Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Description
This study estimates the capitalization effect of golf courses in Maricopa County using the hedonic pricing method. It draws upon a dataset of 574,989 residential transactions from 2000 to 2006 to examine how the aesthetic, non-golf benefits of golf courses capitalize across a gradient of proximity measures. The measures for

This study estimates the capitalization effect of golf courses in Maricopa County using the hedonic pricing method. It draws upon a dataset of 574,989 residential transactions from 2000 to 2006 to examine how the aesthetic, non-golf benefits of golf courses capitalize across a gradient of proximity measures. The measures for amenity value extend beyond home adjacency and include considerations for homes within a range of discrete walkability buffers of golf courses. The models also distinguish between public and private golf courses as a proxy for the level of golf course access perceived by non-golfers. Unobserved spatial characteristics of the neighborhoods around golf courses are controlled for by increasing the extent of spatial fixed effects from city, to census tract, and finally to 2000 meter golf course ‘neighborhoods.’ The estimation results support two primary conclusions. First, golf course proximity is found to be highly valued for adjacent homes and homes up to 50 meters way from a course, still evident but minimal between 50 and 150 meters, and insignificant at all other distance ranges. Second, private golf courses do not command a higher proximity premia compared to public courses with the exception of homes within 25 to 50 meters of a course, indicating that the non-golf benefits of courses capitalize similarly, regardless of course type. The results of this study motivate further investigation into golf course features that signal access or add value to homes in the range of capitalization, particularly for near-adjacent homes between 50 and 150 meters thought previously not to capitalize.
ContributorsJoiner, Emily (Author) / Abbott, Joshua (Thesis director) / Smith, Kerry (Committee member) / Economics Program in CLAS (Contributor) / School of Sustainability (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
In recent years, environment mapping has garnered significant interest in both industrial and academic settings as a viable means of generating comprehensive virtual models of the physical world. These maps are created using simultaneous localization and mapping (SLAM) algorithms that combine depth contours with visual imaging information to create rich,

In recent years, environment mapping has garnered significant interest in both industrial and academic settings as a viable means of generating comprehensive virtual models of the physical world. These maps are created using simultaneous localization and mapping (SLAM) algorithms that combine depth contours with visual imaging information to create rich, layered point clouds. Given the recent advances in virtual reality technology, these generated point clouds can be imported onto the Oculus Rift or similar headset for virtual reality implementation. This project deals with the robotic implementation of RGB-D SLAM algorithms on mobile ground robots to generate complete point clouds that can be processed off-line and imported into virtual reality engines for viewing in the Oculus Rift. This project uses a ground robot along with a Kinect sensor to collect RGB-D data of the surrounding environment to build point cloud maps using SLAM software. These point clouds are then exported as object or polygon files for post-processing in software engines such as Meshlab or Unity. The point clouds generated from the SLAM software can be viewed in the Oculus Rift as is. However, these maps are mainly empty space and can be further optimized for virtual viewing. Additional techniques such as meshing and texture meshing were implemented on the raw point cloud maps and tested on the Oculus Rift. The aim of this project was to increase the potential applications for virtual reality by taking a robotic mapping approach to virtual reality environment development. This project was successful in achieving its objective. The following report details the processes used in developing a remotely-controlled robotic platform that can scan its environment and generate viable point cloud maps. These maps are then processed off line and ported into virtual reality software for viewing through the Oculus Rift.
ContributorsUdupa, Shreya (Author) / Artemiadis, Panagiotis (Thesis director) / Chickamenahalli, Shamala (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description
Yearly changes in the consumer price index are used to adjust social security benefits in order to keep the purchasing power of social security beneficiaries the same. Currently, social security benefits are adjusted using a fixed-weighted price index that reflects the purchasing patterns of workers. However, some believe that a

Yearly changes in the consumer price index are used to adjust social security benefits in order to keep the purchasing power of social security beneficiaries the same. Currently, social security benefits are adjusted using a fixed-weighted price index that reflects the purchasing patterns of workers. However, some believe that a price index that captures the spending habits of the elderly should adjust monthly social security benefits, while others argue that a chain-weighted price index is a more accurate indexation technique. This report finds that if an elderly or chain-weighted price index were implemented this year, there would not be a significant change in the projected insolvency of the social security trust fund, but there could be a substantial decrease in the social security trust fund's yearly cash-flow deficit. Therefore, changing the indexation of social security benefits should not be seen as a short-term solvency fix. Instead, adjusting monthly social security benefits should be about keeping the purchasing power of beneficiaries relatively the same.
ContributorsScobas, Peter Jonathan (Author) / Hobijn, Bart (Thesis director) / Smith, Kerry (Committee member) / Economics Program in CLAS (Contributor) / School of Sustainability (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05