Digital Commons Network^™

Debt, Work, And The State, Kate Sablosky Elengold

Faculty Publications

In every state and the District of Columbia, an individual who owes a debt to the state can lose their license to work. Without the ability to make a living, it is much harder to pay off debt. Although using occupational license restrictions as a debt collection tool appears nonsensical, it has never before been the subject of scholarly debate. This Article thus begins an important conversation about debt, work, and the state.

This Article identifies the pervasive authority that state and local governments have to revoke an individual’s occupational license solely because that person owes a debt to the …

Alienation On Campus: Students, Agency, And A 'Praxis Of Possibility', Julia R. Allison

Dissertations

In the 1950s, 60s, and 70s, the idea of alienation took hold across the United States as a way of explaining feelings of disconnection, powerlessness, and meaninglessness that seemed to be pervading American society. This was no less true on college and university campuses, where students engaged in protest over both government action and inaction and a new youth counterculture took root. What led to alienation’s prominence as a social phenomenon is a matter of some debate, as are the causes of its precipitous decline in the early 70s. However, after an extended silence more recent decades have seen something …

2025 Engage For Change Awards Program, Bonner Center For Civic Engagement

Engage for Change Awards

2025 Award Print: Alfonso Pérez Acosta

Keynote Address: Taylor Scott, Founder, RVA Community Fridges

Leveraging Artificial Intelligent For Optimized Crop Production: An Ann-Based Approach, Yahya Layth Khaleel, Fadya A. Habeeb, Mustafa Abdulfattah Habeeb, Fatimah N. Ameen

Mesopotamian Journal of Computer Science

To incite modern day crop production and ensure sustainability, exact crop recommendations are key to the process. This study pays significant attention to the need for the use of big data tools in studies involving comprehensive data sets that contain information on soil and other environmental characteristics. The set of data used in this research includes Nitrogen, Phosphorus, and Potassium content coordinated with Temperature, Humidity, pH Value, and Rainfall. Knowing these factors is to make a favorable decision about improving agricultural products yield, availability and management of the resources, as well as general well-being of the crops. Specialized advisory on …

Securing The Internet Of Wetland Things (Iowt) Using Machine And Deep Learning Methods: A Survey, Guma Ali, Wamusi Robert, Maad M. Mijwil, Malik Sallam, Jenan Ayad

Mesopotamian Journal of Computer Science

Wetlands are essential ecosystems that provide ecological, hydrological, and economic benefits. However, human activities and climate change are degrading their health and jeopardizing their long-term sustainability. To address these challenges, the Internet of Wetland Things (IoWT) has emerged as an innovative framework integrating advanced sensing, data collection, and communication technologies to monitor and manage wetland ecosystems. Despite its potential, the IoWT faces substantial security and privacy risks, compromising its effectiveness and hindering adoption. This survey explores integrating machine learning (ML) and deep learning (DL) techniques as solutions to address the security threats, vulnerabilities, and challenges inherent in IoWT ecosystems. The …

Enhancing Cybersecurity In Smart Education With Deep Learning And Computer Vision: A Survey, Guma Ali, Aziku Samuel, Maad M. Mijwil, Kholoud Al-Mahzoum, Malik Sallam, Ioannis Adamopoulos, Ayodeji Olalekan Salau, Indu Bala, Klodian Dhoska, Engin Melekoglu

Mesopotamian Journal of Computer Science

The rapid digital transformation of education, driven by the widespread adoption of smart devices and online platforms, has ushered in the era of smart education. While this shift enhances learning experiences, it also introduces significant cybersecurity risks that threaten the confidentiality, integrity, and availability of educational resources, student data, and institutional systems. This survey examines how deep learning (DL) and computer vision (CV) techniques can enhance cybersecurity in smart education environments. By reviewing 202 peer-reviewed research papers published between January 2022 and June 2025 across leading publishers such as ACM Digital Library, Frontiers, Wiley Online Library, IGI Global, Nature, Springer, …

Haze-Image-Dataset: A Large-Scale Benchmark For Image Dehazing In Variable Fog And Low-Light Conditions, Mustafa J. Shahbaz, Ali A.D. Al-Zuky

Mesopotamian Journal of Computer Science

To enhance image dehazing and visual recognition in real-world conditions, we introduce HAZE-IMAGE-DATASET, a large-scale dataset comprising nearly 42,000 images. It is constructed from 1,532 clean images sourced globally and captured using a Samsung smartphone, covering diverse natural and urban scenes. The dataset includes synthetic and real haze variations. Synthetic haze was generated using MATLAB-based atmospheric scattering models with depth maps for 10 fog levels. Colored haze was created using alpha blending (α = 0.4) in six colors: red, green, blue, yellow, white, and black. Low-light conditions were simulated via uniform darkening at 10 levels. Also, 616 real haze images …

Towards Achieving The Un Sustainable Development Goals: The Role Of Ai In Municipality Services, Thabit Sultan Mohammed, Karim Mohammed Aljebory, Ahmed Thabit Sultan

Mesopotamian Journal of Computer Science

In 2015, the United Nations adopted the Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure global peace and prosperity by 2030. However, progress has been hindered by challenges like the COVID-19 pandemic, climate change, funding shortages, political instability, and data limitations. Municipal services, crucial to achieving the SDGs, provide essential functions like waste management, healthcare, and public safety. Artificial Intelligence (AI) offers innovative solutions to enhance these services, improving urban sustainability and fostering public-private collaboration. This research examines AI's role in municipal services, analyzing its applications, benefits, challenges, and future potential through case studies and expert …

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 …

Characterization Of The Biofilm-Forming Ability And Certain Virulence Characters Ofaeromonas Spp. Isolates From Rainbow Trout, Türker Çelebi̇, Ertan Emek Onuk, Esra Demi̇rbaş, Gökçen Di̇nç

Turkish Journal of Veterinary & Animal Sciences

Aeromonas spp., commonly found in the aquatic environment, cause infections in both fish and humans. Their pathogenicitydepends on various virulence factors and ability to form biofilm. The current study aimed to determine the biofilm-forming capabilitiesand certain virulence characteristics of 25 Aeromonas spp. isolates obtained from rainbow trout in Türkiye. The biofilm-forming abilitiesof isolates were investigated comparatively using Congo red agar (CRA), the tube method (TM), and tissue culture plates (TCPs).Potential virulence factors, including hemolytic activity, gelatinase production, serine protease activity, DNase activity, and motility,were evaluated using phenotypic tests. Additionally, the distribution of four known virulence genes, namely aerA, exu, fla, …

A Guide To Urban Planning And Environmentalism, Michael Lewyn

Scholarly Works

Review of The Sustainable Urban Design Handbook, by Nico Larco, Kaarin Knudson.

Repressed Memories And The Body Keeps The Score: Public Perceptions And Prevalence, Kris-Ann S. Anderson, Quincy C. Miller, Deryn Strange, Kamala London

Publications and Research

The “memory wars” resurgence has renewed debates over the validity of repressed memories. This revival appears linked to factors such as changing statutes of limitations, confusion about repression, and unchallenged social media content. In a nationally representative online survey of American adults (N = 1581), we examined (a) beliefs in repression and the body keeps the score, (b) the prevalence of recovered memory claims, and (c) the impact of question phrasing on recovered memory reporting. An overwhelming 94% of respondents expressed belief in repressed memory, and 77% endorsed the idea that the body keeps the score. Additionally, 3.6% (n = …

Does Performance Change Budgets? Punctuated Equilibrium, Performance, And The Budget For Juvenile Justice In An American State, Elaine Yi Lu, Robert Hines, Katherine Willoughby

Publications and Research

How performance informs budgeting and budgets is contentious and unclear. Applying punctuated equilibrium theory, this research seeks to understand if performance information once placed on the media and macropolitical agendas can lead to long term budgetary shifts. This research highlights how the accumulation of performance information punctuated the funding scheme and created a new equilibrium over time.

This research uses mixed methods to study the impact of performance on Florida’s (USA) Department of Juvenile Justice (DJJ) over a 20-year period. First, we conduct a media review of 400 randomly sampled newspaper articles to characterize the media discourse around the DJJ …

Assessing The Predictive Validity Of The Network Inventory Of Risk, Victories, And Needs Assessment (Nirvana) For Youth Receiving Prevention Services., Michael T. Baglivio, Kevin T. Wolff, Katherine Jackowski

Publications and Research

The current study assesses the predictive validity of a newly-developed holistic risk/needs assessment for youth receiving prevention services. Employing a multiyear statewide sample of over 17,000 prevention youth, multivariate and Area Under Curve techniques are used to examine predictive validity in predicting future formal juvenile justice system involvement (new law violations) across sex, race/ethnicity, and multiple youth age ranges. Furthermore, predictive validity across the severity of the subsequent offense type (misdemeanor, non-violent felony, violent felony) was examined. Findings demonstrate large effect sizes for static risk only, dynamic risk only, and total risk plus protective scores on future offending. Sex and …

A Battle Of The Chatbots: An Exploratory Comparison Of Chatgpt, Gemini, Copilot, Claude, Perplexity And Huggingchat, Karen Okamoto

Publications and Research

This exploratory study compares the output of the free versions of six generative artificial intelligence (AI) chatbots—ChatGPT, Gemini, Copilot, Claude, Perplexity and HuggingChat. Five questions were submitted to all of the chatbots and examined according to the length of the response, tone of the response, and any additional features provided by the chatbots such as citations, web links, and helpful follow-up questions. This comparison found that Perplexity excelled at responding to all of the questions though others provided strong outputs as well, pointing to the possible importance of using multiple chatbot for answers and for continually examining different chatbots given …

The Towering Inferno: Art, Policy, And Legacy, Charles R. Jennings

Publications and Research

The Christian Regenhard Center for Emergency Response Studies, leveraging the expertise of its faculty, staff, Advisory Board and colleagues, has consistently programmed activities focused on high-rise fire safety. The upcoming 50^th anniversary of the film The Towering Inferno was an inspiration.

We decided this would be more lighthearted and less purely technical than many of our events. We wanted to consider both the film, and use it to reflect on the state of fire safety in tall buildings in New York City.

Of course it does not escape us that the topic of fire safety is a serious one, …

Understanding Violence In Juvenile Correctional Facilities: A National Study Of Victim-Offender Overlap In The United States, Tzu-Ying Lo, Yu-Hsuan Liu, Amy Adamczyk

Publications and Research

The phenomenon of victim-offender overlap within juvenile correctional facilities is an underexplored area in criminological research. This study examines the prevalence and correlates of victim-offender overlap using data from two collections of the National Survey of Youth in Custody conducted in 2008–2009 and 2012. Our findings reveal that the victim-offender overlap group constitutes a significant proportion of incarcerated youth. Multinomial logistic regression analysis indicates that institutional factors, such as correctional officer legitimacy, in-facility gang membership, fear of inmate assault, experience of filing complaints against staff, and time served, significantly differentiate victim-offenders from the three other groups: victims-only, offenders-only, and those …

Research News, Grants, 2025, Volume 4, Soumyajit Majumdar

Grants (2015-)

Grants and contracts awarded during October - December 2025.

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

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 …

Knowing God: Life Story And Selected Sermons, J. B. Mcbride

Heritage Material

No abstract provided.

Not Forgotten: Mission To Women Amid Global Crisis, Sue Russell, Rochelle Scheuermann, Amanda L. Allen

Heritage Material

No abstract provided.

An Earnest Appeal, James M. Taylor

Heritage Material

No abstract provided.

Defeats Of The Devil: As Seen In The Life Of James M. Taylor, James M. Taylor

Heritage Material

No abstract provided.

Why Teach Holiness?, James M. Taylor

Heritage Material

No abstract provided.

Pictures On The Wall, James M. Taylor

Heritage Material

No abstract provided.

The Judgment, James M. Taylor

Heritage Material

No abstract provided.