837 resultados para Best-Worst Scaling
Resumo:
Team games conceptualized as dynamical systems engender a view of emergent decision-making behaviour under constraints, although specific effects of instructional and body-scaling constraints have yet to be verified empirically. For this purpose, we studied the effects of task and individual constraints on decision-making processes in basketball. Eleven experienced female players performed 350 trials in 1 vs. 1 sub-phases of basketball in which an attacker tried to perturb the stable state of a dyad formed with a defender (i.e. break the symmetry). In Experiment 1, specific instructions (neutral, risk taking or conservative) were manipulated to observe effects on emergent behaviour of the dyadic system. When attacking players were given conservative instructions, time to cross court mid-line and variability of the attacker's trajectory were significantly greater. In Experiment 2, body-scaling of participants was manipulated by creating dyads with different height relations. When attackers were considerably taller than defenders, there were fewer occurrences of symmetry-breaking. When attackers were considerably shorter than defenders, time to cross court mid-line was significantly shorter than when dyads were composed of athletes of similar height or when attackers were considerably taller than defenders. The data exemplify how interacting task and individual constraints can influence emergent decision-making processes in team ball games.
Developing a best practice framework for implementing public private partnerships (PPP) in Hong Kong
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Public Private Partnership (PPP) is a well established methodology for procuring public works projects. By incorporating the private sector’s expertise, efficiency, innovation, business sense, risk sharing, financing etc. into public works projects, the quality of public services and facilities can be uplifted. Like many jurisdictions, Hong Kong is also keen to take aboard this methodology which is so familiar but yet so distant. Although they have been one of the first jurisdictions to utilise the private sector in public works projects, their comfortable financial reserves has meant that there has been no urge to push the movement until recently. PPP has become increasingly popular amongst governments. The Hong Kong Special Administrative Region (HKSAR) government is no exception. Some of the more active works departments have commissioned studies to investigate the best ways to deliver these projects, others have even trialed the method themselves. The efficiency Unit of the HKSAR government has also become an active arm in conducting research in this area. Although so, the information that is currently available is still very broad. Building from their works there is a need to develop a best practice framework for implementing PPP projects in Hong Kong by incorporating international experiences. To develop a best practice framework will require thorough investigation into the benefits, difficulties and critical success factor of PPP. PPP should also be compared with other procurement methods. In order to do so it is important to clearly understand the local situation by an analysis of projects conducted to date. Lessons learnt can further be derived from other countries and incorporated to those derived locally. Finally the best conditions in terms of project nature, complexity, types, and scales for adopting PPP should be derived. The aim and objectives of this study were achieved via a comprehensive literature review, in-depth case analyses, interview survey with experts from both Hong Kong and overseas, and finally a large scale data collection was conducted via a questionnaire survey with PPP practitioners. These findings were further triangulated before they were used as the basis to form the best practice framework presented in this thesis. The framework was then further validated by PPP experts to ensure it is comprehensive, objective, reliable and practical. This study has presented a methodology that can be adopted for future studies. It has also updated our knowledge on the development trends of PPP as well as opened up the experiences of other jurisdictions. The findings have shown that the local industry is familiar with “what” should be done in PPP projects but they are unsure of “how” these goals can be achieved. This framework has allowed this further knowledge to be delivered to PPP practitioners. As a result, the development of this framework can help to resolve the current economic crisis by encouraging more developments and business opportunities for the private sector. In addition, the correct projects can be delivered by PPP, the advantages of PPP can be maximised, and the general public can benefit from the private sector’s participation.
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Energy efficient lubricants are becoming increasingly popular. This is due to a global increase in environmental awareness combined with the potential of reducing operating costs. A new test method of evaluating the energy efficiency of gear oils has been described in this report. The method involves measuring the power required by an FZG test rig to run while using a particular test lubricant. For each oil that was being evaluated, the rig was run for 10 minutes at a load stage of 10. Six extreme pressure (EP) industrial gear oils of mineral base were tested. The difference in power requirements between the best and the worst performing oils was 2.77 and 3.24 kW, respectively. This equates to a 14.6% reduction in power, a significant amount if considered in relation to a high powered industrial machine. The oils of superior performance were noticed to run at reduced temperatures. They were also more expensive than the other products of lesser performance.
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The inclusion or not of chat services within Virtual Reference (VR) is an important topic for university libraries. Increasingly, email supported by a Frequently Asked Questions (FAQ) database is suggested in the scholarly literature as the preferred, cost-effective means for providing university VR services. This paper examines these issues and identifies some best practices for university library VR services relating to chat and email service, collaborative service provision, services staffing, and staff training. Further studies are required to more completely identify best practices for the complete range of VR services.
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Anecdotal evidence highlights issues of alcohol and other drugs (AODs) and its association with safety risk on construction sites. Information is limited however regarding the prevalence of AODs in the workplace and there is limited evidential guidance regarding how to effectively address it. This research aimed to scientifically evaluate the use of AODs within the Australian construction industry in order to reduce the potential resulting safety and performance impacts and engender a cultural change in the workforce. A national qualitative and quantitative evaluation of the use of AODs was conducted with approximately 500 employees. Results indicate that as in the general population, a proportion of those sampled in the construction sector may be at risk of hazardous alcohol consumption and support the need for evidence-based, tailored responses. This is the first known study to scientifically evaluate the use of AODs and potential workplace safety impacts in the construction sector.
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Background and Objective: As global warming continues, the frequency, intensity and duration of heatwaves are likely to increase. However, a heatwave is unlikely to be defined uniformly because acclimatisation plays a significant role in determining the heat-related impact. This study investigated how to best define a heatwave in Brisbane, Australia. Methods: Computerised datasets on daily weather, air pollution and health outcomes between 1996 and 2005 were obtained from pertinent government agencies. Paired t-tests and case-crossover analyses were performed to assess the relationship between heatwaves and health outcomes using different heatwave definitions. Results: The maximum temperature was as high as 41.5°C with a mean maximum daily temperature of 26.3°C. None of the five commonly-used heatwave definitions suited Brisbane well on the basis of the health effects of heatwaves. Additionally, there were pros and cons when locally-defined definitions were attempted using either a relative or absolute definition for extreme temperatures. Conclusion: The issue of how to best define a heatwave is complex. It is important to identify an appropriate definition of heatwave locally and to understand its health effects.
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Abstract: Purpose – Several major infrastructure projects in the Hong Kong Special Administrative Region (HKSAR) have been delivered by the build-operate-transfer (BOT) model since the 1960s. Although the benefits of using BOT have been reported abundantly in the contemporary literature, some BOT projects were less successful than the others. This paper aims to find out why this is so and to explore whether BOT is the best financing model to procure major infrastructure projects. Design/methodology/approach – The benefits of BOT will first be reviewed. Some completed BOT projects in Hong Kong will be examined to ascertain how far the perceived benefits of BOT have been materialized in these projects. A highly profiled project, the Hong Kong-Zhuhai-Macau Bridge, which has long been promoted by the governments of the People's Republic of China, Macau Special Administrative Region and the HKSAR that BOT is the preferred financing model, but suddenly reverted back to the traditional financing model to be funded primarily by the three governments with public money instead, will be studied to explore the true value of the BOT financial model. Findings – Six main reasons for this radical change are derived from the analysis: shorter take-off time for the project; difference in legal systems causing difficulties in drafting BOT agreements; more government control on tolls; private sector uninterested due to unattractive economic package; avoid allegation of collusion between business and the governments; and a comfortable financial reserve possessed by the host governments. Originality/value – The findings from this paper are believed to provide a better understanding to the real benefits of BOT and the governments' main decision criteria in delivering major infrastructure projects.
Resumo:
The World Wide Web has become a medium for people to share information. People use Web-based collaborative tools such as question answering (QA) portals, blogs/forums, email and instant messaging to acquire information and to form online-based communities. In an online QA portal, a user asks a question and other users can provide answers based on their knowledge, with the question usually being answered by many users. It can become overwhelming and/or time/resource consuming for a user to read all of the answers provided for a given question. Thus, there exists a need for a mechanism to rank the provided answers so users can focus on only reading good quality answers. The majority of online QA systems use user feedback to rank users’ answers and the user who asked the question can decide on the best answer. Other users who didn’t participate in answering the question can also vote to determine the best answer. However, ranking the best answer via this collaborative method is time consuming and requires an ongoing continuous involvement of users to provide the needed feedback. The objective of this research is to discover a way to recommend the best answer as part of a ranked list of answers for a posted question automatically, without the need for user feedback. The proposed approach combines both a non-content-based reputation method and a content-based method to solve the problem of recommending the best answer to the user who posted the question. The non-content method assigns a score to each user which reflects the users’ reputation level in using the QA portal system. Each user is assigned two types of non-content-based reputations cores: a local reputation score and a global reputation score. The local reputation score plays an important role in deciding the reputation level of a user for the category in which the question is asked. The global reputation score indicates the prestige of a user across all of the categories in the QA system. Due to the possibility of user cheating, such as awarding the best answer to a friend regardless of the answer quality, a content-based method for determining the quality of a given answer is proposed, alongside the non-content-based reputation method. Answers for a question from different users are compared with an ideal (or expert) answer using traditional Information Retrieval and Natural Language Processing techniques. Each answer provided for a question is assigned a content score according to how well it matched the ideal answer. To evaluate the performance of the proposed methods, each recommended best answer is compared with the best answer determined by one of the most popular link analysis methods, Hyperlink-Induced Topic Search (HITS). The proposed methods are able to yield high accuracy, as shown by correlation scores: Kendall correlation and Spearman correlation. The reputation method outperforms the HITS method in terms of recommending the best answer. The inclusion of the reputation score with the content score improves the overall performance, which is measured through the use of Top-n match scores.
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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.
Resumo:
The rhetoric of masculinity is at melting point in Australian culture. In the nineties, Australian television news and sporting programs have constructed a particularly shrill and insistent form of brash, heterosexual sporting masculinity in football reporting. Against this norm of rippling 'muscularity' and aggressive competition, all so-called aberrant forms of humanity such as women, homosexuals, and men who do not fit into Connell's 'hegemonic masculinity' paradigm have been effectively marginalised and silenced. Class and ethnicity discourses are at best muted, and at worst, ignored in much of the writing about sporting masculinity. While acknowledging the significance of class and ethnicity, this paper explores the nexus between gender, sexuality, the media and League football.
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This article rebuts the still-common assumption that managers of capitalist entities have a duty, principally or even exclusively, to maximise the monetary return to investors on their investments. It argues that this view is based on a misleadingly simplistic conception of human values and motivation. Not only is acting solely to maximise long-term shareholder value difficult, it displays, at best, banal single-mindedness and, at worst, sociopathy. In fact, real investors and managers have rich constellations of values that should be taken account of in all their decisions, including their business decisions. Awareness of our values, and public expression of our commitment to exemplify them, make for healthier investment and, in the long term, a healthier corporate world. Individuals and funds investing on the basis of such values, in companies that express their own, display humanity rather than pathology. Preamble I always enjoyed the discussions that Michael Whincop and I had about the interaction of ethics and economics. Each of us could see an important role for these disciplines, as well as our common discipline of law. We also shared an appreciation of the institutional context within which much of the drama of life is played out. In understanding the behaviour of individuals and the choices they make, it seemed axiomatic to each of us that ethics and economics have a lot to say. This was also true of the institutions in which they operate. Michael ·had a strong interest in 'the new institutional economics' I and I had a strong interest in 'institutionalising ethics' right through the 1990s.' This formed the basis of some fascinating and fruitful discussions. Professor Charles Sampford is Director, Key Centre for Ethics, Law, Justice and Governance, Foundation Professor of Law at Griffith University and President, International Institute for Public Ethics.DrVirginia Berry is a Research Fellow at theKey Centre for Ethics, Law,Justice andGovernance, Griffith University. Oliver Williamson, one of the leading proponents of the 'new institutional economics', published a number of influential works - see Williamson (1975, 1995,1996). Sampford (1991),' pp 185-222. The primary focus of discussions on institutionalising ethics has been in public sectorethics: see, for example, Preston and Sampford (2002); Sampford (1994), pp 114-38. Some discussion has, however, moved beyond the public sector to include business - see Sampford 200408299
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The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.
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Hot and cold temperatures significantly increase mortality rates around the world, but which measure of temperature is the best predictor of mortality is not known. We used mortality data from 107 US cities for the years 1987–2000 and examined the association between temperature and mortality using Poisson regression and modelled a non-linear temperature effect and a non-linear lag structure. We examined mean, minimum and maximum temperature with and without humidity, and apparent temperature and the Humidex. The best measure was defined as that with the minimum cross-validated residual. We found large differences in the best temperature measure between age groups, seasons and cities, and there was no one temperature measure that was superior to the others. The strong correlation between different measures of temperature means that, on average, they have the same predictive ability. The best temperature measure for new studies can be chosen based on practical concerns, such as choosing the measure with the least amount of missing data.
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The overall theme for the 4th Biennial International Network of Indigenous Health Knowledge and Development (INIHKD)Conference was ‘Knowing Our Roots: Indigenous Medicines, Health Knowledges and Best Practices’. Conference activities were grouped around the following broad themes: •Building of Indigenous research capacity, partnerships and workforce; •Sharing of innovative, traditional and contemporary Indigenous knowledges, especially with respect to culturally-grounded interventions and evidenced-based “best and promising practices”; •Identification of successful Indigenous health policy solutions; and •Sharing of ethical, Indigenous-based research protocols and methodologies. This keynote plenary presentation focused on 'best practice' in research asking the questions: What kind of research will I do? What kind of research will I be? What is the contribution that I will make? what will be my legacy?