixing of basaltic and rhyolitic magmas rather than fluid flux melting of the mantle wedge above the subducting Guadalupe Plate. A poor understanding of space-time relationships of volcanism and extension has thus led to incorrect past tectonic interpretations of Comondú-age volcanism.
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Large igneous provinces (LIPs) host the most frequently recurring, largest volume basaltic & silicic eruptions on Earth. The largest volume (>1000 km^3 DRE) and magnitude (>M8) eruptions produce areally extensive (10^4-10^5 km^2) basaltic flow fields and sills, and silicic ignimbrites that are the main LIP building blocks. Basaltic and silicic eruptions have comparable magnitudes, but silicic ignimbrite volumes may be significantly underestimated due to unrecognized and correlated, but voluminous co-ignimbrite ash deposits. Magma composition is no barrier to individual eruption volume. Despite similar magnitudes, flood basaltic and silicic eruptions are very different in eruption mechanism, duration, intensity, vent configuration, and emplacement style. Flood basalts are dominantly effusive Hawaiian-Strombolian, with magma discharge rates of ~10^7-10^8 kg s^-1, and produce dominantly compound pahoehoe flow fields over eruption durations most likely >10 yrs. Most silicic eruptions are moderately to highly explosive, producing cocurrent pyroclastic fountains (rarely Plinian) and suggested to be of short-duration (hours to days) and high intensity (~10^11 kg s^-1). Eruption frequencies are elevated for largemagnitude eruptions of both magma types during LIP formation. In basalt-dominated provinces, large magnitude (>M8) eruptions have much shorter recurrence intervals (10^3-10^4 years) than similar magnitude silicic eruptions (~10^5 years). The huge volumes of magma erupted rapidly in LIPs raises several unresolved issues in terms of locus of magma generation and storage (if any) in the crust prior to eruption, the paths and rates of ascent from magma reservoirs to the surface, and relative aerosol contributions to the stratosphere from the flood basaltic and rhyolitic eruptions.
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Bus travel time estimation and prediction are two important modelling approaches which could facilitate transit users in using and transit providers in managing the public transport network. Bus travel time estimation could assist transit operators in understanding and improving the reliability of their systems and attracting more public transport users. On the other hand, bus travel time prediction is an important component of a traveller information system which could reduce the anxiety and stress for the travellers. This paper provides an insight into the characteristic of bus in traffic and the factors that influence bus travel time. A critical overview of the state-of-the-art in bus travel time estimation and prediction is provided and the needs for research in this important area are highlighted. The possibility of using Vehicle Identification Data (VID) for studying the relationship between bus and cars travel time is also explored.
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Travel time in an important transport performance indicator. Different modes of transport (buses and cars) have different mechanical and operational characteristics, resulting in significantly different travel behaviours and complexities in multimodal travel time estimation on urban networks. This paper explores the relationship between bus and car travel time on urban networks by utilising the empirical Bluetooth and Bus Vehicle Identification data from Brisbane. The technologies and issues behind the two datasets are studied. After cleaning the data to remove outliers, the relationship between not-in-service bus and car travel time and the relationship between in-service bus and car travel time are discussed. The travel time estimation models reveal that the not-in-service bus travel time are similar to the car travel time and the in-service bus travel time could be used to estimate car travel time during off-peak hours
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Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.
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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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This insightful volume presents a collection of innovative works by two of the leading researchers of firm growth: Per Davidsson, Director, Australian Centre for Entrepreneurship Research and Professor of Entrepreneurship, Queensland University of Technology, Australia and Jönköping International Business School, Sweden and Johan Wiklund, Professor of Entrepreneurship, Syracuse University, US and Jönköping International Business School, Sweden. The studies extend previous research by providing stronger theoretical underpinnings and using longitudinal databases that can separate in time the firms’ growth from its presumed causes. They also break new ground by examining different modes of growth, such as sales growth vs. employment growth, and organic growth vs. acquisition-based expansion. Further, the studies investigate the drivers of firm growth and take a critical look at the effects, such as under what circumstances high growth is associated with high profitability. The issue of how firm growth is achieved and managed, and what consequences it has for different stakeholders is both theoretically interesting and practically important. The book will strongly appeal to academics of entrepreneurship, small business management and strategy.
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Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.
Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies
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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.
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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.
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Motorway off-ramps are a significant source of traffic congestion and collisions. Heavy diverging traffic to off-ramps slows down the mainline traffic speed. When the off-ramp queue spillbacks onto the mainline, it leads to a major breakdown of the motorway capacity and a significant threat to the traffic safety. This paper proposes using Variable Speed Limits (VSL) for protection of the motorway off-ramp queue and thus to promote safety in congested diverging areas. To support timely activation of VSL in advance of queue spillover, a proactive control strategy is proposed based on a real-time off-ramp queue estimation and prediction. This process determines the estimated queue size in the near-term future, on which the decision to change speed limits is made. VSL can effectively slow down traffic as it is mandatory that drivers follow the changed speed limits. A collateral benefit of VSL is its potential effect on drivers making them more attentive to the surrounding traffic conditions, and prepared for a sudden braking of the leading car. This paper analyses and quantifies these impacts and potential benefits of VSL on traffic safety and efficiency using the microsimulation approach.
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The second volume of the Handbook on the Knowledge Economy is a worthy companion to the highly successful original volume published in 2005, extending its theoretical depth and developing its coverage. Together the two volumes provide the single best work and reference point for knowledge economy studies. The second volume with fifteen original essays by renowned scholars in the field, provides insightful and robust analyses of the development potential of the knowledge economy in all its aspects, forms and manifestations.
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The nonprofit funding landscape is in flux. Many organisations are having to think differently and develop fresh skills either to enter the fundraising market or to cope better with rising competition for community and corporate support. This new reality affects boards, CEOs and fundraisers alike. Against this backdrop, our exploratory study aimed to build an evidence base and spark more discussion about: - the role Australian nonprofit CEOs and boards play in supporting fundraising/development; - current engagement levels; and - perceptions of leadership in fundraising from two possibly contrasting perspectives: NP leaders (board members and CEOs); and fundraisers. This research has been supported by the Perpetual Foundation, the EF and SL Gluyas Trust and the Edward Corbould Charitable Trust under the management of Perpetual Trustee Company Ltd.
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Modern and Postmodern Los Angeles is examined through the lens of film noir and neo noir. The unique relationship between the city of Los Angeles and cinema is discussed in terms of a historiography emphasizing the role played by these defining film styles and genres. The research draws and extends on the work conducted by Edward Dimendberg, Paula Rabinowitz and Mike Davis, and urban theory approaches associated with the Los Angeles School of Urbanism.