985 resultados para Behavioral information


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Skills in spatial sciences are fundamental to understanding our world in context. Increasing digital presence and the availability of data with accurate spatial components has allowed almost everything researchers and students do to be represented in a spatial context. Representing outcomes and disseminating information has moved from 2D to 4D with time series animation. In the next 5 years industry will not only demand QUT graduates have spatial skills along with analytical skills, graduates will be required to present their findings in spatial visualizations that show spatial, spectral and temporal contexts. Domains such as engineering and science will no longer be the leaders in spatial skills as social sciences, health, arts and the business community gain momentum from place-based research including human interactions. A university that can offer students a pathway to advanced spatial investigation will be ahead of the game.

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Information security and privacy in the healthcare domain is a complex and challenging problem for computer scientists, social scientists, law experts and policy makers. Appropriate healthcare provision requires specialized knowledge, is information intensive and much patient information is of a particularly sensitive nature. Electronic health record systems provide opportunities for information sharing which may enhance healthcare services, for both individuals and populations. However, appropriate information management measures are essential for privacy preservation...

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This paper documents the longitudinal and reciprocal relations among behavioral sleep problems, emotional and attentional self-regulation in a population sample of 4109 children participating in the Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort. Maternal reports of children’s sleep problems and self-regulation were collected at five time points from infancy to 8-9 years of age. Longitudinal structural equation modeling supported a developmental cascade model in which sleep problems have a persistent negative effect on emotional regulation, which in turn contributes to ongoing sleep problems and poorer attentional regulation in children over time. Findings suggest that sleep behaviors are a key target for interventions that aim to improve children’s self-regulatory capacities.

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This research explored the knowledge, skills, qualities, and professional education needs, of information professionals in galleries, libraries, archives and museums (GLAM) in Australia. The findings revealed that although full convergence of these sectors is unlikely, many of the skills, knowledge and qualities would be required across all four sectors. The research used the Grounded Delphi Method, a relatively new methodological extension of the Delphi method that incorporates aspects of Grounded Theory. The findings provide the first empirically based guidelines around what needs to be included in an educational framework for information professionals who will work in the emerging GLAM environment. As the first study of GLAM education requirements in Australia and the wider Asia-Pacific region to take a holistic approach by engaging information professionals across all four sectors, this thesis makes a contribution to the GLAM research field and to information education generally.

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This paper reflects on the critical need for an urgent transformation of higher education curriculum globally, to equip society with professionals who can address our 21st Century sustainable living challenges. Specifically it discusses a toolkit called the ‘Engineering Sustainable Solutions Program’, which is a freely available, rigorously reviewed and robust content resource for higher education institutions to access content on innovations and opportunities in the process of evolving the curriculum...

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The purpose of this paper is to investigate how social media may support information encountering (i.e., where individuals encounter useful and interesting information while seeking or browsing for some other information) and how this may lead to facilitation of tacit knowledge creation and sharing. The study employed a qualitative survey design that interviewed twenty-four physicians who were active users of social media to better understand the phenomenon of information encountering on social media. The data was analysed using the thematic analysis approach. The study found six main ways through which social media supports information encountering. Furthermore, drawing upon knowledge creation theories, the study concluded that information encountering on social media facilitates tacit knowledge creation and sharing among individuals. The study provides new directions for further empirical investigations to examine whether information encountering on social media actually leads to tacit knowledge creation and sharing. The findings of the study may also provide opportunities for users to adopt social media effectively or gain greater value from social media use.

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This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.

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We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

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We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

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This study examined the role of information, efficacy, and 3 stressors in predicting adjustment to organizational change. Participants were 589 government employees undergoing an 18-month process of regionalization. To examine if the predictor variables had long-term effects on adjustment, the authors assessed psychological well-being, client engagement, and job satisfaction again at a 2-year follow-up. At Time 1, there was evidence to suggest that information was indirectly related to psychological well-being, client engagement, and job satisfaction, via its positive relationship to efficacy. There also was evidence to suggest that efficacy was related to reduced stress appraisals, thereby heightening client engagement. Last, there was consistent support for the stress-buffering role of Time 1 self-efficacy in the prediction of Time 2 job satisfaction.

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This study was undertaken to examine the main and interactive effects of work stress and work control on levels of adjustment. Work stress, behavioral control, and informational control were manipulated in an experimental setting in which participants (N = 192) completed an in-basket activity. Although minimal support was found for the main and interactive effects of objective work stress, behavioral control, and informational control on adjustment, analyses involving the subjective measures of these variables revealed strong support for the proposal that work stress, behavioral control, and informational control would exert main effects on adjustment. There was also evidence that subjective levels of behavioral control buffered the negative effects of subjective work stress on positive mood, subjective task performance, and task satisfaction.

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Two experimental studies were conducted to examine whether the stress-buffering effects of behavioral control on work task responses varied as a function of procedural information. Study 1 manipulated low and high levels of task demands, behavioral control, and procedural information for 128 introductory psychology students completing an in-basket activity. ANOVA procedures revealed a significant three-way interaction among these variables in the prediction of subjective task performance and task satisfaction. It was found that procedural information buffered the negative effects of task demands on ratings of performance and satisfaction only under conditions of low behavioral control. This pattern of results suggests that procedural information may have a compensatory effect when the work environment is characterized by a combination of high task demands and low behavioral control. Study 2 (N=256) utilized simple and complex versions of the in-basket activity to examine the extent to which the interactive relationship among task demands, behavioral control, and procedural information varied as a function of task complexity. There was further support for the stress-buffering role of procedural information on work task responses under conditions of low behavioral control. This effect was, however, only present when the in-basket activity was characterized by high task complexity, suggesting that the interactive relationship among these variables may depend on the type of tasks performed at work.

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The present study was designed to examine the main and interactive effects of task demands, work control, and task information on levels of adjustment. Task demands, work control, and task information were manipulated in an experimental setting where participants completed a letter-sorting activity (N= 128). Indicators of adjustment included measures of positive mood, participants' perceptions of task performance, and task satisfaction. Results of the present study provided some support for the main effects of objective task demands, work control, and task information on levels of adjustment. At the subjective level of analysis, there was some evidence to suggest that work control and task information interacted in their effects on levels of adjustment. There was minimal support for the proposal that work control and task information would buffer the negative effects of task demands on adjustment. There was, however, some evidence to suggest that the stress-buffering role of subjective work control was more marked at high, rather than low, levels of subjective task information.

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Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

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Purpose Health service quality is an important determinant for health service satisfaction and behavioral intentions. The purpose of this paper is to investigate requirements of e‐health services and to develop a measurement model to analyze the construct of “perceived e‐health service quality.” Design/methodology/approach The paper adapts the C‐OAR‐SE procedure for scale development by Rossiter. The focal aspect is the “physician‐patient relationship” which forms the core dyad in the healthcare service provision. Several in‐depth interviews were conducted in Switzerland; first with six patients (as raters), followed by two experts of the healthcare system (as judges). Based on the results and an extensive literature research, the classification of object and attributes is developed for this model. Findings The construct e‐health service quality can be described as an abstract formative object and is operationalized with 13 items: accessibility, competence, information, usability/user friendliness, security, system integration, trust, individualization, empathy, ethical conduct, degree of performance, reliability, and ability to respond. Research limitations/implications Limitations include the number of interviews with patients and experts as well as critical issues associated with C‐OAR‐SE. More empirical research is needed to confirm the quality indicators of e‐health services. Practical implications Health care providers can utilize the results for the evaluation of their service quality. Practitioners can use the hierarchical structure to measure service quality at different levels. The model provides a diagnostic tool to identify poor and/or excellent performance with regard to the e‐service delivery. Originality/value The paper contributes to knowledge with regard to the measurement of e‐health quality and improves the understanding of how customers evaluate the quality of e‐health services.