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- Creators: Arizona State University
Description
New communication technologies have undoubtedly altered the ways in which persons interact and have had a profound impact on public life. Engaging this impact, much of the scholarly literature has focused on how these interfaces mediate interaction however, less is known about technology's modulating effects. The current project moves beyond mediation, underscoring how social relations are not only activated by technology, but are actuated by these interfaces. Through an extended case study of Portals, gold shipping containers equipped with audio-visual technology that put persons in digital face-to-face interaction with others around the globe, the current project engages such actuation, highlighting how the co-mingling of affect and technology generate new ways of noticing, living and thinking through the complex relationships of public life. The human/technology relations mediated/modulated by the Portal produce unique atmospheres that activate/actuate public space and blur the boundaries between public and private. Additionally, the atmospheres of the Portal generate a digital co-presence that allows for user/participants to feel with their interlocutors. This “feeling with” suspends user/participants in atmospheres of human connection through the emergence of an imaginative dialogue, and the curating of such atmospheres leads to dialogic transformation. As such, the Portal operates as an atmospheric interface. Engaging the concept of atmosphere attunes those interested in new communication technologies to the complex gatherings these technologies create, and the potentialities and pitfalls of these emerging interfaces on public life.
ContributorsFerderer, Brandon Boyd (Author) / Brouwer, Daniel C. (Thesis advisor) / McHugh, Kevin (Committee member) / Hess, Aaron (Committee member) / Arizona State University (Publisher)
Created2019
Description
Due to the rapid penetration of solar power systems in residential areas, there has
been a dramatic increase in bidirectional power flow. Such a phenomenon of bidirectional
power flow creates a need to know where Photovoltaic (PV) systems are
located, what their quantity is, and how much they generate. However, significant
challenges exist for accurate solar panel detection, capacity quantification,
and generation estimation by employing existing methods, because of the limited
labeled ground truth and relatively poor performance for direct supervised learning.
To mitigate these issue, this thesis revolutionizes key learning concepts to (1)
largely increase the volume of training data set and expand the labelled data set by
creating highly realistic solar panel images, (2) boost detection and quantification
learning through physical knowledge and (3) greatly enhance the generation estimation
capability by utilizing effective features and neighboring generation patterns.
These techniques not only reshape the machine learning methods in the GIS
domain but also provides a highly accurate solution to gain a better understanding
of distribution networks with high PV penetration. The numerical
validation and performance evaluation establishes the high accuracy and scalability
of the proposed methodologies on the existing solar power systems in the
Southwest region of the United States of America. The distribution and transmission
networks both have primitive control methodologies, but now is the high time
to work out intelligent control schemes based on reinforcement learning and show
that they can not only perform well but also have the ability to adapt to the changing
environments. This thesis proposes a sequence task-based learning method to
create an agent that can learn to come up with the best action set that can overcome
the issues of transient over-voltage.
been a dramatic increase in bidirectional power flow. Such a phenomenon of bidirectional
power flow creates a need to know where Photovoltaic (PV) systems are
located, what their quantity is, and how much they generate. However, significant
challenges exist for accurate solar panel detection, capacity quantification,
and generation estimation by employing existing methods, because of the limited
labeled ground truth and relatively poor performance for direct supervised learning.
To mitigate these issue, this thesis revolutionizes key learning concepts to (1)
largely increase the volume of training data set and expand the labelled data set by
creating highly realistic solar panel images, (2) boost detection and quantification
learning through physical knowledge and (3) greatly enhance the generation estimation
capability by utilizing effective features and neighboring generation patterns.
These techniques not only reshape the machine learning methods in the GIS
domain but also provides a highly accurate solution to gain a better understanding
of distribution networks with high PV penetration. The numerical
validation and performance evaluation establishes the high accuracy and scalability
of the proposed methodologies on the existing solar power systems in the
Southwest region of the United States of America. The distribution and transmission
networks both have primitive control methodologies, but now is the high time
to work out intelligent control schemes based on reinforcement learning and show
that they can not only perform well but also have the ability to adapt to the changing
environments. This thesis proposes a sequence task-based learning method to
create an agent that can learn to come up with the best action set that can overcome
the issues of transient over-voltage.
ContributorsHashmy, Syed Muhammad Yousaf (Author) / Weng, Yang (Thesis advisor) / Sen, Arunabha (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2019
Description
Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than deoxyribose nucleic acid (DNA) sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. In 2011, Haynes et al. showed that a synthetic regulator called the Polycomb chromatin Transcription Factor (PcTF), a fusion protein that binds methylated histones, reactivated an artificially-silenced luciferase reporter gene. These synthetic transcription activators are derived from the polycomb repressive complex (PRC) and associate with the epigenetic silencing mark H3K27me3 to reactivate the expression of silenced genes. It is demonstrated here that the duration of epigenetic silencing does not perturb reactivation via PcTF fusion proteins. After 96 hours PcTF shows the strongest reactivation activity. A variant called Pc2TF, which has roughly double the affinity for H3K27me3 in vitro, reactivated the silenced luciferase gene by at least 2-fold in living cells.
ContributorsVargas, Daniel A. (Author) / Haynes, Karmella (Thesis advisor) / Wang, Xiao (Committee member) / Mills, Jeremy (Committee member) / Arizona State University (Publisher)
Created2019
Description
It remains unquestionable that space-based technology is an indispensable component of modern daily lives. Success or failure of space missions is largely contingent upon the complex system analysis and design methodologies exerted in converting the initial idea
into an elaborate functioning enterprise. It is for this reason that this dissertation seeks to contribute towards the search for simpler, efficacious and more reliable methodologies and tools that accurately model and analyze space systems dynamics. Inopportunely, despite the inimical physical hazards, space systems must endure a perturbing dynamical environment that persistently disorients spacecraft attitude, dislodges spacecraft from their designated orbital locations and compels spacecraft to follow undesired orbital trajectories. The ensuing dynamics’ analytical models are complexly structured, consisting of parametrically excited nonlinear systems with external periodic excitations–whose analysis and control is not a trivial task. Therefore, this dissertation’s objective is to overcome the limitations of traditional approaches (averaging and perturbation, linearization) commonly used to analyze and control such dynamics; and, further obtain more accurate closed-form analytical solutions in a lucid and broadly applicable manner. This dissertation hence implements a multi-faceted methodology that relies on Floquet theory, invariant center manifold reduction and normal forms simplification. At the heart of this approach is an intuitive system state augmentation technique that transforms non-autonomous nonlinear systems into autonomous ones. Two fitting representative types of space systems dynamics are investigated; i) attitude motion of a gravity gradient stabilized spacecraft in an eccentric orbit, ii) spacecraft motion in the vicinity of irregularly shaped small bodies. This investigation demonstrates how to analyze the motion stability, chaos, periodicity and resonance. Further, versal deformation of the normal forms scrutinizes the bifurcation behavior of the gravity gradient stabilized attitude motion. Control laws developed on transformed, more tractable analytical models show that; unlike linear control laws, nonlinear control strategies such as sliding mode control and bifurcation control stabilize the intricate, unwieldy astrodynamics. The pitch attitude dynamics are stabilized; and, a regular periodic orbit realized in the vicinity of small irregularly shaped bodies. Importantly, the outcomes obtained are unconventionally realized as closed-form analytical solutions obtained via the comprehensive approach introduced by this dissertation.
into an elaborate functioning enterprise. It is for this reason that this dissertation seeks to contribute towards the search for simpler, efficacious and more reliable methodologies and tools that accurately model and analyze space systems dynamics. Inopportunely, despite the inimical physical hazards, space systems must endure a perturbing dynamical environment that persistently disorients spacecraft attitude, dislodges spacecraft from their designated orbital locations and compels spacecraft to follow undesired orbital trajectories. The ensuing dynamics’ analytical models are complexly structured, consisting of parametrically excited nonlinear systems with external periodic excitations–whose analysis and control is not a trivial task. Therefore, this dissertation’s objective is to overcome the limitations of traditional approaches (averaging and perturbation, linearization) commonly used to analyze and control such dynamics; and, further obtain more accurate closed-form analytical solutions in a lucid and broadly applicable manner. This dissertation hence implements a multi-faceted methodology that relies on Floquet theory, invariant center manifold reduction and normal forms simplification. At the heart of this approach is an intuitive system state augmentation technique that transforms non-autonomous nonlinear systems into autonomous ones. Two fitting representative types of space systems dynamics are investigated; i) attitude motion of a gravity gradient stabilized spacecraft in an eccentric orbit, ii) spacecraft motion in the vicinity of irregularly shaped small bodies. This investigation demonstrates how to analyze the motion stability, chaos, periodicity and resonance. Further, versal deformation of the normal forms scrutinizes the bifurcation behavior of the gravity gradient stabilized attitude motion. Control laws developed on transformed, more tractable analytical models show that; unlike linear control laws, nonlinear control strategies such as sliding mode control and bifurcation control stabilize the intricate, unwieldy astrodynamics. The pitch attitude dynamics are stabilized; and, a regular periodic orbit realized in the vicinity of small irregularly shaped bodies. Importantly, the outcomes obtained are unconventionally realized as closed-form analytical solutions obtained via the comprehensive approach introduced by this dissertation.
ContributorsWASWA, PETER (Author) / Redkar, Sangram (Thesis advisor) / Rogers, Bradley (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2019
Description
The secret Facebook group ////sads only/// was formed in October 2015 to provide a safe space for women and trans and nonbinary people to express their emotions, a sort of digital support group. Members can post individually about things happening in their lives, comment on other members’ posts with advice or support, and contribute to discussion threads. Common subject matters include mental health, relationships, sexuality, gender identity, friendships, careers, family, art, education, and body image. The group’s location on Facebook adds to its utility – it can be an alternative site of community-making and communication, away from the often toxic, triggering, or just plain negative posts that clog up social media news feeds and the unsolicited comments that get appended. The group is informed by principles of affect theory, and in particular, sad girl theory, which was developed by the artist Audrey Wollen. She suggests that femme sadness is a site of power and not just vulnerability. In her view, sadness isn’t passive existence, but instead, an act of resistance. Specifically, it uses the body in a way that is crucial to many definitions of activism, incorporating the violence of revolution, protest, and struggle that has historically been gendered as male. This thesis examines the history and future directions of the ///sads only/// group as well as its theoretical underpinnings and the implications of its intervention, considering such perspectives as cultural studies, gender performance, identity formation, digital citizenship, mental health, and feminist activism.
ContributorsKoerth, Kimberly (Author) / Ward, Mako (Thesis advisor) / Anderson, Lisa (Thesis advisor) / McGibbney Vlahoulis, Michelle (Committee member) / Arizona State University (Publisher)
Created2019
Description
The division of household tasks has been studied extensively over the past fifty years, but there are unanswered questions about why partners still report imbalances. In this study, I employed a grounded theory research design to systematically collect and analyze data from newly cohabitating, dual-earner couples to generate theory. Three prominent theories (relative resources, time availability and gender ideology) served as the framework for this research. The purpose of this study was to expose the processes of meaning-making, interpretations and decision-making regarding divisions of housework and to determine if, and if so how, dissymmetry in household tasks are understood. My research questions addressed the meanings newly cohabitating couples ascribed to household tasks by and explored how they understand their allocation of these tasks. Eighteen in-depth interviews of six newly cohabitating couples were conducted. Results from the study highlight six major themes that contribute to couples’ meaning-making processes regarding housework performance: care, consistency, expectations, gender & upbringing, micromanagement, and task preference. These findings contribute to the broader body of housework literature by demonstrating how grounded theory methods may offer a unique approach to the examination of household task performance. Further, germination of the blended output theory of housework (B.O.T.H.) that emerged from this study could provide an opportunity to better understand changing family structures.
ContributorsTaylor, Jameien R (Author) / Alberts, Janet (Thesis advisor) / Manninen, Bertha (Committee member) / Broome, Benjamin (Committee member) / Arizona State University (Publisher)
Created2019
Description
There are many inconsistencies in the literature regarding how to estimate the Lyapunov Exponent (LyE) for gait. In the last decade, many papers have been published using Lyapunov Exponents to determine differences between young healthy and elderly adults and healthy and frail older adults. However, the differences in methodologies of data collection, input parameters, and algorithms used for the LyE calculation has led to conflicting numerical values for the literature to build upon. Without a unified methodology for calculating the LyE, researchers can only look at the trends found in studies. For instance, LyE is generally lower for young adults compared to elderly adults, but these values cannot be correlated across studies to create a classifier for individuals that are healthy or at-risk of falling. These issues could potentially be solved by standardizing the process of computing the LyE.
This dissertation examined several hurdles that must be overcome to create a standardized method of calculating the LyE for gait data when collected with an accelerometer. In each of the following investigations, both the Rosenstein et al. and Wolf et al. algorithms as well as three normalization methods were applied in order to understand the extent at which these factors affect the LyE. First, the a priori parameters of time delay and embedding dimension which are required for phase space reconstruction were investigated. This study found that the time delay can be standardized to a value of 10 and that an embedding dimension of 5 or 7 should be used for the Rosenstein and Wolf algorithm respectively. Next, the effect of data length on the LyE was examined using 30 to 1300 strides of gait data. This analysis found that comparisons across papers are only possible when similar amounts of data are used but comparing across normalization methods is not recommended. And finally, the reliability and minimum required number of strides for each of the 6 algorithm-normalization method combinations in both young healthy and elderly adults was evaluated. This research found that the Rosenstein algorithm was more reliable and required fewer strides for the calculation of the LyE for an accelerometer.
This dissertation examined several hurdles that must be overcome to create a standardized method of calculating the LyE for gait data when collected with an accelerometer. In each of the following investigations, both the Rosenstein et al. and Wolf et al. algorithms as well as three normalization methods were applied in order to understand the extent at which these factors affect the LyE. First, the a priori parameters of time delay and embedding dimension which are required for phase space reconstruction were investigated. This study found that the time delay can be standardized to a value of 10 and that an embedding dimension of 5 or 7 should be used for the Rosenstein and Wolf algorithm respectively. Next, the effect of data length on the LyE was examined using 30 to 1300 strides of gait data. This analysis found that comparisons across papers are only possible when similar amounts of data are used but comparing across normalization methods is not recommended. And finally, the reliability and minimum required number of strides for each of the 6 algorithm-normalization method combinations in both young healthy and elderly adults was evaluated. This research found that the Rosenstein algorithm was more reliable and required fewer strides for the calculation of the LyE for an accelerometer.
ContributorsSmith, Victoria (Author) / Lockhart, Thurmon E (Thesis advisor) / Spano, Mark L (Committee member) / Honeycutt, Claire F (Committee member) / Lee, Hyunglae (Committee member) / Peterson, Daniel S (Committee member) / Arizona State University (Publisher)
Created2019
Description
Transcriptions and arrangements of works originally written for other instruments have greatly expanded the guitar’s repertoire. This project focuses on a new arrangement of the Suite in A Minor by Élisabeth Jacquet de la Guerre (1665–1729), which originally was composed for harpsichord. The author chose this work because the repertoire for the guitar is critically lacking in examples of French Baroque harpsichord music and also of works by female composers. The suite includes an unmeasured harpsichord prelude––a genre that, to the author’s knowledge, has not been arranged for the modern six-string guitar. This project also contains a brief account of Jacquet de la Guerre’s life, discusses the genre of unmeasured harpsichord preludes, and provides an overview of compositional aspects of the suite. Furthermore, it includes the arrangement methodology, which shows the process of creating an idiomatic arrangement from harpsichord to solo guitar while trying to preserve the integrity of the original work. A summary of the changes in the current arrangement is presented in Appendix B.
ContributorsSewell, David (Author) / Koonce, Frank (Thesis advisor) / Rotaru, Catalin (Committee member) / Suzuki, Kotoka (Committee member) / Arizona State University (Publisher)
Created2019
Description
In order for a robot to solve complex tasks in real world, it needs to compute discrete, high-level strategies that can be translated into continuous movement trajectories. These problems become increasingly difficult with increasing numbers of objects and domain constraints, as well as with the increasing degrees of freedom of robotic manipulator arms.
The first part of this thesis develops and investigates new methods for addressing these problems through hierarchical task and motion planning for manipulation with a focus on autonomous construction of free-standing structures using precision-cut planks. These planks can be arranged in various orientations to design complex structures; reliably and autonomously building such structures from scratch is computationally intractable due to the long planning horizon and the infinite branching factor of possible grasps and placements that the robot could make.
An abstract representation is developed for this class of problems and show how pose generators can be used to autonomously compute feasible robot motion plans for constructing a given structure. The approach was evaluated through simulation and on a real ABB YuMi robot. Results show that hierarchical algorithms for planning can effectively overcome the computational barriers to solving such problems.
The second part of this thesis proposes a deep learning-based algorithm to identify critical regions for motion planning. Further investigation is done whether these learned critical regions can be translated to learn high-level landmark actions for automated planning.
The first part of this thesis develops and investigates new methods for addressing these problems through hierarchical task and motion planning for manipulation with a focus on autonomous construction of free-standing structures using precision-cut planks. These planks can be arranged in various orientations to design complex structures; reliably and autonomously building such structures from scratch is computationally intractable due to the long planning horizon and the infinite branching factor of possible grasps and placements that the robot could make.
An abstract representation is developed for this class of problems and show how pose generators can be used to autonomously compute feasible robot motion plans for constructing a given structure. The approach was evaluated through simulation and on a real ABB YuMi robot. Results show that hierarchical algorithms for planning can effectively overcome the computational barriers to solving such problems.
The second part of this thesis proposes a deep learning-based algorithm to identify critical regions for motion planning. Further investigation is done whether these learned critical regions can be translated to learn high-level landmark actions for automated planning.
ContributorsKumar, Kislay (Author) / Srivastava, Siddharth (Thesis advisor) / Zhang, Yu (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2019
Description
Two-dimensional quantum materials have garnered increasing interest in a wide
variety of applications due to their promising optical and electronic properties. These
quantum materials are highly anticipated to make transformative quantum sensors and
biosensors. Biosensors are currently considered among one of the most promising
solutions to a wide variety of biomedical and environmental problems including highly
sensitive and selective detection of difficult pathogens, toxins, and biomolecules.
However, scientists face enormous challenges in achieving these goals with current
technologies. Quantum biosensors can have detection with extraordinary sensitivity and
selectivity through manipulation of their quantum states, offering extraordinary properties
that cannot be attained with traditional materials. These quantum materials are anticipated
to make significant impact in the detection, diagnosis, and treatment of many diseases.
Despite the exciting promise of these cutting-edge technologies, it is largely
unknown what the inherent toxicity and biocompatibility of two-dimensional (2D)
materials are. Studies are greatly needed to lay the foundation for understanding the
interactions between quantum materials and biosystems. This work introduces a new
method to continuously monitor the cell proliferation and toxicity behavior of 2D
materials. The cell viability and toxicity measurements coupled with Live/Dead
fluorescence imaging suggest the biocompatibility of crystalline MoS2 and MoSSe
monolayers and the significantly-reduced cellular growth of defected MoTe2 thin films
and exfoliated MoS2 nanosheets. Results show the exciting potential of incorporating
kinetic cell viability data of 2D materials with other assay tools to further fundamental
understanding of 2D material biocompatibility.
variety of applications due to their promising optical and electronic properties. These
quantum materials are highly anticipated to make transformative quantum sensors and
biosensors. Biosensors are currently considered among one of the most promising
solutions to a wide variety of biomedical and environmental problems including highly
sensitive and selective detection of difficult pathogens, toxins, and biomolecules.
However, scientists face enormous challenges in achieving these goals with current
technologies. Quantum biosensors can have detection with extraordinary sensitivity and
selectivity through manipulation of their quantum states, offering extraordinary properties
that cannot be attained with traditional materials. These quantum materials are anticipated
to make significant impact in the detection, diagnosis, and treatment of many diseases.
Despite the exciting promise of these cutting-edge technologies, it is largely
unknown what the inherent toxicity and biocompatibility of two-dimensional (2D)
materials are. Studies are greatly needed to lay the foundation for understanding the
interactions between quantum materials and biosystems. This work introduces a new
method to continuously monitor the cell proliferation and toxicity behavior of 2D
materials. The cell viability and toxicity measurements coupled with Live/Dead
fluorescence imaging suggest the biocompatibility of crystalline MoS2 and MoSSe
monolayers and the significantly-reduced cellular growth of defected MoTe2 thin films
and exfoliated MoS2 nanosheets. Results show the exciting potential of incorporating
kinetic cell viability data of 2D materials with other assay tools to further fundamental
understanding of 2D material biocompatibility.
ContributorsTran, Michael, Ph.D (Author) / Tongay, Sefaattin (Thesis advisor) / Green, Matthew (Thesis advisor) / Muhich, Christopher (Committee member) / Arizona State University (Publisher)
Created2019