Digital Commons Network^™

Enhanced Tea Algorithm Performance Using Affine Transformation And Chaotic Arnold Map, Nada Hussein M. Ali, Mays M. Hoobi, Sura Abed Sarab Hussien

Mesopotamian Journal of Computer Science

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing …

Enhanced Iot Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection And Adaptive Smote, Sura Abed Sarab Hussien, Mustafa S. Ibrahim Alsumaidaie, Nada Hussein M. Ali

Mesopotamian Journal of Computer Science

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrate that GWO reduces features from 32 …

Dgen: A Dynamic Generative Encryption Network For Adaptive And Secure Image Processing, Mohammed Rajih Jassim, Qusay M. Salih, Ghada Al-Kateb

Mesopotamian Journal of Computer Science

Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public …

Lightweight Deep Reinforcement Learning Model For Energy-Efficient Resource Allocation In Edge Computing, Ghassan A. Abed, Mohanad A. Al-Askari

Mesopotamian Journal of Computer Science

A lightweight digital twin model for a single 6G cell operating in the D-band (140 GHz) with a 1 GHz bandwidth is presented in this work with the goal of assessing the cell's capacity, coverage, and terminal time in order to support extended reality (XR) applications. With a tangent dispersion of 3 dB and a path exponent of n = 2.2, the model is based on the free-space loss equation as per ITU-R Recommendation P.525. The instantaneous capacity is determined using the Shannon-Hartley theorem. Three XR sessions are created every minute using a Poisson method, and their durations are determined …

Agentic Ai-Enhanced Virtual Reality For Adaptive Immersive Learning Environments, Indra Kishor, Udit Mamodiya, Mohammed Almaayah, Amer Alqutaish, Rami Shehab, Theyazn H. H. Aldhyani

Mesopotamian Journal of Computer Science

Immersive learning using Virtual Reality (VR) has gained prominence for delivering experiential, engaging education. However, most VR learning environments lack real-time adaptability, personalization, and cognitive responsiveness. This study presents an Agentic AI-enabled VR framework that autonomously adjusts pedagogical content, interaction style, and challenge level based on learner behavior, emotions, and performance feedback. The proposed system integrates a reinforcement learning-based agent with a virtual reality module to form an intelligent tutor capable of independent decision-making. A neuro-symbolic model processes multi-modal feedback (gesture, speech, gaze, performance) to determine context-aware pedagogical strategies. The system employs a self-evolving curriculum logic that adapts in real …

A Brief Look At Authoritarianism And Totalitarianism Through A Perspective Of Jewish Law And Tradition, Samuel J. Levine

Scholarly Works

A view of authoritarianism and totalitarianism through a perspective of Jewish law and tradition might take various forms and draw upon different approaches, depending on a number of components, including definitions of terms, modes of analysis, and the scope of disciplines and materials to be incorporated. Rather than attempting to present a comprehensive or determinative presentation of historical and philosophical considerations of these issues, this essay will briefly explore conceptual lessons from narrative, political, and legal sources of Jewish tradition, suggesting that Jewish thought recognizes, at once, both the importance of unity and authority and the dangers of authoritarianism and …

Foundation Models Boost Low-Level Perceptual Similarity Metrics, Abhijay Ghildyal, Nabajeet Barman, Saman Zadtootaghaj

Computer Science Faculty Publications and Presentations

For full-reference image quality assessment (FR-IQA) using deep-learning approaches, the perceptual similarity score between a distorted image and a reference image is typically computed as a distance measure between features extracted from a pretrained CNN or more recently, a Transformer network. Often, these intermediate features require further fine-tuning or processing with additional neural network layers to align the final similarity scores with human judgments. So far, most IQA models based on foundation models have primarily relied on the final layer or the embedding for the quality score estimation. In contrast, this work explores the potential of utilizing the intermediate features …

Osa-Diff: An Origin Sampling Based Adversarial Attack Using Diffusion Models, Shayan Jalalipour, Banafsheh Rekabdar

Computer Science Faculty Publications and Presentations

Diffusion models are becoming an increasingly popular emerging technology, however their use in adversarial attacks remains a scarcely explored topic. We show that diffusion models can be used to create end-to-end hidden adversarial perturbations with high rate of success, and propose a novel diffusion based adversarial attack that allows for substantially faster training time (through improved convergence on high quality images) and with substantially less computational overhead than typical diffusion model training

Polynomial-Time Constant-Approximation For Fair Sum-Of-Radii Clustering, Sina Nezhad, Sayan Bandyapadhyay, Tianzhi Chen

Computer Science Faculty Publications and Presentations

In a seminal work, Chierichetti et al. [20] introduced the (t,k)-fair clustering problem: Given a set of red points and a set of blue points in a metric space, a clustering is called fair if the number of red points in each cluster is at most t times and at least 1/t times the number of blue points in that cluster. The goal is to compute a fair clustering with at most k clusters that optimizes certain objective function. Considering this problem, they designed a polynomial-time O(1)- and O(t)-approximation for the k-center and the k-median objective, respectively. Recently, Carta et …

Retrieval-Augmented Feature Generation For Domain-Specific Classification, Xinhao Zhang, Jinghan Zhang, Fengran Mo, Dakshak Keerthi Chandra, Yu-Zhong Chen, Fei Xie, Kunpeng Liu

Computer Science Faculty Publications and Presentations

Feature generation can significantly enhance learning outcomes, particularly for tasks with limited data. An effective way to improve feature generation is to expand the current feature space using existing features and enriching the informational content. However, generating new, interpretable features usually requires domain-specific knowledge on top of the existing features. In this paper, we introduce a Retrieval-Augmented Feature Generation method, RAFG, to generate useful and explainable features specific to domain classification tasks. To increase the interpretability of the generated features, we conduct knowledge retrieval among the existing features in the domain to identify potential feature associations. These associations are expected …

“Lost-In-The-Later”: Framework For Quantifying Contextual Grounding In Large Language Models, Yufei Tao, Adam Hiatt, Rahul Seetharaman, Ameeta Agrawal

Computer Science Faculty Publications and Presentations

Large language models (LLMs) are capable of leveraging both contextual and parametric knowledge but how they prioritize and integrate these sources remains underexplored. We introduce CoPE, a novel framework for systematically quantifying contextual grounding in LLMs. CoPE distinguishes between contextual knowledge (CK) and parametric knowledge (PK), enabling fine-grained attribution across languages and tasks. Using our newly created MultiWikiAtomic dataset in English, Spanish, and Danish, we analyze how LLMs integrate context, prioritize information, and incorporate PK in open-ended question answering. We find that across models and languages, only around 50 to 76 percent of outputs are grounded in the given context, …

Scitopic: Enhancing Topic Discovery In Scientific Literature Through Advanced Llm, Pengjiang Li, Zaitian Wang, Xinhao Zhang, Ran Zhang, Lu Jiang, Pengfei Wang, Yuanchun Zhou

Computer Science Faculty Publications and Presentations

Topic discovery in scientific literature provides valuable insights for researchers to identify emerging trends and explore new avenues for investigation, facilitating easier scientific information retrieval. Many machine learning methods, particularly deep embedding techniques, have been applied to discover research topics. However, most existing topic discovery methods rely on word embedding to capture the semantics and lack a comprehensive understanding of scientific publications, struggling with complex, high-dimensional text relationships. Inspired by the exceptional comprehension of textual information by large language models (LLMs), we propose an advanced topic discovery method enhanced by LLMs to improve scientific topic identification, namely SciTopic. Specifically, we …

Public Constitutional Ai, Gilad Abiri

Georgia Law Review

We are increasingly subjected to the power of AI authorities. Machine learning models now underpin algorithmic markets, determine whose speech is amplified or restricted, shape government decisions ranging from resource allocation to predictive policing, and influence our access to information on critical issues such as voting and public health. As AI decisions become inescapable, entering domains such as healthcare, education, and law, we must confront a vital question: How can we ensure that AI systems, which increasingly regulate our lives and make decisions that shape our societies, have the authority and legitimacy necessary for effective governance?

To secure AI legitimacy, …

The New Game Theory, Cortelyou C. Kenney

Georgia Law Review

Game theory and the legal system it models are deeply indebted to the idea of efficiency and efficient outcomes. A great many scholars use game theory to rationalize approaches based on efficiency not only to commercial transactions but also to the legal system writ large, including the tort law system and the criminal justice system.

Efficiency and efficient outcomes have a storied history dating back to Vilfredo Pareto, Ronald Coase, and even before that to Adam Smith. But the person who truly popularized the idea of efficiency was John Nash, who won the Nobel Prize for his work on noncooperative …

Learning To Learn: Underprepared College Students Who Succeeded, Todd Spellman

Dissertations and Theses @ UNI

Post-secondary remediation is a topic of great concern for legislators and educators alike. Many describe it as a problem in need of a solution and try to pursue what they see as possible remedies. But solutions are already present in the stories of those who have already successfully navigated this pathway of remediation in college. This study will explore student successes through their remedial coursework at colleges in the American Midwest. While recognizing the historical and cultural context that makes remediation necessary in open-enrollment institutions like community colleges, this study sought student feedback to explore what factors the students felt …

Refining Population-Level Measures Of Early Childhood Vaccination Coverage Using National Immunization Survey-Child Data, Alexandria Nicole Albers

Graduate Student Theses, Dissertations, & Professional Papers

Background: From 2011-2021, the U.S. Advisory Committee on Immunization Practices (ACIP) recommended 10 vaccine series by age 24 months, with guidelines for minimum vaccination age, maximum age for rotavirus vaccination, minimum dose intervals, and a catch-up schedule for delayed series initiation. National vaccination surveillance evaluates series completion based on whether children received the recommended number of doses, including a combined 7-vaccine metric (completed seven series collectively). However, this approach overlooks: 1) vaccinations given too early, too late, or too close together, 2) catch-up schedule vaccinations, and 3) completion of all 10 recommended vaccines.

Purpose: To refine national childhood vaccination coverage …

Evaluating The Accuracy Of Stature Estimation From Tibial Radiographs Using Known And Newly Developed Regression Formulas, Atlantis Kae Baron

Graduate Student Theses, Dissertations, & Professional Papers

This study assesses the accuracy of stature estimation from tibial radiographs using digital measurements as an alternative to traditional osteometric tools. Stature estimation is crucial in forensic anthropology for identifying individuals, especially cases involving skeletal remains. Traditional methods rely on physical measurements and established regression formulas, such as those by Trotter & Gleser (1958).

This research analyzed tibial radiographs from the Forensic Anthropology Skeletal Trauma (FAST) database with ImageJ software to measure tibial lengths digitally. The sample included 59 tibiae, with measurements compared against three regression formulas; Trotter & Gleser (1958), Simon et al. (2023), and a new regression formula …

Binoculars To Bytes: Development And Field Validation Of An Ai-Driven System For Avian Monitoring, Christian J. Dupree

Graduate Student Theses, Dissertations, & Professional Papers

Autonomous camera-trap arrays coupled with artificial-intelligence (AI) vision can lift bird monitoring beyond the spatial, temporal, and labor limits of traditional field surveys. We present Binoculars to Bytes (B2B), an open-source pipeline that turns 180–360° time-lapse imagery into analysis-ready avian data. At Freezout Lake Wildlife Management Area (Montana, USA) the system ran four-hour morning deployments during spring and fall migrations (2023–2024). A YOLO-NAS detector, incrementally refined with a “Specialized Localized Iterative Model” workflow, quadrupled local accuracy and, after confidence-based species-binning, cut false-positive rates in half. Daily AI species lists were benchmarked against contemporaneous eBird citizen-science checklists and recovered ≥ …

College Athlete Workload Management To Improve Performance, Brody Reid

Graduate Student Theses, Dissertations, & Professional Papers

Load management is an often used and misunderstood term within the realm of sport science. It has been described as the reason behind numerous soft tissue injuries as well as being the reason star athletes sit on the bench for games. This review aims to synthesize the existing literature regarding the workload management paradox within sport. Seminal work in this topic has been gathered mostly by Tim Gabbett in the paper “The Injury Prevention Paradox” where a relationship between fitness gain and fatigue accrued is outlined. This theory was first proposed by Roger Bannister in 1975. This paper …

An Interdisciplinary Unit For Today's Learners: Integrating Science, English, And Art To Teach Climate Change, Sydney M. Ruby-Pasternak

Graduate Student Theses, Dissertations, & Professional Papers

As today’s global challenges grow increasingly complex, interdisciplinary thinking is essential for students to make meaningful connections in their learning. Despite this need, high school students continue to have educational experiences in one-subject classrooms, often preventing them from engaging in integrated learning models. This professional project addresses the gap by developing a five-week interdisciplinary unit titled Brushstrokes of Change, which combines climate science with English language arts and visual arts to amplify student understanding of climate change concepts. This unit was designed for grades 9-12 and prioritizes 21^st-Century skills in critical thinking, communication, creativity, and collaboration through …

Sunrise In The Heartland: The Ahmadiyya Movement And The Foundations Of African American Islam, Hazel Videon

Graduate Student Theses, Dissertations, & Professional Papers

During the early 1920s, an immigrant missionary from colonial India named Muhammad Sadiq established headquarters in Chicago for a branch of Islam called the Ahmadiyya Movement in Islam (AMI). The AMI became the first institutional expression of Islam in the United States to draw a significant number of American converts and was particularly popular among African Americans. Following the Second Great Migration, Black migrants to the urban Midwest sought new ways to express their identity, fulfill both spiritual and material needs, and resist racist violence. The AMI became attractive to them as an alternative to respectability politics and drew upon …

Eros And The Sublime: Tools For Reaching Toward An Altered Ecological Consciousness, Aineka Carlson

Graduate Student Theses, Dissertations, & Professional Papers

This thesis explores connections between the Kantian sublime and Anne Carson’s ideas regarding “eros.” Since Kant’s Critique of Judgement was published in 1790, the Kantian sublime has grown in popularity and been utilized by theorists and creative writers alike. While the Kantian sublime is often associated with nature in popular culture, there are certain egocentric and phallocentric elements of this mode of thinking that might inhibit a biocentric mindset. Through a character study of Oryx from Margaret Atwood’s novel Oryx and Crake, this thesis draws relations between the subjugation of women, nature, and the ways in which the popularized …

Structural Optimization And Stability Enhancement Of Uba(2) And Ntl9 Using The Computational Tool: Emcast, Bahar Ghazi Esfahani

Graduate Student Theses, Dissertations, & Professional Papers

This study enhances protein stability prediction by refining EmCAST (Empirical C-Alpha Stability Tool), a computational tool used to identify stabilizing mutations in protein domains. We applied EmCAST to two model proteins: the α-helical ubiquitin-associated domain 2 (UBA(2)) and the α/β N-terminal domain of ribosomal protein L9 (NTL9). Protein stability is critical for proper function, and mutations can lead to misfolding and disease. To validate EmCAST’s predictions, guanidine hydrochloride-induced denaturation was monitored using circular dichroism (CD) spectroscopy for both wild-type and mutant variants. Results guided refinements to EmCAST’s algorithm, incorporating new experimental datasets to improve accuracy. Additionally, we examined the assumption …

Understanding The Factors That Influence University Environment: Gender Differences In Perceptions Of Female And Male Stem Graduate Students., Rachel Robinson

Graduate Student Theses, Dissertations, & Professional Papers

Despite increasing female representation in higher education, women remain underrepresented in STEM (science, technology, engineering, and mathematics) fields. This thesis investigates gendered perceptions of university environment among STEM graduate students, focusing on the role of faculty-student interaction as a form of social capital. The survey was developed and administered with Qualtrics Online Survey Software by members of the Social Science Research Group of the Pacific Northwest Circles of Success: Mentoring Opportunities in STEM. All graduate students in the participating universities pursuing master’s and doctoral degrees in a National Science Foundation STEM recognized program were eligible to complete the survey. Using …

Kinetic Grain Growth In Firn Induced By Meltwater Infiltration On The Greenland Ice Sheet, Kirsten Leigh Gehl

Graduate Student Theses, Dissertations, & Professional Papers

The microstructure of polar firn governs its porosity, permeability, and compaction rate, and is therefore important to studies of surface elevation change, heat and gas exchange, and meltwater infiltration on ice sheets. Previous work on high-elevation, dry-firn has identified two distinct atmospheric drivers of kinetic grain growth in deposited snow, but both mechanisms result in near-surface mm-scale layers. In this work, we show that meltwater infiltration through surface wetting fronts and deep preferential flow in the Greenland Ice Sheet (GrIS) percolation zone leads to the formation and preservation of centi- to decimeter scale layers of faceted firn, ranging from faceted …

Slaying The Windigo: Fear And Faith In The Anthropocene, Daniel J. Irwin

Graduate Student Theses, Dissertations, & Professional Papers

This thesis examines the changing affect of fear in the environment and how it is influencing writing in the Anthropocene. Chapter one lays the groundwork for the present moment of ecocriticism, examining how the relationship with the environment has changed throughout the history of ecocritical writing. The second chapter examines how fear has been an intrinsic element of environmental storytelling, starting with the romantic ideas of the sublime. With the recognition of the impact that humanity has had on Earth over the past several centuries, and the accelerating acceptance of the idea of the Anthropocene since the turn of the …

Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young

Graduate Student Theses, Dissertations, & Professional Papers

Wildfire models drive billions of dollars in risk mitigation efforts. However, the modeling community currently lacks a representative fuelscape on which to base simulations of fire spread in the built environment and the wildland-urban interface (WUI) where vegetation and structures act together as fuel for wildfire. This thesis advances wildfire risk modeling by addressing the underdeveloped representation of the built environment in existing frameworks. By identifying inconsistencies in how structure and defensible space features are defined and used across empirical studies, predictive indices, and fire spread models, this research lays the groundwork for standardized modeling approaches and feature selection (Chapter …

Worn History: The Biography And Value Transformation Of Emma Sansaver's Dress, Lauren I. Stgeorge

Graduate Student Theses, Dissertations, & Professional Papers

This thesis examines the life of Emma Sansaver’s beaded buckskin dress as both a material object and a cultural witness. Worn during her time at the Fort Shaw Government Industrial Indian Boarding School and the 1904 St. Louis World’s Fair, the dress intersects with assimilationist policy, Indigenous resilience, public spectacle, and personal memory. Unlike the regalia of her teammates, Emma’s dress was preserved, first by Emma herself, then by her descendants, and continues to be cared for and displayed in educational and institutional settings today.

Using the theoretical frameworks of Arjun Appadurai and Igor Kopytoff, this project approaches the dress …

Reinventing The Concepts Of Group And Isomorphism In Abstract Algebra, Chrisitan José Lopez-Mercado

Graduate Student Theses, Dissertations, & Professional Papers

This study explores the reinvention of the concepts of group and isomorphism in abstract algebra through design-based research. It investigates how students can reinvent these concepts and how mathematical artifacts transform their mathematical reasoning during the reinvention process. The study identifies a reinvention ecology comprising three interrelated components: students' mathematical activity, social interaction, and the continual emergence of mathematical artifacts. Using the guided reinvention principle of realistic mathematics education, students engaged with contextual situations, such as a 12-hour analog clock and the symmetries of an equilateral triangle, to progressively develop structural observations, formalize group axioms, and assemble them into the …

Bridging The Gap Between Plot-Level And Landscape-Scale Analysis For Wildfire Risk Assessment, Vanessa Leigh Niemczyk

Graduate Student Theses, Dissertations, & Professional Papers

Remote sensing technology has advanced greatly over the past couple of decades proving its ability to aid in wildfire risk assessment and improve our understanding of forest structure and fuel inventory across the landscape. While some aerial and satellite sensors perform better than others, they all have a common weakness, their reduced ability to capture understory fuels with high detail. Terrestrial laser scanning is an emerging solution due to its understory perspective. This research leverages the beneficial aspects of both terrestrial laser scanning and various aerial- or satellite-based remote sensing platforms (aerial laser scanning, digital aerial photogrammetry, and Sentinel-2) to …