Digital Commons Network^™

Finding A Way Out Of The Filter Bubble: The Confusion Of A Heavy Social Media User, Longwen Miao

Masters Theses

This thesis studies how algorithmic recommendation systems reshape visual perception, aesthetic judgment, and the construction of selfhood within contemporary digital culture.

Everything begins with the experience of repeatedly encountering algorithmically recommended content on everyday digital platforms. On these platforms, images, sounds, and social interactions are continuously selected, repeated, and reorganized by predictive systems, forming an environment in which perception is constantly structured and adjusted.

From this observation, the research raises two central questions: how do algorithmic recommendation systems reshape visual perception, aesthetic judgment, and self-recognition, and how might these systems be intervened in or made perceptible through artistic practice? Within …

Computational-Experimental Synergy As A Predictive And Interpretive Tool Through Metal-Organic Framework Investigations, Cristian Sayers

Graduate Student Theses and Dissertations

In the search for tunable materials platforms capable of addressing both clean energy conversion and viable post-combustion carbon capture, metal-organic frameworks (MOFs) have emerged as a uniquely versatile class of porous solids offering high specific surface area, structural tunability, and chemically addressable metal nodes and organic linkers. Realizing their potential requires understanding behavior that spans atomic-scale electronic structure and bulk-scale property response, a regime in which neither computation nor experiment alone is sufficient. This work attempts to develop a tighter integration between density functional theory (DFT) and laboratory investigation, treating the two modalities as mutually informing probes of the same …

Productive Armature, Gabriel Ofem Peter

Masters Theses

What if water was all you had, what if your only source of survival was a body of water? I shudder to think that some people get to be put in this situation in the world we live in. As I understand the importance of water to survival, it is obvious that water can be the only lifeline of survival for a community. This is the experience for residents of Makoko, Lagos. Their survival depends on the Lagos Lagoon, a large body of water flowing in from the Atlantic Ocean. This research looks beyond the surface of what this community …

Frictional Intelligence, Posheng Cheng

Masters Theses

This is an experimental interaction design project that challenges anthropomorphism in human-computer interaction. In particular, the recent advancement of artificial intelligence technologies like Large Language Models has taken anthropomorphism to new heights. The conversational chatbot interface of AI prioritizes mimicking an inherently human communication medium to maximize human-likeness. However, anthropomorphism has several downsides. Conversational interfaces obscure the limitations and the tangible cost of the technology. They also imply fictional moral status and human-level cognitive capabilities, which means general public sentiment focuses on the ``overhyped'' excitement and fear rather than on other socio-ethical and capacity questions that are far more urgent …

Somatic Prosthetics For Planetary Resonance, Disha Dharesh Kumar R

Masters Theses

This thesis investigates how industrial design can transcend extractive technological paradigms in favor of relational interfaces that foster planetary attunement. Framing the climate crisis as a 'crisis of imagination', the research challenges the Western bifurcation of nature and culture by drawing on Indic cosmologies- which recognize stones, plants, and ecosystems as conscious at different levels and participants in a shared cosmic field. By synthesizing research in Biosemiotics, Quantum Information Pansycishm, and Neuroscience, the project redefines intelligence as a distributed, more-than-human phenomenon.

The research materializes as a speculative design artifact: a device that functions as a somatic prosthetic for planetary resonance. …

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

Environmental Mercury Alters Immune Pathways Linked To Autoimmune Risk In Mice Mirroring Humans, Maurgan Lee, Paul Stemmer, Randall Gill, Allen Rosenspire, Anil Aranha, Heather Gibson

Medical Student Research Symposium

Background and Purpose: Mercury is a pervasive environmental contaminant, and human epidemiologic studies have linked chronic low-level exposure to increased autoimmune disease-risk. Dysregulated lymphocyte activation and impaired signaling tolerance are central mechanisms in human autoimmunity. Protein phosphorylation governs lymphocyte differentiation and function, alterations in phosphoproteomic networks may represent a signature of immune disruption. This study evaluates how low dose mercury exposure modifies B and T cell abundance and intracellular signaling patterns in BALB/c and Diversity Outbred (DO) mice.

Methods: BALB/c and DO mice were exposed to low dose HgCl2 in their water for two weeks or provided standard water controls. …

Detection Method For Laboratory Ppe Compliance Wearing Based On Human Key Points, Lijun Peng, Tingqi Su, Peijin Liu, Lin He, Xiewu Zhou, Minxin Zhang

Journal of System Simulation

To address the problems of high missed detection rate and inaccurate judgment of wearing compliance when multi-scale and multi-category targets of laboratory personnel's safety protective equipment are detected in a complex laboratory environment, this paper proposes a laboratory personnel's standard personal protective equipment (PPE) wearing detection method (multi-scale multi- target joint key point detection method, MSMT-JKDM) that integrates multi-scale features and human keypoints. The multi-scale adaptive down sampling (MSA-Down) module and the cascaded group attention transformer (CGA Former) are introduced to enhance the feature representation ability of PPE (especially small targets such as goggles and gloves) in laboratory detection scenarios, …

Goodness-Of-Fit Test For The Kumaraswamy Distribution Via Energy Distance Approach With Applications To Real Data, Joseph Njuki, Thomas Gilbert

Mathematics and Statistics

In this article, we develop a goodness-of-fit test for the Kumaraswamy distribution based on energy statistics. Due to the availability of its quantile (inverse) function, the Kumaraswamy distribution has been shown to be the preferred alternative to the Beta distribution, since both have bounded support in the (0,1) interval. The proposed test procedure is simple and more powerful against general alternatives. Under different settings, simulations show that the proposed test is capable of being well controlled for any given significance (nominal) levels. In terms of power comparisons, the proposed test outperforms other existing methods in different settings. We then apply …

Second Annual Advances In Business Education Conference 2026 Proceedings, Kelsey Metz

Advances in Business Education (ABE) Conference Proceedings

Conference Overview: The Second Annual Advances in Business Education (ABE) Conference was held on May 21–22, 2026, at Lincoln Memorial University in Harrogate, Tennessee. Hosted by the LMU School of Business, the ABE Conference exists to promote teaching excellence, scholarly inquiry, and regional engagement through innovation and collaboration in business education.

With a focus on fostering meaningful dialogue among educators, researchers, students, and industry professionals, the conference welcomed more than 70 attendees representing 11 institutions from across the Appalachian region and beyond.

The event was structured around four key tracks:

Pedagogy and Teaching Excellence: Showcasing innovative teaching methods, instructional technologies, …

Labor Market Responses To Ai: Measuring Wage Effects Across U.S. Occupations, Kaitlin Pham, Karla Rodriguez

Undergraduate Economics Working Paper Series

Artificial intelligence (AI) is rapidly changing economies around the world, with some experts predicting an impact greater than the Industrial Revolution. As AI becomes more common in daily life and business, questions have grown about how it might affect jobs, wages, and inequality. The rise of automation and highly capable AI models has made people wonder which occupations will benefit and which might be at risk. This study looks at how exposure to AI technologies affects wage trajectories in the United States. Using occupational-level data from O*NET and the U.S. Bureau of Labor Statistics, we build an AI exposure index …

New Developments In Space-Filling Designs, Xiankui Yang

USF Tampa Graduate Theses and Dissertations

This dissertation presents three methodological advancements to improve the construction of space-filling designs for meeting different needs of computer experiments. Traditional space-filling designs focus on achieving uniform coverage in the input space, ensuring that design points are spread evenly throughout. However, in some scientific and engineering applications, varied density of design points may be desired for more efficient data collection when prior knowledge implies different emphases. In other cases, ensuring good coverage and/or spread of the response values allows better performance of fitted models in the next stage of applications. Many processes involve variation in response values. Therefore, incorporating variation …

Beyond Stabilization: Biological Healing, Structural Exclusion, And The Recovery Gap After Border-Fall Trauma At The U.S.-Mexico Border, Julia Robinson

Undergraduate Honors Theses

This honors thesis examines the biochemical, ethical, and public health consequences of insufficient post-operative follow-up care for undocumented immigrants injured in border falls. Discussing pathways of inflammation resolution, wound healing, and bone remodeling, this thesis argues that recovery depends on tightly regulated molecular and cellular processes that are highly vulnerable to disruption without continued monitoring and rehabilitation (Loi et al., 2016; Maruyama et al., 2020). When follow-up care is absent, these processes can be predicted to derail, leading to infection, impaired healing, and permanent disability (Chung & Sohn, 2025; Howard et al., 2020; Kruidenier et al., 2018). Framed through principles …

Characterization Of Mixed Metal Biogenic Manganese Oxide Materials For Catalysis And Rare Earth Element Sequestration, Elisa Morales, Jeremy Brown, Chloe Runge, Madeline York, Genesis Dennis, Cole Johnson, Anthony M. Baudino, Norman Paz-Ramirez, John Rey A. Romal, Kari Stone, Sarah E. Shaner

Chemistry Department Faculty Articles

This study explores the potential of utilizing biogenic manganese oxides (BMOs) produced by Mn-oxidizing Pseudomonas putida MnB1 to facilitate metal cation uptake for rare earth element (REE) sequestration and the synthesis of novel materials. Previous studies have shown that P. putida MnB1 efficiently oxidizes environmental Mn(II) to Mn(IV)-oxides, producing BMOs with unique physicochemical properties. Unlike their abiotic counterparts, BMOs exhibit high surface area, reactivity, and amorphous, poorly crystalline structures, making them promising platforms for adsorbing metal cations. This research study, building on the prior work, demonstrates the incorporation of ten different main group, transition, and rare earth metals into the …

Innovation Strategies For Small And Medium-Sized Construction Companies In Nigeria, Olabode Akinkunmi Akindele

Walden Dissertations and Doctoral Studies

No abstract provided.

Operational Responsibility In Ai Governance: A User-Centric Liability Framework, Zhengyang Chen

Faculty Publications

Who bears responsibility when artificial intelligence systems cause harm? This question has become central to AI ethics and governance. Most existing approaches focus on developers, yet this faces serious practical and theoretical problems. Drawing on tort law, agency law, and philosophy of technology, this paper argues that AI should be understood as an instrument whose outputs remain the responsibility of human operators rather than developers. We call this 'user-centric governance.' Placing accountability with deployers promotes public trust by creating clear lines of responsibility, a concern that governance approaches have often overlooked. It preserves democratic accountability by keeping human actors answerable …

Ecological Interest Theory Of “Lucid Waters And Lush Mountains Are Invaluable Assets” And Its Application In The Yellow River Basin, Guangqian Wang, Deyu Zhong

Bulletin of Chinese Academy of Sciences (Chinese Version)

To address the core challenges of quantifying ecological value and converting it into economic gains, this study proposes a theoretical framework of ecological interest (EI) based on the principle that “lucid waters and lush mountains are invaluable assets”. Three fundamental origins of ecological interest are explained, including the temporal value discount, the spatial ecological compensation, and the civilizational occupation-compensation balance. These three dimensions establish the logical connection between ecological and economic values. Setting a 5% annual simple interest rate as the benchmark and adopting “Lucid Waters and Lush Mountains” green certificates as the standardized ecological assets for property rights delineation …

Seizing Strategic High Ground Of Space Computing Power: Global Competition Landscape And China’S Path, Yan Chen, Wenbin Song, Ping Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The deep integration of artificial intelligence and commercial aerospace is accelerating the transformation of space computing power from conceptual exploration to engineering verification, becoming a key direction for building an integrated space-air-ground information infrastructure. This study delves into its strategic value, global landscape, industrial chain bottlenecks, and advancement paths. The research reveals that the core value of space computing power does not lie in replacing ground data centers, but rather in focusing on network coverage blind spots, data transmission limitations, and high-timeliness scenarios, providing a new supply model of “in-orbit computing + space-ground collaboration”. Currently, the world has entered a …

Dialogue Between Mind And Algorithm: Deep Symbiosis Of Psychology And Artificial Intelligence, Xiaolan Fu, Zheng Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

As artificial intelligence (AI) evolves from a supportive tool into a collaborative partner, the convergence of psychology and AI is gradually shifting from one-way application toward deep symbiosis. This study discusses the mutual empowerment resulting from their interaction, as well as the challenges they face and potential pathways to breakthroughs. On the one hand, psychology empowers AI by enhancing its human-like intelligence and social adaptability through cognitive modeling and ethical constraints; on the other hand, AI empowers psychology by leveraging multimodal data and algorithmic models to revolutionize psychological assessment and intervention methods. This deep symbiosis requires a clear-eyed acknowledgment of …

Learning With Geometric Priors In U-Net Variants For Polyp Segmentation, Fabian Vazquez, Jose A. Nuñez, Diego Adame, Alissen Moreno, Augustin Zhan, Huimin Li, Jinghao Yang, Haoteng Tang, Bin Fu, Pengfei Gu

Computer Science Faculty Publications

Accurate and robust polyp segmentation is essential for early colorectal cancer detection and for computer-aided diagnosis. While convolutional neural network-, Transformer-, and Mamba-based U-Net variants have achieved strong performance, they still struggle to capture geometric and structural cues, especially in low-contrast or cluttered colonoscopy scenes. To address this challenge, we propose a novel Geometric Prior-guided Module (GPM) that injects explicit geometric priors into U-Net-based architectures for polyp segmentation. Specifically, we fine-tune the Visual Geometry Grounded Transformer (VGGT) on a simulated ColonDepth dataset to estimate depth maps of polyp images tailored to the endoscopic domain. These depth maps are then processed …

Exploring Resource-Efficient Deep Learning For Medical Image Segmentation, Pallabi Dutta

Doctoral Theses

Automated medical image segmentation improves diagnostic accuracy by au tomating the precise delineation of target anatomical structures in the input images. Artificial Intelligence (AI), and specifically, Deep Learning (DL), has emerged as a state-of-the-art approach for this task. However, the significant computational demands of DL approaches often hinders their deployment. Ad vanced models, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), require substantial processing power and a large memory footprint, limiting their use in resource-constrained settings. This thesis aims to address this challenge by developing a series of novel, resource-efficient DL models that achieve high segmentation accuracy with reduced …

Storyteller: Training-Free Narrative Grounding And Forseebench: Evaluation For Long Form Audio Description, Seung Hyun Hahm

Dartmouth College Master’s Theses

Understanding long-form video requires tracking events, motivations, and relationships across time rather than describing isolated frames. However, existing video--language models (VLMs) and audio description (AD) systems often generate short-horizon descriptions that omit narrative context, causal intent, and story continuity, limiting accessibility for blind and low-vision (BLV) audiences. This thesis investigates how long-form AD can be grounded in narrative memory without relying on expensive supervised training pipelines or heavily curated annotations.

We propose StoryTeller, a training-free retrieval-augmented framework for long-form audio description. Instead of depending solely on frame-level perception, StoryTeller summarizes observations into structured narrative facts that capture who did what …

Butte Priority Soils Operable Unit Butte Reduction Works Smelter Area Intermediate 60% Remedial Design Submittal, Pioneer Technical Services, Inc., Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

An Integrated Framework For Memory-Centric Analysis: From Trace Collection To Co-Design, Dhruv Gajaria, Prajwal Challa, Yasodha Suriyakumar, Joseph Manzano, Nathan Tallent, Andrés Márquez

Computer Science Faculty Publications and Presentations

IntroductionThe memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems-poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing contention effects, bandwidth saturation, and interference patterns that emerge at larger scales. These limitations reflect a processor-centric design philosophy—in both performance analysis tools and system co-design methodologies—that is increasingly misaligned with …

Multi-Level Variable Selection Using A Bart-Enhanced Mixed-Effects Framework, Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette A. Fausto, Liangyuan Hu

College of Health Professions Faculty Papers

Selecting important individual- and cluster-level predictors has become increasingly critical in healthcare research, where data often exhibit hierarchical structures due to collection from multiple clusters. Mixed-effects models, which account for within-cluster correlation and between-cluster heterogeneity, are a natural approach for multilevel variable selection. However, currently available variable selection methods for multilevel data are predominantly based on mixed-effects models that impose restrictive parametric assumptions, potentially limiting their utility when the underlying relationships are nonlinear or involve interactions. While nonparametric methods have shown promise for variable selection in non-clustered data, they have been much less studied in the multilevel setting. Moreover, nonparametric …

Robert, Powers; Unl Chemistry; Nmr-Assisted Drug Discovery, Mark Griep, Robert Powers

Department of Chemistry: Faculty Interviews

Dr. Robert Powers became a chemistry professor at the University of Nebraska-Lincoln in 2003 and is about to retire after 23 years. Prior to UNL, Bob was a drug discovery researcher for 11 years at American Cyanamid, which eventually became Wyeth and is now part of Pfizer. Bob was born in Jersey City, New Jersey. Something in his youth must have sparked an interest in chemistry because he earned a bachelor's in that subject from Rutgers University in New Brunswick. Then he traveled 1200 miles west to Purdue University in Indiana where he earned his doctorate. Next, he did postdoctoral …

Real-Time Instruction Internalization For Large Language Models, Brenden Smith

Theses and Dissertations

For the end user, Large Language Models (LLMs) are programs that process natural language inputs into natural language outputs. In popular usage, this tends to take the form of conversation: a user asks a question, provides information, or gives instructions, and the LLM (hopefully) replies in a manner we would expect of an informed and compliant person. While convenient and intuitive for users, this natural conversational format encourages the misconception that LLMs are learning from conversations, when they do not. This work presents the benefits and practicality of a language model paradigm that meets this user expectation -- that is, …

Spectral Classification Of Diverse Lithologies Using Multi- And Hyperspectral Satellite Data: A Comparative Study, Önder Gürsoy, Emre Özelkan, Rutkay Atun, Ayşe Betül Çalişkan, Ahmet Efe

Turkish Journal of Earth Sciences

Accurate lithological mapping requires selecting the appropriate remote sensing data and classification methods. This study evaluates the performance of four satellite datasets—Landsat 8 OLI, Sentinel-2A, ASTER, and Hyperion EO-1—using three spectral classification techniques: Matched Filtering (MF), Spectral Angle Mapper (SAM), and Spectral Information Divergence (SID). The study area is located between the Zara and Koyulhisar districts in eastern Türkiye and comprises diverse lithological units. A total of 49 rock samples collected in the field were used for validation. The results indicate that MF consistently outperformed the other methods, achieving the highest accuracy with Landsat 8 (Kappa = 94.2%). ASTER data …

Hyperspectral Image Classification Using Novel 1-D And 2-D Deep Neural Networks, Özlem Polat, Zümray Dokur, Tamer Ölmez

Turkish Journal of Earth Sciences

Hyperspectral image (HSI) classification is of critical importance in many fields including agriculture, geology, environmental monitoring, and urban planning. In recent years, many researchers have utilized deep neural networks (DNNs), known for their high performance in the classification of HSIs. When 2-D/3-D convolutional neural networks are used in HSI classification, filters are applied using input patches typically larger than 11 × 11. This allows spectral and spatial features to be evaluated together. However, this combination creates several problems. Because HSIs have low spatial resolution, they often do not contain strong texture details. Furthermore, features with little relevance to classification make …

Formation Mechanism Of High-Quality Reservoirs In The Shanxi Formation Of The Qingyang Gas Field In A Meandering River Delta Setting, Xingming Duan, Shu Liu, Meng Wang, Yecan Fan, Xiyu Wang, Xinan Yu, Zubing Li

Turkish Journal of Earth Sciences

As global energy demand rises, unconventional gas resources, particularly tight gas reservoirs, have become increasingly important for future energy supply. Located in the southwestern Ordos Basin, the Qingyang gas field is a newly discovered deep tightgas field with proven geological reserves exceeding 31.8 × 109 m3 and has become a strategic focus for deep-gas exploration in China. Despite rapid appraisal that delineated several stable gas-bearing zones, a comprehensive understanding of the sedimentary architecture, diagenetic transformation, and enrichment mechanisms of high-quality reservoirs in the Permian Shanxi Formation remains incomplete. Focusing on the Shan 1 Member (hereafter referred to as Shan 1), …