124 resultados para Generating Relation


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Purpose The purpose of this paper is to explore and compare the asset management policies and practices of six Australian states – New South Wales, Victoria, Queensland, South Australia, Western Australia and Tasmania – to improve understanding of the policy context to best shape policy focus and guidelines. Australian state-wide asset management policies and guidelines are an emergent policy domain, generating a substantial body of knowledge. However, these documents are spread across the layers of government and are therefore largely fragmented and lack coherency. Design/methodology/approach The comparative study is based on the thematic mapping technique using the Leximancer software. Findings Asset management policies and guidelines of New South Wales and Victoria have more interconnected themes as compared to other states in Australia. Moreover, based on the findings, New South Wales has covered most of the key concepts in relation to asset management; the remaining five states are yet to develop a comprehensive and integrated approach to asset management policies and guidelines. Research limitations/implications This review and its findings have provided a number of directions on which government policies can now be better constructed and assessed. In doing so, the paper contributes to a coherent way forward to satisfy national emergent and ongoing asset management challenges. This paper outlines a rigorous analytical methodology to inform specific policy changes. Originality/value This paper provides a basis for further research focused on analyzing the context and processes of asset management guidelines and policies.

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With respect to “shape” marks, there would appear to be a “break”, imposed by the Australian Courts, in the logical conclusion that registration of a shape, which performs a functional purpose, or even further, is indistinguishable from the shape of the item or product, creates a perpetual monopoly in the manufacture of that product.

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Following an initial consultation draft (Turnbull 1999a), the Internal control Working Party of the Institute of Chartered Accountants in England and Wales, chaired by Nigel Turnbull, executive director of Rank Group plc. has published Internal Control: Guidance for Directors of Listed companies Incorporated in the UK (Turnbull, 1999b). The guidance is commonly referred to as the Turnbull Report. This paper outlines the key recommendations of the report and discusses some of its implications, particularly in the context of the increasing emphasis on a broader corporate governance role for audit committees. The paper suggests that the increasing role envisaged of audit committees for example lately in the UK by Turnbull, may generate undue expectations are premised on an unsubstantiated notion of the contribution of audit committees.

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Niklas Luhmann's theory of social systems has been widely influential in the German-speaking countries in the past few decades. However, despite its significance, particularly for organization studies, it is only very recently that Luhmann's work has attracted attention on the international stage as well. This Special Issue is in response to that. In this introductory paper, we provide a systematic overview of Luhmann's theory. Reading his work as a theory about distinction generating and processing systems, we especially highlight the following aspects: (i) Organizations are processes that come into being by permanently constructing and reconstructing themselves by means of using distinctions, which mark what is part of their realm and what not. (ii) Such an organizational process belongs to a social sphere sui generis possessing its own logic, which cannot be traced back to human actors or subjects. (iii) Organizations are a specific kind of social process characterized by a specific kind of distinction: decision, which makes up what is specifically organizational about organizations as social phenomena. We conclude by introducing the papers in this Special Issue. Copyright © 2006 SAGE.

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Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.

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Extensive international research points to an association between changed work arrangements, especially those commonly labelled as contingent work, with adverse occupational health and safety (OHS) outcomes. Research also indicates these work arrangements have weakened or bypassed existing OHS and workers’ compensation regulatory regimes. However, there has been little if any research into how OHS inspectors perceive these issues and how they address them during workplace visits or investigations. Between 2003 and 2007 research was undertaken that entailed detailed documentary and statistical analysis, extended interviews with 170 regulatory managers and inspectors, and observational data collected while accompanying inspectors on 118 ‘typical’ workplace visits. Key findings are that inspectors responsible for a range of industries see altered work arrangements as a serious challenge, especially labour hire (agency work) and subcontracting. Though the law imposes clear obligations, inspectors identified misunderstanding/blameshifting and poor compliance amongst parties to these arrangements. The complexity of these work arrangements also posed logistical challenges to inspectorates.

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In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

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This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.

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Female greater wax moths Galleria mellonella display by wing fanning in response to bursts of ultrasonic calls produced by males. The temporal and spectral characteristics of these calls show some similarities with the echolocation calls of bats that emit frequency-modulated (FM) signals. Female G. mellonella therefore need to distinguish between the attractive signals of male conspecifics, which may lead to mating opportunities, and similar sounds made by predatory bats. We therefore predicted that (1) females would display in response to playbacks of male calls; (2) females would not display in response to playbacks of the calls of echolocating bats (we used the calls of Daubenton's bat Myotis daubentonii as representative of a typical FM echolocating bat); and (3) when presented with male calls and bat calls during the same time block, females would display more when perceived predation risk was lower. We manipulated predation risk in two ways. First, we varied the intensity of bat calls to represent a nearby (high risk) or distant (low risk) bat. Second, we played back calls of bats searching for prey (low risk) and attacking prey (high risk). All predictions were supported, suggesting that female G. mellonella are able to distinguish conspecific male mating calls from bat calls, and that they modify display rate in relation to predation risk. The mechanism (s) by which the moths separate the calls of bat and moth must involve temporal cues. Bat and moth signals differ considerably in duration, and differences in duration could be encoded by the moth's nervous system and used in discrimination.

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Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

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This thesis considers whether the Australian Privacy Commissioner's use of its powers supports compliance with the requirement to 'take reasonable steps' to protect personal information in National Privacy Principle 4 of the Privacy Act 1988 (Cth). Two unique lenses were used. First, the Commissioner's use of powers was assessed against the principles of transparency, balance and vigorousness and secondly against alignment with an industry practice approach to securing information. Following a comprehensive review of publicly available materials, interviews and investigation file records, this thesis found that the Commissioner's use of his powers has not been transparent, balanced or vigorous, nor has it been supportive of an industry practice approach to securing data. Accordingly, it concludes that the Privacy Commissioner's use of its regulatory powers is unlikely to result in any significant improvement to the security of personal information held by organisations in Australia.

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With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.