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- Genre: Masters Thesis
- Creators: Yang, Yezhou
Description
Embodied Continuity documents the methodology of Entangled/Embraced, a dance performance piece presented December, 2011 and created as an artistic translation of research conducted January-May, 2011 in the states of Karnataka and Kerala, South India. Focused on the sciences of Ayurveda, Kalaripayattu and yoga, this research stems from an interest in body-mind connectivity, body-mind-environment continuity, embodied epistemology and the implications of ethnography within artistic practice. The document begins with a theoretical grounding covering established research on theories of embodiment; ethnographic methodologies framing research conducted in South India including sensory ethnography, performance ethnography and autoethnography; and an explanation of the sciences of Ayurveda, Kalaripayattu and yoga with a descriptive slant that emphasizes concepts of embodiment and body-mind-environment continuity uniquely inherent to these sciences. Following the theoretical grounding, the document provides an account of methods used in translating theoretical concepts and experiences emerging from research in India into the creation of the Entangled/Embraced dance work. Using dancer and audience member participation to inspire emergent meanings and maintain ethnographic consciousness, Embodied Continuity demonstrates how concepts inspiring research interests, along with ideas emerging from within research experiences, in addition to philosophical standpoints embedded in the ethnographic methodologies chosen to conduct research, weave into the entire project of Entangled/Embraced to unite the phases of research and performance, ethnography and artistry.
ContributorsRamsey, Ashlee (Author) / Vissicaro, Pegge (Thesis advisor) / Standley, Eileen (Committee member) / Dove, Simon (Committee member) / Arizona State University (Publisher)
Created2012
Description
I'll go to the end of time for you (and you don't even know my name) is an evening-length solo performance created and performed by Kristopher K.Q. Pourzal. It premiered November 8-10, 2013 in the Margaret Gisolo Dance Theatre of Arizona State University. The solo was the culmination (suspension, really) of a wild creative journey, the distillation of a process that initially involved several collaborators. Through a series of neurotically/erotically repetitive episodes of self-composed song, text, and dance, the work mines questions of the desire to be seen and the desire to feel alive. The conventions and constructs of the proscenium stage are both utilized and subverted in examining this platform as uniquely suited for revealing the nature of these experiences and their potential relationship. This document is primarily an account of the show's process--its before and after--and serves as a site of exploration, explanation, analysis, reflection, questioning, and ultimately furtherance of the practice-based research made manifest in the performances.
ContributorsPourzal, Kristopher K. Q (Author) / Standley, Eileen (Thesis advisor) / Vissicaro, Pegge (Committee member) / McMahon, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
Description
This ethnographic research focuses on the specific creative processes of one dance-maker who worked collaboratively with seven dancers, a sound designer, a costume designer, and a narrative speaker. Together they created an evening-length dance work entitled "The Now Creature." Throughout the creative process, the dance-maker was interested in noticing attachments, finding freedom from these attachments, and being aware of how the work was affected by the choice to detach or remain attached to certain ideas. This interest stemmed from the dance-maker/researcher's interest in Buddhist philosophy and a system of decision-making she had been developing since childhood. The creative process for "The Now Creature" began with experiments in chance procedures as a method of non-attachment. After the first public showing of the piece, the process shifted to include intuition and aesthetic integration. "Embodied nowness," or the awareness of one's physical and mental sensations in the present moment, played an important role in rehearsals and in the overall process of letting go of attachments. All collaborators kept journals and were usually given specific prompts about which to write. The researcher/dance-maker also conducted one-on-one verbal interviews and group discussions with the collaborators. These data informed the development of the work presented on January 31-February 2 at Arizona State University, Findings from this research can be applied to any kind of creative process, or any life situation that includes decision-making.
ContributorsStein, Denise A (Author) / Vissicaro, Pegge (Thesis advisor) / Kaplan, Robert (Committee member) / Fonow, Mary Margaret (Committee member) / Arizona State University (Publisher)
Created2014
Description
This six month IRB approved qualitative study was held at Arizona State University to see how a group of seven university dancers' body appreciation and body perception would be affected by introduction and familiarized with Bartenieff Fundamentals and other somatic practices. During this process the individuals gained knowledge about their own bodies through somatic movement activities, journal writings, group discussions, and personal interviews. Movers then used this knowledge to create movement phrases that represented their own personal journeys with body image struggles, doubts, and insecurities. These movement phrases were then linked together in a 40-minute expressive movement piece that represented the journey the group of movers had made and was still making together.
ContributorsRodgers, Patricia (Author) / Jackson, Naomi (Thesis advisor) / Britt, Melissa (Committee member) / Vissicaro, Pegge (Committee member) / Arizona State University (Publisher)
Created2014
Accessing the centre: complementary conditioning & somatic wellness for competitive Irish step dance
Description
This thesis examines the integration of somatic principles into Irish Step Dancing. The researcher conducted a twelve week case study that explored how utilizing the Centre-line Support System in training competitive Irish Step Dancers, through integrating Alexander Technique and Bartenieff Fundamentals of Total Body Connectivity can generate increased height and efficiency in jumping and an improvement in upper-body carriage, while longitudinally reducing the occurrence of over-use injuries. Research occurred between January and March 2012 in Tucson, Arizona and Dublin, Ireland. Additional research and reflection occurred in Belfast, Glasgow, and London, United Kingdom; Limerick, Cork, and Galway, Ireland; Amsterdam, The Netherlands; Chicago, Illinois; Phoenix, Arizona; and Los Angeles, California.
ContributorsBuck, Helen (Author) / Vissicaro, Pegge (Thesis advisor) / Hoffner, Kristin (Committee member) / Jackson, Naomi (Committee member) / Arizona State University (Publisher)
Created2012
Description
Every body holds a story. Those stories are rich with physical movements to be expressed, and through the physical expression comes self-awareness and transformation. A partnership between Arizona State University and Arcadia High School was the vehicle in which I implemented a curriculum built around somatic experiences and communal beliefs and values. The framework for this investigated curriculum teaches students' embodiment of self, tolerance and acceptance in collaboration, life skills through applied constructivist principles, and increased critical thinking and problem-solving abilities. This research involved somatic exercises enabling participants to have insight into natural moving patterns, how such patterns relate to others and outside environments. Research concluded with collective dialogue around individual and shared experiences. I worked twice per week with a choreography class with a four unit curriculum. From varying modes of assessment (e.g., one-on-one interviews, group discussions, journals, surveys, ongoing observations) students' responses to this type of curriculum ranged from excitement and curiosity to frustrating and provoking. Although these areas of research are not necessarily new to the field of dance and education, gaps in dialogue, published work, and reliable resources prove these theories and methods are still valued and necessary. This research demonstrates the imperative demand in dance education for deeper connections of self-discovery.
ContributorsYourse, Katie R (Author) / Dyer, Becky (Thesis advisor) / Vissicaro, Pegge (Committee member) / Johnson, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2015
Description
This document outlines the formation and development of Worth the Weight, or WTW, a platform that seeks to sustain the Breaking community in Phoenix, Arizona and connect the generations by bringing them together in a newly and never before seen event in Breaking, an all weight class and division competition. In the last five to ten years there has been a noticeable decline in the local Breaking community, in part due to the introduction of new dance categories, economic and social changes, the cross over of academia and traditional studios in Phoenix; all combining to create a lack of longevity in veterans of the culture to pass on the tools of the trade to the next generation.
WTW is an event that occurs monthly for three consecutive months followed by a month off, totaling nine events and three seasons per calendar year. At each event dancers go head to head in battle in a single elimination style bracket, where they will add a loss or win to their overall season record. The goals of WTW are self-empowerment as well as ownership and investment in the community by those involved through participation in both the event and the planning process; all built on a foundation of trust within the Breaking community. This researcher has thirty years of direct involvement in the Breaking culture with twenty-two of those years as a practitioner in Phoenix, Arizona and co-founder of Furious Styles Crew, Arizona’s longest running Breaking crew. The development of WTW was drawn from this experience along with interviews and observations of Breaking communities worldwide. WTW intends to provide a reliable and consistent outlet during a time of instant gratification, allowing a space for self-discovery and the development of tools to be applied beyond movement. It is hoped that the format of WTW will be a model that can be adapted by other Breaking communities worldwide.
WTW is an event that occurs monthly for three consecutive months followed by a month off, totaling nine events and three seasons per calendar year. At each event dancers go head to head in battle in a single elimination style bracket, where they will add a loss or win to their overall season record. The goals of WTW are self-empowerment as well as ownership and investment in the community by those involved through participation in both the event and the planning process; all built on a foundation of trust within the Breaking community. This researcher has thirty years of direct involvement in the Breaking culture with twenty-two of those years as a practitioner in Phoenix, Arizona and co-founder of Furious Styles Crew, Arizona’s longest running Breaking crew. The development of WTW was drawn from this experience along with interviews and observations of Breaking communities worldwide. WTW intends to provide a reliable and consistent outlet during a time of instant gratification, allowing a space for self-discovery and the development of tools to be applied beyond movement. It is hoped that the format of WTW will be a model that can be adapted by other Breaking communities worldwide.
ContributorsMagaña, Jorge Edson (Author) / Vissicaro, Pegge (Thesis advisor) / Schupp, Karen (Committee member) / Gabbert, Kenneth (Committee member) / Arizona State University (Publisher)
Created2015
Description
In a collaborative environment where multiple robots and human beings are expected
to collaborate to perform a task, it becomes essential for a robot to be aware of multiple
agents working in its work environment. A robot must also learn to adapt to
different agents in the workspace and conduct its interaction based on the presence
of these agents. A theoretical framework was introduced which performs interaction
learning from demonstrations in a two-agent work environment, and it is called
Interaction Primitives.
This document is an in-depth description of the new state of the art Python
Framework for Interaction Primitives between two agents in a single as well as multiple
task work environment and extension of the original framework in a work environment
with multiple agents doing a single task. The original theory of Interaction
Primitives has been extended to create a framework which will capture correlation
between more than two agents while performing a single task. The new state of the
art Python framework is an intuitive, generic, easy to install and easy to use python
library which can be applied to use the Interaction Primitives framework in a work
environment. This library was tested in simulated environments and controlled laboratory
environment. The results and benchmarks of this library are available in the
related sections of this document.
to collaborate to perform a task, it becomes essential for a robot to be aware of multiple
agents working in its work environment. A robot must also learn to adapt to
different agents in the workspace and conduct its interaction based on the presence
of these agents. A theoretical framework was introduced which performs interaction
learning from demonstrations in a two-agent work environment, and it is called
Interaction Primitives.
This document is an in-depth description of the new state of the art Python
Framework for Interaction Primitives between two agents in a single as well as multiple
task work environment and extension of the original framework in a work environment
with multiple agents doing a single task. The original theory of Interaction
Primitives has been extended to create a framework which will capture correlation
between more than two agents while performing a single task. The new state of the
art Python framework is an intuitive, generic, easy to install and easy to use python
library which can be applied to use the Interaction Primitives framework in a work
environment. This library was tested in simulated environments and controlled laboratory
environment. The results and benchmarks of this library are available in the
related sections of this document.
ContributorsKumar, Ashish, M.S (Author) / Amor, Hani Ben (Thesis advisor) / Zhang, Yu (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2017
Description
With the rise of the Big Data Era, an exponential amount of network data is being generated at an unprecedented rate across a wide-range of high impact micro and macro areas of research---from protein interaction to social networks. The critical challenge is translating this large scale network data into actionable information.
A key task in the data translation is the analysis of network connectivity via marked nodes---the primary focus of our research. We have developed a framework for analyzing network connectivity via marked nodes in large scale graphs, utilizing novel algorithms in three interrelated areas: (1) analysis of a single seed node via it’s ego-centric network (AttriPart algorithm); (2) pathway identification between two seed nodes (K-Simple Shortest Paths Multithreaded and Search Reduced (KSSPR) algorithm); and (3) tree detection, defining the interaction between three or more seed nodes (Shortest Path MST algorithm).
In an effort to address both fundamental and applied research issues, we have developed the LocalForcasting algorithm to explore how network connectivity analysis can be applied to local community evolution and recommender systems. The goal is to apply the LocalForecasting algorithm to various domains---e.g., friend suggestions in social networks or future collaboration in co-authorship networks. This algorithm utilizes link prediction in combination with the AttriPart algorithm to predict future connections in local graph partitions.
Results show that our proposed AttriPart algorithm finds up to 1.6x denser local partitions, while running approximately 43x faster than traditional local partitioning techniques (PageRank-Nibble). In addition, our LocalForecasting algorithm demonstrates a significant improvement in the number of nodes and edges correctly predicted over baseline methods. Furthermore, results for the KSSPR algorithm demonstrate a speed-up of up to 2.5x the standard k-simple shortest paths algorithm.
A key task in the data translation is the analysis of network connectivity via marked nodes---the primary focus of our research. We have developed a framework for analyzing network connectivity via marked nodes in large scale graphs, utilizing novel algorithms in three interrelated areas: (1) analysis of a single seed node via it’s ego-centric network (AttriPart algorithm); (2) pathway identification between two seed nodes (K-Simple Shortest Paths Multithreaded and Search Reduced (KSSPR) algorithm); and (3) tree detection, defining the interaction between three or more seed nodes (Shortest Path MST algorithm).
In an effort to address both fundamental and applied research issues, we have developed the LocalForcasting algorithm to explore how network connectivity analysis can be applied to local community evolution and recommender systems. The goal is to apply the LocalForecasting algorithm to various domains---e.g., friend suggestions in social networks or future collaboration in co-authorship networks. This algorithm utilizes link prediction in combination with the AttriPart algorithm to predict future connections in local graph partitions.
Results show that our proposed AttriPart algorithm finds up to 1.6x denser local partitions, while running approximately 43x faster than traditional local partitioning techniques (PageRank-Nibble). In addition, our LocalForecasting algorithm demonstrates a significant improvement in the number of nodes and edges correctly predicted over baseline methods. Furthermore, results for the KSSPR algorithm demonstrate a speed-up of up to 2.5x the standard k-simple shortest paths algorithm.
ContributorsFreitas, Scott (Author) / Tong, Hanghang (Thesis advisor) / Maciejewski, Ross (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2018
Description
Topological methods for data analysis present opportunities for enforcing certain invariances of broad interest in computer vision: including view-point in activity analysis, articulation in shape analysis, and measurement invariance in non-linear dynamical modeling. The increasing success of these methods is attributed to the complementary information that topology provides, as well as availability of tools for computing topological summaries such as persistence diagrams. However, persistence diagrams are multi-sets of points and hence it is not straightforward to fuse them with features used for contemporary machine learning tools like deep-nets. In this paper theoretically well-grounded approaches to develop novel perturbation robust topological representations are presented, with the long-term view of making them amenable to fusion with contemporary learning architectures. The proposed representation lives on a Grassmann manifold and hence can be efficiently used in machine learning pipelines.
The proposed representation.The efficacy of the proposed descriptor was explored on three applications: view-invariant activity analysis, 3D shape analysis, and non-linear dynamical modeling. Favorable results in both high-level recognition performance and improved performance in reduction of time-complexity when compared to other baseline methods are obtained.
The proposed representation.The efficacy of the proposed descriptor was explored on three applications: view-invariant activity analysis, 3D shape analysis, and non-linear dynamical modeling. Favorable results in both high-level recognition performance and improved performance in reduction of time-complexity when compared to other baseline methods are obtained.
ContributorsThopalli, Kowshik (Author) / Turaga, Pavan Kumar (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2017