980 resultados para sticky-price DGSE models


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Developers and policy makers are consistently at odds over the debate as to whether impact fees increase house prices. This debate continues despite the extensive body of theoretical and empirical international literature that discusses the passing on to home buyers of impact fees, and the corresponding increase to housing prices. In attempting to quantify this impact, over a dozen empirical studies have been carried out in the US and Canada since the 1980’s. However the methodologies used vary greatly, as do the results. Despite similar infrastructure funding policies in numerous developed countries, no such empirical works exist outside of the US/Canada. The purpose of this research is to analyse the existing econometric models in order to identify, compare and contrast the theoretical bases, methodologies, key assumptions and findings of each. This research will assist in identifying if further model development is required and/or whether any of these models have external validity and are readily transferable outside of the US. The findings conclude that there is very little explicit rationale behind the various model selections and that significant model deficiencies appear still to exist.

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A synthesis is presented of the predictive capability of a family of near-wall wall-normal free Reynolds stress models (which are completely independent of wall topology, i.e., of the distance fromthe wall and the normal-to-thewall orientation) for oblique-shock-wave/turbulent-boundary-layer interactions. For the purpose of comparison, results are also presented using a standard low turbulence Reynolds number k–ε closure and a Reynolds stress model that uses geometric wall normals and wall distances. Studied shock-wave Mach numbers are in the range MSW = 2.85–2.9 and incoming boundary-layer-thickness Reynolds numbers are in the range Reδ0 = 1–2×106. Computations were carefully checked for grid convergence. Comparison with measurements shows satisfactory agreement, improving on results obtained using a k–ε model, and highlights the relative importance of redistribution and diffusion closures, indicating directions for future modeling work.

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The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

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The decision of Lai v Soineva [2011] QSC 247 in relation to the operation of standard conditions in the Queensland REIQ contract highlights a very practical issue often overlooked in the heat of a transaction .The point is relatively simple. In this instance ,the case concerned the interpretation of the printed "Building and Pest Inspection Clause" but is of relevance to the printed "Finance Clause" in the same contract as the wording and principles are identical. It highlights the issue of knowing well what is in the standard contract and not making assumptions. The case also highlights the cost to a party of dithering in making an election in a time of the essence environment

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This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

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This article addresses the transformation of a process model with an arbitrary topology into an equivalent structured process model. In particular, this article studies the subclass of process models that have no equivalent well-structured representation but which, nevertheless, can be partially structured into their maximally-structured representation. The transformations are performed under a behavioral equivalence notion that preserves the observed concurrency of tasks in equivalent process models. The article gives a full characterization of the subclass of acyclic process models that have no equivalent well-structured representation, but do have an equivalent maximally-structured one, as well as proposes a complete structuring method. Together with our previous results, this article completes the solution of the process model structuring problem for the class of acyclic process models.

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Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

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A pressing cost issue facing construction is the procurement of off-site pre-manufactured assemblies. In order to encourage Australian adoption of off-site manufacture (OSM), a new approach to underlying processes is required. The advent of object oriented digital models for construction design assumes intelligent use of data. However, the construction production system relies on traditional methods and data sources and is expected to benefit from the application of well-established business process management techniques. The integration of the old and new data sources allows for the development of business process models which, by capturing typical construction processes involving OSM, provides insights into such processes. This integrative approach is the foundation of research into the use of OSM to increase construction productivity in Australia. The purpose of this study is to develop business process models capturing the procurement, resources and information flow of construction projects. For each stage of the construction value chain, a number of sub-processes are identified. Business Process Modelling Notation (BPMN), a mainstream business process modelling standard, is used to create base-line generic construction process models. These models identify OSM decision-making points that could provide cost reductions in procurement workflow and management systems. This paper reports on phase one of an on-going research aiming to develop a proto-type workflow application that can provide semi-automated support to construction processes involving OSM and assist in decision-making in the adoption of OSM thus contributing to a sustainable built environment.

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Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

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Shoulder joint is a complex integration of soft and hard tissues. It plays an important role in performing daily activities and can be considered as a perfect compromise between mobility and stability. However, shoulder is vulnerable to complications such as dislocations and osteoarthritis. Finite element (FE) models have been developed to understand shoulder injury mechanisms, implications of disease on shoulder complex and in assessing the quality of shoulder implants. Further, although few, Finite element shoulder models have also been utilized to answer important clinical questions such as the difference between a normal and osteoarthritic shoulder joint. However, due to the absence of experimental validation, it is questionable whether the constitutive models applied in these FE models are adequate to represent mechanical behaviors of shoulder elements (Cartilages, Ligaments, Muscles etc), therefore the confidence of using current models in answering clinically relevant question. The main objective of this review is to critically evaluate the existing FE shoulder models that have been used to investigate clinical problems. Due concern is given to check the adequacy of representative constitutive models of shoulder elements in drawing clinically relevant conclusion. Suggestions have been given to improve the existing shoulder models by inclusion of adequate constitutive models for shoulder elements to confidently answer clinically relevant questions.

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This article focuses on the relationship between private insurance status and dental service utilisation in Australia using data between 1995 and 2001. This article employs joint maximum likelihood to estimate models of time since last dental visit treating private ancillary health insurance (PAHI) as endogenous. The sensitivity of results to the choice between two different but related types of instrumental variables is examined. We find robust evidence in both 1995 and 2001 that individuals with a PAHI policy make significantly more frequent dental consultations relative to those without such coverage. A comparison of the 1995 and 2001 results, however, suggests that there has been an increasing role of PAHI in terms of the frequency of dental consultations over time. This seems intuitive given the trends in the price of unsubsidised private dental consultations. In terms of policy, our results suggest that while government measures to increase private health insurance coverage in Australia has been successful to a significant degree, it may have come at some cost in terms of socio-economic inequality as the privately insured are provided much better access to care and financial protection.

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Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.

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Three dimensional cellular models that mimic disease are being increasingly investigated and have opened an exciting new research area into understanding pathomechanisms. The advantage of 3D in vitro disease models is that they allow systematic and in-depth studies of physiological and pathophysiological processes with less costs and ethical concerns that have arisen with animal models. The purpose of the 3D approach is to allow crosstalk between cells and microenvironment, and with cues from the microenvironment, cells can assemble their niche similar to in vivo conditions. The use of 3D models for mimicking disease processes such as cancer, osteoarthritis etc., is only emerging and allows multidisciplinary teams consisting of tissue engineers, biologist biomaterial scientists and clinicians to work closely together. While in vitro systems require rigorous testing before they can be considered as replicates of the in vivo model, major steps have been made, suggesting that they will become powerful tools for studying physiological and pathophysiological processes. This paper aims to summarize some of the existing 3D models and proposes a novel 3D model of the eye structures that are involved in the most common cause of blindness in the Western World, namely age-related macular degeneration (AMD).