19 resultados para Life support systems (Space environment)

em University of Queensland eSpace - Australia


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In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors ( defined as members of the dairy and associated communities), especially farm suppliers ( input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, purposive sampling, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

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Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

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In order for policy makers to plan effectively for sustainable development, there is a need for measures of welfare that consider changes in the natural capital stock. Current measures based on conventional national accounting are flawed because they are based solely on flow measures and do not account for environmental effects. In this paper, we use an expanded measure of wealth to estimate the value of natural capital for Queensland. The state's stock of natural capital is valued at A$355.6 billion, of which non-timber forest resources account for 45.3%, ecosystem services 20.0%, and mineral resources 17.6%. This figure is a conservative estimate of the true value since some significant components such as the ecological and life-support functions of the environment are excluded. The estimates highlight the relative importance of different forms of natural capital and can be used to draw the attention of policymakers to the need to give adequate weight to the value of such services in decision-making processes. (c) 2005 Elsevier Ltd. All rights reserved.

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A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

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The consequences of demographic dissimilarity for group trust in work teams was examined in a virtual (computer-mediated) and a face-to-face (FTF) environment. Demographic dissimilarity (based on age, gender, country of birth, enrolled degree) was predicted to be negatively associated with group trust in the FTF environment but not in the computer-mediated environment. Participants worked in small groups on a creative task for 3 consecutive days. In the computer-mediated environment, participants worked on the task for an hour per day. In the FTF environment, participants worked on the task for 20 minutes per day. Partial support was found for the effectiveness of computer-mediated groups in reducing the negative consequences of dissimilarity. Age dissimilarity was negatively related to trust in FTF groups but not in computer-mediated groups. Birthplace dissimilarity was positively related to trust in computer-mediated groups. Implications for the successful management of virtual teams are discussed.

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Over the past 30 years, research in the area of applied behaviour. analysis has led to a rich knowledge and understanding of the variables that influence human behaviour. This understanding and knowledge has given rise to a range of assessment and intervention techniques that have been applied to individuals with challenging behaviour. Interventions have produced changes in the severity and frequency of behaviours such as self-injury, aggression, and property destruction, card have also led to the acquisition of desired behaviours. While behaviour change has been achieved, families have expressed a desire for positive behaviour support approaches that adopt a family,focus. Research and development of support frameworks that emphasise the interrelatedness of family members, and the child with a disability as part of his or her family, have gained prominence in the family systems literature. The present paper reviews some of the behaviourally based research in this area. Through the use of a case illustration, the authors discuss the links between behavioural support and family-centred support systems for children with developmental disabilities. Theoretical and practical implications are considered and areas for future research are highlighted.

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Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

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A growing proportion of women reach older age without having married or having children. Assumptions that these older women are lonely, impoverished, and high users of social and health services are based on little evidence. This paper uses data from the Older cohort of the Australian Longitudinal Study on Women's Health to describe self-reported demographics, physical and emotional health, and use of services among 10,108 women aged 73-78, of whom 2.7% are never-married and childless. The most striking characteristic of this group is their high levels of education, which are associated with fewer reported financial difficulties and higher rates of private health insurance. There are few differences in self-reported physical or emotional health or use of health services between these and other groups of older women. Compared with older married women with children, they make higher use of formal services such as home maintenance and meal services, and are also more likely to provide volunteer services and belong to social groups. Overall, there is no evidence to suggest that these women are a problem group. Rather, it seems that their life experiences and opportunities prepare them for a successful and productive older age. (c) 2005 Elsevier Ltd. All rights reserved.