Digital Commons Network^™

Discovery Of Drug Transporter Inhibitors Tied To Long Noncoding Rna In Resistant Cancer Cells; A Computational Model -In Silico- Study, Mohanad Diab, Amel Hamdi, Feras Al-Obeidat, Wael Hafez, Ivan Cherrez-Ojeda, Muneir Gador, Gowhar Rashid, Sana F. Elkhazin, Mahmad Anwar Ibrahim, Tarek Farag Ismail, Samar Sami Alkafaas

All Works

Chemotherapeutic resistance is a major obstacle to chemotherapeutic failure. Cancer cell resistance involves several mechanisms, including epithelial-to-mesenchymal transition (EMT), signaling pathway bypass, drug efflux activation, and impairment of drug entry. P-glycoproteins (P-gp) are an efflux transporter that pumps chemotherapeutic drugs out of cancer cells, resulting in chemotherapeutic resistance. Several types of long noncoding RNA (lncRNAs) have been identified in resistant cancer cells, including ODRUL, MALAT1, and ANRIL. The high expression level of ODRUL is related to the induction of ATP-binding cassette (ABC) gene expression, resulting in the emergence of doxorubicin resistance in osteosarcoma. lncRNAs are observed to be regulators of …

Dsa-Api: Data Standardization Automation Using Ai-Powered Apis, Andrew Asher Turner

Master's Theses

The common factor with current implementations of Artificial Intelligence (AI) is data. Companies are constantly looking for new ways to analyze data, but it comes in various formats: Text, Comma Separated Value (CVE), JavaScript Object Notation (JSON), Extensible Markup Language (XML), and Excel. How can AI be adapted to standardize formats for data analysis, integration, and digestion efficiently? Published research acknowledged that Machine Learning (ML) and AI can provide an automated method to speed up this process and limit the human decision-making error. With the advancement in AI, Application Programming Interfaces (APIs) prompt the idea that they can take in …

Who Should Take Responsibility For Artificial Intelligence Actions And Outcomes? Perception Of Auditors As Users Of Ai Systems, Hanh Hoang Le

Doctoral Dissertations

As artificial intelligence (AI) systems become increasingly embedded in auditing processes, questions arise regarding how professional auditors perceive and allocate responsibility for AI-assisted decisions. This study investigates the effects of AI explainability and auditors’ perceived autonomy on perceived responsibility in the context of audit decision-making. Drawing on theories of moral responsibility and professional judgment, the study employs a 2x2 experimental design using hypothetical audit scenarios to manipulate levels of AI explainability and auditors’ autonomy. Hierarchical regression analysis reveals that perceived autonomy statistically significantly increases auditors’ perception of responsibility for AI-assisted decisionmaking, whereas AI explainability is not a significant predictor. Additionally, …

Transformer Decoder-Enhanced Swin Unetr For Multi-Organ Semantic Segmentation On Openkbp: Improving Radiotherapy Planning Accuracy, Zainab Adnan Jwad, Israa Hadi Ali

Karbala International Journal of Modern Science

Accurate segmentation of organs-at-risk (OARs) in head and neck CT scans is crucial for radiotherapy planning. The CNN-based decoder limitation of Swin UNETR hinders its capacity to process meaningful information from multiple organ positions essential for accurate medical segmentation. The proposed Transformer Decoder-enhanced Swin UNETR model targets the OpenKBP dataset multi-organ segmentation through its dedicated design for this purpose. The model utilizes transformers along with cross-attention approaches in its decoder to improve segmentation mask outputs through analysis of extensive global information. The model gets additional feature representation power through the addition of squeeze-and-excitation (SE) blocks linked with spatial attention mechanisms …

Leveraging Artificial Intelligence In Education To Drive Cross-Sector Innovation, Brent Terwilliger, John Faraca

Publications

As artificial intelligence (AI) reshapes educational practices, particularly in technical fields such as uncrewed systems, robotics, and aviation/ aerospace, its integration raises promise and complexity. This exploratory study features an investigation of the impact AI tools adoption has on instruction, curriculum support, and workforce preparation, with a focus on online learning environments. Drawing from pilot survey data across aviation and aerospace education stakeholders and hands-on evaluation of AI video production platforms, findings reveal diverse applications, perceived benefits, and critical concerns, including ethical, pedagogical, and institutional challenges. Additionally, the analysis explored how AI-enabled education intersects with broader industry and government innovation …

Aerial Robotic Studies Of Volcanic Co2 Emissions, John Ericksen

Computer Science ETDs

Volcanic systems are inherently complex, involving dynamic interactions among magma flow, gas emissions, and atmospheric dispersion. This dissertation focuses on developing and analyzing autonomous UAS algorithms for efficiently surveying volcanic CO2 plumes, introducing several novel methods: the LoCUS algorithm, a swarm coordination and self-healing algorithm that supports gradient-based plume tracking, a transect-based technique that employs a 2D Gaussian fit to calculate CO2 plume flux, and the Sketch algorithm for rapid plume boundary tracing. By treating multiple UAS as a single scientific instrument, these methods leverage swarm algorithms to use in-situ data in ways impossible with individual drones. Validated through simulations …

First Annual Advances In Business Education Conference 2025 Proceedings, Kelsey Metz, Joshua Ray

Advances in Business Education (ABE) Conference Proceedings

Conference Overview: The First Annual Advances in Business Education (ABE) Conference was held on May 16, 2025, at Lincoln Memorial University in Harrogate, Tennessee. Hosted by the LMU School of Business, the ABE Conference was established to promote teaching excellence through innovation and collaboration in business education. With a focus on fostering meaningful dialogue among educators, researchers, and students, the conference welcomed participants from across disciplines and institutions. The event was structured around three key tracks:

Pedagogy & Teaching Excellence: Showcasing innovative teaching methods and strategies for enhancing student learning and engagement.

Business Research: Presenting research focused on advancing knowledge …

Cyber Security Threat Recognition And Preparedness Of Undergraduate Students, Litany Hope Lineberry

Theses and Dissertations

Cybersecurity awareness and preparedness are critical competencies for individuals across academic disciplines and professional sectors. However, undergraduate students often lack sufficient knowledge and skills to recognize and mitigate cybersecurity threats. This dissertation examines cybersecurity threat recognition and preparedness among undergraduate students through a three-phase research approach. Study 1 explores faculty perspectives on students' cybersecurity awareness, identifying gaps in knowledge and preparedness across various fields of study. Study 2 investigates industry professionals' perceptions of new hires’ cybersecurity readiness, assessing the alignment between academic training and industry expectations. Study 3 evaluates the effectiveness of an online intervention designed to enhance students' cybersecurity …

Establishing A Baseline For Detecting Lotl Attacks In Windows Operating Systems, Ashlyn Martin Phillips

Theses and Dissertations

There has been an increasing realization of the rise in living off the land (LOTL) attacks where adversaries misuse legitimate system tools, particularly with state-sponsored actors targeting critical infrastructure in the United States. These attacks are difficult to detect because they allow attackers to remain present in a system without the user’s knowledge for an extended period. This thesis establishes an initial baseline specifically for Windows operating systems to measure normal system activity, focusing on CPU usage, memory utilization, and process activity. It particularly examines the use of PowerShell alongside other applications. The findings from this baseline are used to …

The Confluence, Volume 4, Issue 1, Full Issue

The Confluence

No abstract provided.

Cybersecurity And Global Threats: A Comparative Analysis Of Estonia And Russia’S Policies, María Paula Morales Palacios

The Confluence

As digital technology continues to reshape the foundations of modern life, the question of how states respond to cyber threats has become increasingly urgent. This paper examines how political systems shape national cybersecurity policies by comparing Estonia and Russia, two countries facing similar external threats but governed by vastly different structures. Estonia’s democratic framework emphasizes transparency, citizen participation, and international cooperation, while Russia’s semi-authoritarian model centers on state sovereignty, centralized control, and strategic offensive capabilities. Drawing on key historical events, including the 2007 cyberattacks on Estonia and the 2016 attacks on Russian banks, the paper explores how each state’s political …

Developments On Abbreviations Towards Machine Reading Comprehension, Sing Choi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Machine reading comprehension is a critical step in development of applications that require the semantic understanding of human speech-to-text driven work. Many devices such as smart home appliances like the Amazon Echo Dot, Google Home, or smart assistants like Apple Siri or Microsoft Cortana are examples of these applications. The comprehension task involves a deeper understanding and recognition of named entities such as person names, locations, medicals codes, quantities, abbreviations, and acronyms in speech or text data. In this dissertation, we explore and extend the different approaches and techniques in modern research that tackles the problem of recognition and definition …

System Administration Practices And Experimentation, Nicholas Z. Young

Honors Program Theses and Projects

This undergraduate departmental honors capstone project experiments with and demonstrates System Administration practices that are used in enterprise environments. The skills and practices of System Administrators are crucial to maintain large-scale IT infrastructure. This project aimed to gain a deeper, practical understanding of the role of a System Administrator in an emulated environment. Through hands-on experimentation, this project addressed the responsibilities of a System Administrator, such as controlling user access, adding hardware, automating tasks, monitoring systems, overseeing and developing a backup strategy, maintaining local documentation, and security practices. This project demonstrated some of the complexities that lie in each of …

Computational Thinking, Informal Learning, And Makerspace, Redar Ismail

College of Computing and Digital Media Dissertations

The continuous advancement of technology has made it a crucial tool across various disciplines. As adaptation to this rapidly progressing field occurred, teaching and learning problem-solving skills are more essential than ever for empowering individuals to succeed across diverse fields. Studies have shown that engaging K-12 students in activities encouraging science, technology, engineering, mathematics (STEM), and computational thinking (CT) are critical for teaching them how to deal with complex problems (Rode, Barkhuus, & Ioannou, 2024; Shu & Huang, 2021). Makerspaces and making activities became popular among researchers and educators due to their potential to advance learning, enhance problem-solving skills, and …

The Evolution And Impact Of Blog Analysis Tools: A Study Of Blogtracker's Comprehensive Approach To Digital Discourse Analysis, Oyindamola Koleoso

Theses and Dissertations

This study presents BlogTracker, a comprehensive web-based platform designed to address the growing complexities of analyzing the modern blogosphere. We detail BlogTracker's evolution from earlier blog analysis tools, highlighting its innovative integration of features including real-time data collection, advanced content analysis, sentiment analysis, influence tracking, and narrative analysis. At the core of our contribution is a robust content extraction system that achieves 91.33% accuracy across diverse blog formats, providing a reliable foundation for all analytical functions. This extraction system effectively distinguishes between primary content and peripheral elements, ensuring high-quality inputs for downstream analysis regardless of source blog structure. The platform's …

Modeling Cross-Platform Narrative Templates: A Temporal Knowledge Graph Approach, Ridwan Amure

Theses and Dissertations

Over the past decade, social media platforms have rapidly evolved in scale, functionality, and user engagement, encouraging individuals to maintain active presences across multiple networks. This complex, interconnected ecosystem has also enabled information actors to exploit cross-platform dynamics to amplify the reach of their content and strategically target diverse audiences. Recognizing the persistence and adaptability of such actors, this research emphasizes the need for robust models that can effectively capture and analyze cross-platform narrative diffusion. To this end, we propose a framework that utilizes temporal knowledge graphs to model the evolution and relationships among narratives across platforms. We extract temporal …

Hierarchical Log Bayesian Neural Network For Enhanced Aorta Segmentation, Delin An, Pan Du, Pengfei Gu, Jian-Xun Wang, Chaoli Wang

Computer Science Faculty Publications

Accurate segmentation of the aorta and its associated arch branches is crucial for diagnosing aortic diseases. While deep learning techniques have significantly improved aorta segmentation, they remain challenging due to the intricate multiscale structure and the complexity of the surrounding tissues. This paper presents a novel approach for enhancing aorta segmentation using a Bayesian neural network-based hierarchical Laplacian of Gaussian (LoG) model. Our model consists of a 3D U-Net stream and a hierarchical LoG stream: the former provides an initial aorta segmentation, and the latter enhances blood vessel detection across varying scales by learning suitable LoG kernels, enabling self-adaptive handling …

Beyond Boundaries: A Comprehensive Survey Of Transferable Attacks On Ai Systems, Guangjing Wang, Ce Zhou, Yuanda Wang, Bocheng Chen, Hanqing Guo, Qiben Yan

Computer Science Faculty Research & Creative Works

As Artificial Intelligence (AI) systems increasingly underpin critical applications, from autonomous vehicles to biometric authentication, their vulnerability to transferable attacks presents a growing concern. These attacks, designed to generalize across instances, domains, models, tasks, modalities, or even hardware platforms, pose severe risks to security, privacy, and system integrity. This survey delivers the first comprehensive review of transferable attacks across seven major categories, including evasion, backdoor, data poisoning, model stealing, model inversion, membership inference, and side-channel attacks. We introduce a unified six-dimensional taxonomy: cross-instance, cross-domain, cross-modality, cross-model, cross-task, and cross-hardware, which systematically captures the diverse transfer pathways of adversarial strategies. Through …

Robotic Rhythm: A Contemporary Look At Ai-Driven Editing Tools’ Efficacy In Understanding And Replicating Creative Rhythm Editing Techniques., Alexander Selby-Lara, Charles Howard

Honors Thesis

It is undeniable that artificial intelligence (AI) has made its way into the film world. From AI-generated imagery and sound design in two 2025 Oscar nominees — The Brutalist and Emilia Pérez (Pulver) — to weekly updates and monthly beta releases of existing and new generative image and video models, AI-driven filmmaking tools are here to stay. But what does this mean for the post-production workflow? Much like camera development, editing technology has come a long way from flatbed film editors to Adobe Premiere Pro v. 25.0. Yet, despite each technological leap from system to system, the delicate task of …

Towards The Next Generation Of Storage Stack For Nand Flash Memory-Based Systems, Ziyang Jiao

Dissertations - ALL

The explosive growth of data has led to increased attention on NAND flash-based solid-state drives (SSDs), which offer high performance, low power consumption, and significant capacity per unit volume when compared to traditional hard-disk drives (HDDs). However, as NAND flash memory density continues to scale, modern SSDs suffer from what is known as fail-slow symptoms, and their performance degrades over time as they wear out. In this dissertation, we focus on understanding and addressing the performance, reliability, and sustainability challenges of modern flash-based storage systems by modeling key metrics, analyzing the design tradeoffs between these metrics, and optimizing existing storage …

Harnessing Llms To Detect Hate Speech, Weibin Cai

Theses - ALL

Hate is a sentiment, while hate speech refers to the expression of hate in a form that targets and attacks specific groups, such as race, religion, or gender. With the rise of the internet and social media, hate speech has spread rapidly, gaining wide exposure and posing threats to individual well-being, the profits of major tech companies, and social stability. As a result, both industry and academia have turned their attention to the study of hate speech. One of the most active areas is hate speech detection, which involves training models to predict whether a given piece of content is …

Phishy Pages - The Design Of A User-Interactive Website For Phishing Attack Evaluation, Evan C. Gregory

Honors Theses

Phishing attacks are a widespread, malicious phenomenon. These attacks steal people’s personal information, causing them ruin and lining the pockets of criminals. What makes them so dangerous is that they come in a variety of forms, including emails, websites, phone calls, and social media can be vectors for attackers. Fortunately, these attacks can be stopped by informing potential victims of common signs to look out for. Training is one of the best methods people use to teach web-users how to protect themselves. To train them, however, users must be taken through many examples of phishing attacks to learn the characteristics …

Automation Of Javanese Shadow Puppets Using Machine Control, Kristian Rice, Yinson Tso, Mukhammadali Yuldoshev

Publications and Research

The virtualization of Javanese shadow puppetry (Wayang Kulit) offers a unique opportunity to preserve and revitalize traditional performance art through immersive digital platforms. This project explores the development of a virtual Wayang Kulit experience using real-time 3D engines like Unity/Unreal Engine while focusing on simulating the mechanics and aesthetics of shadow puppet performance. The puppets are designed using detailed 2D planes and rigged with skeletal systems to reflect the stylized motion of traditional puppetry. An aspect of this project is integrating an AI-driven control system that autonomously animates the puppets, learning from recorded puppeteer performances to replicate gesture, rhythm, and …

Exploring Human-Centered Principles To Improve Lecture Slides, Joshua Harlev, Louanne Boyd

Student Scholar Symposium Abstracts and Posters

As a university emphasizing student participation and attention, lectures are central to the educational experience at Chapman. However, slide-based lectures can widely vary in quality and approach. Considering various debunkings of learning styles over the years, it seems more difficult than ever to understand how to most effectively teach students. Effective use of computerized tools has thus become increasingly important as the pace of change continues to increase. Yet, research is available on the effectiveness of teaching methods that can provide guidelines for instructors. With increasingly connected and capable devices at our fingertips, it is imperative to both use the …

Praxly: An Online Ide For The Praxis Cs Test Pseudocode, Benjamin Saupp

James Madison Undergraduate Research Journal (JMURJ)

No abstract provided.

Modeling Literary Connections: Exploring Transregional Resistance In Dalit Poetry, Antara Bhattacharyay

Mathematics, Statistics, and Computer Science Honors Projects

Structuring socio-political identities, the caste system (a graded form of hierarchy) remains entrenched in contemporary Indian society. Dalits, marginalized by the caste system, have expressed their resistance through literature, envisioning substantive equality and social change. In this thesis, I draw on digital humanities methods to examine regional variation in translated Dalit poetry from Bengali, Hindi/Urdu, Marathi, and Tamil languages. I utilize topic modeling—a machine learning algorithm that detects latent semantic structures in a text—as a point of departure for poetry analysis. I observe how topic modeling enables newer readings of the poems, revealing regionally resonant and broader Dalit themes.

Voice Interaction With Conversational Ai Could Facilitate Thoughtful Reflection And Substantive Revision In Writing, Jiho Kim, Philippe Laban, Xiang 'Anthony' Chen, Kenneth C. Arnold

University Faculty Publications and Creative Works

Writing well requires not only expressing ideas but also refining them through revision, a process facilitated by reflection. Prior research suggests that feedback delivered through dialogues, such as those in writing center tutoring sessions, can help writers reflect more thoughtfully on their work compared to static feedback. Recent advancements in multi-modal large language models (LLMs) now offer new possibilities for supporting interactive and expressive voice-based reflection in writing. In particular, we propose that LLM-generated static feedback can be repurposed as conversation starters, allowing writers to seek clarification, request examples, and ask follow-up questions, thereby fostering deeper reflection on their writing. …

Intuiting Interaction: Meta-Reasoning And Meta-Learning As Foundations For Intelligent User Interfaces, Jeffrey Hsu

Theses and Dissertations

This research presents MARCO—a cognitive framework for Intelligent User Interfaces that uses meta-reasoning for context-aware adaptation across diverse tasks. It integrates multiple reasoning modules coordinated by a Meta-Cognitive Unit that selects strategies based on evolving demands. Evaluations show MARCO outperforms baselines in reasoning accuracy and computational efficiency.

Under Pressure: A Quantitative Approach To Measuring Clutch Performance In The Nba, Jack Dell'isola

Honors Projects in Information Systems and Analytics

This research investigates the existence and relevance of clutch performance in the 2023-2024 NBA regular season. Players are analyzed both individually and against league averages to determine their clutch performance levels using an original "clutch score formula". This research aims to answer the questions of whether clutch performance is a real phenomenon, how individual player performance is affected in clutch time, and to determine a formula that can effectively predict the winner of the Clutch Player of the Year Award. The findings and formulas developed in this research help to shed light on the complexities of clutch performance, which has …

Designing An Interactive Exit Ticket System To Enhance Learning In Engineering Education, Tapanga Witt

McNair Scholars Manuscripts

Within Grand Valley State University's (GVSU) Padnos College of Engineering, many first-year Engineering courses consistently see pass rates below 70%, signaling a need for stronger academic support. This is an issue across many universities; students are underprepared and face a lot of challenges with workload, pace, and independence due to the transition from high school to college (Flanigan, 2024). For this project, I designed and developed a website-based exit ticket system to support student reflection and instructor feedback. Using UX design principles, the platform offers a weekly self-reflection form that recommends resources like tutoring, office hours, or study groups. Gamification …