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Description
Bioparticles comprise a diverse amount of materials ubiquitously present in nature. From proteins to aerosolized biological debris, bioparticles have important roles spanning from regulating cellular functions to possibly influencing global climate. Understanding their structures, functions, and properties provides the necessary tools to expand our fundamental knowledge of biological systems and exploit them for useful applications. In order to contribute to this efforts, the work presented in this dissertation focuses on the study of electrokinetic properties of liposomes and novel applications of bioaerosol analysis. Using immobilized lipid vesicles under the influence of modest (less than 100 V/cm) electric fields, a novel strategy for bionanotubule fabrication with superior throughput and simplicity was developed. Fluorescence and bright field microscopy was used to describe the formation of these bilayer-bound cylindrical structures, which have been previously identified in nature (playing crucial roles in intercellular communication) and made synthetically by direct mechanical manipulation of membranes. In the biological context, the results of this work suggest that mechanical electrostatic interaction may play a role in the shape and function of individual biological membranes and networks of membrane-bound structures. A second project involving liposomes focused on membrane potential measurements in vesicles containing trans-membrane pH gradients. These types of gradients consist of differential charge states in the lipid bilayer leaflets, which have been shown to greatly influence the efficacy of drug targeting and the treatment of diseases such as cancer. Here, these systems are qualitatively and quantitatively assessed by using voltage-sensitive membrane dyes and fluorescence spectroscopy. Bioaerosol studies involved exploring the feasibility of a fingerprinting technology based on current understanding of cellular debris in aerosols and arguments regarding sampling, sensitivity, separations and detection schemes of these debris. Aerosolized particles of cellular material and proteins emitted by humans, animals and plants can be considered information-rich packets that carry biochemical information specific to the living organisms present in the collection settings. These materials could potentially be exploited for identification purposes. Preliminary studies evaluated protein concentration trends in both indoor and outdoor locations. Results indicated that concentrations correlate to certain conditions of the collection environment (e.g. extent of human presence), supporting the idea that bioaerosol fingerprinting is possible.
ContributorsCastillo Gutiérrez, Josemar Andreina (Author) / Hayes, Mark A. (Thesis advisor) / Herckes, Pierre (Committee member) / Ghrilanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
Description
As pointed out in the keynote speech by H. V. Jagadish in SIGMOD'07, and also commonly agreed in the database community, the usability of structured data by casual users is as important as the data management systems' functionalities. A major hardness of using structured data is the problem of easily retrieving information from them given a user's information needs. Learning and using a structured query language (e.g., SQL and XQuery) is overwhelmingly burdensome for most users, as not only are these languages sophisticated, but the users need to know the data schema. Keyword search provides us with opportunities to conveniently access structured data and potentially significantly enhances the usability of structured data. However, processing keyword search on structured data is challenging due to various types of ambiguities such as structural ambiguity (keyword queries have no structure), keyword ambiguity (the keywords may not be accurate), user preference ambiguity (the user may have implicit preferences that are not indicated in the query), as well as the efficiency challenges due to large search space. This dissertation performs an expansive study on keyword search processing techniques as a gateway for users to access structured data and retrieve desired information. The key issues addressed include: (1) Resolving structural ambiguities in keyword queries by generating meaningful query results, which involves identifying relevant keyword matches, identifying return information, composing query results based on relevant matches and return information. (2) Resolving structural, keyword and user preference ambiguities through result analysis, including snippet generation, result differentiation, result clustering, result summarization/query expansion, etc. (3) Resolving the efficiency challenge in processing keyword search on structured data by utilizing and efficiently maintaining materialized views. These works deliver significant technical contributions towards building a full-fledged search engine for structured data.
ContributorsLiu, Ziyang (Author) / Chen, Yi (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Jagadish, H V (Committee member) / Arizona State University (Publisher)
Created2011
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
Belief affects behavior and rhetoric has the potential to bring about action. This paper is a critical content analysis of the ideology and rhetoric of key Islamist intellectuals and the Islamist organization Hizb ut-Tahrir, as stated on the website http://english.hizbuttahrir.org. The responses of specific Muslim Reformers are also analyzed. The central argument underlying this analysis centers on the notion that such Islamist ideology and its rhetorical delivery could be a significant trigger for the use of violence; interacting with, yet existing independently of, other factors that contribute to violent actions. In this case, a significant aspect of any solution to Islamist rhetoric would require that Muslim Reformers present a compelling counter-narrative to political Islam (Islamism), one that has an imperative to reduce the amount of violence in the region. Rhetoric alone cannot solve the many complicated issues in the region but we must begin somewhere and countering the explicit and implicit calls to violence of political Islamist organizations like Hizb ut-Tahrir seems a constructive step.
ContributorsBoyer, Paul Daniel (Author) / Mean, Lindsey (Thesis advisor) / Waldron, Vincent (Committee member) / Carter, Heather (Committee member) / Arizona State University (Publisher)
Created2010
Description
This thesis describes a synthetic task environment, CyberCog, created for the purposes of 1) understanding and measuring individual and team situation awareness in the context of a cyber security defense task and 2) providing a context for evaluating algorithms, visualizations, and other interventions that are intended to improve cyber situation awareness. CyberCog provides an interactive environment for conducting human-in-loop experiments in which the participants of the experiment perform the tasks of a cyber security defense analyst in response to a cyber-attack scenario. CyberCog generates the necessary performance measures and interaction logs needed for measuring individual and team cyber situation awareness. Moreover, the CyberCog environment provides good experimental control for conducting effective situation awareness studies while retaining realism in the scenario and in the tasks performed.
ContributorsRajivan, Prashanth (Author) / Femiani, John (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Lindquist, Timothy (Committee member) / Gary, Kevin (Committee member) / Arizona State University (Publisher)
Created2011
Description
With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
The United States is facing an emerging principal shortage. This study examines an intervention to deliver professional development for assistant principals on their way to becoming principals. The intervention intended to boost their sense of efficacy as if they were principals while creating a supportive community of professionals for ongoing professional learning. The community was designed much like a professional learning community (PLC) with the intent of developing into a community of practice (CoP). The participants were all elementary school assistant principals in a Title I district in a large metropolitan area. The researcher interviewed an expert set of school administrators consisting of superintendents and consultants (and others who have knowledge of what a good principal ought to be) about what characteristics and skills were left wanting in principal applicants. The data from these interviews provided the discussion topics for the intervention. The assistant principals met regularly over the course of a semester and discussed the topics provided by the expert set of school administrators. Participant interaction within the sessions followed conversation protocols. The researcher was also a participant in the group and served as the coordinator. Each session was recorded and transcribed. The researcher used a mixed methods approach to analyze the intervention. Participants were surveyed to measure their efficacy before and after the intervention. The session transcripts were analyzed using open and axial coding. Data showed no statistically significant change in the participants' sense of efficacy. Data also showed the participants became a coalescing community of practice.
ContributorsRichman, Bryan (Author) / Puckett, Kathleen (Thesis advisor) / Smith, Jeffery (Committee member) / Foulger, Teresa (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation explores the rhetorical significance of persecution claims produced by demonstrably powerful publics in contemporary American culture. This ideological criticism is driven by several related research questions. First, how do members of apparently powerful groups (men, whites, and Christians) come to see themselves as somehow unjustly marginalized, persecuted, or powerless? Second, how are these discourses related to the public sphere and counterpublicity? I argue that, despite startling similarities, these texts studied here are best understood not as counterpublicity but as a strategy of containment available to hegemonic publics. Because these rhetorics of persecution often seek to forestall movements toward pluralism and restorative justice, the analysis forwarded in this dissertation offers important contributions to ongoing theoretical discussions in the fields of public sphere theory and critical cultural theory and practical advice for progressive political activism and critical pedagogy.
ContributorsDuerringer, Christopher (Author) / Brouwer, Daniel (Thesis advisor) / Carlson, Cheree (Committee member) / McDonald, Kelly (Committee member) / Arizona State University (Publisher)
Created2011
Description
Applications of non-traditional stable isotope variations are moving beyond geosciences to biomedicine, made possible by advances in multiple collector inductively coupled plasma mass spectrometry (MC-ICP-MS) technology. Mass-dependent isotope variation can provide information about the sources of elements and the chemical reactions that they undergo. Iron and calcium isotope systematics in biomedicine are relatively unexplored but have great potential scientific interest due to their essential nature in metabolism. Iron, a crucial element in biology, fractionates during biochemically relevant reactions. To test the extent of this fractionation in an important reaction process, equilibrium iron isotope fractionation during organic ligand exchange was determined. The results show that iron fractionates during organic ligand exchange, and that isotope enrichment increases as a function of the difference in binding constants between ligands. Additionally, to create a mass balance model for iron in a whole organism, iron isotope compositions in a whole mouse and in individual mouse organs were measured. The results indicate that fractionation occurs during transfer between individual organs, and that the whole organism was isotopically light compared with food. These two experiments advance our ability to interpret stable iron isotopes in biomedicine. Previous research demonstrated that calcium isotope variations in urine can be used as an indicator of changes in net bone mineral balance. In order to measure calcium isotopes by MC-ICP-MS, a chemical purification method was developed to quantitatively separate calcium from other elements in a biological matrix. Subsequently, this method was used to evaluate if calcium isotopes respond when organisms are subjected to conditions known to induce bone loss: 1) Rhesus monkeys were given an estrogen-suppressing drug; 2) Human patients underwent extended bed rest. In both studies, there were rapid, detectable changes in calcium isotope compositions from baseline - verifying that calcium isotopes can be used to rapidly detect changes in bone mineral balance. By characterizing iron isotope fractionation in biologically relevant processes and by demonstrating that calcium isotopes vary rapidly in response to bone loss, this thesis represents an important step in utilizing these isotope systems as a diagnostic and mechanistic tool to study the metabolism of these elements in vivo.
ContributorsMorgan, Jennifer Lynn Louden (Author) / Anbar, Ariel D. (Thesis advisor) / Wasylenki, Laura E. (Committee member) / Jones, Anne K. (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2011