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Autonomous Generation Of Ids Rules From Threat Intelligence, Azim Bazarov Aug 2025

Autonomous Generation Of Ids Rules From Threat Intelligence, Azim Bazarov

Theses and Dissertations

Signature-based Intrusion Detection Systems (IDS) detect malicious activities by matching network or host activity against predefined rules. These rules are derived from Cyber Threat Intelligence (CTI), which includes attack signatures and behavioral patterns obtained through automated tools and manual threat analysis, such as sandboxing. The CTI is then transformed into actionable rules for the IDS engine, enabling real-time detection and prevention of threats. The constant evolution of cyber threats necessitates frequent rule updates, which delay deployment time and weaken overall security readiness. Recent advancements in autonomous agentic systems powered by Large Language Models (LLMs) offer the potential for automatic IDS …

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Tools We Use: Evaluating Uav And Photogrammetry Workflows For Early-Stage Site Documentation; Comparative Analysis For Small Landscape Architecture Firms, Bryant Baugus Aug 2025

Tools We Use: Evaluating Uav And Photogrammetry Workflows For Early-Stage Site Documentation; Comparative Analysis For Small Landscape Architecture Firms, Bryant Baugus

Theses and Dissertations

Landscape architects utilize advanced technologies in the design process. Advancements in automation and data capture have opened up new opportunities for UAVs and photogrammetry to produce high-resolution imagery, contours, and 3D models. By leveraging UAVs early in the design process, landscape architects are able to maximize advantages: site analysis through computational software, 3D sectional information, and hydrology prediction. This research focuses specifically on the advantages UAVs offer compared to established workflow methods. It examines four unique workflows for early-stage site documentation: capturing the site with UAVs through photogrammetry, generating a site plan from publicly available GIS data, gathering information from …

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Creating A Framework For Offering Alternative Credentials At Mississippi State University, Marian Montgomery Chancellor Aug 2025

Creating A Framework For Offering Alternative Credentials At Mississippi State University, Marian Montgomery Chancellor

Theses and Dissertations

As workforce demands evolve and learners seek more flexible, skills-focused education options, Mississippi State University’s College of Professional and Continuing Studies (CPCS) must innovate to remain responsive and competitive. This capstone project explores how MSU can design and implement a scalable framework for micro-credentials that align with employer needs, faculty expertise, and adult learner goals. Grounded in qualitative research, including interviews with faculty and industry leaders, the study identifies key workforce gaps—particularly in communication, leadership, and technical skills—and outlines a 6-stage development lifecycle for credential creation. Findings emphasize the importance of industry collaboration, applied learning, and policy support. The resulting …

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Regulating Artificial Intelligence In The U.S.: A Historical-Innovation-Inspired Framework, Di Kevin Gao Aug 2025

Regulating Artificial Intelligence In The U.S.: A Historical-Innovation-Inspired Framework, Di Kevin Gao

Theses and Dissertations

The emergence of OpenAI\textquotesingle s ChatGPT has marked the dawn of a new Artificial Intelligence (AI) era, unleashing a wave of user excitement, moral panic, and apocalyptic warnings. Yet, these concerns have done little to slow the breakneck pace of AI development and deployment. Should the United States adopt the European Union\textquotesingle s top-down, legislation-first approach, or follow the United Kingdom\textquotesingle s bottom-up, court-driven model? This research draws from historical legislative parallels in the U.S. By examining past regulatory frameworks for disruptive technologies, including electricity, automobiles, the telephone, broadband internet, nuclear technology, cryptocurrency, commodity futures, modern pharmaceuticals, and social media, …

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Extreme Artifacts Removal With Curriculum Learning, Sushant Gautam Aug 2025

Extreme Artifacts Removal With Curriculum Learning, Sushant Gautam

Theses and Dissertations

Restoring severely blurred images remains a significant challenge in computer vision, impacting applications in autonomous driving, medical imaging, and photography. This thesis introduces a novel training strategy based on curriculum learning to improve the robustness of deep learning models for extreme image deblurring. Unlike conventional approaches that train on only low to moderate blur levels, this method progressively increases the difficulty by introducing images with higher blur severity over time, allowing the model to adapt incrementally. Additionally, perceptual loss and hinge loss were integrated during training to enhance fine detail restoration and improve training stability. Various curriculum learning strategies were …

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Topnet R1: A Multi-Stage Ai Framework For Topic Discovery In Scientific Abstracts, Md Elias Hossain Aug 2025

Topnet R1: A Multi-Stage Ai Framework For Topic Discovery In Scientific Abstracts, Md Elias Hossain

Theses and Dissertations

Scientific abstracts are rich sources of knowledge, yet extracting meaningful topics remains challenging due to limitations in existing topic modeling techniques. Traditional methods often struggle with interpretability, scalability, and contextual understanding. To overcome these issues, we introduce TopNet R1, a multi-stage ensemble framework that integrates traditional topic models with contextual embeddings from Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer 4 (GPT-4) large language models (LLMs). Top- Net R1 operates in three phases: (1) topic generation using Latent Dirichlet Allocation (LDA), Non-Negative Matrix Factorization (NMF), Latent Semantic Analysis (LSA), and Hierarchical Dirichlet Process (HDP); (2) LLM-assisted pattern recognition …

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Spray Characterization And Fuel Property Analysis Of Tier 3 Gasoline In A Gdi System Using Machine Learning, Kyungwon Lee Aug 2025

Spray Characterization And Fuel Property Analysis Of Tier 3 Gasoline In A Gdi System Using Machine Learning, Kyungwon Lee

Theses and Dissertations

This study investigates the spray behavior of Tier 3 gasoline in gasoline direct injection engines using experimental methods. Tier 3 gasoline, formulated with lower sulfur content, enhances aftertreatment system efficiency and supports cleaner combustion. A comparative fuel property analysis between Tier 3 gasoline and PACE-20, surrogate fuel, was conducted to understand compositional effects on spray. A constant volume spray chamber and optical diagnostics, including diffuse back-illumination extinction, Schlieren, microscopic, and 3D CT reconstruction imaging, were used to examine spray morphology under varying injection conditions. Key spray parameters such as liquid volume fraction, projected liquid volume, droplet size, and cone angle …

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Finite Element Modeling Of Plasma Membrane Injury From Mechanical Stress: A Combined Finite Element And Machine Learning Approach, Eric Flynn Mabowitz Aug 2025

Finite Element Modeling Of Plasma Membrane Injury From Mechanical Stress: A Combined Finite Element And Machine Learning Approach, Eric Flynn Mabowitz

Theses and Dissertations

Low back pain is a leading cause of disability across a wide range of occupations and environments. Exposure to whole-body vibration (WBV) has been linked to an increased prevalence of low back pain, as well as certain neurophysiological complications. While current understanding of WBV effects is largely based on tissue- and whole-body-level studies, a significant gap remains in knowledge regarding how vibrational forces propagate through individual cells. This knowledge gap limits a comprehensive understanding of how these forces affect the human body at the microscopic level. To address this, the present study employs both two-dimensional (2D) and three-dimensional (3D) finite …

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Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald Aug 2025

Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald

Theses and Dissertations

This study explored the interest and perceived barriers to integrating subaquatic diagnostic technologies (SDTs) into hydrotherapy among licensed physical therapists. Seventeen semi-structured interviews were conducted using a mixed-methods design, with 15 interviews included in the final analysis. Quantitative data were analyzed using chi-square tests, while qualitative responses were coded thematically. Results indicated no statistically significant relationships between SDT interest and career stage or hydrotherapy access, though qualitative data highlighted concerns about cost, limited access, and usability. Despite mixed interest in adoption, participants identified several potential benefits of SDTs, including improved treatment tailoring, increased patient buy-in, and enhanced outcome monitoring. Functional …

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Spatial Variability Of Heat Mortality Rate Relationships In Arizona At Primary Care Area Level, Ria Mukherjee Aug 2025

Spatial Variability Of Heat Mortality Rate Relationships In Arizona At Primary Care Area Level, Ria Mukherjee

Theses and Dissertations

Heat Mortality Rates (HMR) in Arizona (AZ) are one of the highest in all of US. The HMR association with environmental, socioeconomic, demographic, and occupational factors has been widely investigated to inform mitigative policy. This study employed linear and spatial models- Ordinary Least Square (OLS), Geographically Weighted Regression (GWR) and multiscale Geographically Weighted Regression (MGWR), across AZ at Primary Care Area (PCAr) level to identify important spatial trends in HMR relationship. Results indicated a significant global association between heat mortality and environmental variables and the elderly population aged 65 and older. In contrast, the working age group between 54 and …

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Unboxing The Black Box: Graph-Based Interpretability In Transformer Models, Ramak Nassiri Aug 2025

Unboxing The Black Box: Graph-Based Interpretability In Transformer Models, Ramak Nassiri

Theses and Dissertations

This thesis introduces a novel interpretability framework for transformer encoder models by hypothesizing that their internal embedding updates define a state transition system. We propose that transformers implicitly learn token-to-token influence dynamics, which can be analyzed using graph-theoretic methods. To validate this, we construct transition graphs from embedding changes and rank token importance using the PageRank algorithm. We develop two transformer models from scratch: a self-supervised model that incorporates serotype tokens to learn contextualized embeddings, and a supervised model initialized with these embeddings. Cosine similarity analysis of their token influence patterns reveals strong structural alignment, with values exceeding 93%. This …

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Decision-Making And Execution Skill Estimation In Continuous Action Space Domains, Delma I. Nieves-Rivera Aug 2025

Decision-Making And Execution Skill Estimation In Continuous Action Space Domains, Delma I. Nieves-Rivera

Theses and Dissertations

In many real-world domains with continuous action spaces, an agent’s performance is driven by two key factors: its decision-making skill, or ability to select high-quality actions, and its execution skill, or precision in carrying out these actions. However, accurately evaluating these skills, particularly when direct information about the agent’s intentions is unavailable, remains a challenging problem. This research addresses this need by developing a theoretical framework and proposing novel estimation methods to assess both decision-making and execution skills based solely on observable data: executed actions and their associated rewards. The work consists of six core studies focused on developing and …

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Markov Chain Monte Carlo Techniques– Innovations In Lifetime Data Analysis And Missing Value Imputations, Tobias Omondi Oketch Aug 2025

Markov Chain Monte Carlo Techniques– Innovations In Lifetime Data Analysis And Missing Value Imputations, Tobias Omondi Oketch

Theses and Dissertations

This dissertation develops scalable Bayesian solutions for two critical challenges in modern data analysis: modeling failure times and imputing missing biological data. First, we introduce an adaptive semi-parametric MCMC framework for Weibull lifetime modeling, addressing the lack of conjugate priors and multidimensional sufficient statistics. Using hierarchical modeling and the No-U-Turn Sampler (NUTS) in STAN, we evaluate 24 prior combinations across 72 simulated datasets. The method yields robust parameter estimates under increasing and decreasing hazard rates and proves effective in predicting prostate cancer patient survival. Second, we assess imputation strategies for high-throughput proteomics data, where missingness distorts signal integrity. We compare …

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Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman Aug 2025

Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman

Theses and Dissertations

Reliable and efficient measurement of wood chip moisture content is crucial for forest-reliant industries, including biofuel production, pulp and paper manufacturing, and bio-refineries, as it directly influences product quality and energy output. Traditional methods like the oven-drying technique, despite their widespread use, are time-consuming and impractical for real-time applications, while modern alternatives such as NIR spectroscopy, electrical capacitance, and microwave analysis are often costly, less portable, and require specialized expertise. This dissertation addresses these limitations by leveraging deep learning and machine vision to develop a scalable, accurate, and portable method for moisture content measurement using RGB images of wood chips. …

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Raspberry Cultivar Evaluation Trial In Mississippi, Apphia Santy Aug 2025

Raspberry Cultivar Evaluation Trial In Mississippi, Apphia Santy

Theses and Dissertations

Raspberries (Rubus idaeus) are valued for their flavor, appearance, and nutritional quality. This study evaluated 26 raspberry cultivars over two seasons (2023 and 2024) in Mississippi under a 50% shade-covered system, using organic and conventional fertilization in 7-gallon containers. Cultivars included floricane- and primocane-fruiting types. Data collected included harvest timing, yield, berry weight, soluble solids content (°Brix), titratable acidity, total phenolic content (TPC), and total flavonoid content (TFC). Results showed cultivar differences in yield, berry quality, and antioxidant levels. In 2023, conventionally fertilized plants produced higher yields; in 2024, fertilizer had no impact. Late-season harvests had elevated phytochemicals. ‘Prelude,’ ‘Nova,’ …

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Plant, Pollinator, And Bird Communities In Working Landscapes Across The Southeastern United States., Craig Andrew Sklarczyk Aug 2025

Plant, Pollinator, And Bird Communities In Working Landscapes Across The Southeastern United States., Craig Andrew Sklarczyk

Theses and Dissertations

The southeastern U.S. is a hot spot for biodiversity, yet we continue to see losses in numerous species and their important ecosystem functions and services. Because private working landscapes are widespread and important to the southeastern U.S. and Mississippi’s economy, we must ensure we are conserving species on these private lands as well. In this project, We examined two groups of taxa, bird and bee communities, each which perform vital ecosystem functions in two of the most spatially dominant systems (working pine forest and row-crop agriculture) in Alabama and Mississippi. We examined bee communities in set-aside hardwood forests at different …

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Confirmatory Factor Analysis Of The Psychopathic Personality Inventory-Revised: Short Form In College-Attending Emerging Adults, Lydia Stanhope Aug 2025

Confirmatory Factor Analysis Of The Psychopathic Personality Inventory-Revised: Short Form In College-Attending Emerging Adults, Lydia Stanhope

Theses and Dissertations

Psychopathy research stems from the work of Dr. Hervey Cleckley, whose research aided in providing the foundation for psychopathy assessments currently utilized in the field. Several researchers used Cleckley’s framework to further home in on characteristics that are central to psychopathy. Among the primary researchers who adapted the characteristics into their own measures are Robert Hare, Paul Frick, and Scott Lilienfeld; the work of these researchers is what helped lead to the creation of the Psychopathic Personality Inventory-Revised: Short Form (PPI-R: SF). The current study aimed to confirm the two-, three-, and eight-factor models from previous versions of the measure …

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Thermo-Mechanical Advancements For Very High Strength And Ultra High Performance Concretes, Lana Grayson Brown Sisung Aug 2025

Thermo-Mechanical Advancements For Very High Strength And Ultra High Performance Concretes, Lana Grayson Brown Sisung

Theses and Dissertations

Interest in the use of high-strength concrete (HSC) has increased in recent years with demand for improved concrete performance. HSCs are widely associated with high heat of hydration and elusive behavior when exposed to high temperatures commonly occurring in mass structures. The optimization of HSC mixture proportioning is difficult due to a wide variety of constituents that influence thermal and mechanical properties. Additionally, determining in-place properties of mass concrete placements is elusive, and there are currently minimal to no test methods available that are both predictive and a direct measurement of mechanical properties. The objective of this dissertation is to …

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Estimating Reliability Of Electric Vehicle Charging Ecosystem Using Principle Of Maximum Entropy, Himanshu Tripathi Aug 2025

Estimating Reliability Of Electric Vehicle Charging Ecosystem Using Principle Of Maximum Entropy, Himanshu Tripathi

Theses and Dissertations

This thesis addresses the challenge of estimating electric vehicle (EV) charging system reliability against unpredictable threats like cyberattacks and extreme weather, where traditional methods fail. We utilize the Principle of Maximum Entropy (PME), a statistical tool that provides unbiased risk estimates using limited information. Applied to the EV charging ecosystem, our case study shows how PME models stress factors to predict failures and optimize maintenance. This approach extends beyond EVs to other complex systems with scarce data, such as smart grids or healthcare devices. By linking uncertainty directly to reliability, PME offers a universal method to improve decision-making under unpredictable …

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Non-Thermal Dbd Plasma-Induced Co₂ Capture And Conversion To Value Added Chemicals, Chinwendu Theresa Umeojiakor Aug 2025

Non-Thermal Dbd Plasma-Induced Co₂ Capture And Conversion To Value Added Chemicals, Chinwendu Theresa Umeojiakor

Theses and Dissertations

Electrified CO2 conversion via nonthermal dielectric-barrier discharge (DBD) plasma presents a promising pathway for integrating renewable energy into the carbon cycle, addressing the dual challenges of CO2 reduction and sustainable fuel generation. In this research, DBD plasma technology was integrated with a sorbent material and/or catalytic materials for CO2 desorption and conversion. Specifically, with Ni/Al2O3 as the catalyst, we investigated CO2 splitting (CO2 to CO and 0.5O2) and hydrogenation (CO2 and H2 to CO and H2O) under adiabatic and subcooled conditions. We find that CO2 splitting shows higher efficiency than hydrogenation, particularly at relatively lower power inputs. While CO2 hydrogenation …

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Optimizing Osb Quality: Assessing The Influence Of Beta-Cyclodextrin With Essential Oil Treatments, Ethan Garrett Turo Aug 2025

Optimizing Osb Quality: Assessing The Influence Of Beta-Cyclodextrin With Essential Oil Treatments, Ethan Garrett Turo

Theses and Dissertations

This study evaluated the mechanical and dimensional performance of oriented strand board (OSB) panels treated with beta-cyclodextrin-essential oil compounds, including betacyclodextrin-only, beta-cyclodextrin-trans-cinnamaldehyde, beta-cyclodextrin-thymol, and betacyclodextrin-nickel. OSB panels were produced using a proprietary spraying system and Dieffenbacher press and tested according to ASTM standards for internal bond strength, modulus of elasticity (MOE), modulus of rupture (MOR), water absorption, and thickness swelling. Results showed that beta-cyclodextrin-trans-cinnamaldehyde enhanced MOE and MOR, while beta-cyclodextrin-thymol significantly improved internal bond strength. Beta-cyclodextrin-nickel demonstrated strong performance in both mechanical strength and water resistance. However, 24-hour submersion results indicated that water resistance may be surface limited. All treatments …

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Academics Vs Athletics: Prioritizing The Students In Student-Athletes And The Importance Of Their Return To The Classroom, Stephen Walker Aug 2025

Academics Vs Athletics: Prioritizing The Students In Student-Athletes And The Importance Of Their Return To The Classroom, Stephen Walker

Theses and Dissertations

The Mississippi High School Activities Association (MHSAA) aims to enhance student- athletes' educational experiences but Law 6.5.1 inadvertently causes students to miss 300 hours of academic instruction annually. This dilemma forces school districts to choose between robust sports programs and rigorous academic schedules, ultimately creating a disadvantage for students. While participation in sports has been linked to improved academic performance, the current structure disproportionately allocates resources to athletics over academics, with only 51% of schools offering after-school academic programs compared to 77% for sports. This paper discusses the benefits of sports, including higher attendance and graduation rates, but also highlights …

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Bridging Physics And Machine Learning: Physics-Informed Neural Networks (Pinn) For Wire-Arc Additive Manufacturing (Waam) Thermal Prediction, Haiye (Justin) Xie Aug 2025

Bridging Physics And Machine Learning: Physics-Informed Neural Networks (Pinn) For Wire-Arc Additive Manufacturing (Waam) Thermal Prediction, Haiye (Justin) Xie

Theses and Dissertations

Over the past decade, additive manufacturing (AM) has gained substantial use in industry and research. It is a promising alternative to traditional subtractive and casting manufacturing. AM not only saves time and materials but can also construct intricate structures within components for specific purposes. Wire-Arc Directed Energy Deposition (WA-DED) is one of the additive manufacturing technologies that offers a high extrusion rate of metal wire materials to fabricate near-net-shape metal components. Accurate temperature control is crucial for controlling the microstructure of metal components fabricated through the AM process. Machine learning has the ability to analyze real-time sensor data, such as …

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Interatomic Potential Of Multiphase Materials Using Modified Embedded Atom Method (Meam) And Artificial Neural Network (Rann), Henan Zhou Aug 2025

Interatomic Potential Of Multiphase Materials Using Modified Embedded Atom Method (Meam) And Artificial Neural Network (Rann), Henan Zhou

Theses and Dissertations

There is a significant need for computer simulations to explore multiphase materials because of their significance in both industry and research. These simulations are both more efficient and less expensive than many experimental approaches, making them an ideal choice for this purpose. It is possible to use molecular dynamics simulations that make use of the MEAM and RANN interatomic potentials in order to comprehend and characterize the properties, performance, and behavior of materials at the atomic scale of different material phases. In the realms of elements, alloys, and impurities, MEAM can be utilized in a wide variety of applications. Through …

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Reactive Molecular Dynamics And Method Development For Applications In Renewable Energy And Sorption Equilibria, Woodrow Wilson Aug 2025

Reactive Molecular Dynamics And Method Development For Applications In Renewable Energy And Sorption Equilibria, Woodrow Wilson

Theses and Dissertations

It is crucial to harness energy from sustainable sources to combat the dwindling nonrenewable feedstocks used to produce everyday commodities and fuels. Liquid-phase heterogeneous catalysis has demonstrated remarkable product selectivity and yields for reactions relevant to biomass valorization under mild operating conditions. However, active site characterization is challenging due to the complex solvated environment and interface. Ground-state first-principles (FP) molecular simulations have provided insights into reactive systems in catalysis. These calculations, however, scale poorly with the number of electrons. Observing atomic motion with molecular dynamics (MD) or sampling static properties with Monte Carlo (MC) simulations at statistically relevant lengths- and …

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Advancing Workforce Development In Digital Health: A Regional Model From The Gcc, Manal Almalki, Osama El-Hassan, Jawad Ahmed, Amr Jamal, Mowafa Househ, Evelyn Hovenga, Paul Barach Aug 2025

Advancing Workforce Development In Digital Health: A Regional Model From The Gcc, Manal Almalki, Osama El-Hassan, Jawad Ahmed, Amr Jamal, Mowafa Househ, Evelyn Hovenga, Paul Barach

College of Population Health Faculty Papers

This study examines the evolution of ZIMAM's role in the Gulf Cooperation Council's (GCC) taskforce on workforce development in digital healthcare. Established in 2016 and formalized as a non-profit organization in 2023, ZIMAM integrates international best practices, regional insights, and innovative strategies to develop a scalable digital health knowledge and skills framework. ZIMAM's methodology includes competency mapping aligned with the Skills Framework for the Information Age (SFIA), stakeholder engagement, and iterative validation to ensure relevance and adaptability. Key ZIMAM initiatives encompass the development of governance structures, capacity-building workshops, annual conferences, and recognition programs such as the ZIMAM-ELSEVIER Digital Health Awards. …

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Development Of A Health Knowledge And Skill-Based Framework For The Digital Age, Evelyn Hovenga, Osama El-Hassan, Manal Almalki, Jawad Ahmed, Paul Barach, Mowafa Househ, Amr Jamal Aug 2025

Development Of A Health Knowledge And Skill-Based Framework For The Digital Age, Evelyn Hovenga, Osama El-Hassan, Manal Almalki, Jawad Ahmed, Paul Barach, Mowafa Househ, Amr Jamal

College of Population Health Faculty Papers

The Gulf Cooperation Council (GCC) region is tackling a significant digital healthcare workforce skills gap by creating a computable unified digital health competency framework and repository. Digital technologies and global competency standards are leveraged to professionalize the digital health knowledge domain and facilitate the development of clear career pathways in digital health. A mixed-methods approach was employed to develop the framework. A standardized categorial structure and information model has been developed to support the creation of this computable framework for workforce evaluation and competency-based career development.

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Towards Data-Driven Science Literacy: Extracting Psycholinguistic Markers In Vaping-Related Online Peer Interactions, Sahiti Myneni Aug 2025

Towards Data-Driven Science Literacy: Extracting Psycholinguistic Markers In Vaping-Related Online Peer Interactions, Sahiti Myneni

Faculty, Staff and Student Publications

Social media debates on e-cigarettes raise public health concerns due to evolving evidence and conflicting guidelines. We analyzed 25,127 vaping-related comments to explore how users discuss vaping-related topics. Our analysis revealed 25 topics grouped into three parent topics: positive effects of vaping, negative effects of vaping, and vaping-related news & information. Significant differences were observed in psycholinguistic characteristics with high emotional exchanges as positive and negative effects of e-cigarettes are debated. Our results can inform interventions promoting science literacy and misinformation resistance.

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The First Thirty Years Of Green Stormwater Infrastructure In Portland, Oregon, Michaela Koucka, Cara Poor, Jordyn Wolfand, Heejun Chang, Vivek Shandas, Adrienne Aiona, Henry Stevens, Tim Kurtz, Svetlana Hedin, Steve Fancher, Joshua Lighthipe, Adam Zucker Aug 2025

The First Thirty Years Of Green Stormwater Infrastructure In Portland, Oregon, Michaela Koucka, Cara Poor, Jordyn Wolfand, Heejun Chang, Vivek Shandas, Adrienne Aiona, Henry Stevens, Tim Kurtz, Svetlana Hedin, Steve Fancher, Joshua Lighthipe, Adam Zucker

Geography Faculty Publications and Presentations

Over the past 30 years, the City of Portland, Oregon, USA, has emerged as a national leader in green stormwater infrastructure (GSI). The initial impetus for implementing sustainable stormwater infrastructure in Portland stemmed from concerns about flooding and water quality in the city’s two major rivers, the Columbia and the Willamette. Heavy rainfall often led to combined sewer overflows, significantly polluting these waterways. A partial solution was the construction of “The Big Pipe” project, a large-scale stormwater containment system designed to filter and regulate overflow. However, Portland has taken a more comprehensive and long-term approach by integrating sustainable stormwater management …

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The Case For Mass Media Communication Theories In The Study Of Artificial Intelligence: A Uses And Gratifications & Parasocial Interaction Theory Approach, Colin Farmer Aug 2025

The Case For Mass Media Communication Theories In The Study Of Artificial Intelligence: A Uses And Gratifications & Parasocial Interaction Theory Approach, Colin Farmer

Theses

This study analyzes communication and relationship building between textual generative Artificial Intelligence programs and their users through the lens of parasocial interactions and uses and gratifications. It measures loneliness, knowledge gaining, and task completion as the primary reasons motivating perceived relationship development with AI applications. Through a quantitative survey, it explores the connections between time spent using AI, as well as the previously mentioned factors and seeks to determine what influences a user’s perceived relationship with an AI chatbot program. Comparisons are also drawn between the relationships with AI and the user’s relationships with celebrities, further expanding the justification for …

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