Consulting Services to Determine the Effectiveness of Vegetation Classification Using WorldView 2 Satellite Data for the Greater Everglades

The purpose of this project was to evaluate the use of remote sensing 1) to detect and map Everglades wetland plant communities at different scales; and 2) to compare map products delineated and resampled at various scales with the intent to quantify and describe the quantitative and qualitative differences between such products. We evaluated data provided by Digital Globe’s WorldView 2 (WV2) sensor with a spatial resolution of 2m and data from Landsat’s Thematic and Enhanced Thematic Mapper (TM and ETM+) sensors with a spatial resolution of 30m. We were also interested in the comparability and scalability of products derived from these data sources. The adequacy of each data set to map wetland plant communities was evaluated utilizing two metrics: 1) model-based accuracy estimates of the classification procedures; and 2) design-based post-classification accuracy estimates of derived maps.

Labeling large scale social media data using budget-driven One-class SVM classification

The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

Numerical simulation for dynamic positioning in pack ice

This thesis investigates the numerical modelling of Dynamic Position (DP) in pack ice. A two-dimensional numerical model for ship-ice interaction was developed using the Discrete Element Method (DEM). A viscous-elastic ice rheology was adopted to model the dynamic behaviour of the ice floes. Both the ship-ice and the ice-ice contacts were considered in the interaction force. The environment forces and the hydrodynamic forces were calculated by empirical formulas. After the current position and external forces were calculated, a Proportional-Integral-Derivative (PID) control and thrust allocation algorithms were applied on the vessel to control its motion and heading. The numerical model was coded in Fortran 90 and validated by comparing computation results to published data. Validation work was first carried out for the ship-ice interaction calculation, and former researchers’ simulation and model test results were used for the comparison. With confidence in the interaction model, case studies were conducted to predict the DP capability of a sample Arctic DP vessel.

Essays on Intergenerational and Regional Aspects of Water Management

This dissertation consists of three essays on different aspects of water management. The first essay focuses on the sustainability of freshwater use by introducing the notion that altruistic parents do bequeath economic assets for their offspring. Constructing a two-period, over-lapping generational model, an optimal ratio of consumption and pollution for old and young generations in each period is determined. Optimal levels of water consumption and pollution change according to different parameters, such as, altruistic degree, natural recharge rate, and population growth. The second essay concerns water sharing between countries in the case of trans-boundary river basins. The paper recognizes that side payments fail to forge water-sharing agreement among the international community and that downstream countries have weak bargaining power. An interconnected game approach is developed by linking the water allocation issue with other non-water issues such as trade or border security problems, creating symmetry between countries in bargaining power. An interconnected game forces two countries to at least partially cooperate under some circumstances. The third essay introduces the concept of virtual water (VW) into a traditional international trade model in order to estimate water savings for a water scarce country. A two country, two products and two factors trade model is developed, which includes not only consumers and producer’s surplus, but also environmental externality of water use. The model shows that VW trade saves water and increases global and local welfare. This study should help policy makers to design appropriate subsidy or tax policy to promote water savings especially in water scarce countries.

Geochemical and stable isotope composition of Middle Campanian marl-limestone rhythmites of the Lehrte West Syncline near Hannover (Lower Saxony, northern Germany)

A cyclic marl-limestone succession of Middle-Late Campanian age has been investigated with respect to a Milankovitch-controlled origin of geochemical data. In general, the major element geochemistry of the marl-limestone rhythmites can be explained by a simple two-component mixing model with the end-members calcium carbonate and 'average shale'-like material. Carbonate content varies from 55 to 90%. Non-carbonate components are clay minerals (illite, smectite) and biogenic silica from sponge spicules, as well as authigenically formed zeolites (strontian heulandite) and quartz. The redox potential suggests oxidizing conditions throughout the section. Trace element and stable isotopic data as well as SEM investigations show that the carbonate mud is mostly composed of low-magnesium calcitic tests of planktic coccolithophorids and calcareous dinoflagellate cysts (calcispheres). Diagenetic overprint results in a decrease of 2% d18O and an increase in Mn of up to 250 ppm. However, the sediment seems to preserve most of its high Sr content compared to the primary low-magnesium calcite of co-occurring belemnite rostra. The periodicity of geochemical cycles is dominated by 413 ka and weak signals between 51 and 22.5 ka, attributable to orbital forcing. Accumulation rates within these cycles vary between 40 and 50 m/Ma. The resulting cyclic sedimentary sequence is the product of (a) changes in primary production of low-magnesium calcitic biogenic material in surface waters within the long eccentricity and the precession, demonstrated by the CaCO3 content and the Mg/Al, Mn/Al and Sr/Al ratios, and (b) fluctuations in climate and continental weathering, which changed the quality of supplied clay minerals (the illite/smectite ratio), demonstrated by the K/Al ratio. High carbonate productivity correlates with smectite-favouring weathering (semi-arid conditions, conspicuously dry and moist seasonal changes in warmer climates). Ti as the proxy indicator for the detrital terrigenous influx, as well as Rb, Si, Zr and Na, shows only low frequency signals, indicating nearly constant rates of supply throughout the more or less pure pelagic carbonate deposition of the long-lasting third-order Middle-Upper Campanian sedimentary cycle.

Lead isotope ratios of basalts from DSDP Leg 37 (Table 1)

Analyses of Pb from mid-ocean ridge basalts obtained from DSDP Leg 37 lie on a line of near-zero-age slope. The data seem consistent with an evolutionary model of three stages, the beginning of the second stage being at about 600 m.y. - the model age obtained for the least radiogenic Pb. The beginning of the third stage of evolution at the time of formation of the rocks apparently did not change the average Th/U ratio since measured values are consistent with the ratio deduced from Pb isotope ratios. Ratios of U/Pb are not consistent with Pb isotope ratios, however, thus ruling out a simple two-stage evolutionary model.

Essays in dynamic optimal taxation: working experience, unemployment scarring and poverty

This thesis investigates the design of optimal tax systems in dynamic environments. The first essay characterizes the optimal tax system where wages depend on stochastic shocks and work experience. In addition to redistributive and efficiency motives, the taxation of inexperienced workers depends on a second-best requirement that encourages work experience, a social insurance motive and incentive effects. Calibrations using U.S. data yield higher expected optimal marginal income tax rates for experienced workers for most of the inexperienced workers. They confirm that the average marginal income tax rate increases (decreases) with age when shocks and work experience are substitutes (complements). Finally, more variability in experienced workers' earnings prospects leads to increasing tax rates since income taxation acts as a social insurance mechanism. In the second essay, the properties of an optimal tax system are investigated in a dynamic private information economy where labor market frictions create unemployment that destroys workers' human capital. A two-skill type model is considered where wages and employment are endogenous. I find that the optimal tax system distorts the first-period wages of all workers below their efficient levels which leads to more employment. The standard no-distortion-at-the-top result no longer holds due to the combination of private information and the destruction of human capital. I show this result analytically under the Maximin social welfare function and confirm it numerically for a general social welfare function. I also investigate the use of a training program and job creation subsidies. The final essay analyzes the optimal linear tax system when there is a population of individuals whose perceptions of savings are linked to their disposable income and their family background through family cultural transmission. Aside from the standard equity/efficiency trade-off, taxes account for the endogeneity of perceptions through two channels. First, taxing labor decreases income, which decreases the perception of savings through time. Second, taxation on savings corrects for the misperceptions of workers and thus savings and labor decisions. Numerical simulations confirm that behavioral issues push labor income taxes upward to finance saving subsidies. Government transfers to individuals are also decreased to finance those same subsidies.

Stress Inversion Using LiDAR Tunnel Deformation Measurements

Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.

Nonequilibrium critical scaling from quantum thermodynamics

The emerging field of quantum thermodynamics is contributing important results and insights into archetypal many-body problems, including quantum phase transitions. Still, the question whether out-of-equilibrium quantities, such as fluctuations of work, exhibit critical scaling after a sudden quench in a closed system has remained elusive. Here, we take a novel approach to the problem by studying a quench across an impurity quantum critical point. By performing density matrix renormalization group computations on the two-impurity Kondo model, we are able to establish that the irreversible work produced in a quench exhibits finite-size scaling at quantum criticality. This scaling faithfully predicts the equilibrium critical exponents for the crossover length and the order parameter of the model, and, moreover, implies a new exponent for the rescaled irreversible work. By connecting the irreversible work to the two-impurity spin correlation function, our findings can be tested experimentally.

Shooting for the Moon or Flying Too Near the Sun? Crossing the Value Rubicon in Precision Cancer Care

In his last two State of the Union addresses, President Barack Obama has focused on the need to deliver innovative solutions to improve human health, through the Precision Medicine Initiative in 2015 and the recently announced Cancer Moonshot in 2016. Precision cancer care has delivered clear patient benefit, but even for high-impact medicines such as imatinib mesylate (Glivec) in chronic myeloid leukaemia, the excitement at the success of this practice-changing clinical intervention has been somewhat tempered by the escalating price of this 'poster child' for precision cancer medicine (PCM). Recent studies on the costs of cancer drugs have revealed significant price differentials, which are a major causative factor behind disparities in the access to new generations of immunological and molecularly targeted agents. In this perspective, we will discuss the benefits of PCM to modern cancer control, but also emphasise how increasing costs are rendering the current approaches to integrating the paradigm of PCM unsustainable. Despite the ever increasing pressure on cancer and health care budgets, innovation will and must continue. Value-based frameworks offer one of the most rational approaches for policymakers committed to improving cancer outcomes through a public health approach.

Catalyst screening: Refinement of the origin of the volcano curve and its implication in heterogeneous catalysis

Understanding the overall catalytic activity trend for rational catalyst design is one of the core goals in heterogeneous catalysis. In the past two decades, the development of density functional theory (DFT) and surface kinetics make it feasible to theoretically evaluate and predict the catalytic activity variation of catalysts within a descriptor-based framework. Thereinto, the concept of the volcano curve, which reveals the general activity trend, usually constitutes the basic foundation of catalyst screening. However, although it is a widely accepted concept in heterogeneous catalysis, its origin lacks a clear physical picture and definite interpretation. Herein, starting with a brief review of the development of the catalyst screening framework, we use a two-step kinetic model to refine and clarify the origin of the volcano curve with a full analytical analysis by integrating the surface kinetics and the results of first-principles calculations. It is mathematically demonstrated that the volcano curve is an essential property in catalysis, which results from the self-poisoning effect accompanying the catalytic adsorption process. Specifically, when adsorption is strong, it is the rapid decrease of surface free sites rather than the augmentation of energy barriers that inhibits the overall reaction rate and results in the volcano curve. Some interesting points and implications in assisting catalyst screening are also discussed based on the kinetic derivation. Moreover, recent applications of the volcano curve for catalyst design in two important photoelectrocatalytic processes (the hydrogen evolution reaction and dye-sensitized solar cells) are also briefly discussed.

Computational approaches and tools for modeling biomass pyrolysis

Thesis (Ph.D.)--University of Washington, 2016-08

Essays in International Finance and Macroeconomics

Thesis (Ph.D.)--University of Washington, 2016-08

Chitosan scaffold as an alternative adsorbent for the removal of hazardous food dyes from aqueous solutions

Hypothesis: The dye adsorption with chitosan is considered an eco-friendly alternative technology in relation to the existing water treatment technologies. However, the application of chitosan for dyes removal is limited, due to its low surface area and porosity. Then we prepared a chitosan scaffold with a megaporous structure as an alternative adsorbent to remove food dyes from solutions. Experiments: The chitosan scaffold was characterized by infrared spectroscopy, scanning electron microscopy and structural characteristics. The potential of chitosan scaffold to remove five food dyes from solutions was investigated by equilibrium isotherms and thermodynamic study. The scaffold–dyes interactions were elucidated, and desorption studies were carried out. Findings: The chitosan scaffold presented pore sizes from 50 to 200 lm, porosity of 92.2 ± 1.2% and specific surface area of 1135 ± 2 m2 g 1. The two-step Langmuir model was suitable to represent the equilibrium data. The adsorption was spontaneous, favorable, exothermic and enthalpy-controlled process. Electrostatic interactions occurred between chitosan scaffold and dyes. Desorption was possible with NaOH solution (0.10 mol L 1). The chitosan megaporous scaffold showed good structural characteristics and high adsorption capacities (788–3316 mg g 1).

Integrability for Relativistic Spin Networks

The evaluation of relativistic spin networks plays a fundamental role in the Barrett-Crane state sum model of Lorentzian quantum gravity in 4 dimensions. A relativistic spin network is a graph labelled by unitary irreducible representations of the Lorentz group appearing in the direct integral decomposition of the space of L^2 functions on three-dimensional hyperbolic space. To `evaluate' such a spin network we must do an integral; if this integral converges we say the spin network is `integrable'. Here we show that a large class of relativistic spin networks are integrable, including any whose underlying graph is the 4-simplex (the complete graph on 5 vertices). This proves a conjecture of Barrett and Crane, whose validity is required for the convergence of their state sum model.