Constraint-based models of metabolism seldom incorporate capacity constraints on intracellular fluxes due to the lack of experimental data. This can sometimes lead to inaccurate growth phenotype predictions. Meanwhile, other forms of data such as fitness profiling data from growth competition experiments have been demonstrated to contain valuable information for elucidating key aspects of the underlying metabolic network. Hence, the optimal capacity constraint identification (OCCI) algorithm is developed to reconcile constraint-based models of metabolism with fitness profiling data by identifying a set of flux capacity constraints that optimally fits a wide array of strains. OCCI is able to identify capacity constraints with considerable accuracy by matching 1,155 in silico-generated growth rates using a simplified model of Escherichia coli central carbon metabolism. Capacity constraints identified using experimental fitness profiles with OCCI generated novel hypotheses, while integrating thermodynamics-based metabolic flux analysis allowed prediction of metabolite concentrations.

Constraint-based models of metabolism seldom incorporate capacity constraints on intracellular fluxes due to the lack of experimental data. This can sometimes lead to inaccurate growth phenotype predictions. Meanwhile, other forms of data such as fitness profiling data from growth competition experiments have been demonstrated to contain valuable information for elucidating key aspects of the underlying metabolic network. Hence, the optimal capacity constraint identification (OCCI) algorithm is developed to reconcile constraint-based models of metabolism with fitness profiling data by identifying a set of flux capacity constraints that optimally fits a wide array of strains. OCCI is able to identify capacity constraints with considerable accuracy by matching 1,155 in silico-generated growth rates using a simplified model of Escherichia coli central carbon metabolism. Capacity constraints identified using experimental fitness profiles with OCCI generated novel hypotheses, while integrating thermodynamics-based metabolic flux analysis allowed prediction of metabolite concentrations.

Over the last two decades, sanitation policy and development has undergone a paradigm shift away from heavily-subsidized, supply-driven approaches towards behavioral-based demand-driven approaches. These current approaches to increase sanitation demand are multi-faceted, requiring multiple stakeholders with varying degrees of interest, knowledge, and capacity. Although efforts exist to increase sanitation access by incorporating engineering design principles with implementation planning approaches, these groups generally work independently without strong connections, thus reducing the potential of their impact. As a result, the design of appropriate sanitation technology is disengaged from the implementation of acceptable technology into communities, disconnecting user preference integration from sanitation technology design and resulting in fewer sanitation technologies being adopted and used. To address these challenges in developing successful interventions, this research examined how user preferences for specific attributes of appropriate sanitation technologies and their respective implementation arrangements influence their adoption and usage. Data for the study included interviews of 1002 sanitation users living in a peri-urban area of South Africa; the surveyed respondents were asked about their existing sanitation technology, their preferences for various sanitation technology design attributes, as well as their perspectives on current and preferred sanitation implementation arrangements. The data revealed that user acceptability of appropriate sanitation technology is influenced by the adoption classification of the users. Through the identification of motives and barriers to sanitation usage that were statistically significant, it exhibited the need to differentiate users who share private sanitation from those use communal sanitation facilities. Results also indicated that user acceptability of appropriate sanitation systems is dependent on the technical design attributes of sanitation. The development of utility functions detailed the significance of seven technical design attributes and determined their respective priorities. An agent-based simulation examined how user preferences for sanitation technology design and implementation influence its adoption and usage. Findings suggest that user acceptability of sanitation technology is dependent on both the technology design and the implementation arrangement being preferred.

Many practical problems raise the challenge of making decisions over time in the presence of both dynamic complexity and pronounced uncertainty regarding evolution of important factors that affect the dynamics of the system. In this thesis, we provide an end-to-end implementation of an easy-to-use system to confront such challenges. This system gives policy makers a new approach to take complementary advantage of decision analysis techniques and System Dynamics by allowing easy creation, evaluation, and interactive exploration of hybrid models. As an important application of this methodology, we extended a System Dynamic model within the context of West Nile virus transmission in Saskatchewan.

Agent-based modeling (ABM) is a modeling and simulation paradigm well-suited to social systems where agents interact and have some degree of autonomy. In their most basic sense, ABMs consist of agents (generally, individuals) interacting in an environment according to a set of behavioural rules. The foundational premise and the conceptual depth of ABM is that simple rules of individual behaviour will aggregate to illuminate complex and/or emergent group-level phenomena that are not specifically encoded by the modeler and that cannot be predicted or explained by the agent-level rules. In essence, ABM has the potential to reveal a whole that is greater than the sum of its parts. In this thesis, ABMs have been utilized as a modeling framework for three specific healthcare applications, including: • the development of an ABM of an emergency department within a hospital allowing the modeling of contact-based infectious diseases such as influenza, and simulating various mitigation strategies; • the development of an ABM to model the effectiveness of a real-time location system (RTLS) using radio frequency identification (RFID) in an emergency department, used for patient tracking as one measure of hospital efficiency; and, • the development of an ABM to test strategies for disaster preparedness (high volume, high risk patients) using a fictitious case of zombies in an emergency department. Although each ABM was purposeful and meaningful for its custom application, each ABM also represented an iteration toward the development of a generic ABM framework. Finally, a thorough critique of ABMs and the modifications required to create a more robust framework are provided. / February 2016

White-tailed deer (Odocoileus virginianus) are important game mammals and potential reservoirs of diseases of domestic livestock, so diseases of deer are of great concern to wildlife managers. In many situations, models can be useful for integrating existing data, understanding disease transmission patterns, and predicting effects on host populations. Individual-based modeling (IBM) has become more commonplace in ecology as a tool to link individual behavior to population dynamics and community interactions, especially for gauging the effects of management actions. Spatially explicit IBMs are especially useful when ecological processes, such as disease transmission, are affected by the spatial composition of the environment. I developed a spatially explicit IBM, DeerLandscapeDisease (DLD), to simulate direct and indirect disease transmission in white-tailed deer. Using data from GPS-collared deer in southern Illinois, I developed methods to identify habitats and times of high contact probability. I parameterized movement models, for use in DLD, using field data from GPS-collared deer in both southern and east-central Illinois. I then used DLD to simulate deer movements and epizootiology in two different landscapes: a predominantly agricultural landscape with fragmented forest patches in east-central Illinois and a landscape dominated by forest in southern Illinois. Behavioral and demographic parameters that could not be estimated from the field data were estimated using published literature of deer ecology. I assumed that bioavailability of infectious pathogens deposited in the environment decreased exponentially. Transmission probabilities were estimated by fitting to published trends in infection prevalence, assuming that infection probability during an encounter was equal for all age classes, so infection prevalence varied with sex- and age-specific behavior. DLD simulations of chronic wasting disease epizootiology demonstrated significant effects of landscape structure, social behavior, and mode of transmission on prevalence, emphasizing the importance of spatial, temporal and behavioral heterogeneity in disease modeling. These results demonstrate the utility of IBMs in incorporating spatio-temporal variables as well as animal behavior when predicting and modeling disease spread.

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

abstract: The Hohokam of central Arizona left behind evidence of a culture markedly different from and more complex than the small communities of O'odham farmers first encountered by Europeans in the sixteenth and seventeenth centuries A.D. Archaeologists have worked for well over a century to document Hohokam culture history, but much about Pre-Columbian life in the Sonoran Desert remains poorly understood. In particular, the organization of the Hohokam economy in the Phoenix Basin has been an elusive and complicated subject, despite having been the focus of much previous research. This dissertation provides an assessment of several working hypotheses regarding the organization and evolution of the pottery distribution sector of the Hohokam economy. This was accomplished using an agent-based modeling methodology known as pattern-oriented modeling. The objective of the research was to first identify a variety of economic models that may explain patterns of artifact distribution in the archaeological record. Those models were abstract representations of the real-world system theoretically drawn from different sources, including microeconomics, mathematics (network/graph theory), and economic anthropology. Next, the effort was turned toward implementing those hypotheses as agent-based models, and finally assessing whether or not any of the models were consistent with Hohokam ceramic datasets. The project's pattern-oriented modeling methodology led to the discard of several hypotheses, narrowing the range of plausible models of the organization of the Hohokam economy. The results suggest that for much of the Hohokam sequence a market-based system, perhaps structured around workshop procurement and shopkeeper merchandise, provided the means of distributing pottery from specialist producers to widely distributed consumers. Perhaps unsurprisingly, the results of this project are broadly consistent with earlier researchers' interpretations that the structure of the Hohokam economy evolved through time, growing more complex throughout the Preclassic, and undergoing a major reorganization resulting in a less complicated system at the transition to the Classic Period. / Dissertation/Thesis / NetLogo code, software, and model initialization data. / Ph.D. Anthropology 2013

Le but de cette thèse est de faciliter et d'accélérer le dessin pour les amateurs ainsi que pour les dessinateurs experts en utilisant des techniques de traitement d'image et d'interaction. Nous identifions trois problèmes spécifiques liés au dessin, et proposons des outils pour aider les utilisateurs à surmonter les principaux défis sur chaque domaine. Dans le chapitre 2, nous présentons un outil de dessin interactif pour aider des débutants à pratiquer les techniques traditionnelles de dessin par observation. Nous construisons cet outil autour de techniques traditionnelle. Nous extrayons automatiquement des guides visuels à partir d'une photographie. L'interface de l'outil affiche ces informations et offre un retour pour guider l'utilisateur dans la reproduction du dessin. Dans le chapitre 3, nous proposons un outil qui permet aux utilisateurs de créer des bijoux par pliage de fils de fer. Cette forme de bijoux faits à la main peut être considérée comme une forme de dessin à base de fil de fer. La méthode présentée aide l'utilisateur dans les principaux défis de la création de bijoux à partir d'un dessin: la décomposition de l'entrée dans un ensemble de fils, et le pliage des fils pour leur donner forme. Dans le chapitre 4, nous proposons une méthode pour aider les designers à enrichir leurs dessins avec de la couleur et de l'ombrage. Les designers tracent souvent des lignes de courbure pour représenter la forme des surfaces lisses dans des esquisses. Nous exploitons cette information et extrapolons les lignes de courbure dans le design. Cette extrapolation nous permet d'estimer la courbure 3D du dessin, pour créer des ombres et des textures sur l'esquisse. / The goal of this thesis is to facilitate and accelerate drawing for amateurs as well as for expert designers and illustrators, employing computer graphics, image processing and interaction techniques. As this is a broad spectrum to tackle, we identify three specific problems related to drawing and propose computer tools to help users overcome the main challenges on each domain. In Chapter 2 we present an interactive drawing tool to help beginners practice drawing-by-observation techniques. We build on a number of traditional techniques to help people gain consciousness of the shapes in a scene. We automatically extract visual guides from a model photograph and offer corrective feedback to guide their reproduction in the drawing. In Chapter 3 we propose a tool that helps users create wire wrapped jewelry. This technique of handmade jewelry can be seen as a form of line drawing with metal wires. The presented method assist the user in the main challenges of creating 2D wire-wrapped jewelry from a drawing: decomposing the input into a set of wires, and bending the wires to give them shape. In Chapter 4 we propose a method to help designers enrich their drawings with color and shading. Professionals frequently draw curvature lines to convey bending of smooth surfaces in concept sketches. We exploit this information and extrapolate curvature lines in a rough concept sketch. This extrapolation allows us to recover the intended 3D curvature and surface normal at each pixel, which we use to compute shading and texturing over the sketch.

In this thesis we study stochastic modeling and simulation methods for biochemical systems. The thesis is focused on systems with multi-state and multi-scale features and divided into two parts. In the first part, we propose new algorithms that improve existing multi-state simulation methods. We first compare the well known Gillespie\\\'s stochastic simulation algorithm (SSA) with the StochSim, an agent-based simulation method. Based on the analysis, we propose a hybrid method that possesses the advantages of both methods. Then we propose two new methods that extend the Network-Free Algorithm (NFA) for rule-based models. Numerical results are provided to show the performance improvement by our new methods. In the second part, we investigate two simulation schemes for the multi-scale feature: Haseltine and Rawlings\\\' hybrid method and the quasi-steady-state stochastic simulation method. We first propose an efficient partitioning strategy for the hybrid method and an efficient way of building stochastic cell cycle models with this new partitioning strategy. Then, to understand conditions where the two simulation methods can be applied, we develop a way to estimate the relaxation time of the fast sub-network, and compare it with the firing interval of the slow sub-network. Our analysis are verified by numerical experiments on different realistic biochemical models. / Ph. D.