Open Access. Powered by Scholars. Published by Universities.®
- Keyword
Articles 1 - 3 of 3
Full-Text Articles in Engineering
Artificial Intelligence Applications For Social Science Research, Megan Stubbs-Richardson, Lauren Brown, Mackenzie Paul, Devon Brenner
Artificial Intelligence Applications For Social Science Research, Megan Stubbs-Richardson, Lauren Brown, Mackenzie Paul, Devon Brenner
Social Science Research Center Publications and Scholarship
Our team developed a database of 250 Artificial Intelligence (AI) applications useful for social science research. To be included in our database, the AI tool had to be useful for: 1) literature reviews, summaries, or writing, 2) data collection, analysis, or visualizations, or 3) research dissemination. In the database, we provide a name, description, and links to each of the AI tools that were current at the time of publication on September 29, 2023. Supporting links were provided when an AI tool was found using other databases. To help users evaluate the potential usefulness of each tool, we documented information …
An Exploration In The Tools Of Options Pricing - Data, Ryan Hinson, Chris Schroeder
An Exploration In The Tools Of Options Pricing - Data, Ryan Hinson, Chris Schroeder
2021 Celebration of Student Scholarship - Oral Presentations
Stock options can be a useful tool in any investor’s portfolio. They allow the skilled investor to increase their leverage and possibility for a higher payout with less risk. However, they are only beneficial if the investor knows how to use them, and if they accurately reflect the price of the option. This presentation hopes to offer some insight into the binomial method of options pricing along with new adjustments to the model in hopes of reflecting a more accurate options price. This, along with the Monte Carlo simulation presented, will hopefully offer some insight into the mathematical investor’s toolbox.
Requirements Engineering Education Slr Data Set 1988-2020, Marian Daun, Alicia M. Grubb, Bastian Tenbergen
Requirements Engineering Education Slr Data Set 1988-2020, Marian Daun, Alicia M. Grubb, Bastian Tenbergen
Data
Requirements Engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or exceeding budgets of software development projects. Therefore, it is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. However, to date there exists no central dataset for RE Education articles. To lay the foundation for this important mission, we conducted a systematic literature review. In this dataset, we present 152 articles from the Requirements Engineering …