961 resultados para Probabilistic choice models


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Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

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The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.

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Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

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Management of groundwater systems requires realistic conceptual hydrogeological models as a framework for numerical simulation modelling, but also for system understanding and communicating this to stakeholders and the broader community. To help overcome these challenges we developed GVS (Groundwater Visualisation System), a stand-alone desktop software package that uses interactive 3D visualisation and animation techniques. The goal was a user-friendly groundwater management tool that could support a range of existing real-world and pre-processed data, both surface and subsurface, including geology and various types of temporal hydrological information. GVS allows these data to be integrated into a single conceptual hydrogeological model. In addition, 3D geological models produced externally using other software packages, can readily be imported into GVS models, as can outputs of simulations (e.g. piezometric surfaces) produced by software such as MODFLOW or FEFLOW. Boreholes can be integrated, showing any down-hole data and properties, including screen information, intersected geology, water level data and water chemistry. Animation is used to display spatial and temporal changes, with time-series data such as rainfall, standing water levels and electrical conductivity, displaying dynamic processes. Time and space variations can be presented using a range of contouring and colour mapping techniques, in addition to interactive plots of time-series parameters. Other types of data, for example, demographics and cultural information, can also be readily incorporated. The GVS software can execute on a standard Windows or Linux-based PC with a minimum of 2 GB RAM, and the model output is easy and inexpensive to distribute, by download or via USB/DVD/CD. Example models are described here for three groundwater systems in Queensland, northeastern Australia: two unconfined alluvial groundwater systems with intensive irrigation, the Lockyer Valley and the upper Condamine Valley, and the Surat Basin, a large sedimentary basin of confined artesian aquifers. This latter example required more detail in the hydrostratigraphy, correlation of formations with drillholes and visualisation of simulation piezometric surfaces. Both alluvial system GVS models were developed during drought conditions to support government strategies to implement groundwater management. The Surat Basin model was industry sponsored research, for coal seam gas groundwater management and community information and consultation. The “virtual” groundwater systems in these 3D GVS models can be interactively interrogated by standard functions, plus production of 2D cross-sections, data selection from the 3D scene, rear end database and plot displays. A unique feature is that GVS allows investigation of time-series data across different display modes, both 2D and 3D. GVS has been used successfully as a tool to enhance community/stakeholder understanding and knowledge of groundwater systems and is of value for training and educational purposes. Projects completed confirm that GVS provides a powerful support to management and decision making, and as a tool for interpretation of groundwater system hydrological processes. A highly effective visualisation output is the production of short videos (e.g. 2–5 min) based on sequences of camera ‘fly-throughs’ and screen images. Further work involves developing support for multi-screen displays and touch-screen technologies, distributed rendering, gestural interaction systems. To highlight the visualisation and animation capability of the GVS software, links to related multimedia hosted online sites are included in the references.

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Purpose: The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone for the assessment of osteoporosis follows a parabolic-type dependence with bone volume fraction; having minima values corresponding to both entire bone and entire marrow. Langton has recently proposed that the primary BUA mechanism may be significant phase interference due to variations in propagation transit time through the test sample as detected over the phase-sensitive surface of the receive ultrasound transducer. This fundamentally simple concept assumes that the propagation of ultrasound through a complex solid : liquid composite sample such as cancellous bone may be considered by an array of parallel ‘sonic rays’. The transit time of each ray is defined by the proportion of bone and marrow propagated, being a minimum (tmin) solely through bone and a maximum (tmax) solely through marrow. A Transit Time Spectrum (TTS), ranging from tmin to tmax, may be defined describing the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit time over the surface of the receive ultrasound transducer. Phase interference may result from interaction of ‘sonic rays’ of differing transit times. The aim of this study was to test the hypothesis that there is a dependence of phase interference upon the lateral inhomogenity of transit time by comparing experimental measurements and computer simulation predictions of ultrasound propagation through a range of relatively simplistic solid:liquid models exhibiting a range of lateral inhomogeneities. Methods: A range of test models was manufactured using acrylic and water as surrogates for bone and marrow respectively. The models varied in thickness in one dimension normal to the direction of propagation, hence exhibiting a range of transit time lateral inhomogeneities, ranging from minimal (single transit time) to maximal (wedge; ultimately the limiting case where each sonic ray has a unique transit time). For the experimental component of the study, two unfocused 1 MHz ¾” broadband diameter transducers were utilized in transmission mode; ultrasound signals were recorded for each of the models. The computer simulation was performed with Matlab, where the transit time and relative amplitude of each sonic ray was calculated. The transit time for each sonic ray was defined as the sum of transit times through acrylic and water components. The relative amplitude considered the reception area for each sonic ray along with absorption in the acrylic. To replicate phase-sensitive detection, all sonic rays were summed and the output signal plotted in comparison with the experimentally derived output signal. Results: From qualtitative and quantitative comparison of the experimental and computer simulation results, there is an extremely high degree of agreement of 94.2% to 99.0% between the two approaches, supporting the concept that propagation of an ultrasound wave, for the models considered, may be approximated by a parallel sonic ray model where the transit time of each ray is defined by the proportion of ‘bone’ and ‘marrow’. Conclusions: This combined experimental and computer simulation study has successfully demonstrated that lateral inhomogeneity of transit time has significant potential for phase interference to occur if a phase-sensitive ultrasound receive transducer is implemented as in most commercial ultrasound bone analysis devices.

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Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

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Process modeling grammars are used to create scripts of a business domain that a process-aware information system is intended to support. A key grammatical construct of such grammars is known as a Gateway. A Gateway construct is used to describe scenarios in which the workflow of a process diverges or converges according to relevant conditions. Gateway constructs have been subjected to much academic discussion about their meaning, role and usefulness, and have been linked to both process-modeling errors and process-model understandability. This paper examines perceptual discriminability effects of Gateway constructs on an individual's abilities to interpret process models. We compare two ways of expressing two convergence and divergence patterns – Parallel Split and Simple Merge – implemented in a process modeling grammar. On the basis of an experiment with 98 students, we provide empirical evidence that Gateway constructs aid the interpretation of process models due to a perceptual discriminability effect, especially when models are complex. We discuss the emerging implications for research and practice, in terms of revisions to grammar specifications, guideline development and design choices in process modeling.

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The configuration of comprehensive Enterprise Systems to meet the specific requirements of an organisation up to today is consuming significant resources. The results of failing implementation projects are severe and may even threaten the organisation’s existence. This paper proposes a method which aims at increasing the efficiency of Enterprise Systems implementations. First, we argue that existing process modelling languages that feature different degrees of abstraction for different user groups exist and are used for different purposes which makes it necessary to integrate them. We describe how to do this using the meta models of the involved languages. Second, we motivate that an integrated process model based on the integrated meta model needs to be configurable and elaborate on the mechanisms by which this model configuration can be achieved. We introduce a business example using SAP modelling techniques to illustrate the proposed method.

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Biological systems exhibit a wide range of contextual effects, and this often makes it difficult to construct valid mathematical models of their behaviour. In particular, mathematical paradigms built upon the successes of Newtonian physics make assumptions about the nature of biological systems that are unlikely to hold true. After discussing two of the key assumptions underlying the Newtonian paradigm, we discuss two key aspects of the formalism that extended it, Quantum Theory (QT). We draw attention to the similarities between biological and quantum systems, motivating the development of a similar formalism that can be applied to the modelling of biological processes.

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The term Design Led Innovation is emerging as a fundamental business process, which is rapidly being adopted by large as well as small to medium sized firms. The value that design brings to an organisation is a different way of thinking, of framing situations and possibilities, doing things and tackling problems: essentially a cultural transformation of the way the firm undertakes its business. Being Design Led is increasingly being seen by business as a driver of company growth, allowing firms to provide a strong point of difference to its stakeholders. Achieving this Design Led process, requires strong leadership to enable the organisation to develop a clear vision for top line growth. Specifically, based on deep customer insights and expanded through customer and stakeholder engagements, the outcomes of which are then adopted by all aspects of the business. To achieve this goal, several tools and processes are available, which need to be linked to new organisational capabilities within a business transformation context. The Design Led Innovation Team focuses on embedding tools and processes within an organisation and matching this with design leadership qualities to enable companies to create breakthrough innovation and achieve sustained growth, through ultimately transforming their business model. As all information for these case studies was derived from publicly accessed data, this resource is not intended to be used as reference material, but rather is a learning tool for designers to begin to consider and explore businesses at a strategic level. It is not the results that are key, but rather the process and philosophies that were used to create these case studies and disseminate this way of thinking amongst the design community. It is this process of unpacking a business guided by the framework of Osterwalder’s Business Model Canvas* which provides an important tool for designers to gain a greater perspective of a company’s true innovation potential.

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Meanings and descriptions of menopause have shifted focus over the past century and a half; more particularly the past sixty years has seen a shift from descriptions of hormone decline and its relation to ageing, femininity and symptoms of menopause since the 1960's to the possibility for preventive medicine afforded by menopause. Medicine is not a static field in its construction of menopause. It has changed, not least by its engagement (positively or negatively) with critique from both within (epidemiological) and without (feminist and social sciences). In this review we identify three recent changes: (1) Increasing concern with women's decision-making. (2) The emergence from within medicine of the rejection of the use of language which defines menopause as a condition of deficiency. (3) New insights from postmodern and poststructural analyses of menopause that examine the epistemological foundations of medical and feminist concepts of menopause and contest fixed descriptions of the experience of menopause. Key aspects of a ‘medical menopause’ nevertheless remain constant: menopause is a loss of hormones that results in predictable effects and risks and may be ameliorated by hormone replacement therapy. A question therefore emerges about how and to what effect medical practitioners have engaged with critiques of the medical menopause?

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Over the past two decades medical researchers and modernist feminist researchers have contested the meaning of menopause. In this article we examine various meanings of menopause in major medical and feminist literature and the construction of menopause in a semi-structured interview study of general practitioners in rural South Australia. Three discursive themes are identified in these interviews; (i) the hormonal menopause – symptoms, risk, prevention; (ii) the informed menopausal woman; and (iii) decision-making and hormone replacement therapy. By using the discourse of prevention, general practitioners construct menopause in relation to women's health care choices, empowerment and autonomy. We argue that the ways in which these concepts are deployed by general practitioners in this study produces and constrains the options available to women. The implications of these general practitioner accounts are discussed in relation to the proposition that medical and feminist descriptions of menopause posit alternative but equally-fixed truths about menopause and their relationship with the range of responses available to women at menopause. Social and cultural explanations of disease causality (c.f.Germov 1998, Hardey 1998) are absent from the new menopause despite their being an integral part of the framework of the women's health movement and health promotion drawn on by these general practitioners. Further, the shift of responsibility for health to the individual woman reinforces practice claims to empower women, but oversimplifies power relations and constructs menopause as a site of self-surveillance. The use of concepts from the women's health movement and health promotion have nevertheless created change in both the positioning of women as having ‘choices’ and the positioning of some general practitioners in terms of greater information provision to women and an attention to the woman's autonomy. In conclusion, we propose that a new menopause has evolved from a discursive shift in medicine and that there exists within this new configuration, claiming the empowerment of women as an integral part of health care for menopause, the possibility for change in medical practice which will broaden, strengthen, and maintain this position.

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Topic modeling has been widely utilized in the fields of information retrieval, text mining, text classification etc. Most existing statistical topic modeling methods such as LDA and pLSA generate a term based representation to represent a topic by selecting single words from multinomial word distribution over this topic. There are two main shortcomings: firstly, popular or common words occur very often across different topics that bring ambiguity to understand topics; secondly, single words lack coherent semantic meaning to accurately represent topics. In order to overcome these problems, in this paper, we propose a two-stage model that combines text mining and pattern mining with statistical modeling to generate more discriminative and semantic rich topic representations. Experiments show that the optimized topic representations generated by the proposed methods outperform the typical statistical topic modeling method LDA in terms of accuracy and certainty.