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- Genre: Masters Thesis
Description
While the literature on caregivers of loved ones with Alzheimer's Disease and Related Disorders (ADRD) has continued to grow, the relationship of ethnicity and acculturation factors with regards to the coping strategies used by caregivers has not been extensively explored. The current study included participants from the Palo Alto site of the Resources for Enhancing Alzheimer's Caregiver Health (REACH) project. The study examined differences in coping strategies between 140 non-Hispanic White, 45 less acculturated Latina, and 61 more acculturated Latina caregivers. Univariate and Multivariate Analysis of Variance, as well as post hoc analyses, were conducted to determine the differences among the three groups. Results indicated less acculturated Latina caregivers employ more avoidant coping strategies compared to non-Hispanic White caregivers. However, no differences were found among the other groups in their use of avoidance coping. Moreover, there were no differences found in the use of social support seeking, count your blessings, problem focused, and blaming others coping among the three groups. These findings have important implications for the design of culturally relevant psychoeducational and therapeutic interventions aimed towards meeting the individual needs of these three populations. In addition, the findings expand on the understanding of maladaptive coping strategies that may be potentially exacerbating caregiver distress among Latina caregivers.
ContributorsFelix, Vitae (Author) / Arciniega, Guillermo M (Thesis advisor) / Robinson-Kurpius, Sharon (Committee member) / Coon, David W. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The current study explored whether intrinsically religious individuals are able to separate the "sin" from the "sinner" (i.e., separate category membership from behavior) when judging homosexual individuals, or whether they are instead subject to the negativity bias (judgments based solely on category membership) in moral judgments. All effects were expected to occur only for participants high in homophobia. Participants were 305 undergraduate male and female students at a large, public university in the southwestern U.S. Respondents read one of five scenarios that described gay or straight targets who were celibate or engaged in same or opposite sex relationships, then were asked to respond to a series of questions evaluating attitudes and behavioral intentions toward the target. Results revealed that homophobia led to a negativity bias in judgments of gay targets, which was intensified by intrinsic religiosity. However, individuals high on intrinsic religiosity and high on homophobia also differentiated between gay targets based on sexual behavior, such that gay targets who were celibate or in an opposite-sex relationship were rated more favorably than gay targets in a same-sex relationship. These findings demonstrate that the negativity bias and "sin vs. sinner" differentiation may both be occurring for intrinsically religious individuals. The moderating effect of homophobia on the interaction between intrinsic religiosity and judgments of gay and straight targets shows us that religiosity itself is not inherently tolerant or intolerant.
ContributorsFilip-Crawford, Gabrielle (Author) / Nagoshi, Craig T. (Thesis advisor) / Kwan, Virginia S.Y. (Committee member) / Neuberg, Steven L. (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
The purpose of this study was to investigate the effect of partial exemplar experience on category formation and use. Participants had either complete or limited access to the three dimensions that defined categories by dimensions within different modalities. The concept of "crucial dimension" was introduced and the role it plays in category definition was explained. It was hypothesized that the effects of partial experience are not explained by a shifting of attention between dimensions (Taylor & Ross, 2009) but rather by an increased reliance on prototypical values used to fill in missing information during incomplete experiences. Results indicated that participants (1) do not fill in missing information with prototypical values, (2) integrate information less efficiently between different modalities than within a single modality, and (3) have difficulty learning only when partial experience prevents access to diagnostic information.
ContributorsCrawford, Thomas (Author) / Homa, Donald (Thesis advisor) / Mcbeath, Micheal (Committee member) / Glenberg, Arthur (Committee member) / Arizona State University (Publisher)
Created2011
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
Few measurement tools provide reliable, valid data on both children's emotional and behavioral engagement in school. The School Liking and Avoidance Questionnaire (SLAQ) is one such self-report measure developed to evaluate a child's degree of engagement in the school setting as it is manifest in a child's school liking and school avoidance. This study evaluated the SLAQ's dimensionality, reliability, and validity. Data were gathered on children from kindergarten through 6th grade (n=396). Participants reported on their school liking and avoidance in the spring of each school year. Scores consistently represented two distinct, yet related subscales (i.e., school liking and school avoidance) that were reliable and stable over time. Validation analyses provided some corroboration of the construct validity of the SLAQ subscales, but evidence of predictive validity was inconsistent with the hypothesized relations (i.e., early report of school liking and school avoidance did not predict later achievement outcomes). In sum, the findings from this study provide some support for the dimensionality, reliability, and validity of the SLAQ and suggest that it can be used for the assessment of young children's behavioral and emotional engagement in school.
ContributorsSmith, Jillian (Author) / Ladd, Gary W. (Thesis advisor) / Ladd, Becky (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2011
Description
Psychology of justice research has demonstrated that individuals are concerned with both the process and the outcomes of a decision-making event. While the literature has demonstrated the importance of formal and informal aspects of procedural justice and the relevancy of moral values, the present study focuses on introducing a new form of justice: Substantive justice. Substantive justice focuses on how the legal system uses laws to constrain and direct human behavior, specifically focusing on the function and the structure of a law. The psychology of justice literature is missing the vital distinction between laws whose function is to create social opportunities versus threats and between laws structured concretely versus abstractly. In the present experiment, we found that participant evaluations of the fairness of the law, the outcome, and the decision-maker all varied depending on the function and structure of the law used as well as the outcome produced. Specifically, when considering adverse outcomes, individuals perceived laws whose function is to create liability (threats) as being fairer when structured as standards (abstract guidelines) rather than rules (concrete guidelines); however, the opposite is true when considering laws whose function is to create eligibility (opportunities). In juxtaposition, when receiving a favorable outcome, individuals perceived laws whose function is to create liability (threats) as being fairer when defined as rules (concrete guidelines) rather than standards (abstract guidelines).
ContributorsLovis-McMahon, David (Author) / Schweitzer, Nicholas J. (Thesis advisor) / Saks, Michael (Thesis advisor) / Kwan, Sau (Committee member) / Arizona State University (Publisher)
Created2011
Description
Separation from a loved one is a highly stressful event. The range and intensity of emotions accompanying such a separation arguably are amplified when one's spouse deploys. This thesis examines at-home spouses (AHSs) of deployed military and how emotion, marital satisfaction, and communication are impacted throughout the deployment cycle. Additionally, I explore technology as a possible coping mechanism to help AHSs adapt and overcome stressfulness of deployment. One hundred sixty-six married females with a partner currently deployed, anticipating deployment, or recently returned from deployment completed an on-line survey. It was predicted AHSs would experience specific emotions during each phase, categorized as "anticipatory," (e.g., anger, worry) "absence" (e.g., lonely, sad) or "post" (e.g., happiness, relief); marital satisfaction also was predicted to be higher among spouses whose partner recently returned from deployment versus was deployed or anticipating deployment. Data showed AHSs whose partner was anticipating or currently deployed reported more "anticipatory" and "absence" emotions than AHSs with a recently returned partner. The former two groups did not differ in these emotions. AHSs with a recently returned partner reported more "post" emotions than the other two groups. Marital satisfaction did not differ based on deployment status. It was also predicted that among AHSs with a currently deployed partner, less negative emotion upon deployment would be associated with more frequent communication during deployment. Data showed AHSs who reported less negative emotion upon deployment engaged in more frequent communication with their deployed partner. Lastly, I predicted AHSs whose partners are currently deployed and who prefer modes of communication allowing direct contact (e.g., Skype) will experience less negative emotions than AHSs who prefer indirect contact (e.g., e-mail). Data showed reports of negative emotion did not differ based on preference for direct versus indirect communication. Therefore, negative emotions may develop and persist before and during deployment, but when the partner returns home, spouses do experience a rebound of positive emotions. Additionally, emotions at the time of deployment may be useful in predicting spouses' communication frequency during deployment. Findings aim to provide knowledge of family life during separation and explore technology as a possible coping mechanism for AHSs.
ContributorsPowell, Katrina D (Author) / Roberts, Nicole A. (Thesis advisor) / Burleson, Mary H. (Committee member) / Hall, Deborah (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011