This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 10 of 68
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Description
Many manmade chemicals used in consumer products are ultimately washed down the drain and are collected in municipal sewers. Efficient chemical monitoring at wastewater treatment (WWT) plants thus may provide up-to-date information on chemical usage rates for epidemiological assessments. The objective of the present study was to extrapolate this concept,

Many manmade chemicals used in consumer products are ultimately washed down the drain and are collected in municipal sewers. Efficient chemical monitoring at wastewater treatment (WWT) plants thus may provide up-to-date information on chemical usage rates for epidemiological assessments. The objective of the present study was to extrapolate this concept, termed 'sewage epidemiology', to include municipal sewage sludge (MSS) in identifying and prioritizing contaminants of emerging concern (CECs). To test this the following specific aims were defined: i) to screen and identify CECs in nationally representative samples of MSS and to provide nationwide inventories of CECs in U.S. MSS; ii) to investigate the fate and persistence in MSS-amended soils, of sludge-borne hydrophobic CECs; and iii) to develop an analytical tool relying on contaminant levels in MSS as an indicator for identifying and prioritizing hydrophobic CECs. Chemicals that are primarily discharged to the sewage systems (alkylphenol surfactants) and widespread persistent organohalogen pollutants (perfluorochemicals and brominated flame retardants) were analyzed in nationally representative MSS samples. A meta-analysis showed that CECs contribute about 0.04-0.15% to the total dry mass of MSS, a mass equivalent of 2,700-7,900 metric tonnes of chemicals annually. An analysis of archived mesocoms from a sludge weathering study showed that 64 CECs persisted in MSS/soil mixtures over the course of the experiment, with half-lives ranging between 224 and >990 days; these results suggest an inherent persistence of CECs that accumulate in MSS. A comparison of the spectrum of chemicals (n=52) analyzed in nationally representative biological specimens from humans and MSS revealed 70% overlap. This observed co-occurrence of contaminants in both matrices suggests that MSS may serve as an indicator for ongoing human exposures and body burdens of pollutants in humans. In conclusion, I posit that this novel approach in sewage epidemiology may serve to pre-screen and prioritize the several thousands of known or suspected CECs to identify those that are most prone to pose a risk to human health and the environment.
ContributorsVenkatesan, Arjunkrishna (Author) / Halden, Rolf U. (Thesis advisor) / Westerhoff, Paul (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Biological systems are complex in many dimensions as endless transportation and communication networks all function simultaneously. Our ability to intervene within both healthy and diseased systems is tied directly to our ability to understand and model core functionality. The progress in increasingly accurate and thorough high-throughput measurement technologies has provided

Biological systems are complex in many dimensions as endless transportation and communication networks all function simultaneously. Our ability to intervene within both healthy and diseased systems is tied directly to our ability to understand and model core functionality. The progress in increasingly accurate and thorough high-throughput measurement technologies has provided a deluge of data from which we may attempt to infer a representation of the true genetic regulatory system. A gene regulatory network model, if accurate enough, may allow us to perform hypothesis testing in the form of computational experiments. Of great importance to modeling accuracy is the acknowledgment of biological contexts within the models -- i.e. recognizing the heterogeneous nature of the true biological system and the data it generates. This marriage of engineering, mathematics and computer science with systems biology creates a cycle of progress between computer simulation and lab experimentation, rapidly translating interventions and treatments for patients from the bench to the bedside. This dissertation will first discuss the landscape for modeling the biological system, explore the identification of targets for intervention in Boolean network models of biological interactions, and explore context specificity both in new graphical depictions of models embodying context-specific genomic regulation and in novel analysis approaches designed to reveal embedded contextual information. Overall, the dissertation will explore a spectrum of biological modeling with a goal towards therapeutic intervention, with both formal and informal notions of biological context, in such a way that will enable future work to have an even greater impact in terms of direct patient benefit on an individualized level.
ContributorsVerdicchio, Michael (Author) / Kim, Seungchan (Thesis advisor) / Baral, Chitta (Committee member) / Stolovitzky, Gustavo (Committee member) / Collofello, James (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to

Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling

Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
ContributorsMeng, Yunsong (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Fainekos, Georgios (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Urban water systems face sustainability challenges ranging from water quality, leaks, over-use, energy consumption, and long-term supply concerns. Resiliency challenges include the capacity to respond to drought, managing pipe deterioration, responding to natural disasters, and preventing terrorism. One strategy to enhance sustainability and resiliency is the development and adoption of

Urban water systems face sustainability challenges ranging from water quality, leaks, over-use, energy consumption, and long-term supply concerns. Resiliency challenges include the capacity to respond to drought, managing pipe deterioration, responding to natural disasters, and preventing terrorism. One strategy to enhance sustainability and resiliency is the development and adoption of smart water grids. A smart water grid incorporates networked monitoring and control devices into its structure, which provides diverse, real-time information about the system, as well as enhanced control. Data provide input for modeling and analysis, which informs control decisions, allowing for improvement in sustainability and resiliency. While smart water grids hold much potential, there are also potential tradeoffs and adoption challenges. More publicly available cost-benefit analyses are needed, as well as system-level research and application, rather than the current focus on individual technologies. This thesis seeks to fill one of these gaps by analyzing the cost and environmental benefits of smart irrigation controllers. Smart irrigation controllers can save water by adapting watering schedules to climate and soil conditions. The potential benefit of smart irrigation controllers is particularly high in southwestern U.S. states, where the arid climate makes water scarcer and increases watering needs of landscapes. To inform the technology development process, a design for environment (DfE) method was developed, which overlays economic and environmental performance parameters under different operating conditions. This method is applied to characterize design goals for controller price and water savings that smart irrigation controllers must meet to yield life cycle carbon dioxide reductions and economic savings in southwestern U.S. states, accounting for regional variability in electricity and water prices and carbon overhead. Results from applying the model to smart irrigation controllers in the Southwest suggest that some areas are significantly easier to design for.
ContributorsMutchek, Michele (Author) / Allenby, Braden (Thesis advisor) / Williams, Eric (Committee member) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2012
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Description
In this dissertation I develop a deep theory of temporal planning well-suited to analyzing, understanding, and improving the state of the art implementations (as of 2012). At face-value the work is strictly theoretical; nonetheless its impact is entirely real and practical. The easiest portion of that impact to highlight concerns

In this dissertation I develop a deep theory of temporal planning well-suited to analyzing, understanding, and improving the state of the art implementations (as of 2012). At face-value the work is strictly theoretical; nonetheless its impact is entirely real and practical. The easiest portion of that impact to highlight concerns the notable improvements to the format of the temporal fragment of the International Planning Competitions (IPCs). Particularly: the theory I expound upon here is the primary cause of--and justification for--the altered (i) selection of benchmark problems, and (ii) notion of "winning temporal planner". For higher level motivation: robotics, web service composition, industrial manufacturing, business process management, cybersecurity, space exploration, deep ocean exploration, and logistics all benefit from applying domain-independent automated planning technique. Naturally, actually carrying out such case studies has much to offer. For example, we may extract the lesson that reasoning carefully about deadlines is rather crucial to planning in practice. More generally, effectively automating specifically temporal planning is well-motivated from applications. Entirely abstractly, the aim is to improve the theory of automated temporal planning by distilling from its practice. My thesis is that the key feature of computational interest is concurrency. To support, I demonstrate by way of compilation methods, worst-case counting arguments, and analysis of algorithmic properties such as completeness that the more immediately pressing computational obstacles (facing would-be temporal generalizations of classical planning systems) can be dealt with in theoretically efficient manner. So more accurately the technical contribution here is to demonstrate: The computationally significant obstacle to automated temporal planning that remains is just concurrency.
ContributorsCushing, William Albemarle (Author) / Kambhampati, Subbarao (Thesis advisor) / Weld, Daniel S. (Committee member) / Smith, David E. (Committee member) / Baral, Chitta (Committee member) / Davalcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Hydrocarbon spill site cleanup is challenging when contaminants are present in lower permeability layers. These are difficult to remediate and may result in long-term groundwater impacts. The research goal is to investigate strategies for long-term reduction of contaminant emissions from sources in low permeability layers through partial source treatment at

Hydrocarbon spill site cleanup is challenging when contaminants are present in lower permeability layers. These are difficult to remediate and may result in long-term groundwater impacts. The research goal is to investigate strategies for long-term reduction of contaminant emissions from sources in low permeability layers through partial source treatment at higher/lower permeability interfaces. Conceptually, this provides a clean/reduced concentration zone near the interface, and consequently a reduced concentration gradient and flux from the lower permeability layer. Treatment by in-situ chemical oxidation (ISCO) was evaluated using hydrogen peroxide (H2O2) and sodium persulfate (Na2S2O8). H2O2 studies included lab and field-scale distribution studies and lab emission reduction experiments. The reaction rate of H2O2 in soils was so fast it did not travel far (<1 m) from delivery points under typical flow conditions. Oxygen gas generated and partially trapped in soil pores served as a dissolved oxygen (DO) source for >60 days in field and lab studies. During that period, the laboratory studies had reduced hydrocarbon impacts, presumably from aerobic biodegradation, which rebounded once the O2 source depleted. Therefore field monitoring should extend beyond the post-treatment elevated DO. Na2S2O8 use was studied in two-dimensional tanks (122-cm tall, 122-cm wide, and 5-cm thick) containing two contrasting permeability layers (three orders of magnitude difference). The lower permeability layer initially contained a dissolved-sorbed contaminant source throughout this layer, or a 10-cm thick non-aqueous phase liquid (NAPL)-impacted zone below the higher/lower permeability interface. The dissolved-sorbed source tank was actively treated for 14 d. Two hundred days after treatment, the emission reduction of benzene, toluene, ethylbenzene, and p-xylene (BTEX) were 95-99% and methyl tert-butyl ether (MTBE) was 63%. The LNAPL-source tank had three Na2S2O8 and two sodium hydroxide (NaOH) applications for S2O82- base activation. The resulting emission reductions for BTEX, n-propylbenzene, and 1,3,5 trymethylbenzene were 55-73%. While less effective at reducing emissions from LNAPL sources, the 14-d treatment delivered sufficient S2O82- though diffusion to remediate BTEX from the 60 cm dissolved-sorbed source. The overall S2O82- utilization in the dissolved source experiment was calculated by mass balance to be 108-125 g S2O82-/g hydrocarbon treated.
ContributorsCavanagh, Bridget (Author) / Johnson, Paul C (Thesis advisor) / Westerhoff, Paul (Committee member) / Kavazanjian, Edward (Committee member) / Bruce, Cristin (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This thesis research focuses on developing a single-cell gene expression analysis method for marine diatom Thalassiosira pseudonana and constructing a chip level tool to realize the single cell RT-qPCR analysis. This chip will serve as a conceptual foundation for future deployable ocean monitoring systems. T. pseudonana, which is a common

This thesis research focuses on developing a single-cell gene expression analysis method for marine diatom Thalassiosira pseudonana and constructing a chip level tool to realize the single cell RT-qPCR analysis. This chip will serve as a conceptual foundation for future deployable ocean monitoring systems. T. pseudonana, which is a common surface water microorganism, was detected in the deep ocean as confirmed by phylogenetic and microbial community functional studies. Six-fold copy number differences between 23S rRNA and 23S rDNA were observed by RT-qPCR, demonstrating the moderate functional activity of detected photosynthetic microbes in the deep ocean including T. pseudonana. Because of the ubiquity of T. pseudonana, it is a good candidate for an early warning system for ocean environmental perturbation monitoring. This early warning system will depend on identifying outlier gene expression at the single-cell level. An early warning system based on single-cell analysis is expected to detect environmental perturbations earlier than population level analysis which can only be observed after a whole community has reacted. Preliminary work using tube-based, two-step RT-qPCR revealed for the first time, gene expression heterogeneity of T. pseudonana under different nutrient conditions. Heterogeneity was revealed by different gene expression activity for individual cells under the same conditions. This single cell analysis showed a skewed, lognormal distribution and helped to find outlier cells. The results indicate that the geometric average becomes more important and representative of the whole population than the arithmetic average. This is in contrast with population level analysis which is limited to arithmetic averages only and highlights the value of single cell analysis. In order to develop a deployable sensor in the ocean, a chip level device was constructed. The chip contains surface-adhering droplets, defined by hydrophilic patterning, that serve as real-time PCR reaction chambers when they are immersed in oil. The chip had demonstrated sensitivities at the single cell level for both DNA and RNA. The successful rate of these chip-based reactions was around 85%. The sensitivity of the chip was equivalent to published microfluidic devices with complicated designs and protocols, but the production process of the chip was simple and the materials were all easily accessible in conventional environmental and/or biology laboratories. On-chip tests provided heterogeneity information about the whole population and were validated by comparing with conventional tube based methods and by p-values analysis. The power of chip-based single-cell analyses were mainly between 65-90% which were acceptable and can be further increased by higher throughput devices. With this chip and single-cell analysis approaches, a new paradigm for robust early warning systems of ocean environmental perturbation is possible.
ContributorsShi, Xu (Author) / Meldrum, Deirdre R. (Thesis advisor) / Zhang, Weiwen (Committee member) / Chao, Shih-hui (Committee member) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The influence of climate variability and reclaimed wastewater on the water supply necessitates improved understanding of the treatability of trace and bulk organic matter. Dissolved organic matter (DOM) mobilized during extreme weather events and in treated wastewater includes natural organic matter (NOM), contaminants of emerging concern (CECs), and microbial extracellular

The influence of climate variability and reclaimed wastewater on the water supply necessitates improved understanding of the treatability of trace and bulk organic matter. Dissolved organic matter (DOM) mobilized during extreme weather events and in treated wastewater includes natural organic matter (NOM), contaminants of emerging concern (CECs), and microbial extracellular polymeric substances (EPS). The goal of my dissertation was to quantify the impacts of extreme weather events on DOM in surface water and downstream treatment processes, and to improve membrane filtration efficiency and CECs oxidation efficiency during water reclamation with ozone. Surface water quality, air quality and hydrologic flow rate data were used to quantify changes in DOM and turbidity following dust storms, flooding, or runoff from wildfire burn areas in central Arizona. The subsequent impacts to treatment processes and public perception of water quality were also discussed. Findings showed a correlation between dust storm events and change in surface water turbidity (R2=0.6), attenuation of increased DOM through reservoir systems, a 30-40% increase in organic carbon and a 120-600% increase in turbidity following severe flooding, and differing impacts of upland and lowland wildfires. The use of ozone to reduce membrane fouling caused by vesicles (a subcomponent of EPS) and oxidize CECs through increased hydroxyl radical (HO●) production was investigated. An "ozone dose threshold" was observed above which addition of hydrogen peroxide increased HO● production; indicating the presence of ambient promoters in wastewater. Ozonation of CECs in secondary effluent over titanium dioxide or activated carbon did not increase radial production. Vesicles fouled ultrafiltration membranes faster (20 times greater flux decline) than polysaccharides, fatty acids, or NOM. Based upon the estimated carbon distribution of secondary effluent, vesicles could be responsible for 20-60% of fouling during ultrafiltration and may play a vital role in other environmental processes as well. Ozone reduced vesicle-caused membrane fouling that, in conjunction with the presence of ambient promoters, helps to explain why low ozone dosages improve membrane flux during full-scale water reclamation.
ContributorsBarry, Michelle (Author) / Barry, Michelle C (Thesis advisor) / Westerhoff, Paul (Committee member) / Fox, Peter (Committee member) / Halden, Rolf (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Modeling dynamic systems is an interesting problem in Knowledge Representation (KR) due to their usefulness in reasoning about real-world environments. In order to effectively do this, a number of different formalisms have been considered ranging from low-level languages, such as Answer Set Programming (ASP), to high-level action languages, such as

Modeling dynamic systems is an interesting problem in Knowledge Representation (KR) due to their usefulness in reasoning about real-world environments. In order to effectively do this, a number of different formalisms have been considered ranging from low-level languages, such as Answer Set Programming (ASP), to high-level action languages, such as C+ and BC. These languages show a lot of promise over many traditional approaches as they allow a developer to automate many tasks which require reasoning within dynamic environments in a succinct and elaboration tolerant manner. However, despite their strengths, they are still insufficient for modeling many systems, especially those of non-trivial scale or that require the ability to cope with exceptions which occur during execution, such as unexpected events or unintended consequences to actions which have been performed. In order to address these challenges, a theoretical framework is created which focuses on improving the feasibility of applying KR techniques to such problems. The framework is centered on the action language BC+, which integrates many of the strengths of existing KR formalisms, and provides the ability to perform efficient reasoning in an incremental fashion while handling exceptions which occur during execution. The result is a developer friendly formalism suitable for performing reasoning in an online environment. Finally, the newly enhanced Cplus2ASP 2 is introduced, which provides a number of improvements over the original version. These improvements include implementing BC+ among several additional languages, providing enhanced developer support, and exhibiting a significant performance increase over its predecessors and similar systems.
ContributorsBabb, Joseph (Author) / Lee, Joohyung (Thesis advisor) / Lee, Yann-Hang (Committee member) / Baral, Chitta (Committee member) / Arizona State University (Publisher)
Created2014