298 resultados para Demographic data
Resumo:
Background: Apart from promoting physical recovery and assisting in activities of daily living, a major challenge in stroke rehabilitation is to minimize psychosocial morbidity and to promote the reintegration of stroke survivors into their family and community. The identification of key factors influencing long-term outcome are essential in developing more effective rehabilitation measures for reducing stroke-related morbidity. The aim of this study was to test a theoretical model of predictors of participation restriction which included the direct and indirect effects between psychosocial outcomes, physical outcome, and socio-demographic variables at 12 months after stroke.--------- Methods: Data were collected from 188 stroke survivors at 12 months following their discharge from one of the two rehabilitation hospitals in Hong Kong. The settings included patients' homes and residential care facilities. Path analysis was used to test a hypothesized model of participation restriction at 12 months.---------- Results: The path coefficients show functional ability having the largest direct effect on participation restriction (β = 0.51). The results also show that more depressive symptoms (β = -0.27), low state self-esteem (β = 0.20), female gender (β = 0.13), older age (β = -0.11) and living in a residential care facility (β = -0.12) have a direct effect on participation restriction. The explanatory variables accounted for 71% of the variance in explaining participation restriction at 12 months.---------- Conclusion: Identification of stroke survivors at risk of high levels of participation restriction, depressive symptoms and low self-esteem will assist health professionals to devise appropriate rehabilitation interventions that target improving both physical and psychosocial functioning.
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The project aimed to understand how young people in different socio-demographic categories (age, gender, rurality) conceptualise and negotiate employment relations and the structural mechanisms (education, industry, legislation) through which youth are socialised in employment citizenship. The study extends previous research on youth employment in that it combines data from young people with that from other key actors in education and employment; that is, schools, employers, government, unions and non-government organizations. Despite the disparate nature of these groups there were some common themes regarding young workers. All agreed, for example, that there was a need for a greater level of employment knowledge and understanding among young people and that the current provisions for information dissemination on this subject are inadequate. There was also general consensus that, despite the need for some further clarifications and some potential limitations, the Child Employment Act 2006 (Qld) was beneficial.
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The recently proposed data-driven background dataset refinement technique provides a means of selecting an informative background for support vector machine (SVM)-based speaker verification systems. This paper investigates the characteristics of the impostor examples in such highly-informative background datasets. Data-driven dataset refinement individually evaluates the suitability of candidate impostor examples for the SVM background prior to selecting the highest-ranking examples as a refined background dataset. Further, the characteristics of the refined dataset were analysed to investigate the desired traits of an informative SVM background. The most informative examples of the refined dataset were found to consist of large amounts of active speech and distinctive language characteristics. The data-driven refinement technique was shown to filter the set of candidate impostor examples to produce a more disperse representation of the impostor population in the SVM kernel space, thereby reducing the number of redundant and less-informative examples in the background dataset. Furthermore, data-driven refinement was shown to provide performance gains when applied to the difficult task of refining a small candidate dataset that was mis-matched to the evaluation conditions.
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This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.
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There is a notable shortage of empirical research directed at measuring the magnitude and direction of stress effects on performance in a controlled environment. One reason for this is the inherent difficulties in identifying and isolating direct performance measures for individuals. Additionally most traditional work environments contain a multitude of exogenous factors impacting individual performance, but controlling for all such factors is generally unfeasible (omitted variable bias). Moreover, instead of asking individuals about their self-reported stress levels we observe workers' behavior in situations that can be classified as stressful. For this reason we have stepped outside the traditional workplace in an attempt to gain greater controllability of these factors using the sports environment as our experimental space. We empirically investigate the relationship between stress and performance, in an extreme pressure situation (football penalty kicks) in a winner take all sporting environment (FIFA World Cup and UEFA European Cup competitions). Specifically, we examine all the penalty shootouts between 1976 and 2008 covering in total 16 events. The results indicate that extreme stressors can have a positive or negative impact on Individuals' performance. On the other hand, more commonly experienced stressors do not affect professionals' performances.
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The technological environment in which Australian SMEs operate can be best described as dynamic and vital. The rate of technological change provides the SME owner/manager a complex and challenging operational context. Wireless applications are being developed that provide mobile devices with Internet content and e-business services. In Australia the adoption of e-commerce by large organisations has been relatively high, however the same cannot be said for SMEs where adoption has been slower than other developed countries. In contrast however mobile telephone adoption and diffusion is relatively high by SMEs. This exploratory study identifies attitudes, perceptions and issues for mobile data technologies by regional SME owner/managers across a range of industry sectors. The major issues include the sector the firm belongs to, the current adoption status of the firm, the level of mistrust of the IT industry, the cost of the technologies and the applications and attributes of the technologies.
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The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides the SME a complex and challenging operational context. The primary aim of this research was to identify the needs of SMEs in regional areas for mobile data technologies (MDT). In this study a distinction was drawn between those respondents who were full-adopters of technology, those who were partial-adopters and those who were non-adopters and these three segments articulated different needs and requirements for MDT. Overall the needs of regional SMEs for MDT can be conceptualised into three areas where the technology will assist business practices, communication, e-commerce and security.
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The seemingly exponential nature of technological change provides SMEs with a complex and challenging operational context. The development of infrastructures capable of supporting the wireless application protocol (WAP) and associated 'wireless' applications represents the latest generation of technological innovation with potential appeals to SMEs and end-users alike. This paper aims to understand the mobile data technology needs of SMEs in a regional setting. The research was especially concerned with perceived needs across three market segments : non-adopters, partial-adopters and full-adopters of new technology. The research was exploratory in nature as the phenomenon under scrutiny is relatively new and the uses unclear, thus focus groups were conducted with each of the segments. The paper provides insights for business, industry and academics.
Resumo:
The technological environment in which contemporary small- and medium-sized enterprises (SMEs) operate can only be described as dynamic. The exponential rate of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides for the SME a complex and challenging operational context. The primary aim of this research was to identify the needs of SMEs in regional areas for mobile data technologies (MDT). In this study a distinction was drawn between those respondents who were full-adopters of technology, those who were partial-adopters, and those who were non-adopters and these three segments articulated different needs and requirements for MDT. Overall, the needs of regional SMEs for MDT can be conceptualised into three areas where the technology will assist business practices; communication, e-commerce and security
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Research suggests that people differ in terms of changing their shopping behaviour during a recession. This paper reports on a preliminary descriptive study assessing what influences those consumers who have altered their shopping behaviour during such times. Driving the alteration of shopping behaviour were both demographic (age, gender, education, and nationality) and psychographic variables (attitudes, and head vs. heart decision making). Overall, the findings show that there are statistically significant differences between the two groups’ that marketers can address in their marketing strategies during the recession.
Resumo:
The technological environment in which contemporary small and medium-sized enterprises (SMEs) operate can only be described as dynamic. The seemingly exponential nature of technological change, characterised by perceived increases in the benefits associated with various technologies, shortening product life cycles and changing standards, provides for the small and medium-sized enterprise a complex and challenging operational context. The development of infrastructures capable of supporting the Wireless Application Protocol (WAP)and associated 'wireless' applications represents the latest generation of technological innovation with potential appeal to SMEs and end-users alike. The primary aim of this research was to understand the mobile data technology needs of SMEs in a regional setting. The research was especially concerned with perceived needs across three market segments; non-adopters of new technology, partial-adopters of new technology and full-adopters of new technology. Working with an industry partner, focus groups were conducted with each of these segments with the discussions focused on the use of the latest WP products and services. Some of the results are presented in this paper.
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We present algorithms, systems, and experimental results for underwater data muling. In data muling a mobile agent interacts with static agents to upload, download, or transport data to a different physical location. We consider a system comprising an Autonomous Underwater Vehicle (AUV) and many static Underwater Sensor Nodes (USN) networked together optically and acoustically. The AUV can locate the static nodes using vision and hover above the static nodes for data upload. We describe the hardware and software architecture of this underwater system, as well as experimental data. © 2006 IEEE.
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This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.
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Disability following a stroke can impose various restrictions on patients’ attempts at participating in life roles. The measurement of social participation, for instance, is important in estimating recovery and assessing quality of care at the community level. Thus, the identification of factors influencing social participation is essential in developing effective measures for promoting the reintegration of stroke survivors into the community. Data were collected from 188 stroke survivors (mean age 71.7 years) 12 months after discharge from a stroke rehabilitation hospital. Of these survivors, 128 (61 %) had suffered a first ever stroke, and 81 (43 %) had a right hemisphere lesion. Most (n = 156, 83 %) were living in their own home, though 32 (17 %) were living in residential care facilities. Path analysis was used to test a hypothesized model of participation restriction which included the direct and indirect effects between social, psychological and physical outcomes and demographic variables. Participation restriction was the dependent variable. Exogenous independent variables were age, functional ability, living arrangement and gender. Endogenous independent variables were depressive symptoms, state self-esteem and social support satisfaction. The path coefficients showed functional ability having the largest direct effect on participation restriction. The results also showed that more depressive symptoms, low state self-esteem, female gender, older age and living in a residential care facility had a direct effect on participation restriction. The explanatory variables accounted for 71% of the variance in explaining participation restriction. Prediction models have empirical and practical applications such as suggesting important factors to be considered in promoting stroke recovery. The findings suggest that interventions offered over the course of rehabilitation should be aimed at improving functional ability and promoting psychological aspects of recovery. These are likely to enhance stroke survivors resume or maximize their social participation so that they may fulfill productive and positive life roles.
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As network capacity has increased over the past decade, individuals and organisations have found it increasingly appealing to make use of remote services in the form of service-oriented architectures and cloud computing services. Data processed by remote services, however, is no longer under the direct control of the individual or organisation that provided the data, leaving data owners at risk of data theft or misuse. This paper describes a model by which data owners can control the distribution and use of their data throughout a dynamic coalition of service providers using digital rights management technology. Our model allows a data owner to establish the trustworthiness of every member of a coalition employed to process data, and to communicate a machine-enforceable usage policy to every such member.