918 resultados para airport infrastructures
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Introduction Better integration of health services and redefinition of health workforce roles through expanding and extending traditional scope of clinical practice have been explored nationally and internationally. This paper aims to extend our earlier work by examining models of expanded and extended scope of paramedic practice for attributes which facilitate such a practice. Methods An exploratory multi-case study analysis of Australia, New Zealand, Canada and the United Kingdom expanded and extended paramedic practices were analysed. Results Successful models of advanced practice harness the capacity and personality of the paramedic practitioner, and are supported by enabling infrastructures, specifically: professional development/ education; clinical guideline and policy (boundary); access to physical infrastructure and clinical support from senior medical practitioners; and, ability to directly refer to other health services (service integration). The scope of advanced practice is however influenced by individual employers’ capacity, perceived needs and preference/ prioritises. The potential for advanced paramedic practice is equally applicable to urban as well as rural Australia. The Council of Ambulance Authorities’ Professional Competency Standard provides the form and functions for building on advanced paramedic practice. Recognition of such advanced paramedic practice provides a structure for professional growth, process for career progression and will support workforce retention. Conclusion The achievement of advanced knowledge and skills has positioned the paramedic profession to be recognized as a valuable clinician. The Council of Ambulance Authorities’ Professional Competency Standards provides the form and function for supporting advanced paramedic practice.
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Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.
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With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.
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Within half an hour of leaving Halifax Airport I managed to get myself lost. I noticed an exit sign for St Margaret’s Bay and, despite written instructions to the contrary, it sounded like the right way to go. But I was on the Lighthouse Route and on my way back to Halifax...
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As airports continue to become more ‘customer-centric’ their digital customer-facing technologies are increasingly embedded within the passenger journey. This study takes a customer-centric view of airport digital technology by exploring the ways that digital technologies are being applied within airports to improve passenger perspectives of service quality during their journey. The literature review develops a framework encompassing the themes of airport service quality (function, interaction and diversion) and digital strategy. This framework has been applied to six airports exhibiting high service quality. Currently, the findings suggest that the improvement of customer function involves the use of automated and self-service technologies providing passengers greater efficiency and effectiveness during processing points. Additionally, technology to improve experience during wait times may entail either aesthetic qualities, or provide some form of productivity to passengers. Alternatively, customer interaction is influenced by digital technology through constant passenger engagement during their journey. As the research nears completion, the influence of these themes on the framework will become more apparent.
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This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.
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This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.
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Air transport is a critical link to regional, rural and remote communities in Australia. Air services provide important economic and social benefits but very little research has been done on assessing the value of regional aviation. This research provides the first empirical evidence that there is short and long run causality between regional aviation and economic growth. The authors analysed 88 regional airports in Australia over a period of 1985–86 to 2010–11 to determine the catalytic impacts of regional air transport on regional economic growth. The analysis was conducted using annual data related to total airport passenger movements – for the level of airport activity, and real aggregate taxable income – to represent economic growth. A significant bi-directional relationship was established: airports have an impact on regional economic growth and the economy directly impacts regional air transport. The economic significance of regional air transport confirms the importance of the airport as infrastructure for regional councils and the need for them to maintain and develop local airports. Funding should be targeted at airports directly to support regional development.
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This thesis introduces a method of applying Bayesian Networks to combine information from a range of data sources for effective decision support systems. It develops a set of techniques in development, validation, visualisation, and application of Complex Systems models, with a working demonstration in an Australian airport environment. The methods presented here have provided a modelling approach that produces highly flexible, informative and applicable interpretations of a system's behaviour under uncertain conditions. These end-to-end techniques are applied to the development of model based dashboards to support operators and decision makers in the multi-stakeholder airport environment. They provide highly flexible and informative interpretations and confidence in these interpretations of a system's behaviour under uncertain conditions.
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This paper collates recent research on mobile phone use in Indigenous communities in Australia. Its key finding is that mobile phones are heavily used in these communities, albeit in unique and unusual ways that may be difficult to comprehend beneath 'top-down' measurements. Rather than framing these uses as being compromises made in lieu of appropriate infrastructures or literacies, it is argued that HCI4D (Human-Computer Interaction for Development) would be better served by seriously plumbing into the information they reveal about how mobile phones are constructed and placed in these communities, and what these factors might reveal about local understandings of development and well-being. A consideration of these specific patterns of appropriation is necessary to push the field beyond top-down, rationalist approaches to development towards more flexible, creative solutions that build from local knowledge and competencies.
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Group interaction within crowds is a common phenomenon and has great influence on pedestrian behaviour. This paper investigates the impact of passenger group dynamics using an agent-based simulation method for the outbound passenger process at airports. Unlike most passenger-flow models that treat passengers as individual agents, the proposed model additionally incorporates their group dynamics as well. The simulation compares passenger behaviour at airport processes and discretionary services under different group formations. Results from experiments (both qualitative and quantitative) show that incorporating group attributes, in particular, the interactions with fellow travellers and wavers can have significant influence on passengers activity preference as well as the performance and utilisation of services in airport terminals. The model also provides a convenient way to investigate the effectiveness of airport space design and service allocations, which can contribute to positive passenger experiences. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.
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The importance of passenger experience in aviation has become well understood in the last several years. It is now generally accepted that the provision of good passenger experience is not an option, but a necessity, from an aviation profitability perspective. In this paper, we paint a picture of the future passenger experience by consolidating a number of industry and research perspectives. Using the future passenger experience as a starting point, we explore the components needed to enable this future vision. From this bottom-up approach, we identify the need to resolve data formatting and data ownership issues. The resolution of these data integration issues is necessary to enable the seamless future travel experience that is envisioned by the aviation industry. By looking at the passenger experience from this bottom-up, data centric perspective, we identify a potential shift in the way that future passenger terminals will be designed. Whereas currently the design of terminals is largely an architectural practice, in the near future, the design of the terminal building may become more of a virtual technology practice. This of course will pose a new set of challenges to designers of airport terminal environments.
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The effect of passenger satisfaction on airport profitability has been widely acknowledged in the aviation industry. As a result, there has been much attention directed towards developing a deeper understanding of the factors that influence the passenger experience. In this paper, we explore passenger experience from a novel perspective - that of the activities expected to be undertaken by passengers while in the airport terminal building. Using the Taxonomy of Passenger Experience (TOPA) as our framework, we look at the pre-travel interview data of 48 participants. The results of our analysis are used to construct an activity-centred account of the expected passenger experience for international departures. Our exploration of the expected passenger experienced revealed that not all of the TOPA activities have an equal impact on the passengers' expected experience. The processing, consumptive, preparatory and queuing activity groups featured most prominently in passengers' accounts of their upcoming airport experiences. Of these, the preparatory category was found to have the most direct impact on passenger satisfaction. Additionally, our analysis indicated that utilising queue time to prepare passengers for upcoming processing activities could have a positive effect on both satisfaction and processing efficiency. A further outcome of this research was the observation that "shopping" did not form a part of the expected experience of any of the interviewed participants. The outcomes of this study can be used by airports to assist in the management of passengers' expected experience in the terminal building. As passenger expectations and passenger satisfaction are intrinsically linked, understanding which activities have the most impact on satisfaction provides a basis from which alternate design choices can be evaluated when constructing, or fine-tuning, airport terminal designs.
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Process improvement and innovation are risky endeavors, like swimming in unknown waters. In this chapter, I will discuss how process innovation through BPM can benefit from Research-as-a-Service, that is, from the application of research concepts in the processes of BPM projects. A further subject will be how innovations can be converted from confidence-based to evidence-based models due to affordances of digital infrastructures such as large-scale enterprise soft-ware or social media. I will introduce the relevant concepts, provide illustrations for digital capabilities that allow for innovation, and share a number of key takeaway lessons for how organizations can innovate on the basis of digital opportunities and principles of evidence-based BPM: the foundation of all process decisions in facts rather than fiction.