Agent-based model of passenger flows in airport terminals

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.

Three-phase model of consumers' behaviours : a synthesis of the theory of planned behaviour, self-determination theory and planning

Using a longitudinal study, an overall behavioural model with three related phases (cognitive, motivational and volitional phase) across three studies was examined to identify the factors that most prominently drive consumer environmental behaviour. This thesis provides empirical evidence to support the behavioural model in an environmental consumption context and shows a new avenue for promoting consumer environmental behaviour.

Can emotion provide a new approach to business model innovation?

Companies require new strategies to drive growth and survival, as the fast pace of change has created the need for greater business flexibility. Therefore, industry leaders are looking to business innovation as a principle source of differentiation and competitive advantage. However, most companies rely heavily on either technology or products to provide business innovation, yet competitors can easily and rapidly surpass these forms of innovation. Business model innovation expands beyond innovation in isolated areas, such as product innovation, to create strategies that incorporate many business avenues to work together to create and deliver value to its customers. Existing literature highlights that a business model’s central role is ‘customer value’. However, the emotional underpinnings of customer value within a business model are not well understood. The integration of customer emotion into business model design and value chain can be viewed as a way to innovate beyond just products, services and processes. This paper investigates the emotional avenues within business strategy and operations, business model innovation and customer engagement. Three propositions are outlined and explored as future research. The significance of this research is to provide companies with a new approach to innovation through a deeper understanding and integration of their customers’ emotions.

A new efficiency model for a regenerative dynamometer

This paper presents two efficiency models for the regenerative dynamometer to be built at the University of Queensland. The models incorporate an accurate accounting of the losses associated with the regenerative dynamometer and the battery modelling technique used. In addition to the models the cycle and instantaneous efficiencies were defined for a regenerative system that requires a desired torque output. The simulation of the models allowed the instantaneous and cycle efficiencies to be examined. The results show the intended dynamometer machine has significant efficiency draw backs but incorporating field winding control, the efficiency can be improved.

Evaluating MPPT converter topologies using a Matlab PV model

An accurate PV module electrical model is presented based on the Shockley diode equation. The simple model has a photo-current current source, a single diode junction and a series resistance, and includes temperature dependences. The method of parameter extraction and model evaluation in Matlab is demonstrated for a typical 60W solar panel. This model is used to investigate the variation of maximum power point with temperature and isolation levels. A comparison of buck versus boost maximum power point tracker (MPPT) topologies is made, and compared with a direct connection to a constant voltage (battery) load. The boost converter is shown to have a slight advantage over the buck, since it can always track the maximum power point.

Evaluating MPPT converter topologies using a MATLAB PV model

An accurate PV module electrical model is presented based on the Shockley diode equation. The simple model has a photo-current current source, a single diode junction and a series resistance, and includes temperature dependences. The method of parameter extraction and model evaluation in Matlab is demonstrated for a typical 60W solar panel. This model is used to investigate the variation of maximumpower point with temperature and insolation levels. A comparison of buck versus boostmaximum power point tracker (MPPT) topologies is made, and compared with a direct connection to a constant voltage (battery) load. The boost converter is shown to have a slight advantage over the buck, since it can always track the maximum power point.

The People-Game-Play model for understanding videogames’ impact on wellbeing

Given the increasing popularity of videogames, understanding when, how and for whom they have a positive or negative impact on wellbeing is critical. We propose a model for exploring these questions based on existing literature and our own research. The People-Game-Play model identifies player characteristics, game features and the experience of play as key determinants of the impact of videogame play on wellbeing. We propose research exploring the relationships within and between each of these key factors is needed and identify some examples of future research in this space.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Packed red blood cells suppress myeloid dendritic cell and monocyte inflammatory responses in a whole blood model of transfusion

Purpose/Objective: The basis for poor outcomes in some patients post transfusion remains largely unknown. Despite leukodepletion, there is still evidence of immunomodulatory effects of transfusion that require further study. In addition, there is evidence that the age of blood components transfused significantly affects patient outcomes. Myeloid dendritic cell (DC) and monocyte immune function were studied utilising an in vitro whole blood model of transfusion. Materials and methods: Freshly collected (‘recipient’) whole blood was cultured with ABO compatible leukodepleted PRBC at 25% blood replacement-volume (6hrs). PRBC were assayed at [Day (D) 2, 14, 28and 42 (date-of expiry)]. In parallel, LPS or Zymosan (Zy) were added to mimic infection. Recipients were maintained for the duration of the time course (2 recipients, 4 PRBC units, n = 8).Recipient DC and monocyte intracellular cytokines and chemokines (IL-6, IL-10, IL-12,TNF-a, IL-1a, IL-8, IP-10, MIP-1a, MIP-1b, MCP-1) were measured using flow cytometry. Changes in immune response were calculated by comparison to a parallel no transfusion control (Wilcoxin matched pairs). Influence of storage age was calculated using ANOVA. Results: Significant suppression of DC and monocyte inflammatory responses were evident. DC and monocyte production of IL-1a was reduced following exposure to PRBC regardless of storage age (P < 0.05 at all time points). Storage independent PRBC mediated suppression of DC and monocyte IL-1a was also evident in cultures costimulated with Zy. In cultures co-stimulated with either LPS or Zy, significant suppression of DC and monocyte TNF-a and IL-6 was also evident. PRBC storage attenuated monocyte TNF-a production when co-cultured with LPS (P < 0.01 ANOVA). DC and monocyte production of MIP-1a was significantly reduced following exposure to PRBC (DC: P < 0.05 at D2, 28, 42; Monocyte P < 0.05 all time points). In cultures co-stimulated with LPS and zymosan, a similar suppression of MIP-1a production was also evident, and production of both DC and monocyte MIP-1b and IP-10 were also significantly reduced. Conclusions: The complexity of the transfusion context was reflected in the whole blood approach utilised. Significant suppression of these key DC and monocyte immune responses may contribute to patient outcomes, such as increased risk of infection and longer hospital stay, following blood transfusion.

Bridging the biology of the ovine TRALI model – human inflammatory cell responses to TRALI inducing supernatants

Background Transfusion-related acute lung injury (TRALI) is a serious and potentially fatal consequence of transfusion. A two-event TRALI model demonstrated date-of-expiry - day (D) 5 platelet (PLT) and D42 packed red blood cell (PRBC) supernatants (SN) induced TRALI in LPS-treated sheep. We have adapted a whole blood transfusion culture model as an investigative bridge between the ovine TRALI model human responses to transfusion. Methods A whole blood transfusion model was adapted to replicate the ovine model - specifically +/- 0.23μg/mL LPS as the first event and 10% SN volume (transfusion) as the second event. Four pooled SN from blood products, previously used in the TRALI ovine model, were investigated: D1-PLT, D5-PLT, D1-PRBC, and D42-PRBC. Fresh human whole blood (recipient) was mixed with combinations of LPS and BP-SN stimuli and incubated in vitro for 6 hrs. Addition of golgi plug enabled measurement of monocyte cytokine production (IL-6, IL-8, IL-10, IL-12, TNF-α, IL-1α, CXCL-5, IP-10, MIP-1α, MCP-1) using multi-colour flow cytometry. Responses for 6 recipients were assessed. Results In the presence of LPS, D42-PRBC-SN significantly increased monocyte IL-6 (P=0.031), IL-8 (P=0.016) and IL-1α (P=0.008) production compared to D1-PRBC-SN. This response to D42-PRBC-SN was LPS-dependent, and was not evident in non-LPSstimulated controls. This response was also specific to D42-PRBC-SN, as similar changes were not evident for the D5-PLT-SN, compared to the D1-PLT-SN, regardless of the presence of LPS. D5-PLT-SN significantly increased IL-12 production (P=0.024) compared to D1-PLT-SN. This response was again LPS-dependent. Conclusions These data demonstrate a novel two-event mechanism of monocyte inflammatory response that was dependent upon both the presence of date-of-expiry blood product SN and LPS. Further, these results demonstrate different cytokines responses induced by date-of-expiry PLT-SN and PRBC-SN. These data are consistent with the evidence from the ovine TRALI model, and enhancing its relevance to transfusion related changes in humans.

Storyboard augmentation of process model grammars for stakeholder communication

Process models are often used to visualize and communicate workflows to involved stakeholders. Unfortunately, process modeling notations can be complex and need specific knowledge to be understood. Storyboards, as a visual language to illustrate workflows as sequences of images, provide natural visualization features that allow for better communication, to provide insight to people from non-process modelling expert domains. This paper proposes a visualization approach using a 3D virtual world environment to visualize storyboards for business process models. A prototype was built to present its applicability via generating output with examples of five major process model patterns and two non-trivial use cases. Illustrative results for the approach show the promise of using a 3D virtual world to visualize complex process models in an unambiguous and intuitive manner.

Bayesian indirect inference using a parametric auxiliary model

Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), we show to be a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) which encompasses pBII as well as general ABC methods so that the connections between the methods can be established.

Princess Alexandra Hospital model of comprehensive geriatric assessment of cancer patients : methodological and logistical aspects

There is increasing momentum in cancer care to implement a two stage assessment process that accurately determines the ability of older patients to cope with, and benefit from, chemotherapy. The two-step approach aims to ensure that patients clearly fit for chemotherapy can be accurately identified and referred for treatment without undergoing a time- and resource-intensive comprehensive geriatric assessment (CGA). Ideally, this process removes the uncertainty of how to classify and then appropriately treat the older cancer patient. After trialling a two-stage screen and CGA process in the Division of Cancer Services at Princess Alexandra Hospital (PAH) in 2011-2012, we implemented a model of oncogeriatric care based on our findings. In this paper, we explore the methodological and practical aspects of implementing the PAH model and outline further work needed to refine the process in our treatment context.

The development of a kinematic model to quantify in-shoe foot motion

A multi-segment foot model was used to develop an accurate and reliable kinematic model to describe in-shoe foot kinematics during gait.

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.