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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
The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.
ContributorsHaghnevis, Moeed (Author) / Askin, Ronald G. (Thesis advisor) / Armbruster, Dieter (Thesis advisor) / Mirchandani, Pitu (Committee member) / Wu, Tong (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
In recent years, service oriented computing (SOC) has become a widely accepted paradigm for the development of distributed applications such as web services, grid computing and cloud computing systems. In service-based systems (SBS), multiple service requests with specific performance requirements make services compete for system resources. IT service providers need to allocate resources to services so the performance requirements of customers can be satisfied. Workload and performance models are required for efficient resource management and service performance assurance in SBS. This dissertation develops two methods to understand and model the cause-effect relations of service-related activities with resources workload and service performance. Part one presents an empirical method that requires the collection of system dynamics data and the application of statistical analyses. The results show that the method is capable to: 1) uncover the impacts of services on resource workload and service performance, 2) identify interaction effects of multiple services running concurrently, 3) gain insights about resource and performance tradeoffs of services, and 4) build service workload and performance models. In part two, the empirical method is used to investigate the impacts of services, security mechanisms and cyber attacks on resources workload and service performance. The information obtained is used to: 1) uncover interaction effects of services, security mechanisms and cyber attacks, 2) identify tradeoffs within limits of system resources, and 3) develop general/specific strategies for system survivability. Finally, part three presents a framework based on the usage profiles of services competing for resources and the resource-sharing schemes. The framework is used to: 1) uncover the impacts of service parameters (e.g. arrival distribution, execution time distribution, priority, workload intensity, scheduling algorithm) on workload and performance, and 2) build service workload and performance models at individual resources. The estimates obtained from service workload and performance models at individual resources can be aggregated to obtain overall estimates of services through multiple system resources. The workload and performance models of services obtained through both methods can be used for the efficient resource management and service performance assurance in SBS.
ContributorsMartinez Aranda, Billibaldo (Author) / Ye, Nong (Thesis advisor) / Wu, Tong (Committee member) / Sarjoughian, Hessam S. (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Avian influenzas are zoonoses, or pathogens borne by wildlife and livestock that
can also infect people. In recent decades, and especially since the emergence of highly pathogenic avian influenza (HPAI) H5N1 in 1996, these diseases have become a significant threat to animal and public health across the world. HPAI H5N1 has caused severe damage to poultry populations, killing, or prompting the culling of, millions of birds in Asia, Africa, and Europe. It has also infected hundreds of people, with a mortality rate of approximately 50%. This dissertation focuses on the ecological and socioeconomic drivers of avian influenza risk, particularly in China, the most populous country to be infected. Among the most significant ecological risk factors are landscapes that serve as “mixing zones” for wild waterfowl and poultry, such as rice paddy, and nearby lakes and wetlands that are important breeding and wintering habitats for wild birds. Poultry outbreaks often involve cross infections between wild and domesticated birds. At the international level, trade in live poultry can spread the disease, especially if the imports are from countries not party to trade agreements with well-developed biosecurity standards. However, these risks can be mitigated in a number of ways. Protected habitats, such as Ramsar wetlands, can segregate wild bird and poultry populations, thereby lowering the chance of interspecies transmission. The industrialization of poultry production, while not without ethical and public health problems, can also be risk-reducing by causing wild-domestic segregation and allowing for the more efficient application of surveillance, vaccination, and other biosecurity measures. Disease surveillance is effective at preventing the spread of avian influenza, including across international borders. Economic modernization in general, as reflected in rising per-capita GDP, appears to mitigate avian influenza risks at both the national and sub-national levels. Poultry vaccination has been effective in many cases, but is an incomplete solution because of the practical difficulties of sustained and widespread implementation. The other popular approach to avian influenza control is culling, which can be highly expensive and raise ethical concerns about large-scale animal slaughter. Therefore, it is more economically efficient, and may even be more ethical, to target the socio-ecological drivers of avian influenza risks, including by implementing the policies discussed here.
can also infect people. In recent decades, and especially since the emergence of highly pathogenic avian influenza (HPAI) H5N1 in 1996, these diseases have become a significant threat to animal and public health across the world. HPAI H5N1 has caused severe damage to poultry populations, killing, or prompting the culling of, millions of birds in Asia, Africa, and Europe. It has also infected hundreds of people, with a mortality rate of approximately 50%. This dissertation focuses on the ecological and socioeconomic drivers of avian influenza risk, particularly in China, the most populous country to be infected. Among the most significant ecological risk factors are landscapes that serve as “mixing zones” for wild waterfowl and poultry, such as rice paddy, and nearby lakes and wetlands that are important breeding and wintering habitats for wild birds. Poultry outbreaks often involve cross infections between wild and domesticated birds. At the international level, trade in live poultry can spread the disease, especially if the imports are from countries not party to trade agreements with well-developed biosecurity standards. However, these risks can be mitigated in a number of ways. Protected habitats, such as Ramsar wetlands, can segregate wild bird and poultry populations, thereby lowering the chance of interspecies transmission. The industrialization of poultry production, while not without ethical and public health problems, can also be risk-reducing by causing wild-domestic segregation and allowing for the more efficient application of surveillance, vaccination, and other biosecurity measures. Disease surveillance is effective at preventing the spread of avian influenza, including across international borders. Economic modernization in general, as reflected in rising per-capita GDP, appears to mitigate avian influenza risks at both the national and sub-national levels. Poultry vaccination has been effective in many cases, but is an incomplete solution because of the practical difficulties of sustained and widespread implementation. The other popular approach to avian influenza control is culling, which can be highly expensive and raise ethical concerns about large-scale animal slaughter. Therefore, it is more economically efficient, and may even be more ethical, to target the socio-ecological drivers of avian influenza risks, including by implementing the policies discussed here.
ContributorsWu, Tong (Author) / Perrings, Charles (Thesis advisor) / Collins, Jim (Committee member) / Daszak, Peter (Committee member) / Minteer, Ben (Committee member) / Kinzig, Ann (Committee member) / Arizona State University (Publisher)
Created2018