929 resultados para scientific computation
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This paper will report on the way expert science teachers’ conceive of scientific literacy in their classrooms, the values related to scientific literacy they hold and how this conception and the underpinning values affect their teaching practice. Three perceived expert science teachers who teach both at senior and middle school levels and across the range of sub-disciplines (one senior biology, one senior chemistry and one senior physics) were interviewed about their understanding of scientific literacy and how this influenced their teaching practice. The three teachers were video recorded teaching a junior science class and a senior science class. The data were analysed to identify values that underpin their conceptions of science and science education. The analysis focussed on the matching of the verbalised conceptions and values with their practice of teaching science. This paper will report on these data.
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Objectives: To quantify randomness and cost when choosing health and medical research projects for funding. Design: Analysis of retrospective data from grant review panels. Setting: The National Health & Medical Research Council of Australia. Participants/Data: All panel members’ scores for grant proposals submitted in 2009. Main outcome measure: The proportion of grant proposals that were always, sometimes and never funded after accounting for random variability arising from variation in panel members’ scores; the cost-effectiveness of different size assessment panels. Results: 59% of 620 funded grants were sometimes not funded when random variability was accounted for. Only 9% of grant proposals were always funded, 61% were never funded and 29% were sometimes funded. The extra cost per grant effectively funded from the most effective system was $18,541. Conclusions: Allocating funding for scientific research in health and medicine is costly and somewhat random. There are many useful research questions to be addressed that could improve current processes.
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Intensive Case Management (ICM) is widely claimed to be an evidence-based and cost effective program for people with high levels of disability as a result of mental illness. However, the findings of recent randomized controlled trials comparing ICM with ‘usual services’ suggest that both clinical and cost effectiveness of ICM may be weakening. Possible reasons for this, including fidelity of implementation, researcher allegiance effects and changes in the wider service environment within which ICM is provided, are considered. The implications for service delivery and research are discussed.
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Scientific visualisations such as computer-based animations and simulations are increasingly a feature of high school science instruction. Visualisations are adopted enthusiastically by teachers and embraced by students, and there is good evidence that they are popular and well received. There is limited evidence, however, of how effective they are in enabling students to learn key scientific concepts. This paper reports the results of a quantitative study conducted in Australian physics and chemistry classrooms. In general there was no statistically significant difference between teaching with and without visualisations, however there were intriguing differences around student sex and academic ability.
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Visual modes of representation have always been very important in science and science education. Interactive computer-based animations and simulations offer new visual resources for chemistry education. Many studies have shown that students enjoy learning with visualisations but few have explored how learning outcomes compare when teaching with or without visualisations. This study employs a quasi-experimental crossover research design and quantitative methods to measure the educational effectiveness - defined as level of conceptual development on the part of students - of using computer-based scientific visualisations versus teaching without visualisations in teaching chemistry. In addition to finding that teaching with visualisations offered outcomes that were not significantly different from teaching without visualisations, the study also explored differences in outcomes for male and female students, students with different learning styles (visual, aural, kinesthetic) and students of differing levels of academic ability.
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Enormous amounts of money and energy are being devoted to the development, use and organisation of computer-based scientific visualisations (e.g. animations and simulations) in science education. It seems plausible that visualisations that enable students to gain visual access to scientific phenomena that are too large, too small or occur too quickly or too slowly to be seen by the naked eye, or to scientific concepts and models, would yield enhanced conceptual learning. When the literature is searched, however, it quickly becomes apparent that there is a dearth of quantitative evidence for the effectiveness of scientific visualisations in enhancing students’ learning of science concepts. This paper outlines an Australian project that is using innovative research methodology to gather evidence on this question in physics and chemistry classrooms.
Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion
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This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.
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Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.
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In order to understand better the role of affect in learning about socio-scientificissues (SSI), this study investigated Year 12 students’ emotional arousal as they participated in an online writing-to-learn science project about the socio-scientific issue of biosecurity. Students wrote a series of hybridised scientific narratives, or BioStories, that integrate scientific information about biosecurity with narrative storylines, and uploaded these to a dedicated website. Throughout their participation in the project, students recorded their emotional responses to the various activities (N=50). Four case students were also video recorded during selected science lessons as they researched, composed and uploaded their BioStories for peer review. Analysis of these data, as well as interview data obtained from the case students, revealed that pride, strength, determination, interest and alertness were among the positive emotions most strongly elicited by the project. These emotions reflected students’ interest in learning about a new socio-scientific issue, and their enhanced feelings of self-efficacy in successfully writing hybridised scientific narratives in science. The results of this study suggest that the elicitation of positive emotional responses as students engage in hybridised writing about SSI with strong links to environmental education, such as biosecurity, can be valuable in engaging students in education for sustainability.
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This paper reports one aspect of a study of 28 young adults (18–26 years) engaging with the uncertain (contested) science of a television news report about recent research into mobile phone health risks. The aim of the study was to examine these young people’s ‘accounts of scientific knowledge’ in this context. Seven groups of friends responded to the news report, initially in focus group discussions. Later in semi-structured interviews they elaborated their understanding of the nature of science through their explanations of the scientists’ disagreement and described their mobile phone safety risk assessments. This paper presents their accounts in terms of their views of the nature of science and their concept understanding. Discussions were audio-recorded then analysed by coding the talk in terms of issues raised, which were grouped into themes and interpreted in terms of a moderate social constructionist theoretical framing. In this context, most participants expressed a ‘common sense’ view of the nature of science, describing it as an atheoretical, technical procedure of scientists testing their personal opinions on the issue, subject to the influence of funding sponsors. The roles of theory and data interpretation were largely ignored. It is argued that the nature of science understanding is crucial to engagement with contemporary socioscientific issues, particularly the roles of argumentation, theory, data interpretation, and the distinction of science from common sense. Implications for school science relate primarily to nature of science teaching and the inclusion of socioscientific issues in school science curricula. Future research directions are considered.
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In this paper, we propose three meta-heuristic algorithms for the permutation flowshop (PFS) and the general flowshop (GFS) problems. Two different neighborhood structures are used for these two types of flowshop problem. For the PFS problem, an insertion neighborhood structure is used, while for the GFS problem, a critical-path neighborhood structure is adopted. To evaluate the performance of the proposed algorithms, two sets of problem instances are tested against the algorithms for both types of flowshop problems. The computational results show that the proposed meta-heuristic algorithms with insertion neighborhood for the PFS problem perform slightly better than the corresponding algorithms with critical-path neighborhood for the GFS problem. But in terms of computation time, the GFS algorithms are faster than the corresponding PFS algorithms.
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Background Scientific research is an essential component in guiding improvements in health systems. There are no studies examining the Sri Lankan medical research output at international level. The present study evaluated the Sri Lankan research performance in medicine as reflected by the research publications output between years 2000-2009. Methods This study was based on Sri Lankan medical research publication data, retrieved from the SciVerse Scopus® from January 2000 to December 2009. The process of article selection was as follows: Affiliation - 'Sri Lanka' or 'Ceylon', Publication year - 'January 2000 to December 2009' and Subject area - 'Life and Health Sciences'. The articles identified were classified according to disease, medical speciality, institutions, major international collaborators, authors and journals. Results Sri Lanka's cumulative medical publications output between years 2000-2009 was 1,740 articles published in 160 different journals. The average annual publication growth rate was 9.1%. Majority of the articles were published in 'International' (n = 950, 54.6%) journals. Most articles were descriptive studies (n = 611, 35.1%), letters (n-345, 19.8%) and case reports (n = 311, 17.9%). The articles were authored by 148 different Sri Lankan authors from 146 different institutions. The three most prolific local institutions were Universities of; Colombo (n = 547), Kelaniya (n = 246) and Peradeniya (n = 222). Eighty four countries were found to have published collaborative papers with Sri Lankan authors during the last decade. UK was the largest collaborating partner (n = 263, 15.1%). Malaria (n = 75), Diabetes Mellitus (n = 55), Dengue (n = 53), Accidental injuries (n = 42) and Lymphatic filariasis (n = 40) were the major diseases studied. The 1,740 publications were cited 9,708 times, with an average citation of 5.6 per paper. The most cited paper had 203 citations, while there were 597 publications with no citations. The Sri Lankan authors' contribution to the global medical research output during the last decade was only 0.086%. Conclusion The Sri Lankan medical research output during the last decade is only a small fraction of the global research output. There it is a necessity to setup an enabling environment for research, with a proper vision, support, funds and training. In addition, collaborations across the region need to be strengthened to face common regional health challenges. Keywords: Sri Lanka, Medical research, Publication, Analysis
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This thesis provides a query model suitable for context sensitive access to a wide range of distributed linked datasets which are available to scientists using the Internet. The model is designed based on scientific research standards which require scientists to provide replicable methods in their publications. Although there are query models available that provide limited replicability, they do not contextualise the process whereby different scientists select dataset locations based on their trust and physical location. In different contexts, scientists need to perform different data cleaning actions, independent of the overall query, and the model was designed to accommodate this function. The query model was implemented as a prototype web application and its features were verified through its use as the engine behind a major scientific data access site, Bio2RDF.org. The prototype showed that it was possible to have context sensitive behaviour for each of the three mirrors of Bio2RDF.org using a single set of configuration settings. The prototype provided executable query provenance that could be attached to scientific publications to fulfil replicability requirements. The model was designed to make it simple to independently interpret and execute the query provenance documents using context specific profiles, without modifying the original provenance documents. Experiments using the prototype as the data access tool in workflow management systems confirmed that the design of the model made it possible to replicate results in different contexts with minimal additions, and no deletions, to query provenance documents.
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In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.
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Unmanned Aerial Vehicles (UAVs) industry is a fast growing sector. Nowadays, the market offers numerous possibilities for off-the-shelf UAVs such as quadrotors or fixed-wings. Until UAVs demonstrate advance capabilities such as autonomous collision avoidance they will be segregated and restricted to flight in controlled environments. This work presents a visual fuzzy servoing system for obstacle avoidance using UAVs. To accomplish this task we used the visual information from the front camera. Images are processed off-board and the result send to the Fuzzy Logic controller which then send commands to modify the orientation of the aircraft. Results from flight test are presented with a commercial off-the-shelf platform.