923 resultados para Controlling feeding practices


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Queensland University of Technology (QUT) is a multidisciplinary university in Brisbane, Queensland, Australia, and has 40,000 students and 1,700 researchers. Notable eResearch infrastructure includes the QUT ePrints repository, Microsoft QUT Research Centre, the OAK (Open Access to Knowledge) Law Project, Cambia and leading research institutes. ---------- The Australian Government, via the Australian National Data Service (ANDS), is funding institutions to identify and describe their research datasets, to develop and populate data repositories and collaborative infrastructure, and to seed the Australian Research Data Commons. QUT is currently broadening its range of research support services, including those to support the management of research data, in recognition of the value of these datasets as products of the research process, and in order to maximize the potential for reuse. QUT is integrating Library and High Performance Computing (HPC) services to achieve its research support goals. ---------- The Library and HPC released an online survey using Key Survey to 1,700 researchers in September 2009. A comprehensive range of eResearch practices and skills was presented for response, and grouped into areas of scholarly communication and open access publishing, using collaborative technologies, data management, data collection and management, computation and visualization tools. Researchers were asked to rate their skill level on each practice. 254 responses were received over two weeks. Eight focus groups were also held with 35 higher degree research (HDR) students and staff to provide additional qualitative feedback. A similar survey was released to 100 support staff and 73 responses were received.---------- Preliminary results from the researcher survey and focus groups indicate a gap between current eResearch practices, and the potential for researchers to engage in eResearch practices. Researchers are more likely to seek advice from their peers, than from support staff. HDR students are more positive about eResearch practices and are more willing to learn new ways of conducting research. An account of the survey methodology, the results obtained, and proposed strategies to embed eResearch practices and skills across and within the research disciplines will be provided.

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We consider the problem of monitoring and controlling the position of herd animals, and view animals as networked agents with natural mobility but not strictly controllable. By exploiting knowledge of individual and herd behavior we would like to apply a vast body of theory in robotics and motion planning to achieving the constrained motion of a herd. In this paper we describe the concept of a virtual fence which applies a stimulus to an animal as a function of its pose with respect to the fenceline. Multiple fence lines can define a region, and the fences can be static or dynamic. The fence algorithm is implemented by a small position-aware computer device worn by the animal, which we refer to as a Smart Collar.We describe a herd-animal simulator, the Smart Collar hardware and algorithms for tracking and controlling animals as well as the results of on-farm experiments with up to ten Smart Collars.

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A virtual fence is created by applying an aversive stimulus to an animal when it approaches a predefined boundary. It is implemented by a small animal-borne computer system with a GPS receiver. This approach allows the implementation of virtual paddocks inside a normal physically-fenced paddock. Since the fence lines are virtual they can be moved by programming to meet the needs of animal or land management. This approach enables us to consider animals as agents with natural mobility that are controllable and to apply a vast body of theory in motion planning. In this paper we describe a herd-animal simulator and physical experiments conducted on a small herd of 10 animals using a Smart Collar. The Smart Collar consists of a GPS, PDA, wireless networking and a sound amplifier. We describe a motion planning algorithm that can move a virtual paddock subject to landscape constraints which is suitable for mustering cows. We present simulation results and data from experiments with 8 cows equipped with Smart Collars.

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Nurse practitioners will become a vital component of the health workforce because of the growing need to manage chronic illness, to deliver effective primary health services, and to manage workforce challenges effectively. In addition, the role of nurse practitioner is an excellent example of increased workforce flexibility and changes to occupational boundaries. This paper draws on an Australasian research project which defined the core role of nurse practitioners, and identified capability as the component of their level of practice that makes their service most useful. We argue that any tendency to write specific protocols to define the limits of nurse practitioner practice will reduce the efficacy of their contribution. The distinction we wish to make in this paper is between guidelines aiming to support practice, and protocols which aim to control practice.