387 resultados para Data Generation

em Queensland University of Technology - ePrints Archive


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The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

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This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

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The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of global warming on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since all building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. Based on a review of the existing weather data generation models, this paper presents an effective method to generate approximate future hourly weather data suitable for the study of the impact of global warming. Depending on the level of information available for the prediction of future weather condition, it is shown that either the method of retaining to current level, constant offset method or diurnal modelling method may be used to generate the future hourly variation of an individual weather parameter. An example of the application of this method to the different global warming scenarios in Australia is presented. Since there is no reliable projection of possible change in air humidity, solar radiation or wind characters, as a first approximation, these parameters have been assumed to remain at the current level. A sensitivity test of their impact on the building energy performance shows that there is generally a good linear relationship between building cooling load and the changes of weather variables of solar radiation, relative humidity or wind speed.

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A large number of methods have been published that aim to evaluate various components of multi-view geometry systems. Most of these have focused on the feature extraction, description and matching stages (the visual front end), since geometry computation can be evaluated through simulation. Many data sets are constrained to small scale scenes or planar scenes that are not challenging to new algorithms, or require special equipment. This paper presents a method for automatically generating geometry ground truth and challenging test cases from high spatio-temporal resolution video. The objective of the system is to enable data collection at any physical scale, in any location and in various parts of the electromagnetic spectrum. The data generation process consists of collecting high resolution video, computing accurate sparse 3D reconstruction, video frame culling and down sampling, and test case selection. The evaluation process consists of applying a test 2-view geometry method to every test case and comparing the results to the ground truth. This system facilitates the evaluation of the whole geometry computation process or any part thereof against data compatible with a realistic application. A collection of example data sets and evaluations is included to demonstrate the range of applications of the proposed system.

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Both creative industries and innovation are slippery fish to handle conceptually, to say nothing of their relationship. This paper faces, first, the problems of definitions and data that can bedevil clear analysis of the creative industries. It then presents a method of data generation and analysis that has been developed to address these problems while providing an evidence pathway supporting the movement in policy thinking from creative output (through industry sectors) to creative input to the broader economy (through a focus on occupations/activity). Facing the test of policy relevance, this work has assisted in moving the ongoing debates about the creative industries toward innovation thinking by developing the concept of creative occupations as input value. Creative inputs as 'enablers' arguably has parallels with the way ICTs have been shown to be broad enablers of economic growth. We conclude with two short instantiations of the policy relevance of this concept: design as a creative input; and creative human capital and education.

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Aim. Our aim in this paper is to explain a methodological/methods package devised to incorporate situational and social world mapping with frame analysis, based on a grounded theory study of Australian rural nurses' experiences of mentoring. Background. Situational analysis, as conceived by Adele Clarke, shifts the research methodology of grounded theory from being located within a postpositivist paradigm to a postmodern paradigm. Clarke uses three types of maps during this process: situational, social world and positional, in combination with discourse analysis. Method. During our grounded theory study, the process of concurrent interview data generation and analysis incorporated situational and social world mapping techniques. An outcome of this was our increased awareness of how outside actors influenced participants in their constructions of mentoring. In our attempts to use Clarke's methodological package, however, it became apparent that our constructivist beliefs about human agency could not be reconciled with the postmodern project of discourse analysis. We then turned to the literature on symbolic interactionism and adopted frame analysis as a method to examine the literature on rural nursing and mentoring as secondary form of data. Findings. While we found situational and social world mapping very useful, we were less successful in using positional maps. In retrospect, we would argue that collective action framing provides an alternative to analysing such positions in the literature. This is particularly so for researchers who locate themselves within a constructivist paradigm, and who are therefore unwilling to reject the notion of human agency and the ability of individuals to shape their world in some way. Conclusion. Our example of using this package of situational and social worlds mapping with frame analysis is intended to assist other researchers to locate participants more transparently in the social worlds that they negotiate in their everyday practice. © 2007 Blackwell Publishing Ltd.

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Aim. This paper is a report of a study to explore rural nurses' experiences of mentoring. Background. Mentoring has recently been proposed by governments, advocates and academics as a solution to the problem for retaining rural nurses in the Australian workforce. Action in the form of mentor development workshops has changed the way that some rural nurses now construct supportive relationships as mentoring. Method. A grounded theory design was used with nine rural nurses. Eleven semi-structured interviews were conducted in various states of Australia during 2004-2005. Situational analysis mapping techniques and frame analysis were used in combination with concurrent data generation and analysis and theoretical sampling. Findings. Experienced rural nurses cultivate novices through supportive mentoring relationships. The impetus for such relationships comes from their own histories of living and working in the same community, and this was termed 'live my work'. Rural nurses use multiple perspectives of self in order to manage their interactions with others in their roles as community members, consumers of healthcare services and nurses. Personal strategies adapted to local context constitute the skills that experienced rural nurses pass-on to neophyte rural nurses through mentoring, while at the same time protecting them through troubleshooting and translating local cultural norms. Conclusion. Living and working in the same community creates a set of complex challenges for novice rural nurses that are better faced with a mentor in place. Thus, mentoring has become an integral part of experienced rural nurses' practice to promote staff retention. © 2007 The Authors.

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This paper presents a strategy for delayed research method selection in a qualitative interpretivist research. An exemplary case details how explorative interviews were designed and conducted in accordance with a paradigm prior to deciding whether to adopt grounded theory or phenomenology for data analysis. The focus here is to determine the most appropriate research strategy in this case the methodological framing to conduct research and represent findings, both of which are detailed. Research addressing current management issues requires both a flexible framework and the capability to consider the research problem from various angles, to derive tangible results for academia with immediate application to business demands. Researchers, and in particular novices, often struggle to decide on an appropriate research method suitable to address their research problem. This often applies to interpretative qualitative research where it is not always immediately clear which is the most appropriate method to use, as the research objectives shift and crystallize over time. This paper uses an exemplary case to reveal how the strategy for delayed research method selection contributes to deciding whether to adopt grounded theory or phenomenology in the initial phase of a PhD research project. In this case, semi-structured interviews were used for data generation framed in an interpretivist approach, situated in a business context. Research questions for this study were thoroughly defined and carefully framed in accordance with the research paradigm‟s principles, while at the same time ensuring that the requirements of both potential research methods were met. The grounded theory and phenomenology methods were compared and contrasted to determine their suitability and whether they meet the research objectives based on a pilot study. The strategy proposed in this paper is an alternative to the more „traditional‟ approach, which initially selects the methodological formulation, followed by data generation. In conclusion, the suggested strategy for delayed research method selection intends to help researchers identify and apply the most appropriate method to their research. This strategy is based on explorations of data generation and analysis in order to derive faithful results from the data generated.

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The interaction and relationship between the global warming and the thermal performance buildings are dynamic in nature. In order to model and understand this behavior, different approaches, including keeping weather variable unchanged, morphing approach and diurnal modelling method, have been used to project and generate future weather data. Among these approaches, various assumptions on the change of solar radiation, air humidity and/or wind characteristics may be adopted. In this paper, an example to illustrate the generation of future weather data for the different global warming scenarios in Australia is presented. The sensitivity of building cooling loads to the possible changes of assumed values used in the future weather data generation is investigated. It is shown that with ± 10% change of the proposed future values for solar radiation, air humidity or wind characteristics, the corresponding change in the cooling load of the modeled sample office building at different Australian capital cities would not exceed 6%, 4% and 1.5% respectively. It is also found that with ±10% changes on the proposed weather variables for both the 2070-high future scenario and the current weather scenario, the corresponding change in the cooling loads at different locations may be weaker (up to 2% difference in Hobart for ±10% change in global solar radiation), similar (less than 0.6%) difference in Hobart for ±10% change in wind speed), or stronger (up to 1.6% difference in Hobart for ±10% change in relative humidity) in the 2070-high future scenario than in the current weather scenario.

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This paper discusses and summarises a recent systematic study on the implication of global warming on air conditioned office buildings in Australia. Four areas are covered, including analysis of historical weather data, generation of future weather data for the impact study of global warming, projection of building performance under various global warming scenarios, and evaluation of various adaptation strategies under 2070 high global warming conditions. Overall, it is found that depending on the assumed future climate scenarios and the location considered, the increase of total building energy use for the sample Australian office building may range from 0.4 to 15.1%. When the increase of annual average outdoor temperature exceeds 2 °C, the risk of overheating will increase significantly. However, the potential overheating problem could be completely eliminated if internal load density is significantly reduced.

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Creative productivity emerges from human interactions (Hartley, 2009, p. 214). In an era when life is lived in rather than with media (Deuze, this issue), this productivity is widely distributed among ephemeral social networks mediated through the internet. Understanding the underlying dynamics of these networks of human interaction is an exciting and challenging task that requires us to come up with new ways of thinking and theorizing. For example, inducting theory from case studies that are designed to show the exceptional dynamics present within single settings can be augmented today by largescale data generation and collections that provide new analytic opportunities to research the diversity and complexity of human interaction. Large-scale data generation and collection is occurring across a wide range of individuals and organisations. This offers a massive field of analysis which internet companies and research labs in particular are keen on exploring. Lazer et al (2009: 721) argue that such analytic potential is transformational for many if not most research fields but that the use of such valuable data must neither remain confined to private companies and government agencies nor to a privileged set of academic researchers whose studies cannot be replicated nor critiqued. In fact, the analytic capacity to have data of such unprecedented scope and scale available not only requires us to analyse what is and could be done with it and by whom (1) but also what it is doing to us, our cultures and societies (2). Part (1) of such analysis is interested in dependencies and their implications. Part (2) of the enquiry embeds part (1) in a larger context that analyses the long-term, complex dynamics of networked human interaction. From the latter perspective we can treat specific phenomena and the methods used to analyse them as moments of evolution.

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Presently organisations engage in what is termed as Global Business Transformation Projects [GBTPs], for consolidating, innovating, transforming and restructuring their processes and business strategies while undergoing fundamental change. Culture plays an important role in global business transformation projects as these involve people of different cultural backgrounds and span across countries, industries and disciplinary boundaries. Nevertheless, there is scant empirical research on how culture is conceptualised beyond national and organisational cultures but also on how culture is to be taken into account and dealt with within global business transformation projects. This research is situated in a business context and discovers a theory that aids in describing and dealing with culture. It draws on the lived experiences of thirty-two senior management practitioners, reporting on more than sixty-one global business transformation projects in which they were actively involved. The research method used is a qualitative and interpretive one and applies a grounded theory approach, with rich data generated through interviews. In addition, vignettes were developed to illustrate the derived theoretical models. The findings from this study contribute to knowledge in multiple ways. First, it provides a holistic account of global business transformation projects that describe the construct of culture by the elements of culture types, cultural differences and cultural diversity. A typology of culture types has been developed which enlarges the view of culture beyond national and organisational culture including an industry culture, professional service firm culture and 'theme' culture. The amalgamation of the culture types instantiated in a global business transformation project compromises its project culture. Second, the empirically grounded process for managing culture in global business transformation projects integrates the stages of recognition, understanding and management as well as the enablement providing a roadmap for dealing with culture in global business transformation projects. Third, this study identified contextual variables to global business transformation projects, which provide the means of describing the environment global business transformation projects are situated, influence the construct of culture and inform the process for managing culture. Fourth, the contribution to the research method is the positioning of interview research as a strategy for data generation and the detailed documentation applying grounded theory to discover theory.

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OBJECTIVE: To explore how registered nurses (RNs) in the general ward perceive discharge processes and practices for patients recently discharged from the intensive care unit (ICU). BACKGROUND: Patients discharged from the ICU environment often require complicated and multifaceted care. The ward-based RN is at the forefront of the care of this fragile patient population, yet their views and perceptions have seldom been explored. DESIGN: A qualitative grounded theory design was used to guide focus group interviews with the RN participants. METHODS: Five semi-structured focus group interviews, including 27 RN participants, were conducted in an Australian metropolitan tertiary referral hospital in 2011. Data analyses of transcripts, field notes and memos used concurrent data generation, constant comparative analysis and theoretical sampling. RESULTS: Results yielded a core category of 'two worlds' stressing the disconnectedness between ICU and the ward setting. This category was divided into sub categories of 'communication disconnect' and 'remember the family'. Properties of 'what we say', 'what we write', 'transfer' and 'information needs' respectively were developed within those sub-categories. CONCLUSION: The discharge process for patients within the ICU setting is complicated and largely underappreciated. There are fundamental, misunderstood differences in prioritisation and care of patients between the areas, with a deep understanding of practice requirements of ward based RNs not being understood. The findings of this research may be used to facilitate inter departmental communications and progress practice development.

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This research has successfully developed a novel synthetic structural health monitoring system model that is cost-effective and flexible in sensing and data acquisition; and robust in the structural safety evaluation aspect for the purpose of long-term and frequent monitoring of large-scale civil infrastructure during their service lives. Not only did it establish a real-world structural monitoring test-bed right at the heart of QUT Gardens Point Campus but it can also facilitate reliable and prompt protection for any built infrastructure system as well as the user community involved.

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Objective: The positioning and meaning of palliative care within the healthcare system lacks clarity which adds a level of complexity to the process of transition to palliative care. This study explores the transition to the palliative care process in the acute care context of metastatic melanoma. Method: A theoretical framework drawing on interpretive and critical traditions informs this research. The pragmatism of symbolic interactionism and the critical theory of Habermas brought a broad orientation to the research. Integration of the theoretical framework and grounded-theory methods facilitated data generation and analysis of 29 interviews with patients, family carers, and healthcare professionals. Results: The key analytical findings depict a scope of palliative care that was uncertain for users of the system and for those working within the system. Becoming “palliative” is not a defined event; nor is there unanimity around referral to a palliative care service. As such, ambiguity and tension contribute to the difficulties involved in negotiating the transition to palliative care. Significance of Results: Our findings point to uncertainty around the scopes of practice in the transition to palliative care. The challenge in the transition process lies in achieving greater coherency of care within an increasingly specialized healthcare system. The findings may not only inform those within a metastatic melanoma context but may contribute more broadly to palliative practices within the acute care setting.