847 resultados para Mining claims
Resumo:
It is nearly 10 years since the introduction of s 299(1)(f) Corporations Act , which requires the disclosure of information regarding a company's environmental performance within its annual report. This provision has generated considerable debate in the years since its introduction, fundamentally between proponents of either a voluntary or mandatory environmental reporting framework. This study examines the adequacy of the current regulatory framework. The environmental reporting practices of 24 listed companies in the resources industries are assessed relative to a standard set by the Global Reporting Initiative (GRI) Sustainability Reporting Guidelines. These Guidelines are argued to represent "international best practice" in environmental reporting and a "scorecard" approach is used to score the quality of disclosure according to this voluntary benchmark. Larger companies in the sample tend to report environmental information over and above the level required by legislation. Some, but not all companies present a stand-alone environmental/sustainability report. However, smaller companies provide minimal information in compliance with s 299(1)(f) . The findings indicate that "international best practice" environmental reporting is unlikely to be achieved by Australian companies under the current regulatory framework. In the current regulatory environment that scrutinises s 299(1)(f) , this article provides some preliminary evidence of the quality of disclosures generated in the Australian market.
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While changes in work and employment practices in the mining sector have been profound, the literature addressing mining work is somewhat partial as it focuses primarily on the workplace as the key (or only) site of analysis, leaving the relationship between mining work and families and communities under-theorized. This article adopts a spatially oriented, case-study approach to the sudden closure of the Ravensthorpe nickel mine in the south-west of Western Australia to explore the interplay between the new scales and mobilities of labour and capital and work–family–community connections in mining. In the context of the dramatically reconfigured industrial arena of mining work, the study contributes to a theoretical engagement between employment relations and the spatial dimensions of family and community in resource-affected communities.
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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.
Resumo:
Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.
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Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.
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The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.
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Many donors, particularly those contemplating a substantial donation, consider whether their donation will be deductible from their taxable income. This motivation is not lost on fundraisers who conduct appeals before the end of the taxation year to capitalise on such desires. The motivation is also not lost on Treasury analysts who perceive the tax deduction as “lost” revenue and wonder if the loss is “efficient” in economic terms. Would it be more efficient for the government to give grants to deserving organisations, rather than permitting donor directed gifts? Better still, what about contracts that lock in the use of the money for a government priority? What place does tax deduction play in influencing a donor to give? Does the size of the gift bear any relationship to the size of the tax deduction? Could an increased level of donations take up an increasing shortfall in government welfare and community infrastructure spending? Despite these questions being asked regularly, little has been rigorously established about the effect of taxation deductions on a donor’s gifts.
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In the shared space of a school playground, matters of ownership and possession are seriously attended to by children in their everyday encounters with others. The study reported here uses conversation analysis and an ethnomethodological approach to investigate a dispute between two children, aged four to six years, as they decide whose idea for the game will be used. Drawing on Sacks’ (1995a) notion of possession, and Sharrock’s (1974) paper “on owning knowledge”, this paper demonstrates how children draw on the phrase, “that’s my idea”, to claim ownership. Analysis of their video-recorded interaction shows how the children used physical actions, gaze and talk to invoke their own intellectual property as a commodity in the dispute. Whilst invoking ownership, analysis highlights that entitlement over people, objects and the decisions of the shared interactional space did not occur unproblematically. Material objects were used to counter claims to ideas, and it was the uptake of the game and the use of play objects by others that led to whether the idea of game category was upheld. This analysis enables adults a glimpse into the complex social organisation of children’s peer group.
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STUDY QUESTION: What is the self-reported use of in vitro fertilization (IVF) and ovulation induction (OI) in comparison with insurance claims by Australian women aged 28–36 years? SUMMARY ANSWER: The self-reported use of IVF is quite likely to be valid; however, the use of OI is less well reported. WHAT IS KNOWN AND WHAT THIS PAPER ADDS: Population-based research often relies on the self-reported use of IVF and OI because access to medical records can be difficult and the data need to include sufficient personal identifying information for linkage to other data sources. There have been few attempts to explore the reliability of the self-reported use of IVF and OI using the linkage to medical insurance claims for either treatment. STUDY DESIGN: This prospective, population-based, longitudinal study included the cohort of women born during 1973–1978 and participating in the Australian Longitudinal Study on Women's Health (ALSWH) (n = 14247). From 1996 to 2009, participants were surveyed up to five times. PARTICIPANTS AND SETTING: Participants self-reported their use of IVF or OI in two mailed surveys when aged 28–33 and 31–36 years (n = 7280), respectively. This study links self-report survey responses and claims for treatment or medication from the universal national health insurance scheme (i.e. Medicare Australia). MAIN RESULTS AND THE ROLE OF CHANCE: Comparisons between self-reports and claims data were undertaken for all women consenting to the linkage (n = 3375). The self-reported use of IVF was compared with claims for OI for IVF (Kappa, K = 0.83), oocyte collection (K = 0.82), sperm preparation (K = 0.83), intracytoplasmic sperm injection (K = 0.40), fresh embryo transfers (K = 0.82), frozen embryo transfers (K = 0.64) and OI for IVF medication (K = 0.17). The self-reported use of OI was compared with ovulation monitoring (K = 0.52) and OI medication (K = 0.71). BIAS, CONFOUNDING AND OTHER REASONS FOR CAUTION: There is a possibility of selection bias due to the inclusion criteria for participants in this study: (1) completion of the last two surveys in a series of five and (2) consent to the linkage of their responses with Medicare data. GENERALIZABILITY TO OTHER POPULATIONS: The results are relevant to questionnaire-based research studies with infertile women in developed countries. STUDY FUNDING/COMPETING INTEREST(S): ALSWH is funded by the Australian Government Department of Health and Ageing. This research is funded by a National Health and Medical Research Council Centre of Research Excellence grant.
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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.
Resumo:
Each year, organizations in Australian mining industry (asset intensive industry) spend substantial amount of capital (A$86 billion in 2009-10) (Statistics, 2011) in acquiring engineering assets. Engineering assets are put to use in operations to generate value. Different functions (departments) of an organization have different expectations and requirements from each of the engineering asset e.g. return on investment, reliability, efficiency, maintainability, low cost of running the asset, low or nil environmental impact and easy of disposal, potential salvage value etc. Assets are acquired from suppliers or built by service providers and or internally. The process of acquiring assets is supported by procurement function. One of the most costly mistakes that organizations can make is acquiring the inappropriate or non-conforming assets that do not fit the purpose. The root cause of acquiring non confirming assets belongs to incorrect acquisition decision and the process of making decisions. It is very important that an asset acquisition decision is based on inputs and multi-criteria of each function within the organization which has direct or indirect impact on the acquisition, utilization, maintenance and disposal of the asset. Literature review shows that currently there is no comprehensive process framework and tool available to evaluate the inclusiveness and breadth of asset acquisition decisions that are taken in the Mining Organizations. This thesis discusses various such criteria and inputs that need to be considered and evaluated from various functions within the organization while making the asset acquisition decision. Criteria from functions such as finance, production, maintenance, logistics, procurement, asset management, environment health and safety, material management, training and development etc. need to be considered to make an effective and coherent asset acquisition decision. The thesis also discusses a tool that is developed to be used in the multi-criteria and cross functional acquisition decision making. The development of multi-criteria and cross functional inputs based decision framework and tool which utilizes that framework to formulate cross functional and integrated asset acquisition decisions are the contribution of this research.
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The sky is falling because the much-vaunted mining ‘boom’ is heading for ‘bust’. The fear-mongering by politicians, the industry and the media has begun in earnest. On ABC TV's 7:30 program on 22 August 2012, Federal Opposition Leader Tony Abbott blamed the Minerals Resource Rent Tax and the Carbon Tax for making ‘a bad investment environment much, much worse’ for the mining industry. The following day, Australia's Resources and Energy Minister Martin Ferguson told us on ABC radio that ‘the resources boom is over’. This must be true because, remember, we were warned to ‘Get ready for the end of the boom’ (David Uren, Economics Editor for The Australian 19 May 2012) due to the ‘Australian resource boom losing steam’ (David Winning & Robb M. Stewart, Wall Street Journal 21 August 2012). Besides, there is ‘unarguable evidence’ that Australia's production costs are ‘too expensive’ and ‘too uncompetitive’: mining magnate Gina Rinehart said so in a YouTube video placed on the Sydney Mining Club's website on 5 September 2012. Can this really be so? What is happening to the mining boom and to the people who depend upon it?
Resumo:
Australia is experiencing an unprecedented expansion in mining due to intense demand from Asian economies thirsty for Australia’s non-renewable resources, with over $260 billion worth of capital investment currently in the pipeline (BREE 10). The scale of the present boom coupled with the longer term intensification of competitiveness in the global resources sector is changing the very nature of mining operations in Australia. Of particular note is the increasingly heavy reliance on a non-resident workforce, currently sourced from within Australia but with some recent proposals for projects to draw on overseas guest workers. This is no longer confined, as it once was, to remote, short term projects or to exploration and construction phases of operations, but is emerging as the preferred industry norm. Depending upon project location, workers may either fly-in, fly-out (FIFO) or drive-in, drive-out (DIDO), the critical point being that these operations are frequently undertaken in or near established communities. Drawing primarily on original fieldwork in one of Australia’s mining regions at the forefront of the boom, this paper explores some of the local impacts of new mining regimes, in particular their tendency to undermine collective solidarities, promote social division and fan cultural conflict.