922 resultados para Government Data


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longitudinal study of data modelling across grades 1-3. The activity engaged children in designing, implementing, and analysing a survey about their new playground. 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. The core components of data modelling addressed here are children’s structuring and representing of data, with a focus on their display of metarepresentational competence (diSessa, 2004). Such competence includes students’ abilities to invent or design a variety of new representations, explain their creations, understand the role they play, and critique and compare the adequacy of representations. Reported here are the ways in which the children structured and represented their data, the metarepresentational competence displayed, and links between their metarepresentational competence and conceptual competence.

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Implementing educational reform requires partnerships, and university-school collaborations in the form of investigative and experimental projects can aim to determine the practicalities of reform. However, there are funded projects that do not achieve intended outcomes. In the context of a new reform initiative in education, namely, science, technology, engineering and mathematics (STEM) education, this article explores the management of a government-funded project. In a university school partnership for STEM education, how can leadership be distributed for achieving project outcomes? Participants included university personnel from different STEM areas, school teachers and school executives. Data collected included observations, interviews, resource materials, and video and photographic images. Findings indicated that leadership roles were distributed and selfactivated by project partners according to their areas of expertise and proximal activeness to the project phases, that is: (1) establishing partnerships; (2) planning and collaboration; (3) project implementation; and (4) project evaluation and further initiatives. Leadership can be intentional and unintentional within project phases, and understanding how leadership can be distributed and selfactivated more purposefully may aid in generating more expedient project outcomes.

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Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

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All Australian governments are significantly increasing the use of contracted community service provision through not for profit (NFP) organisations. These transactions occur through grant arrangements which take the form of standard contracts or deeds rather than drawing on statutory authority. Government inquiries bodies have consistently reported and raised concerns about the fairness of such standard grant contract terms, but failed to provide any mechanism whereby fairness can be assured. The Productivity Commission has suggested that the resulting poor relationship results in inappropriate risk transfer, micro-management, disincentives to innovate and poor service provision. This paper develops and tests a fairness measure based on the principles of the Australian Consumer Law which legislates fairness protections for standard consumer contracts.  

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BACKGROUND The engineering profession in Australia has failed to attract young women for the last decade or so despite all the effort that have gone into promoting engineering as a preferred career choice for girls. It is a missed opportunity for the profession to flourish as a heterogeneous team. Many traditional initiatives and programs have failed to make much impact or at best incremental improvement into attracting and retaining more women in the profession. The reasons why girls and young women in most parts of the world show little interest in engineering haven't changed, despite all the efforts to address them, the issue proposed here in this paper is with the perceptions of engineering in the community and the confidence to pursue it. This gender imbalance is detrimental for the engineering profession, and hence an action-based intervention strategy was devised by the Women in Engineering Qld Chapter of Engineers Australia in 2012 to change the perceptions of school girls by redesigning the engagement strategy and key messages. As a result, the “Power of Engineering Inc” (PoE) was established as a not-for-profit organisation, and is a collaborative effort between government, schools, universities, and industry. This paper examines a case study in changing the perceptions of year 9 and 10 school girls towards an engineering career. PURPOSE To evaluate and determine the effectiveness of an intervention in changing the perceptions of year 9 and 10 school girls about engineering career options, but specifically, “What were their perceptions of engineering before today and have those perceptions changed?” DESIGN/METHOD The inaugural Power of Engineering (PoE) event was held on International Women’s Day, Thursday 8 March 2012 and was attended by 131 high school female students (year 9 and 10) and their teachers. The key message of the day was “engineering gives you the power to change the world”. A questionnaire was conducted with the participating high school female students, collecting both quantitative and qualitative data. The survey instrument has not been validated. RESULTS The key to the success of the event was as a result of collaboration between all participants involved and the connection created between government, schools, universities and industry. Of the returned surveys (109 of 131), 91% of girls would now consider a career in engineering and 57% who had not considered engineering before the day would now consider a career in engineering. Data collected found significant numbers of negative and varying perceptions about engineering careers prior to the intervention. CONCLUSIONS The evidence in this research suggests that the intervention assisted in changing the perceptions of year 9 and 10 female school students towards engineering as a career option. Whether this intervention translates into actual career selection and study enrolment is to be determined. In saying this, the evidence suggests that there is a critical and urgent need for earlier interventions prior to students selecting their subjects for year 11 and 12. This intervention could also play its part in increasing the overall pool of students engaged in STEM education.

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In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is also proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.

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This paper presents an input-orientated data envelopment analysis (DEA) framework which allows the measurement and decomposition of economic, environmental and ecological efficiency levels in agricultural production across different countries. Economic, environmental and ecological optimisations search for optimal input combinations that minimise total costs, total amount of nutrients, and total amount of cumulative exergy contained in inputs respectively. The application of the framework to an agricultural dataset of 30 OECD countries revealed that (i) there was significant scope to make their agricultural production systemsmore environmentally and ecologically sustainable; (ii) the improvement in the environmental and ecological sustainability could be achieved by being more technically efficient and, even more significantly, by changing the input combinations; (iii) the rankings of sustainability varied significantly across OECD countries within frontier-based environmental and ecological efficiency measures and between frontier-based measures and indicators.

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Mobile telecommunications have become a key lifestyle and technological trend of the twenty first century. In the context of increased urbanism and pressure on cites for citizen engagement for the purpose of creating good public places the potential of these technologies raises critical questions for planning professionals. Even though technology has become integral to all functions within our urban environment, little is known about perceptions and relationship between urban planners and the ubiquitous, ever-present digital layer of urban data and information. This paper explores this issue, via three focus groups and an additional follow-up interview with planners from local and state government, education and private sector. This paper explores the issues of integrating information and communication technologies into planning practice and the affordances that these technologies offer for community consultation and placemaking.

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The ability to forecast machinery health is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models which attempt to forecast machinery health based on condition data such as vibration measurements. This paper demonstrates how the population characteristics and condition monitoring data (both complete and suspended) of historical items can be integrated for training an intelligent agent to predict asset health multiple steps ahead. The model consists of a feed-forward neural network whose training targets are asset survival probabilities estimated using a variation of the Kaplan–Meier estimator and a degradation-based failure probability density function estimator. The trained network is capable of estimating the future survival probabilities when a series of asset condition readings are inputted. The output survival probabilities collectively form an estimated survival curve. Pump data from a pulp and paper mill were used for model validation and comparison. The results indicate that the proposed model can predict more accurately as well as further ahead than similar models which neglect population characteristics and suspended data. This work presents a compelling concept for longer-range fault prognosis utilising available information more fully and accurately.

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Cost implications related to the physical resources such as land and building in organisation is significant. Management entity of government or private sectors has often ignored the importance and the contribution gained from the physical resources towards their organisation. This source is a precious asset that can generate income if properly managed. This paper aims to explore the current trends in space management internationally, both from the government and private sector perspectives. A case study is conducted to study the level of effectiveness of space management in one of the government institutions in Malaysia. The findings from the case study will be compared with the current international trend of space management. The study will enrich the current understanding of space management in government properties, as well as to compare the level of space management effectiveness of government properties in Malaysia with the international trends and proposed suggestions to improve current practices of space management of Malaysian government’s properties. Keywords:

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Our paper approaches Twitter through the lens of “platform politics” (Gillespie, 2010), focusing in particular on controversies around user data access, ownership, and control. We characterise different actors in the Twitter data ecosystem: private and institutional end users of Twitter, commercial data resellers such as Gnip and DataSift, data scientists, and finally Twitter, Inc. itself; and describe their conflicting interests. We furthermore study Twitter’s Terms of Service and application programming interface (API) as material instantiations of regulatory instruments used by the platform provider and argue for a more promotion of data rights and literacy to strengthen the position of end users.

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The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.

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This paper describes a generalised linear mixed model (GLMM) approach for understanding spatial patterns of participation in population health screening, in the presence of multiple screening facilities. The models presented have dual focus, namely the prediction of expected patient flows from regions to services and relative rates of participation by region- service combination, with both outputs having meaningful implications for the monitoring of current service uptake and provision. The novelty of this paper lies with the former focus, and an approach for distributing expected participation by region based on proximity to services is proposed. The modelling of relative rates of participation is achieved through the combination of different random effects, as a means of assigning excess participation to different sources. The methodology is applied to participation data collected from a government-funded mammography program in Brisbane, Australia.