Digital Commons Network^™

Latent Class Patterns Of Medication Attitudes And Their Correlates Among Older Adults In The United States, Jiaming Liang, Min Ji Kwak, Mona Shirvani, Alexander Testa, Rafael Samper-Ternent, Zhigang Xie, Jack Tsai

Faculty, Staff and Student Publications

No abstract provided.

April 23, 2026, The Daily Mississippian

Daily Mississippian (all digitized issues)

No abstract provided.

April 23, 2026, James Madison University

The Breeze, 2020-

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia.

Cognition In Pair-Living Owl Monkeys: The Role Of Partner Affiliation In The Willingness To Cooperate To Solve A Cognitive Task, Aaron J. Mencia

Electronic Theses and Dissertations 2020 - Present

Cooperative problem-solving tasks, including the loose-string paradigm, require individuals to coordinate their actions simultaneously to obtain a shared reward. These paradigms have been used extensively to assess social cognition, behavioral coordination, and partner preferences across taxa. Although the loose-string paradigm has been widely tested, it has not been applied to pair-bonded, monogamous primates such as owl monkeys (Aotus nancymaae), which exhibit affiliative behaviors including food sharing and bi-parental care. Investigating cooperation in this species may offer some clarification on whether more stable social bonds are associated with cooperative and cognitive task success as compared to those observed in …

Exam Analysis: A Quantitative Approach To Software Pedagogy, Christopher Shepard

Theses

Software engineering exams serve as a tool for evaluating a broad range of skills in the classroom, including theoretical understanding, practical application, and process reasoning. Despite their importance, post-assessment analysis is often overlooked, and the absence of structured reflection by instructors can limit their effectiveness and mask patterns in student performance. By treating exams as data, educators can uncover trends that drive more effective teaching strategies, refine evaluation methods, and work to strengthen student support systems. We conducted a systematic analysis of existing exam data and administered a student survey to determine if student perceptions align with actual outcomes, asking …

Psychometric Analysis Of The German Version Of The Barriers To Healthcare Checklist-Short Form, Judith Peth, Nicole David, Sophia Duckert, Petia Gewohn, Daniel Schottle, Pascal Rahlff, Alexander Konnopka, Hannah Konig, Kai Vogeley, Christina Nicolaidis, Dora M. Raymaker, Holger Schulz

School of Social Work Faculty Publications and Presentations

Background: Autistic people face multiple barriers to health care. To recognize specific barriers in a standardized way, autistic people, health care providers, and researchers need a suitable measure. The Academic Autistic Spectrum Partnership in Research and Education successfully developed the Barriers to Healthcare Checklist— Short Form (BHC-SF). It remains unclear whether (1) a German version of the BHC-SF performs well in terms of psychometric properties and (2) the BHC-SF consists of multiple constructs (i.e., assessing structural validity). Methods: We created a translated and culturally adapted version of the 17-item BHC-SF and used it with 345 autistic people in Germany. Psychometric …

Aspects Of Urban Planning In Bet She’An-Scythopolis: A View From Rhometalkes’ Alleys, Benjamin Y. Arubas, Leah Di Segni

'Atiqot

Intercity roads, colonnaded and drained streets, agoras and forums of the Roman and Late-Antiquity city of Bet She’an-Scythopolis—all have been widely studied, producing an ample bibliography. Not so are alleys, although they must have served various functions as thoroughfares for foot traffic or in relation to the buildings that overlooked them. These buildings could have been domestic, commercial or public, causing the function of the alley to surely change accordingly. This paper is dedicated to the study of two such alleys, which existed solely amidst public buildings, and whose story can be told based on the results of excavations and …

Roads To The Holy City: An Integrated Archaeological And Spatial Analysis Of Access Routes Leading To Jerusalemin The Second Century Bce–Seventh Century Ce, Yosef Spiezer, Boaz Zissu, Yehiel Zelinger

'Atiqot

This study presents a comprehensive analysis of Jerusalem’s transportation network by integrating archaeological evidence from rescue excavations with Geographic Information Systems (GIS)-based spatial analysis and literary sources. Three distinct development phases were observed. In the Hasmonean and Early Roman periods (63 BCE–70 CE), roads primarily served Jewish pilgrimage and were accompanied by religious infrastructure such as miqwa’ot (ritual baths), water reservoirs and elaborate tombs reflecting Jerusalem’s sacred status. In the Middle and Late Roman periods (70–324 CE) systematic road construction followed the Jewish revolts, emphasizing military and administrative functions through straight, paved routes marked with milestones, including forts, watchtowers, water …

Eyes To The East: Round Watchtowers Overlooking The Roads Leading From The Jordan Valley To The Kingdom Of Israel In Iron Age Ii, Ron Be’Eri, Avishay Oz, Аlexander Wiegmann, Yael Widerker Hilu, Tzachi Lang

'Atiqot

A small, isolated round tower, dating from the Iron Age, was unearthed near the settlement of Poriyya, overlooking the Jordan Valley. This tower is discussed below together with other, similar Iron Age structures exposed in eastern Samaria, which were built along main roads in the Kingdom of Israel under the initiative of the rulers of the Omride dynasty. It is suggested that these towers commanded the Jordan River crossings and the Gil‘ad Mountains, controlling the routes ascending from the Jordan Valley to the key administrative regions of the Kingdom of Israel. The research presented below considers historical sources dating from …

Global Trends In Dietary Exposure To Polychlorinated Naphthalenes (Pcns): A Review Of Contamination Levels And Health Implications, Vhodaho Nevondo, Okechukwu Jonathan Okonkwo

Engineering and Technology Journal

Polychlorinated naphthalenes (PCNs) belong to a class of persistent organic pollutants that are structurally related to chlorinated dibenzo-p-dioxins, dibenzofurans, and other chlorinated biphenyls as a result of the presence of benzene rings in their respective structures. Additionally, they display high levels of persistence in the environment, bioaccumulative, and dioxin-like toxicities characteristics. Although the production and use of PCNs is either banned or greatly regulated in several countries around the globe, unintentional production in industrial thermal processes and legacy usage have resulted in the ubiquity of these compounds in the environment and the food chain. Several studies have shown various exposure …

Exploring The Dual Advising System For Students’ Success: A Developmental Advising Model, Louisa Godwyll, Eugene Kwarteng-Nantwi, Pious Jojo Adu-Akoh

Mid-Western Educational Researcher

This qualitative study explored the dual advising system for student success at a U.S. higher education institution. Research has indicated that approximately 40–60% of students enrolled in doctoral programs do not complete their doctoral degrees. High attrition rates have led some institutions to adopt a dual advising system, a form of developmental advising, to support doctoral students’ success. Creamer and Creamer’s (1994) developmental advising model served as the conceptual framework of the study. The model defines the first stage of advising as defining task, where advisors engage in teaching and utilize strategies to help students attain educational, career, and individual …

Memahami Tindakan Anti-Dumping Masyarakat Eropa (M.E.), Muhammad Ashri

Jurnal Hukum & Pembangunan

Abstract

Ex-04-142 Modeling Distress And Evaluating Chatbot Safety For Suicide-Related Social Media Texts, Rehma Razzak

C-Day Computing Showcase

This project addresses the urgent need for transparent chatbot safety evaluations amid rising concerns about AI-facilitated self-harm. Using public social media datasets, we simulate two tasks: (1) detecting suicidal ideation via emotion-based risk scoring, and (2) stress-testing a support-style chatbot against 888 high-risk prompts, including euphemisms and “for a story” framing. A multi-label classifier trained on GoEmotions feeds emotion profiles into a logistic regression model to generate suicidality risk scores. These scores guide a local chatbot built with Ollama’s llama3, which analyzes user messages and steers responses toward safe, empathetic behavior. Evaluation shows ~90% of replies were safe or supportive. …

Gc-178-191 Communication App: Ai-Assisted Aac Platform​, Alex Wills, Maryam Koya

C-Day Computing Showcase

The Communication App is an accessibility-focused mobile application designed to support individuals with speech impairments, strong or unrecognized accents, and neurodivergent communication needs. The system leverages AI assisted speech-to-text (STT) and text-to-speech (TTS) technologies to enable real-time and seamless communication between users.This project aims to bridge communication gaps by providing a customizable, adaptive platform that learns user speech patterns over time. The application integrates cloud-based services, secure communication protocols, and an intuitive user interface to ensure usability, performance, and accessibility.

Grm-174-228 Mitigating Prompt-Induced Variability In Llm Outputs, Crystal Tubbs

C-Day Computing Showcase

Large language models in enterprise settings often produce structurally invalid outputs when users communicate informally, creating silent failure modes that pass unnoticed in downstream systems. This study investigates how prompt variation alone impacts schema compliance and output reliability. We evaluate three architectures across two tasks and four prompt styles, isolating the effect of interaction style on model behavior. Results show that baseline systems achieve 100% compliance under structured prompts but fail completely under ambiguous and casual inputs. A minimal reliability pipeline consisting of generation, self critique, and schema validation restores 100% compliance across all conditions at a predictable computational cost.

Grp-03-141 Stress-Testing Parkinson’S Disease Screening: A Cross-Modal Analysis Of Drawing And Speech Models, Rehma Razzak

C-Day Computing Showcase

Medical AI systems are increasingly deployed in clinical settings, yet most published models report only clean accuracy, dataset details, and training procedures—while omitting security‑critical evaluations such as robustness to perturbations, adversarial vulnerability, and failure modes under realistic noise. This project addresses that gap by building a cross‑modal robustness assessment for Parkinson’s disease (PD) screening models across handwriting trajectories, speech‑derived acoustic features, and an LLM‑based preprocessing layer. Despite strong clean performance (visual subject‑level ROC AUC ≈ 0.99; audio ≈ 1.0), the visual pipeline proved highly brittle to realistic acquisition distortions. Downsampling and point‑dropout caused near‑chance collapse, while pressure noise and XY …

Grp-08-168 Diagnosing Faults In Electrical Power Systems Of Satellites, Jared Lasley, Nguyen Thi Binh Nguyen

C-Day Computing Showcase

Satellite systems cost hundreds of millions of dollars or more to launch. To be resistant to catastrophic failures (and total loss of investment), satellite systems are designed with redundant sub-systems and are further equipped with numerous sensors and other health-monitoring sub-systems. In this poster, we consider an approach to fault diagnosis based on probabilistic logic programming. In particular, we propose to use ProbLog to model and reason with the electrical power system (EPS) of a satellite. Once we model a system using (probabilistic) first-order logic, we can take the system state and any (unexpected) sensor readings, and through automated reasoning, …

Grp-180-147 Quantum Augmented Microgrids (Quam) Simulator, Nitin Jha, Prateek Paudel

C-Day Computing Showcase

Small modular nuclear reactors (SMRs) are redefining the energy generation landscape by enabling the deployment of modular, scalable, and pre-built power units that can be used to build distributed autonomous microgrids for critical infrastructure and burgeoning AI factories. Often, these microgrids are linked together to provide a resilient, decentralized power generation infrastructure. Consequently, the cybersecurity of microgrids is of critical importance. In this work, we propose a quantum augmented network framework for resilient microgrids. We integrate the ideas of secure quantum networking, quantum anonymous notification, and quantum random number generation to strengthen the integrity, confidentiality, and privacy of microgrid networks. …

Uc-135-129 Fishgame: Mobile Hyper-Casual Fishing Game, Lauren Rousell, Lisbeth Martinez, Jacob Portillo, Jacob Miller

C-Day Computing Showcase

fishGame is a strategy-driven hyper-casual mobile game that combines the accessibility of traditional mobile gameplay with the progression depth of a roguelike. The project was developed over a three-month period using Unity 6.3 and related production tools. Following the completion of an alpha build, testing was conducted through gameplay sessions and a detailed follow-up survey to gather feedback on player experience, clarity, and engagement. Results indicated that fishGame was well received, with players reporting low levels of confusion and strong replayability. These findings suggest a clear interest in mobile games that offer greater depth while preserving the immediacy and simplicity …

Uc-142-177 Multiplayer Spsu Tub Racing Video Game, William Pitts, William Urvan, Thomas Powell, Joshua Young

C-Day Computing Showcase

Multiplayer Bathtub Racing revives a well-known Southern Polytechnic State University tradition through a digital multiplayer experience built in Unity. The project extends a prior single-player tub racing game by adding online multiplayer

Uc-158-205 Scrappyfin — Ind, Simulated Digital Wallet &​ Fraud Detection Platform, Logan Davis, Dante Galvan, Zahaira Jordan, Avery Bracey, Chris Pham

C-Day Computing Showcase

ScrappyFin is an educational FinTech platform developed in partnership with The Home Depot to simulate a digital wallet system and demonstrate fraud detection techniques. Users can create virtual wallets and perform synthetic transactions in a controlled environment, enabling analysis of financial behavior without real risk. The platform combines rule-based logic with machine learning models to identify suspicious activity, such as unusual transaction amounts or patterns. An admin dashboard provides clear explanations for flagged transactions. ScrappyFin showcases how modern financial systems detect risk while serving as a practical learning tool for software engineering and data-driven applications.

Grp-125-144 Mapping The Affordances Of Human-Ai Interaction: A Large-Scale Text Mining And Statistical Analysis Of Llm Usage Patterns, Anil Vallepu

C-Day Computing Showcase

People increasingly communicate with AI for schoolwork, office tasks, and daily needs. This study investigates the affordances of human-AI interaction using modern text mining and statistical analysis on the WildChat-1M dataset of over 1.1 million real-world ChatGPT user conversation logs. We apply BERTopic to extract latent interaction topics, compute a probabilistic topic-document matrix P(T|D), and perform rigorous statistical testing including Welch’s T-test and ANOVA to compare affordance patterns between GPT-3.5 and GPT-4.0 Results reveal that creative writing, Coding, message drafting and many interesting topics are the dominant affordances, while a spatio-temporal trend analysis maps how interaction patterns evolve globally over …

Grm-134-128 Neurovision: Mapping Brain Signals To Language And Visual Meaning, Siri Yellu

C-Day Computing Showcase

NeuroVision presents a unified framework for mapping electroencephalography (EEG) signals to language and visual meaning. Extracting semantic information from EEG remains a fundamental challenge due to its low signal-to-noise ratio, high dimensionality, and inter-subject variability. To address these challenges, we propose a multimodal representation learning framework that aligns EEG signals with both textual and visual embeddings through temporal modeling, spatial brain-region decomposition, and contrastive learning. The framework integrates self-supervised pretraining with supervised multimodal alignment to learn robust and transferable representations. Experimental results demonstrate BLEU-1 of 0.1106 and ROUGE-1 of 0.1493 for EEG-to-text generation, alongside a 52% improvement in retrieval performance …

Gc-172-139 Detection Of Sms Spam Using Transformer Bert Model, Nathan Bonner, Zachary Kandell, Michael Hayes, David Quintanilla, Leon Greenberg

C-Day Computing Showcase

This project evaluates automated SMS spam classification by comparing traditional machine learning against modern transformer architectures. We built a Bidirectional LSTM (BiLSTM) baseline using TF-IDF feature extraction and NearMiss-1 undersampling to handle severe class imbalances. We then compared this against a fine-tuned Hugging Face Sentence-BERT model. Preliminary results show Sentence-BERT significantly outperformed the BiLSTM baseline (99.01% vs. 95.65% accuracy). These findings demonstrate that transformer-based embeddings offer a highly accurate, scalable solution for spam mitigation without relying on aggressive data undersampling.

Gc-154-201 Evaluation Of Generative Ai Responses To Pharmacy Prompts, Abrar Syed

C-Day Computing Showcase

Generative AI (GenAI) is increasingly used in pharmacy for drug information and decision support, yet accuracy remains variable. We systematically reviewed studies that reported full prompts and model responses to evaluate correctness across pharmacy‑relevant tasks. GenAI performed well on basic drug facts but was inconsistent for patient-specific recommendations and interaction checking, with occasional hallucinations. Findings support cautious, supplementary use in pharmacy practice and education.

Grp-0100-193 Are Tgnn-Based Intrusion Detection Results Trustworthy? A Dataset Audit And Evaluation Framework, Faysal Chowdhoury, Sait Suer, Yinning Zhang

C-Day Computing Showcase

Temporal Graph Neural Networks (TGNNs) have reported near-perfect accuracy in Network Intrusion Detection (NID). However, this research reveals these results are often artifacts of dataset flaws rather than genuine model capability. Through a systematic audit of five benchmark datasets, we identify critical issues: node identity leakage, feature extraction artifacts, train/test contamination, and temporal sparsity. We demonstrate that models often learn to recognize specific attacker IP addresses instead of generalizing attack behavior. We propose a standardized evaluation framework featuring leakage-aware relabeling and attack-aware chronological splitting to provide a more reliable basis for future TGNN-NID research.

Uc-164-215 Hootnest: Ai-Powered Ksu Student Assistant, Tabitha Washington, Aspen Steele

C-Day Computing Showcase

HootNest helps prospective Kennesaw State students get clear, reliable answers about college life. It is designed for students who may not have easy access to counselors, mentors, or campus visits. The chatbot allows students to ask the chatbot anything they need to know.

Ur-171-118 Aidflow: A Predictive Financial Aid Transparency System For Students, Chaathurya Nakkana

C-Day Computing Showcase

Students frequently experience delays and confusion regarding financial aid refunds due to unclear system statuses and lack of communication. This project introduces AidFlow, a predictive financial aid transparency system that translates complex financial data into clear explanations, predicts refund timelines, and provides actionable guidance. A rule-based model and system pipeline were developed to simulate real-world scenarios and improve student understanding and decision-making.

Gc-126-148 Allies Connect- Georgia's Nonprofit And Volunteer Coordination Platform, Molly Calhoun, Takeshia Banks, David Castro, Ryan Hanrahan, Tarik Davis

C-Day Computing Showcase

Georgia's nonprofit services face an issue of discoverability. While many nonprofits have the resources to help their community members succeed, they have trouble actually connecting to members of the community that need their support. Connecting with these resources is challenging for community members because their avenues of communication are spread across the internet. Some have their own websites, some have a Facebook page where they post events, some rely on word of mouth and fliers, and others rely on phone chains to keep their community members informed. This means that community members seeking support need to be able to access …

Toyon 68 - Full Issue

Toyon: Multilingual Literary Magazine

No abstract provided.