Matching Items (17)
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- All Subjects: Technology
- Creators: Department of Psychology
Description
Company X has developed RealSenseTM technology, a depth sensing camera that provides machines the ability to capture three-dimensional spaces along with motion within these spaces. The goal of RealSense was to give machines human-like senses, such as knowing how far away objects are and perceiving the surrounding environment. The key issue for Company X is how to commercialize RealSense's depth recognition capabilities. This thesis addresses the problem by examining which markets to address and how to monetize this technology. The first part of the analysis identified potential markets for RealSense. This was achieved by evaluating current markets that could benefit from the camera's gesture recognition, 3D scanning, and depth sensing abilities. After identifying seven industries where RealSense could add value, a model of the available, addressable, and obtainable market sizes was developed for each segment. Key competitors and market dynamics were used to estimate the portion of the market that Company X could capture. These models provided a forecast of the discounted gross profits that could be earned over the next five years. These forecasted gross profits, combined with an examination of the competitive landscape and synergistic opportunities, resulted in the selection of the three segments thought to be most profitable to Company X. These segments are smart home, consumer drones, and automotive. The final part of the analysis investigated entrance strategies. Company X's competitive advantages in each space were found by examining the competition, both for the RealSense camera in general and other technologies specific to each industry. Finally, ideas about ways to monetize RealSense were developed by exploring various revenue models and channels.
ContributorsDunn, Nicole (Co-author) / Boudreau, Thomas (Co-author) / Kinzy, Chris (Co-author) / Radigan, Thomas (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / WPC Graduate Programs (Contributor) / Department of Psychology (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Science (Contributor) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation study. This research seeks to determine the acquisition processes that contribute significantly to total simulated program time in the acquisition system for all programs reaching Milestone C. Specifically, this research examines the effect of increased scope management, technology maturity, and decreased variation and mean process times in post-Design Readiness Review contractor activities by performing additional simulation analyses. Potential policies are formulated from the results to further improve program acquisition completion time.
ContributorsWorger, Danielle Marie (Author) / Wu, Teresa (Thesis director) / Shunk, Dan (Committee member) / Wirthlin, J. Robert (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
Telemedicine is a multipurpose tool that allows medical professionals to use technology as a means to evaluate, diagnose, and treat patients remotely. This paper focuses on the challenges that developing telemedicine programs face, specifically discussing target population, user experience, and physician adoption. Various users of telemedicine share their experiences overcoming such challenges with the greater goal of this paper being to facilitate the growth of telemedicine programs.
ContributorsPalakodaty, Shivani Venkatasri (Author) / Liss, Julie (Thesis director) / Berisha, Visar (Committee member) / School of International Letters and Cultures (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
In this study, the implementation of educational technology and its effect on learning and user experience is measured. A demographic survey, pretest/posttest, and educational experience survey was used to collect data on the control and experimental groups. The experimental group was subjected to different learning material than the control group with the use of the Elements 4D mobile application by Daqri to learn basic chemical elements and compounds. The control group learning material provided all the exact information as the application, but in the 2D form of a printed packet. It was expected the experimental group would outperform the control group and have a more enjoyable experience and higher performance. After data analysis, it was concluded that the control group outperformed the experimental group on performance and both groups has similar experiences in contradiction to the hypothesis. Once the factors that contribute to the limitations of different study duration, learning the application beforehand, and only-memorization questions are addressed, the study can be conducted again. Application improvements may also alter the future results of the study and hopefully lead to full implementation into a curriculum.
ContributorsApplegate, Garrett Charles (Author) / Atkinson, Robert (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Early adolescence is a pivotal stage of social and emotional development. Socialization traditionally occurs in person, but social interactions via technology (e.g., social media, video games) have grown in popularity. However, little research has been conducted on how early adolescents interact with technology and how these interactions relate to their socialization as well as other factors such as reading habits or academic achievement. Seventh and eighth grade students (n = 719) completed a survey that captured information about their technology use, their academic habits and performance, and extracurricular involvement. It was hypothesized that those involved in more extracurricular activities would use the internet more socially and that internet use would be negatively correlated to both academic performance and recreational reading. Responses indicated that a majority of students have access to technology (e.g. internet, computers, television, gaming consoles, and tablets) in their homes. Social media use differed drastically between platforms. Analyses indicated a relation between amount of extracurricular activities on social television watching and social internet use, but not on social gaming. A significant negative correlation was found between recreational reading and time spent socializing online, but there was no significant effect of these factors on academic performance. Thus, hypotheses were partially supported by the relation between amount of extracurriculars and social internet use and the negative correlation between time spent socializing online and recreational reading.
ContributorsHorner, Kate Elizabeth (Author) / McNamara, Danielle (Thesis director) / McCarthy, Kathryn (Committee member) / Davis, Mary (Committee member) / Division of Teacher Preparation (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Body-worn camera technology is a relatively new player in the field of criminal justice. As much as they are being reported on or discussed, in reality, body-worn cameras have not been in use long enough to have strong empirical support. Recent studies outlined some of the perceived benefits and costs of the body-worn cameras. Research has been done on both officer and citizen perceptions of the cameras, but little has been done in regards to other stakeholders, especially those in the criminal justice system. This study takes 13 interviews of community and criminal justice stakeholders in Tempe, Arizona and examines trends to identify unifying themes. The study found that 11 out of 13 stakeholders believed that the positives of the body-worn cameras outweighed the negatives. There was agreement among the parties that the strongest benefit of the cameras would be the transparency that it provides police departments, while most regarded the largest negative to be a lack of available resources to deal with the amount of data produced. As this is a small qualitative dataset, further research should be conducted about stakeholder perceptions in other cities, as well as solutions to some of the concerns raised by Tempe interviewees.
ContributorsArenas, Lauren (Author) / White, Michael (Thesis director) / Gaub, Janne (Committee member) / Department of Psychology (Contributor) / School of Criminology and Criminal Justice (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Smart cities ""utilize information and communication technologies with the aim to increase the life quality of their inhabitants while providing sustainable development"". The Internet of Things (IoT) allows smart devices to communicate with each other using wireless technology. IoT is by far the most important component in the development of smart cities. Company X is a leader in the semiconductor industry looking to grow its revenue in the IoT space. This thesis will address how Company X can deliver IoT solutions to government municipalities with the goal of simultaneously increasing revenue through value-added engagement and decreasing spending by more efficiently managing infrastructure upgrades.
ContributorsJiang, Yichun (Co-author) / Davidoff, Eric (Co-author) / Dawoud, Mariam (Co-author) / Rodenbaugh, Ryan (Co-author) / Sinclair, Brynn (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Psychology (Contributor) / School of Sustainability (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The widespread use of statistical analysis in sports-particularly Baseball- has made it increasingly necessary for small and mid-market teams to find ways to maintain their analytical advantages over large market clubs. In baseball, an opportunity for exists for teams with limited financial resources to sign players under team control to long-term contracts before other teams can bid for their services in free agency. If small and mid-market clubs can successfully identify talented players early, clubs can save money, achieve cost certainty and remain competitive for longer periods of time. These deals are also advantageous to players since they receive job security and greater financial dividends earlier in their career. The objective of this paper is to develop a regression-based predictive model that teams can use to forecast the performance of young baseball players with limited Major League experience. There were several tasks conducted to achieve this goal: (1) Data was obtained from Major League Baseball and Lahman's Baseball Database and sorted using Excel macros for easier analysis. (2) Players were separated into three positional groups depending on similar fielding requirements and offensive profiles: Group I was comprised of first and third basemen, Group II contains second basemen, shortstops, and center fielders and Group III contains left and right fielders. (3) Based on the context of baseball and the nature of offensive performance metrics, only players who achieve greater than 200 plate appearances within the first two years of their major league debut are included in this analysis. (4) The statistical software package JMP was used to create regression models of each group and analyze the residuals for any irregularities or normality violations. Once the models were developed, slight adjustments were made to improve the accuracy of the forecasts and identify opportunities for future work. It was discovered that Group I and Group III were the easiest player groupings to forecast while Group II required several attempts to improve the model.
ContributorsJack, Nathan Scott (Author) / Shunk, Dan (Thesis director) / Montgomery, Douglas (Committee member) / Borror, Connie (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
In 2010, for the first time in human history, more than half of the world's total population lived in cities; this number is expected to increase to 60% or more by 2050. The goal of this research effort is to create a comprehensive model and modelling framework for megacities, middleweight cities, and urban agglomerations, collectively referred to as dense urban areas. The motivation for this project comes from the United States Army's desire for readiness in all operating environments including dense urban areas. Though there is valuable insight in research to support Army operational behaviors, megacities are of unique interest to nearly every societal sector imaginable. A novel application for determining both main effects and interactive effects between factors within a dense urban area is a Design of Experiments- providing insight on factor causations. Regression Modelling can also be employed for analysis of dense urban areas, providing wide ranging insights into correlations between factors and their interactions. Past studies involving megacities concern themselves with general trend of cities and their operation. This study is unique in its efforts to model a singular megacity to enable decision support for military operational planning, as well as potential decision support to city planners to increase the sustainability of these dense urban areas and megacities.
ContributorsMathesen, Logan Michael (Author) / Zenzen, Frances (Thesis director) / Jennings, Cheryl (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This project uses SAS (Statistical Analysis Software) to create a regression model that provides a prediction for which NFL playoff team will win the Super Bowl in a given year.
ContributorsOleksyn, Alexander (Author) / Schneider, Laurence (Thesis director) / Hansen, Whitney (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2023-05