Barrett, The Honors College Thesis/Creative Project Collection
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.
Our study surveyed 43 DFS users to determine how they began playing DFS, what they like about DFS, and what they dislike about DFS. From the data collected, it was determined that TFS and DFS users are similar in their competitive nature, in their increased levels of sports consumption and investment, and in their increased favoritism towards individual players over teams. The main differences between TFS and DFS users were how each felt they were at a disadvantage, the levels of camaraderie within the sport, and their stance on gambling. TFS users felt their disadvantages came from lackluster commissioners while DFS users felt that the companies themselves were setting them at a disadvantage. TFS users placed more value on the camaraderie and social sport while DFS users placed more value on profit and excitement. TFS users felt that TFS was not gambling and that DFS was, while DFS users accepted DFS as gambling.
To achieve this goal, a model of swarm robots transportation should be designed, which is cruise control for this scenario. Secondly, based on free body diagram, force equilibrium equation can be deduced. Then, the function of plant can be deduced based on cruise control and force equilibrium equations. Thirdly, list potential controllers, which may implement desired controls of swarm robots, and test their performance. Modify value of gains and do simulations of these controller. After analyzing results of simulation, the best controller can be selected.
In the last section, there is conclusion of entire thesis project and pointing out future work. The section of future work will mention potential difficulties of building entire control system, which allow swarm robots transport over inclines in real environment.
It's a book about two people from two very different cultures, but have a shared experience growing up. Atinuke is a Nigerian girl who grew up in well-to-do home, but lived with an abusive father. Noah, on the other hand, is a white American boy who also grew up in a model home with very rich parents and a long line of rich ancestors. However, his parents are not on talking terms, his mother is dependent on him for her happiness and he has no relationship with his father. Once the two protagonists break away from their respective prisons, they meet, they learn from each other and they develop a bond.
Women’s roles in society have changed significantly throughout the years. The movement to support the rights of women has been ongoing throughout the evolution of society but has been especially prevalent in the last century. The 1960s are when women began to enter the workforce instead of being limited to presuming roles as homemakers. Since that point in time, women have continued to thrive in the workforce and have pursued a larger variety of positions in various fields. Even though the opportunities for women continue to grow, there still seems to be an underrepresentation of women in science, technology, engineering, and mathematics (STEM) related fields. The underrepresentation of women pursuing physician and entrepreneurship roles in STEM will be analyzed and the challenges this group of people specifically encounter will be examined. Our first proposal to encourage women to enter STEM focuses on middle-school initiatives and incubator programs. The second proposal, based on commonalities females face within the workforce, is finding a better work/home life balance with the development of new maternity/paternity leave policies. Through these initiatives, we believe that the gender gap in STEM can be bridged.
Women’s roles in society have changed significantly throughout the years. The movement to support the rights of women has been ongoing throughout the evolution of society but has been especially prevalent in the last century. The 1960s are when women began to enter the workforce instead of being limited to presuming roles as homemakers. Since that point in time, women have continued to thrive in the workforce and have pursued a larger variety of positions in various fields. Even though the opportunities for women continue to grow, there still seems to be an underrepresentation of women in science, technology, engineering, and mathematics (STEM) related fields. The underrepresentation of women pursuing physician and entrepreneurship roles in STEM will be analyzed and the challenges this group of people specifically encounter will be examined. Our first proposal to encourage women to enter STEM focuses on middle-school initiatives and incubator programs. The second proposal, based on commonalities females face within the workforce, is finding a better work/home life balance with the development of new maternity/paternity leave policies. Through these initiatives, we believe that the gender gap in STEM can be bridged.
Artificial Intelligence’s facial recognition programs are inherently racially biased. The programs are not necessarily created with the intent to disproportionately impact marginalized communities, but through their data mining process of learning, they can become biased as the data they use may train them to think in a biased manner. Biased data is difficult to spot as the programming field is homogeneous and this issue reflects underlying societal biases. Facial recognition programs do not identify minorities at the same rate as their Caucasian counterparts leading to false positives in identifications and an increase of run-ins with the law. AI does not have the ability to role-reverse judge as a human does and therefore its use should be limited until a more equitable program is developed and thoroughly tested.