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- Creators: Haydn, Joseph, 1732-1809
Description
Ionizing radiation used in the patient diagnosis or therapy has negative effects on the patient body in short term and long term depending on the amount of exposure. More than 700,000 examinations are everyday performed on Interventional Radiology modalities [1], however; there is no patient-centric information available to the patient or the Quality Assurance for the amount of organ dose received. In this study, we are exploring the methodologies to systematically reduce the absorbed radiation dose in the Fluoroscopically Guided Interventional Radiology procedures. In the first part of this study, we developed a mathematical model which determines a set of geometry settings for the equipment and a level for the energy during a patient exam. The goal is to minimize the amount of absorbed dose in the critical organs while maintaining image quality required for the diagnosis. The model is a large-scale mixed integer program. We performed polyhedral analysis and derived several sets of strong inequalities to improve the computational speed and quality of the solution. Results present the amount of absorbed dose in the critical organ can be reduced up to 99% for a specific set of angles. In the second part, we apply an approximate gradient method to simultaneously optimize angle and table location while minimizing dose in the critical organs with respect to the image quality. In each iteration, we solve a sub-problem as a MIP to determine the radiation field size and corresponding X-ray tube energy. In the computational experiments, results show further reduction (up to 80%) of the absorbed dose in compare with previous method. Last, there are uncertainties in the medical procedures resulting imprecision of the absorbed dose. We propose a robust formulation to hedge from the worst case absorbed dose while ensuring feasibility. In this part, we investigate a robust approach for the organ motions within a radiology procedure. We minimize the absorbed dose for the critical organs across all input data scenarios which are corresponding to the positioning and size of the organs. The computational results indicate up to 26% increase in the absorbed dose calculated for the robust approach which ensures the feasibility across scenarios.
ContributorsKhodadadegan, Yasaman (Author) / Zhang, Muhong (Thesis advisor) / Pavlicek, William (Thesis advisor) / Fowler, John (Committee member) / Wu, Tong (Committee member) / Arizona State University (Publisher)
Created2013
Description
During the initial stages of experimentation, there are usually a large number of factors to be investigated. Fractional factorial (2^(k-p)) designs are particularly useful during this initial phase of experimental work. These experiments often referred to as screening experiments help reduce the large number of factors to a smaller set. The 16 run regular fractional factorial designs for six, seven and eight factors are in common usage. These designs allow clear estimation of all main effects when the three-factor and higher order interactions are negligible, but all two-factor interactions are aliased with each other making estimation of these effects problematic without additional runs. Alternatively, certain nonregular designs called no-confounding (NC) designs by Jones and Montgomery (Jones & Montgomery, Alternatives to resolution IV screening designs in 16 runs, 2010) partially confound the main effects with the two-factor interactions but do not completely confound any two-factor interactions with each other. The NC designs are useful for independently estimating main effects and two-factor interactions without additional runs. While several methods have been suggested for the analysis of data from nonregular designs, stepwise regression is familiar to practitioners, available in commercial software, and is widely used in practice. Given that an NC design has been run, the performance of stepwise regression for model selection is unknown. In this dissertation I present a comprehensive simulation study evaluating stepwise regression for analyzing both regular fractional factorial and NC designs. Next, the projection properties of the six, seven and eight factor NC designs are studied. Studying the projection properties of these designs allows the development of analysis methods to analyze these designs. Lastly the designs and projection properties of 9 to 14 factor NC designs onto three and four factors are presented. Certain recommendations are made on analysis methods for these designs as well.
ContributorsShinde, Shilpa (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Committee member) / Fowler, John (Committee member) / Jones, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
Description
The upstream transmission of bulk data files in Ethernet passive optical networks (EPONs) arises from a number of applications, such as data back-up and multimedia file upload. Existing upstream transmission approaches lead to severe delays for conventional packet traffic when best-effort file and packet traffic are mixed. I propose and evaluate an exclusive interval for bulk transfer (EIBT) transmission strategy that reserves an EIBT for file traffic in an EPON polling cycle. I optimize the duration of the EIBT to minimize a weighted sum of packet and file delays. Through mathematical delay analysis and verifying simulation, it is demonstrated that the EIBT approach preserves small delays for packet traffic while efficiently serving bulk data file transfers. Dynamic circuits are well suited for applications that require predictable service with a constant bit rate for a prescribed period of time, such as demanding e-science applications. Past research on upstream transmission in passive optical networks (PONs) has mainly considered packet-switched traffic and has focused on optimizing packet-level performance metrics, such as reducing mean delay. This study proposes and evaluates a dynamic circuit and packet PON (DyCaPPON) that provides dynamic circuits along with packet-switched service. DyCaPPON provides (i) flexible packet-switched service through dynamic bandwidth allocation in periodic polling cycles, and (ii) consistent circuit service by allocating each active circuit a fixed-duration upstream transmission window during each fixed-duration polling cycle. I analyze circuit-level performance metrics, including the blocking probability of dynamic circuit requests in DyCaPPON through a stochastic knapsack-based analysis. Through this analysis I also determine the bandwidth occupied by admitted circuits. The remaining bandwidth is available for packet traffic and I analyze the resulting mean delay of packet traffic. Through extensive numerical evaluations and verifying simulations, the circuit blocking and packet delay trade-offs in DyCaPPON is demonstrated. An extended version of the DyCaPPON designed for light traffic situation is introduced in this article as well.
ContributorsWei, Xing (Author) / Reisslein, Martin (Thesis advisor) / Fowler, John (Committee member) / Palais, Joseph (Committee member) / McGarry, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Economic and environmental concerns necessitate the preference for retrofits over new construction in manufacturing facilities for incorporating modern technology, expanding production, becoming more energy-efficient and improving operational efficiency. Despite the technical and functional challenges in retrofits, the expectation from the project team is to; reduce costs, ensure the time to market and maintain a high standard for quality and safety. Thus, the construction supply chain faces increasing pressure to improve performance by ensuring better labor productivity, among other factors, for efficiency gain. Building Information Modeling (BIM) & off-site prefabrication are determined as effective management & production methods to meet these goals. However, there are limited studies assessing their impact on labor productivity within the constraints of a retrofit environment. This study fills the gap by exploring the impact of BIM on labor productivity (metric) in retrofits (context).
BIM use for process tool installation at a semiconductor manufacturing facility serves as an ideal environment for practical observations. Direct site observations indicate a positive correlation between disruptions in the workflow attributed to an immature use of BIM, waste due to rework and high non-value added time at the labor work face. Root-cause analysis traces the origins of the said disruptions to decision-factors that are critical for the planning, management and implementation of BIM. Analysis shows that stakeholders involved in decision-making during BIM planning, management and implementation identify BIM-value based on their immediate utility for BIM-use instead of the utility for the customers of the process. This differing value-system manifests in the form of unreliable and inaccurate information at the labor work face.
Grounding the analysis in theory and observations, the author hypothesizes that stakeholders of a construction project value BIM and BIM-aspects (i.e. geometrical information, descriptive information and workflows) differently and the accuracy of geometrical information is critical for improving labor productivity when using prefabrication in retrofit construction. In conclusion, this research presents a BIM-value framework, associating stakeholders with their relative value for BIM, the decision-factors for the planning, management and implementation of BIM and the potential impact of those decisions on labor productivity.
BIM use for process tool installation at a semiconductor manufacturing facility serves as an ideal environment for practical observations. Direct site observations indicate a positive correlation between disruptions in the workflow attributed to an immature use of BIM, waste due to rework and high non-value added time at the labor work face. Root-cause analysis traces the origins of the said disruptions to decision-factors that are critical for the planning, management and implementation of BIM. Analysis shows that stakeholders involved in decision-making during BIM planning, management and implementation identify BIM-value based on their immediate utility for BIM-use instead of the utility for the customers of the process. This differing value-system manifests in the form of unreliable and inaccurate information at the labor work face.
Grounding the analysis in theory and observations, the author hypothesizes that stakeholders of a construction project value BIM and BIM-aspects (i.e. geometrical information, descriptive information and workflows) differently and the accuracy of geometrical information is critical for improving labor productivity when using prefabrication in retrofit construction. In conclusion, this research presents a BIM-value framework, associating stakeholders with their relative value for BIM, the decision-factors for the planning, management and implementation of BIM and the potential impact of those decisions on labor productivity.
ContributorsGhosh, Arundhati (Author) / Chasey, Allan D (Thesis advisor) / Laroche, Dominique-Claude (Committee member) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2015
Description
Fiber-Wireless (FiWi) network is the future network configuration that uses optical fiber as backbone transmission media and enables wireless network for the end user. Our study focuses on the Dynamic Bandwidth Allocation (DBA) algorithm for EPON upstream transmission. DBA, if designed properly, can dramatically improve the packet transmission delay and overall bandwidth utilization. With new DBA components coming out in research, a comprehensive study of DBA is conducted in this thesis, adding in Double Phase Polling coupled with novel Limited with Share credits Excess distribution method. By conducting a series simulation of DBAs using different components, we found out that grant sizing has the strongest impact on average packet delay and grant scheduling also has a significant impact on the average packet delay; grant scheduling has the strongest impact on the stability limit or maximum achievable channel utilization. Whereas the grant sizing only has a modest impact on the stability limit; the SPD grant scheduling policy in the Double Phase Polling scheduling framework coupled with Limited with Share credits Excess distribution grant sizing produced both the lowest average packet delay and the highest stability limit.
ContributorsZhao, Du (Author) / Reisslein, Martin (Thesis advisor) / McGarry, Michael (Committee member) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
For more than twenty years, clinical researchers have been publishing data regarding incidence and risk of adverse events (AEs) incurred during hospitalizations. Hospitals have standard operating policies and procedures (SOPP) to protect patients from AE. The AE specifics (rates, SOPP failures, timing and risk factors) during heart failure (HF) hospitalizations are unknown. There were 1,722 patients discharged with a primary diagnosis of HF from an academic hospital between January 2005 and December 2007. Three hundred eighty-one patients experienced 566 AEs, classified into four categories: medication (43.9%), infection (18.9%), patient care (26.3%), or procedural (10.9%). Three distinct analyses were performed: 1) patient's perspective of SOPP reliability including cumulative distribution and hazard functions of time to AEs; 2) Cox proportional hazards model to determine independent patient-specific risk factors for AEs; and 3) hospital administration's perspective of SOPP reliability through three years of the study including cumulative distribution and hazard functions of time between AEs and moving range statistical process control (SPC) charts for days between failures of each type. This is the first study, to our knowledge, to consider reliability of SOPP from both the patient's and hospital administration's perspective. AE rates in hospitalized patients are similar to other recently published reports and did not improve during the study period. Operations research methodologies will be necessary to improve reliability of care delivered to hospitalized patients.
ContributorsHuddleston, Jeanne (Author) / Fowler, John (Thesis advisor) / Montgomery, Douglas C. (Thesis advisor) / Gel, Esma (Committee member) / Shunk, Dan (Committee member) / Arizona State University (Publisher)
Created2012
Description
In the entire supply chain, demand planning is one of the crucial aspects of the production planning process. If the demand is not estimated accurately, then it causes revenue loss. Past research has shown forecasting can be used to help the demand planning process for production. However, accurate forecasting from historical data is difficult in today's complex volatile market. Also it is not the only factor that influences the demand planning. Factors, namely, Consumer's shifting interest and buying power also influence the future demand. Hence, this research study focuses on Just-In-Time (JIT) philosophy using a pull control strategy implemented with a Kanban control system to control the inventory flow. Two different product structures, serial product structure and assembly product structure, are considered for this research. Three different methods: the Toyota Production System model, a histogram model and a cost minimization model, have been used to find the number of kanbans that was used in a computer simulated Just-In-Time Kanban System. The simulation model was built to execute the designed scenarios for both the serial and assembly product structure. A test was performed to check the significance effects of various factors on system performance. Results of all three methods were collected and compared to indicate which method provides the most effective way to determine number of kanbans at various conditions. It was inferred that histogram model and cost minimization models are more accurate in calculating the required kanbans for various manufacturing conditions. Method-1 fails to adjust the kanbans when the backordered cost increases or when product structure changes. Among the product structures, serial product structures proved to be effective when Method-2 or Method-3 is used to calculate the kanban numbers for the system. The experimental result data also indicated that the lower container capacity collects more backorders in the system, which increases the inventory cost, than the high container capacity for both serial and assembly product structures.
ContributorsSahu, Pranati (Author) / Askin, Ronald G. (Thesis advisor) / Shunk, Dan L. (Thesis advisor) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2012
Description
Buildings (approximately half commercial and half residential) consume over 70% of the electricity among all the consumption units in the United States. Buildings are also responsible for approximately 40% of CO2 emissions, which is more than any other industry sectors. As a result, the initiative smart building which aims to not only manage electrical consumption in an efficient way but also reduce the damaging effect of greenhouse gases on the environment has been launched. Another important technology being promoted by government agencies is the smart grid which manages energy usage across a wide range of buildings in an effort to reduce cost and increase reliability and transparency. As a great amount of efforts have been devoted to these two initiatives by either exploring the smart grid designs or developing technologies for smart buildings, the research studying how the smart buildings and smart grid coordinate thus more efficiently use the energy is currently lacking. In this dissertation, a "system-of-system" approach is employed to develop an integrated building model which consists a number of buildings (building cluster) interacting with smart grid. The buildings can function as both energy consumption unit as well as energy generation/storage unit. Memetic Algorithm (MA) and Particle Swarm Optimization (PSO) based decision framework are developed for building operation decisions. In addition, Particle Filter (PF) is explored as a mean for fusing online sensor and meter data so adaptive decision could be made in responding to dynamic environment. The dissertation is divided into three inter-connected research components. First, an integrated building energy model including building consumption, storage, generation sub-systems for the building cluster is developed. Then a bi-level Memetic Algorithm (MA) based decentralized decision framework is developed to identify the Pareto optimal operation strategies for the building cluster. The Pareto solutions not only enable multiple dimensional tradeoff analysis, but also provide valuable insight for determining pricing mechanisms and power grid capacity. Secondly, a multi-objective PSO based decision framework is developed to reduce the computational effort of the MA based decision framework without scarifying accuracy. With the improved performance, the decision time scale could be refined to make it capable for hourly operation decisions. Finally, by integrating the multi-objective PSO based decision framework with PF, an adaptive framework is developed for adaptive operation decisions for smart building cluster. The adaptive framework not only enables me to develop a high fidelity decision model but also enables the building cluster to respond to the dynamics and uncertainties inherent in the system.
ContributorsHu, Mengqi (Author) / Wu, Teresa (Thesis advisor) / Weir, Jeffery (Thesis advisor) / Wen, Jin (Committee member) / Fowler, John (Committee member) / Shunk, Dan (Committee member) / Arizona State University (Publisher)
Created2012
ContributorsHaydn, Joseph, 1732-1809 (Composer)
ContributorsHaydn, Joseph, 1732-1809 (Composer)