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- Creators: College of Liberal Arts and Sciences
ContributorsSoto-Berelov, Mariela (Author) / Fall, Patricia L. (Author) / Barton, C. Michael (Author) / Falconer, Steven E. (Author) / Sarjoughian, Hessam S. (Author) / Arrowsmith, J. Ramon (Author)
Created2007
Description
Internet sites that support user-generated content, so-called Web 2.0, have become part of the fabric of everyday life in technologically advanced nations. Users collectively spend billions of hours consuming and creating content on social networking sites, weblogs (blogs), and various other types of sites in the United States and around the world. Given the fundamentally emotional nature of humans and the amount of emotional content that appears in Web 2.0 content, it is important to understand how such websites can affect the emotions of users. This work attempts to determine whether emotion spreads through an online social network (OSN). To this end, a method is devised that employs a model based on a general threshold diffusion model as a classifier to predict the propagation of emotion between users and their friends in an OSN by way of mood-labeled blog entries. The model generalizes existing information diffusion models in that the state machine representation of a node is generalized from being binary to having n-states in order to support n class labels necessary to model emotional contagion. In the absence of ground truth, the prediction accuracy of the model is benchmarked with a baseline method that predicts the majority label of a user's emotion label distribution. The model significantly outperforms the baseline method in terms of prediction accuracy. The experimental results make a strong case for the existence of emotional contagion in OSNs in spite of possible alternative arguments such confounding influence and homophily, since these alternatives are likely to have negligible effect in a large dataset or simply do not apply to the domain of human emotions. A hybrid manual/automated method to map mood-labeled blog entries to a set of emotion labels is also presented, which enables the application of the model to a large set (approximately 900K) of blog entries from LiveJournal.
ContributorsCole, William David, M.S (Author) / Liu, Huan (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Candan, Kasim S (Committee member) / Arizona State University (Publisher)
Created2011
Description
Free/Libre Open Source Software (FLOSS) is the product of volunteers collaborating to build software in an open, public manner. The large number of FLOSS projects, combined with the data that is inherently archived with this online process, make studying this phenomenon attractive. Some FLOSS projects are very functional, well-known, and successful, such as Linux, the Apache Web Server, and Firefox. However, for every successful FLOSS project there are 100's of projects that are unsuccessful. These projects fail to attract sufficient interest from developers and users and become inactive or abandoned before useful functionality is achieved. The goal of this research is to better understand the open source development process and gain insight into why some FLOSS projects succeed while others fail. This dissertation presents an agent-based model of the FLOSS development process. The model is built around the concept that projects must manage to attract contributions from a limited pool of participants in order to progress. In the model developer and user agents select from a landscape of competing FLOSS projects based on perceived utility. Via the selections that are made and subsequent contributions, some projects are propelled to success while others remain stagnant and inactive. Findings from a diverse set of empirical studies of FLOSS projects are used to formulate the model, which is then calibrated on empirical data from multiple sources of public FLOSS data. The model is able to reproduce key characteristics observed in the FLOSS domain and is capable of making accurate predictions. The model is used to gain a better understanding of the FLOSS development process, including what it means for FLOSS projects to be successful and what conditions increase the probability of project success. It is shown that FLOSS is a producer-driven process, and project factors that are important for developers selecting projects are identified. In addition, it is shown that projects are sensitive to when core developers make contributions, and the exhibited bandwagon effects mean that some projects will be successful regardless of competing projects. Recommendations for improving software engineering in general based on the positive characteristics of FLOSS are also presented.
ContributorsRadtke, Nicholas Patrick (Author) / Collofello, James S. (Thesis advisor) / Janssen, Marco A (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Sundaram, Hari (Committee member) / Arizona State University (Publisher)
Created2011
Description
Meteorology is an uncommon term rarely resonating through elementary classrooms. However, it is a concept found in both fourth and sixth grade Arizona science standards. As issues involving the environment are becoming more pertinent, it is important to study and understand atmospheric processes along with fulfilling the standards for each grade level. This thesis project teaches the practical skills of weather map reading and weather forecasting through the creation and execution of an after school lesson with the aide of seven teen assistants.
ContributorsChoulet, Shayna (Author) / Walters, Debra (Thesis director) / Oliver, Jill (Committee member) / Balling, Robert (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
Description
Plants are essential to human life. They release oxygen into the atmosphere for us to breathe. They also provide shelter, medicine, clothing, tools, and food. For many people, the food that is on their tables and in their supermarkets isn't given much thought. Where did it come from? What part of the plant is it? How does it relate to others in the plant kingdom? How do other cultures use this plant? The most many of us know about them is that they are at the supermarket when we need them for dinner (Nabhan, 2009) (Vileisis, 2008).
ContributorsBarron, Kara (Author) / Landrum, Leslie (Thesis director) / Swanson, Tod (Committee member) / Pigg, Kathleen (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
DescriptionBased on previous research and findings it is proven that a non-profit class to create awareness will be beneficial in the prevention of eating disorders. This analysis will provide significant research to defend the proposed class.
ContributorsAllen, Brittany (Author) / Chung, Deborah (Author) / Fey, Richard (Thesis director) / Peck, Sidnee (Committee member) / Mazurkiewicz, Milena (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
Description
Restraint stress is the most commonly used laboratory stressor. It is difficult to characterize as psychological or physical, because past studies show psychological features, but the nature of confinement adds a physical dimension. This was the first study to investigate how experience with restraint stress affects brain response to the next stress without a physical burden. Pair-housed adult male rats were transported to a novel context and restrained or left undisturbed (6hr). The next day, rats were returned to the same context and were either restrained or left undisturbed in the context (n=8/group). After 90min, rats were euthanized to determine functional activation in limbic structures using Fos immunohistochemistry and to measure HPA axis reactivity through blood serum corticosterone levels. Regardless of day 1 experience, context exposure on day 2 enhanced Fos expression in CA1 and CA3 of the hippocampus, basolateral amygdala, and central amygdala. Conversely, other regions and corticosterone levels demonstrated modulation from the previous day's experience. Specifically, rats that were placed back into the restraint context but not restrained on day 2 showed enhanced Fos expression in the dentate gyrus suprapyramidal blade (DGSup), and infralimbic cortex (IL). Also Fos expression was attenuated in rats that received two restraint exposures in the IL and medial amygdala (MEA), suggesting habituation. Only the DG infrapyramidal blade (DGInf) showed enhanced Fos expression to restraint on day 2 without influence of the previous day. While context predominately directed Fos activation, prior experience with restraint influenced Fos expression in the DGSup, IL, MEA and corticosterone levels to support restraint having psychological components.
ContributorsAnouti, P. Danya (Author) / Conrad, D. Cheryl (Thesis director) / Hammer, Ronald (Committee member) / Hoffman, N. Ann (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
Description
Purpose: To examine: (1) whether Non-Hispanic Blacks (NHB) and Non-Hispanic Whites (NHW) with diagnosed arthritis differed in self-reported physical activity (PA) levels, (2) if NHB and NHW with arthritis differed on potential correlates of PA based on the Social Ecological Model (Mcleroy et al., 1988), and (3) if PA participation varied by race/ethnicity after controlling for age, gender, education, and BMI. Methods: This study was a secondary data analysis of data collected from 2006-2008 in Chicago, IL as part of the Midwest Roybal Center for Health Promotion. Bivariate analyses were used to assess potential differences between race in meeting either ACR or ACSM PA guidelines. Comparisons by race between potential socio-demographic correlates and meeting physical activity guidelines were assessed using Chi-squares. Potential differences by race in psychosocial, arthritis, and health-related and environmental correlates were assessed using T-tests. Finally, logistic regression analyses were used to examine if race was still associated with PA after controlling for socio-demographic characteristics. Results: A greater proportion of NHW (68.1% and 35.3%) than NHB (46.5% and 20.9%) met both the arthritis-specific and the American College of Sports Medicine (ACSM) recommendations for physical activity, respectively. NHB had significantly lower self-efficacy for exercise and reported greater impairments in physical function compared to NHW. Likewise, NHB reported more crime and less aesthetics within their neighborhood. NHW were 2.56 times more likely to meet arthritis-specific PA guidelines than NHB after controlling for age, gender, education, marital status, and BMI. In contrast, after controlling for sociodemographic characteristics, age and gender were the only significant predictors of meeting ACSM PA guidelines. Discussion: There were significant differences between NHB and NHW individuals with arthritis in meeting PA guidelines. After controlling for age, gender, education, and BMI non-Hispanic White individuals were still significantly more likely to meet PA guidelines. Interventions aimed at promoting higher levels of physical activity among individuals with arthritis need to consider neighborhood aesthetics and crime when designing programs. More arthritis-specific programs are needed in close proximity to neighborhoods in an effort to promote physical activity.
ContributorsChuran, Christopher (Author) / Der Ananian, Cheryl (Thesis advisor) / Adams, Marc (Committee member) / Campbell, Kathryn (Committee member) / Arizona State University (Publisher)
Created2013
Description
A semiconductor supply chain modeling and simulation platform using Linear Program (LP) optimization and parallel Discrete Event System Specification (DEVS) process models has been developed in a joint effort by ASU and Intel Corporation. A Knowledge Interchange Broker (KIBDEVS/LP) was developed to broker information synchronously between the DEVS and LP models. Recently a single-echelon heuristic Inventory Strategy Module (ISM) was added to correct for forecast bias in customer demand data using different smoothing techniques. The optimization model could then use information provided by the forecast model to make better decisions for the process model. The composition of ISM with LP and DEVS models resulted in the first realization of what is now called the Optimization Simulation Forecast (OSF) platform. It could handle a single echelon supply chain system consisting of single hubs and single products In this thesis, this single-echelon simulation platform is extended to handle multiple echelons with multiple inventory elements handling multiple products. The main aspect for the multi-echelon OSF platform was to extend the KIBDEVS/LP such that ISM interactions with the LP and DEVS models could also be supported. To achieve this, a new, scalable XML schema for the KIB has been developed. The XML schema has also resulted in strengthening the KIB execution engine design. A sequential scheme controls the executions of the DEVS-Suite simulator, CPLEX optimizer, and ISM engine. To use the ISM for multiple echelons, it is extended to compute forecast customer demands and safety stocks over multiple hubs and products. Basic examples for semiconductor manufacturing spanning single and two echelon supply chain systems have been developed and analyzed. Experiments using perfect data were conducted to show the correctness of the OSF platform design and implementation. Simple, but realistic experiments have also been conducted. They highlight the kinds of supply chain dynamics that can be evaluated using discrete event process simulation, linear programming optimization, and heuristics forecasting models.
ContributorsSmith, James Melkon (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Davulcu, Hasan (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2012
Description
The complexity of the systems that software engineers build has continuously grown since the inception of the field. What has not changed is the engineers' mental capacity to operate on about seven distinct pieces of information at a time. The widespread use of UML has led to more abstract software design activities, however the same cannot be said for reverse engineering activities. The introduction of abstraction to reverse engineering will allow the engineer to move farther away from the details of the system, increasing his ability to see the role that domain level concepts play in the system. In this thesis, we present a technique that facilitates filtering of classes from existing systems at the source level based on their relationship to concepts in the domain via a classification method using machine learning. We showed that concepts can be identified using a machine learning classifier based on source level metrics. We developed an Eclipse plugin to assist with the process of manually classifying Java source code, and collecting metrics and classifications into a standard file format. We developed an Eclipse plugin to act as a concept identifier that visually indicates a class as a domain concept or not. We minimized the size of training sets to ensure a useful approach in practice. This allowed us to determine that a training set of 7:5 to 10% is nearly as effective as a training set representing 50% of the system. We showed that random selection is the most consistent and effective means of selecting a training set. We found that KNN is the most consistent performer among the learning algorithms tested. We determined the optimal feature set for this classification problem. We discussed two possible structures besides a one to one mapping of domain knowledge to implementation. We showed that classes representing more than one concept are simply concepts at differing levels of abstraction. We also discussed composite concepts representing a domain concept implemented by more than one class. We showed that these composite concepts are difficult to detect because the problem is NP-complete.
ContributorsCarey, Maurice (Author) / Colbourn, Charles (Thesis advisor) / Collofello, James (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013