999 resultados para Coalescent Approach


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This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity (TFP) change and Simar and Wilson’s (2007) bootstrapped truncated regression approach which first derives bias-corrected efficiency estimates before being regressed against explanatory variables to help quantify sources of inefficiencies. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Sources of efficiency were attributed to quality of worker and flexible work arrangements while the use of foreign workers lowered efficiency.

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Because of increased competition between healthcare providers, higher customer expectations, stringent checks on insurance payments and new government regulations, it has become vital for healthcare organisations to enhance the quality of the care they provide, to increase efficiency, and to improve the cost effectiveness of their services. Consequently, a number of quality management concepts and tools are employed in the healthcare domain to achieve the most efficient ways of using time, manpower, space and other resources. Emergency departments are designed to provide a high-quality medical service with immediate availability of resources to those in need of emergency care. The challenge of maintaining a smooth flow of patients in emergency departments is a global problem. This study attempts to improve the patient flow in emergency departments by considering Lean techniques and Six Sigma methodology in a comprehensive conceptual framework. The proposed research will develop a systematic approach through integration of Lean techniques with Six Sigma methodology to improve patient flow in emergency departments. The results reported in this paper are based on a standard questionnaire survey of 350 patients in the Emergency Department of Aseer Central Hospital in Saudi Arabia. The results of the study led us to determine the most significant variables affecting patient satisfaction with patient flow, including waiting time during patient treatment in the emergency department; effectiveness of the system when dealing with the patient’s complaints; and the layout of the emergency department. The proposed model will be developed within a performance evaluation metric based on these critical variables, to be evaluated in future work within fuzzy logic for continuous quality improvement.

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Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

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The Beyond Compliance project, which began in July 2011 with funding from the Standards and Trade Development Facility for 2 years, aims to enhance competency and confidence in the South East Asian sub-region by applying a Systems Approach for pest risk management. The Systems Approach involves the use of integrated measures, at least two of which are independent, that cumulatively reduce the risk of introducing exotic pests through trade. Although useful in circumstances where single measures are inappropriate or unavailable, the Systems Approach is inherently more complicated than single-measure approaches, which may inhibit its uptake. The project methodology is to take prototype decision-support tools, such as Control Point-Bayesian Networks (CP-BN), developed in recent plant health initiatives in other regions, including the European PRATIQUE project, and to refine them within this sub-regional context. Case studies of high-priority potential agricultural trade will be conducted by National Plant Protection Organizations of participating South East Asian countries in trials of the tools, before further modifications. Longer term outcomes may include: more robust pest risk management in the region (for exports and imports); greater inclusion of stakeholders in development of pest risk management plans; increased confidence in trade negotiations; and new opportunities for trade.

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Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

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The main focus of ‘Kaleidoscope: Reframing evaluation through a stakeholder approach to sustainable, cultural change in Higher Education’ is to develop a set of principles to guide user-led engagement in widespread organisational change and maximise its impact. The word kaleidoscope represents the unique lens through which each institution will need to view their cultural specificity and local context through an extensive process of collaboration and engagement, followed by communication and dissemination. Kaleidoscope has particular relevance when new approaches to learning and teaching evaluation are introduced by tertiary institutions. Building on the Reframe Project, which involved three years of user-led consultation and was designed to meet stakeholders’ needs, QUT successfully introduced a new evaluation framework in 2013 across the university. Reframe was evidence based, involved scholarly reflection and was founded on a strong theoretical framework. The evolution of the evaluation framework included analysis of scholarly literature and environmental scans across the higher education sector (Alderman, et al., 2012), researched development of conceptual theory (Alderman, et al., in press 2013), incorporated the stakeholder voice and framed within project management principles (Alderman & Melanie, 2012). Kaleidoscope’s objectives are for QUT to develop its research-based stakeholder approach to distil the successful experience exhibited in the Reframe Project into a transferable set of guidelines for use by other tertiary institutions across the sectors. These guidelines will assist others to design, develop, and deploy, their own culturally specific widespread organisational change informed by stakeholder engagement and organisational buy-in. It is intended that these guidelines will promote, support and enable other tertiary institutions to embark on their own projects and maximise the impact. In correlation with a our conference paper, this round table presents the Draft Guidelines and Framework ready for external peer review by evaluation practitioners, as part of Kaleidoscope’s dissemination (Hinton & Gannaway, 2011) applying illuminative evaluation theory (Parlett & Hamilton, 1976), through conference workshops and linked round table discussions (Shapiro, et al., 1983; Jacobs, 2000).

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Evaluation practices in the higher education sector have been criticised for having unclear purpose and principles; ignoring the complexity and changing nature of learning and teaching and the environments in which they occur; relying almost exclusively on student ratings of teachers working in classroom settings; lacking reliability and validity; using data for inappropriate purposes; and focusing on accountability and marketing rather than the improvement of learning and teaching. In response to similar criticism from stakeholders, in 2011 Queensland University of Technology began a project, entitled REFRAME, to review its approach to evaluation, particularly the student survey system it had been using for the past five years. This presentation will outline the scholarly, evidence based methodology used to undertake institution-wide change, meet the needs of stakeholders suitable to the cultural needs of the institution. It is believed that this approach is broadly applicable to other institutions contemplating change with regard to evaluation of learning and teaching.

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This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

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The world’s increasing complexity, competitiveness, interconnectivity, and dependence on technology generate new challenges for nations and individuals that cannot be met by continuing education as usual. With the proliferation of complex systems have come new technologies for communication, collaboration, and conceptualisation. These technologies have led to signifi cant changes in the forms of mathematical and scientifi c thinking required beyond the classroom. Modelling, in its various forms, can develop and broaden students’ mathematical and scientific thinking beyond the standard curriculum. This chapter first considers future competencies in the mathematical sciences within an increasingly complex world. Consideration is then given to interdisciplinary problem solving and models and modelling, as one means of addressing these competencies. Illustrative case studies involving complex, interdisciplinary modelling activities in Years 1 and 7 are presented.

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This chapter introduces the reader to the relational approach to information literacy, its evolution and use in contemporary research and emerging directions. It presents the relational approach, first introduced by Australian information literacy researchers, as an integration of experiential, contextual and transformational perspectives. The chapter opens with a reflection on the wider information literacy domain. It then addresses the development of the approach, its fundamental elements and characteristics, and explores the adoption of the approach in key contexts including education, workplace and community settings. The chapter explores significant studies that have contributed to its evolution and reflects on the impact of the development of the relational framework and related research. The chapter concludes with a focus on directions emerging from the relational understanding ofinformation literacy and potential implications.

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Surveys have identified that many older motorcyclists are returning riders but it is difficult to draw conclusions about their crash risk because of discrepancies in definitions and the inability to identify returning riders in official crash databases. Analyses of NSW crash data were undertaken in which returning riders were defined as aged 25 and over, holding a full licence 10 years prior to the crash, and not the registered operator of one or more motorcycles during the 5-10 years prior to the crash. Based on this definition, there were 472 riders in casualty crashes in 2005-09 who were returning riders (5.5% of riders aged 25 and over in casualty crashes) and the characteristics of their crashes were similar to those involving continuing riders. In contrast, crashes of new riders were more likely to have characteristics suggestive of relatively more riding in urban areas, probably for transport rather than recreation. More work is recommended to assess the validity of the definition to allow a better understanding of the effects of long periods away from riding on riding skills and crash risk.

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It is well-known that the use of off-site manufacture (OSM) techniques can assist in timely completion of a construction project though the utilisation of such techniques may have other disadvantages. Currently, OSM uptake within the Australian construction industry is limited. To successfully incorporate OSM practices within a construction project, it is crucial to understand the impact of OSM adoption on the processes used during a construction project. This paper presents how a systematic process-oriented approach may be able to support OSM utilisation within a construction project. Process modelling, analysis and automation techniques which are well-known within the Business Process Management (BPM) discipline have been applied to develop a collection of construction process models that represent the end-to-end generic construction value chain. The construction value chain enables researchers to identify key activities, resources, data, and stakeholders involved in construction processes in each defined construction phase. The collection of construction process models is then used as a basis for identification of potential OSM intervention points in collaboration with domain experts from the Australian construction industry. This ensures that the resulting changes reflect the needs of various stakeholders within the construction industry and have relevance in practice. Based on the input from the domain experts, these process models are further refined and operational requirements are taken into account to develop a prototype process automation (workflow) system that can support and coordinate OSM-related process activities. The resulting workflow system also has the potential to integrate with other IT solutions used within the construction industry (e.g., BIM, Acconex). As such, the paper illustrates the role that process-oriented thinking can play in assisting OSM adoption within the industry.

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Determining what consequences are likely to serve as effective punishment for any given behaviour is a complex task. This chapter focuses specifically on illegal road user behaviours and the mechanisms used to punish and deter them. Traffic law enforcement has traditionally used the threat and/or receipt of legal sanctions and penalties to deter illegal and risky behaviours. This process represents the use of positive punishment, one of the key behaviour modification mechanisms. Behaviour modification principles describe four types of reinforcers: positive and negative punishments and positive and negative reinforcements. The terms ‘positive’ and ‘negative’ are not used in an evaluative sense here. Rather, they represent the presence (positive) or absence (negative) of stimuli to promote behaviour change. Punishments aim to inhibit behaviour and reinforcements aim to encourage it. This chapter describes a variety of punishments and reinforcements that have been and could be used to modify illegal road user behaviours. In doing so, it draws on several theoretical perspectives that have defined behavioural reinforcement and punishment in different ways. Historically, the main theoretical approach used to deter risky road use has been classical deterrence theory which has focussed on the perceived certainty, severity and swiftness of penalties. Stafford and Warr (1993) extended the traditional deterrence principles to include the positive reinforcement concept of punishment avoidance. Evidence of the association between punishment avoidance experiences and behaviour has been established for a number of risky road user behaviours including drink driving, unlicensed driving, and speeding. We chose a novel way of assessing punishment avoidance by specifying two sub-constructs (detection evasion and punishment evasion). Another theorist, Akers, described the idea of competing reinforcers, termed differential reinforcement, within social learning theory (1977). Differential reinforcement describes a balance of reinforcements and punishments as influential on behaviour. This chapter describes comprehensive way of conceptualising a broad range of reinforcement and punishment concepts, consistent with Akers’ differential reinforcement concept, within a behaviour modification framework that incorporates deterrence principles. The efficacy of three theoretical perspectives to explain self-reported speeding among a sample of 833 Australian car drivers was examined. Results demonstrated that a broad range of variables predicted speeding including personal experiences of evading detection and punishment for speeding, intrinsic sensations, practical benefits expected from speeding, and an absence of punishing effects from being caught. Not surprisingly, being younger was also significantly related to more frequent speeding, although in a regression analysis, gender did not retain a significant influence once all punishment and reinforcement variables were entered. The implications for speed management, as well as road user behaviour modification more generally, are discussed in light of these findings. Overall, the findings reported in this chapter suggest that a more comprehensive approach is required to manage the behaviour of road users which does not rely solely on traditional legal penalties and sanctions.

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A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

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This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.