922 resultados para Government Data
Resumo:
Background Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. Methods In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns: (a) a gene set, and (b) the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. Conclusions This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.
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miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star
Resumo:
The IEEE Subcommittee on the Application of Probability Methods (APM) published the IEEE Reliability Test System (RTS) [1] in 1979. This system provides a consistent and generally acceptable set of data that can be used both in generation capacity and in composite system reliability evaluation [2,3]. The test system provides a basis for the comparison of results obtained by different people using different methods. Prior to its publication, there was no general agreement on either the system or the data that should be used to demonstrate or test various techniques developed to conduct reliability studies. Development of reliability assessment techniques and programs are very dependent on the intent behind the development as the experience of one power utility with their system may be quite different from that of another utility. The development and the utilization of a reliability program are, therefore, greatly influenced by the experience of a utlity and the intent of the system manager, planner and designer conducting the reliability studies. The IEEE-RTS has proved to be extremely valuable in highlighting and comparing the capabilities (or incapabilities) of programs used in reliability studies, the differences in the perception of various power utilities and the differences in the solution techniques. The IEEE-RTS contains a reasonably large power network which can be difficult to use for initial studies in an educational environment.
Resumo:
The IEEE Reliability Test System (RTS) developed by the Application of Probability Method Subcommittee has been used to compare and test a wide range of generating capacity and composite system evaluation techniques and subsequent digital computer programs. A basic reliability test system is presented which has evolved from the reliability education and research programs conducted by the Power System Research Group at the University of Saskatchewan. The basic system data necessary for adequacy evaluation at the generation and composite generation and transmission system levels are presented together with the fundamental data required to conduct reliability-cost/reliability-worth evaluation
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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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This study considers patterns of political participation in Australia in the early 21st Century, using recent data from the Australian Election Study. The paper reassesses how Australia fits within broader patterns of political participation and investigates major predictors of participation in Australia to see how these have or have not changed in a globalised era that has brought new challenges. Factors considered include socio-demographic variables, such as education, age, gender, birthplace and place of residence and also attitudinal orientations towards politics, such as political interest, efficacy and trust. The paper pays particular attention to those who have moved to Australia from other countries. One of the most important findings is that immigrants show little or no sign of any participatory disadvantage and indeed tend to participate more than the Australian-born in some modes of participation, such as campaign activities. The analysis also identifies a clear participatory divide within a number of socio-demographic groups in use of the internet for gaining election information.
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Research indicates that enrolments in separate special educational settings for students with disruptive behaviour have increased in a number of educational jurisdictions internationally. Recent analysis of school enrolment data has identified a similar increase in the New South Wales (NSW) government school sector; however, questions have been raised as to their use and effectiveness. To situate the NSW experiment with behaviour schools in a broader context, the paper begins with a review of the international research literature. This is followed by a discussion of the NSW experience with the aim of identifying parallels and gaps in the research. The paper concludes by outlining important questions and directions for research to better understand and improve the educational experiences and outcomes of disruptive disaffected students in Australia’s largest school system.
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The last few decades have witnessed a broad international movement towards the development of inclusive schools through targeted special education funding and resourcing policies. Student placement statistics are often used as a barometer of policy success but they may also be an indication of system change. In this paper, trends in student enrolments from the Australian state of New South Wales are considered in an effort to understand what effect inclusive education has had in this particular region of the world.
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This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.
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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, 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. Data reliability issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. Participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data reliability has become an urgent demand. This study 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 propose to design a reputation framework to enhance data reliability and also investigate some critical elements that should be aware of during developing and designing new reputation systems.
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A significant gap exists in the Australian research literature on the disproportionate over-representation of minority groups in special education. The aim of this paper is to make a contribution to the research evidence-base by sketching an outline of the issue as it presents in Australia’s largest education system in the state of New South Wales. Findings from this research show that Indigenous students are equally represented in special schools enrolling students with autism, physical, sensory, and intellectual disabilities, but significantly over-represented in special schools enrolling students under the categories of emotional disturbance, behaviour disorder and juvenile detention. Factors that might influence the disproportionate over-representation of Indigenous children and young people are discussed, and based on these observations, some practical implications for policy and practice are provided.
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Education in the 21st century demands a model for understanding a new culture of learning in the face of rapid change, open access data and geographical diversity. Teachers no longer need to provide the latest information because students themselves are taking an active role in peer collectives to help create it. This paper examines, through an Australian case study entitled ‘Design Minds’, the development of an online design education platform as a key initiative to enact a government priority for state-wide cultural change through design-based curriculum. Utilising digital technology to create a supportive community, ‘Design Minds’ recognises that interdisciplinary learning fostered through engagement will empower future citizens to think, innovate, and discover. This paper details the participatory design process undertaken with multiple stakeholders to create the platform. It also outlines a proposed research agenda for future measurement of its value in creating a new learning culture, supporting regional and remote communities, and revitalising frontline services. It is anticipated this research will inform ongoing development of the online platform, and future design education and research programs in K-12 schools in Australia.
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Open the sports or business section of your daily newspaper, and you are immediately bombarded with an array of graphs, tables, diagrams, and statistical reports that require interpretation. Across all walks of life, the need to understand statistics is fundamental. Given that our youngsters’ future world will be increasingly data laden, scaffolding their statistical understanding and reasoning is imperative, from the early grades on. The National Council of Teachers of Mathematics (NCTM) continues to emphasize the importance of early statistical learning; data analysis and probability was the Council’s professional development “Focus of the Year” for 2007–2008. We need such a focus, especially given the results of the statistics items from the 2003 NAEP. As Shaughnessy (2007) noted, students’ performance was weak on more complex items involving interpretation or application of items of information in graphs and tables. Furthermore, little or no gains were made between the 2000 NAEP and the 2003 NAEP studies. One approach I have taken to promote young children’s statistical reasoning is through data modeling. Having implemented in grades 3 –9 a number of model-eliciting activities involving working with data (e.g., English 2010), I observed how competently children could create their own mathematical ideas and representations—before being instructed how to do so. I thus wished to introduce data-modeling activities to younger children, confi dent that they would likewise generate their own mathematics. I recently implemented data-modeling activities in a cohort of three first-grade classrooms of six year- olds. I report on some of the children’s responses and discuss the components of data modeling the children engaged in.
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Student satisfaction data has been collected on a national basis in Australia since 1972. In recent years this data has been used by federal government agencies to allocate funding, and by students in selecting their universities of choice. The purpose of this paper is to present the findings of an action research project designed to identify and implement unit improvement initiatives over a three year period for an underperforming unit. This research utilises student survey data and teacher reflections to identify areas of unit improvement, with a view to aligning learning experiences, teaching and assessment to learning outcomes and improved student satisfaction. This research concludes that whilst a voluntary student survey system may be imperfect, it nevertheless provides important data that can be utilised to the benefit of the unit, learning outcomes and student satisfaction ratings, as well as wider course related outcomes. Extrapolation of these findings is recommended to other underperforming units.
Resumo:
This study seeks to answer the question of “why is policy innovation in Indonesia, in particular reformed state asset management laws and regulations, stagnant?” through an empirical and qualitative approach, identifying and exploring potential impeding influences to the full and equal implementation of said laws and regulations. The policies and regulations governing the practice of state asset management has emerged as an urgent question among many countries worldwide (Conway, 2006; Dow, Gillies, Nichols, & Polen, 2006; Kaganova, McKellar, & Peterson, 2006; McKellar, 2006b) for there is heightened awareness of the complex and crucial role that state assets play in public service provision. Indonesia is an example of such country, introducing a ‘big-bang’ reform in state asset management laws, policies, regulations, and technical guidelines. Two main reasons propelled said policy innovation: a) world-wide common challenges in state asset management practices - such as incomplete information system, accountability, and governance adherence/conceptualisation (Kaganova, McKellar and Peterson 2006); and b) unfavourable state assets audit results in all regional governments across Indonesia. The latter reasoning is emphasised, as the Indonesian government admits to past neglect in ensuring efficiency and best practice in its state asset management practices. Prior to reform there was euphoria of building and developing state assets and public infrastructure to support government programs of the day. Although this euphoria resulted in high growth within Indonesia, there seems to be little attention paid to how state assets bought/built is managed. Up until 2003-2004 state asset management is considered to be minimal; inventory of assets is done manually, there is incomplete public sector accounting standards, and incomplete financial reporting standards (Hadiyanto 2009). During that time transparency, accountability, and maintenance state assets was not the main focus, be it by the government or the society itself (Hadiyanto 2009). Indonesia exemplified its enthusiasm in reforming state asset management policies and practices through the establishment of the Directorate General of State Assets in 2006. The Directorate General of State Assets have stressed the new direction that it is taking state asset management laws and policies through the introduction of Republic of Indonesia Law Number 38 Year 2008, which is an amended regulation overruling Republic of Indonesia Law Number 6 Year 2006 on Central/Regional Government State Asset Management (Hadiyanto, 2009c). Law number 38/2008 aims to further exemplify good governance principles and puts forward a ‘the highest and best use of assets’ principle in state asset management (Hadiyanto, 2009a). The methodology of this study is that of qualitative case study approach, with a triangulated data collection method of document analysis (all relevant state asset management laws, regulations, policies, technical guidelines, and external audit reports), semi-structured interviews, and on-site observation. Empirical data of this study involved a sample of four Indonesian regional governments and 70 interviews, performed during January-July 2010. The analytical approach of this study is that of thematic analysis, in an effort to identify common influences and/or challenges to policy innovation within Indonesia. Based on the empirical data of this study specific impeding influences to state asset management reform is explored, answering the question why innovative policy implementation is stagnant. An in-depth analysis of each influencing factors to state asset management reform, and the attached interviewee’s opinions for each factor, suggests the potential of an ‘excuse rhetoric’; whereby the influencing factors identified are a smoke-screen, or are myths that public policy makers and implementers believe in; as a means to explain innovative policy stagnancy. This study offers insights to Indonesian policy makers interested in ensuring the conceptualisation and full implementation of innovative policies, particularly, although not limited to, within the context of state asset management practices.