Matching Items (1,008)
Description
It has been identified in the literature that there exists a link between the built environment and non-motorized transport. This study aims to contribute to existing literature on the effects of the built environment on cycling, examining the case of the whole State of California. Physical built environment features are classified into six groups as: 1) local density, 2) diversity of land use, 3) road connectivity, 4) bike route length, 5) green space, 6) job accessibility. Cycling trips in one week for all children, school children, adults and employed-adults are investigated separately. The regression analysis shows that cycling trips is significantly associated with some features of built environment when many socio-demographic factors are taken into account. Street intersections, bike route length tend to increase the use of bicycle. These effects are well-aligned with literature. Moreover, both local and regional job accessibility variables are statistically significant in two adults' models. However, residential density always has a significant negatively effect on cycling trips, which is still need further research to confirm. Also, there is a gap in literature on how green space affects cycling, but the results of this study is still too unclear to make it up. By elasticity analysis, this study concludes that street intersections is the most powerful predictor on cycling trips. From another perspective, the effects of built environment on cycling at workplace (or school) are distinguished from at home. This study implies that a wide range of measures are available for planners to control vehicle travel by improving cycling-level in California.
ContributorsWang, Kailai, M.U.E.P (Author) / Salon, Deborah (Thesis advisor) / Rey, Sergio (Committee member) / Li, Wenwen (Committee member) / Arizona State University (Publisher)
Created2015
Description
This dissertation explores the megamachine, a prominent metaphor in American humanist and philosopher of technology, Lewis Mumford's Myth of the Machine series. The term refers critically to dynamic, regimented human capacities that drive scientific and technical innovation in society. Mumford's view of the nature of collectives focuses on qualities and patterns that emerge from the behavior of groups, societies, systems, and ecologies. It is my aim to reenergize key concepts about collective capacities drawn from Lewis Mumford's critique of historical and modern sociotechnical arrangements. I investigate the possibility of accessing those capacities through improved design for Technology Assessment (TA), formal practices that engage experts and lay citizens in the evaluation of complex scientific and technical issues.
I analyze the components of Mumford's megamachine and align key concerns in two pivotal works that characterize the impact of collective capacities on society: Bruno Latour's Pasteurization of France (1988) and Elias Canetti's Crowds and Power (1962). As I create a model of collective capacities in the sociotechnical according to the parameters of Mumford's megamachine, I rehabilitate two established ideas about the behavior of crowds and about the undue influence of technological systems on human behavior. I depart from Mumford's tactics and those of Canetti and Latour and propose a novel focus for STS on "sociotechnical crowds" as a meaningful unit of social measure. I make clear that Mumford's critique of the sociotechnical status quo still informs the conditions for innovation today.
Using mixed mode qualitative methods in two types of empirical field studies, I then investigate how a focus on the characteristics and components of collective human capacities in sociotechnical systems can affect the design and performance of TA. I propose a new model of TA, Emergent Technology Assessment (ETA), which includes greater public participation and recognizes the interrelationship among experience, affect and the material in mediating the innovation process. The resulting model -- the "soft" megamachine --introduces new strategies to build capacity for responsible innovation in society.
I analyze the components of Mumford's megamachine and align key concerns in two pivotal works that characterize the impact of collective capacities on society: Bruno Latour's Pasteurization of France (1988) and Elias Canetti's Crowds and Power (1962). As I create a model of collective capacities in the sociotechnical according to the parameters of Mumford's megamachine, I rehabilitate two established ideas about the behavior of crowds and about the undue influence of technological systems on human behavior. I depart from Mumford's tactics and those of Canetti and Latour and propose a novel focus for STS on "sociotechnical crowds" as a meaningful unit of social measure. I make clear that Mumford's critique of the sociotechnical status quo still informs the conditions for innovation today.
Using mixed mode qualitative methods in two types of empirical field studies, I then investigate how a focus on the characteristics and components of collective human capacities in sociotechnical systems can affect the design and performance of TA. I propose a new model of TA, Emergent Technology Assessment (ETA), which includes greater public participation and recognizes the interrelationship among experience, affect and the material in mediating the innovation process. The resulting model -- the "soft" megamachine --introduces new strategies to build capacity for responsible innovation in society.
ContributorsGano, Gretchen (Author) / Guston, David (Thesis advisor) / Miller, Clark (Thesis advisor) / Selin, Cynthia (Committee member) / Wetmore, Jameson (Committee member) / Arizona State University (Publisher)
Created2014
Description
Nearly 25 years ago, parallel computing techniques were first applied to vector spatial analysis methods. This initial research was driven by the desire to reduce computing times in order to support scaling to larger problem sets. Since this initial work, rapid technological advancement has driven the availability of High Performance Computing (HPC) resources, in the form of multi-core desktop computers, distributed geographic information processing systems, e.g. computational grids, and single site HPC clusters. In step with increases in computational resources, significant advancement in the capabilities to capture and store large quantities of spatially enabled data have been realized. A key component to utilizing vast data quantities in HPC environments, scalable algorithms, have failed to keep pace. The National Science Foundation has identified the lack of scalable algorithms in codified frameworks as an essential research product. Fulfillment of this goal is challenging given the lack of a codified theoretical framework mapping atomic numeric operations from the spatial analysis stack to parallel programming paradigms, the diversity in vernacular utilized by research groups, the propensity for implementations to tightly couple to under- lying hardware, and the general difficulty in realizing scalable parallel algorithms. This dissertation develops a taxonomy of parallel vector spatial analysis algorithms with classification being defined by root mathematical operation and communication pattern, a computational dwarf. Six computational dwarfs are identified, three being drawn directly from an existing parallel computing taxonomy and three being created to capture characteristics unique to spatial analysis algorithms. The taxonomy provides a high-level classification decoupled from low-level implementation details such as hardware, communication protocols, implementation language, decomposition method, or file input and output. By taking a high-level approach implementation specifics are broadly proposed, breadth of coverage is achieved, and extensibility is ensured. The taxonomy is both informed and informed by five case studies im- plemented across multiple, divergent hardware environments. A major contribution of this dissertation is a theoretical framework to support the future development of concrete parallel vector spatial analysis frameworks through the identification of computational dwarfs and, by extension, successful implementation strategies.
ContributorsLaura, Jason (Author) / Rey, Sergio J. (Thesis advisor) / Anselin, Luc (Committee member) / Wang, Shaowen (Committee member) / Li, Wenwen (Committee member) / Arizona State University (Publisher)
Created2015
Description
This dissertation explores the functional purpose of imagination as it is enacted in the context of shaping large transitions in sociotechnical systems. Large sociotechnical systems undergoing profound transitions embody instantiations where societies experience profound changes in the ‘rules of the game’ that underpin the conduct of daily life. The forms of imagination that guide these transformations, known in the political theory literature as ‘imaginaries,’ play a profound yet undertheorized role in transition of sociotechnical systems from one configuration to another. Expanding on this relationship, the study draws on three case studies of energy systems change in the United States during 20th and 21st century. Each case study explores unique element of how actors at a variety of levels – transnational governance, regional electrification, and in-home energy marketing – define and the possibilities for ideal human and technological action and interaction through a transition. These actors defining the parameters of a new form of systems operation and configuration are as equally focused on defining how these new configurations shape fundamental ideas that underpin American democratic sensibility. Moreover, in the process of articulating a new configuration of energy and society – be that in terms of managing global resource flows or the automation of energy use in a residential home – questions of what makes an ideal member of a society are interlinked with new contractual relationships between energy producers and energy users. Transitions research could and should pay greater attention to the normative commitments emergent systems actors – as it is in these commitments we can chart pathways to redefine the parameters that underpin emergent transitions.
ContributorsTidwell, Abraham (Author) / Miller, Clark (Thesis advisor) / Adamson, Joni (Committee member) / Ellison, Karin (Committee member) / Richter, Jennifer (Committee member) / Smith, Jessica (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Energiewende aims to drastically reduce Germany’s greenhouse gas emissions, without relying on nuclear power, while maintaining a secure and affordable energy supply. Since 2000 the country’s renewable-energy share has increased exponentially, accounting in 2017 for over a third of Germany's gross electricity consumption. This unprecedented achievement is the result of policies, tools, and institutional arrangements intended to steer society to a low-carbon economy. Despite its resounding success in renewable-energy deployment, the Energiewende is not on track to meet its decarbonization goals. Energiewende rules and regulations have generated numerous undesired consequences, and have cost much more than anticipated, a burden borne primarily by energy consumers. Why has the Energiewende not only made energy more expensive, but also failed to bring Germany closer to its decarbonization goals? I analyzed the Energiewende as a complex socio-technical system, examining its legal framework and analyzing the consequences of successive regulations; identifying major political and energy players and the factors that motivated them to pursue socio-technical change; and documenting the political trends and events in which the Energiewende is rooted and which continue to shape it. I analyzed the dynamics and the loopholes that created barriers to transition, pushed the utility sector to the brink of dissolution, and led to such undesirable outcomes as negative wholesale prices and forced exports of electricity to Germany’s European neighbors. Thirty high-level energy experts and stakeholders were interviewed to find out how the best-informed members of German society perceive the Energiewende. Surprisingly, although they were highly critical of the way the transition has unfolded, most were convinced that the transition would eventually succeed. But their definitions of success did not always depend on achieving carbon-mitigation targets. Indeed, Germany jeopardizes the achievement of these targets by changing too many policy and institutional variables at too fast a pace. Good intentions and commitment are not enough to create economies based on intermittent energy sources: they will also require intensive grid expansion and breakthroughs in storage technology. The Energiewende demonstrates starkly that collective action driven by robust political consensus is not sufficient for steering complex socio-technical systems in desired directions.
ContributorsSturm, Christine (Author) / Sarewitz, Daniel (Thesis advisor) / Miller, Clark (Committee member) / Anderies, John (Committee member) / Hirt, Paul (Committee member) / Arizona State University (Publisher)
Created2018
Description
Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.
ContributorsZhou, Xiran (Author) / Li, Wenwen (Thesis advisor) / Myint, Soe Win (Committee member) / Arundel, Samantha Thompson (Committee member) / Arizona State University (Publisher)
Created2019
Description
The humanities as a discipline have typically not used a rigid or technical method of assessment in the process of analysis. GIScience offers numerous benefits to this discipline by applying spatial analysis to rigorously understand it. Photography studios developed in the mid-19th Century as a highly popular business and emerging technology. This project was initiated by Dr. Jeremy Rowe with support from the ASU Emeritus College Research and Creative Activity and Undergraduate Research Initiative grants, and seeks to use GIS tools to understand the explosive growth of photography studios in the New York City area, specifically Manhattan and Brooklyn. Demonstrated in this project are several capabilities of the ESRI online GIS, including queries for year information, a tool showing growth over time, and a generated density map of photography studios.
ContributorsAbeln, Garrett James (Author) / Li, Wenwen (Thesis director) / Rowe, Jeremy (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Politics and Global Studies (Contributor)
Created2015-05
Description
Is nuclear power sustainable when compared to other energy sources? A truly sustainable energy source provides an environmental benefit, minimizes costs to consumers both socially and economically, and continues to do so in both the short and the long term. Taking the zero-carbon nature of nuclear generation as its net environmental benefit, this paper the evaluates the economic and social costs of nuclear power to determine if nuclear power's reputation as "unsustainable" is warranted. The sustainability of nuclear power is evaluated in two main categories. The first part focuses on the economics of nuclear power. There are many preconceived notions regarding nuclear power and its associated industry. This section addresses those notions to determine their validity given recent data. The prevalent types of nuclear plants across the U.S., the economics of the stages of nuclear energy production, and its competitiveness relative to other energy sources are addressed, culminating in an evaluation of its modern economic attractiveness as well as its future economic viability. A sustainability assessment would not be complete without addressing the social costs of an energy source, as a sustainable source must be both economically and socially viable. If it can be established that nuclear power can provide energy at lower rates and at a lower cost in terms of externalities, then it would be considered truly sustainable. To investigate those externalities, the second part of the analysis focuses on the human costs associated with the various stages of nuclear energy production. Those costs are then compared to those of alternatives sources of power, and selected case studies are examined to illustrate the ultimate risks associated with nuclear power operations. By quantifying these aspects and comparing the results to alternatives in the field, a better understanding of nuclear energy technology and its potential is achieved. The reader can then ascertain whether nuclear power's reputation as being "unsustainable" is, or is not, a reputation it deserves.
ContributorsRudolph, Alexander James (Author) / Miller, Clark (Thesis director) / Richter, Jennifer (Committee member) / School of Sustainability (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
With the new independence of adulthood, college students are a group susceptible to adopting unsupported, if not harmful, health practices. A survey of Arizona State University undergraduate students (N=200) was conducted to evaluate supplement use, trust in information sources, and beliefs about supplement regulation. Of those who reported using supplements, college students most frequently received information from friends and family. STEM majors in fields unrelated to health who were taking a supplement were found to be less likely to receive information about the supplement from a medical practitioner than those in health fields or those in non-STEM majors (-26.9%, p=0.018). STEM majors in health-related fields were 15.0% more likely to treat colds and/or cold symptoms with research-supported methods identified from reliable sources, while non-health STEM and non-STEM majors were more likely to take unsupported cold treatments (p=0.010). Surveyed students, regardless of major, also stated they would trust a medical practitioner for supplement advice above other sources (88.0%), and the majority expressed a belief that dietary supplements are approved/regulated by the government (59.8%).
ContributorsPerez, Jacob Tanner (Author) / Hendrickson, Kirstin (Thesis director) / Lefler, Scott (Committee member) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
ContributorsChandler, N. Kayla (Author) / Neisewander, Janet (Thesis director) / Sanabria, Federico (Committee member) / Olive, M. Foster (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2013-05