Browsing by Author "James Wilson, Committee Member"

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    A Markov Chain Framework for Approximation of Cycle Time in Semiconductor Manufacturing Toolsets.
    (2010-11-11) Akhavan-Tabatabaei, Raha; Yahya Fathi, Committee Chair; James Wilson, Committee Member; Charles Culbreth Jr, Committee Member; Reha Uzsoy, Committee Member; SHANTIKUMAR, J. GEORGE (E), Committee Member; Janice Wells, Committee Member
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    Performance Model for a Public Logistics Network
    (2009-01-07) Xiang, Ling; Michael Kay, Committee Chair; Tao Pang, Committee Member; James Wilson, Committee Member; Russell King, Committee Member
    A public logistics network (PLN) has been proposed as an alternative to private networks for the ground transport of parcels. In this dissertation, a heuristic approach to approximate the package average waiting time in a PLN is presented; and then based on this waiting time approximation, a PLN design procedure is developed. A PLN can be viewed as a priority queuing network with bulk arrivals and bulk service. It is difficult to obtain a closed-form solution for package average waiting time in a PLN. The problem is reformulated so that trucks transport loads instead of individual packages, thereby relaxing the bulk arrivals and bulk service feature. The package average waiting time is approximated fairly accurately by Kingman’s equation when the server utilization is high. A simulation model is created to determine the parameters needed in Kingman’s equation (the coefficient of variation for package interarrival times and for truck interarrival times). A regression analysis of the results shows that the headway ratio is around 5.5. The package average waiting time is approximated by the product of the truck headway (truck average interarrival time) and the headway ratio. The PLN simulation with protocols and the package bidding process is discussed as an extension to the basic simulation model. Packages bid for their trips along the way. The highest bidder gets the highest priority for truck transport services. Results from a simulation model incorporating a series of protocols developed by Kay show that a PLN with these protocols performs better than a FIFO system. For the PLN design problem, the goal is to design a PLN that results in the minimal package average waiting time for the entire network. Potential locations (search space) for the distribution centers (DCs) are found using the U.S. network of interstate and highways. A genetic algorithm (GA) was applied to search for the optimal number of DCs, their locations, and direct arc connections between each pair of DCs.
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    Sign Maintenance Strategies for Agencies to Comply with the FHWA Minimum Retroreflectivity Standards.
    (2010-10-28) Harris, Elizabeth; William Rasdorf, Committee Chair; Joseph Hummer, Committee Chair; James Wilson, Committee Member; George List, Committee Member
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    Simulation of Colorectal Cancer: The natural history of disease
    (2004-06-09) Cubbage, Daniel Frederick; James Wilson, Committee Member; Henry Nuttle, Committee Member; Stephen Roberts, Committee Chair
    This thesis presents a comprehensive, fully verified, and validated model of the natural history of Colorectal Cancer (CRC). CRC is the fourth most common type of cancer and the second leading cause of cancer death among both men and women. Individuals who develop CRC often fail to detect symptoms until the cancer is in an advanced stage. There are a number of screening methods designed to detect CRC in its early stages or prevent CRC by identifying and removing adenomous polyps, a pre-malignant form. However, because of the long latency of CRC and the time needed for clinical trials, it is not practical to provide clinical trials of all the screening and treatment strategies for CRC. Models offer an alternative means to analyze of screening/surveillance recommendations. Before considering any CRC medical interventions with a model, a model of the natural history of CRC is of fundamental importance. A model of the natural history of CRC requires a compromise of knowledge of CRC and data describing it. These compromises are described by modeling assumptions regarding the actual process of CRC development. To summarize the outcomes, the two primary measurements are the costs associated with the treatments and the years of life, or life-years. These measurements can be modified in several ways, by discounting or adjusting life-years to reflect the quality of life based upon different states of health. Within the medical decision-making community, two primary types of models for CRC have been developed, Markov models and discrete-event simulations. While the Markov models are easy to build and provide a basic analysis of the impact of screening, a more flexible, but more complex, approach is the discrete-event simulation model. One discrete-event simulation is the Vanderbilt Model that is the predecessor to the Vanderbilt-NC State model presented in this thesis. The Vanderbilt-NC State model improves the original Vanderbilt model with enhanced features such as database storage of inputs and Excel outputs. It also models additional important factors such as race, family history, reference year, risk effects, and histology. The object-oriented design allows the discrete-event simulation to follow the adenomas and people through the system, rather than forcing these objects into a process flow. When an individual is created, his natural death and first adenoma development are scheduled. The adenoma object is then responsible for its own progression up to cancer and potential cancer death. It also schedules the next adenoma, which will then follow its own timeline through the simulation. Once the model was constructed, it had to be verified and validated against cancer information from clinical studies. A detailed calibration procedure was implemented to match the model output with the cancer incidence, adenoma prevalence, and people with adenomas. In the process of validation, the Vanderbilt-NC State model outcomes are compared to data from other sources that were not used in the fitting process. The model?s output was compared to the cumulative risk of getting cancer obtained from a national CRC database (SEER). The model was also compared to a previous simulation that sampled from an adjusted lifetime that had the risk of CRC eliminated. This comparison was performed to validate the life-year gain associated with the elimination of CRC. Finally, the Vanderbilt-NC State model was compared to the previous Vanderbilt model. In each of the comparisons, the Vanderbilt-NC State model was consistent with the patterns and magnitudes of outcomes found in the external data. Once the model matched the literature results, analysis could be performed to determine the impact of CRC. According to the model, CRC reduces average lifespan by 0.24 years. This average loss of life comes from approximately 2.5% of the population losing an average of over 10 years of life. The average cost associated with the diagnosis and treatment of the disease is $2,188 per person. The model is the first comprehensive model of CRC and can be extended to consider screening and other medical interventions without direct experimentation using patients.
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    Simulation Optimization of Prostate Cancer Screening Using a Parallel Genetic Algorithm.
    (2010-08-27) Underwood, Daniel; Brian Denton, Committee Chair; James Wilson, Committee Member; John Baugh, Committee Member
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    Statistical Analysis of Novel Dielectric Materials for Microelectronics
    (2005-02-21) Hunt-Lowery, Alisa; Yahya Fathi, Committee Co-Chair; Victor Zhirnov, Committee Member; Jon-Paul Maria, Committee Co-Chair; Thomas Johnson, Committee Member; James Wilson, Committee Member
    This research analyzes the re-oxidation annealing process of Barium titanate thin films on copper foils made by Chemical Solution Deposition. During this anneal, the temperature and oxygen pressure settings must be optimized to ensure the elimination of oxygen vacancies without oxidizing the copper foil substrate. This research utilizes Design of Experiments (DOE) to study the impact of re-oxidation furnace temperature and pressure on the dielectric loss tangent response. Two designs of experiments were run. The first experiment, a 32 DOE, examined a large range of temperature and pressure levels. Due to the high susceptibility of uncontrollable factors such as humidity and film position in the crystallization anneal furnace, an adequate model could not be developed. However, the temperature at 550°C and a pressure of 10-5 Torr yielded a lower mean and standard deviation of the loss tangent response. A second and smaller scale experiment, a 22 with a center point, was run around 550°C and 10-5 Torr to determine if more optimal temperature and pressure settings existed in the local area. Two second order response surface models were developed from two crystallization anneals that were statistically significant. The most significant finding was that the optimum level for temperature and pressure in the re-oxidation anneal furnace in this experiment is 550°C and 2x10-5 Torr. While the models concluded that the temperature, pressure, temperature quadratic, and interaction between pressure and temperature were important effects in the model, there were differences in the curvature of the models due to the temperature quadratic effect.