342 resultados para analytical approaches


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In developed countries the relationship between socioeconomic position (SEP) and health is unequivocal. Those who are socioeconomically disadvantaged are known to experience higher morbidity and mortality from a range of chronic diet-related conditions compared to those of higher SEP. Socioeconomic inequalities in diet are well established. Compared to their more advantaged counterparts, those of low SEP are consistently found to consume diets less consistent with dietary guidelines (i.e. higher in fat, salt and sugar and lower in fibre, fruit and vegetables). Although the reasons for dietary inequalities remain unclear, understanding how such differences arise is important for the development of strategies to reduce health inequalities. Both environmental (e.g. proximity of supermarkets, price, and availability of foods) and psychosocial (e.g. taste preference, nutrition knowledge) influences are proposed to account for inequalities in food choices. Although in the United States (US), United Kingdom (UK), and parts of Australia, environmental factors are associated with socioeconomic differences in food choices, these factors do not completely account for the observed inequalities. Internationally, this context has prompted calls for further exploration of the role of psychological and social factors in relation to inequalities in food choices. It is this task that forms the primary goal of this PhD research. In the small body of research examining the contribution of psychosocial factors to inequalities in food choices, studies have focussed on food cost concerns, nutrition knowledge or health concerns. These factors are generally found to be influential. However, since a range of psychosocial factors are known determinants of food choices in the general population, it is likely that a range of factors also contribute to inequalities in food choices. Identification of additional psychosocial factors of relevance to inequalities in food choices would provide new opportunities for health promotion, including the adaption of existing strategies. The methodological features of previous research have also hindered the advancement of knowledge in this area and a lack of qualitative studies has resulted in a dearth of descriptive information on this topic. This PhD investigation extends previous research by assessing a range of psychosocial factors in relation to inequalities in food choices using both quantitative and qualitative techniques. Secondary data analyses were undertaken using data obtained from two Brisbane-based studies, the Brisbane Food Study (N=1003, conducted in 2000), and the Sixty Families Study (N=60, conducted in 1998). Both studies involved main household food purchasers completing an interviewer-administered survey within their own home. Data pertaining to food-purchasing, and psychosocial, socioeconomic and demographic characteristics were collected in each study. The mutual goals of both the qualitative and quantitative phases of this investigation were to assess socioeconomic differences in food purchasing and to identify psychosocial factors relevant to any observed differences. The quantitative methods then additionally considered whether the associations examined differed according to the socioeconomic indicator used (i.e. income or education). The qualitative analyses made a unique contribution to this project by generating detailed descriptions of socioeconomic differences in psychosocial factors. Those with lower levels of income and education were found to make food purchasing choices less consistent with dietary guidelines compared to those of high SEP. The psychosocial factors identified as relevant to food-purchasing inequalities were: taste preferences, health concerns, health beliefs, nutrition knowledge, nutrition concerns, weight concerns, nutrition label use, and several other values and beliefs unique to particular socioeconomic groups. Factors more tenuously or inconsistently related to socioeconomic differences in food purchasing were cost concerns, and perceived adequacy of the family diet. Evidence was displayed in both the quantitative and qualitative analyses to suggest that psychosocial factors contribute to inequalities in food purchasing in a collective manner. The quantitative analyses revealed that considerable overlap in the socioeconomic variation in food purchasing was accounted for by key psychosocial factors of importance, including taste preference, nutrition concerns, nutrition knowledge, and health concerns. Consistent with these findings, the qualitative transcripts demonstrated the interplay between such influential psychosocial factors in determining food-purchasing choices. The qualitative analyses found socioeconomic differences in the prioritisation of psychosocial factors in relation to food choices. This is suggestive of complex cultural factors that distinguish advantaged and disadvantaged groups and result in socioeconomically distinct schemas related to health and food choices. Compared to those of high SEP, those of lower SEP were less likely to indicate that health concerns, nutrition concerns, or food labels influenced food choices, and exhibited lower levels of nutrition knowledge. In the absence of health or nutrition-related concerns, taste preferences tended to dominate the food purchasing choices of those of low SEP. Overall, while cost concerns did not appear to be a main determinant of socioeconomic differences in food purchasing, this factor had a dominant influence on the food choices of some of the most disadvantaged respondents included in this research. The findings of this study have several implications for health promotion. The integrated operation of psychosocial factors on food purchasing inequalities indicates that multiple psychosocial factors may be appropriate to target in health promotion. It also seems possible that the inter-relatedness of psychosocial factors would allow health promotion targeting a single psychosocial factor to have a flow-on affect in terms of altering other influential psychosocial factors. This research also suggests that current mass marketing approaches to health promotion may not be effective across all socioeconomic groups due to differences in the priorities and main factors of influence in food purchasing decisions across groups. In addition to the practical recommendations for health promotion, this investigation, through the critique of previous research, and through the substantive study findings, has highlighted important methodological considerations for future research. Of particular note are the recommendations pertaining to the selection of socioeconomic indicators, measurement of relevant constructs, consideration of confounders, and development of an analytical approach. Addressing inequalities in health has been noted as a main objective by many health authorities and governments internationally. It is envisaged that the substantive and methodological findings of this thesis will make a useful contribution towards this important goal.

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Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

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Deep Raman Spectroscopy is a domain within Raman spectroscopy consisting of techniques that facilitate the depth profiling of diffusely scattering media. Such variants include Time-Resolved Raman Spectroscopy (TRRS) and Spatially-Offset Raman Spectroscopy (SORS). A recent study has also demonstrated the integration of TRRS and SORS in the development of Time-Resolved Spatially-Offset Raman Spectroscopy (TR-SORS). This research demonstrates the application of specific deep Raman spectroscopic techniques to concealed samples commonly encountered in forensic and homeland security at various working distances. Additionally, the concepts behind these techniques are discussed at depth and prospective improvements to the individual techniques are investigated. Qualitative and quantitative analysis of samples based on spectral data acquired from SORS is performed with the aid of multivariate statistical techniques. By the end of this study, an objective comparison is made among the techniques within Deep Raman Spectroscopy based on their capabilities. The efficiency and quality of these techniques are determined based on the results procured which facilitates the understanding of the degree of selectivity for the deeper layer exhibited by the individual techniques relative to each other. TR-SORS was shown to exhibit an enhanced selectivity for the deeper layer relative to TRRS and SORS whilst providing spectral results with good signal-to-noise ratio. Conclusive results indicate that TR-SORS is a prospective deep Raman technique that offers higher selectivity towards deep layers and therefore enhances the non-invasive analysis of concealed substances from close range as well as standoff distances.

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Energy efficiency of buildings is attracting significant attention from the research community as the world is moving towards sustainable buildings design. Energy efficient approaches are measures or ways to improve the energy performance and energy efficiency of buildings. This study surveyed various energy-efficient approaches for commercial building and identifies Envelope Thermal Transfer Value (ETTV) and Green applications (Living wall, Green facade and Green roof) as most important and effective methods. An in-depth investigation was carried out on these energy-efficient approaches. It has been found that no ETTV model has been developed for sub-tropical climate of Australia. Moreover, existing ETTV equations developed for other countries do not take roof heat gain into consideration. Furthermore, the relationship of ETTV and different Green applications have not been investigated extensively in any literature, and the energy performance of commercial buildings in the presence of Living wall, Green facade and Green roof has not been investigated in the sub-tropical climate of Australia. The study has been conducted in two phases. First, the study develops the new formulation, coefficient and bench mark value of ETTV in the presence of external shading devices. In the new formulation, roof heat gain has been included in the integrated heat gain model made of ETTV. In the 2nd stage, the study presents the relationship of thermal and energy performance of (a) Living wall and ETTV (b) Green facade and ETTV (c) Combination of Living wall, Green facade and ETTV (d) Combination of Living wall, Green Roof and ETTV in new formulations. Finally, the study demonstrates the amount of energy that can be saved annually from different combinations of Green applications, i.e., Living wall, Green facade; combination of Living wall and Green facade; combination of Living wall and Green roof. The estimations are supported by experimental values obtained from extensive experiments of Living walls and Green roofs.

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Literacy studies have begun to examine the spatial dimension of literacy practices in a way that foregrounds space, and that considers space as constitutive to human relations and practices. This chapter provides an introduction to spatial literacy research, providing a guide to key theorists, themes, and studies that have shaped historical and new developments in spatial approaches to literacy practice and pedagogy. It begins by reconceptualising socio-spatial approaches to literacy research and defines terms. Intersections with related social theories are examined, with an emphasis on critical approaches and the politics of space. It clarifies the relationship between socio-spatial and socio-cultural paradigms, revisiting the spatial in seminal socio-cultural research. It covers new ground,including networks, flows, and deterritorialisation of literacy practice. The chapter concludes with challenges and recommendations for future language research and educational practice.

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BACKGROUND: The treatment for deep surgical site infection (SSI) following primary total hip arthroplasty (THA) varies internationally and it is at present unclear which treatment approaches are used in Australia. The aim of this study is to identify current treatment approaches in Queensland, Australia, show success rates and quantify the costs of different treatments. METHODS: Data for patients undergoing primary THA and treatment for infection between January 2006 and December 2009 in Queensland hospitals were extracted from routinely used hospital databases. Records were linked with pathology information to confirm positive organisms. Diagnosis and treatment of infection was determined using ICD-10-AM and ACHI codes, respectively. Treatment costs were estimated based on AR-DRG cost accounting codes assigned to each patient hospital episode. RESULTS: A total of n=114 patients with deep surgical site infection were identified. The majority of patients (74%) were first treated with debridement, antibiotics and implant retention (DAIR), which was successful in eradicating the infection in 60.3% of patients with an average cost of $13,187. The remaining first treatments were 1-stage revision, successful in 89.7% with average costs of $27,006, and 2-stage revisions, successful in 92.9% of cases with average costs of $42,772. Multiple treatments following 'failed DAIR' cost on average $29,560, for failed 1-stage revision were $24,357, for failed 2-stage revision were $70,381 and were $23,805 for excision arthroplasty. CONCLUSIONS: As treatment costs in Australia are high primary prevention is important and the economics of competing treatment choices should be carefully considered. These currently vary greatly across international settings.

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Despite growing recognition of creativity's importance for young people, the creativity of adolescents remains a neglected field of study. Hence, grounded theory research was conducted with 20 adolescents from two Australian schools regarding their self-reported experiences of creativity in diverse domains. Four approaches to the creative process – adaptation, transfer, synthesis, and genesis – emerged from the research. These approaches used by students across a range of domains contribute to the literature in two key ways: (a) explaining how adolescents engage in the creative process, theorised from adolescent creators’ self-reports of their experiences and (b) confirms hybrid theories that recognise that creativity has elements of both domain-generality and domain-specificity. The findings have educational implications for both students and teachers. For students, enhancing metacognitive awareness of their preferred approaches to creativity was reported as a valuable experience in itself, and might also enable adolescents to expand their creativity through experimenting with other ways of engaging in the creative process. For teachers, using these understandings to underpin their pedagogies can promote metacognitive awareness and experimentation, and also provide teachers with a framework for assessing students’ creative processes.

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Application of "advanced analysis" methods suitable for non-linear analysis and design of steel frame structures permits direct and accurate determination of ultimate system strengths, without resort to simplified elastic methods of analysis and semi-empirical specification equations. However, the application of advanced analysis methods has previously been restricted to steel frames comprising only compact sections that are not influenced by the effects of local buckling. A research project has been conducted with the aim of developing concentrated plasticity methods suitable for practical advanced analysis of steel frame structures comprising non-compact sections. This paper contains a comprehensive set of analytical benchmark solutions for steel frames comprising non-compact sections, which can be used to verify the accuracy of simplified concentrated plasticity methods of advanced analysis. The analytical benchmark solutions were obtained using a distributed plasticity shell finite element model that explicitly accounts for the effects of gradual cross-sectional yielding, longitudinal spread of plasticity, initial geometric imperfections, residual stresses, and local buckling. A brief description and verification of the shell finite element model is provided in this paper.

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This thesis introduced Bayesian statistics as an analysis technique to isolate resonant frequency information in in-cylinder pressure signals taken from internal combustion engines. Applications of these techniques are relevant to engine design (performance and noise), energy conservation (fuel consumption) and alternative fuel evaluation. The use of Bayesian statistics, over traditional techniques, allowed for a more in-depth investigation into previously difficult to isolate engine parameters on a cycle-by-cycle basis. Specifically, these techniques facilitated the determination of the start of pre-mixed and diffusion combustion and for the in-cylinder temperature profile to be resolved on individual consecutive engine cycles. Dr Bodisco further showed the utility of the Bayesian analysis techniques by applying them to in-cylinder pressure signals taken from a compression ignition engine run with fumigated ethanol.

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We have previously reported a preliminary taxonomy of patient error. However, approaches to managing patients' contribution to error have received little attention in the literature. This paper aims to assess how patients and primary care professionals perceive the relative importance of different patient errors as a threat to patient safety. It also attempts to suggest what these groups believe may be done to reduce the errors, and how. It addresses these aims through original research that extends the nominal group analysis used to generate the error taxonomy. Interviews were conducted with 11 purposively selected groups of patients and primary care professionals in Auckland, New Zealand, during late 2007. The total number of participants was 83, including 64 patients. Each group ranked the importance of possible patient errors identified through the nominal group exercise. Approaches to managing the most important errors were then discussed. There was considerable variation among the groups in the importance rankings of the errors. Our general inductive analysis of participants' suggestions revealed the content of four inter-related actions to manage patient error: Grow relationships; Enable patients and professionals to recognise and manage patient error; be Responsive to their shared capacity for change; and Motivate them to act together for patient safety. Cultivation of this GERM of safe care was suggested to benefit from 'individualised community care'. In this approach, primary care professionals individualise, in community spaces, population health messages about patient safety events. This approach may help to reduce patient error and the tension between personal and population health-care.

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Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

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Skin cancer is one of the most commonly occurring cancer types, with substantial social, physical, and financial burdens on both individuals and societies. Although the role of UV light in initiating skin cancer development has been well characterized, genetic studies continue to show that predisposing factors can influence an individual's susceptibility to skin cancer and response to treatment. In the future, it is hoped that genetic profiles, comprising a number of genetic markers collectively involved in skin cancer susceptibility and response to treatment or prognosis, will aid in more accurately informing practitioners' choices of treatment. Individualized treatment based on these profiles has the potential to increase the efficacy of treatments, saving both time and money for the patient by avoiding the need for extensive or repeated treatment. Increased treatment responses may in turn prevent recurrence of skin cancers, reducing the burden of this disease on society. Currently existing pharmacogenomic tests, such as those that assess variation in the metabolism of the anticancer drug fluorouracil, have the potential to reduce the toxic effects of anti-tumor drugs used in the treatment of non-melanoma skin cancer (NMSC) by determining individualized appropriate dosage. If the savings generated by reducing adverse events negate the costs of developing these tests, pharmacogenomic testing may increasingly inform personalized NMSC treatment.

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To date, available literature mainly discusses Twitter activity patterns in the context of individual case studies, while comparative research on a large number of communicative events, their dynamics and patterns is missing. By conducting a comparative study of more than forty different cases (covering topics such as elections, natural disasters, corporate crises, and televised events) we identify a number of distinct types of discussion which can be observed on Twitter. Drawing on a range of communicative metrics, we show that thematic and contextual factors influence the usage of different communicative tools available to Twitter users, such as original tweets, @replies, retweets, and URLs. Based on this first analysis of the overall metrics of Twitter discussions, we also demonstrate stable patterns in the use of Twitter in the context of major topics and events.

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This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.

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This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include a definition of KG in PBOs, a conceptual framework to investigate KG and a methodological framework for empirical inquiry into KG in PBO settings. Our definition highlights the contingent nature of KG processes in relation to their organizational context. The conceptual framework addresses macro- and micro-level elements of KG and their interaction. The methodological framework proposes five different research approaches, structured by differentiation and integration of various ontological and epistemological stances. Together these contributions provide a novel platform for understanding KG in PBOs and developing new insights into the design and execution of research on KG within PBOs.