Thesis (M. P. A.)--Texas State University-San Marcos, 2009. / "Fall 2009." Includes bibliographical references (leaves 104-109).

Thesis supervisor: B Ravikumar. Includes bibliographic references (p. 132-135).

Thesis (Ph. D.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references. Also available via the World Wide Web.

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 2003. / Includes bibliographical references.

High Efficiency Deep Grinding (HEDG) combines high depths of cut, high grinding wheel speeds with high work piece feed rates to deliver a very high stock removal process that can produce components free of surface damage. High contact temperatures are a characteristic of the process and this produces a mass of hot grinding sparks being ejected from the grinding zone. Neat oil cutting fluids are typically used in HEDG due to their excellent lubricity, but the high grinding wheel speeds employed leads to high levels of highly volatile cutting fluid mist in the machine canopy. This mist can mix with the hot grinding sparks being ejected from the grinding zone to create a potential fire hazard. The project aim was to produce a cutting fluid application strategy for the HEDG regime, focusing on establishing the thermal characteristics of cutting fluids in order to determine the optimum cutting fluid for the HEDG process. The cutting fluid application strategy also involved investigating the optimum means by which to apply the cutting fluid, based on minimising amount of cutting fluid used in the process and in reducing the potential fire hazard. The characteristics that have a thermal impact on the grinding process are the cooling, lubrication, ignition and misting properties of the fluid. A series of tests were established to investigate these properties and therefore allow different fluids to be compared and contrasted for their suitability for the HEDG regime based. Once an optimal cutting fluid had been established, the project then investigated the optimal method of applying this fluid, with particular reference to the type and design of the nozzle used to apply the fluid to the grinding zone. As part of these trials, a series of benchmark tests were also conducted using long established cutting fluid application techniques to enable the benefits of the new strategy to be evaluated. The project concluded that high viscosity neat oil ester based cutting fluids were the best fluids to be used in the HEDG regime due to they excellent lubricity and low misting properties coupled to their relatively high resistance to ignition when compared to neat mineral oils. The studies also found that using a high viscosity ester based fluid and then applying it using a coherent jet nozzle, significant reductions in the grinding powder and specific grinding energy could be achieved whilst significantly lowering the amount of mist in the machine, thus reducing the potential fire hazard and the volume of cutting fluid used by the process.

Earthquake-induced landslides are a significant seismic hazard that can generate large economic losses. Predicting earthquake-induced landslides often involves an assessment of the expected sliding displacement induced by the ground shaking. A deterministic approach is commonly used for this purpose. This approach predicts sliding displacements using the expected ground shaking and the best-estimate slope properties (i.e., soil shear strengths, ground water conditions and thicknesses of sliding blocks), and does not consider the aleatory variability in predictions of ground shaking or sliding displacements or the epistemic uncertainties in the slope properties. In this dissertation, a probabilistic framework for predicting the sliding displacement of flexible sliding masses during earthquakes is developed. This framework computes a displacement hazard curve using: (1) a ground motion hazard curve from a probabilistic seismic hazard analysis, (2) a model for predicting the dynamic response of the sliding mass, (3) a model for predicting the sliding response of the sliding mass, and (4) a logic tree that incorporates the uncertainties in the various input parameters. The developed probabilistic framework for flexible sliding masses is applied to a slope at a site in California. The results of this analysis show that the displacements predicted by the probabilistic approach are larger than the deterministic approach due to the influence of the uncertainties in the slope properties. Reducing these uncertainties can reduce the predicted displacements. Regional maps of seismic landslide potential are used in land-use planning and to identify zones that require detailed, site-specific studies. Current seismic landslide hazard mapping efforts typically utilize deterministic approaches to estimate rigid sliding block displacements and identify potential slope failures. A probabilistic framework that uses displacement hazard curves and logic-tree analysis is developed for regional seismic landslide mapping efforts. A computationally efficient approach is developed that allows the logic-tree approach to be applied for regional analysis. Anchorage, Alaska is used as a study area to apply the developed approach. With aleatory variability and epistemic uncertainties considered, the probabilistic map shows that the area of high/very high hazard of seismic landslides increases by a factor of 3 compared with a deterministic map. / text

In biomedical research and lifetime data analysis, the comparison of two hazard functions usually plays an important role in practice. In this thesis, we consider the standard independent two-sample framework under right censoring. We construct efficient and useful confidence intervals for the ratio and difference of two hazard functions using smoothed empirical likelihood methods. The empirical log-likelihood ratio is derived and its asymptotic distribution is a chi-squared distribution. Furthermore, the proposed method can be applied to medical diagnosis research. Simulation studies show that the proposed EL confidence intervals have better performance in terms of coverage accuracy and average length than the traditional normal approximation method. Finally, our methods are illustrated with real clinical trial data. It is concluded that the empirical likelihood methods provide better inferential outcomes.

The first two chapters of this dissertation concern the effect of public catastrophic insurance programs. In the first chapter, I show how these programs, which only protect against large health shocks, induce advantageous selection in private insurance. I use data on older Americans with Medicare insurance from the Health and Retirement Study to test if individuals with supplemental private health insurance are systematically lower-risk in states with public catastrophic insurance programs. I find that these programs decrease the average health risk for the privately insured by $700 and that a one standard deviation increase in an individual’s health risk decreases her probability of having private insurance by 4 percentage points. In the second chapter, I show that these programs reduce the incentive to invest in risk-reducing activities. I find large decreases in self-protection after a program is introduced and that individuals for whom the program is less generous are more likely to engage in self-protection. These effects are stronger for women than for men and apply to a variety of investments in health, including decisions about smoking, obesity, and cancer screening. The third chapter considers a different form of government intervention in insurance markets. In this chapter, I study laws mandating that employer-sponsored health insurance provide coverage for mental illness. I show that industries for which mental health coverage became more generous had larger increases in the average mental distress of their insured workforce. Part of the increase in generosity was due to regulations mandating coverage of mental health benefits. I then show that these regulations affected the behavior of individuals in the labor market—individuals who value more generous mental health benefits and switch jobs work longer hours after these regulations take effect, but individuals who do not value mental health benefits decrease their labor supply. These results are consistent with firms cutting back on their demand for labor due to the cost of the mandate, which leads to lower wages and a decrease in labor supply by individuals who do not value mental health benefits, but an increase in labor supply by individuals who do value mental health benefits highly.

The goal of every program or project manager is to have a safe reliable product and to have an understanding of the residual risk of operating that product. Two very important systems engineering analysis tools to achieve those objectives are Hazard Analysis and Failure Modes and Effects Analysis. Sometimes seen strictly as Safety and Reliability tasks, these analyses are key to a successful program or project and require input from all stakeholders. When viewed in the Systems Engineering process, Safety and Reliability are truly specialty disciplines within Systems Engineering. Hazard Analysis is used to improve system safety while Failure Modes and Effects Analysis is used to identify ways to increase product reliability; both analyses are required to improve systems design and fully capture the risk for a system or program. Depending on how the analyses are scoped, there could be a perception of overlap and duplication of effort. This paper will present a systems engineering approach to show the need and benefits for performing both types of analyses. Both analysis processes are required to ensure that all possible hazardous conditions and failure modes have been identified and addressed to minimize overall risk to the program/project and to ensure a safe and reliable system. / text

The three chapters in this dissertation look at different aspects of the labor market and its players. The first chapter estimates the impact of using the internet for job search on job match quality. Using both the semi-parametric Meyer (1990) model and the non-parametric Hausman Woutersen (2014) hazard model, the paper finds that exit rate from employment is at least 28% lower when internet is used as a job search tool. The second chapter looks at the effect of past unemployment on future wages. It is believed that employers may use past unemployment as a signal of low productivity. In this situation workers with a history of unemployment may receive lower wages. The paper uses the Machado Mata (2005) quantile decomposition technique to decompose the wage difference into differences due to characteristics and differences due to rewards. Results indicate that workers with an unemployment spell of more than three months receive at least 12% lower wages and that more than 40% of this wage difference can be attributed to the lower rewards received by the previously unemployed.. The last chapter focuses on human capital formation and looks at some of the reasons behind the low levels of schooling India. Using the Indian Household Development Survey (2005), the paper finds that income continues to be an important factor behind the low level of primary school enrollment. On average, poor students have at least 3% lower enrollment rates, when compared to similar skilled non-poor students.