894 resultados para Averaging operators


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Uncooperative iris identification systems at a distance and on the move often suffer from poor resolution and poor focus of the captured iris images. The lack of pixel resolution and well-focused images significantly degrades the iris recognition performance. This paper proposes a new approach to incorporate the focus score into a reconstruction-based super-resolution process to generate a high resolution iris image from a low resolution and focus inconsistent video sequence of an eye. A reconstruction-based technique, which can incorporate middle and high frequency components from multiple low resolution frames into one desired super-resolved frame without introducing false high frequency components, is used. A new focus assessment approach is proposed for uncooperative iris at a distance and on the move to improve performance for variations in lighting, size and occlusion. A novel fusion scheme is then proposed to incorporate the proposed focus score into the super-resolution process. The experiments conducted on the The Multiple Biometric Grand Challenge portal database shows that our proposed approach achieves an EER of 2.1%, outperforming the existing state-of-the-art averaging signal-level fusion approach by 19.2% and the robust mean super-resolution approach by 8.7%.

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Following the success of Coalbed Natural Gas (CBNG) operations in the United States, companies in Australia and New Zealand have been actively exploring and developing this technology for the last two decades. In particular, the Bowen and Surat basins in Queensland, Australia, have undergone extensive CBNG development. Unfortunately, awareness of potential environmental problems associated with CBNG abstraction has not been widespread and legislation has at times struggled to keep up with rapid development. In Australia, the combined CBNG resource for both the Bowen and Surat basins has been estimated at approximately 10,500 PJ with gas content as high as 10 m3/tonne of coal. There are no official estimates for the magnitude of the CBNG resource in New Zealand but initial estimates suggest this could be up to 1,300 PJ with gas content ranging from 1 to 5 m3/tonne of coal. In Queensland, depressurization of the Walloon Coal Measures to recover CBNG has the potential to induce drawdown in adjacent deep aquifer systems through intraformational groundwater flow. In addition, CBNG operators have been disposing their co-produced water by using large unlined ponds, which is not the best practice for managing co-produced water. CBNG waters in Queensland have the typical geochemical signature associated with CBNG waters (Van Voast, 2003) and thus have the potential to impair soils and plant growth where land disposal is considered. Water quality from exploration wells in New Zealand exhibit the same characteristics although full scale production has not yet begun. In general, the environmental impacts that could arise from CBNG water extraction depend on the aquifer system, the quantity and quality of produced water, and on the method of treatment and disposal being used. Understanding these impacts is necessary to adequately manage CBNG waters so that environmental effects are minimized; if properly managed, CBNG waters can be used for beneficial applications and can become a valuable resource to stakeholders.

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Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.

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The concept of moving block signallings (MBS) has been adopted in a few mass transit railway systems. When a dense queue of trains begins to move from a complete stop, the trains can re-start in very close succession under MBS. The feeding substations nearby are likely to be overloaded and the service will inevitably be disturbed unless substations of higher power rating are used. By introducing starting time delays among the trains or limiting the trains’ acceleration rate to a certain extent, the peak energy demand can be contained. However, delay is introduced and quality of service is degraded. An expert system approach is presented to provide a supervisory tool for the operators. As the knowledge base is vital for the quality of decisions to be made, the study focuses on its formulation with a balance between delay and peak power demand.

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This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

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Condition monitoring on rails and train wheels is vitally important to the railway asset management and the rail-wheel interactions provide the crucial information of the health state of both rails and wheels. Continuous and remote monitoring is always a preference for operators. With a new generation of strain sensing devices in Fibre Bragg Grating (FBG) sensors, this study explores the possibility of continuous monitoring of the health state of the rails; and investigates the required signal processing techniques and their limitations.

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The track allocation problem (TAP) at a multi-track, multi-platform mainline railway station is defined by the station track layout and service timetable, which implies combinations of spatial and temporal conflicts. Feasible solutions are available from either traditional planning or advanced intelligent searching methods and their evaluations with respect to operational requirements are essential for the operators. To facilitate thorough analysis, a timed Coloured Petri Nets (CPN) model is presented here to encapsulate the inter-relationships of the spatial and temporal constraints in the TAP.

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Routing trains within passenger stations in major cities is a common scheduling problem for railway operation. Various studies have been undertaken to derive and formulate solutions to this route allocation problem (RAP) which is particularly evident in mainland China nowadays because of the growing traffic demand and limited station capacity. A reasonable solution must be selected from a set of available RAP solutions attained in the planning stage to facilitate station operation. The selection is however based on the experience of the operators only and objective evaluation of the solutions is rarely addressed. In order to maximise the utilisation of station capacity while maintaining service quality and allowing for service disturbance, quantitative evaluation of RAP solutions is highly desirable. In this study, quantitative evaluation of RAP solutions is proposed and it is enabled by a set of indices covering infrastructure utilisation, buffer times and delay propagation. The proposed evaluation is carried out on a number of RAP solutions at a real-life busy railway station in mainland China and the results highlight the effectiveness of the indices in pinpointing the strengths and weaknesses of the solutions. This study provides the necessary platform to improve the RAP solution in planning and to allow train re-routing upon service disturbances.

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A schedule coordination problem involving two train services provided by different operators is modeled as an optimization of revenue intake. The coordination is achieved through the adjustment of commencement times of the train services by negotiation. The problem is subject to constraints regarding to passenger demands and idle costs of rolling-stocks from both operators. This paper models the operators as software agents having the flexibility to incorporate one of the two (and potentially more) proposed negotiation strategies. Empirical results show that agents employing different combination of strategies have significant impact on the quality of solution and negotiation time.

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This paper presents the simulation model development of passenger flow in a metro station. The model allows studies of passenger flow in stations with different layouts and facilities, thus providing valuable information, such as passenger flow and density of passenger at critical locations and passenger-handling facilities within a station, to the operators. The adoption of the concept of Petri nets in the simulation model is discussed. Examples are provided to demonstrate its application to passenger flow analysis, train scheduling and the testing of alternative station layouts.

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Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

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From the business viewpoint, the railway timetable is a list of the products presented by the railway transportation operators to the customers, specifying the schedules of all the train services on a railway line or network. In order to evaluate the quality of the train service schedules, a number of indices are proposed in this paper. These indices primarily take the passengers’ needs, such as waiting time, transfer time and transport capacity into consideration. Delay rate is usually used in post-evaluation. In this study, we propose to give an evaluation on the probability that the scheduled train services are likely to be delayed and the recovery ability of the timetable after delay has occurred. The evaluation identifies the possible problems in the services, such as excessive waiting time, non-seamless transfer, and high possibility of delay. This paper also discusses the improvement of these problems through certain adjustments on the timetable. The indices for evaluation and the adjustment method on timetable are then applied to a case study on the Hu-Ning-Hang railway in China, followed by the discussions of the merits of the proposed indices for timetable evaluation and possible improvement.

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The demand for high quality rail services in the twenty-first century has put an ever increasing demand on all rail operators. In order to meet the expectation of their patrons, the maintenance regime of railway systems has to be tightened up, the track conditions have to be well looked after, the rolling stock must be designed to withstand heavy duty. In short, in an ideal world where resources are unlimited, one needs to implement a very rigorous inspection regime in order to take care of the modem needs of a railway system [1]. If cost were not an issue, the maintenance engineers could inspect the train body by the most up-to-date techniques such as ultra-sound examination, x-ray inspection, magnetic particle inspection, etc. on a regular basis. However it is inconceivable to have such a perfect maintenance regime in any commercial railway. Likewise, it is impossible to have a perfect rolling stock which can weather all the heavy duties experienced in a modem railway. Hence it is essential that some condition monitoring schemes are devised to pick up potential defects which could manifest into safety hazards. This paper introduces an innovative condition monitoring system for track profile and, together with an instrumented car to carry out surveillance of the track, will provide a comprehensive railway condition monitoring system which is free from the usual difficulty of electromagnetic compatibility issues in a typical railway environment

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The travel and hospitality industry is one which relies especially crucially on word of mouth, both at the level of overall destinations (Australia, Queensland, Brisbane) and at the level of travellers’ individual choices of hotels, restaurants, sights during their trips. The provision of such word-of-mouth information has been revolutionised over the past decade by the rise of community-based Websites which allow their users to share information about their past and future trips and advise one another on what to do or what to avoid during their travels. Indeed, the impact of such user-generated reviews, ratings, and recommendations sites has been such that established commercial travel advisory publishers such as Lonely Planet have experienced a pronounced downturn in sales ¬– unless they have managed to develop their own ways of incorporating user feedback and contributions into their publications. This report examines the overall significance of ratings and recommendation sites to the travel industry, and explores the community, structural, and business models of a selection of relevant ratings and recommendations sites. We identify a range of approaches which are appropriate to the respective target markets and business aims of these organisations, and conclude that there remain significant opportunities for further operators especially if they aim to cater for communities which are not yet appropriately served by specific existing sites. Additionally, we also point to the increasing importance of connecting stand-alone ratings and recommendations sites with general social media spaces like Facebook, Twitter, and LinkedIn, and of providing mobile interfaces which enable users to provide updates and ratings directly from the locations they happen to be visiting. In this report, we profile the following sites: * TripAdvisor, the international market leader for travel ratings and recommendations sites, with a membership of some 11 million users; * IgoUgo, the other leading site in this field, which aims to distinguish itself from the market leader by emphasising the quality of its content; * Zagat, a long-established publisher of restaurant guides which has translated its crowdsourcing model from the offline to the online world; * Lonely Planet’s Thorn Tree site, which attempts to respond to the rise of these travel communities by similarly harnessing user-generated content; * Stayz, which attempts to enhance its accommodation search and booking services by incorporating ratings and reviews functionality; and * BigVillage, an Australian-based site attempting to cater for a particularly discerning niche of travellers; * Dopplr, which connects travel and social networking in a bid to pursue the lucrative market of frequent and business travellers; * Foursquare, which builds on its mobile application to generate a steady stream of ‘check-ins’ and recommendations for hospitality and other services around the world; * Suite 101, which uses a revenue-sharing model to encourage freelance writers to contribute travel writing (amongst other genres of writing); * Yelp, the global leader in general user-generated product review and recommendation services. In combination, these profiles provide an overview of current developments in the travel ratings and recommendations space (and beyond), and offer an outlook for further possibilities. While no doubt affected by the global financial downturn and the reduction in travel that it has caused, travel ratings and recommendations remain important – perhaps even more so if a reduction in disposable income has resulted in consumers becoming more critical and discerning. The aggregated word of mouth from many tens of thousands of travellers which these sites provide certainly has a substantial influence on their users. Using these sites to research travel options has now become an activity which has spread well beyond the digirati. The same is true also for many other consumer industries, especially where there is a significant variety of different products available – and so, this report may also be read as a case study whose findings are able to be translated, mutatis mutandis, to purchasing decisions from household goods through consumer electronics to automobiles.

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This paper sets out to examine from published literature and crash data analyses whether alcohol in bicycle crashes is an issue about which we should be concerned. It discusses factors that have the potential to increase the number of bicycle crashes in which alcohol is involved (such growth in the size and diversity of the cyclist population, and balance and coordination demands) and factors which may reduce the importance of alcohol in bicycle crashes (such as time of data factors and child riders). It also examines data availability issues that contribute to difficulties in determining the true magnitude of the issue. Methods: This paper reviews previous research and reports analyses of data from Queensland, Australia, that examine the role of alcohol in Police-reported road crashes. In Queensland it is an offence to ride a bicycle or drive a motor vehicle with a BAC exceeding 0.05% (or lower for novice and professional drivers). Results: In the five years 2003-2007, alcohol was reported as involved in 165 bicycle crashes (4%). The bicycle rider was coded as “under the influence” or “over the prescribed BAC limit” in 15 were single unit crashes (12%). In multi-vehicle bicycle crashes, alcohol involvement was reported for 16 cyclists (0.4%) and 110 operators of other vehicles (3%). Additional analyses including characteristics of the cyclist crashes involving alcohol and the importance of missing data will be discussed in the paper. Conclusion: The increase in participation in cycling and the vulnerability of cyclists to injuries support the need to examine the role of alcohol in bicycle crashes. Current data suggest that alcohol on the part of the vehicle driver is a larger concern than alcohol on the part of the cyclist, but improvements in data collection are needed before more precise conclusions can be drawn.