824 resultados para Sustainability performance framework


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Rail joints are provided with a gap to account for thermal movement and to maintain electrical insulation for the control of signals and/or broken rail detection circuits. The gap in the rail joint is regarded as a source of significant problems for the rail industry since it leads to a very short rail service life compared with other track components due to the various, and difficult to predict, failure modes – thus increasing the risk for train operations. Many attempts to improve the life of rail joints have led to a large number of patents around the world; notable attempts include strengthening through larger-sized joint bars, an increased number of bolts and the use of high yield materials. Unfortunately, no design to date has shown the ability to prolong the life of the rail joints to values close to those for continuously welded rail (CWR). This paper reports the results of a fundamental study that has revealed that the wheel contact at the free edge of the railhead is a major problem since it generates a singularity in the contact pressure and railhead stresses. A design was therefore developed using an optimisation framework that prevents wheel contact at the railhead edge. Finite element modelling of the design has shown that the contact pressure and railhead stress singularities are eliminated, thus increasing the potential to work as effectively as a CWR that does not have a geometric gap. An experimental validation of the finite element results is presented through an innovative non-contact measurement of strains. Some practical issues related to grinding rails to the optimal design are also discussed.

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In fisheries managed using individual transferable quotas (ITQs) it is generally assumed that quota markets are well-functioning, allowing quota to flow on either a temporary or permanent basis to those able to make best use of it. However, despite an increasing number of fisheries being managed under ITQs, empirical assessments of the quota markets that have actually evolved in these fisheries remain scarce. The Queensland Coral Reef Fin-Fish Fishery (CRFFF) on the Great Barrier Reef has been managed under a system of ITQs since 2004. Data on individual quota holdings and trades for the period 2004-2012 were used to assess the CRFFF quota market and its evolution through time. Network analysis was applied to assess market structure and the nature of lease-trading relationships. An assessment of market participants’ abilities to balance their quota accounts, i.e., gap analysis, provided insights into market functionality and how this may have changed in the period observed. Trends in ownership and trade were determined, and market participants were identified as belonging to one out of a set of seven generalized types. The emergence of groups such as investors and lease-dependent fishers is clear. In 2011-2012, 41% of coral trout quota was owned by participants that did not fish it, and 64% of total coral trout landings were made by fishers that owned only 10% of the quota. Quota brokers emerged whose influence on the market varied with the bioeconomic conditions of the fishery. Throughout the study period some quota was found to remain inactive, implying potential market inefficiencies. Contribution to this inactivity appeared asymmetrical, with most residing in the hands of smaller quota holders. The importance of transaction costs in the operation of the quota market and the inequalities that may result are discussed in light of these findings

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Graphene and carbon nanotubes (CNTs) are attractive electrode materials for supercapacitors. However, challenges such as the substrate-limited growth of CNTs, nanotube bundling in liquid electrolytes, under-utilized basal planes, and stacking of graphene sheets have so far impeded their widespread application. Here we present a hybrid structure formed by the direct growth of CNTs onto vertical graphene nanosheets (VGNS). VGNS are fabricated by a green plasma-assisted method to break down and reconstruct a natural precursor into an ordered graphitic structure. The synergistic combination of CNTs and VGNS overcomes the challenges intrinsic to both materials. The resulting VGNS/CNTs hybrids show a high specific capacitance with good cycling stability. The charge storage is based mainly on the non-Faradaic mechanism. In addition, a series of optimization experiments were conducted to reveal the critical factors that are required to achieve the demonstrated high supercapacitor performance.

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When designed effectively dashboards are expected to reduce information overload and improve performance management. Hence, interest in dashboards has increased recently,which is also evident from the proliferation of dashboard solution providers in the market. Despite dashboards popularity, little is known about the extent of their effectiveness in organizations. Dashboards draw from multiple disciplines but ultimately use visualization to communicate important information to stakeholders. Thus,a better understanding of visualization can improve the design and use of dashboards. This paper reviews the foundations and roles of dashboards in performance management and proposes a framework for future research, which can enhance dashboard design and perceived usefulness depending on the fit between the features of the dashboard and the characteristics of the users.

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The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.

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Introduction: Emergency department nurse practitioner services are one of the most frequently implemented service delivery models in Australian hospitals. This research examined factors influencing sustainability of this innovative service delivery model and offers some recommendations for future service integration. Background Many health service innovations have been implemented in an attempt to meet the growing demand for efficient, cost effective health care however, sustainability of many of these innovations has not been evaluated and is poorly understood. Aim The aim of the research was to identify factors that influence sustainability of emergency department nurse practitioner services and to operationalise a theoretical framework for evaluating innovation sustainability. Methodology The research used case study methodology. The case was emergency nurse practitioner services, and units of analysis were emergency department staff, emergency nurse practitioners and documents relating to nurse practitioner services. The data collection methods included, survey, one-on-one interviews, document analysis and telephone survey. Results This research shows that emergency nurse practitioner services partially comply with the factors of sustainability as described in the Sustainability of Innovation theoretical framework: Political, Organisational, Workforce, Financial and Innovation specific factors. Where services do not entirely meet the factors the existing benefits of the service may outweigh the barriers and other means of working around shortfalls are also implemented by staff to ensure patient safety. Conclusion The rapidly expanding emergency nurse practitioner service has been examined using case study methodology to find that certain factors may be threatening the sustainability of this health service innovation. Potentially an innovation may be sustained when only some factors are met in the short term, however, long term sustainability may be challenged if factors are not addressed and supported.

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

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This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.

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This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

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Mapping and evaluating a student's progress on placement is a core element of social work education but there has been scant attention to indicate how to effectively create and assess student learning and performance. This paper outlines a project undertaken by the Combined Schools of Social Work to develop a common learning and assessment tool that is being used by all social work schools in Victoria. The paper describes how the Common Assessment Tool (CAT) was developed, drawing on the Australian Association of Social Work Practice Standards, leading to seven key learning areas that form the basis of the assessment of a student's readiness for practice. An evaluation of the usefulness of the CAT was completed by field educators, liaison staff, and students, which confirmed that the CAT was a useful framework for evaluating students' learning goals. The feedback also identified a number of problematic features that were addressed in a revised CAT and rating scale.

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Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

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The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

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The relationship between governance arrangements and sustainability planning outcomes in complex governance systems remains poorly understood, despite significant discussions of governance in the environmental management literature emerging in the last decade. In order to analyse and examine the relationship between the health of sustainability planning governance and decision-making outcomes, this paper applies the Governance Systems Analysis framework (GSA) in the Cairns region. This paper analyses the sustainability planning governance arrangements in the Cairns region by exploring the capacity, connectivity and knowledge use of institutions in the region to deliver desired sustainability planning outcomes. The paper finds that the planning for sustainability in the Cairns region is on a knife’s edge, and could fail or succeed to deliver its intended decision-making outcomes. The paper concludes with recommendations for governance reform for sustainability in the Cairns region.

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Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available.

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Corporations' commitment to their social responsibilities has long been a global concern with reference to sustainability, transparency and fair practice, which is of great concern to stakeholders. Corporations are expected to be responsible to the society they operate within and do business in a socially responsible manner.