468 resultados para technology support


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Expert knowledge is valuable in many modelling endeavours, particularly where data is not extensive or sufficiently robust. In Bayesian statistics, expert opinion may be formulated as informative priors, to provide an honest reflection of the current state of knowledge, before updating this with new information. Technology is increasingly being exploited to help support the process of eliciting such information. This paper reviews the benefits that have been gained from utilizing technology in this way. These benefits can be structured within a six-step elicitation design framework proposed recently (Low Choy et al., 2009). We assume that the purpose of elicitation is to formulate a Bayesian statistical prior, either to provide a standalone expert-defined model, or for updating new data within a Bayesian analysis. We also assume that the model has been pre-specified before selecting the software. In this case, technology has the most to offer to: targeting what experts know (E2), eliciting and encoding expert opinions (E4), whilst enhancing accuracy (E5), and providing an effective and efficient protocol (E6). Benefits include: -providing an environment with familiar nuances (to make the expert comfortable) where experts can explore their knowledge from various perspectives (E2); -automating tedious or repetitive tasks, thereby minimizing calculation errors, as well as encouraging interaction between elicitors and experts (E5); -cognitive gains by educating users, enabling instant feedback (E2, E4-E5), and providing alternative methods of communicating assessments and feedback information, since experts think and learn differently; and -ensuring a repeatable and transparent protocol is used (E6).

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Life-cycle management (LCM) has been employed in the management of construction projects for many years in order to reduce whole life cost, time, risk and improve the service to owners. However, owing to lack of an effective information sharing platform, the current LCM of construction projects is not effectively used in the construction industry. Based upon the analysis of the information flow of LCM, a virutal prototyping (VP)-based communication and collaboration information platform is proposed. Following this, the platform is customized using DASSAULT sofware. The whole process of implementing the VP-based LCM are also discussed and, from a simple case study, it is demonstrated that the VP-based communication and collaboration information platform is an effective tool to support the LCM of construction projects.

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Queensland University of Technology has a long standing in providing tertiary education and training in ionising radiation. The radiological laboratory plays an important part in this education and training. As radiological applications are diversified in the fields of health and environment, the laboratory provides support for a number of scenarios in the use of experimental situations in radiation detection and radiation protection. This paper discusses the role that a radiological laboratory technician plays in the functionality of a radiological laboratory.

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The field of collaborative health planning faces significant challenges due to the lack of effective information, systems and the absence of a framework to make informed decisions. These challenges have been magnified by the rise of the healthy cities movement, consequently, there have been more frequent calls for localised, collaborative and evidence-driven decision-making. Some studies in the past have reported that the use of decision support systems (DSS) for planning healthy cities may lead to: increase collaboration between stakeholders and the general public, improve the accuracy and quality of the decision-making processes and improve the availability of data and information for health decision-makers. These links have not yet been fully tested and only a handful of studies have evaluated the impact of DSS on stakeholders, policy-makers and health planners. This study suggests a framework for developing healthy cities and introduces an online Geographic Information Systems (GIS)-based DSS for improving the collaborative health planning. It also presents preliminary findings of an ongoing case study conducted in the Logan-Beaudesert region of Queensland, Australia. These findings highlight the perceptions of decision-making prior to the implementation of the DSS intervention. Further, the findings help us to understand the potential role of the DSS to improve collaborative health planning practice.

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In a seminal data mining article, Leo Breiman [1] argued that to develop effective predictive classification and regression models, we need to move away from the sole dependency on statistical algorithms and embrace a wider toolkit of modeling algorithms that include data mining procedures. Nevertheless, many researchers still rely solely on statistical procedures when undertaking data modeling tasks; the sole reliance on these procedures has lead to the development of irrelevant theory and questionable research conclusions ([1], p.199). We will outline initiatives that the HPC & Research Support group is undertaking to engage researchers with data mining tools and techniques; including a new range of seminars, workshops, and one-on-one consultations covering data mining algorithms, the relationship between data mining and the research cycle, and limitations and problems with these new algorithms. Organisational limitations and restrictions to these initiatives are also discussed.

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Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.

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Findings from an Australian case study of adult women expose general, light and basic use of mobile phones. Participants used their mobile phone mainly for coordination and to a lesser extent for practicing intrinsic interactions motivated by emotional support purposes. This paper focuses on social and emotional support over the mobile phone. Though crucial to individuals, emotional support seems to be a neglected area of research among mobile communication studies, all the more so when focusing on adult women. This study addresses this literature gap. The empirical findings are based on a case study of 26 women over 35 years of age residing in one coastal Australian town. The research design included a combination of quantitative and qualitative methods. This paper examines the communication methods adult women use for social and emotional support, and analyses reasons and social implications of this limited intrinsic communication use pattern over the mobile phone.

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In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

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INTRODUCTION: Since the introduction of its QUT ePrints institutional repository of published research outputs, together with the world’s first mandate for author contributions to an institutional repository, Queensland University of Technology (QUT) has been a leader in support of green road open access. With QUT ePrints providing our mechanism for supporting the green road to open access, QUT has since then also continued to expand its secondary open access strategy supporting gold road open access, which is also designed to assist QUT researchers to maximise the accessibility and so impact of their research. ---------- METHODS: QUT Library has adopted the position of selectively supporting true gold road open access publishing by using the Library Resource Allocation budget to pay the author publication fees for QUT authors wishing to publish in the open access journals of a range of publishers including BioMed Central, Public Library of Science and Hindawi. QUT Library has been careful to support only true open access publishers and not those open access publishers with hybrid models which “double dip” by charging authors publication fees and libraries subscription fees for the same journal content. QUT Library has maintained a watch on the growing number of open access journals available from gold road open access publishers and their increased rate of success as measured by publication impact. ---------- RESULTS: This paper reports on the successes and challenges of QUT’s efforts to support true gold road open access publishers and promote these publishing strategy options to researchers at QUT. The number and spread of QUT papers submitted and published in the journals of each publisher is provided. Citation counts for papers and authors are also presented and analysed, with the intention of identifying the benefits to accessibility and research impact for early career and established researchers.---------- CONCLUSIONS: QUT Library is eager to continue and further develop support for this publishing strategy, and makes a number of recommendations to other research institutions, on how they can best achieve success with this strategy.

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INTRODUCTION: Queensland University of Technology (QUT) Library is partnering with High Performance Computing (HPC) services and the Division of Research and Commercialisation to develop and deliver a range of integrated research support services and systems designed to enhance the research capabilities of the University. Existing and developing research support services include - support for publishing strategies including open access, bibliographic citation and ranking services, research data management, use of online collaboration tools, online survey tools, quantitative and qualitative data analysis, content management and storage solutions. In order to deliver timely and effective research referral and support services, it is imperative that library staff maintain their awareness of, and develop expertise in new eResearch methods and technologies. ---------- METHODS: In 2009/10 QUT Library initiated an online survey for support staff and researchers and a series of focus groups for researchers aimed at gaining a better understanding of current and future eresearch practices and skills. These would better inform the development of a research skills training program and the development of new research support services. The Library and HPC also implemented a program of seminars and workshops designed to introduce key library staff to a broad range of eresearch concepts and technologies. Feedback was obtained after each training session. A number of new services were implemented throughout 2009 and 2010. ---------- RESULTS: Key findings of the survey and focus groups are related to the development of the staff development program. Feedback from program attendees is provided and evaluated. The staff development program is assessed in terms of its success to support the implementation of new research support services. --------- CONCLUSIONS QUT Library has embarked on an ambitious awareness and skills development program to assist Library staff transition a period of rapid change and broadening scope for the Library. Successes and challenges of the program are discussed. A number of recommendations are made in retrospect and also looking forward to the future training needs of Library staff to support the University’s future research goals.