Matching Items (112)
Filtering by
- Genre: Doctoral Dissertation
- Creators: Yan, Hao
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. 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
Description
The principle of Darwinian evolution has been applied in the laboratory to nucleic acid molecules since 1990, and led to the emergence of in vitro evolution technique. The methodology of in vitro evolution surveys a large number of different molecules simultaneously for a pre-defined chemical property, and enrich for molecules with the particular property. DNA and RNA sequences with versatile functions have been identified by in vitro selection experiments, but many basic questions remain to be answered about how these molecules achieve their functions. This dissertation first focuses on addressing a fundamental question regarding the molecular recognition properties of in vitro selected DNA sequences, namely whether negatively charged DNA sequences can be evolved to bind alkaline proteins with high specificity. We showed that DNA binders could be made, through carefully designed stringent in vitro selection, to discriminate different alkaline proteins. The focus of this dissertation is then shifted to in vitro evolution of an artificial genetic polymer called threose nucleic acid (TNA). TNA has been considered a potential RNA progenitor during early evolution of life on Earth. However, further experimental evidence to support TNA as a primordial genetic material is lacking. In this dissertation we demonstrated the capacity of TNA to form stable tertiary structure with specific ligand binding property, which suggests a possible role of TNA as a pre-RNA genetic polymer. Additionally, we discussed the challenges in in vitro evolution for TNA enzymes and developed the necessary methodology for future TNA enzyme evolution.
ContributorsYu, Hanyang (Author) / Chaput, John C (Thesis advisor) / Chen, Julian (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2013
Description
The ribosome is a ribozyme and central to the biosynthesis of proteins in all organisms. It has a strong bias against non-alpha-L-amino acids, such as alpha-D-amino acids and beta-amino acids. Additionally, the ribosome is only able to incorporate one amino acid in response to one codon. It has been demonstrated that reengineering of the peptidyltransferase center (PTC) of the ribosome enabled the incorporation of both alpha-D-amino acids and beta-amino acids into full length protein. Described in Chapter 2 are five modified ribosomes having modifications in the peptidyltrasnferase center in the 23S rRNA. These modified ribosomes successfully incorporated five different beta-amino acids (2.1 - 2.5) into E. coli dihydrofolate reductase (DHFR). The second project (Chapter 3) focused on the study of the modified ribosomes facilitating the incorporation of the dipeptide glycylphenylalanine (3.25) and fluorescent dipeptidomimetic 3.26 into DHFR. These ribosomes also had modifications in the peptidyltransferase center in the 23S rRNA of the 50S ribosomal subunit. The modified DHFRs having beta-amino acids 2.3 and 2.5, dipeptide glycylphenylalanine (3.25) and dipeptidomimetic 3.26 were successfully characterized by the MALDI-MS analysis of the peptide fragments produced by "in-gel" trypsin digestion of the modified proteins. The fluorescent spectra of the dipeptidomimetic 3.26 and modified DHFR having fluorescent dipeptidomimetic 3.26 were also measured. The type I and II DNA topoisomerases have been firmly established as effective molecular targets for many antitumor drugs. A "classical" topoisomerase I or II poison acts by misaligning the free hydroxyl group of the sugar moiety of DNA and preventing the reverse transesterfication reaction to religate DNA. There have been only two classes of compounds, saintopin and topopyrones, reported as dual topoisomerase I and II poisons. Chapter 4 describes the synthesis and biological evaluation of topopyrones. Compound 4.10, employed at 20 µM, was as efficient as 0.5 uM camptothecin, a potent topoisomerase I poison, in stabilizing the covalent binary complex (~30%). When compared with a known topoisomerase II poison, etoposide (at 0.5 uM), topopyorone 4.10 produced similar levels of stabilized DNA-enzyme binary complex (~34%) at 5 uM concentration.
ContributorsMaini, Rumit (Author) / Hecht, Sidney M. (Thesis advisor) / Gould, Ian (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2013
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 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
Description
The biological and chemical diversity of protein structure and function can be greatly expanded by position-specific incorporation of non-natural amino acids bearing a variety of functional groups. Non-cognate amino acids can be incorporated into proteins at specific sites by using orthogonal aminoacyl-tRNA synthetase/tRNA pairs in conjunction with nonsense, rare, or 4-bp codons. There has been considerable progress in developing new types of amino acids, in identifying novel methods of tRNA aminoacylation, and in expanding the genetic code to direct their position. Chemical aminoacylation of tRNAs is accomplished by acylation and ligation of a dinucleotide (pdCpA) to the 3'-terminus of truncated tRNA. This strategy allows the incorporation of a wide range of natural and unnatural amino acids into pre-determined sites, thereby facilitating the study of structure-function relationships in proteins and allowing the investigation of their biological, biochemical and biophysical properties. Described in Chapter 1 is the current methodology for synthesizing aminoacylated suppressor tRNAs. Aminoacylated suppressor tRNACUAs are typically prepared by linking pre-aminoacylated dinucleotides (aminoacyl-pdCpAs) to 74 nucleotide (nt) truncated tRNAs (tRNA-COH) via a T4 RNA ligase mediated reaction. Alternatively, there is another route outlined in Chapter 1 that utilizes a different pre-aminoacylated dinucleotide, AppA. This dinucleotide has been shown to be a suitable substrate for T4 RNA ligase mediated coupling with abbreviated tRNA-COHs for production of 76 nt aminoacyl-tRNACUAs. The synthesized suppressor tRNAs have been shown to participate in protein synthesis in vitro, in an S30 (E. coli) coupled transcription-translation system in which there is a UAG codon in the mRNA at the position corresponding to Val10. Chapter 2 describes the synthesis of two non-proteinogenic amino acids, L-thiothreonine and L-allo-thiothreonine, and their incorporation into predetermined positions of a catalytically competent dihydrofolate reductase (DHFR) analogue lacking cysteine. Here, the elaborated proteins were site-specifically derivitized with a fluorophore at the thiothreonine residue. The synthesis and incorporation of phosphorotyrosine derivatives into DHFR is illustrated in Chapter 3. Three different phosphorylated tyrosine derivatives were prepared: bis-nitrobenzylphosphoro-L-tyrosine, nitrobenzylphosphoro-L-tyrosine, and phosphoro-L-tyrosine. Their ability to participate in a protein synthesis system was also evaluated.
ContributorsNangreave, Ryan Christopher (Author) / Hecht, Sidney M. (Thesis advisor) / Yan, Hao (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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 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
Description
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solution conformations and dynamics of proteins and protein-DNA complexes are often difficult to predict from their crystal structures. The crystal structure only shows a snapshot of the different conformations these biological molecules can have in solution. Multiple different conformations can exist in solution and potentially have more importance in the biological activity. DNA sliding clamps are a family of proteins with known crystal structures. These clamps encircle the DNA and enable other proteins to interact more efficiently with the DNA. Eukaryotic PCNA and prokaryotic β clamp are two of these clamps, some of the most stable homo-oligomers known. However, their solution stability and conformational equilibrium have not been investigated in depth before. Presented here are the studies involving two sliding clamps: yeast PCNA and bacterial β clamp. These studies show that the β clamp has a very different solution stability than PCNA. These conclusions were reached through various different fluorescence-based experiments, including fluorescence correlation spectroscopy (FCS), Förster resonance energy transfer (FRET), single molecule fluorescence, and various time resolved fluorescence techniques. Interpretations of these, and all other, fluorescence-based experiments are often affected by the properties of the fluorophores employed. Often the fluorescence properties of these fluorophores are influenced by their microenvironments. Fluorophores are known to sometimes interact with biological molecules, and this can have pronounced effects on the rotational mobility and photophysical properties of the dye. Misunderstanding the effect of these photophysical and rotational properties can lead to a misinterpretation of the obtained data. In this thesis, photophysical behaviors of various organic dyes were studied in the presence of deoxymononucleotides to examine more closely how interactions between fluorophores and DNA bases can affect fluorescent properties. Furthermore, the properties of cyanine dyes when bound to DNA and the effect of restricted rotation on FRET are presented in this thesis. This thesis involves studying fluorophore photophysics in various microenvironments and then expanding into the solution stability and dynamics of the DNA sliding clamps.
ContributorsRanjit, Suman (Author) / Levitus, Marcia (Thesis advisor) / Lindsay, Stuart (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2013
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 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