190 resultados para Pryor, Roger A. (Roger Atkinson), 1828-1919.


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This paper examines the instances and motivations for noble cause corruption perpetrated by NSW police officers. Noble cause corruption occurs when a person tries to produce a just outcome through unjust methods, for example, police manipulating evidence to ensure a conviction of a known offender. Normal integrity regime initiatives are unlikely to halt noble cause corruption as its basis lies in an attempt to do good by compensating for the apparent flaws in an unjust system. This paper suggests that the solution lies in a change of culture through improved leadership and uses the political theories of Roger Myerson to propose a possible solution. Evidence from police officers in transcripts of the Wood Inquiry (1997) are examined to discern their participation in noble cause corruption and their rationalisation of this behaviour. The overall findings are that officers were motivated to indulge in this type of corruption through a desire to produce convictions where they felt the system unfairly worked against their ability to do their job correctly. We have added to the literature by demonstrating that the rewards can be positive. Police are seeking job satisfaction through the ability to convict the guilty. They will be able to do this through better equipment and investigative powers.

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In Golder Associates Pty Ltd v Challen [2012] QDC 11 Samios DCJ recognised a solicitor’s lien over the file for unpaid fees and confirmed that a lien should not be lightly set aside. The decision, which is under appeal, adds to the range of authorities which are now grappling with some of the provisions of the Legal Profession Act 2007 (Qld) (the LPA) relating to costs billing and assessment. These would appear to have been drafted without a great deal of intellectual rigour (cf. Turner v Mitchells Solicitors [2011] QDC 61 at [26]).

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In this 25th year of publication of the Accounting Research Journal we pay tribute to the efforts of the dedicated Editors who have successfully guided and developed the journal since its inception in 1988. After the rapid growth in accounting and finance research in the 1970s and 1980s the absence of outlets in Asia-Pacific region to publish novel, timely and applied research became increasingly apparent. In response to this gap, ARJ’s first volume was published in 1988 by the School of Accountancy at the Queensland Institute of Technology (QIT), which became the Queensland University of Technology (QUT) in the following year. The founding Editor was Myles McGregor-Lowndes and his editorship continued for three years until Scott Holmes took over as Editor in 1991. In 1992, Robert Faff joined Scott Holmes as Joint Editor, and their joint editorship continued for six years until Robert Faff took the reins as Editor in 1998. At that time Scott remained as Associate Editor and the editorial team was joined by Roger Willett as Consulting Editor and Chris Lambert as Associate Editor. This arrangement continued until 2002 when Tim Brailsford was newly appointed as Managing Editor. The editorship returned to QUT in 2008 and was taken on by Chris Ryan with our support as Co-editors. Since 2011 we have been the Joint Editors. Table 1 lists the individuals who have been involved in editing ARJ over the 25-year period and their roles...

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In response to a focus on reading, this paper examines the notion of reading online; as such it uses the term ‘networked reading’ to describe any act of reading in an online or digital environment. In accordance with this notion of ‘networked’ reading, the paper provides a broad introduction to AustLit: the Australian Literature Resource. This is followed by an examination of a suite of services and digital tools (LORE) developed by the Aus-e-Lit project that extends the scope of AustLit records and facilitates links to external resources. The focus of the final section of the paper is on a collection of Full Text resources located within the AustLit subset Children’s Literature Digital Resources (CLDR). It proposes a number of ways in which these texts, and an accompanying anthology of critical articles, can be utilised in classrooms across the Primary, Middle and Senior School spectrum.

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This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

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The objective of the study was to assess, from a health service perspective, whether a systematic program to modify kidney and cardiovascular disease reduced the costs of treating end-stage kidney failure. The participants in the study were 1,800 aboriginal adults with hypertension, diabetes with microalbuminuria or overt albuminuria, and overt albuminuria, living on two islands in the Northern Territory of Australia during 1995 to 2000. Perindopril was the primary treatment agent, and other medications were also used to control blood pressure. Control of glucose and lipid levels were attempted, and health education was offered. Evaluation of program resource use and costs for follow-up periods was done at 3 and 4.7 years. On an intention-to-treat basis, the number of dialysis starts and dialysis-years avoided were estimated by comparing the fate of the treatment group with that of historical control subjects, matched for disease severity, who were followed in the before the treatment program began. For the first three years, an estimated 11.6 person-years of dialysis were avoided, and over 4.7 years, 27.7 person-years of dialysis were avoided. The net cost of the program was 1,210 dollars more per person per year than status quo care, and dialyses avoided gave net savings of 1.0 million dollars at 3 years and 3.4 million dollars at 4.6 years. The treatment program provided significant health benefit and impressive cost savings in dialysis avoided.

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Optimal Asset Maintenance decisions are imperative for efficient asset management. Decision Support Systems are often used to help asset managers make maintenance decisions, but high quality decision support must be based on sound decision-making principles. For long-lived assets, a successful Asset Maintenance decision-making process must effectively handle multiple time scales. For example, high-level strategic plans are normally made for periods of years, while daily operational decisions may need to be made within a space of mere minutes. When making strategic decisions, one usually has the luxury of time to explore alternatives, whereas routine operational decisions must often be made with no time for contemplation. In this paper, we present an innovative, flexible decision-making process model which distinguishes meta-level decision making, i.e., deciding how to make decisions, from the information gathering and analysis steps required to make the decisions themselves. The new model can accommodate various decision types. Three industrial case studies are given to demonstrate its applicability.

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Asset management (AM) processes play an important role in assisting enterprises to manage their assets more efficiently. To visualise and improve AM processes, the processes need to be modelled using certain process modelling methodologies. Understanding the requirements for AM process modelling is essential for selecting or developing effective AM process modelling methodologies. However, little research has been done on analysing the requirements. This paper attempts to fill this gap by investigating the features of AM processes. It is concluded that AM process modelling requires intuitive representation of its processes, ‘fast’ implementation of the process modelling, effective evaluation of the processes and sound system integration.

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The ability to forecast machinery health is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models which attempt to forecast machinery health based on condition data such as vibration measurements. This paper demonstrates how the population characteristics and condition monitoring data (both complete and suspended) of historical items can be integrated for training an intelligent agent to predict asset health multiple steps ahead. The model consists of a feed-forward neural network whose training targets are asset survival probabilities estimated using a variation of the Kaplan–Meier estimator and a degradation-based failure probability density function estimator. The trained network is capable of estimating the future survival probabilities when a series of asset condition readings are inputted. The output survival probabilities collectively form an estimated survival curve. Pump data from a pulp and paper mill were used for model validation and comparison. The results indicate that the proposed model can predict more accurately as well as further ahead than similar models which neglect population characteristics and suspended data. This work presents a compelling concept for longer-range fault prognosis utilising available information more fully and accurately.

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Preventive Maintenance (PM) is often applied to improve the reliability of production lines. A Split System Approach (SSA) based methodology is presented to assist in making optimal PM decisions for serial production lines. The methodology treats a production line as a complex series system with multiple (imperfect) PM actions over multiple intervals. The conditional and overall reliability of the entire production line over these multiple PM intervals are hierarchically calculated using SSA, and provide a foundation for cost analysis. Both risk-related cost and maintenance-related cost are factored into the methodology as either deterministic or random variables. This SSA based methodology enables Asset Management (AM) decisions to be optimised considering a variety of factors including failure probability, failure cost, maintenance cost, PM performance, and the type of PM strategy. The application of this new methodology and an evaluation of the effects of these factors on PM decisions are demonstrated using an example. The results of this work show that the performance of a PM strategy can be measured by its Total Expected Cost Index (TECI). The optimal PM interval is dependent on TECI, PM performance and types of PM strategies. These factors are interrelated. Generally, it was found that a trade-off between reliability and the number of PM actions needs to be made so that one can minimise Total Expected Cost (TEC) for asset maintenance.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

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The Coping Orientation to Problems Experienced is a multidimensional scale designed to assess how people respond to stress. The COPE has been validated in a variety of populations displaying variations in factor structure. However, in terms of mental health populations, it has only been validated in alcohol-dependent samples. This paper investigated the factor structure of the COPE in a sample of adults diagnosed with depression and anxiety. Two hundred and seventy-one patients attending cognitive behaviour therapy for anxiety and depression completed the COPE. Confirmatory factor analysis found a poor fit for both lower order and higher order factors based upon the Lyne and Roger (2000) study. Exploratory factor analyses identified six primary subscales (Active Planning, Social Support, Denial, Acceptance, Disengagement, Restraint) which explained approximately 60% of the variance in coping. These 6 subscales may assist researchers and clinicians to validly measure coping in anxious and depressed adults.

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WHAT: An interactive installation with full body interface, digital projection, multi-touch sensitive screen surfaces, interactive 3D gaming software, motorised dioramas, 4.1 spatial sound & new furniture forms - investigating the cultural dimensions of sustainability through the lens of 'time'. “Time is change, time is finitude. Humans are a finite species. Every decision we make today brings that end closer, or alternatively pushes it further away. Nothing can be neutral”. Tony Fry DETAILS: Each participant/viewer lies comfortably on their back. Directly above them is a semi-transparent Perspex screen that displays projected 3D imagery and is simultaneously sensitive to the lightest of finger touches. Depending upon the ever changing qualities of the projected image on this screen the participant can see through its surface to a series of physical dioramas suspended above, lit by subtle LED spotlighting. This diorama consists of a slowly rotating series of physical environments, which also include several animatronic components, allowing the realtime composition of whimsical ‘landscapes’ of both 'real' and 'virtual' media. Through subtle, non-didactic touch-sensitive interactivity the participant then has influence over both the 3D graphic imagery, the physical movements of the diorama and the 4 channel immersive soundscape, creating an uncanny blend of physical and virtual media. Five speakers positioned around the room deliver a rich interactive soundscape that responds both audibly and physically to interactions.