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 79
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Description
This dissertation explores the use of bench-scale batch microcosms in remedial design of contaminated aquifers, presents an alternative methodology for conducting such treatability studies, and - from technical, economical, and social perspectives - examines real-world application of this new technology. In situ bioremediation (ISB) is an effective remedial approach for

This dissertation explores the use of bench-scale batch microcosms in remedial design of contaminated aquifers, presents an alternative methodology for conducting such treatability studies, and - from technical, economical, and social perspectives - examines real-world application of this new technology. In situ bioremediation (ISB) is an effective remedial approach for many contaminated groundwater sites. However, site-specific variability necessitates the performance of small-scale treatability studies prior to full-scale implementation. The most common methodology is the batch microcosm, whose potential limitations and suitable technical alternatives are explored in this thesis. In a critical literature review, I discuss how continuous-flow conditions stimulate microbial attachment and biofilm formation, and identify unique microbiological phenomena largely absent in batch bottles, yet potentially relevant to contaminant fate. Following up on this theoretical evaluation, I experimentally produce pyrosequencing data and perform beta diversity analysis to demonstrate that batch and continuous-flow (column) microcosms foster distinctly different microbial communities. Next, I introduce the In Situ Microcosm Array (ISMA), which took approximately two years to design, develop, build and iteratively improve. The ISMA can be deployed down-hole in groundwater monitoring wells of contaminated aquifers for the purpose of autonomously conducting multiple parallel continuous-flow treatability experiments. The ISMA stores all sample generated in the course of each experiment, thereby preventing the release of chemicals into the environment. Detailed results are presented from an ISMA demonstration evaluating ISB for the treatment of hexavalent chromium and trichloroethene. In a technical and economical comparison to batch microcosms, I demonstrate the ISMA is both effective in informing remedial design decisions and cost-competitive. Finally, I report on a participatory technology assessment (pTA) workshop attended by diverse stakeholders of the Phoenix 52nd Street Superfund Site evaluating the ISMA's ability for addressing a real-world problem. In addition to receiving valuable feedback on perceived ISMA limitations, I conclude from the workshop that pTA can facilitate mutual learning even among entrenched stakeholders. In summary, my doctoral research (i) pinpointed limitations of current remedial design approaches, (ii) produced a novel alternative approach, and (iii) demonstrated the technical, economical and social value of this novel remedial design tool, i.e., the In Situ Microcosm Array technology.
ContributorsKalinowski, Tomasz (Author) / Halden, Rolf U. (Thesis advisor) / Johnson, Paul C (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Bennett, Ira (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems.

Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems. In particular, the focus is on an information theoretic analysis for P2P systems with synchronization errors and developing new signaling solutions for several asynchronous cooperative communication systems. The first part of the dissertation presents several bounds on the capacity of the P2P systems with synchronization errors. First, binary insertion and deletion channels are considered where lower bounds on the mutual information between the input and output sequences are computed for independent uniformly distributed (i.u.d.) inputs. Then, a channel suffering from both synchronization errors and additive noise is considered as a serial concatenation of a synchronization error-only channel and an additive noise channel. It is proved that the capacity of the original channel is lower bounded in terms of the synchronization error-only channel capacity and the parameters of both channels. On a different front, to better characterize the deletion channel capacity, the capacity of three independent deletion channels with different deletion probabilities are related through an inequality resulting in the tightest upper bound on the deletion channel capacity for deletion probabilities larger than 0.65. Furthermore, the first non-trivial upper bound on the 2K-ary input deletion channel capacity is provided by relating the 2K-ary input deletion channel capacity with the binary deletion channel capacity through an inequality. The second part of the dissertation develops two new relaying schemes to alleviate asynchronism issues in cooperative communications. The first one is a single carrier (SC)-based scheme providing a spectrally efficient Alamouti code structure at the receiver under flat fading channel conditions by reducing the overhead needed to overcome the asynchronism and obtain spatial diversity. The second one is an orthogonal frequency division multiplexing (OFDM)-based approach useful for asynchronous cooperative systems experiencing excessive relative delays among the relays under frequency-selective channel conditions to achieve a delay diversity structure at the receiver and extract spatial diversity.
ContributorsRahmati, Mojtaba (Author) / Duman, Tolga M. (Thesis advisor) / Zhang, Junshan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different control algorithms. The focus

The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different control algorithms. The focus of this thesis is to design scheduling and power control algorithms in wireless networks, and analyze their performances. In this thesis, we first study the multicast capacity of wireless ad hoc networks. Gupta and Kumar studied the scaling law of the unicast capacity of wireless ad hoc networks. They derived the order of the unicast throughput, as the number of nodes in the network goes to infinity. In our work, we characterize the scaling of the multicast capacity of large-scale MANETs under a delay constraint D. We first derive an upper bound on the multicast throughput, and then propose a lower bound on the multicast capacity by proposing a joint coding-scheduling algorithm that achieves a throughput within logarithmic factor of the upper bound. We then study the power control problem in ad-hoc wireless networks. We propose a distributed power control algorithm based on the Gibbs sampler, and prove that the algorithm is throughput optimal. Finally, we consider the scheduling algorithm in collocated wireless networks with flow-level dynamics. Specifically, we study the delay performance of workload-based scheduling algorithm with SRPT as a tie-breaking rule. We demonstrate the superior flow-level delay performance of the proposed algorithm using simulations.
ContributorsZhou, Shan (Author) / Ying, Lei (Thesis advisor) / Zhang, Yanchao (Committee member) / Zhang, Junshan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival

Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival estimates are based upon accurate direct sequence spread spectrum (DSSS) code and carrier phase tracking. Current multipath mitigating GNSS solutions include fixed radiation pattern antennas and windowed delay-lock loop code phase discriminators. A new multipath mitigating code tracking algorithm is introduced that utilizes a non-symmetric correlation kernel to reject multipath. Independent parameters provide a means to trade-off code tracking discriminant gain against multipath mitigation performance. The algorithm performance is characterized in terms of multipath phase error bias, phase error estimation variance, tracking range, tracking ambiguity and implementation complexity. The algorithm is suitable for modernized GNSS signals including Binary Phase Shift Keyed (BPSK) and a variety of Binary Offset Keyed (BOC) signals. The algorithm compensates for unbalanced code sequences to ensure a code tracking bias does not result from the use of asymmetric correlation kernels. The algorithm does not require explicit knowledge of the propagation channel model. Design recommendations for selecting the algorithm parameters to mitigate precorrelation filter distortion are also provided.
ContributorsMiller, Steven (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Tsakalis, Konstantinos (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption

The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption and large-scale deployment are often hindered by people's concerns about the security, user privacy, or both. In this dissertation, we aim to address a number of challenging security and privacy issues in heterogeneous wireless and mobile networks in an attempt to foster their widespread adoption. Our contributions are mainly fivefold. First, we introduce a novel secure and loss-resilient code dissemination scheme for wireless sensor networks deployed in hostile and harsh environments. Second, we devise a novel scheme to enable mobile users to detect any inauthentic or unsound location-based top-k query result returned by an untrusted location-based service providers. Third, we develop a novel verifiable privacy-preserving aggregation scheme for people-centric mobile sensing systems. Fourth, we present a suite of privacy-preserving profile matching protocols for proximity-based mobile social networking, which can support a wide range of matching metrics with different privacy levels. Last, we present a secure combination scheme for crowdsourcing-based cooperative spectrum sensing systems that can enable robust primary user detection even when malicious cognitive radio users constitute the majority.
ContributorsZhang, Rui (Author) / Zhang, Yanchao (Thesis advisor) / Duman, Tolga Mete (Committee member) / Xue, Guoliang (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart

Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This work focuses on a generalized assessment of source zone natural attenuation (SZNA) at chlorinated aliphatic hydrocarbon (CAH) impacted sites. Given the numbers of sites and technical challenges for cleanup there is a need for a SZNA method at CAH impacted sites. The method anticipates that decision makers will be

This work focuses on a generalized assessment of source zone natural attenuation (SZNA) at chlorinated aliphatic hydrocarbon (CAH) impacted sites. Given the numbers of sites and technical challenges for cleanup there is a need for a SZNA method at CAH impacted sites. The method anticipates that decision makers will be interested in the following questions: 1-Is SZNA occurring and what processes contribute? 2-What are the current SZNA rates? 3-What are the longer-term implications? The approach is macroscopic and uses multiple lines-of-evidence. An in-depth application of the generalized non-site specific method over multiple site events, with sampling refinement approaches applied for improving SZNA estimates, at three CAH impacted sites is presented with a focus on discharge rates for four events over approximately three years (Site 1:2.9, 8.4, 4.9, 2.8kg/yr as PCE, Site 2:1.6, 2.2, 1.7, 1.1kg/y as PCE, Site 3:570, 590, 250, 240kg/y as TCE). When applying the generalized CAH-SZNA method, it is likely that different practitioners will not sample a site similarly, especially regarding sampling density on a groundwater transect. Calculation of SZNA rates is affected by contaminant spatial variability with reference to transect sampling intervals and density with variations in either resulting in different mass discharge estimates. The effects on discharge estimates from varied sampling densities and spacings were examined to develop heuristic sampling guidelines with practical site sampling densities; the guidelines aim to reduce the variability in discharge estimates due to different sampling approaches and to improve confidence in SZNA rates allowing decision-makers to place the rates in perspective and determine a course of action based on remedial goals. Finally bench scale testing was used to address longer term questions; specifically the nature and extent of source architecture. A rapid in-situ disturbance method was developed using a bench-scale apparatus. The approach allows for rapid identification of the presence of DNAPL using several common pilot scale technologies (ISCO, air-sparging, water-injection) and can identify relevant source architectural features (ganglia, pools, dissolved source). Understanding of source architecture and identification of DNAPL containing regions greatly enhances site conceptualization models, improving estimated time frames for SZNA, and possibly improving design of remedial systems.
ContributorsEkre, Ryan (Author) / Johnson, Paul Carr (Thesis advisor) / Rittmann, Bruce (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2013
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Description
To further the efforts producing energy from more renewable sources, microbial electrochemical cells (MXCs) can utilize anode respiring bacteria (ARB) to couple the oxidation of an organic substrate to the delivery of electrons to the anode. Although ARB such as Geobacter and Shewanella have been well-studied in terms of their

To further the efforts producing energy from more renewable sources, microbial electrochemical cells (MXCs) can utilize anode respiring bacteria (ARB) to couple the oxidation of an organic substrate to the delivery of electrons to the anode. Although ARB such as Geobacter and Shewanella have been well-studied in terms of their microbiology and electrochemistry, much is still unknown about the mechanism of electron transfer to the anode. To this end, this thesis seeks to elucidate the complexities of electron transfer existing in Geobacter sulfurreducens biofilms by employing Electrochemical Impedance Spectroscopy (EIS) as the tool of choice. Experiments measuring EIS resistances as a function of growth were used to uncover the potential gradients that emerge in biofilms as they grow and become thicker. While a better understanding of this model ARB is sought, electrochemical characterization of a halophile, Geoalkalibacter subterraneus (Glk. subterraneus), revealed that this organism can function as an ARB and produce seemingly high current densities while consuming different organic substrates, including acetate, butyrate, and glycerol. The importance of identifying and studying novel ARB for broader MXC applications was stressed in this thesis as a potential avenue for tackling some of human energy problems.
ContributorsAjulo, Oluyomi (Author) / Torres, Cesar (Thesis advisor) / Nielsen, David (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Popat, Sudeep (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In situ remediation of contaminated aquifers, specifically in situ bioremediation (ISB), has gained popularity over pump-and-treat operations. It represents a more sustainable approach that can also achieve complete mineralization of contaminants in the subsurface. However, the subsurface reality is very complex, characterized by hydrodynamic groundwater movement, geological heterogeneity, and mass-transfer

In situ remediation of contaminated aquifers, specifically in situ bioremediation (ISB), has gained popularity over pump-and-treat operations. It represents a more sustainable approach that can also achieve complete mineralization of contaminants in the subsurface. However, the subsurface reality is very complex, characterized by hydrodynamic groundwater movement, geological heterogeneity, and mass-transfer phenomena governing contaminant transport and bioavailability. These phenomena cannot be properly studied using commonly conducted laboratory batch microcosms lacking realistic representation of the processes named above. Instead, relevant processes are better understood by using flow-through systems (sediment columns). However, flow-through column studies are typically conducted without replicates. Due to additional sources of variability (e.g., flow rate variation between columns and over time), column studies are expected to be less reproducible than simple batch microcosms. This was assessed through a comprehensive statistical analysis of results from multiple batch and column studies. Anaerobic microbial biotransformations of trichloroethene and of perchlorate were chosen as case studies. Results revealed that no statistically significant differences were found between reproducibility of batch and column studies. It has further been recognized that laboratory studies cannot accurately reproduce many phenomena encountered in the field. To overcome this limitation, a down-hole diagnostic device (in situ microcosm array - ISMA) was developed, that enables the autonomous operation of replicate flow-through sediment columns in a realistic aquifer setting. Computer-aided design (CAD), rapid prototyping, and computer numerical control (CNC) machining were used to create a tubular device enabling practitioners to conduct conventional sediment column studies in situ. A case study where two remediation strategies, monitored natural attenuation and bioaugmentation with concomitant biostimulation, were evaluated in the laboratory and in situ at a perchlorate-contaminated site. Findings demonstrate the feasibility of evaluating anaerobic bioremediation in a moderately aerobic aquifer. They further highlight the possibility of mimicking in situ remediation strategies on the small-scale in situ. The ISMA is the first device offering autonomous in situ operation of conventional flow-through sediment microcosms and producing statistically significant data through the use of multiple replicates. With its sustainable approach to treatability testing and data gathering, the ISMA represents a versatile addition to the toolbox of scientists and engineers.
ContributorsMcClellan, Kristin (Author) / Halden, Rolf U. (Thesis advisor) / Johnson, Paul C (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Asymptotic comparisons of ergodic channel capacity at high and low signal-to-noise ratios (SNRs) are provided for several adaptive transmission schemes over fading channels with general distributions, including optimal power and rate adaptation, rate adaptation only, channel inversion and its variants. Analysis of the high-SNR pre-log constants of the ergodic capacity

Asymptotic comparisons of ergodic channel capacity at high and low signal-to-noise ratios (SNRs) are provided for several adaptive transmission schemes over fading channels with general distributions, including optimal power and rate adaptation, rate adaptation only, channel inversion and its variants. Analysis of the high-SNR pre-log constants of the ergodic capacity reveals the existence of constant capacity difference gaps among the schemes with a pre-log constant of 1. Closed-form expressions for these high-SNR capacity difference gaps are derived, which are proportional to the SNR loss between these schemes in dB scale. The largest one of these gaps is found to be between the optimal power and rate adaptation scheme and the channel inversion scheme. Based on these expressions it is shown that the presence of space diversity or multi-user diversity makes channel inversion arbitrarily close to achieving optimal capacity at high SNR with sufficiently large number of antennas or users. A low-SNR analysis also reveals that the presence of fading provably always improves capacity at sufficiently low SNR, compared to the additive white Gaussian noise (AWGN) case. Numerical results are shown to corroborate our analytical results. This dissertation derives high-SNR asymptotic average error rates over fading channels by relating them to the outage probability, under mild assumptions. The analysis is based on the Tauberian theorem for Laplace-Stieltjes transforms which is grounded on the notion of regular variation, and applies to a wider range of channel distributions than existing approaches. The theory of regular variation is argued to be the proper mathematical framework for finding sufficient and necessary conditions for outage events to dominate high-SNR error rate performance. It is proved that the diversity order being d and the cumulative distribution function (CDF) of the channel power gain having variation exponent d at 0 imply each other, provided that the instantaneous error rate is upper-bounded by an exponential function of the instantaneous SNR. High-SNR asymptotic average error rates are derived for specific instantaneous error rates. Compared to existing approaches in the literature, the asymptotic expressions are related to the channel distribution in a much simpler manner herein, and related with outage more intuitively. The high-SNR asymptotic error rate is also characterized under diversity combining schemes with the channel power gain of each branch having a regularly varying CDF. Numerical results are shown to corroborate our theoretical analysis. This dissertation studies several problems concerning channel inclusion, which is a partial ordering between discrete memoryless channels (DMCs) proposed by Shannon. Specifically, majorization-based conditions are derived for channel inclusion between certain DMCs. Furthermore, under general conditions, channel equivalence defined through Shannon ordering is shown to be the same as permutation of input and output symbols. The determination of channel inclusion is considered as a convex optimization problem, and the sparsity of the weights related to the representation of the worse DMC in terms of the better one is revealed when channel inclusion holds between two DMCs. For the exploitation of this sparsity, an effective iterative algorithm is established based on modifying the orthogonal matching pursuit algorithm. The extension of channel inclusion to continuous channels and its application in ordering phase noises are briefly addressed.
ContributorsZhang, Yuan (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Zhang, Junshan (Committee member) / Reisslein, Martin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2013