Theses and Dissertations
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 149
Description
With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For Twitter data extraction, we developed a multi-threaded application which seamlessly extracts, cleans and stores millions of tweets matching our keywords from Twitter Streaming API. For keyword extraction, we used topics and perspectives which were extracted using n-grams techniques and later approved by our social scientists. After the data is extracted, we aggregate the tweet contents that belong to every user on a weekly basis. Finally, we applied linear and logistic regression using SLEP, an open source sparse learning package to compute weekly score for users and mapping them to one of the 27 organizations on a radical or counter radical scale. Since, we are mapping users to organizations on a weekly basis, we are able to track user's behavior and important new events that triggered shifts among users between organizations. This thesis study can further be extended to identify topics and organization specific influential users and new users from various social media platforms like Facebook, YouTube etc. can easily be mapped to existing organizations on a radical or counter-radical scale.
ContributorsPoornachandran, Sathishkumar (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Woodward, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
There is a lack of music therapy services for college students who have problems with depression and/or anxiety. Even among universities and colleges that offer music therapy degrees, there are no known programs offering music therapy to the institution's students. Female college students are particularly vulnerable to depression and anxiety symptoms compared to their male counterparts. Many students who experience mental health problems do not receive treatment, because of lack of knowledge, lack of services, or refusal of treatment. Music therapy is proposed as a reliable and valid complement or even an alternative to traditional counseling and pharmacotherapy because of the appeal of music to young women and the potential for a music therapy group to help isolated students form supportive networks. The present study recruited 14 female university students to participate in a randomized controlled trial of short-term group music therapy to address symptoms of depression and anxiety. The students were randomly divided into either the treatment group or the control group. Over 4 weeks, each group completed surveys related to depression and anxiety. Results indicate that the treatment group's depression and anxiety scores gradually decreased over the span of the treatment protocol. The control group showed either maintenance or slight worsening of depression and anxiety scores. Although none of the results were statistically significant, the general trend indicates that group music therapy was beneficial for the students. A qualitative analysis was also conducted for the treatment group. Common themes were financial concerns, relationship problems, loneliness, and time management/academic stress. All participants indicated that they benefited from the sessions. The group progressed in its cohesion and the participants bonded to the extent that they formed a supportive network which lasted beyond the end of the protocol. The results of this study are by no means conclusive, but do indicate that colleges with music therapy degree programs should consider adding music therapy services for their general student bodies.
ContributorsAshton, Barbara (Author) / Crowe, Barbara J. (Thesis advisor) / Rio, Robin (Committee member) / Davis, Mary (Committee member) / Arizona State University (Publisher)
Created2013
Description
When people look for things in their environment they use a target template - a mental representation of the object they are attempting to locate - to guide their attention around a scene and to assess incoming visual input to determine if they have found that for which they are searching. However, unlike laboratory experiments, searchers in the real-world rarely have perfect knowledge regarding the appearance of their target. In five experiments (with nearly 1,000 participants), we examined how the precision of the observer's template affects their ability to conduct visual search. Specifically, we simulated template imprecision in two ways: First, by contaminating our searchers' templates with inaccurate features, and second, by introducing extraneous features to the template that were unhelpful. In those experiments we recorded the eye movements of our searchers in order to make inferences regarding the extent to which attentional guidance and decision-making are hindered by template imprecision. We also examined a third way in which templates may become imprecise; namely, that they may deteriorate over time. Overall, our findings support a dual-function theory of the target template, and highlight the importance of examining template precision in future research.
ContributorsHout, Michael C (Author) / Goldinger, Stephen D (Thesis advisor) / Azuma, Tamiko (Committee member) / Homa, Donald (Committee member) / Reichle, Erik (Committee member) / Arizona State University (Publisher)
Created2013
Description
Two groups of cochlear implant (CI) listeners were tested for sound source localization and for speech recognition in complex listening environments. One group (n=11) wore bilateral CIs and, potentially, had access to interaural level difference (ILD) cues, but not interaural timing difference (ITD) cues. The second group (n=12) wore a single CI and had low-frequency, acoustic hearing in both the ear contralateral to the CI and in the implanted ear. These `hearing preservation' listeners, potentially, had access to ITD cues but not to ILD cues. At issue in this dissertation was the value of the two types of information about sound sources, ITDs and ILDs, for localization and for speech perception when speech and noise sources were separated in space. For Experiment 1, normal hearing (NH) listeners and the two groups of CI listeners were tested for sound source localization using a 13 loudspeaker array. For the NH listeners, the mean RMS error for localization was 7 degrees, for the bilateral CI listeners, 20 degrees, and for the hearing preservation listeners, 23 degrees. The scores for the two CI groups did not differ significantly. Thus, both CI groups showed equivalent, but poorer than normal, localization. This outcome using the filtered noise bands for the normal hearing listeners, suggests ILD and ITD cues can support equivalent levels of localization. For Experiment 2, the two groups of CI listeners were tested for speech recognition in noise when the noise sources and targets were spatially separated in a simulated `restaurant' environment and in two versions of a `cocktail party' environment. At issue was whether either CI group would show benefits from binaural hearing, i.e., better performance when the noise and targets were separated in space. Neither of the CI groups showed spatial release from masking. However, both groups showed a significant binaural advantage (a combination of squelch and summation), which also maintained separation of the target and noise, indicating the presence of some binaural processing or `unmasking' of speech in noise. Finally, localization ability in Experiment 1 was not correlated with binaural advantage in Experiment 2.
ContributorsLoiselle, Louise (Author) / Dorman, Michael F. (Thesis advisor) / Yost, William A. (Thesis advisor) / Azuma, Tamiko (Committee member) / Liss, Julie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Concussion, a subset of mild traumatic brain injury (mTBI), has recently been brought to the forefront of the media due to a large lawsuit filed against the National Football League. Concussion resulting from injury varies in severity, duration, and type, based on many characteristics about the individual that research does not presently understand. Chronic fatigue, poor working memory, impaired self-awareness, and lack of attention to task are symptoms commonly present post-concussion. Currently, there is not a standard method of assessing concussion, nor is there a way to track an individual's recovery, resulting in misguided treatment for better prognosis. The aim of the following study was to determine patient specific higher-order cognitive processing deficits for clinical diagnosis and prognosis of concussion. Six individuals (N=6) were seen during the acute phase of concussion, two of whom were seen subsequently when their symptoms were deemed clinically resolved. Subjective information was collected from both the patient and from neurology testing. Each individual completed a task, in which they were presented with degraded speech, taxing their higher-order cognitive processing. Patient specific behavioral patterns are noted, creating a unique paradigm for mapping subjective and objective data for each patient's strategy to compensate for deficits and understand speech in a difficult listening situation. Keywords: concussion, cognitive processing
ContributorsBerg, Dena (Author) / Liss, Julie M (Committee member) / Azuma, Tamiko (Committee member) / Caviness, John (Committee member) / Arizona State University (Publisher)
Created2013
Description
The pay-as-you-go economic model of cloud computing increases the visibility, traceability, and verifiability of software costs. Application developers must understand how their software uses resources when running in the cloud in order to stay within budgeted costs and/or produce expected profits. Cloud computing's unique economic model also leads naturally to an earn-as-you-go profit model for many cloud based applications. These applications can benefit from low level analyses for cost optimization and verification. Testing cloud applications to ensure they meet monetary cost objectives has not been well explored in the current literature. When considering revenues and costs for cloud applications, the resource economic model can be scaled down to the transaction level in order to associate source code with costs incurred while running in the cloud. Both static and dynamic analysis techniques can be developed and applied to understand how and where cloud applications incur costs. Such analyses can help optimize (i.e. minimize) costs and verify that they stay within expected tolerances. An adaptation of Worst Case Execution Time (WCET) analysis is presented here to statically determine worst case monetary costs of cloud applications. This analysis is used to produce an algorithm for determining control flow paths within an application that can exceed a given cost threshold. The corresponding results are used to identify path sections that contribute most to cost excess. A hybrid approach for determining cost excesses is also presented that is comprised mostly of dynamic measurements but that also incorporates calculations that are based on the static analysis approach. This approach uses operational profiles to increase the precision and usefulness of the calculations.
ContributorsBuell, Kevin, Ph.D (Author) / Collofello, James (Thesis advisor) / Davulcu, Hasan (Committee member) / Lindquist, Timothy (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012
Description
Contention based IEEE 802.11MAC uses the binary exponential backoff algorithm (BEB) for the contention resolution. The protocol suffers poor performance in the heavily loaded networks and MANETs, high collision rate and packet drops, probabilistic delay guarantees, and unfairness. Many backoff strategies were proposed to improve the performance of IEEE 802.11 but all ignore the network topology and demand. Persistence is defined as the fraction of time a node is allowed to transmit, when this allowance should take into account topology and load, it is topology and load aware persistence (TLA). We develop a relation between contention window size and the TLA-persistence. We implement a new backoff strategy where the TLA-persistence is defined as the lexicographic max-min channel allocation. We use a centralized algorithm to calculate each node's TLApersistence and then convert it into a contention window size. The new backoff strategy is evaluated in simulation, comparing with that of the IEEE 802.11 using BEB. In most of the static scenarios like exposed terminal, flow in the middle, star topology, and heavy loaded multi-hop networks and in MANETs, through the simulation study, we show that the new backoff strategy achieves higher overall average throughput as compared to that of the IEEE 802.11 using BEB.
ContributorsBhyravajosyula, Sai Vishnu Kiran (Author) / Syrotiuk, Violet R. (Thesis advisor) / Sen, Arunabha (Committee member) / Richa, Andrea (Committee member) / Arizona State University (Publisher)
Created2013
Description
As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.
ContributorsShirazipourazad, Shahrzad (Author) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Saripalli, Srikanth (Committee member) / Arizona State University (Publisher)
Created2014
Description
Sometimes difficult life events challenge our existing resources in such a way that routinized responses are inadequate to handle the challenge. Some individuals will persist in habitual, automatic behavior, regardless of environmental cues that indicate a mismatch between coping strategy and the demands of the stressor. Other individuals will marshal adaptive resources to construct new courses of action and reconceptualize the problem, associated goals and/or values. A mixed methods approach was used to describe and operationalize cognitive shift, a relatively unexplored construct in existing literature. The study was conducted using secondary data from a parent multi-year cross-sectional study of resilience with eight hundred mid-aged adults from the Phoenix metro area. Semi-structured telephone interviews were analyzed using a purposive sample (n=136) chosen by type of life event. Participants' beliefs, assumptions, and experiences were examined to understand how they shaped adaptation to adversity. An adaptive mechanism, "cognitive shift," was theorized as the transition from automatic coping to effortful cognitive processes aimed at novel resolution of issues. Aims included understanding when and how cognitive shift emerges and manifests. Cognitive shift was scored as a binary variable and triangulated through correlational and logistic regression analyses. Interaction effects revealed that positive personality attributes influence cognitive shift most when people suffered early adversity. This finding indicates that a certain complexity, self-awareness and flexibility of mind may lead to a greater capacity to find meaning in adversity. This work bridges an acknowledged gap in literature and provides new insights into resilience.
ContributorsRivers, Crystal T (Author) / Zautra, Alex (Thesis advisor) / Davis, Mary (Committee member) / Kurpius, Sharon (Committee member) / Arizona State University (Publisher)
Created2014
Description
Previous research has shown that people can implicitly learn repeated visual contexts and use this information when locating relevant items. For example, when people are presented with repeated spatial configurations of distractor items or distractor identities in visual search, they become faster to find target stimuli in these repeated contexts over time (Chun and Jiang, 1998; 1999). Given that people learn these repeated distractor configurations and identities, might they also implicitly encode semantic information about distractors, if this information is predictive of the target location? We investigated this question with a series of visual search experiments using real-world stimuli within a contextual cueing paradigm (Chun and Jiang, 1998). Specifically, we tested whether participants could learn, through experience, that the target images they are searching for are always located near specific categories of distractors, such as food items or animals. We also varied the spatial consistency of target locations, in order to rule out implicit learning of repeated target locations. Results suggest that participants implicitly learned the target-predictive categories of distractors and used this information during search, although these results failed to reach significance. This lack of significance may have been due the relative simplicity of the search task, however, and several new experiments are proposed to further investigate whether repeated category information can benefit search.
ContributorsWalenchok, Stephen C (Author) / Goldinger, Stephen D (Thesis advisor) / Azuma, Tamiko (Committee member) / Homa, Donald (Committee member) / Hout, Michael C (Committee member) / Arizona State University (Publisher)
Created2014