807 resultados para Torrens system automation


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The delivery of human services occurs through a complex and often volatile system characterised by both competing and cooperating efforts. A recent strategic intention of government has been to integrate disparate service providers and programs into a more effective and efficient system using competitive funding regimes. A program of amalgamation has also been forecast and promoted as a further mechanism by which to link up smaller agencies thus creating economy and efficiency in the scale and scope of their service modes. Despite the current reliance on competitive funding models and amalgamation as the preferred ways forward for the sector little is known about their integrative capacity including their ability to predict outcomes and their consequences : the ‘unknown unknowns’. Drawing on an extensive data set of human services integration initiatives in Queensland, Australia, this paper examines the impact of government policy and service models and the risks arising from the tensions between competition and accountability on the one hand and the established good will and trust on the other. It is argued that unresolved, these tensions can lead to a weakening of the social infrastructure and make the system more vulnerable to inherent systemic risks. The paper finds that government’s efforts to externalise risk to the non-government sector leads to fragmentation of the service system and fractured collaborative capability. These unintended outcomes themselves have the unintended consequence of leaving governments disconnected from the service system and unable to provide the leadership role and direction necessary for sustained integration. Moreover, facilitating such a leadership role is undermined by behaviours that are directly contrary to collective integration models.

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This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

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This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

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Electricity has been the major source of power in most railway systems. Reliable, efficient and safe power distribution to the trains is vitally important to the overall quality of railway service. Like any large-scale engineering system, design, operation and planning of traction power systems rely heavily on computer simulation. This paper reviews the major features on modelling and the general practices for traction power system simulation; and introduces the development of the latest simulation approach with discussions on simulation results and practical applications. Remarks will also be given on the future challenges on traction power system simulation.

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This paper seeks to explore how organisations can effectively use performance management systems (PMS) to monitor collective identities. The monitoring of relationships between identity and an influential PMS—the balanced scorecard (BSC)—are explored. Drawing from identity and management accounting literature, this paper argues that identity products, patternings and processes are commonly positioned, monitored and interpreted through the multiple perspectives and levels of the BSC. Specifically, human, technical and organisational capital under the Learning and Growth perspective of the BSC can incorporate various identity measures that sustain the relative, distinctive and fluid nature of identities. The value of this research is to strengthen the theoretical grounds which position identity as an important dimension of organisational capital in PMS.

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Objective: On-road driving before gaining a valid licence (pre-Licence driving) represents a risk for all road users. Pre-Licence driving among young people who obtained a Provisional licence within an enhanced graduated driver licensing program in Queensland, Australia, was investigated. Methods: Recently-licensed drivers (n = 1032) aged 17-19 years (M = 17.54) completed a survey exploring their driving experiences while on their Learners licence. Six months later, 355 of these drivers completed the same survey exploring their experiences on their Provisional (intermediate) licence. Results: Twelve percent of participants reported pre-Licence driving. Pre-Licence drivers reported significantly more risky driving as Learners and Provisional drivers. Conclusions: Pre-Licence drivers not only place themselves and other road users at risk at the time but also continue to do so through their subsequent risky driving. Pre-licence driving should be discouraged, and parents should be encouraged to monitor car use and the driving behaviour of their children.

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The gastric-derived orexigenic peptide ghrelin affects brain circuits involved in energy balance as well as in reward. Indeed, ghrelin activates an important reward circuit involved in natural- as well as drug-induced reward, the cholinergic-dopaminergic reward link. It has been hypothesized that there is a common reward mechanism for alcohol and sweet substances in both animals and humans. Alcohol dependent individuals have higher craving for sweets than do healthy controls and the hedonic response to sweet taste may, at least in part, depend on genetic factors. Rat selectively bred for high sucrose intake have higher alcohol consumption than non-sucrose preferring rats and vice versa. In the present study a group of alcohol-consuming individuals selected from a population cohort was investigated for genetic variants of the ghrelin signalling system in relation to both their alcohol and sucrose consumption. Moreover, the effects of GHS-R1A antagonism on voluntary sucrose- intake and operant self-administration, as well as saccharin intake were investigated in preclinical studies using rodents. The effects of peripheral grelin administration on sucrose intake were also examined. Here we found associations with the ghrelin gene haplotypes and increased sucrose consumption, and a trend for the same association was seen in the high alcohol consumers. The preclinical data show that a GHS-R1A antagonist reduces the intake and self-administration of sucrose in rats as well as saccharin intake in mice. Further, ghrelin increases the intake of sucrose in rats. Collectively, our data provide a clear indication that the GHS-R1A antagonists reduces and ghrelin increases the intake of rewarding substances and hence, the central ghrelin signalling system provides a novel target for the development of drug strategies to treat addictive behaviours. © 2011 Landgren et al.

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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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Recent surveys of information technology management professionals show that understanding business domains in terms of business productivity and cost reduction potential, knowledge of different vertical industry segments and their information requirements, understanding of business processes and client-facing skills are more critical for Information Systems personnel than ever before. In an attempt to restrucuture the information systems curriculum accordingly, our view it that information systems students need to develop an appreciation for organizational work systems in order to understand the operation and significance of information systems within such work systems.