Magnetic Resonance Imaging Safety And Considerations, Lauren Mosier

Medical Imaging Senior Posters

Abstract

Magnetic Resonance Imaging (MRI) is considered to be a safe, non-invasive diagnostic modality. However, the presence of a strong magnetic field creates inherent risks when safety protocols are not followed. This project examines MRI safety, with particular focus on the recent fatality in New York, where a person was killed by a projectile accident in the scanner room. Such events highlight the catastrophic consequences that can result from lapses in screening procedures, inadequate staff training, or poor enforcement of zone protocols. By reviewing this incident in the context of MRI safety protocols, this project emphasizes the ongoing need for …

2025 Intersession Catalog, Illinois Math And Science Academy

Intersession Catalogs

No abstract provided.

Evaluation Of The 2025 Globe U.S. Virtual Srs, Eleanor M. Jaffee, Globe U.S. Coordination Office

Publications and Media

No abstract provided.

Applied Statistics Course Offerings: Spring 2025, University Of Mississippi. Graduate School

GMAS Course List

No abstract provided.

Data For Research Collaboration And Co-Authorship In The Gulf Of Mexico, 2000–2018, Owen Temby, Dongkyu Kim, Juliet Vallejo

Datasets

This dataset documents research collaboration and co-authorship among organizations engaged in environmental science in the Gulf of Mexico from 2000 to 2018. The data were compiled through bibliometric analysis of scientific articles, with each record containing publication-level and author affiliation information, as well as institutional and country codes. The dataset provides the basis for network analysis of collaborative patterns among institutions in the United States, Mexico, and Cuba. Variable definitions and data structure are described in the accompanying README file.

The Ripple Effects Of Microaggressions: Understanding Employee Responses And The Moderating Role Of Racial Representation At Work, Tyleen Lopez

Wayne State University Dissertations

Despite the advancement of research on microaggressions, their impact on employees’ emotional well-being and behavior remains unclear (Fattoracci & King, 2023). In response, I examine the associations between microaggressions, hurt feelings, and counterproductive work behaviors (i.e., withdrawal and production deviance). Additionally, I consider racial representation as a potential moderator. Drawing upon social identity theory, social categorization theory, and the Stressor-Emotion Model, I argue that microaggressions lead to hurt feelings, prompting employees to engage in counterproductive work behaviors as a coping mechanism (Tajfel & Turner, 1979; Tajfel et al., 1971; Spector & Fox, 2005). Furthermore, I argue that the positive indirect …

Centering Sisterhood: An Exploration Of Black Mothers’ Wellness Experiences Through A Group Therapy Intervention, Kimberly Stokes

Wayne State University Dissertations

The brilliance of Black mothers has centered their community’s progression and perseverance for centuries. Yet, most of the psychological research is either absent or promotes a deficit-framing of their experiences. In the present study, I use critical qualitative methodology to center the wellness experiences of Black mothers through analyzing a group therapy intervention entitled, Invincible Black Women. I aimed to promote strength-based, holistic research and practice for Black mothers. The research questions guiding this study focused on group participants’ definitions and applications of care practices as well as the role of mothering as explained in group therapy sessions. Sessions were …

Guide To The Warrick L. Carter Collection, Columbia College Chicago

CBMR Collection Guides / Finding Aids

Contains the original scores, arrangements, and teaching materials created by Dr. Warrick L. Carter, an educator, musician, performer, administrator, drummer, and composer, who served in leadership roles at Berklee College of Music in Boston, Massachusetts, Walt Disney Entertainment, and as the first African American president of Columbia College Chicago in Illinois. The collection holds his jazz compositions and arrangements for small and large ensembles.

Cybersecurity And Business Analytics: Strengthening Financial And Governmental Digital Defenses, Bushra F. Malik, Ravindar Reddy Gopireddy

Accounting, Business Analytics, Economics, and Finance Department Faculty Articles

The rapid digitization of financial services and federal operations has significantly increased cybersecurity risks. Cybercriminals are continuously evolving their attack methodologies, targeting financial institutions and government agencies to exploit vulnerabilities in digital infrastructures. Business analytics has emerged as a powerful tool in combating these threats by leveraging artificial intelligence (AI), machine learning (ML), and big data analytics to detect, analyze, and prevent cyber threats in real time. This paper explores the convergence of cybersecurity and business analytics, emphasizing their combined role in strengthening threat intelligence, fraud detection, incident response, and regulatory compliance. The research provides insights into emerging security trends, …

Impacts Of A Yoga And Mindfulness Course On High School Students, Nick R. Abel, Akande Akande, Brandie M. Oliver

Scholarship and Professional Work – Education

This research investigates the impact of a yoga and mindfulness (YM) course taught by a high school counselor in the United States to address student anxiety, stress, and coping skills. Pre- and post-tests administered to participants and a control group indicated significant reductions in anxiety and stress among class participants, suggesting YM interventions can effectively enhance student wellbeing in school settings. Implications for educators include integrating YM practices into a comprehensive program to support holistic student wellbeing.

2025 Youth Transitions Advisory Council Annual Report, Tennessee Commission On Children And Youth, Tennessee. Youth Transitions Advisory Council.

Annual Reports

In accordance with T.C.A. 37-2-601 – 37-2-606 the Tennessee Commission on Children and Youth is pleased to provide the 2025 Annual Report of the Youth Transitions Advisory Council. The Youth Transitions Advisory Council brings dedicated advocates together from across the state who are developing and implementing new strategies to meet the challenges of engaging former foster youth and other young adults as they make the critical transition from adolescence to adulthood. This report outlines the work of the Youth Transitions Advisory Council as the members continue to develop strategies to assist these young adults as they prepare for success in …

Fusion-Based Utilization And Synthesis Of Efficient Detections, Ethan C. Rogers, Parker H. Liberatore, Thomas G. James

Endeavors: Mississippi State Undergraduate Research Journal

This study aimed to develop hardware and software for an object detection fusion system, using three different sensors. The system was built and studied with the motivating application of autonomous drones searching for and detecting people in a search-and-rescue scenario. The system’s performance was compared to that of individual sensors deployed for the same task. The focus of the research was to prove the competence and benefits of a decision-level fusion method as it was applied to a lightweight object detection architecture, and the driving motivators behind the study were simplicity in implementation and good computational performance. In short, the …

Winter 2025, Southwestern Oklahoma State University Office Of Institutional Advancement And Alumni

Echoes from the Hill

From the President

Dear Southwestern Oklahoma State University (SWOSU) alumni, emeriti, & friends –

I hope that this issue of Echoes From The Hill finds you and yours well.
Here on the SWOSU Hilltop we are excited as the Spring 2025 semester is underway!

This latest edition of Echoes highlights the happy times we shared together last Fall during our 2024 Homecoming and our 2024 Charitable Hunt! You will also read about our 2024 Athletic Hall of Fame honorees and learn about the many achievements of SWOSU graduates engaged in a wide variety of industries, causes, and sectors throughout the …

Unh: The Magazine Of The University Of New Hampshire, Winter 2025, Unh Magazine

UNH Magazine

No abstract provided.

Virtual Fixtures For Teleoperated Robots For The Visually Impaired, Vishwaak Chandran Thamaraiselvan

Computer Science and Engineering Theses - Archive

This paper presents our preliminary study on enabling individuals with visual impairments to safely operate mobile robots and vehicles. To achieve this, we developed a teleoperation with accessibility at its core. The system incorporates features that enhance usability and situational awareness, including assistive control based on artificial potential fields to prevent collisions and ensure smooth navigation. It also provides multimodal feedback through (a) haptic vibrations on the gamepad controller, which convey the proximity of nearby objects detected by the robot’s laser sensor, and (b) color-coded overlays that differentiate paths, obstacles, and people through semantic segmentation performed by a deep neural …

Event-Based Histogram Of Gradients For Lane Detection, Ganesh Gupta

Computer Science and Engineering Theses - Archive

In the rapidly evolving landscape of autonomous driving technology, lane detection systems stand as fundamental guardians of vehicular safety. The National Highway Traffic Safety Administration identifies unintentional lane departures as responsible for approximately one-third of all road accidents—a sobering statistic that underscores the critical importance of robust lane detection methodologies. This thesis embarks on an academic exploration at the intersection of neuromorphic engineering and computer vision, examining how the distinctive properties of event-based cameras might be harnessed to enhance lane detection capabilities under challenging environmental conditions. Unlike conventional frame-based imaging sensors that capture entire scenes at fixed intervals, event-based cameras …

Modeling Trust And Deception In Multi-Agent Reinforcement Learning Using The Werewolf Game, Pathikkumar Dharmeshbhai Patel

Computer Science and Engineering Theses - Archive

This thesis explores the emergence of trust, deception, and adaptive strategy in multi-agent reinforcement learning (MARL) environments using the social deduction game Werewolf as a simulation framework. In this environment, agents operate with hidden roles, incomplete information, and the need to reason about others’ intentions- mirroring the complexities of real-world social interactions. We present and evaluate two agent architectures: Agent vA, a symbolic, heuristic-based agent with probabilistic trust modeling and scalable memory structures; and Agent vB, a modular Q-learning agent that learns phase-specific policies through reinforcement. Agent vA relies on symbolic reasoning, bounded belief updates, and generalizable heuristics, while Agent …

Exploring Instruction Generation For Uavs: Dataset Adaptation, Model Behavior, And Diagnostic Insights, Seyedarman Vaziri Bozorg

Computer Science and Engineering Theses - Archive

This thesis explores the development of an answering agent capable of generating natural language instructions for unmanned aerial vehicles (UAVs), grounded in a limited, real-world dialogue dataset. The objective is to adapt a static dataset into a training pipeline that can support instruction generation and serve as a foundation for future interactive systems involving question-asking agents and internal dialogue. A hybrid architecture is implemented using a semantic teacher model (MPNet) and a T5-base encoder-decoder trained with contrastive and supervised objectives. The adapted training process yields statistically acceptable performance across standard evaluation metrics. However, qualitative analysis reveals a mismatch between metric …

Rearchitecting Aerial Omniverse Digital Twin For Script-Driven And Scalable Simulations, Sarath Chandra Viswanadh Nagadevara

Computer Science and Engineering Theses - Archive

The Nvidia Aerial Omniverse Digital Twin (AODT) platform provides a comprehensive framework for modeling radio network behavior under varying user mobility scenarios for 5G, 6G, and beyond. However, the current AODT implementation relies on a graphical user interface (GUI) to manually configure simulation parameters and initiate runs, which limits its capability to support automated, large-scale simulations that are needed by future cellular networks. In this study, we re-architect AODT to enable automation and control through scripts by decoupling its original simulation backend engine from the GUI. We adopt a client-server architecture, where the server runs the simulation backend engine controlled …

Centrality Algorithms For Weighted Homogeneous Multilayer Networks, Ayomide Ayowole-Obi

Computer Science and Engineering Theses - Archive

Applications need to be modeled for analyses. With the availability of many alternate data Models, choosing one needs to be done carefully by considering the complexity of data to be modeled and its analyses requirements. Social networks and other newer applications are primarily relationship-oriented and also have multiple types of entities and relationships. Although simple and attributed graphs have been used historically for modeling these applications, recently, multilayer networks (or MLNs) have been shown to be more effective in preserving the semantics of the application better and further provide flexibility of analyses. However, choice of MLN as a data model …

Training Data Privacy In Machine Learning: A Systematization Of Attacks And Defenses, Mohammad Sufyaan Saeed

Computer Science and Engineering Theses - Archive

Training and deploying Machine Learning (ML) models introduce significant data confidentiality risks, as modern models can inadvertently memorize and leak information about their training data. While attacks such as membership inference and model inversion are well studied, the literature remains fragmented, with inconsistent threat models and unclear relationships across attack classes and defenses. This work presents a Systematization of Knowledge (SoK) that unifies the landscape of training-data privacy attacks and defenses, aligning them with the NIST Adversarial Machine Learning (AML) taxonomy to enable standardized threat modeling and comparison. Our analysis shows that, despite significant progress in characterizing attack vectors, defenses …

Methods Of Optimizing Storage And Retrieval Of Structured Data, Neelim Haider

Computer Science and Engineering Theses - Archive

Storing and retrieving large amounts of data reliably is becoming more and more important as time goes on. There are high demands to store highly personal information such as social security numbers, bank account information, and residence information to rapidly changing data such as employee information, inventory information, and stock information. Therefore, the ability of a system to store, remove, and update such information efficiently and correctly is critical. There are different types of data that database systems can potentially hold: structured, unstructured, and semistructured data. Various database models have been developed to provide a framework that allows designers to …

Technology-Facilitated Abuse (Tfa): Analyzing Trends, Tactics, And Victim Responses On Reddit, Solomon G. Dandekar

Computer Science and Engineering Theses - Archive

The increasing integration of technology into daily life has provided numerous benefits but also significant risks, particularly when exploited by malicious actors in cases of technology facilitated abuse (TFA). Per- petrators can misuse technology to monitor, control, and intimidate their partners, random strangers, etc. exacerbating cycles of abuse. From location tracking and cellphone surveillance to smart device manipula- tion, spyware, and doxing, digital tools have become powerful instruments for coercion and control. This research project investigates the role of technology in stalking and harassment by analyzing discussions on a relevant subreddit where victims share their experiences, strategies for coping, and …

Transformer And Recurrent Architectures For Dynamics Prediction And Policy Learning On Long-Horizon Tasks, Vinal Jitendrabhai Gadhiya

Computer Science and Engineering Theses - Archive

Model-based reinforcement learning promises improved sample efficiency by learning environment dynamics and using them for planning or policy improvement. However, the choice of neural architecture for dynamics prediction significantly impacts the model's ability to capture temporal dependencies and maintain long-term context, capabilities crucial for complex, open-world environments.

This thesis investigates three neural architectures for learning world models: Transformer-based, GRU-based, and a hybrid Transformer+GRU approach. We evaluate these architectures on Crafter, a 2D open-world survival environment that requires long-horizon planning and sequential task completion. In Crafter, agents must perform hierarchical sequences of actions, such as collecting wood, placing a table, and …

Diversity-Driven Xor Secret Sharing: Reliable And Secure Multi-Path Transmission, Richard M. Olu Jordan

Computer Science and Engineering Theses - Archive

The growing reliance on distributed storage and multipath communication sys- tems has intensified the need for security mechanisms that remain robust even when individual nodes or channels are compromised. Secret sharing provides an information- theoretic approach to achieving both confidentiality and availability, and XOR-based constructions in particular offer lightweight and highly structured designs. This thesis develops a unified analytical framework for understanding and evalu- ating XOR-based secret sharing schemes across multiple operational settings, includ- ing plaintext storage, encrypted-data scenarios, and noisy binary symmetric chan- nels (BSCs). Building on a general (t, n) system model, we examine five threshold configurations—(2, 3), …

A Deep Reinforcement Learning Framework For Sequential Art Creation, Asmin Pothula

Computer Science and Engineering Theses - Archive

Most computational art systems rely on generative models that produce a complete artwork in a single pass, without capturing the gradual, decision-driven process through which human artists construct visual pieces. Prior research in sequential, stroke-based image generation, including differentiable neural painters and model-based reinforcement learning agents, has explored step-by-step creation, but these systems typically aim to reconstruct the input image within the same visual representation space, closely matching brushstrokes, textures, or colors to the target. In contrast, this thesis investigates sequential art creation in a different artistic representation, where the final artwork does not share the same visual form as …

Crime Theory Informed Agent-Based Modeling For Crime Prediction And Patrolling Route Optimization, Shohreh Moradi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Crime reduction remains a global priority, demanding both accurate modeling of criminal dynamics and efficient allocation of scarce policing resources. To address these needs, this study presents a two‐fold framework that (1) simulates street‐level crime patterns using an agent‐based model (ABM) grounded in Routine Activity Theory (RAT), Rational Choice Theory (RCT), and Crime Pattern Theory (CPT), and (2) optimizes patrol routing through a time-dependent, multi‐visit mixed‐integer linear programming (MILP) formulation.

In the first component, we integrate real‐world crime, environmental, and census data to reproduce realistic offender, citizen, and Police behaviors, capturing where and when robbery, burglary, and larceny occur across …

Guided-Mode Resonant Nanopatterns For Raman Generation And Photonic Devices, Renjie Chen

Electrical Engineering Dissertations - Archive

This dissertation explores advanced strategies for enhancing Raman amplification in silicon photonic devices, focusing on guided-mode resonance engineering and resonant mode manipulation. Silicon, despite its indirect bandgap, exhibits a strong Raman scattering coefficient, enabling it to function as a viable gain medium for integrated photonic systems. However, the realization of efficient, compact, and low-threshold silicon Raman amplifiers and lasers necessitates innovative design approaches that overcome inherent material and structural limitations.

The first chapter provides a fundamental overview of optics, including physical principles, spectral characteristics, guided-mode resonance, simulation methods, and nanopattern fabrication methods.

The second chapter delves into silicon-based Raman amplification …

Characterization And Modeling Of Polyphase Machines And Power Conditioning Components, Nathan Lockhart

Electrical Engineering Dissertations - Archive

Microgrid power configurations have become increasingly prevalent in recent power systems due to the rise of power electronic energy generation, energy storage, and the many diverse electrical demands. Microgrids offer numerous advantages over traditional power electronic networks, which rely on large rotating generators to supply power over extensive distances to multiple users. Remote power grids are particularly beneficial for smaller networks that may be isolated or have unique power requirements, often incorporating energy storage to enhance operational flexibility. Advances in power electronics, such as medium voltage DC distribution, are enhancing the reliability, redundancy, and integration capabilities of isolated microgrids.

To …

Scalable Approaches Towards Characterizing And Mitigating Emerging Phishing Scams, Sayak Saha Roy

Computer Science and Engineering Dissertations - Archive

Phishing scams are among the most dangerous and persistent forms of cybercrime, leveraging social engineering to exploit human behavior and obtain sensitive information, leading to widespread identity theft and data breaches. In the past year, these attacks have resulted in financial losses exceeding $10 billion in the United States alone. As phishing scams continue to evolve, they have not only expanded in scale but also grown in sophistication, spreading rapidly across social media and employing adversarial techniques to evade detection by anti-scam tools. The situation is further exacerbated by the availability of advanced phishing kits, and more recently, generative AI, …