915 resultados para Data reporting
Resumo:
Traffic Simulation models tend to have their own data input and output formats. In an effort to standardise the input for traffic simulations, we introduce in this paper a set of data marts that aim to serve as a common interface between the necessaary data, stored in dedicated databases, and the swoftware packages, that require the input in a certain format. The data marts are developed based on real world objects (e.g. roads, traffic lights, controllers) rather than abstract models and hence contain all necessary information that can be transformed by the importing software package to their needs. The paper contains a full description of the data marts for network coding, simulation results, and scenario management, which have been discussed with industry partners to ensure sustainability.
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In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector major infrastructure market, especially in very large economic infrastructure procured using Pubic Private Partnerships, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI) into the Australian construction market. This paper aims to report on progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major infrastructure projects and which is designed to give an improved understanding of matters surrounding FDI into the Australian construction sector. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors and as head contractors bidding for Australian major infrastructure public sector projects. Elsewhere, the authors have developed Dunning’s principal hypothesis associated with his eclectic framework in order to suit the context of this research and to address a weakness arising in Dunning’s principal hypothesis that is based on a nominal approach to the factors in the eclectic framework and which fail to speak to the relative explanatory power of these factors. In this paper, an approach to reviewing and analysing secondary data, as part of the first stage investigation in this research, is developed and some illustrations given, vis-à-vis the selected sector (roads, bridges and tunnels) in Australia (as the host location) and using one of the selected home countries (Spain). In conclusion, some tentative thoughts are offered in anticipation of the completion of the first stage investigation - in terms of the extent to which this first stage based on secondary data only might suggest the relative importance of the factors in the eclectic framework. It is noted that more robust conclusions are expected following the future planned stages of the research and these stages including primary data are briefly outlined. Finally, and beyond theoretical contributions expected from the overall approach taken to developing and testing Dunning’s framework, other expected contributions concerning research method and practical implications are mentioned.
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Researchers are increasingly involved in data-intensive research projects that cut across geographic and disciplinary borders. Quality research now often involves virtual communities of researchers participating in large-scale web-based collaborations, opening their earlystage research to the research community in order to encourage broader participation and accelerate discoveries. The result of such large-scale collaborations has been the production of ever-increasing amounts of data. In short, we are in the midst of a data deluge. Accompanying these developments has been a growing recognition that if the benefits of enhanced access to research are to be realised, it will be necessary to develop the systems and services that enable data to be managed and secured. It has also become apparent that to achieve seamless access to data it is necessary not only to adopt appropriate technical standards, practices and architecture, but also to develop legal frameworks that facilitate access to and use of research data. This chapter provides an overview of the current research landscape in Australia as it relates to the collection, management and sharing of research data. The chapter then explains the Australian legal regimes relevant to data, including copyright, patent, privacy, confidentiality and contract law. Finally, this chapter proposes the infrastructure elements that are required for the proper management of legal interests, ownership rights and rights to access and use data collected or generated by research projects.
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This report provides an evaluation of the current available evidence-base for identification and surveillance of product-related injuries in children in Queensland. While the focal population was children in Queensland, the identification of information needs and data sources for product safety surveillance has applicability nationally for all age groups. The report firstly summarises the data needs of product safety regulators regarding product-related injury in children, describing the current sources of information informing product safety policy and practice, and documenting the priority product surveillance areas affecting children which have been a focus over recent years in Queensland. Health data sources in Queensland which have the potential to inform product safety surveillance initiatives were evaluated in terms of their ability to address the information needs of product safety regulators. Patterns in product-related injuries in children were analysed using routinely available health data to identify areas for future intervention, and the patterns in product-related injuries in children identified in health data were compared to those identified by product safety regulators. Recommendations were made for information system improvements and improved access to and utilisation of health data for more proactive approaches to product safety surveillance in the future.
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Assurance of learning is a predominant feature in both quality enhancement and assurance in higher education. Assurance of learning is a process that articulates explicit program outcomes and standards, and systematically gathers evidence to determine the extent to which performance matches expectations. Benefits accrue to the institution through the systematic assessment of whole of program goals. Data may be used for continuous improvement, program development, and to inform external accreditation and evaluation bodies. Recent developments, including the introduction of the Tertiary Education and Quality Standards Agency (TEQSA) will require universities to review the methods they use to assure learning outcomes. This project investigates two critical elements of assurance of learning: 1. the mapping of graduate attributes throughout a program; and 2. the collection of assurance of learning data. An audit was conducted with 25 of the 39 Business Schools in Australian universities to identify current methods of mapping graduate attributes and for collecting assurance of learning data across degree programs, as well as a review of the key challenges faced in these areas. Our findings indicate that external drivers like professional body accreditation (for example: Association to Advance Collegiate Schools of Business (AACSB)) and TEQSA are important motivators for assuring learning, and those who were undertaking AACSB accreditation had more robust assurance of learning systems in place. It was reassuring to see that the majority of institutions (96%) had adopted an embedding approach to assuring learning rather than opting for independent standardised testing. The main challenges that were evident were the development of sustainable processes that were not considered a burden to academic staff, and obtainment of academic buy in to the benefits of assuring learning per se rather than assurance of learning being seen as a tick box exercise. This cultural change is the real challenge in assurance of learning practice.
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Abstract OBJECTIVE: Depression, anxiety and alcohol misuse frequently co-occur. While there is an extensive literature reporting on the efficacy of psychological treatments that target depression, anxiety or alcohol misuse separately, less research has examined treatments that address these disorders when they co-occur. We conducted a systematic review to determine whether psychological interventions that target alcohol misuse among people with co-occurring depressive or anxiety disorders are effective. DATA SOURCES: We systematically searched the PubMed and PsychINFO databases from inception to March 2010. Individual searches in alcohol, depression and anxiety were conducted, and were limited to 'human' published 'randomized controlled trials' or 'sequential allocation' articles written in English. STUDY SELECTION: We identified randomized controlled trials that compared manual guided psychological interventions for alcohol misuse among individuals with depressive or anxiety disorders. Of 1540 articles identified, eight met inclusion criteria for the review. DATA EXTRACTION: From each study, we recorded alcohol and mental health outcomes, and other relevant clinical factors including age, gender ratio, follow-up length and drop-out rates. Quality of studies was also assessed. DATA SYNTHESIS: Motivational interviewing and cognitive-behavioral interventions were associated with significant reductions in alcohol consumption and depressive and/or anxiety symptoms. Although brief interventions were associated with significant improvements in both mental health and alcohol use variables, longer interventions produced even better outcomes. CONCLUSIONS: There is accumulating evidence for the effectiveness of motivational interviewing and cognitive behavior therapy for people with co-occurring alcohol and depressive or anxiety disorders.
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As the development of ICD-11 progresses, the Australian Bureau of Statistics is beginning to consider what will be required to successfully implement the new version of the classification. This paper will present early thoughts on the following: building understanding amongst the user community of upcoming changes and the implications of those changes; the need for training of coders and data users; development of analytical methods and conduct of comparability studies; processes to test, accept and implement new or updated coding software; assessment of coding quality; changes to data analyses and reporting processes; updates to regular publications; and assessing the resources required for successful implementation.
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Background Caring for a child with a disability can be a unique and challenging experience, with families often relying on informal networks for support. Often, grandparents are key support resources, yet little is known about their roles and experiences. Reporting on data collected in a larger Australian study, this article explores grandparents' experiences of caring for a child with a disability and the impact on their family relationships and quality of life. Method A qualitative purposive sampling design was utilised; semi-structured interviews were conducted with 22 grandparents (17 women, 5 men) of children with a disability. Grandparents ranged in age from 55 to 75 years old and lived within a 90-min drive of Brisbane, Australia. Interviews were transcribed and responses analysed using a thematic approach, identifying categories, themes and patterns. Findings Four key themes characterised grandparents' views about their role in the family: holding own emotions (decision to be positive), self-sacrifice (decision to put family needs first), maintaining family relationships (being the ‘go-between’) and quality of life for family in the future (concerns about the future). Conclusions Grandparents are central to family functioning and quality of life, but this contribution comes with a significant cost to their own personal well-being. Implications for policy, practice and research are discussed, particularly grandparents' fear that their family could not cope without their support.
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This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Some of the core components of data modelling are addressed. A selection of results from the first data modelling activity implemented during the second year (2010; second grade) of a current longitudinal study are reported. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Reported here are children's abilities to identify diverse and complex attributes, sort and classify data in different ways, and create and interpret models to represent their data.
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PURPOSE/OBJECTIVES: To determine the prevalence of malnutrition and chemotherapy-induced nausea and vomiting (CINV) limiting dietary intake in a chemotherapy unit. DESIGN Cross sectional descriptive audit. SETTING: Chemotherapy ambulatory care unit in an Australian teaching hospital. SAMPLE 121 patients receiving chemotherapy for malignancies, ≥18yrs and able to provide verbal consent. METHODS: An Accredited Practicing Dietitian collected all data. Chi-square tests were used to determine the relationship of malnutrition with variables and demographic data. MAIN RESEARCH VARIABLES: Nutritional status, weight change, BMI, prior dietetic input, CINV and CINV that limited dietary intake. FINDINGS Thirty one (26%) participants were malnourished, 12 (10%) had intake-limiting CINV, 22 (20%) reported significant weight loss and 20 (18%) required improved nutrition symptom management. High nutrition risk diagnoses, CINV, BMI and weight loss were significantly associated with malnutrition. Thirteen (35%) participants with malnutrition, significant weight loss, intake-limiting CINV and/or critically requiring improved symptom management reported no dietetic input; the majority of whom were overweight or obese. CONCLUSIONS: This audit determined over one quarter of patients receiving chemotherapy in this ambulatory setting were malnourished and the majority of patients reporting intake-limiting CINV were malnourished. IMPLICATIONS FOR NURSING Patients with malnutrition and/or intake-limiting CINV and in need of improved nutrition symptom management may be overlooked, especially patients who are overweight or obese - an increasing proportion of the Australian population. Evidence-based practice guidelines recommend implementing validated nutrition screening tools, such as the Malnutrition Screening Tool, in patients undergoing chemotherapy to identify those at risk of malnutrition requiring dietitian referral.
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Methodological differences among studies of vasomotor symptoms limit rigorous comparison or systematic review. Vasomotor symptoms generally include hot flushes and night sweats although other associated symptoms exist. Prevalence rates vary between and within populations, but different studies collect data on frequency, bothersomeness, and/or severity using different outcome measures and scales, making comparisons difficult. We reviewed only cross-cultural studies of menopausal symptoms that explicitly examined symptoms in general populations of women in different countries or different ethnic groups in the same country. This resulted in the inclusion of nine studies: Australian/Japanese Midlife Women's Health Study (AJMWHS), Decisions At Menopause Study (DAMeS), Four Major Ethnic Groups (FMEG), Hilo Women's Health Survey (HWHS), Mid-Aged Health in Women from the Indian Subcontinent (MAHWIS), Penn Ovarian Aging Study (POAS), Study of Women's Health Across the Nation (SWAN), Women's Health in Midlife National Study (WHiMNS), and Women's International Study of Health and Sexuality (WISHeS). These studies highlight the methodological challenges involved in conducting multi-population studies, particularly when languages differ, but also highlight the importance of performing multivariate and factor analyses. Significant cultural differences in one or more vasomotor symptoms were observed in 8 of 9 studies, and symptoms were influenced by the following determinants: menopausal status, hormones (and variance), age (or actually, the square of age, age2), BMI, depression, anxiety, poor physical health, perceived stress, lifestyle factors (hormone therapy use, smoking and exposure to passive smoke), and acculturation (in immigrant populations). Recommendations are made to improve methodological rigor and facilitate comparisons in future cross-cultural menopause studies.
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This paper reviews the methods used in cross-cultural studies of menopausal symptoms with the goal of formulating recommendations to facilitate comparisons of menopausal symptoms across cultures. It provides an overview of existing approaches and serves to introduce four separate reviews of vasomotor, psychological, somatic, and sexual symptoms at midlife. Building on an earlier review of cross-cultural studies of menopause covering time periods until 2004, these reviews are based on searches of Medline, PsycINFO, CINAHL and Google Scholar for English-language articles published from 2004 to 2010 using the terms “cross cultural comparison” and “menopause.” Two major criteria were used: a study had to include more than one culture, country, or ethnic group and to have asked about actual menopausal symptom experience. We found considerable variation across studies in age ranges, symptom lists, reference period for symptom recall, variables included in multivariate analyses, and the measurement of factors (e.g., menopausal status and hormonal factors, demographic, anthropometric, mental/physical health, and lifestyle measures) that influence vasomotor, psychological, somatic and sexual symptoms. Based on these reviews, we make recommendations for future research regarding age range, symptom lists, reference/recall periods, and measurement of menopausal status. Recommendations specific to the cross-cultural study of vasomotor, psychological, somatic, and sexual symptoms are found in the four reviews that follow this introduction.
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Data flow analysis techniques can be used to help assess threats to data confidentiality and integrity in security critical program code. However, a fundamental weakness of static analysis techniques is that they overestimate the ways in which data may propagate at run time. Discounting large numbers of these false-positive data flow paths wastes an information security evaluator's time and effort. Here we show how to automatically eliminate some false-positive data flow paths by precisely modelling how classified data is blocked by certain expressions in embedded C code. We present a library of detailed data flow models of individual expression elements and an algorithm for introducing these components into conventional data flow graphs. The resulting models can be used to accurately trace byte-level or even bit-level data flow through expressions that are normally treated as atomic. This allows us to identify expressions that safely downgrade their classified inputs and thereby eliminate false-positive data flow paths from the security evaluation process. To validate the approach we have implemented and tested it in an existing data flow analysis toolkit.
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Road asset managers are overwhelmed with a high volume of raw data which they need to process and utilise in supporting their decision making. This paper presents a method that processes road-crash data of a whole road network and exposes hidden value inherent in the data by deploying the clustering data mining method. The goal of the method is to partition the road network into a set of groups (classes) based on common data and characterise the class crash types to produce a crash profiles for each cluster. By comparing similar road classes with differing crash types and rates, insight can be gained into these differences that are caused by the particular characteristics of their roads. These differences can be used as evidence in knowledge development and decision support.
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This paper argues for a renewed focus on statistical reasoning in the elementary school years, with opportunities for children to engage in data modeling. Data modeling involves investigations of meaningful phenomena, deciding what is worthy of attention, and then progressing to organizing, structuring, visualizing, and representing data. Reported here are some findings from a two-part activity (Baxter Brown’s Picnic and Planning a Picnic) implemented at the end of the second year of a current three-year longitudinal study (grade levels 1-3). Planning a Picnic was also implemented in a grade 7 class to provide an opportunity for the different age groups to share their products. Addressed here are the grade 2 children’s predictions for missing data in Baxter Brown’s Picnic, the questions posed and representations created by both grade levels in Planning a Picnic, and the metarepresentational competence displayed in the grade levels’ sharing of their products for Planning a Picnic.