911 resultados para FULL CCSDT MODEL


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Passenger flow studies in airport terminals have shown consistent statistical relationships between airport spatial layout and pedestrian movement, facilitating prediction of movement from terminal designs. However, these studies are done at an aggregate level and do not incorporate how individual passengers make decisions at a microscopic level. Therefore, they do not explain the formation of complex movement flows. In addition, existing models mostly focus on standard airport processing procedures such as immigration and security, but seldom consider discretionary activities of passengers, and thus are not able to truly describe the full range of passenger flows within airport terminals. As the route-choice decision-making of passengers involves many uncertain factors within the airport terminals, the mechanisms to fulfill the capacity of managing the route-choice have proven difficult to acquire and quantify. Could the study of cognitive factors of passengers (i.e. human mental preferences of deciding which on-airport facility to use) be useful to tackle these issues? Assuming the movement in virtual simulated environments can be analogous to movement in real environments, passenger behaviour dynamics can be similar to those generated in virtual experiments. Three levels of dynamics have been devised for motion control: the localised field, tactical level, and strategic level. A localised field refers to basic motion capabilities, such as walking speed, direction and avoidance of obstacles. The other two fields represent cognitive route-choice decision-making. This research views passenger flow problems via a "bottom-up approach", regarding individual passengers as independent intelligent agents who can behave autonomously and are able to interact with others and the ambient environment. In this regard, passenger flow formation becomes an emergent phenomenon of large numbers of passengers interacting with others. In the thesis, first, the passenger flow in airport terminals was investigated. Discretionary activities of passengers were integrated with standard processing procedures in the research. The localised field for passenger motion dynamics was constructed by a devised force-based model. Next, advanced traits of passengers (such as their desire to shop, their comfort with technology and their willingness to ask for assistance) were formulated to facilitate tactical route-choice decision-making. The traits consist of quantified measures of mental preferences of passengers when they travel through airport terminals. Each category of the traits indicates a decision which passengers may take. They were inferred through a Bayesian network model by analysing the probabilities based on currently available data. Route-choice decision-making was finalised by calculating corresponding utility results based on those probabilities observed. Three sorts of simulation outcomes were generated: namely, queuing length before checkpoints, average dwell time of passengers at service facilities, and instantaneous space utilisation. Queuing length reflects the number of passengers who are in a queue. Long queues no doubt cause significant delay in processing procedures. The dwell time of each passenger agent at the service facilities were recorded. The overall dwell time of passenger agents at typical facility areas were analysed so as to demonstrate portions of utilisation in the temporal aspect. For the spatial aspect, the number of passenger agents who were dwelling within specific terminal areas can be used to estimate service rates. All outcomes demonstrated specific results by typical simulated passenger flows. They directly reflect terminal capacity. The simulation results strongly suggest that integrating discretionary activities of passengers makes the passenger flows more intuitive, observing probabilities of mental preferences by inferring advanced traits make up an approach capable of carrying out tactical route-choice decision-making. On the whole, the research studied passenger flows in airport terminals by an agent-based model, which investigated individual characteristics of passengers and their impact on psychological route-choice decisions of passengers. Finally, intuitive passenger flows in airport terminals were able to be realised in simulation.

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Portable water-filled barriers (PWFB) are roadside structures used to separate moving traffic from work-zones. Numerical PWFB modelling is preferred in the design stages prior to actual testing. This paper aims to study the fluid-structure interaction of PWFB under vehicular impact using several methods. The strategy to treat water as non-structural mass was proposed and the errors were investigated. It was found that water can be treated with the FEA-NSM model for velocities higher than 80kmh-1. However, full SPH/FEA model is still the best treatment for water and necessary for lower impact velocities. The findings in this paper can be used as guidelines for modelling and designing PWFB.

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Business process modelling as a practice and research field has received great attention over recent years. Organizations invest significantly into process modelling in terms of training, tools, capabilities and resources. The return on this investment is a function of process model re-use, which we define as the recurring use of process models to support organizational work tasks. While prior research has examined re-use as a design principle, we explore re-use as a behaviour, because evidence suggest that analysts’ re-use of process models is indeed limited. In this paper we develop a two-stage conceptualization of the key object-, behaviour- and socioorganization-centric factors explaining process model re-use behaviour. We propose a theoretical model and detail implications for its operationalization and measurement. Our study can provide significant benefits to our understanding of process modelling and process model use as key practices in analysis and design.

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Purpose: In animal models hemi-field deprivation results in localised, graded vitreous chamber elongation and presumably deprivation induced localised changes in retinal processing. The aim of this research was to determine if there are variations in ERG responses across the retina in normal chick eyes and to examine the effect of hemi-field and full-field deprivation on ERG responses across the retina and at earlier times than have previously been examined electrophysiologically. Methods: Chicks were either untreated, wore monocular full-diffusers or half-diffusers (depriving nasal retina) (n = 6-8 each group) from day 8. mfERG responses were measured using the VERIS mfERG system across the central 18.2º× 16.7º (H × V) field. The stimulus consisted of 61 unscaled hexagons with each hexagon modulated between black and white according to a pseudorandom binary m-sequence. The mfERG was measured on day 12 in untreated chicks, following 4 days of hemi-field diffuser wear, and 2, 48 and 96 h after application of full-field diffusers. Results: The ERG response of untreated chick eyes did not vary across the measured field; there was no effect of retinal location on the N1-P1 amplitude (p = 0.108) or on P1 implicit time (p > 0.05). This finding is consistent with retinal ganglion cell density of the chick varying by only a factor of two across the entire retina. Half-diffusers produced a ramped retina and a graded effect of negative lens correction (p < 0.0001); changes in retinal processing were localized. The untreated retina showed increasing complexity of the ERG waveform with development; form-deprivation prevented the increasing complexity of the response at the 2, 48 and 96 h measurement times and produced alterations in response timing. Conclusions: Form-deprivation and its concomitant loss of image contrast and high spatial frequency images prevented development of the ERG responses, consistent with a disruption of development of retinal feedback systems. The characterisation of ERG responses in normal and deprived chick eyes across the retina allows the assessment of concurrent visual and retinal manipulations in this model. (Ophthalmic & Physiological Optics © 2013 The College of Optometrists.)

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Enterprise Social Networks continue to be adopted by organisations looking to increase collaboration between employees, customers and industry partners. Offering a varied range of features and functionality, this technology can be distinguished by the underlying business models that providers of this software deploy. This study identifies and describes the different business models through an analysis of leading Enterprise Social Networks: Yammer, Chatter, SharePoint, Connections, Jive, Facebook and Twitter. A key contribution of this research is the identification of consumer and corporate models as extreme approaches. These findings align well with research on the adoption of Enterprise Social Networks that has discussed bottom-up and top-down approaches. Of specific interest are hybrid models that wrap a corporate model within a consumer model and may, therefore, provide synergies on both models. From a broader perspective, this can be seen as the merging of the corporate and consumer markets for IT products and services.

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This paper proposes that critical realism can provide a useful theoretical foundation to study enterprise architecture (EA) evolution. Specifically it will investigate the practically relevant and academically challenging question of how EAs integrate the Service-oriented Architecture (SOA). Archer’s Morphogenetic theory is used as an analytical approach to distinguish the architectural conditions under which SOA is introduced, to study the relationships between these conditions and SOA introduction, and to reflect on EA evolution (elaborations) that then take place. The focus lies on the reasons why EA evolution takes place (or not) and what architectural changes happen. This paper uses the findings of a literature review to build an a-priori model informed by Archer’s theory to understand EA evolution in a field that often lacks a solid theoretical groundwork. The findings are threefold. First, EA can evolve on different levels (different integration outcomes). Second, the integration outcomes are classified into three levels: business architecture, information systems architecture and technology architecture. Third, the analytical separation using Archer’s theory is helpful in order to understand how these different integration outcomes are generated.

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Health care systems are highly dynamic not just due to developments and innovations in diagnosis and treatments, but also by virtue of emerging management techniques supported by modern information and communication technology. A multitude of stakeholders such as patients, nurses, general practitioners or social carers can be integrated by modeling complex interactions necessary for managing the provision and consumption of health care services. Furthermore, it is the availability of Service-oriented Architecture (SOA) that supports those integration efforts by enabling the flexible and reusable composition of autonomous, loosely-coupled and web-enabled software components. However, there is still the gap between SOA and predominantly business-oriented perspectives (e.g. business process models). The alignment of both views is crucial not just for the guided development of SOA but also for the sustainable evolution of holistic enterprise architectures. In this paper, we combine the Semantic Object Model (SOM) and the Business Process Modelling Notation (BPMN) towards a model-driven approach to service engineering. By addressing a business system in Home Telecare and deriving a business process model, which can eventually be controlled and executed by machines; in particular by composed web services, the full potential of a process-centric SOA is exploited.

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Background: An arteriovenous loop (AVL) enclosed in a polycarbonate chamber in vivo, produces a fibrin exudate which acts as a provisional matrix for the development of a tissue engineered microcirculatory network. Objectives: By administering enoxaparin sodium - an inhibitor of fibrin polymerization, the significance of fibrin scaffold formation on AVL construct size (including the AVL, fibrin scaffold, and new tissue growth into the fibrin), growth, and vascularization were assessed and compared to controls. Methods: In Sprague Dawley rats, an AVL was created on femoral vessels and inserted into a polycarbonate chamber in the groin in 3 control groups (Series I) and 3 experimental groups (Series II). Two hours before surgery and 6 hours post-surgery, saline (Series I) or enoxaparin sodium (0.6 mg/kg, Series II) was administered intra-peritoneally. Thereafter, the rats were injected daily with saline (Series I) or enoxaparin sodium (1.5 mg/kg, Series II) until construct retrieval at 3, 10, or 21 days. The retrieved constructs underwent weight and volume measurements, and morphologic/morphometric analysis of new tissue components. Results: Enoxaparin sodium treatment resulted in the development of smaller AVL constructs at 3, 10, and 21 days. Construct weight and volume were significantly reduced at 10 days (control weight 0.337 ± 0.016 g [Mean ± SEM] vs treated 0.228 ± 0.048, [P < .001]: control volume 0.317 ± 0.015 mL vs treated 0.184 ± 0.039 mL [P < .01]) and 21 days (control weight 0.306 ± 0.053 g vs treated 0.198 ± 0.043 g [P < .01]: control volume 0.285 ± 0.047 mL vs treated 0.148 ± 0.041 mL, [P < .01]). Angiogenesis was delayed in the enoxaparin sodium-treated constructs with the absolute vascular volume significantly decreased at 10 days (control vascular volume 0.029 ± 0.03 mL vs treated 0.012 ± 0.002 mL [P < .05]). Conclusion: In this in vivo tissue engineering model, endogenous, extra-vascularly deposited fibrin volume determines construct size and vascular growth in the first 3 weeks and is, therefore, critical to full construct development.

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Research with typically developing groups has identified loneliness as a significant predictor of a range of physical and mental health problems. This paper reviews research about loneliness in children and adults with intellectual disability. Although a considerable body of evidence has highlighted the difficulties individuals with intellectual disability have with friendships, there is a relative scarcity of research focused explicitly on loneliness. The available evidence suggests that up to half of those with intellectual disability are chronically lonely, compared with around 15-30% of people in the general population. The cognitive, physical and mental health problems already associated with intellectual disability are likely to be compounded by experiences of chronic loneliness. We argue that people with intellectual disability are highly vulnerable to loneliness and present a theoretical model of vulnerability that comprises three reciprocally influencing domains: social attitudes and expectations; opportunities and experiences; and skill deficits associated with intellectual disability. We propose that societal views which have traditionally devalued and stigmatised those with intellectual disability limit their opportunities for experiencing social and emotional connectedness with others. Individual skill deficits in areas such as communication, self-regulation and social understanding, as well as functional difficulties associated with intellectual disability, also potentially influence the opportunities and experiences of people with intellectual disability, both directly and via multiple layers of the social context. In turn, limited opportunities will entrench particular skill deficits and reinforce negative attitudes towards intellectual disability. Future research about loneliness and intellectual disability needs to address the difficulties of measuring emotional isolation in this population, as well as the possibility that people with intellectual disability may understand, experience and interpret loneliness somewhat differently from others. The model proposed in this paper provides a starting point for developing a more sophisticated understanding of the experience of loneliness for individuals with intellectual disability.

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Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

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Full-resolution 3D Ground-Penetrating Radar (GPR) data were combined with high-resolution hydraulic conductivity (K) data from vertical Direct-Push (DP) profiles to characterize a portion of the highly heterogeneous MAcro Dispersion Experiment (MADE) site. This is an important first step to better understand the influence of aquifer heterogeneities on observed anomalous transport. Statistical evaluation of DP data indicates non-normal distributions that have much higher similarity within each GPR facies than between facies. The analysis of GPR and DP data provides high-resolution estimates of the 3D geometry of hydrostratigraphic zones, which can then be populated with stochastic K fields. The lack of such estimates has been a significant limitation for testing and parameterizing a range of novel transport theories at sites where the traditional advection-dispersion model has proven inadequate.

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One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

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Stock indexes are passive 'value-weighted' portfolios and should not have alphas which are significantly different from zero. If an index produces an insignificant alphan, then significant alphas for equity funds using this index can be attributed solely to manager performance. However, recent literature sugests that US Stock indexes can demonstrate significant alphas, which ultimately raise questions regarding equity fund manager performance in both the US and abroad. in this paper, we employ the Carhart four-factor model and newly available Asian-Pacific risk factors to generate alphas and risk factor loadings for eight Australian stock indexes from January 2004 to December 2012. We ifnd that the initial full sample period analysis does not provide indication of significant alphas in the indexes examined. However, by carrying out 36-month rolling regressions, we discover at least four significant alphas in seven of the eight indexes and factor loading variability. As previously reported in the US, this paper confirms similar issues with the four-factor model using Australian stock indexes and performance benchmarking. In effectively measuring Australian equity fund manager performance, it is therefore essential to evaluate a fund's alpha and risk factors relative to the alpha and risk factors of the appropriate benchmark index.

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Introduced in this paper is a Bayesian model for isolating the resonant frequency from combustion chamber resonance. The model shown in this paper focused on characterising the initial rise in the resonant frequency to investigate the rise of in-cylinder bulk temperature associated with combustion. By resolving the model parameters, it is possible to determine: the start of pre-mixed combustion, the start of diffusion combustion, the initial resonant frequency, the resonant frequency as a function of crank angle, the in-cylinder bulk temperature as a function of crank angle and the trapped mass as a function of crank angle. The Bayesian method allows for individual cycles to be examined without cycle-averaging|allowing inter-cycle variability studies. Results are shown for a turbo-charged, common-rail compression ignition engine run at 2000 rpm and full load.