981 resultados para Torrens system automation


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This paper examines some of the central global ethical and governance challenges of climate change and carbon emis-sions reduction in relation to globalization, the “global financial crisis” (GFC), and unsustainable conceptions of the “good life”, and argues in favour of the development of a global carbon “integrity system”. It is argued that a funda-mental driver of our climate problems is the incipient spread of an unsustainable Western version of the “good life”, where resource-intensive, high-carbon western lifestyles, although frequently criticized as unsustainable and deeply unsatisfying, appear to have established an unearned ethical legitimacy. While the ultimate solution to climate change is the development of low carbon lifestyles, the paper argues that it is also important that economic incentives support and stimulate that search: the sustainable versions of the good life provide an ethical pull, whilst the incentives provide an economic push. Yet, if we are going to secure sustainable low carbon lifestyles, it is argued, we need more than the ethical pull and the economic push. Each needs to be institutionalized—built into the governance of global, regional, national, sub-regional, corporate and professional institutions. Where currently weakness in each exacerbates the weaknesses in others, it is argued that governance reform is required in all areas supporting sustainable, low carbon versions of the good life.

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For the 2005 season, Mackay Sugar and its growers agreed to implement a new cane payment system. The aim of the new system was to better align the business drivers between the mill and its growers and as a result improve business decision making. The technical basis of the new cane payment system included a fixed sharing of the revenue from sugar cane between the mill and growers. Further, the new system replaced the CCS formula with a new estimate of recoverable sugar (PRS) and introduced NIR for payment analyses. Significant mill and grower consultation processes led to the agreement to implement the new system in 2005 and this consultative approach has been reflected in two seasons of successful operation.

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Micro aerial vehicles (MAVs) are a rapidly growing area of research and development in robotics. For autonomous robot operations, localization has typically been calculated using GPS, external camera arrays, or onboard range or vision sensing. In cluttered indoor or outdoor environments, onboard sensing is the only viable option. In this paper we present an appearance-based approach to visual SLAM on a flying MAV using only low quality vision. Our approach consists of a visual place recognition algorithm that operates on 1000 pixel images, a lightweight visual odometry algorithm, and a visual expectation algorithm that improves the recall of place sequences and the precision with which they are recalled as the robot flies along a similar path. Using data gathered from outdoor datasets, we show that the system is able to perform visual recognition with low quality, intermittent visual sensory data. By combining the visual algorithms with the RatSLAM system, we also demonstrate how the algorithms enable successful SLAM.