974 resultados para Archaea, operational taxonomic unit


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Retirement village assets are different from traditional residential assets due to their operation in accordance with statutory legislation. Designed for independent living, retirement villages provide either detached or semi-detached residential dwellings with car parking and small private yards with community facilities providing a shared congregational area for village activities and socialising. In essence, the village operator provides the land and buildings to the residents who pay an amount on entry for the right of occupation. On departure from the units an agreed proportion of either the original purchase price or the sale price is paid to the outgoing resident. As ongoing levies are typically offset by ongoing operational expenses the market value of the operator's interest in the retirement village is therefore predominantly based upon the estimated future income from deferred management fees and capital gain upon roll-over receivable by the operator in accordance with the respective residency agreements. Given the lumpiness of these payments, there is general acceptance that the most appropriate approach to valuation is through discounted cash flow (DCF) analysis. There is however inconsistency between valuers across Australia in how they undertake their DCF analysis, leading to differences in reported values and subsequent confusion among users of valuation services. To give guidance to valuers and enhance confidence from users of valuation services this paper investigates the five major elements of DCF methodology, namely cash flows, escalation factors, holding period, terminal value and discount rate.

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Variable Speed Limits (VSL) is a control tool of Intelligent Transportation Systems (ITS) which can enhance traffic safety and which has the potential to contribute to traffic efficiency. This study presents the results of a calibration and operational analysis of a candidate VSL algorithm for high flow conditions on an urban motorway of Queensland, Australia. The analysis was done using a framework consisting of a microscopic simulation model combined with runtime API and a proposed efficiency index. The operational analysis includes impacts on speed-flow curve, travel time, speed deviation, fuel consumption and emission.

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This presentation discusses some of the general issues relating to the classification of UAS for the purposes of defining and promulgating safety regulations. One possible approach for the definition of a classification scheme for UAS Type Certification Categories reviewed.

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Organisations are increasingly investing in complex technological innovations, such as enterprise information systems, with the aim of improving the operation of the business, and in this way gaining competitive advantage. However, the implementation of technological innovations tends to have an excessive focus on either technology innovation effectiveness, or the resulting operational effectiveness. Focusing on either one of them is detrimental to long-term performance. Cross-functional teams have been used by many organisations as a way of involving expertise from different functional areas in the implementation of technologies. The role of boundary spanning actors is discussed as they bring a common language to the cross-functional teams. Multiple regression analysis has been used to identify the structural relationships and provide an explanation for the influence of cross-functional teams, technology innovation effectiveness and operational effectiveness in the continuous improvement of operational performance. The findings indicate that cross functional teams have an indirect influence on continuous improvement of operational performance through the alignment between technology innovation effectiveness and operational effectiveness.

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CCTV and surveillance networks are increasingly being used for operational as well as security tasks. One emerging area of technology that lends itself to operational analytics is soft biometrics. Soft biometrics can be used to describe a person and detect them throughout a sparse multi-camera network. This enables them to be used to perform tasks such as determining the time taken to get from point to point, and the paths taken through an environment by detecting and matching people across disjoint views. However, in a busy environment where there are 100's if not 1000's of people such as an airport, attempting to monitor everyone is highly unrealistic. In this paper we propose an average soft biometric, that can be used to identity people who look distinct, and are thus suitable for monitoring through a large, sparse camera network. We demonstrate how an average soft biometric can be used to identify unique people to calculate operational measures such as the time taken to travel from point to point.

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Between 2001 and 2005, the US airline industry faced financial turmoil. At the same time, the European airline industry entered a period of substantive deregulation. This period witnessed opportunities for low-cost carriers to become more competitive in the market as a result of these combined events. To help assess airline performance in the aftermath of these events, this paper provides new evidence of technical efficiency for 42 national and international airlines in 2006 using the data envelopment analysis (DEA) bootstrap approach first proposed by Simar and Wilson (J Econ, 136:31-64, 2007). In the first stage, technical efficiency scores are estimated using a bootstrap DEA model. In the second stage, a truncated regression is employed to quantify the economic drivers underlying measured technical efficiency. The results highlight the key role played by non-discretionary inputs in measures of airline technical efficiency.

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Knowledge base is one of the emerging concepts in the Knowledge Management area. As there exists no agreed- upon standard definition of a knowledge base, this paper defines a knowledge base in terms of our research of Enterprise Systems (ES). The knowledge base is defined with reference to Learning Network Theory. Using this theoretical framework, we investigate the roles of management and operational staff in organisations and how their interactions can create a better ES-knowledge base to contribute to ES success. We focus on the post- implementation phase of ES as part of the ES lifecycle. Our findings will facilitate future research directions and contribute to better understandings of how the knowledge base can be integrated and how this integration leads to Enterprise System success.

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Research has shown that people with a mental illness are an at-risk group for sexually transmitted infections. A programme for preventing risk behaviours for sexually transmitted infections among people with psychiatric disorder was designed and implemented by mental health occupational therapists. This programme used an interactive didactic approach to provide education and awareness of sexual health issues to acute psychiatric inpatients. Twenty-four participants completed a sexual health questionnaire, which was designed for this study, both before and after attending the programme. They had a higher than expected knowledge of sexually transmitted infections and safe sex practices at pre-test. The education programme resulted in a statistically significant but modest increase in sexual health knowledge. These findings indicate that there are benefits in providing sexual health education to clients with a mental illness. Further programme development should be directed towards sexual health decision-making and behaviour change.

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Fiber Bragg grating (FBG) sensor technology has been attracting substantial industrial interests for the last decade. FBG sensors have seen increasing acceptance and widespread use for structural sensing and health monitoring applications in composites, civil engineering, aerospace, marine, oil & gas, and smart structures. One transportation system that has been benefitted tremendously from this technology is railways, where it is of the utmost importance to understand the structural and operating conditions of rails as well as that of freight and passenger service cars to ensure safe and reliable operation. Fiberoptic sensors, mostly in the form of FBGs, offer various important characteristics, such as EMI/RFI immunity, multiplexing capability, and very long-range interrogation (up to 230 km between FBGs and measurement unit), over the conventional electrical sensors for the distinctive operational conditions in railways. FBG sensors are unique from other types of fiber-optic sensors as the measured information is wavelength-encoded, which provides self-referencing and renders their signals less susceptible to intensity fluctuations. In addition, FBGs are reflective sensors that can be interrogated from either end, providing redundancy to FBG sensing networks. These two unique features are particularly important for the railway industry where safe and reliable operations are the major concerns. Furthermore, FBGs are very versatile and transducers based on FBGs can be designed to measure a wide range of parameters such as acceleration and inclination. Consequently, a single interrogator can deal with a large number of FBG sensors to measure a multitude of parameters at different locations that spans over a large area.

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Mandatory data breach notification laws are a novel and potentially important legal instrument regarding organisational protection of personal information. These laws require organisations that have suffered a data breach involving personal information to notify those persons that may be affected, and potentially government authorities, about the breach. The Australian Law Reform Commission (ALRC) has proposed the creation of a mandatory data breach notification scheme, implemented via amendments to the Privacy Act 1988 (Cth). However, the conceptual differences between data breach notification law and information privacy law are such that it is questionable whether a data breach notification scheme can be solely implemented via an information privacy law. Accordingly, this thesis by publications investigated, through six journal articles, the extent to which data breach notification law was conceptually and operationally compatible with information privacy law. The assessment of compatibility began with the identification of key issues related to data breach notification law. The first article, Stakeholder Perspectives Regarding the Mandatory Notification of Australian Data Breaches started this stage of the research which concluded in the second article, The Mandatory Notification of Data Breaches: Issues Arising for Australian and EU Legal Developments (‘Mandatory Notification‘). A key issue that emerged was whether data breach notification was itself an information privacy issue. This notion guided the remaining research and focused attention towards the next stage of research, an examination of the conceptual and operational foundations of both laws. The second article, Mandatory Notification and the third article, Encryption Safe Harbours and Data Breach Notification Laws did so from the perspective of data breach notification law. The fourth article, The Conceptual Basis of Personal Information in Australian Privacy Law and the fifth article, Privacy Invasive Geo-Mashups: Privacy 2.0 and the Limits of First Generation Information Privacy Laws did so for information privacy law. The final article, Contextualizing the Tensions and Weaknesses of Information Privacy and Data Breach Notification Laws synthesised previous research findings within the framework of contextualisation, principally developed by Nissenbaum. The examination of conceptual and operational foundations revealed tensions between both laws and shared weaknesses within both laws. First, the distinction between sectoral and comprehensive information privacy legal regimes was important as it shaped the development of US data breach notification laws and their subsequent implementable scope in other jurisdictions. Second, the sectoral versus comprehensive distinction produced different emphases in relation to data breach notification thus leading to different forms of remedy. The prime example is the distinction between market-based initiatives found in US data breach notification laws compared to rights-based protections found in the EU and Australia. Third, both laws are predicated on the regulation of personal information exchange processes even though both laws regulate this process from different perspectives, namely, a context independent or context dependent approach. Fourth, both laws have limited notions of harm that is further constrained by restrictive accountability frameworks. The findings of the research suggest that data breach notification is more compatible with information privacy law in some respects than others. Apparent compatibilities clearly exist as both laws have an interest in the protection of personal information. However, this thesis revealed that ostensible similarities are founded on some significant differences. Data breach notification law is either a comprehensive facet to a sectoral approach or a sectoral adjunct to a comprehensive regime. However, whilst there are fundamental differences between both laws they are not so great to make them incompatible with each other. The similarities between both laws are sufficient to forge compatibilities but it is likely that the distinctions between them will produce anomalies particularly if both laws are applied from a perspective that negates contextualisation.

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Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several differ- ent approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational struc- tures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments.