Matching Items (104)
Description
Farmers' markets are a growing trend both in Arizona and the broader U.S., as many recognize them as desirable alternatives to the conventional food system. As icons of sustainability, farmers' markets are touted as providing many environmental, social, and economic benefits, but evidence is mounting that local food systems primarily serve the urban elite, with relatively few low-income or minority customers. However, the economic needs of the market and its vendors often conflict with those of consumers. While consumers require affordable food, farmers need to make a profit. How farmers' markets are designed and governed can significantly influence the extent to which they can meet these needs. However, very little research explores farmers' market design and governance, much less its capacity to influence financial success and participation for underprivileged consumers. The present study examined this research gap by addressing the following research question: How can farmers' markets be institutionally designed to increase the participation of underprivileged consumers while maintaining a financially viable market for local farmers? Through a comparative case study of six markets, this research explored the extent to which farmers' markets in Central Arizona currently serve the needs of farmer-vendors and underprivileged consumers. The findings suggest that while the markets serve as a substantial source of income for some vendors, participation by low-income and minority consumers remains low, and that much of this appears to be due to cultural barriers to access. Management structures, site characteristics, market layout, community programs, and staffing policies are key institutional design features, and the study explores how these can be leveraged to better meet the needs of the diverse participants while improving the markets' financial success.
ContributorsTaylor, Carissa (Author) / Aggarwal, Rimjhim (Thesis advisor) / York, Abigail (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2013
Description
During the months from June to November 2012, the city of Bangalore was faced with a serious solid waste management (SWM) crisis. In the wake of the upheaval, the state court declared source segregation to be mandatory. Yet, while the legislation was clear, the pathway towards a course of action for the transition was not clear and hence, Bangalore was stuck in a state of limbo. The objectives for this thesis spiraled organically from this crisis. The first objective was to examine the gaps in Bangalore's transition to a more sustainable SWM system. Six particular gaps were identified, which in essence, were opportunities to re-shape the system. The gaps identified included: conflicting political agendas, the exclusion of some key actors, and lack of adequate attention to cultural aspects, provision of appropriate incentives, protection of livelihoods and promotion of innovation. Opportunities were found in better incentivization of sustainable SWM goals, protecting livelihoods that depend on waste, enhancing innovation and endorsing local, context based SWM solutions. Building on this understanding of gaps, the second objective was to explore an innovative, local, bottom-up waste-management model called the Vellore Zero Waste Model, and assess its applicability to Bangalore. The adaptability of the model depended on several factors such as, willingness of actors to redefine their roles and change functions, ability of the municipality to assure quality and oversight, willingness of citizen to source segregate, and most importantly, the political will and collective action needed to ensure and sustain the transition. The role of communication as a vital component to facilitate productive stakeholder engagement and to promote role change was evident. Therefore, the third objective of the study was to explore how interpersonal competencies and communication strategies could be used as a tool to facilitate stakeholder engagement and encourage collective action. In addressing these objectives, India was compared with Austria because Austria is often cited as having some of the best SWM practices in the world and has high recycling rates to show for its reputation.
ContributorsRengarajan, Nivedita (Author) / Aggarwal, Rimjhim (Thesis advisor) / Chhetri, Nalini (Committee member) / Manuel-Navarrete, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Childhood obesity has been on the rise for the past decade, and it has been hypothesized that students' food choices may be influenced by easy access to food outlets near their schools that provide unhealthful options. But the results of recent studies on the relationship between the food environment around schools and student weight status are mixed and often contradictory. Most studies have used measures of weight and height that were self-reported by students, or have relied on data from a relatively small sample of students. I examine the association between weight status among school students and the food environment surrounding their schools using professionally-measured, student-level data across the full school-age spectrum. De-identified data were obtained for over 30,000 K-12 students in 79 public schools located in four New Jersey cities. Locations of alternative food-outlets (specifically, supermarkets, convenience stores, small grocery stores, and limited-service restaurants) were obtained from commercial sources and geocoded to develop proximity measures. A simplified social-ecological framework was used to conceptualize the multi-level the association between students' BMI and school proximity to food outlets and multivariate analyses were used to estimate this relationship controlling for student- and school-level factors. Over twenty percent of the students were obese, compared to the national average at 17% (Ogden, Carroll, Kit, & Flegal, 2012). On average, students had 2.6 convenience stores, 2.9 limited-service restaurants, and 0.1 supermarkets within a quarter mile of their school. This study suggests that easy access to small grocery stores (which this study uniquely examines as a separate food outlet category) that offer healthy choices including five types of fresh vegetable, five types of fresh fruits, low-fat dairy, and lean meats is associated with lower BMI z score and lower probability of being obese for middle and high school students. This suggests that improving access to such small food outlets may be a promising area for future investigation in obesity mitigation research. Also, this study separates students of pre-schools, kindergartens and elementary schools (neighborhood schools) from that of the middle and high schools (non-neighborhood) schools because the two groups of schools have different neighborhood characteristics, as well as open-school and bussing policies that result in different levels of exposure that students have to the food outlets around the schools. The result of this study suggests that the relationship between students' weight outcomes and food environment around schools is different in the two groups of schools.
ContributorsTang, Xuyang (Author) / Abbott, Joshua K (Thesis advisor) / Ohri-Vachaspati, Punam (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Arizona State University (Publisher)
Created2013
Description
Energy is a central concern of sustainability because how we produce and consume energy affects society, economy, and the environment. Sustainability scientists are interested in energy transitions away from fossil fuels because they are nonrenewable, increasingly expensive, have adverse health effects, and may be the main driver of climate change. They see an opportunity for developing countries to avoid the negative consequences fossil-fuel-based energy systems, and also to increase resilience, by leap-frogging-over the centralized energy grid systems that dominate the developed world. Energy transitions pose both challenges and opportunities. Obstacles to transitions include 1) an existing, centralized, complex energy-grid system, whose function is invisible to most users, 2) coordination and collective-action problems that are path dependent, and 3) difficulty in scaling up RE technologies. Because energy transitions rely on technological and social innovations, I am interested in how institutional factors can be leveraged to surmount these obstacles. The overarching question that underlies my research is: What constellation of institutional, biophysical, and social factors are essential for an energy transition? My objective is to derive a set of "design principles," that I term institutional drivers, for energy transitions analogous to Ostrom's institutional design principles. My dissertation research will analyze energy transitions using two approaches: applying the Institutional Analysis and Development Framework and a comparative case study analysis comprised of both primary and secondary sources. This dissertation includes: 1) an analysis of the world's energy portfolio; 2) a case study analysis of five countries; 3) a description of the institutional factors likely to promote a transition to renewable-energy use; and 4) an in-depth case study of Thailand's progress in replacing nonrenewable energy sources with renewable energy sources. My research will contribute to our understanding of how energy transitions at different scales can be accomplished in developing countries and what it takes for innovation to spread in a society.
ContributorsKoster, Auriane Magdalena (Author) / Anderies, John M (Thesis advisor) / Aggarwal, Rimjhim (Committee member) / Van Der Leeuw, Sander (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
With the rapid development of mobile sensing technologies like GPS, RFID, sensors in smartphones, etc., capturing position data in the form of trajectories has become easy. Moving object trajectory analysis is a growing area of interest these days owing to its applications in various domains such as marketing, security, traffic monitoring and management, etc. To better understand movement behaviors from the raw mobility data, this doctoral work provides analytic models for analyzing trajectory data. As a first contribution, a model is developed to detect changes in trajectories with time. If the taxis moving in a city are viewed as sensors that provide real time information of the traffic in the city, a change in these trajectories with time can reveal that the road network has changed. To detect changes, trajectories are modeled with a Hidden Markov Model (HMM). A modified training algorithm, for parameter estimation in HMM, called m-BaumWelch, is used to develop likelihood estimates under assumed changes and used to detect changes in trajectory data with time. Data from vehicles are used to test the method for change detection. Secondly, sequential pattern mining is used to develop a model to detect changes in frequent patterns occurring in trajectory data. The aim is to answer two questions: Are the frequent patterns still frequent in the new data? If they are frequent, has the time interval distribution in the pattern changed? Two different approaches are considered for change detection, frequency-based approach and distribution-based approach. The methods are illustrated with vehicle trajectory data. Finally, a model is developed for clustering and outlier detection in semantic trajectories. A challenge with clustering semantic trajectories is that both numeric and categorical attributes are present. Another problem to be addressed while clustering is that trajectories can be of different lengths and also have missing values. A tree-based ensemble is used to address these problems. The approach is extended to outlier detection in semantic trajectories.
ContributorsKondaveeti, Anirudh (Author) / Runger, George C. (Thesis advisor) / Mirchandani, Pitu (Committee member) / Pan, Rong (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data mining, machine learning, and geovisualization techniques. Three different types of spatiotemporal activity data were collected through different data collection approaches: (1) crowd sourced geo-tagged digital photos, representing people's travel activity, were retrieved from the website Panoramio.com through information retrieval techniques; (2) the same techniques were used to crawl crowd sourced GPS trajectory data and related metadata of their daily activities from the website OpenStreetMap.org; and finally (3) preschool children's daily activities and interactions tagged with time and geographical location were collected with a novel TabletPC-based behavioral coding system. The proposed methodology is applied to these data to (1) automatically recommend optimal multi-day and multi-stay travel itineraries for travelers based on discovered attractions from geo-tagged photos, (2) automatically detect movement types of unknown moving objects from GPS trajectories, and (3) explore dynamic social and socio-spatial patterns of preschool children's behavior from both geographic and social perspectives.
ContributorsLi, Xun (Author) / Anselin, Luc (Thesis advisor) / Koschinsky, Julia (Committee member) / Maciejewski, Ross (Committee member) / Rey, Sergio (Committee member) / Griffin, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
This document presents a new implementation of the Smoothed Particles Hydrodynamics algorithm using DirectX 11 and DirectCompute. The main goal of this document is to present to the reader an alternative solution to the largely studied and researched problem of fluid simulation. Most other solutions have been implemented using the NVIDIA CUDA framework; however, the proposed solution in this document uses the Microsoft general-purpose computing on graphics processing units API. The implementation allows for the simulation of a large number of particles in a real-time scenario. The solution presented here uses the Smoothed Particles Hydrodynamics algorithm to calculate the forces within the fluid; this algorithm provides a Lagrangian approach for discretizes the Navier-Stockes equations into a set of particles. Our solution uses the DirectCompute compute shaders to evaluate each particle using the multithreading and multi-core capabilities of the GPU increasing the overall performance. The solution then describes a method for extracting the fluid surface using the Marching Cubes method and the programmable interfaces exposed by the DirectX pipeline. Particularly, this document presents a method for using the Geometry Shader Stage to generate the triangle mesh as defined by the Marching Cubes method. The implementation results show the ability to simulate over 64K particles at a rate of 900 and 400 frames per second, not including the surface reconstruction steps and including the Marching Cubes steps respectively.
ContributorsFigueroa, Gustavo (Author) / Farin, Gerald (Thesis advisor) / Maciejewski, Ross (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as: visual boosting to allow for quicker consumption of large data sets, the bond energy algorithm to find finer patterns and anomalies through contrast, multi-dimensional scaling, flow lines, user guided clustering, and row-column ordering. User input is applied on precomputed data sets to provide for real time interaction. General applicability of the techniques are tested against industrial trade, social networking, financial, and sparse data sets of varying dimensionality.
ContributorsHayden, Thomas (Author) / Maciejewski, Ross (Thesis advisor) / Wang, Yalin (Committee member) / Runger, George C. (Committee member) / Mack, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2014