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    Detecting Stuttering Types Using Deep Learning 

    Mau, Brayden (2024-04)
    Stuttering, recognized as a prevalent speech disfluency, presents considerable challenges in achieving accurate identification. Notably, technological advancements, such as Apple’s Siri, highlight the complexities encountered ...
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    Machine Learning to Detect Stuttering : Detecting Different Types of Stuttering Using Multiple Machine Learning Algorithms 

    Scott, Thomas (2024-04)
    Stuttering is an important problem largely addressed with speech therapy. It can adversely affect the quality of the affected person’s daily life. If machine learners can be designed to detect stuttering types in speech, ...
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    Emotion Sentiment Analysis in Turkish Music 

    Nguyen, Nguyen (2024-04)
    Music has become an indispensable element of human life. Its rhythms, melodies, and harmonies resonate deeply within us, touching our emotions and echoing sentiments in us. In recent years, many music emotion sentiment ...
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    Analysis of Gait Motion Sensor Authentication with Machine Learning 

    Kokal, Sara (2024-04)
    In recent decades, mobile devices have evolved in potential and prevalence significantly while advancements in security have stagnated. As smartphones now hold unprecedented amounts of sensitive data, there is an increasing ...
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    A Machine Learning Approach Towards Prediction of Pancreatic Cancer Using Gene Expression and DNA Methylation 

    Keller, Paige; Morehead, Samuel; Caterer, Zachary (2024-04)
    DNA methylation is a process that can affect gene accessibility and therefore gene expression. Methylation can affect genes that are associated with suppressing or contributing to tumor growth and progression. In this ...
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    Exploring Machine Learning Models : For IoT Network Intrusion Detection : A Literature Review and Comparative Analysis 

    Hagen, Jack; Strate, Ayden (2024-04)
    The Internet of Things (IoT) is a complex network of low-powered interconnected devices that communicate and exchange data over the internet. IoT devices are a popular target for cybercriminals because of the user data ...
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    Detecting Cyberbullying with Machine Learning 

    Root, Andrew; Jakubowski, Liam (2024-04)
    The pervasiveness of Social Media in modern life is indisputable. Unfortunately, its potential to facilitate malicious and harmful sentiments has been exploited by many users of the technology. This phenomenon is known as ...
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    New Language Game+ : Digital Humanities for Wittgenstein 

    Fiebig, Motgan; Ruthy, Stephen (2024-04)
    The object of this study is to utilize data-focused tools to obtain novel insights into the philosophy of Ludwig Wittgenstein. The project is inspired by the philosopher Mark Alfano (2019). Alfano’s investigation centered ...
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    AI in GI : Reducing Colonoscopy Report Review Time and Cognitive Burden for Clinicians and Patients 

    Mau, Brayden; Rolli, Alexandra C. (2025-04)
    This project aims to standardize follow-up recommendations for colonoscopies by leveraging Generative AI and Natural Language Processing (NLP) to analyze colonoscopy and pathology reports. Current follow-up guidelines vary ...
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    Patterns and Characteristics Unique to AI-Generated and Human-Written Text Responses 

    Smith, Brianna; Diamond, Jacob (2025-04)
    The recent advancements in LLMs and Gen-AI technology, such as ChatGPT, Gemini, and Llamas, have widespread applications. Such AI-based solutions strive to achieve extremely high levels of effectiveness in identifying and ...
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    AuthorGomes, Rahul (5)Dave, Rushit (4)Mohan, Pavithra Devy (4)Caterer, Zachary (3)DeWitte, Matthew (3)Hagen, Jack (3)Kamrowski, Connor (3)Mahan, Oliver (3)Mau, Brayden (3)Bolka, Karen (2)... View MoreSubject
    Department of Computer Science (50)
    Posters (50)Machine learning (30)Artificial intelligence (8)Pancreatic cancer (5)Authentication (4)Computer security (4)College students (3)Department of Geography and Anthropology (3)DNA Methylation (3)... View MoreDate Issued2022 (25)2025 (12)2024 (10)2021 (3)Has File(s)
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