75 resultados para Arun Upneja


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Generally, major public funding is invested in civil infrastructure assets. The efficiency and comfort level of expected and actual living standards is largely dependant on the management strategies of these assets. Buildings are one of the major & vital assets, which need to be maintained primarily to ensure their functionality by effective & efficient delivery of services and to optimise economic benefits. In Australia, billions of dollars are spent annually managing and maintaining built assets. These assets make up the social and economic infrastructure, which facilitate the essential services to public and business. Buildings are one of the prime & fundamental assets, which need to be managed effectively and efficiently to ensure that related services are delivered economically and sustainably

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This paper compares and reviews the recommendations and contents of the guide for the design and construction of externally bonded FRP systems for strengthening concrete structures reported by ACI committee 440 and technical report of Externally bonded FRP reinforcement for RC structures (FIB 14) in application of carbon fiber reinforced polymer (CFRP) composites in strengthening of an aging reinforced concrete headstock. The paper also discusses the background, limitations, strengthening for flexure and shear, and other related issues in use of FRP for strengthening of a typical reinforced concrete headstock structure such as durability, de-bonding, strengthening limits, fire and environmental conditions. A case study of strengthening of a bridge headstock using FRP composites is presented as a worked example in order to illustrate and compare the differences between these two design guidelines when used in conjunction with the philosophy of the Austroads (1992) bridge design code.

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A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.

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This paper presents a comparative study of primarily Australian (and limited international) practices and guidelines on Buildings Asset Management (BAM). The objective of this study was to identify potential gaps in current practices and potential areas of research for further improvement. The paper starts with an overview of BAM. Later sections cover current BAM practices and guidelines across different states of Australia; give a limited overview of international practices and concludes with the authors’ observations.

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The study will cross-fertilise Information Systems (IS) and Services Marketing ideas through reconceptualising the information system as a service (ISaaS). The study addresses known limitations of arguably the two most significant dependent variables in these disciplines - Information System Success or IS-Impact, and Service Quality. Planned efforts to synthesise analogous conceptions across these disciplines, are expected to force a deeper theoretical understanding of the broad notions of success, quality, value and satisfaction and their interrelations. The aims of this research are to: (1) yield a conceptually superior and more extensively validated IS success measurement model, and (2) develop and operationalise a more rigorously validated Service Quality measurement model, while extending the ‘service’ notion to ‘operational computer-based information systems in organisations’. In the development of the new models the study will address contemporary validation issues.

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This is a video of the first of a seminar series which took place 10th February 2010. The presentations showcase how QUT researchers engage with new technology and techniques when conducting research. This sharing of eresearch experience resulted in great feedback from colleagues attending the presentations. Welcome – Prof Arun Sharma Presentations Prof Christian Langton, Prof Edward Chung, Assoc Prof Axel Bruns, Prof David Kavanagh, Prof Paul Roe, Martin Borchert, Dr Kirsty Kitto, Prof Robin Drogemuller, Prof Peter Corke, Assoc Prof Marcus Foth, Close – Prof Tom Cochrane.

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Local governments are service driven rather than asset driven. Understanding this distinction is critical to ensuring that community needs are appropriately addressed. Translating community needs and desires into infrastructure is a complex yet little understood process. In this paper, we look at two case studies that explore the interface between service outcomes and the specification of performance requirements for the assets. The two case studies we look at are: a public health issue resulting from inadequate public amenities in a beach resort and the prioritisation of maintenance work in a world of increasing service demands and declining funding. The case studies all use the same investment logic mapping framework to establish clear drivers as to the problem that councils are responding to in delivering their services. The key to the framework is the separation of concern between service management and asset management.

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Building for a sustainable environment requires sustainable infrastructure assets. Infrastructure capacity management is the process of ensuring optimal provision of such infrastructure assets. Effectiveness in this process will enable the infrastructure asset owners and its stakeholders to receive full value on their investment. Business research has shown that an organisation can only achieve business value when it has the right capabilities. This paradigm can also be applied to infrastructure capacity management. With limited access to resources, the challenge for infrastructure organisations is to identify and develop core capabilities to enable infrastructure capacity management. This chapter explores the concept of capability and identifies the core capability needed in infrastructure capacity management. Through a case study of the Port of Brisbane, this chapter shows that infrastructure organisations must develop their intelligence gathering capability to effectively manage the capacity of their infrastructure assets.

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Road agencies require comprehensive, relevan and quality data describing their road assets to support their investment decisions. An investment decision support system for raod maintenance and rehabilitation mainly comprise three important supporting elements namely: road asset data, decision support tools and criteria for decision-making. Probability-based methods have played a crucial role in helping decision makers understand the relationship among road related data, asset performance and uncertainties in estimating budgets/costs for road management investment. This paper presents applications of the probability-bsed method for road asset management.

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A one-sided classifier for a given class of languages converges to 1 on every language from the class and outputs 0 infinitely often on languages outside the class. A two-sided classifier, on the other hand, converges to 1 on languages from the class and converges to 0 on languages outside the class. The present paper investigates one-sided and two-sided classification for classes of recursive languages. Theorems are presented that help assess the classifiability of natural classes. The relationships of classification to inductive learning theory and to structural complexity theory in terms of Turing degrees are studied. Furthermore, the special case of classification from only positive data is also investigated.

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While it is commonly accepted that computability on a Turing machine in polynomial time represents a correct formalization of the notion of a feasibly computable function, there is no similar agreement on how to extend this notion on functionals, that is, what functionals should be considered feasible. One possible paradigm was introduced by Mehlhorn, who extended Cobham's definition of feasible functions to type 2 functionals. Subsequently, this class of functionals (with inessential changes of the definition) was studied by Townsend who calls this class POLY, and by Kapron and Cook who call the same class basic feasible functionals. Kapron and Cook gave an oracle Turing machine model characterisation of this class. In this article, we demonstrate that the class of basic feasible functionals has recursion theoretic properties which naturally generalise the corresponding properties of the class of feasible functions, thus giving further evidence that the notion of feasibility of functionals mentioned above is correctly chosen. We also improve the Kapron and Cook result on machine representation.Our proofs are based on essential applications of logic. We introduce a weak fragment of second order arithmetic with second order variables ranging over functions from NN which suitably characterises basic feasible functionals, and show that it is a useful tool for investigating the properties of basic feasible functionals. In particular, we provide an example how one can extract feasible programs from mathematical proofs that use nonfeasible functions.

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In the terminology of Logic programming, current search engines answer Sigma1 queries (formulas of the form where is a boolean combination of attributes). Such a query is determined by a particular sequence of keywords input by a user. In order to give more control to users, search engines will have to tackle more expressive queries, namely, Sigma2 queries (formulas of the form ). The purpose of the talk is to examine which directions could be explored in order to move towards more expressive languages, more powerful search engines, and the benefits that users should expect.

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In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty, and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exists where the more mind changes the learner is willing to accept, the lesser the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.

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The topic of the present work is to study the relationship between the power of the learning algorithms on the one hand, and the expressive power of the logical language which is used to represent the problems to be learned on the other hand. The central question is whether enriching the language results in more learning power. In order to make the question relevant and nontrivial, it is required that both texts (sequences of data) and hypotheses (guesses) be translatable from the “rich” language into the “poor” one. The issue is considered for several logical languages suitable to describe structures whose domain is the set of natural numbers. It is shown that enriching the language does not give any advantage for those languages which define a monadic second-order language being decidable in the following sense: there is a fixed interpretation in the structure of natural numbers such that the set of sentences of this extended language true in that structure is decidable. But enriching the original language even by only one constant gives an advantage if this language contains a binary function symbol (which will be interpreted as addition). Furthermore, it is shown that behaviourally correct learning has exactly the same power as learning in the limit for those languages which define a monadic second-order language with the property given above, but has more power in case of languages containing a binary function symbol. Adding the natural requirement that the set of all structures to be learned is recursively enumerable, it is shown that it pays o6 to enrich the language of arithmetics for both finite learning and learning in the limit, but it does not pay off to enrich the language for behaviourally correct learning.