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Description
In an effort to address the lack of literature in on-campus active travel, this study aims to investigate the following primary questions:<br/>• What are the modes that students use to travel on campus?<br/>• What are the motivations that underlie the mode choice of students on campus?<br/>My first stage of research involved a series of qualitative investigations. I held one-on-one virtual interviews with students in which I asked them questions about the mode they use and why they feel that their chosen mode works best for them. These interviews served two functions. First, they provided me with insight into the various motivations underlying student mode choice. Second, they provided me with an indication of what explanatory variables should be included in a model of mode choice on campus.<br/>The first half of the research project informed a quantitative survey that was released via the Honors Digest to attract student respondents. Data was gathered on travel behavior as well as relevant explanatory variables.<br/>My analysis involved developing a logit model to predict student mode choice on campus and presenting the model estimation in conjunction with a discussion of student travel motivations based on the qualitative interviews. I use this information to make a recommendation on how campus infrastructure could be modified to better support the needs of the student population.
ContributorsMirtich, Laura Christine (Author) / Salon, Deborah (Thesis director) / Fang, Kevin (Committee member) / School of Public Affairs (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Regional differences of inventive activity and economic growth are important in economic geography. These differences are generally explained by the theory of localized knowledge spillovers, which argues that geographical proximity among economic actors fosters invention and innovation. However, knowledge production involves an increasing number of actors connecting to non-local partners. The space of knowledge flows is not tightly bounded in a given territory, but functions as a network-based system where knowledge flows circulate around alignments of actors in different and distant places. The purpose of this dissertation is to understand the dynamics of network aspects of knowledge flows in American biotechnology. The first research task assesses both spatial and network-based dependencies of biotechnology co-invention across 150 large U.S. metropolitan areas over four decades (1979, 1989, 1999, and 2009). An integrated methodology including both spatial and social network analyses are explicitly applied and compared. Results show that the network-based proximity better defines the U.S. biotechnology co-invention urban system in recent years. Co-patenting relationships of major biotechnology centers has demonstrated national and regional association since the 1990s. Associations retain features of spatial proximity especially in some Midwestern and Northeastern cities, but these are no longer the strongest features affecting co-inventive links. The second research task examines how biotechnology knowledge flows circulate over space by focusing on the structural properties of intermetropolitan co-invention networks. All analyses in this task are conducted using social network analysis. Evidence shows that the architecture of the U.S. co-invention networks reveals a trend toward more organized structures and less fragmentation over the four years of analysis. Metropolitan areas are increasingly interconnected into a large web of networked environment. Knowledge flows are less likely to be controlled by a small number of intermediaries. San Francisco, New York, Boston, and San Diego monopolize the central positions of the intermetropolitan co-invention network as major American biotechnology concentrations. The overall network-based system comes close to a relational core/periphery structure where core metropolitan areas are strongly connected to one another and to some peripheral areas. Peripheral metropolitan areas are loosely connected or even disconnected with each other. This dissertation provides empirical evidence to support the argument that technological collaboration reveals a network-based system associated with different or even distant geographical places, which is somewhat different from the conventional theory of localized knowledge spillovers that once dominated understanding of the role of geography in technological advance.
ContributorsLee, Der-Shiuan (Author) / Ó Huallacháin, Breandán (Thesis advisor) / Anselin, Luc (Committee member) / Kuby, Michael (Committee member) / Lobo, Jose (Committee member) / Arizona State University (Publisher)
Created2011
Description
In today's world, unprecedented amounts of data of individual mobile objects have become more available due to advances in location aware technologies and services. Studying the spatio-temporal patterns, processes, and behavior of mobile objects is an important issue for extracting useful information and knowledge about mobile phenomena. Potential applications across a wide range of fields include urban and transportation planning, Location-Based Services, and logistics. This research is designed to contribute to the existing state-of-the-art in tracking and modeling mobile objects, specifically targeting three challenges in investigating spatio-temporal patterns and processes; 1) a lack of space-time analysis tools; 2) a lack of studies about empirical data analysis and context awareness of mobile objects; and 3) a lack of studies about how to evaluate and test agent-based models of complex mobile phenomena. Three studies are proposed to investigate these challenges; the first study develops an integrated data analysis toolkit for exploration of spatio-temporal patterns and processes of mobile objects; the second study investigates two movement behaviors, 1) theoretical random walks and 2) human movements in urban space collected by GPS; and, the third study contributes to the research challenge of evaluating the form and fit of Agent-Based Models of human movement in urban space. The main contribution of this work is the conceptualization and implementation of a Geographic Knowledge Discovery approach for extracting high-level knowledge from low-level datasets about mobile objects. This allows better understanding of space-time patterns and processes of mobile objects by revealing their complex movement behaviors, interactions, and collective behaviors. In detail, this research proposes a novel analytical framework that integrates time geography, trajectory data mining, and 3D volume visualization. In addition, a toolkit that utilizes the framework is developed and used for investigating theoretical and empirical datasets about mobile objects. The results showed that the framework and the toolkit demonstrate a great capability to identify and visualize clusters of various movement behaviors in space and time.
ContributorsNara, Atsushi (Author) / Torrens, Paul M. (Thesis advisor) / Myint, Soe W (Committee member) / Kuby, Michael (Committee member) / Griffin, William A. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Defines the concept of the arcology as conceived by architect Paolo Soleri. Arcology combines "architecture" and "ecology" and explores a visionary notion of a self-contained urban community that has agricultural, commercial, and residential facilities under one roof. Two real-world examples of these projects are explored: Arcosanti, AZ and Masdar City, Abu Dhabi, UAE. Key aspects of the arcology that could be applied to an existing urban fabric are identified, such as urban design fostering social interaction, reduction of automobile dependency, and a development pattern that combats sprawl. Through interviews with local representatives, a holistic approach to applying arcology concepts to the Phoenix Metro Area is devised.
ContributorsSpencer, Sarah Anne (Author) / Manuel-Navarrete, David (Thesis director) / Salon, Deborah (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Sustainability (Contributor)
Created2015-05
Description
The objective of this dissertation is to empirically analyze the results of the retail location decision making process and how chain networks evolve given their value platform. It employs one of the largest cross-sectional databases of retailers ever assembled, including 50 US retail chains and over 70,000 store locations. Three closely related articles, which develop new theory explaining location deployment and behaviors of retailers, are presented. The first article, "Regionalism in US Retailing," presents a comprehensive spatial analysis of the domestic patterns of retailers. Geographic Information Systems (GIS) and statistics examine the degree to which the chains are deployed regionally versus nationally. Regional bias is found to be associated with store counts, small market deployment, and the location of the founding store, but not the age of the chain. Chains that started in smaller markets deploy more stores in other small markets and vice versa for chains that started in larger markets. The second article, "The Location Types of US Retailers," is an inductive analysis of the types of locations chosen by the retailers. Retail locations are classified into types using cluster analysis on situational and trade area data at the geographical scale of the individual stores. A total of twelve distinct location types were identified. A second cluster analysis groups together the chains with the most similar location profiles. Retailers within the same retail business often chose similar types of locations and were placed in the same clusters. Retailers generally restrict their deployment to one of three overall strategies including metropolitan, large retail areas, or market size variety. The third article, "Modeling Retail Chain Expansion and Maturity through Wave Analysis: Theory and Application to Walmart and Target," presents a theory of retail chain expansion and maturity whereby retailers expand in waves with alternating periods of faster and slower growth. Walmart diffused gradually from Arkansas and Target grew from the coasts inward. They were similar, however, in that after expanding into an area they reached a point of saturation and opened fewer stores, then moved on to other areas, only to revisit the earlier areas for new stores.
ContributorsJoseph, Lawrence (Author) / Kuby, Michael (Thesis advisor) / Matthews, Richard (Committee member) / Ó Huallacháin, Breandán (Committee member) / Kumar, Ajith (Committee member) / Arizona State University (Publisher)
Created2013
Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The contemporary architectural pedagogy is far removed from its ancestry: the classical Beaux-Arts and polytechnic schools of the 19th century and the Bauhaus and Vkhutemas models of the modern period. Today, the "digital" has invaded the academy and shapes pedagogical practices, epistemologies, and ontologies within it, and this invasion is reflected in teaching practices, principles, and tools. Much of this digital integration goes unremarked and may not even be explicitly taught. In this qualitative research project, interviews with 18 leading architecture lecturers, professors, and deans from programs across the United States were conducted. These interviews focused on advanced practices of digital architecture, such as the use of digital tools, and how these practices are viewed. These interviews yielded a wealth of information about the uses (and abuses) of advanced digital technologies within the architectural academy, and the results were analyzed using the methods of phenomenology and grounded theory. Most schools use digital technologies to some extent, although this extent varies greatly. While some schools have abandoned hand-drawing and other hand-based craft almost entirely, others have retained traditional techniques and use digital technologies sparingly. Reasons for using digital design processes include industry pressure as well as the increased ability to solve problems and the speed with which they could be solved. Despite the prevalence of digital design, most programs did not teach related design software explicitly, if at all, instead requiring students (especially graduate students) to learn to use them outside the design studio. Some of the problems with digital design identified in the interviews include social problems such as alienation as well as issues like understanding scale and embodiment of skill.
ContributorsAlqabandy, Hamad (Author) / Brandt, Beverly (Thesis advisor) / Mesch, Claudia (Committee member) / Newton, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Description
Measuring the success of a transportation project as it is envisioned in the Regional Transportation Plan (RTP) and is detailed in an Environmental Impact Statement (EIS) is not part of any current planning process, for a post construction analysis may have political consequences for the project participants, would incur additional costs, and may be difficult to define in terms of scope. With local, state and federal budgets shrinking, funding sources are demanding that the performance of a project be evaluated and project stakeholders be held accountable. The Transportation Research Board (TRB) developed a framework that allows transportation agencies to customize their reporting so that a project's performance can be measured. In the case of the Red Mountain Freeway, the selected performance measure allows for comparing the population forecasts, the traffic volumes, and the project costs defined in the final EIS to actual population growth, actual average annual daily traffic (ADT), and actual project costs obtained from census data, the City of Mesa, and contractor bids, respectively. The results show that population projections for both Maricopa County and the City of Mesa are within less than half a percent of the actual annual population growth. The traffic analysis proved more difficult due to inconsistencies within the EIS documents, variations in the local arterials used to produce traffic volume, and in the projection time-spans. The comparison for the total increase in traffic volume generated a difference of 11.34 percent and 89.30 percent. An adjusted traffic volume equal to all local arterials and US 60 resulted in a difference of 40 percent between the projected and actual ADT values. As for the project cost comparison, not only were the costs within the individual documents inconsistent, but they were underestimated by as much as 75 percent. Evaluating the goals as described in an EIS document using the performance measure guidelines provided by the TRB may provide the tool that can help promote conflict resolution for political issues that arise, streamline the planning process, and measure the performance of the transportation system, so that lessons learned can be applied to future projects.
ContributorsKizior, Angelika (Author) / Golub, Aaron (Thesis advisor) / Kuby, Michael (Committee member) / Wentz, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2012
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012