Since the 1970s, Asia has experienced rapid urbanization processes, which are distinct from U.S. society, and the direction of Asian urbanization is more strongly affected by economic globalization. The desakota model, proposed by McGee and Ginsburg in 1991, focuses on how internal domestic and local forces drive the specific rural-urban transformation in Asia. However, the McGee-Ginsburg model does not emphasize the importance of globalization on Asian urbanization. To fill the gap, this study develops a GIS-based CA framework based on the desakota model to not only simulate the unique urbanization processes in Asia but also integrate the influence of globalization into Asian urban dynamics. Three approaches are developed in the CA simulation: 1) physical constraints and land-use classification from remotely sensed images in 1993, 2000, and 2008, are incorporated into micro-scale transformation; 2) population dynamics, shifts of economic activities, and foreign direct investment (FDIs), a representative of the impact of globalization, are applied for multi-scale interconnection; 3) the Monte Carlo mechanism is finally introduced to combine the above two approaches and implement the simulation process. The Taipei metropolitan area, a rapid urbanizing region that highly interacts with the global economy in Asia, is chosen to examine this model. The CA simulation model establishes a strong interaction between FDIs, an indicator representing impacts of globalization, and the dazzling Asian urban model. The combination of multi-scale economic factors and micro-scale land-use transformation also reveals how urban growth of the Taipei metropolis in recent years fits the characterization of the desakota model, and how desakota regions, the growth generators, interact with city cores. As a result, the research not only successfully links the influence of globalization with the desakota model and simulates urban dynamics of Asian cities but also provides scenarios of different FDI inputs for governments to better handle urban growth with global impacts under the deep economic recession since 2007.

Recent advances in the field of educational technology have promoted the re-purposing of entertainment-oriented games and software for educational applications. This thesis extends a project developed at Texas A&M University called Room 309, a re-purposed modification of Valve Software’s Source Development Kit that models classroom scenarios to pre-service teachers. To further explore effectiveness in the area of re-playability, this work incorporates emergent game behaviors and environments using cellular automata, randomness, and influence maps within the existing nonemergent structure. By introducing these qualities game play is expected to become less predictable, thus increasing the effectiveness of Room 309 as a learning tool.

Material damage such as dislocations and microcracks are characteristic of early stages of fatigue. Accumulation of these nascent cracks leads to non-linear elastic response of the material. These non-linearities can be detected from harmonic generation for propagating elastic waves. The long term goal of this study is to investigate the non-linear elastic propagation in parts with complex geometry. Cellular Automata is introduced as a new simulation method, in order to develop new analysis on quadratic non-linearities. An existing linear code was progressively modified to take into account a different constitutive law. Also the boundary conditions need to be reviewed to ensure free stress with the non-linear behavior. The propagation of the longitudinal wave is investigated in detail. Numerical accuracy is validated from comparison with a closed, for both linear and non-linear code. The reflection of the non-linear P-wave gives confirmation for the correct treatment of the boundary condition. Finally the capabilities of the Cellular Automata code are underlined for reflection of Lamb waves for various boundary conditions.

<p>Biofilms are communities of sessile microorganisms attached to a surface and imbeddedin a matrix of extracellular polysaccharide substances. These communities can be foundin diverse aquatic environments, such as in industrial pipes and in humans. By formingmicrocolony structures, which are highly resistant to adverse physical conditions as wellas antimicrobial agents, biofilms are very problematic when associated with e.g.persistent infections. In order to find new ways of controlling biofilm growth, theprocesses involved in biofilm development must be investigated further. The maininterest of this study is the occurrence of void formation inside biofilms. Thisphenomenon has been observed in several studies and has been correlated to cell deathinside the microcolonies. The occurrence of cell death has recently been associated withthe presence of nitric oxide in the biofilm. In this study, the implications of nitric oxideaccumulation on biofilm development were investigated using an individual-basedmodel. Specifically, the role of nitric oxide in void formation was considered. A largenumber of simulations were run using different parameter settings in order to determine ifnitric oxide could account for the occurrence of void formation observed experimentally.The general predictions made by the model system showed agreement to someexperimental data, but not to others. Sloughing, the detachment of chunks of cells fromthe biofilm, was observed in the majority of simulations. In some cases, the model alsopredicted the presence of live cells inside the voids, which has been observedexperimentally.</p>

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Dr. Michael Leamy; Committee Member: Dr. Karim Sabra; Committee Member: Dr. Aldo Ferri. Part of the SMARTech Electronic Thesis and Dissertation Collection.

As CMOS scaling faces a technological barrier in the near future, novel design paradigms are being proposed to keep up with the ever growing need for computation power and speed. Most of these novel technologies have device sizes comparable to atomic and molecular scales. At these levels the quantum mechanical effects play a dominant role in device performance, thus inducing uncertainty. The wave nature of particle matter and the uncertainty associated with device operation make a case for probabilistic modeling of the device. As the dimensions go down to a molecular scale, functioning of a nano-device will be governed primarily by the atomic level device physics. Modeling a device at such a small scale will require taking into account the quantum mechanical phenomenon inherent to the device. In this dissertation, we studied one such nano-device: Quantum-Dot Cellular Automata (QCA). We used probabilistic modeling to perform a fast approximation based method to estimate error, power and reliability in large QCA circuits. First, we associate the quantum mechanical probabilities associated with each QCA cell to design and build a probabilistic Bayesian network. Our proposed modeling is derived from density matrix-based quantum modeling, and it takes into account dependency patterns induced by clocking. Our modeling scheme is orders of magnitude faster than the coherent vector simulation method that uses quantum mechanical simulations. Furthermore, our output node polarization values match those obtained from the state of the art simulations. Second, we use this model to approximate power dissipated in a QCA circuit during a non-adiabatic switching event and also to isolate the thermal hotspots in a design. Third, we also use a hierarchical probabilistic macromodeling scheme to model QCA designs at circuit level to isolate weak spots early in the design process. It can also be used to compare two functionally equivalent logic designs without performing the expensive quantum mechanical simulations. Finally, we perform optimization studies on different QCA layouts by analyzing the designs for error and power over a range of kink energies.To the best of our knowledge the non-adiabatic power model presented in this dissertation is the first work that uses abrupt clocking scheme to estimate realistic power dissipation. All prior works used quasi-adiabatic power dissipation models. The hierarchical macromodel design is also the first work in QCA design that uses circuit level modeling and is faithful to the underlying layout level design. The effect of kink energy to study power-error tradeoffs will be of great use to circuit designers and fabrication scientists in choosing the most suitable design parameters such as cell size and grid spacing.

published_or_final_version / Physics / Master / Master of Philosophy

This study extends a recently-developed [1] cellular automata (CA) elastodynamic modeling approach to arbitrary two-dimensional geometries through development of a rule set appropriate for triangular cells. The approach is fully object-oriented (OO) and exploits OO conventions to produce compact, general, and easily-extended CA classes. Meshes composed of triangular cells allow the elastodynamic response of arbitrary two-dimensional geometries to be computed accurately and efficiently. As in the previous rectangular CA method, each cell represents a state machine which updates in a stepped-manner using a local "bottom-up" rule set and state input from neighboring cells. The approach avoids the need to develop partial differential equations and the complexity therein. Several advantages result from the method's discrete, local and object-oriented nature, including the ability to compute on a massively-parallel basis and to easily add or subtract cells in a multi-resolution manner. The extended approach is used to generate the elastodynamic responses of a variety of general geometries and loading cases (Dirichlet and Nuemann), which are compared to previous results and/or comparison results generated using the commercial finite element code, COMSOL. These include harmonic interior domain loading, uniform boundary traction, and ramped boundary displacement. Favorable results are reported in all cases, with the CA approach requiring fewer degrees of freedom to achieve similar or better accuracy, and considerably less code development.

Thesis (M.A.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 88-91). / viii, 91 leaves, bound col. ill., col. maps 29 cm

Simulating geographic phenomena in a realistic and plausible way requires real-world entities to be abstracted based on the dynamic physical characteristics they exhibit, and treated as individuals in a simulation domain. These processes cannot be adequately supported by the traditional spatial model based on cellular-space such as Cellular Automata (CA). Although this approach has received a great attention as a most favoured technique for simulating the geographic phenomena from different aspects, the need for a generic spatial model to overcome the limitations encountered in such an approach has been raised. This applies particularly to the way real-world entities are represented in a simulation domain regarding their physical characteristics and temporal aspects. In this thesis, a new computational approach for a spatial model suitable for simulating geographic phenomena is presented: the vector agents model. The vector agent is goal-oriented, adaptable, physically defined by an Euclidean geometry and able to change its own geometric characteristics while interacting with other agents in its neighbourhood using a set of rules. The agent is modelled with sensor, state, and strategies. The successful implementation of the model�s architecture allows the representation of the physical characteristics of real-world entities and to observe their complex and dynamic behaviour in a simulation domain. Vector agents have developed out of a need to create a systematic basis for the geometric components of Geographic Automata Systems (GAS), as outlined by Torrens and Benenson (2005). A generic vector agents model was built, then tested and validated from different aspects, from which results demonstrated the model�s efficiency. It is confirmed that vector agents are flexible in producing different complex shapes and patterns for recreating real geographic phenomena through the generic use of three algorithms of geometric manipulation: midpoint displacement by using the relaxed Brownian Motion (fractal-like) algorithm, edge displacement and vertex displacement. The effectiveness of this was initially ascertained visually. A simple heuristic to govern shape growth rate and complexity was derived based on the interplay of the three algorithms. There was a further abstract model comparison against the cellular-agents environment, with the result that vector agents have the ability to emerge patterns similar to what can be produced by cellular-agents with the advantage of representing entities as individuals with their own attributes with realistic geometric boundaries. On the other hand, the city as a complex geographic phenomenon was used as a specific domain for validating the model with a real-world system. The results of the urban land use simulations (driven by simple rules based on three classical urban theories) confirmed that: (a) the model is flexible enough to incorporate various external rules based on real-world systems and (b) the model has a sufficient capability in emerging a variety of patterns under several environments close to actual patterns. The agent environment also proved to be an effective way of easily combining the rules associated with each urban theory (different agents behaved according to different theories). Finally, limitations raised through the development of this work are addressed leading to outline possible extensions of both model computation and the domain of applications.