Digital Commons Network^™

Steam Olympics Raises $7,500 For Iwu Scholarships, Emily Bollinger

Press Releases 2020-2029

No abstract provided.

The Impact Of Prior Abusive Dating Experiences And Gender On Romance Scam Victimization And Monetary Loss, Trevor Rowe

Department of Psychology

Online romance scams are a rapidly expanding cybercrime that affects millions of people each year, financially and emotionally. This study examines an underexplored question: Will individuals with a greater number of abusive partners be more vulnerable to romance scam victimizations and lose more money? Adult dating app users (N = 518) completed an online survey. After controlling for being approached for relationships, those with a greater number of past abusive partners were more likely to be victims and lost more money. In addition, men reported a higher frequency of romance scam victimizations and more money loss.

Hawk's Herald -- April 23, 2026, Roger Williams University

Hawk's Herald

No abstract provided.

Data Analysis For A Regional Department Of Transportation, Maxwell Cook, Kendall Klewer, Jocelyn Wood

2026 Student Academic Showcase

The given client is the regional office of a state department of a transportation agency that oversees five counties within the state. The regional office has provided information pertaining to areas such as financials, car accidents, and contractors which will be used to explore a variety of data trends and insights. The goal of the data exploration is to determine if there are other ways in which money can be reallocated to create an optimized spending plan for future projects. Actual award cost versus estimated award cost, contractor versus timeliness of projects, and type of job versus employers in a …

Extending Cubesat Star Tracker Operation To Very Low Earth Orbit Using A 2d-Morphological Clutter Filter, Jaxyn Kyli Kirian

Honors Capstone Projects and Theses

No abstract provided.

Educational Policy Committee Minutes, Clemson University Board Of Trustees, 2026 April 26, Clemson University Board Of Trustees, Clemson University Board Of Trustees

Minutes

No abstract provided.

Beyond Measurable Success: An Autoethnographic And Phenomenological Study Of Resilience And Educational Transformation After Incarceration, Robert L. Hudson

Graduate Theses & Dissertations

The purpose of this study was to examine how formerly incarcerated students make meaning of their higher education experiences as a means of navigating systemic barriers, fostering resilience, and reconstructing identity during post-incarceration reintegration. Existing scholarship on formerly incarcerated students in higher education emphasizes barriers, recidivism, and completion outcomes while paying limited attention to the subjective meaning making processes through which students interpret their educational experiences (Abeyta, 2022; Bozick et al., 2018; Donaldson & Viera, 2021). Formerly incarcerated learners have largely been positioned as subjects of inquiry rather than as knowledge producers about their own educational lives. This qualitative study …

Cross-Attention Mechanism For Medical Visual Question Answering, Nada Fadhil Mohammed, Israa H. Ali

Baghdad Science Journal

Visual Question Answering (VQA) is a machine learning task that aims to create systems capable of answering natural language questions based on given images. Medical VQA systems, a domain-specific application of VQA, assist in understanding clinically relevant information from medical images. These systems leverage deep neural techniques to generate accurate answers to questions, which can be closed-ended or open-ended. This paper proposes a Cross-Attention Mechanism-based Medical VQA system. The proposed Medical VQA system achieves good performance through the integration of three-key components, each addressing critical challenges in medical visual question answering: The biomedical domain-specific pretraining of BioBERT enables extracting powerful …

A Multi-Model Ensemble Framework For Assistive Image Captioning With Voice Interaction For The Visually Impaired Users, Alaa Noori Mazher, Ghadah K. Al-Khafaji

Baghdad Science Journal

Visual impairment greatly restricts an individual's ability for perception and interaction with the environment, making everyday activities challenging without the availability of appropriate assistive technologies. One major barrier is the inability to perceive visual scenes, which are essential for spatial awareness, wayfinding, and situational knowledge. This study aims to address this gap through the proposal of an intelligent assistive image captioning system specifically designed for visually impaired individuals. The system employs the best available computer vision and natural language processing techniques in generating context-oriented text captions for an image infused with interactive voice responses. Here, four models of Convolutional Neural …

An Informative Analysis Of Applying Feature Reduction Methods To Supervised Machine Learning Algorithms, Mustafa S. Abd

Baghdad Science Journal

Feature reduction techniques are fundamental to enhancing machine learning (ML) algorithms by reducing the number of features in a dataset. The study here explores the impact of Principle Component Analysis (PCA) on ML algorithms within an unbalanced classification framework, in partnership with feature selection techniques like Cluster Variation Attribute Evaluator (CVAE) and Correlation Attribute Evaluator (CAE). In addition, the research introspects a comparison analysis evaluating the effectiveness of several ML methods, including Multilayer Perceptron (MLP), Decision Tree J48, k-Nearest Neighbor (k-NN) and Sequential Minimal Optimization (SMO). The informative analysis of results signifies that the MLP technique with PCA minimized the …

Mandibular Landmark Determination Based On Statistical Features Of Panoramic Radiograph Images Using Multi-Output Neural Network, Nur Nafiiyah, Agus Harjoko, Kang-Hyun Jo, Rini Widyaningrum, Eha Renwi Astuti, Alhidayati Asymal

Baghdad Science Journal

The mandible is crucial in orthodontic treatment, forensic identification, and clinical diagnosis. However, manually identifying mandibular landmarks is time-consuming and highly dependent on expert skill, necessitating a more reliable automated prediction method. Previous research has used linear and nonlinear regression methods, in which each model predicts a single landmark point, resulting in inefficiency. In addition, these methods only use the centroid of the binary image of the mandible as input. This research proposes a multi-output neural network model that is able to predict multiple mandibular landmark points simultaneously. The proposed neural network architecture in predicting mandibular landmark points is 11 …

Montana Kaimin, April 23, 2026, Students Of The University Of Montana, Missoula

Montana Kaimin, 1898-present

Student newspaper of the University of Montana, Missoula.

Mechanism Of Improved Miscibility Of Co2–Oil Systems By Multiester-Headgroup Surfactants, Ning Xu, Yanling Wang, Baojun Bai, Yu Zhang, Wenjing Shi, Zhaonian Zhang, Wenhui Ding, Peixu Ma, Zan Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In the pursuit of carbon neutrality, the CO₂-enhanced oil recovery provides dual benefits by enabling both carbon sequestration and incremental oil production. However, its application is limited by high minimum miscibility pressure. CO₂-philic and oil-affinitive surfactants have emerged as an effective, low-dosage, and cost-efficient strategy to reduce the minimum miscibility pressure. In this study, macroscopic phase behavior experiments combined with molecular dynamics simulations were employed to systematically elucidate the influence of multiester-head surfactants on CO₂–oil miscibility. Using a modified pressure–volume–temperature apparatus equipped with optical power monitoring, we determined that multiester-head surfactants reduced the first-contact …

How Ai-Enabled Hiring Affects Organizational Health? Challenges And Future Direction, Shiza Hirani

Creating Healthy Work Environments (CHWE)

In today’s competitive landscape of hiring, organizations are responsible to not only maintain ethical integrity, ensure fairness, and protect job applicants' privacy, but also uphold a more data-driven and streamlined approach to save time per hire. The integration of Artificial Intelligence (AI) into the workplace presents opportunities such as enhanced productivity, efficiency, and creation of new roles. However, the widespread implementation of AI also raises ethical and privacy challenges that can deteriorate organizational health. AI-driven systems can inadvertently introduce biases and black box properties in hiring decisions which can erode trust and transparency, compromise employee privacy, and increase psychological stress …

Empirical Modeling Of Magnetic Braking In Millisecond Pulsars, Sophie Dore Vanderwaal

Honors Capstone Projects and Theses

No abstract provided.

Factors That Affect African American Representation In Cybersecurity Academic Programs In The United States, Damon Walker

Dissertations

The U.S. cybersecurity workforce continues to experience a critical talent shortage alongside persistent inequities in racial representation, particularly at the faculty level within higher education. This mixed-methods dissertation examines African American representation among faculty in cybersecurity academic programs designated by the National Centers of Academic Excellence in Cybersecurity (NCAE-C) and investigates the factors that influence recruitment, retention, and advancement. Grounded in a transformative research framework, the study integrates quantitative analysis of national institutional data with qualitative interviews to illuminate structural patterns and lived experiences shaping representation.

Quantitative findings revealed pronounced underrepresentation: African American faculty comprise 2.57% (130 of 5,051) of …

Spartan Daily, April 23, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 37

Predicting Telecom Customer Churn: A Statistically Validated Kpi Framework With Machine Learning And Revenue Impact Modeling, Moeez Islam Malik '27, Amy Ehinomen Eremionkhale

Student Research

This capstone project addresses a core business problem in the telecommunications industry: how to detect, measure, and prevent customer churn before it occurs, using a KPI framework validated by statistical analysis and machine learning. Applied to 7,043 customer records across 37 variables from a California-based telecom operator, the analysis integrates descriptive KPI computation, Pearson correlation analysis, chi-square tests of independence, and logistic regression churn prediction. The research confirms that customer tenure (r = −0.352, p < 0.001) and contract type (Cramér's V = 0.410, p < 0.001) are the dominant predictors of churn, and that a logistic regression model achieves AUC-ROC = 0.8307 — sufficient for proactive deployment. A 5-percentage-point churn reduction preserves $273,670 in annual revenue and $1.55M in customer lifetime value. The project delivers an integrated analytical framework, a predictive retention model, a 16-chart visualization suite, and a 12-page Power BI executive dashboard.

Llm For Clinical Named Entity Recognition: A Study On Rag With Pubmed And Umls, Apoorv Tripathi

Electronic Theses and Dissertations 2020 - Present

The first step of biomedical NLP is recognizing clinical named entities, which consist of identifying and categorizing a variety of clinical entities such as diseases, symptoms, genetics, diagnostic tests, procedures, etc. from a body of unstructured clinical text. This study presents a PubMed and UMLS based Retrieval Augmented Generation framework which improves the performance of the Large Language Models to identify clinical entities by providing context. In particular, the framework consists of a two-stage pipeline, where candidate tokens are identified from initial LLM-based classification and refined with retrieved context from either PubMed or UMLS. The proposed framework is assessed across …

Differentiable Objectives For 3d Scene Relighting Via Gradient Descent On Olat Basis Coefficients, Anson Savage

Theses and Dissertations

Designing effective lighting is an iterative and often time-consuming process. This work contributes to automatic lighting design research by presenting a render-engine agnostic optimization routine: gradient descent on RGB multipliers of one-light-at-a-time (OLAT) basis images. We compare several objective functions to accomplish lighting tasks and show that our method is capable of quickly and effectively exploring different lighting styles using either text prompts or reference images. We also present several datasets specific to lighting tasks and show that fine-tuning on these datasets can improve performance.

Advanced Studies In Characterization Of Pyrolysis Products From Live Vegetation, Mahsa Alizadeh

Theses and Dissertations

Fire is a naturally occurring element in many ecosystems which can have both positive and negative effects. However, in recent years the frequency of the fires and the area they affect has increased. The rapid spread of wildland fires coupled with the limited resources available to forest services to manage wildland fires highlights the urgency for accurate prediction of fire spread. Fire prediction models enable the fire management services to predict the spread of fire and prioritize firefighting efforts more effectively. Understanding reactions and mechanisms occurring during wildland fires improves the fire prediction models. During wildland fires, the biomass covering …

Re: Approval Letter For The Butte Priority Soils Operably Unit (Bpsou) Revised Draft Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System (Btl) Second Quarter 2025 (Dated April 10, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Optimization Of Pediatric Multidetector Ct Imaging Parameters Using A Machine Learning–Based Monte Carlo Simulation Model, Ali O. Masoud, Adithya Rajnaryanan, Khamis O. Amour, Ahmed M. Jusabani, Justin E Ngaile, Manoj Kumar, Mwingereza John Kumwenda Dr

Tanzania Journal of Science

This study utilized Monte Carlo (MC) simulations to optimize radiation doses in pediatric multidetector computed tomography (MDCT) head scans by analyzing key parameters like tube current (mA), tube voltage (kV), pitch, and slice thickness. The findings indicate that reducing tube current significantly lowers the Computed Tomography Dose Index (CTDIvol) and Dose Length Product (DLP), effectively minimizing patient radiation exposure. Higher pitch values (0.7–0.9) further reduced radiation by decreasing beam overlap, while using a thinner slice thickness (0.6 mm) improved dose efficiency. A comparison highlighted the effectiveness of optimization: simulated parameters kVp 100, mAs 81, pitch 0.98 yielded a CTDIvol of …

Optimizing K-Nearest Neighbor Based On Dragonfly Algorithm For Diabetes Retinopathy Classification, Ahmed Subhi Abdalkafor, Alaa Abdalqahar Jihad, Esam Taha Yassen

Baghdad Science Journal

The K-Nearest Neighbors (KNN) has been proven to be an effective method for addressing classification problems. The performance of the KNN algorithm is heavily dependent on the value of parameter K, which represents the number of nearest neighbors. Choosing an inappropriate value for K can affect the classification accuracy because a smaller chosen K can lead to overfitting and vice versa. So, the appropriate selection of the K value has a significant impact on the performance of KNN. Manually, adjusting the value of K is a very difficult process because the appropriate choices for this value depend on the status …

Editorial, Yuval Baruch

'Atiqot

Editorial

Spectator 2026-04-23, Editors Of The Spectator

The Spectator

No abstract provided.

Advances In The Design Of Bio-Organic Resistive Switching Memory, Muhammad Awais, Yi Sheng Wong, Feng Zhao, Kuan Yew Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

Bio-organic materials have garnered significant attention as sustainable candidates for non-volatile resistive switching memory (RSM) because of their specialized chemical, structural, and environmental advantages. This review presents a design-centered perspective on bio-organic RSM by outlining the key device components required for effective device engineering, including electrode materials, memristive thin films, intermediate layers, substrates, and electrical measurement strategies. Each component is discussed in detail with respect to the material properties and operational parameters that influence overall device performance, such as functional groups, interfacial interactions, and processing conditions. The review further analyses the critical roles of electrode pairing, interfacial chemistry, additive incorporation, …

A New Reinforcement Learning Agent Framework For Digital Image Forgery Detection Using Prioritized Experience Replay, Muthana S. Mahdi, Saad N. Alsaad, Hasanen S. Abdullah

Baghdad Science Journal

Digital image forgery detection has become an urgent and complex problem in an age when powerful editing tools can easily alter photographs. The familiar maxim ``a picture is worth a thousand words'' can no longer be taken at face value, since even subtle manipulations may conceal or fabricate critical details. Conventional detection methods frequently suffer from highly imbalanced datasets and narrow feature representations that fail to capture the diverse artifacts introduced by modern editing techniques. In response, this work presents a novel framework that casts the forgery detection task as a reinforcement learning problem, enabling an agent to learn a …

Kenyon Collegian - April 23, 2026

The Kenyon Collegian

No abstract provided.

Excavations At Jerusalem: The Byzantine Street (Area S2), Moran Hagbi, Joe Uziel

'Atiqot

This report presents the results of an excavation conducted on the northwestern corner of the City of David, between the Giv‘ati Parking Lot and the Ottoman walls of the Old City of Jerusalem. Six strata were exposed, spanning the Early Roman and Early Islamic periods. The main archaeological feature exposed was a section of a stone-paved street dating to the late Byzantine period. The street, previously exposed in other excavations, was a primary south–north artery running along the Tyropoeon Valley and linking between the City of David and the upper parts of Jerusalem. This street was likely an important route, …