986 resultados para Grouped data
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BACKGROUND: Frequent illness and injury among workers with high body mass index (BMI) can raise the costs of employee healthcare and reduce workforce maintenance and productivity. These issues are particularly important in vocational settings such as the military, which require good physical health, regular attendance and teamwork to operate efficiently. The purpose of this study was to compare the incidence of injury and illness, absenteeism, productivity, healthcare usage and administrative outcomes among Australian Defence Force personnel with varying BMI. METHODS: Personnel were grouped into cohorts according to the following ranges for (BMI): normal (18.5-24.9 kg/m²; n = 197), overweight (25-29.9 kg/m²; n = 154) and obese (≥30 kg/m²) with restricted body fat (≤28 % for females, ≤24 % for males) (n = 148) and with no restriction on body fat (n = 180). Medical records for each individual were audited retrospectively to record the incidence of injury and illness, absenteeism, productivity, healthcare usage (i.e., consultation with medical specialists, hospital stays, medical investigations, prescriptions) and administrative outcomes (e.g., discharge from service) over one year. These data were then grouped and compared between the cohorts. RESULTS: The prevalence of injury and illness, cost of medical specialist consultations and cost of medical scans were all higher (p <0.05) in both obese cohorts compared with the normal cohort. The estimated productivity losses from restricted work days were also higher (p <0.05) in the obese cohort with no restriction on body fat compared with the normal cohort. Within the obese cohort, the prevalence of injury and illness, healthcare usage and productivity were not significantly greater in the obese cohort with no restriction on body fat compared with the cohort with restricted body fat. The number of restricted work days, the rate of re-classification of Medical Employment Classification and the rate of discharge from service were similar between all four cohorts. CONCLUSIONS: High BMI in the military increases healthcare usage, but does not disrupt workforce maintenance. The greater prevalence of injury and illness, greater healthcare usage and lower productivity in obese Australian Defence Force personnel is not related to higher levels of body fat.
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There is still no comprehensive information strategy governing access to and reuse of public sector information, applying on a nationwide basis, across all levels of government – local, state and federal - in Australia. This is the case both for public sector materials generally and for spatial data in particular. Nevertheless, the last five years have seen some significant developments in information policy and practice, the result of which has been a considerable lessening of the barriers that previously acted to impede the accessibility and reusability of a great deal of spatial and other material held by public sector agencies. Much of the impetus for change has come from the spatial community which has for many years been a proponent of the view “that government held information, and in particular spatial information, will play an absolutely critical role in increasing the innovative capacity of this nation.”1 However, the potential of government spatial data to contribute to innovation will remain unfulfilled without reform of policies on access and reuse as well as the pervasive practices of public sector data custodians who have relied on government copyright to justify the imposition of restrictive conditions on its use.
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Open Educational Resources (OER) are teaching, learning and research materials that have been released under an open licence that permits online access and re-use by others. The 2012 Paris OER Declaration encourages the open licensing of educational materials produced with public funds. Digital data and data sets produced as a result of scientific and non-scientific research are an increasingly important category of educational materials. This paper discusses the legal challenges presented when publicly funded research data is made available as OER, arising from intellectual property rights, confidentiality and information privacy laws, and the lack of a legal duty to ensure data quality. If these legal challenges are not understood, addressed and effectively managed, they may impede and restrict access to and re-use of research data. This paper identifies some of the legal challenges that need to be addressed and describes 10 proposed best practices which are recommended for adoption to so that publicly funded research data can be made available for access and re-use as OER.
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Members of the World Trade Organisation (WTO) are obliged to implement the Agreement on Trade-related Intellectual Property Rights 1994 (TRIPS) which establishes minimum standards for the protection and enforcement of intellectual property rights. Almost two decades after TRIPS was adopted at the conclusion of the Uruguay Round of trade negotiations, it is widely accepted that intellectual property systems in developing and least-developed countries must be consistent with, and serve, their development needs and objectives. In adopting the Development Agenda in 2007, the World Intellectual Property Organisation (WIPO) emphasised the importance to developing and least-developed countries of being able to obtain access to knowledge and technology and to participate in collaborations and exchanges with research and scientific institutions in other countries. Access to knowledge, information and technology is crucial if creativity and innovation is to be fostered in developing and least-developed countries. It is particularly important that developing and least-developed countries give effect to their TRIPS obligations by implementing intellectual property systems and adopting intellectual property management practices that enable them to benefit from knowledge flows and support their engagement in international research and science collaborations. However, developing and least-developed countries did not participate in the deliberations leading to the adoption in 2004 by Organisation for Economic Co-operation and Development (OECD) member countries of the Ministerial Declaration on Access to Research Data from Public Funding, nor have they formulated policies on access to publicly funded research outputs such as those developed by the National Institutes of Health in the United States, the United Kingdom Research Councils or the Australian National Health and Medical Research Council. These issues are considered from the viewpoint of Malaysia, a developing country whose economy has grown strongly in recent years. Lacking an established policy covering access to the outputs of publicly funded research, data sharing and licensing practices continue to be fragmented. Obtaining access to research data requires arrangements to be negotiated with individual data owners and custodians. Given the potential for restrictions on access to impact negatively on scientific progress and development in Malaysia, measures are required to ensure that access to knowledge and research results is facilitated. This paper proposes a policy framework for Malaysia‘s public research universities that recognises intellectual property rights while enabling the open access to research data that is essential for innovation and development. It also considers how intellectual property rights in research data can be managed in order to give effect to the policy‘s open access objectives.
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Buildings are key mediators between human activity and the environment around them, but details of energy usage and activity in buildings is often poorly communicated and understood. ECOS is an Eco-Visualization project that aims to contextualize the energy generation and consumption of a green building in a variety of different climates. The ECOS project is being developed for a large public interactive space installed in the new Science and Engineering Centre of the Queensland University of Technology that is dedicated to delivering interactive science education content to the public. This paper focuses on how design can develop ICT solutions from large data sets to create meaningful engagement with environmental data.
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Key decisions at the collection, pre-processing, transformation, mining and interpretation phase of any knowledge discovery from database (KDD) process depend heavily on assumptions and theorectical perspectives relating to the type of task to be performed and characteristics of data sourced. In this article, we compare and contrast theoretical perspectives and assumptions taken in data mining exercises in the legal domain with those adopted in data mining in TCM and allopathic medicine. The juxtaposition results in insights for the application of KDD for Traditional Chinese Medicine.
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Abstract (provisional) Background Food Frequency Questionnaires (FFQs) are commonly used in epidemiologic studies to assess long-term nutritional exposure. Because of wide variations in dietary habits in different countries, a FFQ must be developed to suit the specific population. Sri Lanka is undergoing nutritional transition and diet-related chronic diseases are emerging as an important health problem. Currently, no FFQ has been developed for Sri Lankan adults. In this study, we developed a FFQ to assess the regular dietary intake of Sri Lankan adults. Methods A nationally representative sample of 600 adults was selected by a multi-stage random cluster sampling technique and dietary intake was assessed by random 24-h dietary recall. Nutrient analysis of the FFQ required the selection of foods, development of recipes and application of these to cooked foods to develop a nutrient database. We constructed a comprehensive food list with the units of measurement. A stepwise regression method was used to identify foods contributing to a cumulative 90% of variance to total energy and macronutrients. In addition, a series of photographs were included. Results We obtained dietary data from 482 participants and 312 different food items were recorded. Nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Conclusion We developed a FFQ and the related nutrient composition database for Sri Lankan adults. Culturally specific dietary tools are central to capturing the role of diet in risk for chronic disease in Sri Lanka. The next step will involve the verification of FFQ reproducibility and validity.
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Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.
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Health complaint statistics are important for identifying problems and bringing about improvements to health care provided by health service providers and to the wider health care system. This paper overviews complaints handling by the eight Australian state and territory health complaint entities, based on an analysis of data from their annual reports. The analysis shows considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded. Complaints from the public are an important accountability mechanism and open a window on service quality. The lack of a national approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. We need a national approach to complaints data collection in order to better respond to patients’ concerns.
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Background and aims: Lower-limb lymphoedema is a serious and feared sequela after treatment for gynaecological cancer. Given the limited prospective data on incidence of and risk factors for lymphoedema after treatment for gynaecological cancer we initiated a prospective cohort study in 2008. Methods: Data were available for 353 women with malignant disease. Participants were assessed before treatment and at regular intervals after treatment for two years. Follow-up visits were grouped into time-periods of six weeks to six months (time 1), nine months to 15 months (time 2), and 18 months to 24 months (time 3). Preliminary data analyses were undertaken up to time 2 using generalised estimating equations to model the repeated measures data of Functional Assessment of Cancer Therapy-General (FACT-G) quality of life (QoL) scores and self-reported swelling at each follow-up period (best-fitting covariance structure). Results: Depending on the time-period, between 30% and 40% of patients self-reported swelling of the lower limb. The QoL of those with self-reported swelling was lower at all time-periods compared with those who did not have swelling. Mean (95% CI) FACT-G scores at time 0, 1 and 2 were 80.7 (78.2, 83.2), 83.0 (81.0, 85.0) and 86.3 (84.2, 88.4), respectively for those with swelling and 85.0 (83.0, 86.9), 86.0 (84.1, 88.0) and 88.9 (87.0, 90.7), respectively for those without swelling. Conclusions: Lower-limb swelling adversely influences QoL and change in QoL over time in patients with gynaecological cancer.
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Background: National physical activity data suggest that there is a considerable difference in physical activity levels of US and Australian adults. Although different surveys (Active Australia and BRFSS) are used, the questions are similar. Different protocols, however, are used to estimate “activity” from the data collected. The primary aim of this study was to assess whether the 2 approaches to the management of PA data could explain some of the difference in prevalence estimates derived from the two national surveys. Methods: Secondary data analysis of the most recent AA survey (N = 2987). Results: 15% of the sample was defined as “active” using Australian criteria but as “inactive” using the BRFSS protocol, even though weekly energy expenditure was commensurate with meeting current guidelines. Younger respondents (age < 45 y) were more likely to be “misclassified” using the BRFSS criteria. Conclusions: The prevalence of activity in Australia and the US appears to be more similar than we had previously thought.
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Client owners usually need an estimate or forecast of their likely building costs in advance of detailed design in order to confirm the financial feasibility of their projects. Because of their timing in the project life cycle, these early stage forecasts are characterized by the minimal amount of information available concerning the new (target) project to the point that often only its size and type are known. One approach is to use the mean contract sum of a sample, or base group, of previous projects of a similar type and size to the project for which the estimate is needed. Bernoulli’s law of large numbers implies that this base group should be as large as possible. However, increasing the size of the base group inevitably involves including projects that are less and less similar to the target project. Deciding on the optimal number of base group projects is known as the homogeneity or pooling problem. A method of solving the homogeneity problem is described involving the use of closed form equations to compare three different sampling arrangements of previous projects for their simulated forecasting ability by a cross-validation method, where a series of targets are extracted, with replacement, from the groups and compared with the mean value of the projects in the base groups. The procedure is then demonstrated with 450 Hong Kong projects (with different project types: Residential, Commercial centre, Car parking, Social community centre, School, Office, Hotel, Industrial, University and Hospital) clustered into base groups according to their type and size.
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The selection of appropriate analogue materials is a central consideration in the design of realistic physical models. We investigate the rheology of highly-filled silicone polymers in order to find materials with a power-law strain-rate softening rheology suitable for modelling rock deformation by dislocation creep and report the rheological properties of the materials as functions of the filler content. The mixtures exhibit strain-rate softening behaviour but with increasing amounts of filler become strain-dependent. For the strain-independent viscous materials, flow laws are presented while for strain-dependent materials the relative importance of strain and strain rate softening/hardening is reported. If the stress or strain rate is above a threshold value some highly-filled silicone polymers may be considered linear visco-elastic (strain independent) and power-law strain-rate softening. The power-law exponent can be raised from 1 to ~3 by using mixtures of high-viscosity silicone and plasticine. However, the need for high shear strain rates to obtain the power-law rheology imposes some restrictions on the usage of such materials for geodynamic modelling. Two simple shear experiments are presented that use Newtonian and power-law strain-rate softening materials. The results demonstrate how materials with power-law rheology result in better strain localization in analogue experiments.