325 resultados para Line importance evaluation


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This study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable et al, 2006). IS-Impact is defined as "a measure at a point in time, of the stream of net benefits from the IS [Information System], to date and anticipated, as perceived by all key-user-groups" (Gable Sedera and Chan, 2008). Track efforts have yielded the bicameral IS-Impact measurement model; the "impact" half includes Organizational-Impact and Individual-Impact dimensions; the "quality" half includes System-Quality and Information-Quality dimensions. The IS-Impact model, by design, is intended to be robust, simple and generalisable, to yield results that are comparable across time, stakeholders, different systems and system contexts. The model and measurement approach employs perceptual measures and an instrument that is relevant to key stakeholder groups, thereby enabling the combination or comparison of stakeholder perspectives. Such a validated and widely accepted IS-Impact measurement model has both academic and practical value. It facilitates systematic operationalisation of a main dependent variable in research (IS-Impact), which can also serve as an important independent variable. For IS management practice it provides a means to benchmark and track the performance of information systems in use. From examination of the literature, the study proposes that IS-Impact is an Analytic Theory. Gregor (2006) defines Analytic Theory simply as theory that ‘says what is’, base theory that is foundational to all other types of theory. The overarching research question thus is "Does IS-Impact positively manifest the attributes of Analytic Theory?" In order to address this question, we must first answer the question "What are the attributes of Analytic Theory?" The study identifies the main attributes of analytic theory as: (1) Completeness, (2) Mutual Exclusivity, (3) Parsimony, (4) Appropriate Hierarchy, (5) Utility, and (6) Intuitiveness. The value of empirical research in Information Systems is often assessed along the two main dimensions - rigor and relevance. Those Analytic Theory attributes associated with the ‘rigor’ of the IS-Impact model; namely, completeness, mutual exclusivity, parsimony and appropriate hierarchy, have been addressed in prior research (e.g. Gable et al, 2008). Though common tests of rigor are widely accepted and relatively uniformly applied (particularly in relation to positivist, quantitative research), attention to relevance has seldom been given the same systematic attention. This study assumes a mainly practice perspective, and emphasises the methodical evaluation of the Analytic Theory ‘relevance’ attributes represented by the Utility and Intuitiveness of the IS-Impact model. Thus, related research questions are: "Is the IS-Impact model intuitive to practitioners?" and "Is the IS-Impact model useful to practitioners?" March and Smith (1995), identify four outputs of Design Science: constructs, models, methods and instantiations (Design Science research may involve one or more of these). IS-Impact can be viewed as a design science model, composed of Design Science constructs (the four IS-Impact dimensions and the two model halves), and instantiations in the form of management information (IS-Impact data organised and presented for management decision making). In addition to methodically evaluating the Utility and Intuitiveness of the IS-Impact model and its constituent constructs, the study aims to also evaluate the derived management information. Thus, further research questions are: "Is the IS-Impact derived management information intuitive to practitioners?" and "Is the IS-Impact derived management information useful to practitioners? The study employs a longitudinal design entailing three surveys over 4 years (the 1st involving secondary data) of the Oracle-Financials application at QUT, interspersed with focus groups involving senior financial managers. The study too entails a survey of Financials at four other Australian Universities. The three focus groups respectively emphasise: (1) the IS-Impact model, (2) the 2nd survey at QUT (descriptive), and (3) comparison across surveys within QUT, and between QUT and the group of Universities. Aligned with the track goal of producing IS-Impact scores that are highly comparable, the study also addresses the more specific utility-related questions, "Is IS-Impact derived management information a useful comparator across time?" and "Is IS-Impact derived management information a useful comparator across universities?" The main contribution of the study is evidence of the utility and intuitiveness of IS-Impact to practice, thereby further substantiating the practical value of the IS-Impact approach; and also thereby motivating continuing and further research on the validity of IS-Impact, and research employing the ISImpact constructs in descriptive, predictive and explanatory studies. The study also has value methodologically as an example of relatively rigorous attention to relevance. A further key contribution is the clarification and instantiation of the full set of analytic theory attributes.

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This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

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Hydrocarbon spills on roads are a major safety concern for the driving public and can have severe cost impacts both on pavement maintenance and to the economy through disruption to services. The time taken to clean-up spills and re-open roads in a safe driving condition is an issue of increasing concern given traffic levels on major urban arterials. Thus, the primary aim of the research was to develop a sorbent material that facilitates rapid clean-up of road spills. The methodology involved extensive research into a range of materials (organic, inorganic and synthetic sorbents), comprehensive testing in the laboratory, scale-up and field, and product design (i.e. concept to prototype). The study also applied chemometrics to provide consistent, comparative methods of sorbent evaluation and performance. In addition, sorbent materials at every stage were compared against a commercial benchmark. For the first time, the impact of diesel on asphalt pavement has been quantified and assessed in a systematic way. Contrary to conventional thinking and anecdotal observations, the study determined that the action of diesel on asphalt was quite rapid (i.e. hours rather than weeks or months). This significant finding demonstrates the need to minimise the impact of hydrocarbon spills and the potential application of the sorbent option. To better understand the adsorption phenomenon, surface characterisation techniques were applied to selected sorbent materials (i.e. sand, organo-clay and cotton fibre). Brunauer Emmett Teller (BET) and thermal analysis indicated that the main adsorption mechanism for the sorbents occurred on the external surface of the material in the diffusion region (sand and organo-clay) and/or capillaries (cotton fibre). Using environmental scanning electron microscopy (ESEM), it was observed that adsorption by the interfibre capillaries contributed to the high uptake of hydrocarbons by the cotton fibre. Understanding the adsorption mechanism for these sorbents provided some guidance and scientific basis for the selection of materials. The study determined that non-woven cotton mats were ideal sorbent materials for clean-up of hydrocarbon spills. The prototype sorbent was found to perform significantly better than the commercial benchmark, displaying the following key properties: • superior hydrocarbon pick-up from the road pavement; • high hydrocarbon retention capacity under an applied load; • adequate field skid resistance post treatment; • functional and easy to use in the field (e.g. routine handling, transportation, application and recovery); • relatively inexpensive to produce due to the use of raw cotton fibre and simple production process; • environmentally friendly (e.g. renewable materials, non-toxic to environment and operators, and biodegradable); and • rapid response time (e.g. two minutes total clean-up time compared with thirty minutes for reference sorbents). The major outcomes of the research project include: a) development of a specifically designed sorbent material suitable for cleaning up hydrocarbon spills on roads; b) submission of patent application (serial number AU2005905850) for the prototype product; and c) preparation of Commercialisation Strategy to advance the sorbent product to the next phase (i.e. R&D to product commercialisation).

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Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

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A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented