566 resultados para Modeling Geomorphological Processes


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When organizational scandals occur, the common refrain among commentators is: 'Where was the board in all this?' 'How could the directors not have known what was going on?''Why didn't the board intervene?' The scandals demonstrate that board monitoring or oganizational performance is a matter of great importance. By monitoring, we mean the act of keeping the organization under review. In many English-speaking countries, directors have a legal duty of care, which includes duties to monitor the performance of their organizations (Hopt and von Hippel 2010). However, statutory law typically merely states the duty, while providing little guidance on how that duty can be met.

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Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

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Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

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An estuary is formed at the mouth of a river where the tides meet a freshwater flow and it may be classified as a function of the salinity distribution and density stratification. An overview of the broad characteristics of the estuaries of South-East Queensland(Australia) is presented herein, where the small peri-urban estuaries may provide an useful indicator of potential changes which might occur in larger systems with growing urbanisation. Small peri-urban estuaries exhibits many key hydrological features and associated with ecosystem types of larger estuaries, albeit at smaller scales, often with a greater extent of urban development as a proportion of catchment area. We explore the potential for some smaller peri-urban estuaries to be used as natural laboratories to gain some much needed information on the estuarine processes, although any dynamics similarity is presently limited by critical absence of in-depth physical investigation in larger estuarine systems. The absence of the detailed turbulence and sedimentary data hampers the understanding and modelling of the estuarine zones. The interactions between the various stake holders are likely to define the vision for the future of South-East Queensland's peri-urban estuaries. This will require a solid understanding of the bio-physical function and capacity of the peri-urban estuaries. Based upon the knowledge gap, it is recommended that an adaptive trial and error approach be adopted for the future of investigation and management strategies.

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Over the past few decades, biodiesel produced from oilseed crops and animal fat is receiving much attention as a renewable and sustainable alternative for automobile engine fuels, and particularly petroleum diesel. However, current biodiesel production is heavily dependent on edible oil feedstocks which are unlikely to be sustainable in the longer term due to the rising food prices and the concerns about automobile engine durability. Therefore, there is an urgent need for researchers to identify and develop sustainable biodiesel feedstocks which overcome the disadvantages of current ones. On the other hand, artificial neural network (ANN) modeling has been successfully used in recent years to gain new knowledge in various disciplines. The main goal of this article is to review recent literatures and assess the state of the art on the use of ANN as a modeling tool for future generation biodiesel feedstocks. Biodiesel feedstocks, production processes, chemical compositions, standards, physio-chemical properties and in-use performance are discussed. Limitations of current biodiesel feedstocks over future generation biodiesel feedstock have been identified. The application of ANN in modeling key biodiesel quality parameters and combustion performance in automobile engines is also discussed. This review has determined that ANN modeling has a high potential to contribute to the development of renewable energy systems by accelerating biodiesel research.

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Groundwater flow models are usually characterized as being either transient flow models or steady state flow models. Given that steady state groundwater flow conditions arise as a long time asymptotic limit of a particular transient response, it is natural for us to seek a finite estimate of the amount of time required for a particular transient flow problem to effectively reach steady state. Here, we introduce the concept of mean action time (MAT) to address a fundamental question: How long does it take for a groundwater recharge process or discharge processes to effectively reach steady state? This concept relies on identifying a cumulative distribution function, $F(t;x)$, which varies from $F(0;x)=0$ to $F(t;x) \to \infty$ as $t\to \infty$, thereby providing us with a measurement of the progress of the system towards steady state. The MAT corresponds to the mean of the associated probability density function $f(t;x) = \dfrac{dF}{dt}$, and we demonstrate that this framework provides useful analytical insight by explicitly showing how the MAT depends on the parameters in the model and the geometry of the problem. Additional theoretical results relating to the variance of $f(t;x)$, known as the variance of action time (VAT), are also presented. To test our theoretical predictions we include measurements from a laboratory–scale experiment describing flow through a homogeneous porous medium. The laboratory data confirms that the theoretical MAT predictions are in good agreement with measurements from the physical model.

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Jakarta, Indonesia’s chronic housing shortage poses multiple challenges for contemporary policy-makers. While it may be in the city’s interest to increase the availability of housing, there is limited land to do so. Market pressures, in tandem with government’s desire for housing availability, demand consideration of even marginal lands, such as those within floodplains, for development. Increasingly, planning for a flood resilient Jakarta is complicated by a number of factors, including: the city is highly urbanized and land use data is limited; flood management is technically complex, creating potential barriers to engagement for both decision-makers and the public; inherent uncertainty exists throughout modelling efforts, central to management; and risk and liability for infrastructure investments is unclear. These obstacles require localized watershed-level participatory planning to address risks of flooding where possible and reduce the likelihood that informal settlements occur in areas of extreme risk. This paper presents a preliminary scoping study for determination of an effective participatory planning method to encourage more resilient development. First, the scoping study provides background relevant to the challenges faced in planning for contemporary Jakarta. Second, the study examines the current use of decision-support tools, such as Geographic Information Systems (GIS), in planning for Jakarta. Existing capacity in the use of GIS allows for consideration of the use of an emerging method of community consultation - Multi-Criteria Decision-Making (MCDM) support systems infused with geospatial information - to aid in engagement with the public and improve decision-making outcomes. While these methods have been used in Australia to promote stakeholder engagement in urban intensification, the planned research will be an early introduction of the method to Indonesia. As a consequence of this intervention, it is expected that planning activities will result in a more resilient city, capable of engaging with disaster risk management in a more effective manner.

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Recent studies have started to explore context-awareness as a driver in the design of adaptable business processes. The emerging challenge of identifying and considering contextual drivers in the environment of a business process are well understood, however, typical methods and models for business process design do not yet consider this context. In this paper, we describe our work on the design of a method framework and appropriate models to enable a context-aware process design approach. We report on our ongoing work with an Australian insurance provider and describe the design science we employed to develop innovative and useful artifacts as part of a context-aware method framework. We discuss the utility of these artifacts in an application in the claims handling process at the case organization.

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Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We proposed an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.

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Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

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The importance of applying unsaturated soil mechanics to geotechnical engineering design has been well understood. However, the consumption of time and the necessity for a specific laboratory testing apparatus when measuring unsaturated soil properties have limited the application of unsaturated soil mechanics theories in practice. Although methods for predicting unsaturated soil properties have been developed, the verification of these methods for a wide range of soil types is required in order to increase the confidence of practicing engineers in using these methods. In this study, a new permeameter was developed to measure the hydraulic conductivity of unsaturated soils using the steady-state method and directly measured suction (negative pore-water pressure) values. The apparatus is instrumented with two tensiometers for the direct measurement of suction during the tests. The apparatus can be used to obtain the hydraulic conductivity function of sandy soil over a low suction range (0-10 kPa). Firstly, the repeatability of the unsaturated hydraulic conductivity measurement, using the new permeameter, was verified by conducting tests on two identical sandy soil specimens and obtaining similar results. The hydraulic conductivity functions of the two sandy soils were then measured during the drying and wetting processes of the soils. A significant hysteresis was observed when the hydraulic conductivity was plotted against the suction. However, the hysteresis effects were not apparent when the conductivity was plotted against the volumetric water content. Furthermore, the measured unsaturated hydraulic conductivity functions were compared with predictions using three different predictive methods that are widely incorporated into numerical software. The results suggest that these predictive methods are capable of capturing the measured behavior with reasonable agreement.

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Packaged software is pre-built with the intention of licensing it to users in domestic settings and work organisations. This thesis focuses upon the work organisation where packaged software has been characterised as one of the latest ‘solutions’ to the problems of information systems. The study investigates the packaged software selection process that has, to date, been largely viewed as objective and rational. In contrast, this interpretive study is based on a 21⁄2 year long field study of organisational experiences with packaged software selection at T.Co, a consultancy organisation based in the United Kingdom. Emerging from the iterative process of case study and action research is an alternative theory of packaged software selection. The research argues that packaged software selection is far from the rationalistic and linear process that previous studies suggest. Instead, the study finds that aspects of the traditional process of selection incorporating the activities of gathering requirements, evaluation and selection based on ‘best fit’ may or may not take place. Furthermore, even where these aspects occur they may not have equal weight or impact upon implementation and usage as may be expected. This is due to the influence of those multiple realities which originate from the organisational and market environments within which packages are created, selected and used, the lack of homogeneity in organisational contexts and the variously interpreted characteristics of the package in question.

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The affordances concept describes the possibilities for goal-oriented action that technical objects offer to specified users. This notion has received growing attention from IS researchers. However, few studies have gone beyond contextualizing parts of the concept to a specific setting – the tip of the iceberg. In this research-in-progress paper, we report on our efforts to further develop the IS discipline’s understanding of affordances from informational objects. Specifically, we seek to extend extant theory on the origin and actualization of affordances. We develop a model that describes the process by which affordances are perceived and actualized and their dependence on information and actualization effort. We illustrate our emergent theory in the context of conceptual process models used by analysts for purposes of information systems analysis and design. We offer suggestions for operationalizing and testing this model empirically, and provide details about our design of a mixed-methods study currently in progress.

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This paper aims to contribute to an understanding of what actually takes place during consulting engagements. It draws on data collected from a qualitative case study of eight engagements by a niche consultancy in Australia to describe how consultants actively engage boundary crossing processes to address knowledge boundaries encountered during formal interactions with clients. While consultants actively managed knowledge boundary processes during interactions, by applying techniques such as evoking an ‘ideal state’ for clients, the engagements also yielded many missed opportunities for knowledge transformation.

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Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.