Digital Commons Network^™

2025 Spring Graduate Recognition Program, Propulsion Research Center, Robert Frederick

PRC Graduate Recognition

This program includes the graduate recognition program for spring 2025. Includes photographs, upcoming events, recent publications, and student profiles.

The Evolution Of India’S ‘Counter-Terrorism (Ct)’ Policy In The 21st Century, Mule Rohit Ashok

Journal of Terrorism Studies

The changing nature of modern terrorism has proved a major threat to the global security architecture. The 9/11 terrorist attack on the United States of America, the world's ‘Police State’, is apparent. Consequently, the international community launched collective fights at different levels to deal with it. However, the nation-state at the individual level also designed a ‘Counter-Terror (CT)’ policy mechanism within the scope of the foreign policy paradigm to safeguard national security. India, since its independence, has consistently faced security challenges from terrorism from its neighbours, and has followed the same suit. The major CT policy was grounded in the …

Exploring The Dark Horizon : Artificial Intelligence (Ai) As Cyberterrorism Tools, Krisnayanto Krisnayanto, Suryadi Suryadi

Journal of Terrorism Studies

This Journal utilizes a thorough literature review approach to explore the evolving relationship between artificial intelligence (AI) and its potential use as a tool for terrorism. With the rapid advancement of AI technologies, there is a growing concern about their possible misuse by terrorist groups. This study extensively examines existing research, policy documents, and expert opinions and investigates the complex connections between AI and terrorism. The literature review delves into historical examples, current case studies, and emerging trends to clarify the various ways in which AI could be employed for harmful purposes by terrorist organizations. By analyzing recruitment strategies, communication …

Emerging Technologies In Boko Haram's Operations And Counter-Terrorism Efforts In Central Africa, Abraham Ename Minko

Journal of Terrorism Studies

The interplay between terrorism and technology in Central Africa has intensified, particularly with Boko Haram’s rise. This research explores how emerging technologies enhance Boko Haram's operations and the corresponding counter-terrorism efforts. It examines Boko Haram’s use of social media for recruitment, encrypted messaging for secure communication, and advanced weaponry like drones and improvised explosive devices (IEDs). These technologies have expanded Boko Haram’s reach and operational efficiency, challenging security forces. The study also evaluates technological countermeasures implemented by Central African governments and international bodies, including surveillance, cyber intelligence, and data analytics. It assesses the effectiveness of these measures, noting successes and …

Light & Faith: May 2025, Taylor University

Light & Faith

No abstract provided.

May 2025 News Releases, University Of Montana--Missoula. Office Of University Relations

University of Montana News Releases, 1928, 1956-present

No abstract provided.

Optimized Filtrations For Stormwater Quality Improvement By Porous Media–Biochar Applications: Column Experiments And Inverse Modeling, Sumiaya Amin Preota, Chu-Lin Cheng, Myung Hwangbo, Jongsun Kim

School of Earth, Environmental, & Marine Sciences Faculty Publications

Stormwater reuse plays a critical role under changing climates and increasing water demands. This study investigates the removal efficacy of lead (Pb2+) and ammonia (NH3) using sand and rice husk (RH) biochar for potential stormwater quality improvements and treatments. Column experiments combined with HYDRUS inverse modeling were conducted to optimize adsorption isotherms from breakthrough curves. Among linear and non-linear models, the Langmuir and Freundlich models performed better for sand and biochar, respectively. RH biochar showed much higher adsorption capacity of both Pb2+ (4.813 mg/g) and NH3 (6.188 mg/g). In contrast, sand showed a relatively limited adsorption capacity for Pb2+ (0.118 …

Exploring The Biasing Effects Of Gender On Personality Disorder Diagnoses Formulated By Artificial Intelligence, Zoe Colclough

Student Theses

Gender bias is prevalent in personality disorder assessments, and while artificial intelligence has been posited as a solution to improve diagnostic objectivity and accuracy, the potential for such technologies to propagate human gender bias in mental health contexts remains underexplored. This study investigated the influences of gender bias on the diagnostic performance of ChatGPT-4o for personality disorders using three factorial research designs, which involved experimentally manipulating patient gender in a combined sample of 360 vignettes and case studies. Vignettes were synthesized through a novel artificial intelligence-assisted methodology established for this research, and case studies were identified from the literature. Significant …

Examining Portrayals Of Gender In The Design Of Ai Voice Assistants, Olivia Fratangelo

Student Theses

This capstone project provides a theoretical framework for shifting the ways in which we think about and discuss anthropomorphized features of technological products, focusing specifically on applying this framework to the gendered design of AI voice assistants. The goal in providing this framework is to prompt readers to consider how we can think more critically about technology beyond our “preferences” and biases. Our roles as consumers of technology do not have to be passive ones. In fact, the dialectical relationship between humanity and technology makes everyone who contributes to society not just a consumer, but a developer of technology in …

May 1, 2024, James Madison University

The Breeze, 2020-

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia.

Movement Ecology And Trophic Dynamics In The Northern Gulf Of Mexico: Implications For Fisheries Management, Calvin Chee

Master's Theses

The northern Gulf of Mexico (nGOM) is a diverse and productive region for living marine resources. The region supports lucrative commercial and recreational fisheries ranging from low-trophic-level species, such as penaeid shrimps and forage fishes, to high-trophic-level predators (e.g. Yellowfin Tuna). This thesis contributes to the region’s ecological knowledge, with the primary aim of enhancing management efforts and providing direct management advice to two important fisheries. In Chapter 1, we develop a traditional per-recruit model for Southern Flounder, as well as a spatiotemporally integrated per-recruit model that incorporates the spatial distribution of fishing effort and the stock’s movement ecology. Fish …

Mapping The Underthing: Literary Geography And Geographic Education In The Slow Regard Of Silent Things, Colby Mcclain

Master's Theses

This thesis examines the imagined geography of Patrick Rothfuss’ The Slow Regard of Silent Things. Through textual analysis, it investigates how fictional spaces can be mapped, the significance of toponyms (i.e., place-names), and the broader implications for literary and geographic studies. Of the fifty-two (52) toponyms analyzed, thirty-eight (38) were meaningfully identified using the text and the Oxford English Dictionary (OED), revealing deliberate naming schemes associated with function, emotion, or symbolism. These findings provide insight into the main character’s world, and her unique relationship with space and place. This study demonstrates that even wholly imagined settings have an underlying …

Chemistry Education At The University Of Southern Mississippi Through Computation And Active Learning Methods, Sadie Pitre

Honors Theses

Education is one of the pillars of society. It evolves alongside scientific progress, shaping how students learn and engage with complex topics. The incorporation of new educational standards at The University of Southern Mississippi (USM) was implemented in two parts: through computational chemistry laboratory exercises for teaching laboratories and through the synthesis of organic molecules for research projects in an upper-level spectroscopy class. The goal of these projects is to improve learning of abstract and/or complex topics beyond the teaching methods traditionally utilized in the undergraduate laboratory and in the classroom.

Computational chemistry, which uses theoretical calculations to model molecular …

May 1, 2025, The Daily Mississippian

Daily Mississippian (all digitized issues)

No abstract provided.

Advanced Day-Ahead Scheduling Of Hvac Demand Response Control Using Novel Strategy Of Q-Learning, Model Predictive Control, And Input Convex Neural Networks, Rahman Heidarykiany, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present a Q-Learning optimization algorithm for smart home HVAC systems. The proposed algorithm combines new convex deep neural network models with model predictive control (MPC) techniques. More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. As a novel RL approach, the proposed algorithm generates day-ahead HVAC demand response (DR) signals in smart homes that optimally reduce and/or shift peak energy usage, reduce electricity costs, …

The Relationship Between Weather Variablity And Agricultural Land Cover Change In North Dakota (1997-2023) And Its Implication For Future Change, Sabrina Karim

Theses and Dissertations

Climate variability and weather patterns play a critical role in shaping agricultural land use and land cover (LULC), particularly in states like North Dakota, where agriculture dominates the landscape. This study explores the impacts of climatic factors—specifically rainfall, temperature, and Growing Degree Days (GDD)—on agricultural land cover (ALC) changes in North Dakota from 1997 to 2023, with projections for 2033. By combining historical analysis and predictive modeling, the research examines how climate variability has influenced crop dynamics and provides insights into future scenarios. The research uses advanced geospatial tools, including Google Earth Engine, and machine learning techniques such as Random …

The Antitrust–Copyright Interface In The Age Of Generative Artificial Intelligence, Daryl Lim, Peter K. Yu

Faculty Scholarship

The U.S. government's antitrust actions against Big Tech have recently surged in response to the growing dominance of Amazon, Apple, Google, Meta, and Microsoft. In fall 2023, the Federal Trade Commission filed a controversial submission in response to the U.S. Copyright Office's request for comments on artificial intelligence (AI) and copyright. This submission hinted at the agency's eagerness to fully deploy its enforcement powers in the AI sector, including targeting AI developers that have used copyrighted works without authorization to train AI models.

This article examines the changing interface of antitrust and copyright law in the age of generative AI. …

The "Not Seen" Effect Of International Financial Centers: Innovation In The Global Financial Ecosystem, Charlotte Ku, Andrew P. Morriss

Faculty Scholarship

International Financial Centers (IFCs) are hubs of legal and financial innovation, developing specialized frameworks that facilitate cross-border investment, enhance global capital mobility, and support economic growth. Through jurisdictional competition, professional clustering, and adaptive regulatory frameworks, IFCs have pioneered legal structures that enable enterprises of all sizes to participate in the global economy. Using case studies of the International Business Company, the Limited Liability Company, the Protected Cell Company, and advances in trust law and applying the theoretical frameworks of social scientist Richard Florida and psychologist Mihalyi Csikszentmihalyi, this Article illustrates how IFCs serve as laboratories for financial experimentation, generating widely …

Building A Virtual Gallery: How The User Journey Can Inform Technological Innovation Towards Best Practice In Creating A Virtual Gallery?, Paula Cordeiro

Postgraduate

Building a Virtual Gallery: How can the user journey inform technological innovation towards best practice in creating a virtual gallery?

This research investigates how user journey frameworks can inform technological innovation towards best practice in creating a virtual gallery and how virtual hubs can serve as cultural and heritage art spaces, through collaborative interaction with Regional Councils. This exegesis, together with the accompanying creative artwork, Byron Bay Regional Gallery_Virtual Hub (BRGVirtual-Hub), explore the potential of VR gallery design as a platform to emerge from my literature review, technological innovation, cultural and social interaction, artistic collaboration and real-time connectivity among local …

Yield And Economics Following 5 Years Of Integrated Weed Management In Cotton, Amar Godar, Jason K. Norseworthy, L. Tom Barber, Roger Farr, Ty Smith

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

The implementation of integrated weed management (IWM) practices in conventional management systems involves additional costs and can influence both short-term and long-term cotton (Gossypium hirsutum L.) yields, ultimately affecting economic viability. This study, conducted from fall 2018 to fall 2023 near Marianna, AR, evaluated four IWM practices in a large-plot, fixed-plot factorial design: zero tolerance for weed seed rain, soil inversion deep tillage every third year in the fall, a preplant terminated cereal rye cover crop, and dicamba-resistant cotton technology. Long-term economic impacts were assessed using the 5-year average cost-adjusted yield, with the base program (excluding all IWM practices) serving …

Intelligent Crowdsourcing Based On Online Social Networks, Adedamola Adesokan

Electrical and Computer Engineering ETDs

The prevalence of Online Social Networks has completely changed how individuals communicate and cooperate. This dissertation explores the integration of intelligent crowdsourcing mechanisms into OSNs, focusing on game theory, reinforcement learn- ing, and social network dynamics to enhance the allocation of tasks, participation by users, and distribution of rewards. It proposes several models that utilize trust- based models, hedonic coalition games, and influencer dynamics for optimization of crowdsourcing. The major challenges to be addressed include task selection, reward distribution, and incentivizing participation, taking into consideration aspects re- lated to social influence, trust, and user engagement. The models so proposed have …

But For A Free Press: A Response To Press Freedom Skeptics, Patrick J. Charles, Kevin Francis O'Neill

William & Mary Bill of Rights Journal

This Article is divided into three Parts. Part I will outline the history-in-law case for why the historical record sufficiently supports recognizing distinct constitutional press freedoms. Part II then provides a history-in-law response to some of the most common arguments made by press freedom skeptics as to why distinct constitutional press freedoms should not be recognized by the courts. Lastly, Part III makes the case for why the recognition of distinct constitutional press freedoms should become a jurisprudential reality and provides a roadmap to accomplish this.

This abstract has been taken from the authors' introduction.

A Comprehensive Performance Comparison Of Machine Learning And Federated Learning For Intrusion Detection In Vehicular Ad-Hoc Networks Using Can-Bus Data, Tim Leonhardt

Honors Theses

Federated Learning (FL) is a Machine Learning (ML) approach that decentralizes training across distributed devices, eliminating the need to centralize data. Unlike traditional ML, where models are trained on aggregated data, FL sends a global model to multiple nodes for local training, with updated parameters transmitted back to the server for aggregation. This process preserves data privacy, making FL ideal for sensitive applications like cybersecurity. However, FL introduces challenges such as data heterogeneity, communication overhead, and difficulties in achieving model convergence, which can impact performance.

This study investigates a fundamental assumption in ML and FL research: that the superior performance …

Cache-Augmented Generation In Rag Pipelines: Fast And Memory-Efficient Approach To Multi-Agent Knowledge Query Systems, Yaju Gopal Shrestha

Honors Theses

This thesis presents an implementation and evaluation of Cache-Augmented Generation (CAG) for knowledge query systems, building upon the approach introduced by Chan et al. (2024). Traditional Retrieval-Augmented Generation (RAG) systems (Lewis et al., 2020) face challenges including high latency, excessive memory usage, and complex infrastructure requirements. By implementing a cache-augmented architecture that preloads relevant knowledge and eliminates real-time retrieval, our approach significantly improves response time while reducing resource requirements. The research demonstrates the effectiveness of CAG through a comprehensive implementation for The University of Southern Mississippi's chatbot system, achieving a 49.02% improvement in response time compared to traditional RAG approaches. …

Cellular Telemetry For Real-Time River Flow Velocity Data From Fluvial Acoustic Tomography Loggers, Joshua Lee Seymour

Honors Theses

Streamflow is a critical element in understanding watershed processes and the effects of land use on those processes because it is the primary medium through which water, sediment, nutrients, organic material, thermal energy, and aquatic species move. Fluvial Acoustic Tomography (FAT) systems offer accurate direct measurements of river section-averaged flow velocity by measuring reciprocal acoustic travel times between at least two acoustic nodes positioned on opposite riverbanks. However, similar to many in-situ sensors used in estuarine and riverine environments, FAT loggers require manual data retrieval, which is time-consuming, labor-intensive, and limits real-time access and increases maintenance costs. This project presents …

Tuning The Morphology Of Triblock Copolymers Via Homopolymer Blending, John F. Searles

Honors Theses

Morphology plays an important role in the physical properties of block copolymer (BCP) materials. Depending on the type of morphology and chemical composition of the blocks, BCPs are used in applications ranging from soft biomaterials for biomedical devices to rigid materials for ballistics protection. Due to incompatibility between comonomers and required block weight ratios to achieve targeted morphologies, it is generally necessary to use complex, time-consuming, and expensive synthetic techniques to prepare BCPs. As a result, there is increased interest in the development of new processing methods to tailor block copolymer morphology without the need for additional synthesis. The morphological …

The Numerical Method For Finding All The Zeros Of A Function F (X) On An Interval [A,B], Franissa Simon

Honors Theses

In this study, we develop a simple mathematical method for finding all the roots of a function on a specified interval. Existing classical numerical methods, including the Bisection Method, Secant Method, and Newton Method, cannot find all the zeros of a function f (x) on an interval [a,b]. Popular numerical root solvers like Matlab’s ‘fzero’, Maple’s ‘fsolve’, and SageMath’s ‘find_root’ typically yield only a single zero. This thesis explores a proposed interval computation bisection method, a systematic approach based on the traditional Bisection Method and interval computation. Unlike traditional bisection, which relies on the intermediate value theorem, this approach uses …

Nostalgia, Economic Revitalization, And Community Relationships In Hattiesburg's Recent Historic Preservation Efforts, Jordan Jones

Honors Theses

This paper examines the reasons behind the modern interest in historic preservation in Hattiesburg, Mississippi, and argues that its supporters are driven primarily by nostalgia towards what they envision as “Old Hattiesburg” and its aesthetics, interest in economic opportunities, and the strengthened sense of community made possible through historic preservation. From the foundation of Hattiesburg to today, there have been shifts in interest in Downtown and its historic districts, and they fluctuate based on changing political, economic, and social trends. In order to contextualize Hattiesburg’s historic preservation, this thesis draws upon secondary scholarship on historic preservation, economic revitalization, and historical …

Sensory Awareness In Architectural Design And Construction: A Guide To Inclusion And Hospitality For All, Morgan Harwell

Honors Theses

Modern approaches to architectural design and construction have gravitated toward elegance, glossiness, and over exaggeration of a bright environment through materials such as marble, glass, white paint, and fluorescent lighting. While these choices can be alluring, their impact on individuals with disabilities and sensory processing disorders is typically dismissed. This study explores the intersection of architectural elements — such as lighting, noise, scent, and spatial organization — and sensory overload in disabled individuals. Through a detailed literature review, education of architectural principles, and incorporation of building techniques, this study proposes a computer-generated three-dimensional model of a shopping center. The primary …

Evaluating Accuracy In Legal Research: A Comparative Analysis Of Traditional And Artificial Intelligence-Driven Methods, Lily Collins

Honors Theses

Legal professionals are challenged with performing accurate legal research to meet professional standards. The use of artificial intelligence (AI) presents a potential for enhanced efficiency. However, knowledge and process gaps exist, questioning the accuracy of results generated by AI. The uncertainty of accurate results poses a risk for poor outcomes for all stakeholders. This thesis aimed to quantitatively measure the accuracy of AI legal research in comparison to traditional legal research. Accuracy and relevance were measured by analyzing case precedent results using three legal research platforms, Westlaw, Nexis Uni, and Chat GPT. The three platforms represented traditional and AI-driven research, …