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Description
The purpose of the current study was to use structural equation modeling-based quantitative genetic models to characterize latent genetic and environmental influences on proneness to three discrete negative emotions in middle childhood, according to mother-report, father-report and in-home observation. One primary aim was to test the extent to which covariance among the three emotions could be accounted for by a single, common genetically- and environmentally-influenced negative emotionality factor. A second aim was to examine the extent to which different reporters appeared to be tapping into the same genetically- and environmentally-influenced aspects of each emotion. According to mother- and father-report, moderate to high genetic influences were evident for all emotions, with mother- and father-report of fear and father-report of anger showing the highest heritability. Significant common environmental influences were also found for mother-report of anger and sadness in both univariate and multivariate models. For observed emotion, anger was moderately heritable with no evidence for common environmental variance, but sadness, object fear and social fear all showed modest to moderate common environmental influences and no significant genetic variance. In addition, cholesky decompositions examining genetic and environmental influences across reporter suggested that despite considerable overlap between mother-report and father-report, there was also reporter-specific variance on anger, sadness, and fear. Specifically, there were significant common environmental influences on mother-report of anger- and sadness that were not shared with father-report, and genetic influences on father-report of sadness and fear that were not shared with mother-report. In-home observations were not highly correlated enough with parent-report to support multivariate analysis for any emotion. Finally, according to both mother- and father-report, a single set of genetic and environmental influences was sufficient to account for covariance among all three negative emotions. However, fear was primarily explained by genetic influences not shared with other emotions, and anger also showed considerable emotion-specific genetic variance. In both cases, findings support the value of a more emotion-specific approach to temperament, and highlight the need to consider distinctions as well as commonalities across emotions, reporters and situations.
ContributorsClifford, Sierra (Author) / Lemery, Kathryn (Thesis advisor) / Shiota, Michelle (Committee member) / Eisenberg, Nancy (Committee member) / Arizona State University (Publisher)
Created2013
Description
Parallel Monte Carlo applications require the pseudorandom numbers used on each processor to be independent in a probabilistic sense. The TestU01 software package is the standard testing suite for detecting stream dependence and other properties that make certain pseudorandom generators ineffective in parallel (as well as serial) settings. TestU01 employs two basic schemes for testing parallel generated streams. The first applies serial tests to the individual streams and then tests the resulting P-values for uniformity. The second turns all the parallel generated streams into one long vector and then applies serial tests to the resulting concatenated stream. Various forms of stream dependence can be missed by each approach because neither one fully addresses the multivariate nature of the accumulated data when generators are run in parallel. This dissertation identifies these potential faults in the parallel testing methodologies of TestU01 and investigates two different methods to better detect inter-stream dependencies: correlation motivated multivariate tests and vector time series based tests. These methods have been implemented in an extension to TestU01 built in C++ and the unique aspects of this extension are discussed. A variety of different generation scenarios are then examined using the TestU01 suite in concert with the extension. This enhanced software package is found to better detect certain forms of inter-stream dependencies than the original TestU01 suites of tests.
ContributorsIsmay, Chester (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Kao, Ming-Hung (Committee member) / Lanchier, Nicolas (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation of a software solution which can be used in the academia and industry for research in cyber physical systems related applications. The major features of the project are: creating a modular system for motion planning, use of Robot Operating System (ROS), use of triangulation for environment decomposition and using stargazer sensor for localization. The project is built on an open source software called ROS which provides an environment where it is very easy to integrate different modules be it software or hardware on a Linux based platform. Use of ROS implies the project or its modules can be adapted quickly for different applications as the need arises. The final software package created and tested takes a data file as its input which contains the LTL specifications, a symbols list used in the LTL and finally the environment polygon data containing real world coordinates for all polygons and also information on neighbors and parents of each polygon. The software package successfully ran the experiment of coverage, reachability with avoidance and sequencing.
ContributorsPandya, Parth (Author) / Fainekos, Georgios (Thesis advisor) / Dasgupta, Partha (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2013
Description
Culture informs ideas about healthy and acceptable body types. Through globalization the U.S.-European body model has become increasingly significant in local contexts, influencing local body models. While Puerto Ricans have historically valued plump bodies - a biocultural legacy of a historically food scarce environment - this dissertation investigated shifts in these ideals across generations to a stronger preference for thinness. A sample of 23 intergenerational family triads of women, and one close male relative or friend per woman, were administered quantitative questionnaires. Ethnographic interviews were conducted with a sub-sample of women from 16 triads and 1 quintet. Questions about weight history and body sizes were used to address cultural changes in body models. Findings indicate the general trend for all generations has been a reduction in the spectrum of acceptable bodies to an almost singular idealized thin body. Female weight gain during puberty and influence of media produced varied responses across age groups. Overall, Puerto Ricans find it acceptable to gain weight with ageing, during a divorce, and postpartum. Thin bodies are associated with beauty and health, but healthy women that do not resemble the thin ideal, submit themselves to dangerous weight loss practices to achieve self and social acceptance. Further research and direct interventions need to be conducted to alter perceptions that conflate beauty with health in order to address the `normative discontent' women of all ages experience. Weight discrimination and concern with being overweight were evident in Puerto Rican everyday life, indicated by the role of media and acculturation in this study. Anti-fat attitudes were stronger for individuals that identified closely with United States culture. Exposure to drama and personal transformation television programs are associated with increased body image dissatisfaction, and increased exposure to variety shows and celebrity news shows is associated with increased anti-fat attitudes and body dissatisfaction. In sum, the positive valuation of fat in the Puerto Rican cultural body size model in the 1970s has shifted toward a negative valuation of fat and a preference for thin body size.
ContributorsRodriguez-Soto, Isa (Author) / Maupin, Jonathan (Thesis advisor) / Wutich, Amber (Committee member) / Walters-Pacheco, Kattia (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation explores the role of smart home service provisions (SHSP) as motivational agents supporting goal attainment and human flourishing. Evoking human flourishing as a lens for interaction encapsulates issues of wellbeing, adaptation and problem solving within the context of social interaction. To investigate this line of research a new, motivation-sensitive approach to design was implemented. This approach combined psychometric analysis from motivational psychology's Personal Project Analysis (PPA) and Place Attachment theory's Sense of Place (SoP) analysis to produce project-centered motivational models for environmental congruence. Regression analysis of surveys collected from 150 (n = 150) young adults about their homes revealed PPA motivational dimensions had significant main affects on all three SoP factors. Model one indicated PPA dimensions Fearful and Value Congruency predicted the SoP factor Place Attachment (p = 0.012). Model two indicated the PPA factor Positive Affect and PPA dimensions Value Congruency, Self Identity and Autonomy predicted Place Identity (p = .0003). Model three indicated PPA dimensions Difficulty and Likelihood of Success predicted the SoP factor Place Dependency. The relationships between motivational PPA dimensions and SoP demonstrated in these models informed creation of a set of motivational design heuristics. These heuristics guided 20 participants (n = 20) through co-design of paper prototypes of SHSPs supporting goal attainment and human flourishing. Normative analysis of these paper prototypes fashioned a design framework consisting of the use cases "make with me", "keep me on task" and "improve myself"; the four design principles "time and timing", "guidance and accountability", "project ambiguity" and "positivity mechanisms"; and the seven interaction models "structuring time", "prompt user", "gather resources", "consume content", "create content", "restrict and/or restore access to content" and "share content". This design framework described and evaluated three technology probes installed in the homes of three participants (n = 3) for field-testing over the course of one week. A priori and post priori samples of psychometric measures were inconclusive in determining if SHSP motivated goal attainment or increased environmental congruency between young adults and their homes.
ContributorsBrotman, Ryan Scott (Author) / Burleson, Winsow (Thesis advisor) / Heywood, William (Committee member) / Forlizzi, Jodi (Committee member) / Arizona State University (Publisher)
Created2013
Description
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2013
Description
Despite significant advances in digital pathology and automation sciences, current diagnostic practice for cancer detection primarily relies on a qualitative manual inspection of tissue architecture and cell and nuclear morphology in stained biopsies using low-magnification, two-dimensional (2D) brightfield microscopy. The efficacy of this process is limited by inter-operator variations in sample preparation and imaging, and by inter-observer variability in assessment. Over the past few decades, the predictive value quantitative morphology measurements derived from computerized analysis of micrographs has been compromised by the inability of 2D microscopy to capture information in the third dimension, and by the anisotropic spatial resolution inherent to conventional microscopy techniques that generate volumetric images by stacking 2D optical sections to approximate 3D. To gain insight into the analytical 3D nature of cells, this dissertation explores the application of a new technology for single-cell optical computed tomography (optical cell CT) that is a promising 3D tomographic imaging technique which uses visible light absorption to image stained cells individually with sub-micron, isotropic spatial resolution. This dissertation provides a scalable analytical framework to perform fully-automated 3D morphological analysis from transmission-mode optical cell CT images of hematoxylin-stained cells. The developed framework performs rapid and accurate quantification of 3D cell and nuclear morphology, facilitates assessment of morphological heterogeneity, and generates shape- and texture-based biosignatures predictive of the cell state. Custom 3D image segmentation methods were developed to precisely delineate volumes of interest (VOIs) from reconstructed cell images. Comparison with user-defined ground truth assessments yielded an average agreement (DICE coefficient) of 94% for the cell and its nucleus. Seventy nine biologically relevant morphological descriptors (features) were computed from the segmented VOIs, and statistical classification methods were implemented to determine the subset of features that best predicted cell health. The efficacy of our proposed framework was demonstrated on an in vitro model of multistep carcinogenesis in human Barrett's esophagus (BE) and classifier performance using our 3D morphometric analysis was compared against computerized analysis of 2D image slices that reflected conventional cytological observation. Our results enable sensitive and specific nuclear grade classification for early cancer diagnosis and underline the value of the approach as an objective adjunctive tool to better understand morphological changes associated with malignant transformation.
ContributorsNandakumar, Vivek (Author) / Meldrum, Deirdre R (Thesis advisor) / Nelson, Alan C. (Committee member) / Karam, Lina J (Committee member) / Ye, Jieping (Committee member) / Johnson, Roger H (Committee member) / Bussey, Kimberly J (Committee member) / Arizona State University (Publisher)
Created2013
Description
We solve the problem of activity verification in the context of sustainability. Activity verification is the process of proving the user assertions pertaining to a certain activity performed by the user. Our motivation lies in incentivizing the user for engaging in sustainable activities like taking public transport or recycling. Such incentivization schemes require the system to verify the claim made by the user. The system verifies these claims by analyzing the supporting evidence captured by the user while performing the activity. The proliferation of portable smart-phones in the past few years has provided us with a ubiquitous and relatively cheap platform, having multiple sensors like accelerometer, gyroscope, microphone etc. to capture this evidence data in-situ. In this research, we investigate the supervised and semi-supervised learning techniques for activity verification. Both these techniques make use the data set constructed using the evidence submitted by the user. Supervised learning makes use of annotated evidence data to build a function to predict the class labels of the unlabeled data points. The evidence data captured can be either unimodal or multimodal in nature. We use the accelerometer data as evidence for transportation mode verification and image data as evidence for recycling verification. After training the system, we achieve maximum accuracy of 94% when classifying the transport mode and 81% when detecting recycle activity. In the case of recycle verification, we could improve the classification accuracy by asking the user for more evidence. We present some techniques to ask the user for the next best piece of evidence that maximizes the probability of classification. Using these techniques for detecting recycle activity, the accuracy increases to 93%. The major disadvantage of using supervised models is that it requires extensive annotated training data, which expensive to collect. Due to the limited training data, we look at the graph based inductive semi-supervised learning methods to propagate the labels among the unlabeled samples. In the semi-supervised approach, we represent each instance in the data set as a node in the graph. Since it is a complete graph, edges interconnect these nodes, with each edge having some weight representing the similarity between the points. We propagate the labels in this graph, based on the proximity of the data points to the labeled nodes. We estimate the performance of these algorithms by measuring how close the probability distribution of the data after label propagation is to the probability distribution of the ground truth data. Since labeling has a cost associated with it, in this thesis we propose two algorithms that help us in selecting minimum number of labeled points to propagate the labels accurately. Our proposed algorithm achieves a maximum of 73% increase in performance when compared to the baseline algorithm.
ContributorsDesai, Vaishnav (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (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
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
ContributorsMeng, Yunsong (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Fainekos, Georgios (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2013