991 resultados para digitization, statistics, Google Analytics
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“World food security … is at its lowest in half a century,” wrote Julian Cribb FTSE, a wellknown consultant in science communication and founding editor of www.sciencealert. com.au in the lead article in the 2008 ATSE Focus magazine issue entitled “Food for the world: the nation’s challenge”. Food security continues to be a key national and international concern and it is pleasing to see this issue of Focus again exploring aspects of the topic with the aim of continuing to raise awareness of issues and influencing relevant policy decisions. Statistics (or statistical science, more broadly) has been critical to the information and decision-making value chain needed to optimise agriculture and the food supply chain. The key steps are most often addressed by multidisciplinary research groups including statisticians in collaboration with life and physical scientists, agri-industry personnel and other relevant stakeholders.
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Australia has a significantly higher suicide rate than England. Rather than accepting that this ‘statistical fact’ is a direct reflection of some positivist truth, this paper begins with the premise that how suicide is counted depends upon what counts as suicide. This study involves semi-structured interviews with coroners both in Australia and England, as well as observations at inquests. Important differences between the two coronial systems include: first, quite different logics of operation; second, the burden of proof for reaching a finding of suicide is significantly higher in England; and third, the presence of family members at English inquests results in far greater pressure being brought to bear upon coroners. These combined factors result in a reduced likelihood of English coroners reaching a finding of suicide. The conclusions are twofold. First, this research supports existing criticisms of comparative suicide statistics. Second, this research adds theoretical weight to criticisms of positivist analyses of social phenomena.
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Heterogeneous health data is a critical issue when managing health information for quality decision making processes. In this paper we examine the efficient aggregation of lifestyle information through a data warehousing architecture lens. We present a proof of concept for a clinical data warehouse architecture that enables evidence based decision making processes by integrating and organising disparate data silos in support of healthcare services improvement paradigms.
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Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.
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A new Bachelor of Science (BSc) course was introduced at Queensland University of Technology (QUT) in 2013 and focused on inquiry-based, collaborative and active learning. Two of the first year units required that students carry out a group poster assessment task. This poster provides a preliminary evaluation from an academic staff perspective of the assessment approach used, whereby students created digital posters to utilise the affordances of new learning spaces. The digital posters approach was first introduced to a group of academic staff from the Science and Engineering Faculty (SEF) in 2012 during a professional development program to explicitly develop skills and shared understandings of teaching in collaborative learning spaces (Steel & Andrews, 2012). Considerations were given to the pedagogical requirements of a poster assessment task, the affordances of the learning space and an identification of possible benefits of using Google Sites to create digital posters. Positive feedback from this group (as highlighted in the quotes shown) and subsequent approval from unit coordinators for two of the new first year BSc units meant that the approach was adopted for Semester 1, 2013 with approximately 360 students in each unit.
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Yield in cultivated cotton (Gossypium spp.) is affected by the number and distribution of fibres initiated on the seed surface but, apart from simple statistical summaries, little has been done to assess this phenotype quantitatively. Here we use two types of spatial statistics to describe and quantify differences in patterning of cotton ovule fibre initials (FI). The following five different species of Gossypium were analysed: G. hirsutum L., G. barbadense L., G. arboreum, G. raimondii Ulbrich. and G. trilobum (DC.) Skovsted. Scanning electron micrographs of FIs were taken on the day of anthesis. Cell centres for fibre and epidermal cells were digitised and analysed by spatial statistics methods appropriate for marked point processes and tessellations. Results were consistent with previously published reports of fibre number and spacing. However, it was shown that the spatial distributions of FIs in all of species examined exhibit regularity, and are not completely random as previously implied. The regular arrangement indicates FIs do not appear independently of each other and we surmise there may be some form of mutual inhibition specifying fibre-initial development. It is concluded that genetic control of FIs differs from that of stomata, another well studied plant idioblast. Since spatial statistics show clear species differences in the distribution of FIs within this genus, they provide a useful method for phenotyping cotton. © CSIRO 2007.
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Background Whilst waiting for patients undergoing surgery, a lack of information regarding the patient’s status and the outcome of surgery, can contribute to the anxiety experienced by family members. Effective strategies for providing information to families are therefore required. Objectives To synthesize the best available evidence in relation to the most effective information-sharing interventions to reduce anxiety for families waiting for patients undergoing an elective surgical procedure. Inclusion criteria Types of participants All studies of family members over 18 years of age waiting for patients undergoing an elective surgical procedure were included, including those waiting for both adult and pediatric patients. Types of intervention All information-sharing interventions for families of patients undergoing an elective surgical procedure were eligible for inclusion in the review. Types of studies All randomized controlled trials (RCTs) quasi-experimental studies, case-controlled and descriptive studies, comparing one information-sharing intervention to another or to usual care were eligible for inclusion in the review. Types of outcomes Primary outcome: The level of anxiety amongst family members or close relatives whilst waiting for patients undergoing surgery, as measured by a validated instrument such as the S-Anxiety portion of the State-Trait Anxiety Inventory (STAI). Secondary outcomes: Family satisfaction and other measurements that may be considered indicators of stress and anxiety, such as mean arterial pressure (MAP) and heart rate. Search strategy A comprehensive search, restricted to English language only, was undertaken of the following databases from 1990 to May 2013: Medline, CINAHL, EMBASE, ProQuest, Web of Science, PsycINFO, Scopus, Dissertation and Theses PQDT (via ProQuest), Current Contents, CENTRAL, Google Scholar, OpenGrey, Clinical Trials, Science.gov, Current Controlled Trials and National Institute for Clinical Studies (NHMRC). Methodological quality Two independent reviewers critically appraised retrieved papers for methodological quality using the standardized critical appraisal instruments for randomized controlled trials and descriptive studies from the Joanna Briggs Institute Meta Analysis of Statistics Assessment and Review Instruments (JBI-MAStARI). Data extraction Two independent reviewers extracted data from included papers using a customized data extraction form. Data synthesis Statistical pooling was not possible, mainly due to issues with data reporting in two of the studies, therefore the results are presented in narrative form. Results Three studies with a total of 357 participants were included in the review. In-person reporting to family members was found to be effective in comparison with usual care in which no reports were provided. Telephone reporting was also found to be effective at reducing anxiety, in comparison with usual care, although not as effective as in-person reporting. The use of paging devices to keep family members informed were found to increase, rather than decrease anxiety. Conclusions Due to the lack of high quality research in this area, the strength of the conclusions are limited. It appears that in-person and telephone reporting to family members decreases anxiety, however the use of paging devices increases anxiety.
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Three core components in developing children’s understanding and appreciation of data — establish a context, pose and answer statistical questions, represent and interpret data — lay the foundation for the fourth component: use data to enhance existing context.
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We present a Connected Learning Analytics (CLA) toolkit, which enables data to be extracted from social media and imported into a Learning Record Store (LRS), as defined by the new xAPI standard. Core to the toolkit is the notion of learner access to their own data. A number of implementational issues are discussed, and an ontology of xAPI verb/object/activity statements as they might be unified across 7 different social media and online environments is introduced. After considering some of the analytics that learners might be interested in discovering about their own processes (the delivery of which is prioritised for the toolkit) we propose a set of learning activities that could be easily implemented, and their data tracked by anyone using the toolkit and a LRS.
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Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.
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The majority of sugar mill locomotives are equipped with GPS devices from which locomotive position data is stored. Locomotive run information (e.g. start times, run destinations and activities) is electronically stored in software called TOTools. The latest software development allows TOTools to interpret historical GPS information by combining this data with run information recorded in TOTools and geographic information from a GIS application called MapInfo. As a result, TOTools is capable of summarising run activity details such as run start and finish times and shunt activities with great accuracy. This paper presents 15 reports developed to summarise run activities and speed information. The reports will be of use pre-season to assist in developing the next year's schedule and for determining priorities for investment in the track infrastructure. They will also be of benefit during the season to closely monitor locomotive run performance against the existing schedule.
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One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.