Digital Commons Network^™

Synthesizing Deception: Countering Large Language Model-Generated Phishing Campaigns Through Adaptive Semantic Anomaly Detection, Bekim Fetaji, Debabrata Samanta

Mesopotamian Journal of Computer Science

The paper fills in a gap in the literature that demonstrates an insufficient number of sturdy detection schemes that can recognize the small semantic aberrations inherent in LLM-generated deceptive text. Our proposed co-design hybrid model is Semantic Anomaly Detection with Isolation Forest (SADI) model that combines the synergistic mixture of a fine-tuned transformer-based LLM for deep semantic feature extraction with Isolation Forest algorithm that detects anomalies efficiently. This study introduces SADI, an adaptive semantic-anomaly detector for large-language-model phishing emails. Using a corpus of 10 000 messages, SADI attains an F1 score of 0.981 (95 % CI 0.978–0.984) and processes a …

Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention Via A Mobile App, Ayad Hameed Mousa, Ibrahim Oday Alrubaye, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Mudatheer M. Al-Slivani, Rusul Mansoor Al-Amri, Liaw Geok Pheng

Mesopotamian Journal of Computer Science

Diabetes is a widespread disease worldwide that does not differentiate between children and adults. It also affects the elderly and pregnant women. However, early detection of the disease facilitates its control to avoid the effects resulting from delayed diagnosis. With the emergence of artificial intelligence represented by machine learning techniques and its use in most sectors, accordingly, the adoption of machine learning techniques to help in disease prediction has become a necessity. This study proposes a machine learning algorithm-based approach for diabetes prediction. This study uses three datasets, two of which are private and the other includes the Pima Indians …

Bioaccumulation Of Legacy And Novel Pfas In The Environment, Hesham Taher, Rainer Lohmann

Graduate School of Oceanography Faculty Publications

The bioaccumulation of per- and polyfluoroalkyl substances (PFAS), both legacy and novel, in the environment presents significant ecological and health risks. PFAS are a diverse group of synthetic chemicals known for their persistence and bioaccumulation, which can cause widespread environmental contamination and health risks. Strong carbon-fluorine bonds give these compounds unparalleled stability, preventing them from degrading and enabling them to endure in a range of environmental matrices, including water, soil, and biota. Legacy PFAS, including perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS), have been extensively studied and regulated, resulting in lower concentrations in some environmental media. However, novel PFAS, …

Corporate ‘Capture Strategies’ Impacting Human And Ecosystem Health, Alex T. Ford, Marlene Ågerstrand, Michael G. Bertram, Miriam L. Diamond, Rainer Lohmann, Andreas Schäffer, Martin Scheringer, Gabriel Sigmund, Anna Soehl, Maria Clara V.M. Starling, Noriyuki Suzuki, Marta Venier, Penny Vlahos

Graduate School of Oceanography Faculty Publications

The concept of regulatory capture has been extensively studied in academic literature, primarily within the social sciences. This phenomenon has been increasingly discussed in the environmental sciences as the impacts of regulatory capture on human and ecosystem health have become increasingly apparent. Regulatory capture is just one tactic employed by vested interests in the strategy of delaying, weakening, or abolishing policies designed to protect the public interest. Here, we define capture strategies as ‘the act of influencing individuals, organizations, or governments to prioritize corporate interests over those of human and ecosystem health’. Similar to the evolution of terms like whitewashing …

Data Privacy Regulations In The Gaming Industry: A Comparative Analysis Of Singapore, Macau, And Japan, Miloslava Plachkinova

Faculty Articles

This study explores the relatively under-researched area of comparing data privacy regulations and best practices across different countries, with a focus on the gaming industry. It provides an overview of general data privacy principles and existing global regulations, analyzing how gaming operators leverage personal data for competitive advantage. Specifically, the research examines the data privacy approaches and regulatory requirements in Singapore, Macau, and Japan, highlighting the cultural and historical contexts influencing these regulations. Through a comparative analysis, the article discusses the compliance needs for gaming operators in these jurisdictions.

Is It Getting Better? An Evaluation Of Two Successive Generations Of Chatgpt In Answering Specialized Vascular Surgery Questions, Dongjin Suh, Quang Le, Leana Dogbe, Kedar Lavingia, Michael Amendola

Department Surgery Faculty Publications

Purpose: Large language models (LLMs) can generate clinically relevant text; however, their performance in highly specialized medical domains remains uncertain. This study evaluated ChatGPT-3.5 and ChatGPT-4 (OpenAI) using vascular surgery board–style questions from the Vascular Education and Self-Assessment Program, version 4 (VESAP4) and compared the two public model versions (June and November 2023).

Materials and Methods: All non-image VESAP4 questions (n=384) were presented independently three times to each model version (ChatGPT-3.5 June/November; ChatGPT-4, June/November). Outcomes included accuracy (proportion correct), consistency (same option letter across all three attempts and “consistently correct”), explanation length (word count), and modes of failure classified for …

Separation And Surface Examination Of Spacecraft Cabin Particulates, Grace A. Belancik

Master's Theses

Particulate matter in the atmosphere is a known detriment to human health, but several factors affect any particulate’s particular toxicity including particle size, surface area, and chemical composition. Extensive studies have been conducted to examine particulate hazards on Earth, but in crewed spacecraft, like the International Space Station (ISS), the particulate environment is wholly unique due to both the controlled environment and lack of gravity. Atmospheric sampling studies are underway, but another convenient source of airborne particulates for analysis is the contents of the vacuum bags used by the astronauts to clean the air vents. However, no method currently exists …

Knowledge And Ontology Enhanced Approach To Natural Language Understanding (Koe-Nlu) In Computational Social Media And Healthcare, Naga Usha Gayathri Lokala

Theses and Dissertations

Natural Language Understanding (NLU) faces both opportunities and challenges as the amount of social media and healthcare data grows. This is particularly evident in context-sensitive applications such as evaluating cognitive health, identifying mental health symptoms, and monitoring drug abuse. Even though traditional NLU models work well for processing language in a wide range of areas, they often lack the ability to understand language in a specific domain, reason in context, and incorporate structured external knowledge. This dissertation talks about the Knowledge and Ontology Enhanced Approach to Natural Language Understanding (KOE-NLU), a new framework that is meant to make NLU systems …

Advances In Ocean Mapping And Nautical Cartography, Giuseppe Masetti, Ian Church, Anand Hiroji, Ove Andersen

Center for Coastal and Ocean Mapping

The Special Issue of Geomatics on "Advances in Ocean Mapping and Nautical Cartography" addresses emerging methodologies, technologies, and applications in ocean mapping. This collection includes studies on the development of high-resolution seabed mapping techniques, innovative data processing for marine cartography, and advancements in hydrographic surveying. It highlights the importance of integrating geospatial data from sources such as remote sensing, autonomous underwater vehicles, and satellite-based observations. Additionally, articles discuss challenges and strategies for ensuring data accuracy and accessibility, reflecting a growing interest in sustainable marine resource management and navigation safety enhancements.

Unh/Noaa Joint Hydrographic Center 2025 Performance And Progress Report Executive Summary, Larry A. Mayer

Center for Coastal and Ocean Mapping

No abstract provided.

Calcium Carbonate Microparticles As Acid Responsive Targeted Drug Delivery Carriers For Oral Diseases And Its Anti-Bacterial Activity, Hem Raj Joshi

Dissertations and Theses

Dental diseases are mostly caused by bacterial infections in the teeth, forming biofilms that release acids and decay the enamel of the teeth. More than half of the world's population were affected by oral diseases, including periodontitis (gum disease), dental caries (cavities), and oral cancer. Chlorhexidine (CHX) is the mostly used antimicrobial drug for dental diseases, but its overexposure to the healthy teeth causes many side effects, such as tooth staining, taste alteration, and many more. Taking advantage of the acidic environment of infected teeth, we designed a pH responsive targeted drug delivery system using calcium carbonate microparticles (CCMPs) as …

Convergence In Cancer: Integrative Multi-Modal Modeling For Pan-Cancer Drug Response Prediction, Jessica Zylla

Dissertations and Theses

Heterogeneity and rarity can make cancer difficult to study and treat. Cancer's heterogeneity, evident in tumor locations, tumor cell types, subtypes, and microbiota within the tumor microenvironment, complicates diagnosis, prognosis, and treatment. Research into the tumor microenvironment and its microbiota is an evolving area of oncology that may advance cancer drug-patient response. Cancer-omics signatures are crucial to drug response, yet there is no tool that physicians use as a gold standard. Research indicates that microbial presence can alter drug metabolism and immune response, affecting cancer-drug efficacy on a patient-specific basis. This work highlights the need for training readiness in transdisciplinary …

A Comprehensive Exploration Of 6g Wireless Communication Technologies, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md. Shahriar Uzzal, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts toward superconvergence, non-IP-based networking protocols, and information-centric networks, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into …

Differentiating Opioid Use Disorder From Healthy Controls Via Ml Analysis Of Rs-Fmri Networks, Ahmed Temtam, Megan A. Witherow, Liangsuo Ma, M. Shibly Sadique, F. Gerard Moeller, C. Kenneth, Dianne Wright, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping …

Ml Model To Better Identify Instances Of Bullying Faced By Members Of The Lgbtq+ Community, Arslan Bisharat

Master's Theses

Cyberbullying poses a significant threat to online communities, with the LGBTQ+ community facing disproportionately higher rates of harassment. While existing cyberbullying detection systems have made progress in identifying general instances of online harassment, they often fail to capture the nuanced and context-dependent nature of LGBTQ+-targeted bullying. This thesis presents a novel approach to this challenge by developing SpectrumNet, an LGBTQ+-centric transformer-based model for cyberbullying detection. Our research was conducted in two phases. In Phase 1, we evaluated the effectiveness of pre-trained transformer models (RoBERTa, BERT, and GPT-2) in identifying LGBTQ+-related cyberbullying. Building on these findings, Phase 2 introduced SpectrumNet which …

Machine Learning Predicting Acute Pain And Opioid Dose In Radiation Treated Oropharyngeal Cancer Patients, Vivian Salama, Laia Humbert-Vidan, Brandon Godinich, Kareem A Wahid, Dina M Elhabashy, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Ariana J Sahli, Katherine A Hutcheson, Gary Brandon Gunn, David I Rosenthal, Clifton D Fuller, Amy C Moreno

Faculty, Staff and Student Publications

Introduction: Acute pain is common among oral cavity/oropharyngeal cancer (OCC/OPC) patients undergoing radiation therapy (RT). This study aimed to predict acute pain severity and opioid doses during RT using machine learning (ML), facilitating risk-stratification models for clinical trials.

Methods: A retrospective study examined 900 OCC/OPC patients treated with RT during 2017-2023. Pain intensity was assessed using NRS (0-none, 10-worst) and total opioid doses were calculated using morphine equivalent daily dose (MEDD) conversion factors. Analgesics efficacy was assessed using combined pain intensity and total MEDD. ML predictive models were developed and validated, including Logistic Regression (LR), Support Vector Machine (SVM), Random …

Computational Bridges: Enhancing Natural Language Processing Of Swahili., Joyce Murungi

Harrisburg University Other Works

Swahili remains significantly underrepresented in natural language processing (NLP) despite being one of the most widely spoken languages in Africa. Computational Bridges: Enhancing Natural Language Processing of Swahili addresses this gap through computational linguistics, corpus creation, and large-scale analysis of Swahili syntax and lexical structure. Central to this study is GUMZO, a novel corpus developed from spontaneous conversational data collected from YouTube videos, television panel discussions, political speeches, religious discourse, and unscripted broadcasts. Unlike many existing datasets that rely on formal or translated text, GUMZO captures authentic language use and provides a stronger foundation for NLP research involving low-resource languages. …

Shining Light On Policy: The Case For Solar Panel Mandates On New Construction Projects, Emily Glazier

Cardozo Journal of Equal Rights & Social Justice

The note argues that solar panel mandates on new construction projects are a necessary and sensible approach to reducing greenhouse gas emissions and achieving climate goals, but their implementation must include provisions to protect vulnerable communities and address environmental justice concerns. While such mandates face legal and political challenges, the benefits of decreased emissions and energy independence outweigh the costs, particularly when paired with measures like community solar systems, incentives, and exemptions.

New Jersey's Mitigation And Adaptation To Climate Change: An Economic Analysis Of The State's Societal Benefits Charge And Community Solar Energy Program, Nicole S. Provost

Theses, Dissertations and Culminating Projects

Understanding the current trajectory of New Jersey’s emissions and the existing legislation and programs implemented to help reduce emissions, it is evident that the State requires further actions to spur heightened emission reductions to reach its goals. One known impactful policy that could significantly accelerate this process is a carbon tax, which applies to emission-intensive goods. Although this policy does not currently exist in New Jersey, the State has a Societal Benefits Charge (SBC) that applies an approximate 3% charge to electricity and gas consumption on residential and commercial utility customers’ monthly energy bills, where revenues fund programs that offer …

Earth Observations Reveal Impacts Of Climate Variability On Maize Cropping Systems In Sub-Saharan Africa, Adomas Liepa, Michael Thiel, Hannes Taubenböck, Doris Klein, Ingolf Steffan-Dewenter, Marcell K. Peters, Sarah Schönbrodt-Stitt, Insa Otte, Tobias Landmann, Zeyaur R. Khan, Michael Ochieng Obondo, Frank Chidawanyika, Emily A. Martin, Tobias Ullmann

All Peer-Reviewed Publications

In Kenya, climate variability and change threaten smallholder, rainfed farms, with crop failures, yield reductions, and pest infestations. Efficient agroecological strategies, such as Push-Pull intercropping, offer documented benefits including pest control, improved soil fertility, and water conservation compared to traditional maize monocropping. To date, no studies exist comparing traditional maize monocropping and Push-Pull intercropping using earth observation tools over several growing seasons in East Africa. Our research addresses this by harmonizing Landsat 7, 8, 9 with Sentinel-2 remote sensing time series from 2016 to 2023. Phenological metrics of 15 growing seasons are extracted based on a threshold method using the …

Is Youth's Engagement In Agribusiness An Opportunity Or A Necessity? A Closer Look At The Situation In South Kivu, Eastern Democratic Republic Of The Congo, Cool Dady Mangole, Paul Martin Dontsop Nguezet, Shiferaw Feleke, Victor Manyong, Kamala Kaghoma Christian, Zoumana Bamba, Tahirou Abdoulaye

All Peer-Reviewed Publications

Despite the broad focus on necessity- and opportunity-driven entrepreneurship in research and policy, the entrepreneurial dichotomy within the agribusiness context has not been adequately addressed. This study contributes to closing this knowledge gap by examining youth's perceptions of agribusiness through the lens of the push-pull motivation framework. Results reveal that 47% of youth are driven into agribusiness by both necessity and opportunity, while 41% by necessity alone and only 12% by opportunity alone. Key factors shaping youth's perceptions include gender, education, food processing participation, agribusiness-related training, land ownership, monthly income, and family farming background. The result further identifies significant heterogeneity …

Spatial Analytics To Elucidate The Incubation Period And Drivers Of Visceral Leishmaniasis: Case Of Turkana County In Kenya, Kennedy Senagi, Maureen Nzilani, Evans Omondi, David P. Tchouassi, Tobias Landmann, Damaris Matoke-Muhia, Emmanuel Okunga, Barrington Gesimba, Elfatih M. Abdel-Rahman, Dawn Maranga, Joseph M. Ndungu, Daniel Masiga

All Peer-Reviewed Publications

Introduction: Visceral leishmaniasis (VL) is a severe and neglected tropical disease of public health concern. VL is fatal if not treated. Kenya has experienced multiple outbreaks of the disease since 2017. The underlying drivers of the disease risk dynamics, as well as the incubation period, are not well understood. Methods: We implemented statistical (spatial logistic regression and Bayesian spatial) and machine learning (random forest, support vector machine, AdaBoost, logistic regression, and extra trees) models to estimate the incubation period and predict areas of low/high risk in Turkana County, an endemic VL foci in Kenya. Two-year (2019–2020) patient data were sourced …

Kelp Guardians Can Save The World: A Food Sovereignty Lab Report Of The Ghvtlh-K’Vsh Shu'-Srnelh-'I~ (Kelp Guardians) California Sea Grant, Delaney A. Schroeder-Echavarria

Cal Poly Humboldt theses and projects

As partners of the Ghvtlh-k’vsh Shu'-srnelh-'i~ (Kelp Guardians) California Sea Grant project, the Rou Dalagurr Food Sovereignty Lab and Traditional Ecological Knowledges Institute has actively engaged with local educators, Tribal organizations, and Tribal Nations to create youth-centered curricula, researched through a community-based participatory research lens. This is demonstrated through an innovative approach to recruiting and retaining Indigenous youth and community interest in coastal and marine ecosystems and resources by connecting with Indigenous cultural practices, Indigenous sciences, and community-based programs to encourage future careers. The Kelp Guardians project is led by the Tolowa Dee-ni’ Nation (TDN or Nation) and includes various …

Assessment Of The Genetic Population Structure And Extent Of Clonality In A Rare Serpentine Endemic, Lathyrus Biflorus T.W. Nelson & J.P. Nelson (Fabaceae), Using Ddrad Sequencing, Ashley Dickinson

Cal Poly Humboldt theses and projects

Lathyrus biflorus, or the two-flowered pea, is a rare herbaceous perennial restricted to a single population in Northern California. The species is considered critically imperiled but remains unprotected under state or federal endangered species acts. Despite its rarity, little is known about its life history, reproductive biology, or genetic diversity. Using genome-wide reduced representation sequencing, this study aimed to address these gaps by investigating the molecular evidence of clonality, the number and diversity of genets (unique genetic individuals which can be made up of one or many clonal units or ramets), and overall genetic health of the population. My …

Home Range, Habitat Use, And Fall Migration Of Lewis’S Woodpeckers In The Eastern Cascade Range, Oregon, Cameron Piper

Cal Poly Humboldt theses and projects

Lewis’s woodpecker (Melanerpes lewis), a burn specialist, is experiencing range-wide population declines despite increasing fire activity in the western U.S. The White River Wildlife Area in Oregon hosts the state's only year-round population, raising questions about their breeding, habitat use, and migration. In summer 2024, we tracked nine woodpeckers using telemetry to estimate home range size and overlap. Full home ranges averaged 428 ha, with 66 ha core areas, and showed evidence of growing after nesting. Home ranges overlapped extensively (Full: 91 ± 13%; Core: 63 ± 29%), though individuals had distinct areas of intense use. Males had …

Semi-Supervised Multimodal Multi-Instance Learning For Aortic Stenosis Diagnosis, Zhe Huang, Xiaowei Yu, Benjamin S. Wessler, Michael C. Hughes

Computer Science Faculty Research & Creative Works

Automated interpretation of ultrasound imaging of the heart (echocardiograms) could improve the detection and treatment of aortic stenosis (AS), a deadly heart disease. However, existing deep learning pipelines for assessing AS from echocardiograms have two key limitations. First, most methods rely on limited 2D cineloops, thereby ignoring widely available Spectral Doppler imaging that contains important complementary information about pressure gradients and blood flow abnormalities associated with AS. Second, obtaining labeled data is difficult. There are often far more unlabeled echocardiogram recordings available, but these remain underutilized by existing methods. To overcome these limitations, we introduce Semi-supervised Multimodal Multiple-Instance Learning (SMMIL), …

Environmental Monitoring Report: For Work Performed: July 1, 2022 Through June 30, 2023, Tennessee. Department Of Environment And Conservation

Environmental Monitoring Reports

This FY2023 EMR presents results for 20 independent projects, originally defined in TDEC’s FY2023 Environmental Monitoring Plan (EMP) and subsequently completed over the course of FY2023 period of performance.

In The Footsteps Of Moose: Using Non-Invasive Techniques To Identify Cause-Specific Calf Mortalities And Evaluate Moose (Alces Alces) Movements Pertaining To Mineral Lick Locations On Ancestral Lands Of The Grand Portage Ojibwe, Anna B. Weesies

Electronic Theses and Dissertations

Following a sharp moose (Alces alces; mooz, Anishinaabemowin, Ojibwe language) population decline in northeastern Minnesota during the early 2000s, the Grand Portage Band of Lake Superior Chippewa initiated a long-term moose collaring effort to assess survival and mortality causes. Moose are a culturally important species to the Band, with annual subsistence hunts held on the Reservation and adjacent 1854 Ceded Territory. Continued research guides culturally appropriate management decisions aimed at bolstering calf and adult survival, helping to preserve this moose in Minnesota today and for subsequent generations. Chapter 1 identifies cause-specific calf mortality rates in this multi-predator system using minimally …

Characterizing A Free-Roaming Cat Population To Predict Predation Of Threatened Species In An Island Ecosystem, Sarah Gheida

Electronic Theses and Dissertations

No abstract provided.

An Integrated Wetland Condition Index And Environmental Metric Framework For The Prairie Pothole Region, Mercedes L. Batalla

Electronic Theses and Dissertations

The USDA-NRCS Agricultural Conservation Easement Program (ACEP) assists landowners with protecting, restoring, and enhancing wetlands. Evaluating wetland conservation efforts is crucial for informing future management decisions. However, assessment frameworks vary across regions and among stakeholders. The Prairie Pothole Region is an ecologically unique landscape characterized by its abundance of wetlands that provide important ecosystem services. To evaluate wetlands enrolled in ACEP, I sampled forty-five semi-permanent wetlands in the Prairie Pothole Region from July – August 2023 and 2024. I selected and sampled twenty-six wetlands enrolled in ACEP. Nineteen additional wetlands not enrolled in ACEP were also sampled; these included nine …