Digital Commons Network^™

The Implications Of Chatgpt For Legal Services And Society, Andrew Perlman

Michigan Technology Law Review

On November 30, 2022, OpenAI released a chatbot called ChatGPT.1 To demonstrate the chatbot’s sophistication and its potential implications, both for legal services and society more generally, most of this paper was generated in about an hour through prompts within ChatGPT. Only this abstract, the preface, the outline headers, the footnotes, the epilogue, and the prompts were written by a person. ChatGPT generated the rest of the text with no human editing. To be clear, the responses generated by ChatGPT were imperfect and at times problematic, and the use of an AI tool for law-related services raises a host of …

Automated Verification Of Compiler Transformations, Yanzhao Wang

Dissertations and Theses

The ever-growing complexity of software and its target hardware makes it increasingly challenging to develop reliable compilers that preserve the semantics of source code during compilation. Traditional testing methods often lack sufficient test coverage and fail to identify subtle errors and undefined behaviors that can lead to compiler malfunctions. Furthermore, while formal compiler certification ensures semantic preservation through theorem proving, the inherent complexity of this process makes re-certification after each compiler revision substantially labor-intensive. This often significantly hinders the improvement of compilers.

This research aims to bridge the gap between increasing compiler complexity and the limited scalability of formal verification …

Inferring Tlb Configuration With Performance Tools, Cristian Agredo, Tor J. Langehaug, Scott R. Graham

Faculty Publications

Modern computing systems are primarily designed for maximum performance, which inadvertently introduces vulnerabilities at the micro-architecture level. While cache side-channel analysis has received significant attention, other Central Processing Units (CPUs) components like the Translation Lookaside Buffer (TLB) can also be exploited to leak sensitive information. This paper focuses on the TLB, a micro-architecture component that is vulnerable to side-channel attacks. Despite the coarse granularity at the page level, advancements in tools and techniques have made TLB information leakage feasible. The primary goal of this study is not to demonstrate the potential for information leakage from the TLB but to establish …

Effect Of Virtual Reality Technology On Ce/Cs Based Laboratories Education – A, Mariam Abdulla Al Nuaimi

Thesis/ Dissertation Defenses

Virtual reality (VR) is becoming increasingly popular in different fields, as institutions strive to incorporate technology into the education process. This thesis explores the effect of the use of VR on the users learning experience, and whether gamification, and human-computer interaction (HCI) affect the VR experience in a positive way. The main goal of this thesis is to explore the VR environment in STEM courses/Labs and investigate its effect on learning advanced topics. Specifically, we developed Digital Design & Computer Organization Lab (CS/CE Laboratory) as a VR environment to research this topic. We set and conducted experiments, surveyed participating students …

Scholar Perspectives On The Impact Of A Scientific Community Program For Neurodivergent Undergraduate Stem Scholars, Dylan Sullivan, Fernando Zavala, Derek Hidalgo, Jacob Stolle, Rebecca Matte, Christin B. Monroe

Journal of Science Education for Students with Disabilities

Despite the adaptive strengths and unique problem-solving skills demonstrated by neurodivergent (ND) individuals, they remain underrepresented in Science, Technology, Engineering and Mathematics (STEM) fields. High unemployment rates among individuals with disabilities emphasize the need for addressing barriers to entry and persistence in the workforce. This study introduces a program designed to enhance opportunities for neurodivergent STEM scholars with financial needs, supported by the National Science Foundation (NSF). The program involves: 1) a weekly cohort course to engage in professional development, 2) use of the Birkman Method® survey to help scholars identify and communicate strengths, fostering self-awareness and growth, and 3) …

Seshaiyer: Understanding Non-Linear Dynamics Of Interacting Subpopulations And Implicit Human Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Predicting And Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence In Pancreatic Cancer, Guangbo Yu, Zigeng Zhang, Aydin Eresen, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Vahid Yaghmai, Zhuoli Zhang

Pharmacy Faculty Articles and Research

Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and limited treatment options. This review examines the challenges and potential of using immunotherapy to treat pancreatic cancer, highlighting the role of artificial intelligence (AI) as a promising tool to enhance early detection and monitor the effectiveness of these therapies. By synthesizing recent advancements and identifying gaps in the current research, this review aims to provide a comprehensive overview of how AI and immunotherapy can be integrated to develop more personalized and effective treatment strategies. The insights from this review may guide future research efforts …

Holistic & Socially Just Admissions Procedures In An Artificially Intelligent (Ai) World, Lucinda Bratini, Ali Cunningham Abbott, Tracy N. Baker

Faculty and Staff Publications & Presentations

In our ever-evolving social context, the counseling profession continues to center social justice and decolonial praxis in training programs. Simultaneously, we remain attuned to shifts in machine learning and artificial intelligence (AI) which require us to adjust and grow. This roundtable discussion shares the development of a holistic admissions review (HAR) pilot process, which incorporates relational, diversity and social justice values alongside AI innovations and current CACREP considerations.

Comparison Of Efficient Deep Learning Architectures For Lactobacillus Species Identification, Dea Aisyah Rusmawati, Ishak Ariawan, Afrinal Firmanda

Karbala International Journal of Modern Science

Identifying microorganism species, such as Lactobacillus, is essential in ensuring the food products' quality and safety. Traditional laboratory practice requires expert knowledge and experience, but the method is expensive and time-consuming due to complex sample preparation. Faster, more accurate, and cheaper computational methods, such as transfer learning technology, are needed for the Lactobacillus species classification. The technique has been effective in a variety of image recognition contexts. Deep learning architecture can also be applied as an innovative strategy for digital image-based identification. Therefore, this research aims to compare several deep-learning architectures in classifying bacterial strains of Lactobacillus. The four architectures …

Improving Infectious Disease Predictions Through The Use Of Metapopulation Sir Modeling And Graph Convolutional Neural Networks, Petr Kisselev, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Ethical Responsibility In The Design Of Artificial Intelligence (Ai) Systems, David K. Mcgraw

International Journal on Responsibility

This article aims to provide an overview of the ethical questions surrounding the responsibilities of designers of artificial intelligence (AI) systems. First, the author delves into the philosophical underpinnings of this responsibility, examining various ethical theories to grasp the moral obligations individuals have towards others and society. The author contends that designers of technology bear the responsibility of considering the broader societal implications of their creations. Subsequently, the author scrutinizes the fundamental question of whether AI systems present unique ethical concerns compared to conventional technologies, pinpointing factors such as complexity, opacity, autonomy, unpredictability, uncertainty, and the potential for significant social …

Modeling Of Radio Array Distribution, Yahya Emran Abdelhadi

Thesis/ Dissertation Defenses

In the quest to understand the mysteries of the universe through radio astronomy, selecting the right tools and methods is crucial. Just as radio astronomy provides a unique lens through which to study the universe, the adoption of open-source software, such as Python, similarly offers a distinct advantage in scientific research. Today most research is done on open-source code which reduces the limitation to have access to the science and research resources to improve the quality and the contributed researcher. For some people, access to software and tools is very expensive and limited. This work focuses on converting the IDL …

Developing A Framework For Digital Twin Data Quality And Security Controls, Ahmad Abdelbaset Hassan

Thesis/ Dissertation Defenses

This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin standards and policies that is going to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust standards to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed …

Hybridizing Reinforcement Learning With Metaheuristics For Improved Traffic Signal Control And Optimization In Urban Transportation Networks, Jiyana Nikhil Jaisinghani

Thesis/ Dissertation Defenses

Managing road traffic in metropolitan cities is a crucial aspect of Intelligent Transportation Systems (ITS). The rapid growth of population and vehicles has led to increasing traffic congestion, which negatively affects travel times, fuel consumption, and air quality in urban areas. Intersections and their traffic lights are key contributors to this congestion, making efficient and adaptable Traffic Signal Control (TSC) and Traffic Signal Scheduling (TSS) essential. TSC manages traffic flow at intersections, while TSS optimizes the timing and sequencing of traffic signals. The techniques, Reinforcement Learning (RL) and Metaheuristic Optimization (MO), have shown promising results in addressing traffic control challenges …

Simplify Workflows: Ai As A Coding Companion, Tiffany Garrett

Library Scholarship

Artificial Intelligence is on everyone’s minds and has been the topic of the past two Matheson Lectures. But, what is the role of academic health sciences libraries? Moving the theoretical into practical, seven of our colleagues will present real-life case studies. What worked - what didn’t - what would they do differently?

This entry is from one of those case presentations on how a librarian at Roseman University of Health Sciences used AI to complete simple computer programming projects that optimized a few library workflows.

Competitive Conquest: Charting The Climb To Pokémon Supremacy, Robert Dilworth

BCoE Publications

This manuscript presents a comprehensive exploration of optimizing Pokémon gameplay through data-driven methodologies, aimed at enhancing competitive performance in high-stakes environments. In the first section, we introduce a robust Pokémon teambuilding algorithm that leverages statistical analysis of championship-winning compositions. By employing multiple linear regression techniques, we predict team performance based on critical factors such as Base Stat Totals (BSTs) and various coverage types. This integration of data science principles into Pokémon strategy underscores the importance of offensive capabilities over defensive considerations, ultimately contributing to advancements in teambuilding strategies. Our proficiency in R programming facilitated the development of an efficient codebase …

Telu Activation Function For Fast And Stable Deep Learning, Alfredo Fernandez

USF Tampa Graduate Theses and Dissertations

We propose the Hyperbolic Tangent Exponential Linear Unit (TeLU), a neural network hidden activation function defined as $TeLU(x)=x \cdot tanh(e^x)$. TeLU’s design is grounded in the core principles of key activation functions, achieving strong convergence by closely approximating the identity function in its active region while effectively mitigating the vanishing gradient problem in its saturating region. Its simple formulation enhances computational efficiency, leading to improvements in scalability and convergence speed. Unlike many modern activation functions, TeLU seamlessly combines the simplicity and effectiveness of ReLU with the smoothness and analytic properties essential for learning stability in deep neural networks. TeLU’s ability …

Exploring Llm Integration And Its Influence On Agent Behavior And Productivity In Insurance Call Centers, Gerardo L. Wibmer Gonzalez

USF Tampa Graduate Theses and Dissertations

This study investigates the theoretical impacts of supportive AI tools, specifically Large Language Models (LLMs), on agent behavior and communication dynamics in call centers. While technological advancements have streamlined operations, limited research addresses the indirect ways these tools influence agent behavior. Using frameworks like context switching—the cognitive shift required when external stimuli prompt attention shifts—and the Hawthorne effect, where perceived observation modifies behavior, we examine how LLMs shape communication patterns. In call centers, this context switching occurs indirectly as agents adapt to AI note-taking features, whereas in industries like Architecture, Engineering, and Construction (AEC), automation tools prompt more immediate changes …

Student Perceptions Of A Novel No-Cost Mobile Application For Ophthalmic History And Physical Examination, Soryan Kumar, Anagha Lokhande, Spandana Jarmale, Arnav Kumar, Samantha Rosenthal, Grayson W. Armstrong, Michael Migliori, Jamie Schaefer

Journal of Academic Ophthalmology

Background: Mobile applications have shown promise in enhancing medical trainee performance. In ophthalmology, a comprehensive mobile app can streamline the trainee education process by providing guidance for patient intake. Language barriers pose additional challenges impacting the quality of care for Spanish-speaking patients; literature has documented the adverse impacts of inadequate translation on quality of medical care for both trainees and patients. We aim to develop a free mobile application to guide medical trainees through the ophthalmic patient intake process and assist with Spanish-language translation.

Methods: We developed EyeCheck as a free mobile application for ophthalmology trainee education with …

Ai-Powered Pedagogy: Revolutionizing Students’ Learning Experiences Through Integration Of Ai Technologies, Amna Awad Alsaedi

Thesis/ Dissertation Defenses

This research examines the integration of artificial intelligence (AI) within the educational sector with the aim of enhancing student learning outcomes. AI offers tailored learning experiences, interactive educational content, prompt feedback, and access to diverse learning resources. Nonetheless, challenges including addiction, costliness, privacy infringement, bias, ethical dilemmas, market competition, and moral considerations require resolution. Research particularly delves into the utilization of chatbots, and algorithms designed to simulate human interactions and generate text resembling human speech. Educational applications powered by AI have the potential to heighten student engagement, comprehension, and academic performance by substituting traditional assignments with concise, information-rich lessons. Furthermore, …

Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous

Thesis/ Dissertation Defenses

With the increase in popularity of online communities, such as social media platforms, online games, and chatroom servers, there is a need to improve chat and content moderation. Platforms have reported an increase in the prevalence of toxic behavior and hate speech. Meanwhile, moderators are reporting difficulties in keeping up with the amount of data to check as well and the type of content they are exposed to, which further harms their own mental health. The main objective of this work is to address the challenges that exist within online communities with the rising prevalence of hate speech. Additionally, some …

A Novel Algorithmic Approach To Safeguarding Inter-Vehicular Communications And Privacy, Susan Zehra

Graduate Student Government Association Research Conference

Vehicular networks have become a crucial technology for implementing various safety applications for both drivers and passengers. These networks are currently receiving significant attention due to their ability to facilitate access to a diverse range of ubiquitous services. However, the growing popularity of vehicular networks has also led to an increase in security vulnerabilities within their inter-vehicular services and communications, resulting in a rise in security attacks and threats.

Ensuring the security of vehicular networks is paramount, as their deployment should not compromise the safety and privacy of stakeholders. Effectively defending against a broad spectrum of attacks necessitates the development …

Factors Impacting The Adoption And Acceptance Of Chatgpt In Educational Settings: A Narrative Review Of Empirical Studies, Mousa Al-Kfairy

All Works

This narrative review synthesizes and analyzes empirical studies on the adoption and acceptance of ChatGPT in higher education, addressing the need to understand the key factors influencing its use by students and educators. Anchored in theoretical frameworks such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Diffusion of Innovation (DoI) Theory, Technology–Organization–Environment (TOE) model, and Theory of Planned Behavior, this review highlights the central constructs shaping adoption behavior. The confirmed factors include hedonic motivation, usability, perceived benefits, system responsiveness, and relative advantage, whereas the effects of social influence, facilitating conditions, privacy, and security …

Permission Recommendation For Android Applications: Leveraging Natural Language Processing On App Descriptions, Saeed Salem Al Shebli

Thesis/ Dissertation Defenses

This study develops an NLP-based system to recommend essential permissions for Android apps by analyzing app descriptions. It leverages advanced models, including LSTM and ensemble techniques, to align permissions with app functionality while minimizing unnecessary requests.

On The Work Of Cartan And Münzner On Isoparametric Hypersurfaces, Thomas E. Cecil, Patrick J. Ryan

Mathematics and Computer Science Department Faculty Scholarship

A hypersurface Mⁿ in a real space form Rⁿ⁺¹, Sⁿ⁺¹, or Hⁿ⁺¹ is isoparametric if it has constant principal curvatures. This paper is a survey of the fundamental work of Cartan and Münzner on the theory of isoparametric hypersurfaces in real space forms, in particular, spheres. This work is contained in four papers of Cartan [3]–[6] published during the period 1938–1940, and two papers of Münzner [47]–[48] that were published in preprint form in the early 1970’s, and as journal articles in 1980–1981. These papers of Cartan and Münzner have been the …

Ai-Enabled Methodological Frameworks To Enhance The Robustness Of Machine Learning Models In Various Domains And Dynamic Environments, Mohammad Noroozi

USF Tampa Graduate Theses and Dissertations

This dissertation explores novel approaches to address complex challenges in various domains, focusing on ensuring that machine learning (ML) models can reliably detect both the data they are trained on and unseen data. Reliable detection of unfamiliar inputs is critical for deploying models in real-world applications, where performance can degrade when faced with novel or unexpected information. Each domain addressed in this work introduces a set of contributions aimed at enhancing model performance, broadening generalization through diverse training data, and improving robustness against adversarial attacks. Three sets of contributions are presented, each encapsulated in a chapter.

One of the contributions …

Classification Manner Utilizing Electroencephalography Signals To Investigate Waveforms, Wessam Al-Salman, Ali Basim Al-Khafaji, Mishall Al-Zubaidie

Karbala International Journal of Modern Science

Waveform detection has been an area of continuous investigation for many years. One important waveform in sleep stage 2 is the k-complex. Numerous researchers have created various strategies for auto-k-complex detection; some of these strategies state that the automated detection techniques are adequate. Because of its analytically relevant resolution, the Electroencephalogram (EEG) is a commonly utilized technique to analyze the k-complexes in order to understand the nervous system activity of the brain. Several researchers have classified waveforms using EEGs in a variety of ways. It appears that the majority of the waveform detection had limitations. The …

Bacterial Cellulose Production From Fermented Fruits And Vegetables Byproducts: A Comprehensive Study On Chemical And Morphological Properties, Yati Maryati, Hakiki Melanie, Windri Handayani, Yasman Yasman

Karbala International Journal of Modern Science

This study aimed to produce α-cellulose from Bacterial Cellulose SCOBY (BCS) using alternative substrates from fermented fruit and vegetable byproducts: katuk leaves (KT), kale leaves (KL), guava (JB), dragon fruit (NG), and banana (PS). BCS production involved juice extraction, SCOBY inoculation, and sucrose addition, followed by 21 days of fermentation. Initially, the NG medium had the highest concentration of Total Reducing Sugars (TRS), but all media showed a decline as sugars were consumed. Fermentation reduced pH and increased total polyphenols, with KL and JB showing the highest rise (0.13-0.15 mg GAE/mL). Flavonoid levels varied, decreasing in KL and PS but …

Metabolite Profiling Of Potential Fraction From Ethyl Acetate Extract Of Ziziphus Mauritiana Leaves By Lc-Ms/Ms Analysis, Nurhayati Bialangi, Weny Ja Musa, Boima Situmeang

Karbala International Journal of Modern Science

In Indonesia, the treatment with leaves as a traditional medicine is still firmly integrated into the community to overcome various health problems experienced, one of which is the treatment with Bidara leaves (Ziziphus mauritiana). Ziziphus mauritiana belongs to family of Rhamnaceae, and it is generally considered a potential source of antioxidant and cholesterol lowering. This study aimed to examine phytochemical characterization, antioxidant potential, and cholesterol-lowering effects of ethyl acetate fraction derived from Ziziphus mauritiana. Extraction was accomplished using ethyl acetate, and the resultant extract was fractionated through chromatography with a blend of n-hexane and ethyl acetate as …

Information Technology Managers’ Strategies For Implementing Data Governance, Dieudonne Mayi

Walden Dissertations and Doctoral Studies

As businesses increasingly view data as a strategic asset, effective data governance (DG) frameworks are crucial for ensuring data integrity and compliance. IT managers face challenges in fully integrating DG with IT governance, leading to issues like inconsistent data availability, compromised security, and costly outcomes such as data loss, legal actions, and compliance penalties. Grounded in Abraham et al.’s DG conceptual framework and Khatri and Brown’s unified DG framework, this qualitative pragmatic study investigates the strategies IT managers use to implement successful DG within organizations. A sample of 11 IT managers from U.S. companies with established DG practices participated in …