987 resultados para Statistical efficiency
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Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.
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The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.
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ZnO is a promising photoanode material for dye-sensitized solar cells (DSCs) due to its high bulk electron mobility and because different geometrical structures can easily be tailored. Although various strategies have been taken to improve ZnO-based DSC efficiencies, their performances are still far lower than TiO2 counterparts, mainly because low conductivity Zn2+–dye complexes form on the ZnO surfaces. Here, cone-shaped ZnO nanocrystals with exposed reactive O-terminated {101̅1} facets were synthesized and applied in DSC devices. The devices were compared with DSCs made from more commonly used rod-shaped ZnO nanocrystals where {101̅0} facets are predominantly exposed. When cone-shaped ZnO nanocrystals were used, DSCs sensitized with C218, N719, and D205 dyes universally displayed better power conversion efficiency, with the highest photoconversion efficiency of 4.36% observed with the C218 dye. First-principles calculations indicated that the enhanced DSCs performance with ZnO nanocone photoanodes could be attributed to the strength of binding between the dye molecules and reactive O-terminated {101̅1} ZnO facets and that more effective use of dye molecules occurred due to a significantly less dye aggregation on these ZnO surfaces compared to other ZnO facets.
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The Department of Culture and the Arts undertook the first mapping of Perth’s creative industries in 2007 in partnership with the City of Perth and the Departments of Industry and Resources and the Premier and Cabinet. The 2013 Creative Industries Statistical Analysis for Western Australia report has updated the mapping with the 2011 Census employment data to provide invaluable information for the State’s creative industries, their peak associations and potential investors. The report maps sector employment numbers and growth between the 2006 and 2011 Census in the areas of music, visual and performing arts, film, TV and radio, advertising and marketing, software and digital content, publishing, and architecture and design, which includes designer fashion.
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Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.
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For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.
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Dose-finding trials are a form of clinical data collection process in which the primary objective is to estimate an optimum dose of an investigational new drug when given to a patient. This thesis develops and explores three novel dose-finding design methodologies. All design methodologies presented in this thesis are pragmatic. They use statistical models, incorporate clinicians' prior knowledge efficiently, and prematurely stop a trial for safety or futility reasons. Designing actual dose-finding trials using these methodologies will minimize practical difficulties, improve efficiency of dose estimation, be flexible to stop early and reduce possible patient discomfort or harm.
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This chapter addresses data modelling as a means of promoting statistical literacy in the early grades. Consideration is first given to the importance of increasing young children’s exposure to statistical reasoning experiences and how data modelling can be a rich means of doing so. Selected components of data modelling are then reviewed, followed by a report on some findings from the third-year of a three-year longitudinal study across grades one through three.
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At NDSS 2012, Yan et al. analyzed the security of several challenge-response type user authentication protocols against passive observers, and proposed a generic counting based statistical attack to recover the secret of some counting based protocols given a number of observed authentication sessions. Roughly speaking, the attack is based on the fact that secret (pass) objects appear in challenges with a different probability from non-secret (decoy) objects when the responses are taken into account. Although they mentioned that a protocol susceptible to this attack should minimize this difference, they did not give details as to how this can be achieved barring a few suggestions. In this paper, we attempt to fill this gap by generalizing the attack with a much more comprehensive theoretical analysis. Our treatment is more quantitative which enables us to describe a method to theoretically estimate a lower bound on the number of sessions a protocol can be safely used against the attack. Our results include 1) two proposed fixes to make counting protocols practically safe against the attack at the cost of usability, 2) the observation that the attack can be used on non-counting based protocols too as long as challenge generation is contrived, 3) and two main design principles for user authentication protocols which can be considered as extensions of the principles from Yan et al. This detailed theoretical treatment can be used as a guideline during the design of counting based protocols to determine their susceptibility to this attack. The Foxtail protocol, one of the protocols analyzed by Yan et al., is used as a representative to illustrate our theoretical and experimental results.
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Standard Monte Carlo (sMC) simulation models have been widely used in AEC industry research to address system uncertainties. Although the benefits of probabilistic simulation analyses over deterministic methods are well documented, the sMC simulation technique is quite sensitive to the probability distributions of the input variables. This phenomenon becomes highly pronounced when the region of interest within the joint probability distribution (a function of the input variables) is small. In such cases, the standard Monte Carlo approach is often impractical from a computational standpoint. In this paper, a comparative analysis of standard Monte Carlo simulation to Markov Chain Monte Carlo with subset simulation (MCMC/ss) is presented. The MCMC/ss technique constitutes a more complex simulation method (relative to sMC), wherein a structured sampling algorithm is employed in place of completely randomized sampling. Consequently, gains in computational efficiency can be made. The two simulation methods are compared via theoretical case studies.
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Energy efficiency is a complex topic to integrate into higher education curricula, with limited success internationally or in Australia. This paper discusses one of the successful initiatives within the Energy Efficiency Training Program, which was jointly managed and implemented by the New South Wales Office of Environment and Heritage and Department of Education and Communities. The state government initiative aimed to increase the knowledge and skills of the New South Wales workforce, help business to identify and implement energy efficiency projects, and provide professional development for the training providers. Key sectors targeted included property, construction, manufacturing and services. The Program was externally evaluated over the three years 2011 to 2013 and a range of insights were gained through these facilitated reflective opportunities, confirming and building upon literature on the topic to date. This paper presents lessons learned from the engineering part of the program (‘the project’), spanning government agencies, academic institutions, and academia. The paper begins with a contextual summary, followed by a synthesis of key learnings and implications for future training initiatives. It is intended that sharing these lessons will contribute to literature in the field, and assist other organisations in Australia and overseas planning similar initiatives.
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Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,i something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This paper outlines an investigation into these factors and focuses on better understanding the performance of and interaction between: design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. In doing so the paper presents a framework for improving energy efficiency in existing commercial buildings by considering a range of interconnected and synergistic elements.
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The Australian Government’s Skills for the Carbon Challenge (SCC) initiative aims to accelerate industry and the education sectors response to climate change. As part of the SCC initiative, the Department of Industry, Innovation, Climate Change, Science, Research and Tertiary Education (DIICCSRTE) provided funding to investigate the state of energy efficiency education in engineering-related Australian Technical and Further Education (TAFE) Programs. The following document reports on the outcomes of a multi-stage consultation project that engaged with participants from over 80% of TAFE institutions across Australia with the aim of supporting and enhancing future critical skills development in this area. Specifically, this report presents the findings of a national survey, based on a series of TAFE educator focus groups, conducted in May 2013 aimed at understanding the experiences and insights of Australian TAFE educators teaching engineering-related courses. Responses were received from 224 TAFE Educators across 50 of the 61 TAFE institutions in Australia (82% response rate).
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Today, many sectors across society are recognising the need to swiftly reduce their growing energy demand, as well as meeting remaining demand with low emissions options. A key ingredient to addressing such issues is equipping professionals – in particular engineers – with emerging energy efficiency knowledge and skills. This paper responds to an identified engineering education gap in Australia, by investigating options to increase energy efficiency content for both undergraduate and postgraduate engineers. The authors summarise the findings of the multi-stage methodology funded by the National Framework for Energy Efficiency (2008-2009), highlighting identified key barriers and benefits to such curriculum renewal. The findings are intended for use by engineering departments, accreditation agencies, professional bodies and government, to identify opportunities for moving forward based on rigorous research, and then to strategically plan the transition. This process, focused on energy efficiency, may also provide valuable parallels for a range of sustainable engineering related topics.
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BACKGROUND There is a growing volume of open source ‘education material’ on energy efficiency now available however the Australian government has identified a need to increase the use of such materials in undergraduate engineering education. Furthermore, there is a reported need to rapidly equip engineering graduates with the capabilities in conducting energy efficiency assessments, to improve energy performance across major sectors of the economy. In January 2013, building on several years of preparatory action-research initiatives, the former Department of Industry, Innovation, Climate Change, Science, Research and Tertiary Education (DIICCSRTE) offered $600,000 to develop resources for energy efficiency related graduate attributes, targeting Engineers Australia college disciplines, accreditation requirements and opportunities to address such requirements. PURPOSE This paper discusses a $430,000 successful bid by a university consortium led by QUT and including RMIT, UA, UOW, and VU, to design and pilot several innovative, targeted open-source resources for curriculum renewal related to energy efficiency assessments, in Australian engineering programs (2013-2014), including ‘flat-pack’, ‘media-bites’, ‘virtual reality’ and ‘deep dive’ case study initiatives. DESIGN/ METHOD The paper draws on literature review and lessons learned by the consortium partners in resource development over the last several years to discuss methods for selecting key graduate attributes and providing targeted resources, supporting materials, and innovative delivery options to assist universities deliver knowledge and skills to develop such attributes. This includes strategic industry and key stakeholders engagement. The paper also discusses processes for piloting, validating, peer reviewing, and refining these resources using a rigorous and repeatable approach to engaging with academic and industry colleagues. RESULTS The paper provides an example of innovation in resource development through an engagement strategy that takes advantage of existing networks, initiatives, and funding arrangements, while informing program accreditation requirements, to produce a cost-effective plan for rapid integration of energy efficiency within education. By the conference, stakeholder workshops will be complete. Resources will be in the process of being drafted, building on findings from the stakeholder engagement workshops. Reporting on this project “in progress” provides a significant opportunity to share lessons learned and take on board feedback and input. CONCLUSIONS This paper provides a useful reference document for others considering significant resource development in a consortium approach, summarising benefits and challenges. The paper also provides a basis for documenting the second half of the project, which comprises piloting resources and producing a ‘good practice guide’ for energy efficiency related curriculum renewal.