This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

Displaying 1 - 10 of 160
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Description
The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters

The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters from human auditory models, such as auditory patterns and loudness, involves computationally intensive operations which can strain device resources. Hence, strategies for implementing computationally efficient human auditory models for loudness estimation have been studied in this thesis. Existing algorithms for reducing computations in auditory pattern and loudness estimation have been examined and improved algorithms have been proposed to overcome limitations of these methods. In addition, real-time applications such as perceptual loudness estimation and loudness equalization using auditory models have also been implemented. A software implementation of loudness estimation on iOS devices is also reported in this thesis. In addition to the loudness estimation algorithms and software, in this thesis project we also created new illustrations of speech and audio processing concepts for research and education. As a result, a new suite of speech/audio DSP functions was developed and integrated as part of the award-winning educational iOS App 'iJDSP." These functions are described in detail in this thesis. Several enhancements in the architecture of the application have also been introduced for providing the supporting framework for speech/audio processing. Frame-by-frame processing and visualization functionalities have been developed to facilitate speech/audio processing. In addition, facilities for easy sound recording, processing and audio rendering have also been developed to provide students, practitioners and researchers with an enriched DSP simulation tool. Simulations and assessments have been also developed for use in classes and training of practitioners and students.
ContributorsKalyanasundaram, Girish (Author) / Spanias, Andreas S (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2013
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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
The consumption of feedstocks from agriculture and forestry by current biofuel production has raised concerns about food security and land availability. In the meantime, intensive human activities have created a large amount of marginal lands that require management. This study investigated the viability of aligning land management with biofuel production

The consumption of feedstocks from agriculture and forestry by current biofuel production has raised concerns about food security and land availability. In the meantime, intensive human activities have created a large amount of marginal lands that require management. This study investigated the viability of aligning land management with biofuel production on marginal lands. Biofuel crop production on two types of marginal lands, namely urban vacant lots and abandoned mine lands (AMLs), were assessed. The investigation of biofuel production on urban marginal land was carried out in Pittsburgh between 2008 and 2011, using the sunflower gardens developed by a Pittsburgh non-profit as an example. Results showed that the crops from urban marginal lands were safe for biofuel. The crop yield was 20% of that on agricultural land while the low input agriculture was used in crop cultivation. The energy balance analysis demonstrated that the sunflower gardens could produce a net energy return even at the current low yield. Biofuel production on AML was assessed from experiments conducted in a greenhouse for sunflower, soybean, corn, canola and camelina. The research successfully created an industrial symbiosis by using bauxite as soil amendment to enable plant growth on very acidic mine refuse. Phytoremediation and soil amendments were found to be able to effectively reduce contamination in the AML and its runoff. Results from this research supported that biofuel production on marginal lands could be a unique and feasible option for cultivating biofuel feedstocks.
ContributorsZhao, Xi (Author) / Landis, Amy (Thesis advisor) / Fox, Peter (Committee member) / Chester, Mikhail (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
A semiconductor supply chain modeling and simulation platform using Linear Program (LP) optimization and parallel Discrete Event System Specification (DEVS) process models has been developed in a joint effort by ASU and Intel Corporation. A Knowledge Interchange Broker (KIBDEVS/LP) was developed to broker information synchronously between the DEVS and LP

A semiconductor supply chain modeling and simulation platform using Linear Program (LP) optimization and parallel Discrete Event System Specification (DEVS) process models has been developed in a joint effort by ASU and Intel Corporation. A Knowledge Interchange Broker (KIBDEVS/LP) was developed to broker information synchronously between the DEVS and LP models. Recently a single-echelon heuristic Inventory Strategy Module (ISM) was added to correct for forecast bias in customer demand data using different smoothing techniques. The optimization model could then use information provided by the forecast model to make better decisions for the process model. The composition of ISM with LP and DEVS models resulted in the first realization of what is now called the Optimization Simulation Forecast (OSF) platform. It could handle a single echelon supply chain system consisting of single hubs and single products In this thesis, this single-echelon simulation platform is extended to handle multiple echelons with multiple inventory elements handling multiple products. The main aspect for the multi-echelon OSF platform was to extend the KIBDEVS/LP such that ISM interactions with the LP and DEVS models could also be supported. To achieve this, a new, scalable XML schema for the KIB has been developed. The XML schema has also resulted in strengthening the KIB execution engine design. A sequential scheme controls the executions of the DEVS-Suite simulator, CPLEX optimizer, and ISM engine. To use the ISM for multiple echelons, it is extended to compute forecast customer demands and safety stocks over multiple hubs and products. Basic examples for semiconductor manufacturing spanning single and two echelon supply chain systems have been developed and analyzed. Experiments using perfect data were conducted to show the correctness of the OSF platform design and implementation. Simple, but realistic experiments have also been conducted. They highlight the kinds of supply chain dynamics that can be evaluated using discrete event process simulation, linear programming optimization, and heuristics forecasting models.
ContributorsSmith, James Melkon (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Davulcu, Hasan (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Debugging is a boring, tedious, time consuming but inevitable step of software development and debugging multiple threaded applications with user interactions is even more complicated. Since concurrency and synchronism are normal features in Android mobile applications, the order of thread execution may vary in every run even with the same

Debugging is a boring, tedious, time consuming but inevitable step of software development and debugging multiple threaded applications with user interactions is even more complicated. Since concurrency and synchronism are normal features in Android mobile applications, the order of thread execution may vary in every run even with the same input. To make things worse, the target erroneous cases may happen just in a few specific runs. Besides, the randomness of user interactions makes the whole debugging procedure more unpredictable. Thus, debugging a multiple threaded application is a tough and challenging task. This thesis introduces a replay mechanism for debugging user interactive multiple threaded Android applications. The approach is based on the 'Lamport Clock' concept, 'Event Driven' implementation and 'Client-Server' architecture. The debugger tool described in this thesis provides a user controlled debugging environment where users or developers are allowed to use modified record application to generate a log file. During the record time, all the necessary events like thread creation, synchronization and user input are recorded. Therefore, based on the information contained in the generated log files, the debugger tool can replay the application off-line since log files provide the deterministic order of execution. In this case, user or developers can replay an application as many times as they need to pinpoint the errors in the applications.
ContributorsLu, He (Author) / Lee, Yann-Hang (Thesis advisor) / Fainekos, Georgios (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2012
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Description
With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human

With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human to provide it some supervisory parameters that modify the degree of autonomy or allocate extra tasks to the robot. In this regard, this thesis presents an approach to include a provision to accept and incorporate such human inputs and modify the navigation functions of the robot accordingly. Concepts such as applying kinematical constraints while planning paths, traversing of unknown areas with an intent of maximizing field of view, performing complex tasks on command etc. have been examined and implemented. The approaches have been tested in Robot Operating System (ROS), using robots such as the iRobot Create, Personal Robotics (PR2) etc. Simulations and experimental demonstrations have proved that this approach is feasible for solving some of the existing problems and that it certainly can pave way to further research for enhancing functionality.
ContributorsVemprala, Sai Hemachandra (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits

The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits that are easily identified or tracked. Indeed it has been shown that patients with enduring symptoms have difficulty describing their problems; therefore, there is an urgent need for a sensitive measure of brain activity that corresponds with higher order cognitive processing. The development of a neurophysiological metric that maps to clinical resolution would inform decisions about diagnosis and prognosis, including the need for clinical intervention to address cognitive deficits. The literature suggests the need for assessment of concussion under cognitively demanding tasks. Here, a joint behavioral- high-density electroencephalography (EEG) paradigm was employed. This allows for the examination of cortical activity patterns during speech comprehension at various levels of degradation in a sentence verification task, imposing the need for higher-order cognitive processes. Eight participants with concussion listened to true-false sentences produced with either moderately to highly intelligible noise-vocoders. Behavioral data were simultaneously collected. The analysis of cortical activation patterns included 1) the examination of event-related potentials, including latency and source localization, and 2) measures of frequency spectra and associated power. Individual performance patterns were assessed during acute injury and a return visit several months following injury. Results demonstrate a combination of task-related electrophysiology measures correspond to changes in task performance during the course of recovery. Further, a discriminant function analysis suggests EEG measures are more sensitive than behavioral measures in distinguishing between individuals with concussion and healthy controls at both injury and recovery, suggesting the robustness of neurophysiological measures during a cognitively demanding task to both injury and persisting pathophysiology.
ContributorsUtianski, Rene (Author) / Liss, Julie M (Thesis advisor) / Berisha, Visar (Committee member) / Caviness, John N (Committee member) / Dorman, Michael (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Contaminants of emerging concern (CECs) present in wastewater effluent can threat its safe discharge or reuse. Additional barriers of protection can be provided using advanced or natural treatment processes. This dissertation evaluated ozonation and constructed wetlands to remove CECs from wastewater effluent. Organic CECs can be removed by hydroxyl radical

Contaminants of emerging concern (CECs) present in wastewater effluent can threat its safe discharge or reuse. Additional barriers of protection can be provided using advanced or natural treatment processes. This dissertation evaluated ozonation and constructed wetlands to remove CECs from wastewater effluent. Organic CECs can be removed by hydroxyl radical formed during ozonation, however estimating the ozone demand of wastewater effluent is complicated due to the presence of reduced inorganic species. A method was developed to estimate ozone consumption only by dissolved organic compounds and predict trace organic oxidation across multiple wastewater sources. Organic and engineered nanomaterial (ENM) CEC removal in constructed wetlands was investigated using batch experiments and continuous-flow microcosms containing decaying wetland plants. CEC removal varied depending on their physico-chemical properties, hydraulic residence time (HRT) and relative quantities of plant materials in the microcosms. At comparable HRTs, ENM removal improved with higher quantity of plant materials due to enhanced sorption which was verified in batch-scale studies with plant materials. A fate-predictive model was developed to evaluate the role of design loading rates on organic CEC removal. Areal removal rates increased with hydraulic loading rates (HLRs) and carbon loading rates (CLRs) unless photolysis was the dominant removal mechanism (e.g. atrazine). To optimize CEC removal, wetlands with different CLRs can be used in combination without lowering the net HLR. Organic CEC removal in denitrifying conditions of constructed wetlands was investigated and selected CECs (e.g. estradiol) were found to biotransform while denitrification occurred. Although level of denitrification was affected by HRT, similar impact on estradiol was not observed due to a dominant effect from plant biomass quantity. Overall, both modeling and experimental findings suggest considering CLR as an equally important factor with HRT or HLR to design constructed wetlands for CEC removal. This dissertation provided directions to select design parameters for ozonation (ozone dose) and constructed wetlands (design loading rates) to meet organic CEC removal goals. Future research is needed to understand fate of ENMs during ozonation and quantify the contributions from different transformation mechanisms occurring in the wetlands to incorporate in a model and evaluate the effect of wetland design.
ContributorsSharif, Fariya (Author) / Westerhoff, Paul (Thesis advisor) / Halden, Rolf (Committee member) / Fox, Peter (Committee member) / Herckes, Pierre (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