Matching Items (7)
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- All Subjects: artificial intelligence
- All Subjects: Open Source
- Creators: Meuth, Ryan
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
Description
Debate provides a valuable educational opportunity for students to learn a variety of portable research and public speaking skills, but many of its goals are hindered by the lack of a dedicated software. Currently, the primary tool for research and presentation of evidence is paperlessdebate.com's Verbatim, which is built as a template for Microsoft Word. While functional, Verbatim suffers from several shortcomings; its reliance on Word means that it cannot be fully cross-platform, and it also means that it is difficult to streamline Verbatim's workflow for the particular needs of debaters. Thus, the goal of this project was to fill the need for a stand-alone, cross platform application that debaters (and coaches) can use to research and present evidence. The bulk of the project consisted of creating a specialized editor, including a variety of features catered towards usability in a range of debate contexts. Additionally, the software is integrated with a back end database such that it can also replace the mixture of storage solutions (such as Dropbox and Microsoft's OneDrive) that teams currently use to maintain and share their data. In order to make the software more extensible and to improve its accessibility, it is released as free open source software under the GNU General Public License v3.0. This paper describes the core features of the application and the motivation behind those features' implementations, and briefly includes a discussion of the companion mobile app for Android devices. It also reviews the technologies that were used to create the software's implementation.
ContributorsRedman, Colin (Author) / Symonds, Adam (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience connected to the same battery supply. Plus, almost all conventional electric boards come with proprietary software and hardware designs, meaning that modifying or improving upon their logic is extremely difficult if not impossible. Therefore, our group aims to prototype an improved, open-source electric skateboard design to determine the feasibility of our ideas.
ContributorsGarcia, Brendan (Author) / Woodburne, Ian (Co-author) / Meuth, Ryan (Thesis director) / Michael, Katina (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
Personal electric vehicles, or PEVs, help individuals navigate short to mid distance commutes in environments that lack effective public transportation solutions. This is known as the “Last Mile” problem. A particular solution, electric skateboards, are highly energy efficient due to their size but lack auxiliary features for safety and user-convenience connected to the same battery supply. Plus, almost all conventional electric boards come with proprietary software and hardware designs, meaning that modifying or improving upon their logic is extremely difficult if not impossible. Therefore, our group aims to prototype an improved, open-source electric skateboard design to determine the feasibility of our ideas.
ContributorsWoodburne, Ian (Author) / Garcia, Brendan (Co-author) / Meuth, Ryan (Thesis director) / Michael, Katina (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
Artistic expression can be made more accessible through the use of technological interfaces such as auditory analysis, generative artificial intelligence models, and simplification of complicated systems, providing a way for human driven creativity to serve as an input that allow users to creatively express themselves. Studies and testing were done with industry standard performance technology and protocols to create an accessible interface for creative expression. Artificial intelligence models were created to generate art based on simple text inputs. Users were then invited to display their creativity using the software, and a comprehensive performance showcased the potential of the system for artistic expression.
ContributorsPardhe, Joshua (Author) / Lim, Kang Yi (Co-author) / Meuth, Ryan (Thesis director) / Brian, Jennifer (Committee member) / Hermann, Kristen (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
Artistic expression can be made more accessible through the use of technological interfaces such as auditory analysis, generative artificial intelligence models, and simplification of complicated systems, providing a way for human driven creativity to serve as an input that allow users to creatively express themselves. Studies and testing were done with industry standard performance technology and protocols to create an accessible interface for creative expression. Artificial intelligence models were created to generate art based on simple text inputs. Users were then invited to display their creativity using the software, and a comprehensive performance showcased the potential of the system for artistic expression.
ContributorsLim, Kang Yi (Author) / Pardhe, Joshua (Co-author) / Meuth, Ryan (Thesis director) / Brian, Jennifer (Committee member) / Hermann, Kristen (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
Cognitive technology has been at the forefront of the minds of many technology, government, and business leaders, because of its potential to completely revolutionize their fields. Furthermore, individuals in financial statement auditor roles are especially focused on the impact of cognitive technology because of its potential to eliminate many of the tedious, repetitive tasks involved in their profession. Adopting new technologies that can autonomously collect more data from a broader range of sources, turn the data into business intelligence, and even make decisions based on that data begs the question of whether human roles in accounting will be completely replaced. A partial answer: If the ramifications of past technological advances are any indicator, cognitive technology will replace some human audit operations and grow some new and higher order roles for humans. It will shift the focus of accounting professionals to more complex judgment and analysis.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
ContributorsWitkop, David (Author) / Dawson, Gregory (Thesis director) / Munshi, Perseus (Committee member) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05