Artificial Intelligence and Robotics Commons^™

Ghostwriter To Co-Author: Helping Students Leverage Ai In The Classroom, Ishani Banerji

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Optimizing Ideation And Digital Prepress Workflows With Ai Integration, Carl N. Blue

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Requiring Students To Integrate Chatgptinto Course Assignments, Mark Small, Venera Balidemaj

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Using Ai In The Teacher Preparation Programs And Social Studies Classrooms, Brandon Beck

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Language Portraits: A Space To Explore Identities In A Graduate Course, Hazel Vega

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Ai-Enhanced Education: Fostering Creativity, Efficiency, And Future-Ready Skills, Rodger Eugene Bishop

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Critical Ai Engagement: Crafting Assignments That Encourage Productive Engagement With Ai, Carl Ehrett

Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI

No abstract provided.

Challenging Others When Posting Misinformation: A Uk Vs. Arab Cross-Cultural Comparison On The Perception Of Negative Consequences And Injunctive Norms, Muaadh Noman, Selin Gurgun, Keith Phalp, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

This study investigates the factors influencing the willingness to challenge misinformation on social media across two cultural contexts, the United Kingdom (UK) and Arab countries. A total of 462 participants completed an online survey (250 UK, 212 Arabs). The analysis revealed that three types of negative consequences (relationship cost, negative impact on the person being challenged, futility) and also injunctive norms influence the willingness to challenge misinformation. Cross-cultural comparisons using t-tests showed significant differences between the UK and the Arab countries in all factors except the injunctive norms. Multiple regression analyses identified differences between the UK and Arab participants concerning …

Texcot22, Md Ahmed Al Muzaddid, William J. Beksi

Computer Science and Engineering Datasets - Archive

The TexCot22 dataset is a set of cotton crop video sequences for training and testing multi-object tracking methods. Each tracking sequence is 10 to 20 seconds in length. The dataset contains of a total of 30 sequences of which 17 are for training and the remaining 13 are for testing. Among the training sequences, 2 of them consist of roughly 5,000 annotated images, which can be used to train a cotton boll detection model. The video sequences were captured at 4K resolution and at distinct frame rates (e.g., 10, 15, 30). There are typically 2 to 10 cotton bolls per …

Creative Technologies: A Conversation With Roy Magnuson, Roy Magnuson, Maureen Russell

Faculty Publications - Music

[In lieu of an abstract, the introduction is provided.] Today I am speaking with Roy Magnuson, Associate Professor Creative Technologies in the School of Music at Illinois State University (ISU). (see Figure 1) His music has been performed throughout the United States and Europe at venues such as the World Saxophone Congress, WASBE, CBDNA, the RED NOTE New Music Festival, and the Robb Composers’ Symposium. Magnuson is also the creator of the virtual reality composition software solsticeVR and the conducting software RibbonsVR. He is a member of ASCAP, and his music is recorded on Albany Records and NAXOS.

Racism Detection In Tweets, Ndjeuha Gihane

All Graduate Projects

Since the advent of social networks in 1997, businesses and people’s lives have changed in a good way. From promoting companies to reaching out to friends and family, social networking has become a major element in our lives. X is a very popular platform that is used by many people, including celebrities and politicians, to communicate with their audience. Like other platforms, X is not spared by the racism contained in the tweets. We should be able to catch those racist comments on any social media and block the accounts of those responsible for them. To do so, we have …

Crafting Effective Prompts: Leveraging Generative Ai In Libraries, April Sheppard, Kristin Flachsbart

Staff and Faculty Scholarship

Discover how strategic prompt design can help you harness the power of generative artificial intelligence (AI) in your library. Through a series of examples, the presenters will demonstrate the impact that well-crafted prompts can have on the quality and relevance of AI-generated outputs.

A Comparison Of Machine Learning Surrogate Models Of Street-Scale Flooding In Norfolk, Virginia, Diana Mcspadden, Steven Goldenberg, Binata Roy, Malachi Schram, Jonathan L. Goodall, Heather Richter

Community & Environmental Health Faculty Publications

Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random …

Usage And Knowledge Of Online Tools And Generative Ai: A Survey Of Students, Rahul R. Divekar Phd, Lisette Gonzalez, Sophia Guerra, Natasha Boos

Department of Experience Design (XD) Faculty Publications

Artificial Intelligence (AI) tools like ChatGPT are poised to transform student and educator workflows in higher education. However, there is less documentation on the range of tools students in higher education use, how they use them and in coordination with other online tools for learning, and their expertise using AI tools. We present a mixed-method analysis of a survey conducted at a doctoral-granting university in the United States investigating the adoption of AI tools in the context of other technologies. The findings include how the students used GenAI tools in light of other on-line technologies, their perception of expertise on …

Developing Policies For The Ethical Use Of Artificial Intelligence In Higher Education And Libraries, April Sheppard, Matthew Mayton

Staff and Faculty Scholarship

This presentation will provide sample artificial intelligence policy language from various higher education institutions and academic libraries. Topics covered will include the acceptable use of AI in the classroom, the role of faculty in making AI-related decisions, syllabus statements, AI use and detection, AI literacy, and library policies regarding AI. Participants will be able to compare and contrast policies to help them develop their own policies that work for their unique organization.

Survey Of Memory Consolidation Techniques For Video Question Answering, Matthew Couts, Pha Nguyen, Khoa Luu

Inquiry: The University of Arkansas Undergraduate Research Journal

Video Question Answering (VideoQA) is a field of research focused on developing models that can engage in natural conversations with humans about the content of videos. Currently, the most successful approaches involve analyzing videos frame-by-frame, which is computationally and memory-intensive. To imitate human memory, the Atkinson-Shiffrin memory model can formulate the machine’s video understanding capability through Vision-Language Models. Reducing the number of frames processed by the model is a crucial operation in this approach category and can be handled by a memory consolidation algorithm. The memory consolidation algorithm should be able to determine the keyframes to transfer from short-term to …

The Measure Of Efficiency And Effectiveness When Using Artificial Intelligence (Ai) In Radiology, Jordan Watts

Theses, Dissertations and Capstones

Introduction: The use of artificial intelligence in radiology has helped radiologists identify patterns and abnormalities in medical images to diagnose and treat patients. Deep learning and machine learning algorithms have been used to assist physicians in detecting features that are not noticeable to the human eye. The FDA has approved almost 400 AI algorithms for radiology and estimated that the market for AI in medical imaging would grow from $21.48 billion in 2018 to $264.85 billion in 2028.

Purpose of the Study: The purpose of this research was to evaluate the use of artificial intelligence in radiology to determine its …

Machine Intelligence With Associative Memory And Event-Driven Transaction History, Rao Mikkilineni, W. Patrick Kelly

Barowsky School of Business | Faculty Scholarship

Digital machine intelligence has evolved from its inception in the form of computation of numbers to AI, which is centered around performing cognitive tasks that humans can perform, such as predictive reasoning or complex calculations. The state of the art includes tasks that are easily described by a list of formal, mathematical rules or a sequence of event-driven actions such as modeling, simulation, business workflows, interaction with devices, etc., and also tasks that are easy to do “intuitively”, but are hard to describe formally or as a sequence of event-driven actions such as recognizing spoken words or faces. While these …

Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala

2024 REYES Proceedings

With advancements in AI-driven natural language generation, distinguishing between AI-generated and human-written text has become imperative for ensuring content authenticity across industries. This study explores the effectiveness of Bidirectional Encoder Representations from Transformers (BERT) in addressing this classification challenge. Utilizing a diverse dataset and robust preprocessing techniques, BERT achieved a peak F1-score of 0.94364, outperforming traditional models such as Logistic Regression and Support Vector Machines. The results underscore the potential of transformer-based models in addressing real-world con- tent verification problems. Future enhancements include fine-tuning and expanding datasets for greater generalizability.

Predicting Compressive Strength Of Concrete Incorporating Fly Ash, Blast Furnace Slag, And Superplasticizer Using Machine Learning Techniques, Muhammad Faisal Yaqub

2024 REYES Proceedings

Concrete is the second most essential element in the construction industry, and its strength requirements vary based on the specific conditions of each project. However, determining the compressive strength of concrete involves laboratory tests, which wastes a lot of time and money. Researchers have developed machine learning models that predict the compressive strength of cement-based concrete having various mixes. In this research, the compressive strength of concrete incorporating fly ash, blast furnace slag, and superplasticizer is predicted using different machine learning models, namely, Linear Regression, Random Forest Regression, Decision Tree Regression, Extreme Gradient Boosting, Light Gradient Boosting, AdaBoost, and CatBoost …