Competition in the global economic scenario has led to the use of simulation in many areas such as manufacturing, health systems, military systems and transportation. With the importance of simulation in supporting decision making and operations, model building has been recognised as one of the crucial steps in simulation studies. However, model building is not as easy as it may seem. It can be time-consuming and expensive, and requires special training, skills and experience. This research, therefore, aims to investigate a new method to rapidly build a simulation model based on the classification of problems in assembly lines using a cladistics technique and template approach. Three objectives were established in order to achieve the aim and a four-stage research programme was developed according to these objectives. The first stage starts by developing a thorough understanding of and collecting typical problems in assembly lines. The next stage formulates the classification of problems and the main deliverable is a cladogram, a tree structure that can be used to represent the evolution of problems and their characteristics. The third stage focuses on the development of a proof-of-concept prototype based on an established classification and template approach. The prototype helps users to develop a model by providing the physical elements and specific elements required for the performance measures analysis. The prototype is then tested and validated in the final stage. The results show that the prototype developed can help to rapidly build a simulation model and reduce model development time.

Wetland, one of the three major ecosystems on earth, can prevent flood, purify water quality and provide habitat for wildlife; also protects the shore line from erosion, and has many other functions and values. Owing to the economic development and the rapid population growth, the land resource has being inadequate to meet all demands. Thus, coastal wetlands have become the target of development. This tendency causes reduction and fragmentary of wetlands, degradation of ecosystem and depletion of ecological resources. To avoid the improper development on the wetland, it is necessary to integrate considerations over the social economy, ecosystem, and management strategy. Based on the unique feature of the wetland, it is therefore possible to effectively manage the wetland resources for achieving the goal of sustainable development. This study explores the group model building approach which design for the discussion of the various potential effects of the yacht industry park may have on Cheting Wetland. Participants of stakeholders in Cheting had met several times and the structured debates had been organized with them in order to promote the emergence of a consensual view of the main issues and their implications. And then, a system dynamic model was built to evaluate the development in the wetlands zone. The authentic results of the policies and scenario analyses inspected the effectiveness of the designate plans for Cheting Wetland development. Particular Wetland Zone, Artificial Floating Island and In Lieu Fee were adopted as management strategies in Cheting Wetland Zone case. The study concludes that: under single-policy condition, implementation of Particular Wetland Zone is the best management strategy; while under the multi-policy conditions, the combination of Wetland Zone and Artificial Floating Island would have the best managerial performance. Additional benefits of the GMB study include: (1) providing stakeholders with information and knowledge to understand the behavior of wetland environment system; (2) A revealing gap between system behavior patterns and participants¡¦ mental model. Both achievements will further promote the participants to introspect and to improve their mental model, eventually help the whole community to reach consensus about wetland management.

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Background: The selection and prioritizing of requirements is the most difficult challenge insoftware development. Prioritizing requirements is a difficult task. Due to the importance of thepriority of requirements, many methods have been developed on how to prioritize requirements.However, with the increase of software modules and the expansion of software platforms, thesingle requirement prioritization method can no longer match the increase in the number ofrequirements. Little is know in how to find and develop integrated requirement prioritizationmethod. Objectives: The main purpose of this research is to explore the main challenges and successcriteria that practitioners consider when determining the priority of product requirements. Builda good requirement prioritization model to tackle these challenges. And evaluate the strengthsand limitations of this model. Method: We conducted a questionnaire survey to learn more about the major problems andsuccess criteria for prioritizing product requirements. After that, we presented a model thatcombined the KANO model and Analytic Hierarchy Process (AHP), and we examined its practicality. Finally, using Focus Group Research, we analyzed the benefits and limitations of theintegrated model and improved solutions. Result: The results show that practitioners face many challenges in product requirement prioritization. The model we developed is suitable for a variety of scenarios. It helps practitionersmanage priorities and improve end-user satisfaction, which can solve these challenges to a certain extent. Conclusion: Our research collected many major challenges encountered by requirement analysts and product managers in the process of requirement prioritization. And developed a newrequirement prioritization model, got a better understanding of requirement prioritization whichcan inspire practitioners to build more better requirement prioritization models.

This thesis contributes with a number of topics to the subject of string compactifications, especially in the instance of the E₈ × E₈ heterotic string theory compactified on smooth Calabi-Yau threefolds. In the first half of the work, I discuss the Hodge plot associated with Calabi-Yau threefolds that are hypersurfaces in toric varieties. The intricate structure of this plot is explained by the existence of certain webs of elliptic-K3 fibrations, whose mirror images are also elliptic-K3 fibrations. Such manifolds arise from reflexive polytopes that can be cut into two parts along slices corresponding to the K3 fiber. Any two half-polytopes over a given slice can be combined into a reflexive polytope. This fact, together with a remarkable relation on the additivity of Hodge numbers, give to the Hodge plot the appearance of a fractal. Moving on, I discuss a different type of web of manifolds, by looking at smooth Z₃-quotients of Calabi-Yau three-folds realised as complete intersections in products of projective spaces. Non-simply connected Calabi-Yau three-folds provide an essential ingredient in heterotic string compactifications. Such manifolds are rare in the classical constructions, but they can be obtained as quotients of homotopically trivial Calabi-Yau three-folds by free actions of finite groups. Many of these quotients are connected by conifold transitions. In the second half of the work, I explore an algorithmic approach to constructing E₈ × E₈ heterotic compactifications using holomorphic and poly-stable sums of line bundles over complete intersection Calabi-Yau three-folds that admit freely acting discrete symmetries. Such Abelian bundles lead to N = 1 supersymmetric GUT theories with gauge group SU(5) × U(4) and matter fields in the 10, ⁻10, ⁻5, 5 and 1 representations of SU(5). The extra U(1) symmetries are generically Green-Schwarz anomalous and, as such, they survive in the low energy theory only as global symmetries. These, in turn, constrain the low energy theory and in many cases forbid the existence of undesired operators, such as dimension four or five proton decay operators. The line bundle construction allows for a systematic computer search resulting in a plethora of models with the exact matter spectrum of the Minimally Supersymmetric Standard Model, one or more pairs of Higgs doublets and no exotic fields charged under the Standard Model group. In the last part of the thesis I focus on the case study of a Calabi-Yau hypersurface embedded in a product of four CP1 spaces, referred to as the tetraquadric manifold. I address the question of the finiteness of the class of consistent and physically viable line bundle models constructed on this manifold. Line bundle sums are part of a moduli space of non-Abelian bundles and they provide an accessible window into this moduli space. I explore the moduli space of heterotic compactifications on the tetraquadric hypersurface around a locus where the vector bundle splits as a direct sum of line bundles, using the monad construction. The monad construction provides a description of poly-stable S(U(4) × U(1))–bundles leading to GUT models with the correct field content in order to induce standard-like models. These deformations represent a class of consistent non-Abelian models that has co-dimension one in Kähler moduli space.

With increasingly complex safety-critical systems like healthcare being developed and managed, there is a need for a tool that allows us to understand their complexity, design better strategies and guide effective change. System dynamics (SD) has been widely used in modelling across a range of applications from socio-economic to engineering systems, but its potential has not yet been fully realised as a tool for understanding trade-off dynamics between safety and efficiency in healthcare. SD has the potential to provide balanced and trustworthy insights into strategic decision making. Participatory SD modelling and learning is particularly important in healthcare since problems in healthcare are difficult to comprehend due to complexity, involvement of multiple stakeholders in decision making and fragmented structure of delivery systems. Participatory SD modelling triangulates stakeholder expertise, data and simulation of implementation plans prior to attempting change. It provides decision-makers with an evaluation and learning tool to analyse impacts of changes and determine which input data is most likely to achieve desired outcomes. This thesis aims to examine the feasibility of applying participatory SD modelling approach to safe and efficient staffing level management within hospital pharmacies and to evaluate the utility and usability of participatory SD modelling approach as a learning method. A case study was conducted looking at trade-offs between dispensing backlog (efficiency) and dispensing errors (safety) in a hospital pharmacy dispensary in an English teaching hospital. A participatory modelling approach was employed where the stakeholders from the hospital pharmacy dispensary were engaged in developing an integrated qualitative conceptual model. The model was constructed using focus group sessions with 16 practitioners consisting of labelling and checking practitioners, the literature and hospital pharmacy databases. Based on the conceptual model, a formal quantitative simulation model was then developed using an SD simulation approach, allowing different scenarios and strategies to be identified and tested. Besides the baseline or business as usual scenario, two additional scenarios (hospital winter pressures and various staffing arrangements, interruptions and fatigue) identified by the pharmacist team were simulated and tested using a custom simulation platform (Forio: user-friendly GUI) to enable stakeholders to play out the likely consequences of the intervention scenarios. We carried out focus group-based survey of 21 participants working in the hospital pharmacy dispensaries to evaluate the applicability, utility and usability of how participatory SD enhanced group learning and building of shared vision for problems within the hospital dispensaries. Findings from the simulation illustrate the knock-on impact rework has on dispensing errors, which is often missing from the traditional linear model-based approaches. This potentially downward-spiral knock-on effect makes it more challenging to deal with demand variability, for example, due to hospital winter pressures. The results provide pharmacy management in-depth insights into potential downward-spiral knock-on effects of high workload and potential challenges in dealing with demand variability. Results and simulated scenarios reveal that it is better to have a fixed adequate staff number throughout the day to keep backlog and dispensing errors to a minimum than calling additional staff to combat growing backlog; and that whilst having a significant amount of trainees might be cost efficient, it has a detrimental effect on dispensing errors (safety) as number of rework done to correct the errors increases and contributes to the growing backlog. Finally, capacity depletion initiated by high workload (over 85% of total workload), even in short bursts, has a significant effect on the amount of rework. Evaluative feedback revealed that participatory SD modelling can help support consensus agreement, thus gaining a deeper understanding of the complex interactions in the systems they strive to manage. The model introduced an intervention to pharmacy management by changing their mental models on how hospital winter pressures, various staffing arrangements, interruptions and fatigue affect productivity and safety. Although the outcome of the process is the model as an artefact, we concluded that the main benefit is the significant mental model change on how hospital winter pressures, various staffing arrangements, interruptions and fatigue are interconnected, as derived from participants involvement and their interactions with the GUI scenarios. The research contributes to the advancement of participatory SD modelling approach within healthcare by evaluating its utility and usability as a learning method, which until recently, has been dominated by the linear reductionist approaches. Methodologically, this is one of the few studies to apply participatory SD approach as a modelling tool for understanding trade-offs dynamics between safety and efficiency in healthcare. Practically, this research provides stakeholders and managers, from pharmacists to managers the decision support tools in the form of a GUI-based platform showcasing the integrated conceptual and simulation model for staffing level management in hospital pharmacy.

Discrete-event simulation can be a useful tool in analyzing complex system dynamics in various industries. However, it is difficult for entry-level users of discrete-event simulation software to both collect the appropriate data to create a model and to actually generate the base-case simulation model. These difficulties decrease the usefulness of simulation software and limit its application in areas in which it could be potentially useful. This research proposes and evaluates a data collection and analysis methodology that would allow for the programmatic generation of simulation models using production tracking data. It uses data collected from a GPS device that follows products as they move through a system. The data is then analyzed by identifying accelerations in movement as the products travel and then using those accelerations to determine discrete events of the system. The data is also used to identify flow paths, pseudo-capacities, and to characterize the discrete events. Using the results of this analysis, it is possible to then generate a base-case discrete event simulation. The research finds that discrete event simulations can be programmatically generated within certain limitations. It was found that, within these limitations, the data collection and analysis method could be used to build and characterize a representative simulation model. A test scenario found that a model could be generated with 2.1% error on the average total throughput time of a product in the system, and less than 8% error on the average throughput time of a product through any particular process in the system. The research also found that the time to build a model under the proposed method is likely significantly less, as it took an experienced simulation modeler .4% of the time to build a simple model based off a real-world scenario programmatically than it did to build the model manually.

Institutional and epistemological differences between science and management present a challenge to the implementation of sustainable environmental management. Environmental problems are complex and require at least multidisciplinary, but most effectively transdisciplinary approaches for learning, understanding, decision-making and problem solving. This means building bridges between institutional and epistemological differences. The role of system dynamics modelling in integrating environmental science and management is examined in this thesis. An action research methodology is adopted where, over cycles of case studies, the practical application of system dynamics modelling is evaluated. The role of system dynamics modelling in the management of coastal sand dunes, tourism, threatened species management and water management is explored in the case studies. It has been found that system dynamics modelling is a potentially powerful tool for integrating environmental science and management, principally assisting communication between scientists and management stakeholders. System dynamics group model-building, in particular, has the potential to facilitate stakeholder learning and assist stakeholders to think holistically about the complex systems they are trying to manage. It was also found that engaging stakeholders in system dynamics group model-building process is difficult. A model of factors influencing the adoption of system dynamics group model-building has been developed from this research. The model can be applied to assess the suitability of potential case studies and identify potential weaknesses that need to be addressed if the approach is to succeed.

This thesis examined the factors correlated with rapid and benign progression of disease in a group of 1452 Parkinsons disease (PD) patients. The data were collected in a movement disorders clinic at the Royal University Hospital, University of Saskatchewan run by Dr. Alex Rajput and Dr. Ali Rajput. This data is a clinical dataset of PD patients collected from 1970 through to February, 2005. This was a retrospective cases-only study, with anticipated analytical follow-up if any correlations were detected between progression type of PD and the many independent variables available in the dataset. <p>Rapid progression was defined as those subjects who reached Hoehn and Yahr stage 3 within three years or H&Y stage 4 or 5 within five years. Subjects who remained in Hoehn and Yahr stage 1 or 2, ten years after onset of disease, were defined as having benign progression. The study analyzed demographic and clinical findings at first visit to this clinic associated with rapid and benign progression of PD. <p> Analysis revealed that, at first clinic visit, benign progression was positively associated with disease duration (OR=1.41; 95% CI 1.27, 1.57), male sex (OR=3.23; 95% CI 1.70, 6.16), and current smoking habit (OR=2.33; 95% CI 0.67, 8.11). Benign progression was negatively associated with older age of onset (OR=0.36; 95% CI 0.25, 0.50), past history of smoking (OR=0.46; 95% CI 0.24, 0.89), current or past use of levodopa (OR=0.45; 95% CI 0.21, 0.98), and mild to severe rigidity (OR=0.43; 95% CI 0.23, 0.80). <p>Analysis also revealed that, at first clinic visit, rapid progression was positively associated with older age of onset (OR=2.45; 95% CI 1.80, 3.33) and mild to severe rigidity (OR=1.73; 95% CI 1.02, 2.94). Rapid progression was negatively associated with disease duration (OR=0.52; 95% CI 0.44, 0.62), male sex (OR=0.58; CI 0.35, 0.95), and mild to severe resting tremor (OR=0.47; CI 0.28, 0.77). <p>The results of this study indicate that age of onset, disease duration, male sex, and rigidity are good potential predictors of disease progression in PD because they have opposite associations with rapid and benign progression. History of levodopa use was negatively associated with benign progression and as such may be good indicator of non-benign progression. Although previous studies found no predictive value for smoking history, the current study reported a unique association between smoking history and benign progression. Past smoking history was negatively associated with benign progression. While there was a positive association with current smoking history, the result was not statistically significant. Resting tremor was negatively associated with rapid progression and as such may be a good indicator of non-rapid progression. <p> Disease characteristics collected at first clinic visit are useful in predicting the course of progression of PD. With more rapid progression of PD closer and more frequent follow-up of patients may be necessary.

This thesis examined the factors correlated with rapid and benign progression of disease in a group of 1452 Parkinsons disease (PD) patients. The data were collected in a movement disorders clinic at the Royal University Hospital, University of Saskatchewan run by Dr. Alex Rajput and Dr. Ali Rajput. This data is a clinical dataset of PD patients collected from 1970 through to February, 2005. This was a retrospective cases-only study, with anticipated analytical follow-up if any correlations were detected between progression type of PD and the many independent variables available in the dataset. <p>Rapid progression was defined as those subjects who reached Hoehn and Yahr stage 3 within three years or H&Y stage 4 or 5 within five years. Subjects who remained in Hoehn and Yahr stage 1 or 2, ten years after onset of disease, were defined as having benign progression. The study analyzed demographic and clinical findings at first visit to this clinic associated with rapid and benign progression of PD. <p> Analysis revealed that, at first clinic visit, benign progression was positively associated with disease duration (OR=1.41; 95% CI 1.27, 1.57), male sex (OR=3.23; 95% CI 1.70, 6.16), and current smoking habit (OR=2.33; 95% CI 0.67, 8.11). Benign progression was negatively associated with older age of onset (OR=0.36; 95% CI 0.25, 0.50), past history of smoking (OR=0.46; 95% CI 0.24, 0.89), current or past use of levodopa (OR=0.45; 95% CI 0.21, 0.98), and mild to severe rigidity (OR=0.43; 95% CI 0.23, 0.80). <p>Analysis also revealed that, at first clinic visit, rapid progression was positively associated with older age of onset (OR=2.45; 95% CI 1.80, 3.33) and mild to severe rigidity (OR=1.73; 95% CI 1.02, 2.94). Rapid progression was negatively associated with disease duration (OR=0.52; 95% CI 0.44, 0.62), male sex (OR=0.58; CI 0.35, 0.95), and mild to severe resting tremor (OR=0.47; CI 0.28, 0.77). <p>The results of this study indicate that age of onset, disease duration, male sex, and rigidity are good potential predictors of disease progression in PD because they have opposite associations with rapid and benign progression. History of levodopa use was negatively associated with benign progression and as such may be good indicator of non-benign progression. Although previous studies found no predictive value for smoking history, the current study reported a unique association between smoking history and benign progression. Past smoking history was negatively associated with benign progression. While there was a positive association with current smoking history, the result was not statistically significant. Resting tremor was negatively associated with rapid progression and as such may be a good indicator of non-rapid progression. <p> Disease characteristics collected at first clinic visit are useful in predicting the course of progression of PD. With more rapid progression of PD closer and more frequent follow-up of patients may be necessary.