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- Creators: Beethoven, Ludwig van, 1770-1827
Description
Transformation Is... is an arts practice-led research in Dance and Design, embodying and materializing concepts of structure, leadership and agency and their role in bringing about desired social transformation. My personal experiences as a foreign student interested in transformative experiences gave origin to this arts practice-led research. An auto-ethnographic approach informed by grounded theory methods shaped this creative inquiry in which dance was looked at as data and rehearsals became research fields. Within the context of social choreography, a transformational leadership style was applied to promote agency using improvisational movement scores to shape individual and collective creative explorations. These explorations gave birth to a flexible and transformable dance installation that served as a metaphor for social structure. Transformation revealed itself in this research as a sequence of process and product oriented stages that resulted in a final performance piece in which a site-specific interactive installation was built before the audience's eyes. This work became a metaphor of how individual actions and interactions effect the construction of social reality and how inner-transformation and collaboration are key in the process of designing and building new egalitarian social structures.
ContributorsSibauste Bermudez, Janelle (Author) / Kaplan, Robert (Thesis advisor) / Britt, Melissa (Committee member) / Standley, Eileen (Committee member) / Arizona State University (Publisher)
Created2014
Description
Although many studies have looked into the benefits and consequences of consuming breakfast, most have not looked into the unintended consequences of breakfast being served at school; specifically the consumption of an additional breakfast. This cross-sectional study investigated the prevalence and health related outcomes of the consumption of an additional breakfast at school amongst youth using a survey assessing possible predictors (i.e. parental education, morning activities, race), the ASA-kids 24-hr dietary recall, and height and weight measurements. A total of fifty-eight participants (aged 13.5±1.6 years; 55.2% male) were recruited at after school library programs and Boys and Girls Clubs in the Phoenix, Arizona Metro Area during 2014. The main outcomes measured were BMI percentile, total calories, iron, sodium, carbohydrates, added sugar, and fiber. In the study, the prevalence of consumption of an additional breakfast at school at least once a week or more was 32.7%. There were no significant differences between the consumption of an additional breakfast and not an additional breakfast amongst the main outcomes measures. The directionality of the relationship between the consumption of an additional breakfast and overweight/obesity amongst youth was inverse (OR = 0.309; p-value = 0.121), but this was not significant. This study found that the consumption of an additional breakfast at school is not contributing to overweight/obesity in youth, nor does it alter overall caloric and nutrient intake. School breakfast programs are important for providing breakfast and key nutrients to youth.
ContributorsSimpson, Julie (Author) / Bruening, Meg (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Rider, Linda (Committee member) / Arizona State University (Publisher)
Created2015
Description
Time-series plots are used in many scientific and engineering applications. In this thesis, two new plug-ins for piecewise constant and event time-series are developed within the Eclipse BIRT (Business Intelligence and Reporting Tools) framework. These customizable plug-ins support superdense time, which is required for plotting the dynamics of Parallel DEVS models. These plug-ins are designed to receive time-based alphanumerical data sets from external computing sources, which can then be dynamically plotted. Static and dynamic time-series plotting are demonstrated in two settings. First, as standalone plug-ins, they can be used to create static plots, which can then be included in BIRT reports. Second, the plug-ins are integrated into the DEVS-Suite simulator where runtime simulated data generated from model components are dynamically plotted. Visual representation of data sets can simplify and improve model verification and simulation validation.
ContributorsSundaramoorthi, Savitha (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Maciejewski, Ross (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2015
Description
"Linked Together" is a choreographic piece inspired by at-risk youth and their ability to learn, grow, and transform their lives through dance. The idea for the piece originated from dance programs implemented with under-resourced populations in Virginia, Panama, and India. My teaching experiences in these places sparked the development of a longer, more comprehensive dance program in Arizona, with a Boys and Girls Club. The Arizona dance program included specific somatics exercises, focused on the integration of mind and body, as well as other types of improvisations, to help the participants learn about movement concepts and develop original movement.
The title "Linked Together" suggests that all people are connected in many ways, regardless of personal differences such as socioeconomic status or language. The dancers included myself, Arizona State University (ASU) dance students, as well as Boys and Girls Club dance program participants. For the concert, all dancers portrayed stories and concepts related to empowerment through emotionally charged movement, and thereby provided audience members with a visceral lens through which to see the transformative powers of dance. The data collected from this project through observations, surveys, and interviews suggest that constructive behaviors that are internalized through dance can flow seamlessly into the non-dance world, encouraging people to think creatively, collaborate with others, gain a sense of ownership, and feel empowered in all parts of life.
The title "Linked Together" suggests that all people are connected in many ways, regardless of personal differences such as socioeconomic status or language. The dancers included myself, Arizona State University (ASU) dance students, as well as Boys and Girls Club dance program participants. For the concert, all dancers portrayed stories and concepts related to empowerment through emotionally charged movement, and thereby provided audience members with a visceral lens through which to see the transformative powers of dance. The data collected from this project through observations, surveys, and interviews suggest that constructive behaviors that are internalized through dance can flow seamlessly into the non-dance world, encouraging people to think creatively, collaborate with others, gain a sense of ownership, and feel empowered in all parts of life.
ContributorsDaniel, Chareka (Author) / Fitzgerald, Mary (Thesis advisor) / Britt, Melissa (Committee member) / Manning, Linda (Committee member) / Arizona State University (Publisher)
Created2015
Description
A new algebraic system, Test Algebra (TA), is proposed for identifying faults in combinatorial testing for SaaS (Software-as-a-Service) applications. In the context of cloud computing, SaaS is a new software delivery model, in which mission-critical applications are composed, deployed, and executed on cloud platforms. Testing SaaS applications is challenging because new applications need to be tested once they are composed, and prior to their deployment. A composition of components providing services yields a configuration providing a SaaS application. While individual components
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
in the configuration may have been thoroughly tested, faults still arise due to interactions among the components composed, making the configuration faulty. When there are k components, combinatorial testing algorithms can be used to identify faulty interactions for t or fewer components, for some threshold 2 <= t <= k on the size of interactions considered. In general these methods do not identify specific faults, but rather indicate the presence or absence of some fault. To identify specific faults, an adaptive testing regime repeatedly constructs and tests configurations in order to determine, for each interaction of interest, whether it is faulty or not. In order to perform such testing in a loosely coupled distributed environment such as
the cloud, it is imperative that testing results can be combined from many different servers. The TA defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. The results, using the TA, remain the same.
ContributorsQi, Guanqiu (Author) / Tsai, Wei-Tek (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarjoughian, Hessam S. (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
While obesity rates have plateaued within the last decade,
two-thirds of the United States
population is currently classified as overweight (defined a
s a body mass index [BMI] of
25-29.9 kg/m²) or obese (a BMI greater than 30 kg/m²). Bariatric
surgical interventions
are not only more effective than behavioral treatments
in the short term but are the only
form of obesity intervention with evidence of consisten
t long-term effectiveness.
However, even among bariatric surgery patients, weight
loss often stabilizes and it is
estimated that more than 20% of bariatric surgery patient
s will regain a significant
amount of weight that was initially lost long-term. Li
ttle research to date has been
conducted on physical activity in post bariatric surgery pati
ents. More specifically, there
have been no studies to date examining the effects of Me
ditative Movement (MM)
programs on body composition in bariatric patients. A s
tudy using an 8-week Tai Chi
Easy program was conducted in female gastric bypass patient
s to explore feasibility of
MM in the bariatric population as well as pre- and post-in
tervention changes in weight,
mindfulness, eating behaviors, body awareness, physical a
ctivity patterns, dietary quality
and mood. Data analysis revealed that there were no s
ignificant changes in weight or
physical activity patterns; however, significant changes w
ere observed in anxiety, overall
body awareness and cognitive restraint in eating. Addit
ionally, a significant decrease in
processed meat consumption and a weak trend towards increa
sed consumption of fruits
may suggest an overall improvement in dietary quality.
two-thirds of the United States
population is currently classified as overweight (defined a
s a body mass index [BMI] of
25-29.9 kg/m²) or obese (a BMI greater than 30 kg/m²). Bariatric
surgical interventions
are not only more effective than behavioral treatments
in the short term but are the only
form of obesity intervention with evidence of consisten
t long-term effectiveness.
However, even among bariatric surgery patients, weight
loss often stabilizes and it is
estimated that more than 20% of bariatric surgery patient
s will regain a significant
amount of weight that was initially lost long-term. Li
ttle research to date has been
conducted on physical activity in post bariatric surgery pati
ents. More specifically, there
have been no studies to date examining the effects of Me
ditative Movement (MM)
programs on body composition in bariatric patients. A s
tudy using an 8-week Tai Chi
Easy program was conducted in female gastric bypass patient
s to explore feasibility of
MM in the bariatric population as well as pre- and post-in
tervention changes in weight,
mindfulness, eating behaviors, body awareness, physical a
ctivity patterns, dietary quality
and mood. Data analysis revealed that there were no s
ignificant changes in weight or
physical activity patterns; however, significant changes w
ere observed in anxiety, overall
body awareness and cognitive restraint in eating. Addit
ionally, a significant decrease in
processed meat consumption and a weak trend towards increa
sed consumption of fruits
may suggest an overall improvement in dietary quality.
ContributorsSmith, Lisa L. (Author) / Larkey, Linda K (Thesis advisor) / Ainsworth, Barbara (Committee member) / Chisum, Jack (Committee member) / Ohri-Vachaspati, Punam (Committee member) / McClain, Darya (Committee member) / Arizona State University (Publisher)
Created2014
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
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
Mobile ad hoc networks (MANETs) have attracted attention for mission critical applications. This dissertation investigates techniques of statistical monitoring and control for overhead reduction in a proactive MANET routing protocol. Proactive protocols transmit overhead periodically. Instead, we propose that the local conditions of a node should determine this transmission decision. While the goal is to minimize overhead, a balance in the amount of overhead transmitted and the performance achieved is required. Statistical monitoring consists of techniques to determine if a characteristic has shifted away from an in-control state. A basic tool for monitoring is a control chart, a time-oriented representation of the characteristic. When a sample deviates outside control limits, a significant change has occurred and corrective actions are required to return to the in-control state. We investigate the use of statistical monitoring of local conditions in the Optimized Link State Routing (OLSR) protocol. Three versions are developed. In A-OLSR, each node uses a Shewhart chart to monitor betweenness of its two-hop neighbourhood. Betweenness is a social network metric that measures a node's influence; betweenness is larger when a node has more influence. Changes in topology are associated with changes in betweenness. We incorporate additional local node conditions including speed, density, packet arrival rate, and number of flows it forwards in A+-OLSR. Response Surface Methodology (RSM) is used to optimize timer values. As well, the Shewhart chart is replaced by an Exponentially Weighted Moving Average (EWMA) chart, which is more sensitive to small changes in the characteristic. It is known that control charts do not work as well in the presence of correlation. Hence, in A*-OLSR the autocorrelation in the time series is removed and an Auto-Regressive Integrated Moving Average (ARIMA) model found; this removes the dependence on node speed. A*-OLSR also extends monitoring to two characteristics concurrently using multivariate cumulative sum (MCUSUM) charts. The protocols are evaluated in simulation, and compared to OLSR and its variants. The techniques for statistical monitoring and control are general and have great potential to be applied to the adaptive control of many network protocols.
ContributorsShaukat, Kahkashan (Author) / Syrotiuk, Violet R. (Thesis advisor) / Colbourn, Charles J (Committee member) / Montgomery, Douglas C. (Committee member) / Sarjoughian, Hessam S. (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012