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- Genre: Masters Thesis
Description
A new method for generating artificial fingerprints is presented. Due to their uniqueness and durability, fingerprints are invaluable tools for identification for law enforcement and other purposes. Large databases of varied, realistic artificial fingerprints are needed to aid in the development and evaluation of automated systems for criminal or biometric identification. Further, an effective method for simulating fingerprints may provide insight into the biological processes underlying print formation. However, previous attempts at simulating prints have been unsatisfactory. We approach the problem of creating artificial prints through a pattern formation model. We demonstrate how it is possible to generate distinctive patterns that strongly resemble real fingerprints via a system of partial differential equations with a suitable domain and initial conditions.
ContributorsColtin, Kevin (Author) / Armbruster, Hans D (Thesis advisor) / Platte, Rodrigo B (Committee member) / Welfert, Bruno D (Committee member) / Arizona State University (Publisher)
Created2013
Description
From 2D planar MOSFET to 3D FinFET, the geometry of semiconductor devices is getting more and more complex. Correspondingly, the number of mesh grid points increases largely to maintain the accuracy of carrier transport and heat transfer simulations. By substituting the conventional uniform mesh with non-uniform mesh, one can reduce the number of grid points. However, the problem of how to solve governing equations on non-uniform mesh is then imposed to the numerical solver. Moreover, if a device simulator is integrated into a multi-scale simulator, the problem size will be further increased. Consequently, there exist two challenges for the current numerical solver. One is to increase the functionality to accommodate non-uniform mesh. The other is to solve governing physical equations fast and accurately on a large number of mesh grid points.
This research rst discusses a 2D planar MOSFET simulator and its numerical solver, pointing out its performance limit. By analyzing the algorithm complexity, Multigrid method is proposed to replace conventional Successive-Over-Relaxation method in a numerical solver. A variety of Multigrid methods (standard Multigrid, Algebraic Multigrid, Full Approximation Scheme, and Full Multigrid) are discussed and implemented. Their properties are examined through a set of numerical experiments. Finally, Algebraic Multigrid, Full Approximation Scheme and Full Multigrid are integrated into one advanced numerical solver based on the exact requirements of a semiconductor device simulator. A 2D MOSFET device is used to benchmark the performance, showing that the advanced Multigrid method has higher speed, accuracy and robustness.
This research rst discusses a 2D planar MOSFET simulator and its numerical solver, pointing out its performance limit. By analyzing the algorithm complexity, Multigrid method is proposed to replace conventional Successive-Over-Relaxation method in a numerical solver. A variety of Multigrid methods (standard Multigrid, Algebraic Multigrid, Full Approximation Scheme, and Full Multigrid) are discussed and implemented. Their properties are examined through a set of numerical experiments. Finally, Algebraic Multigrid, Full Approximation Scheme and Full Multigrid are integrated into one advanced numerical solver based on the exact requirements of a semiconductor device simulator. A 2D MOSFET device is used to benchmark the performance, showing that the advanced Multigrid method has higher speed, accuracy and robustness.
ContributorsGuo, Xinchen (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Ferry, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
This thesis presents a model for the buying behavior of consumers in a technology market. In this model, a potential consumer is not perfectly rational, but exhibits bounded rationality following the axioms of prospect theory: reference dependence, diminishing returns and loss sensitivity. To evaluate the products on different criteria, the analytic hierarchy process is used, which allows for relative comparisons. The analytic hierarchy process proposes that when making a choice between several alternatives, one should measure the products by comparing them relative to each other. This allows the user to put numbers to subjective criteria. Additionally, evidence suggests that a consumer will often consider not only their own evaluation of a product, but also the choices of other consumers. Thus, the model in this paper applies prospect theory to products with multiple attributes using word of mouth as a criteria in the evaluation.
ContributorsElkholy, Alexander (Author) / Armbruster, Dieter (Thesis advisor) / Kempf, Karl (Committee member) / Li, Hongmin (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis considers the application of basis pursuit to several problems in system identification. After reviewing some key results in the theory of basis pursuit and compressed sensing, numerical experiments are presented that explore the application of basis pursuit to the black-box identification of linear time-invariant (LTI) systems with both finite (FIR) and infinite (IIR) impulse responses, temporal systems modeled by ordinary differential equations (ODE), and spatio-temporal systems modeled by partial differential equations (PDE). For LTI systems, the experimental results illustrate existing theory for identification of LTI FIR systems. It is seen that basis pursuit does not identify sparse LTI IIR systems, but it does identify alternate systems with nearly identical magnitude response characteristics when there are small numbers of non-zero coefficients. For ODE systems, the experimental results are consistent with earlier research for differential equations that are polynomials in the system variables, illustrating feasibility of the approach for small numbers of non-zero terms. For PDE systems, it is demonstrated that basis pursuit can be applied to system identification, along with a comparison in performance with another existing method. In all cases the impact of measurement noise on identification performance is considered, and it is empirically observed that high signal-to-noise ratio is required for successful application of basis pursuit to system identification problems.
ContributorsThompson, Robert C. (Author) / Platte, Rodrigo (Thesis advisor) / Gelb, Anne (Committee member) / Cochran, Douglas (Committee member) / Arizona State University (Publisher)
Created2012
Description
A functioning food web is the basis of a functioning community and ecosystem. Thus, it is important to understand the dynamics that control species behaviors and interactions. Alterations to the fundamental dynamics can prove detrimental to the future success of our environment. Research and analysis focus on the global dynamics involved in intraguild predation (IGP), a three species subsystem involving both competition and predation. A mathematical model is derived using differential equations based on pre-existing models to accurately predict species behavior. Analyses provide sufficient conditions for species persistence and extinction that can be used to explain global dynamics. Dynamics are compared for two separate models, one involving a specialist predator and the second involving a generalist predator, where systems involving a specialist predator are prone to unstable dynamics. Analyses have implications in biological conservation tactics including various methods of prevention and preservation. Simulations are used to compare dynamics between models involving continuous time and those involving discrete time. Furthermore, we derive a semi-discrete model that utilizes both continuous and discrete time series dynamics. Simulations imply that Holling's Type III functional response controls the potential for three species persistence. Complicated dynamics govern the IGP subsystem involving the white-footed mouse, gypsy moth, and oak, and they ultimately cause the synchronized defoliation of forests across the Northeastern United States. Acorn mast seasons occur every 4-5 years, and they occur simultaneously across a vast geographic region due to universal cues. Research confirms that synchronization can be transferred across trophic levels to explain how this IGP system ultimately leads to gypsy moth outbreaks. Geographically referenced data is used to track and slow the spread of gypsy moths further into the United States. Geographic Information Systems (GIS) are used to create visual, readily accessible, displays of trap records, defoliation frequency, and susceptible forest stands. Mathematical models can be used to explain both changes in population densities and geographic movement. Analyses utilizing GIS softwares offer a different, but promising, way of approaching the vast topic of conservation biology. Simulations and maps are produced that can predict the effects of conservation efforts.
ContributorsWedekin, Lauren (Author) / Kang, Yun (Thesis advisor) / Green, Douglas (Committee member) / Miller, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Presented is a study on the chemotaxis reaction process and its relation with flow topology. The effect of coherent structures in turbulent flows is characterized by studying nutrient uptake and the advantage that is received from motile bacteria over other non-motile bacteria. Variability is found to be dependent on the initial location of scalar impurity and can be tied to Lagrangian coherent structures through recent advances in the identification of finite-time transport barriers. Advantage is relatively small for initial nutrient found within high stretching regions of the flow, and nutrient within elliptic structures provide the greatest advantage for motile species. How the flow field and the relevant flow topology lead to such a relation is analyzed.
ContributorsJones, Kimberly (Author) / Tang, Wenbo (Thesis advisor) / Kang, Yun (Committee member) / Jones, Donald (Committee member) / Arizona State University (Publisher)
Created2015
Description
Topological methods for data analysis present opportunities for enforcing certain invariances of broad interest in computer vision: including view-point in activity analysis, articulation in shape analysis, and measurement invariance in non-linear dynamical modeling. The increasing success of these methods is attributed to the complementary information that topology provides, as well as availability of tools for computing topological summaries such as persistence diagrams. However, persistence diagrams are multi-sets of points and hence it is not straightforward to fuse them with features used for contemporary machine learning tools like deep-nets. In this paper theoretically well-grounded approaches to develop novel perturbation robust topological representations are presented, with the long-term view of making them amenable to fusion with contemporary learning architectures. The proposed representation lives on a Grassmann manifold and hence can be efficiently used in machine learning pipelines.
The proposed representation.The efficacy of the proposed descriptor was explored on three applications: view-invariant activity analysis, 3D shape analysis, and non-linear dynamical modeling. Favorable results in both high-level recognition performance and improved performance in reduction of time-complexity when compared to other baseline methods are obtained.
The proposed representation.The efficacy of the proposed descriptor was explored on three applications: view-invariant activity analysis, 3D shape analysis, and non-linear dynamical modeling. Favorable results in both high-level recognition performance and improved performance in reduction of time-complexity when compared to other baseline methods are obtained.
ContributorsThopalli, Kowshik (Author) / Turaga, Pavan Kumar (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2017
Description
I investigate two models interacting agent systems: the first is motivated by the flocking and swarming behaviors in biological systems, while the second models opinion formation in social networks. In each setting, I define natural notions of convergence (to a ``flock" and to a ``consensus'', respectively), and study the convergence properties of each in the limit as $t \rightarrow \infty$. Specifically, I provide sufficient conditions for the convergence of both of the models, and conduct numerical experiments to study the resulting solutions.
ContributorsTheisen, Ryan (Author) / Motsch, Sebastien (Thesis advisor) / Lanchier, Nicholas (Committee member) / Kostelich, Eric (Committee member) / Arizona State University (Publisher)
Created2018
Description
There was a growing trend in the automotive market on the adoption of Hybrid Electric Vehicles (HEVs) for consumers to purchase. This was partially due to external pressures such as the effects of global warming, cost of petroleum, governmental regulations, and popularity of the vehicle type. HEV technology relied on a variety of factors which included the powertrain (PT) of the system, external driving conditions, and the type of driving pattern being driven. The core foundation for HEVs depended heavily on the battery pack and chemistry being adopted for the vehicle performance and operations. This paper focused on the effects of hot and arid temperatures on the performance of LiFePO4 (LFP) battery packs and presented a possible modeling method for overall performance.
Lithium-ion battery (LIB) packs were subjected to room and high temperature settings while being cycled under a current profile created from a drive cycle. The Federal Urban Driving Schedule (FUDS) was selected and modified to simulate normal city driving situation using an electric only drive mode. Capacity and impedance fade of the LIB packs were monitored over the lifetime of the pack to determine the overall performance through the variables of energy and power fade. Regression analysis was done on the energy and power fade of the LIB pack to determine the duration life of LIB packs for HEV applications. This was done by comparing energy and power fade with the average lifetime mileage of a vehicle.
The collected capacity and impedance data was used to create an electrical equivalent model (EEM). The model was produced through the process of a modified Randles circuit and the creation of the inverse constant phase element (ICPE). Results indicated the model had a potential for high fidelity as long as a sufficient amount of data was gathered. X-ray powder diffraction (XRD) and a scanning electron microscope (SEM) was performed on a fresh and cycled LFP battery. SEM results suggested a dramatic growth on LFP crystals with a reduction in carbon coating after cycling. XRD effects showed a slight uniformed strain and decrease in size of LFP olivine crystals after cycling.
Lithium-ion battery (LIB) packs were subjected to room and high temperature settings while being cycled under a current profile created from a drive cycle. The Federal Urban Driving Schedule (FUDS) was selected and modified to simulate normal city driving situation using an electric only drive mode. Capacity and impedance fade of the LIB packs were monitored over the lifetime of the pack to determine the overall performance through the variables of energy and power fade. Regression analysis was done on the energy and power fade of the LIB pack to determine the duration life of LIB packs for HEV applications. This was done by comparing energy and power fade with the average lifetime mileage of a vehicle.
The collected capacity and impedance data was used to create an electrical equivalent model (EEM). The model was produced through the process of a modified Randles circuit and the creation of the inverse constant phase element (ICPE). Results indicated the model had a potential for high fidelity as long as a sufficient amount of data was gathered. X-ray powder diffraction (XRD) and a scanning electron microscope (SEM) was performed on a fresh and cycled LFP battery. SEM results suggested a dramatic growth on LFP crystals with a reduction in carbon coating after cycling. XRD effects showed a slight uniformed strain and decrease in size of LFP olivine crystals after cycling.
ContributorsOpitz, Andrew (Author) / Kannan, Arunachala (Thesis advisor) / Mayyas, Abdel (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2016
Description
A numerical study of chemotaxis in 3D turbulence is presented here. Direct Numerical
Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial
species and by applying the dynamical systems theory the effect of flow topology on the
variability of chemotaxis is analyzed. It is done by injecting a highly localized patch of nutrient
in the turbulent flow, and analyzing the evolution of reaction associated with the observed
high and low stretching regions. The Gaussian nutrient patch is released at different locations
and the corresponding nutrient uptake is obtained. The variable stretching characteristics of
the flow is depicted by Lagrangian Coherent Structures and the roles they play in affecting the
uptake are analyzed. The Lagrangian Coherent Structures are quantified by the Finite Time
Lyapunov Exponents which is a measure of the average stretching experienced by the flow in
finite time. It is found that in high stretching regions, the motile bacteria are attracted to the
nutrient patch very quickly, but also dispersed quickly; whereas in low stretching regions the
bacteria respond slower towards the nutrient patch. However the total uptake is intricately
determined by stretching history. These reaction characteristics are reflected in the several
realizations of simulations. This helps in understanding turbulence intensity and how it affects
the uptake of the nutrient.
Simulation were used to calculate the nutrient uptake for both motile and non-motile bacterial
species and by applying the dynamical systems theory the effect of flow topology on the
variability of chemotaxis is analyzed. It is done by injecting a highly localized patch of nutrient
in the turbulent flow, and analyzing the evolution of reaction associated with the observed
high and low stretching regions. The Gaussian nutrient patch is released at different locations
and the corresponding nutrient uptake is obtained. The variable stretching characteristics of
the flow is depicted by Lagrangian Coherent Structures and the roles they play in affecting the
uptake are analyzed. The Lagrangian Coherent Structures are quantified by the Finite Time
Lyapunov Exponents which is a measure of the average stretching experienced by the flow in
finite time. It is found that in high stretching regions, the motile bacteria are attracted to the
nutrient patch very quickly, but also dispersed quickly; whereas in low stretching regions the
bacteria respond slower towards the nutrient patch. However the total uptake is intricately
determined by stretching history. These reaction characteristics are reflected in the several
realizations of simulations. This helps in understanding turbulence intensity and how it affects
the uptake of the nutrient.
ContributorsGeorge, Jino (Author) / Tang, Wenbo (Thesis advisor) / Peet, Yulia (Thesis advisor) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2017