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Physical Sciences and Mathematics Commons™
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- Machine learning (5)
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- Fraud detection (1)
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Articles 1 - 12 of 12
Full-Text Articles in Physical Sciences and Mathematics
Ai As A License Review Assistant, Nat Gustafson-Sundell
Ai As A License Review Assistant, Nat Gustafson-Sundell
Library Services Publications
I will present the steps we have taken to develop a prototype AI assistant for license review. I’ll explain our criteria for the selection of an AI tool for this project. We reviewed ChatGPT, Claude 2, Bard, and PDF readers. My goal was to develop an initial prototype in a Jupyter Notebook environment so I could easily re-load context information, including a license checklist, but I’ll explain why I revised this goal, instead to linger over license review interactions with ChatBots. I’ll discuss early results, demonstrate example license review interactions, and outline my next steps.
The Library & Generative Ai, Nat Gustafson-Sundell, Mark Mccullough
The Library & Generative Ai, Nat Gustafson-Sundell, Mark Mccullough
Library Services Publications
A demonstration of several AI tools, including ChatGPT, ChatPDF, Consensus, and more. The focus of the session is on potential student uses of the tools and related library initiatives, so we address the limits of ChatGPT as an information source. Librarians can help students learn how to use these tools responsibly and provide leadership on campus as AI is integrated into assignments.
A Machine Learning Approach To Deepfake Detection, Delaney Conrad
A Machine Learning Approach To Deepfake Detection, Delaney Conrad
All Undergraduate Theses and Capstone Projects
The ability to manipulate videos has been around for decades but a process that once would take time, money, and professionals, can now be created by anyone due to the rapid advancement of deepfake technology. Deepfakes use deep learning artificial intelligence to make fake digital content, typically in the form of swapping a person’s face in a video or image. This technology could easily threaten and manipulate individuals, corporations, and political organizations, so it is essential to find methods for detecting deepfakes. As the technology for creating deepfakes continues to improve, these manipulated videos are becoming increasingly undetectable. It is …
A Methodology For Detecting Credit Card Fraud, Kayode Ayorinde
A Methodology For Detecting Credit Card Fraud, Kayode Ayorinde
All Graduate Theses, Dissertations, and Other Capstone Projects
Fraud detection has appertained to many industries such as banking, retails, financial services, healthcare, etc. As we know, fraud detection is a set of campaigns undertaken to avert the acquisition of illegal means to obtain money or property under false pretense. With an unlimited and growing number of ways fraudsters commit fraud crimes, detecting online fraud was so tricky to achieve. This research work aims to examine feasible ways to identify credit card fraudulent activities that negatively impact financial institutes. In the United States, an average of U.S consumers lost a median of $429 from credit card fraud in 2017, …
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess, Masudul Hoque
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess, Masudul Hoque
All Graduate Theses, Dissertations, and Other Capstone Projects
Chess is a strategy board game with its inception dating back to the 15th century. The Covid-19 pandemic has led to a chess boom online with 95,853,038 chess games being played during January, 2021 on lichess.com. Along with the chess boom, instances of cheating have also become more rampant. Classifications have been used for anomaly detection in different fields and thus it is a natural idea to develop classifiers to detect cheating in chess. However, there are no specific examples of this, and it is difficult to obtain data where cheating has occurred. So, in this paper, we develop 4 …
Fault Detection And Classification Of A Single Phase Inverter Using Artificial Neural Networks, Ayomikun Samuel Orukotan
Fault Detection And Classification Of A Single Phase Inverter Using Artificial Neural Networks, Ayomikun Samuel Orukotan
All Graduate Theses, Dissertations, and Other Capstone Projects
The detection of switching faults of power converters or the Circuit Under Test (CUT) is real-time important for safe and efficient usage. The CUT is a single-phase inverter. This thesis presents two unique methods that rely on backpropagation principles to solve classification problems with a two-layer network. These mathematical algorithms or proposed networks are able to diagnose single, double, triple, and multiple switching faults over different iterations representing range of frequencies. First, the fault detection and classification problems are formulated as neural network-based classification problems and the neural network design process is clearly described. Then, neural networks are trained over …
Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan
Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan
All Graduate Theses, Dissertations, and Other Capstone Projects
From the book "Speaking into the Air: A History of the Idea of Communication," written by John Durham Peters, we understand a notion about developing one’s destiny; people have the freedom to choose multiple paths to follow (Peters, 2012). If we reject this idea, it is also easy for people to come up with distinct explanations. Even though the meaning of the same issues might vary subject to who is interpreting them, the primary concepts can be interpreted as more or less the same. If we study these two--"artificial intelligence" and "communication"- simultaneously, we can assume some characteristics. Thus, this …
Automatic Distinction Between Twitter Bots And Humans, Jeremiah Stubbs
Automatic Distinction Between Twitter Bots And Humans, Jeremiah Stubbs
All Undergraduate Theses and Capstone Projects
Weak artificial intelligence uses encoded functions of rules to process information. This kind of intelligence is competent, but lacks consciousness, and therefore cannot comprehend what it is doing. In another view, strong artificial intelligence has a mind of its own that resembles a human mind. Many of the bots on Twitter are only following a set of encoded rules. Previous studies have created machine learning algorithms to determine whether a Twitter account was being run by a human or a bot. Twitter bots are improving and some are even fooling humans. Creating a machine learning algorithm that differentiates a bot …
A Statistical Analysis And Machine Learning Of Genomic Data, Jongyun Jung
A Statistical Analysis And Machine Learning Of Genomic Data, Jongyun Jung
All Graduate Theses, Dissertations, and Other Capstone Projects
Machine learning enables a computer to learn a relationship between two assumingly related types of information. One type of information could thus be used to predict any lack of informaion in the other using the learned relationship. During the last decades, it has become cheaper to collect biological information, which has resulted in increasingly large amounts of data. Biological information such as DNA is currently analyzed by a variety of tools. Although machine learning has already been used in various projects, a flexible tool for analyzing generic biological challenges has not yet been made. The recent advancements in the DNA …
Improving Speech Recognition For Interviews With Both Clean And Telephone Speech, Sung Woo Choi
Improving Speech Recognition For Interviews With Both Clean And Telephone Speech, Sung Woo Choi
Journal of Undergraduate Research at Minnesota State University, Mankato
High quality automatic speech recognition (ASR) depends on the context of the speech. Cleanly recorded speech has better results than speech recorded over telephone lines. In telephone speech, the signal is band-pass filtered which limits frequencies available for computation. Consequently, the transmitted speech signal may be distorted by noise, causing higher word error rates (WER). The main goal of this research project is to examine approaches to improve recognition of telephone speech while maintaining or improving results for clean speech in mixed telephone-clean speech recordings, by reducing mismatches between the test data and the available models. The test data includes …
Comparing Ai Archetypes And Hybrids Using Blackjack, Robert Edward Noonan
Comparing Ai Archetypes And Hybrids Using Blackjack, Robert Edward Noonan
All Graduate Theses, Dissertations, and Other Capstone Projects
The discipline of artificial intelligence (AI) is a diverse field, with a vast variety of philosophies and implementations to consider. This work attempts to compare several of these paradigms as well as their variations and hybrids, using the card game of blackjack as the field of competition. This is done with an automated blackjack emulator, written in Java, which accepts computer-controlled players of various AI philosophies and their variants, training them and finally pitting them against each other in a series of tournaments with customizable rule sets. In order to avoid bias towards any particular implementation, the system treats each …
An Exploration Of Multi-Agent Learning Within The Game Of Sheephead, Brady Brau
An Exploration Of Multi-Agent Learning Within The Game Of Sheephead, Brady Brau
All Graduate Theses, Dissertations, and Other Capstone Projects
In this paper, we examine a machine learning technique presented by Ishii et al. used to allow for learning in a multi-agent environment and apply an adaptation of this learning technique to the card game Sheephead. We then evaluate the effectiveness of our adaptation by running simulations against rule-based opponents. Multi-agent learning presents several layers of complexity on top of a single-agent learning in a stationary environment. This added complexity and increased state space is just beginning to be addressed by researchers. We utilize techniques used by Ishii et al. to facilitate this multi-agent learning. We model the environment of …