Computer Sciences Commons^™

Roomiq, Po Kya, Eh Paw, Nicole Holt, Riley Lindsay

ATU Scholars Symposium

1. RoomIQ is a smart room scheduling system designed to replace the current booking process for Corley Room 230 at Arkansas Tech University (ATU). The existing system presents challenges in efficiency, accessibility, and real-time coordination. Our goal is to deliver a user-friendly, real- time coordinated reservation solution that improves both functionality and overall user experience. The system will operate on an iPad Mini mounted outside the room, allowing users to instantly check availability and reserve the space on-site. This provides a convenient solution for immediate scheduling needs. In addition, a QR code displayed at the entrance will allow users to access …

Blazewatch: A Web-Based Management System For Volunteer Fire Departments, Michael J. Heinzen, Locke G. Weisler, Hunter S. King, Ryan N. Williams

ATU Scholars Symposium

BlazeWatch is a web application developed for rural volunteer fire departments. Volunteer fire departments often rely on manual processes and paper records systems to manage district fire dues, emergency call documentation, and equipment tracking. These inefficiencies can increase administrative workload and reduce efficiency. BlazeWatch is a secure full-stack web application designed to streamline administrative management for volunteer fire stations while providing a public-facing interface for general department information as well as a way for users to pay their fire dues. The system is built using an Angular frontend and a .NET backend with Identity-based authentication to ensure secure access control. …

Memorra: A Mobile-First Reminder Application For Personal And Social Event Management, Aaron Ngo, Caden Cash, Asher Wise

ATU Scholars Symposium

Memorra is a mobile-first reminder application designed to help individuals manage important dates and social commitments in a secure and reliable manner. Many users—including older adults, students, working professionals, and individuals experiencing cognitive overload—struggle to consistently remember birthdays, anniversaries, deadlines, and other significant events amid demanding schedules. To address this challenge, Memorra provides a centralized platform for managing reminders and organizing events with timely push notifications. The system architecture employs Flutter and Dart for cross-platform mobile development, supported by Firebase services—including Firestore, Authentication, Hosting, and Cloud Messaging—for backend functionality, real-time data management, and notification delivery. Secure user authentication, encrypted data …

Moneyup: A Predictive Financial Management System For College Students, Isaiah J. Adams, Malaya E. Wilburd, Dan V. Le, Joshua P. Golden

ATU Scholars Symposium

College students often lack accessible tools that combine real-time financial tracking, mobile accessibility, predictive analytics, and secure system design, leaving many without structured insight into their spending behavior. MoneyUP is a full-stack financial management platform developed to address these challenges through a secure, data-driven budgeting system deployed as both a web application and a cross-platform Flutter mobile application. The system integrates the Plaid API in its Sandbox environment to synchronize simulated banking data for secure testing without exposing live financial credentials. Transaction data is processed and stored using Supabase with a relational PostgreSQL database structured to enforce normalization, referential integrity, …

Llm-Based Stock Sentiment And Market Intelligence Platform, Joshua Thrower, Andrew Pinkerton, Ian Duggan, Wyatt Lester

ATU Scholars Symposium

Financial markets increasingly react to social media discourse, yet investors lack tools to translate this unstructured commentary into measurable indicators. Platforms such as YouTube host extensive discussions about publicly traded equities, but extracting reliable sentiment trends from high-volume, noisy comment streams remains technically challenging. This project develops a stock sentiment and market intelligence platform that transforms YouTube comment data into aggregated sentiment indicators aligned to specific equities. Comments are mapped to equities using ticker specific keyword identification combined with contextual filtering to reduce false associations from ambiguous or off-topic mentions. The system assigns numerical sentiment scores to individual comments and …

Aiw26s: Applied Llms, Chengjie Zheng

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the concept of applied large language models (LLMs), focusing on how users can move from simple prompt-based interaction to building structured, repeatable AI-driven workflows. Participants explore how AI enables faster prototyping, lowers barriers to entry, and expands who can participate in building technology. Through a hands-on demonstration, attendees learn how to transform raw inputs into meaningful outputs such as summaries, key concepts, and actionable steps. The session emphasizes the importance of clear problem definition, iterative refinement, and critical evaluation when working with AI systems.

Fully Decentralized Hierarchical Federated Learning At The Edge With Post-Quantum Secure Communication, Tariq Qayyum

Thesis/ Dissertation Defenses

Federated learning (FL) enables collaborative model training without centralizing raw data, but deploying FL at scale in real edge environments remains challenging because iterative training and aggregation must operate over heterogeneous, resource-constrained, and often mobile devices with time-varying connectivity. Conventional hierarchical federated learning (HFL) partially mitigates communication cost by introducing fog/edge aggregation, yet many designs retain cloud-based global aggregation and cloud-centric coordination. This places wide-area network latency on the critical path of every training round, creates a single point of failure, and limits responsiveness as model sizes and federation scale grow. Moreover, moving coordination and aggregation closer to the edge …

Romance Scam Reporting And Support: Help-Seeking Timing, Trust, And Escalation, Ld Herrera

Research & Publications

Built on social engineering and identity deception, romance scams often create financial loss and distress. For victims, it can be difficult to know where to go, what information is needed, and what outcomes are realistic. This paper reports results from an anonymous survey of people who were targeted by or experienced a romance scam (completed surveys: n=386), focusing on (1) when and whether victims first reach out for help, (2) perceived difficulty and confidence in navigating support, (3) how trust relates to expectations of assistance, and (4) how loss severity relates to transfer-method complexity. When help was sought, it was …

Ai Exposure And The Future Of Work: Tasks, Skill Demand, And Education, Erik Vasilauskas, Michael Horrigan

External Papers and Reports

No abstract provided.

Ai Method For Classification Of Diagnosis Of Near-Infrared Breast Lesion Images, Kaiquan Chen, Fangyang Shen, Honggang Wang, Zhengchao Dong, Jizhong Xiao, Ming Ma, Afroza Aktar, Christopher Chow, Wenxiong Zhang

Publications and Research

In near-infrared optical breast lesion screening and diagnosis systems, high-speed four-dimensional scanners can dynamically acquire tens of thousands of lesion images within a five-minute period. Currently, manual computer annotation is required to generate standard samples from these scanned breast lesion images, a process that depends heavily on physicians with clinical expertise. On average, a single physician can annotate only approximately ten samples per working day. As a result, this process is time-consuming and labor-intensive, and the collected samples often suffer from low accuracy, large variability, and limited diagnostic reliability. Several AI-based annotation tools, such as QuPath, HALO AI™, and X-AnyLabeling, …

Department Portfolio Web App*, Phillip Suvacarov, Tommy Aitchison

Campus Research Month

Southern Adventist University’s School of Computing produces numerous course projects, capstones, and research papers each year, yet there is no centralized, public showcase for this work. Our system provides a structured submission workflow for current and former students, faculty approval to ensure academic quality, and moderated commenting and likes to encourage constructive engagement. We outline the content model, role-based access control, and review queue, and describe search, tagging, and media support (including PDFs, images, and code links). By making student work visible beyond the classroom, the portfolio supports recruitment, alumni relations, and employer outreach while strengthening the School’s scholarly community.

Improving User Experience And Functionality: The Redesign Of Sorora In React Native*, Katherine A. Arroyo, Oswin S. Shin

Campus Research Month

This project redesigned and extended Sorora, a safety-focused mobile application built in React Native. The original Android Minimum Viable Product (MVP) included location tracking, an SOS button, and a basic contact list, but the interface lacked clarity, and the feature set created friction during urgent situations. We improved the UI and UX using Nielsen's usability heuristics, reduced navigation complexity, and redesigned the emergency workflow for deliberate, fast interaction.

Redesigning A Fitness App Interface For Physiological Constrained Users*, Joseph E. Manzanillo

Campus Research Month

As fitness tracking converges with medical monitoring, inclusive design becomes a matter of health equity. This research utilizes a Polar Beat redesign to address exclusionary "sporty" aesthetics that can exclude 300 million colorblind users. Based in Human-Computer Interaction (HCI), the study implements WCAG AA standards and color-blind-verified filters to mitigate data loss during Situational Induced Impairment (SIID), when high-intensity exercise compromises cognitive and visual processing. By optimizing user journeys for Paralympic and geriatric archetypes, this work demonstrates that accessibility is the essential bridge transitioning mobile fitness apps into viable, inclusive instruments for clinical medical use.

A Strategic Roadmap For Assessing And Educating On Personal Cybersecurity Practices In Universities*, Ryan Lopez, Ysani Peña

Campus Research Month

Universities face a common cybersecurity threat: their own users. Although organizations may meet compliance standards and implement robust security infrastructures, the individual user remains the weakest link. This is particularly evident in higher education institutions, where both students and employees are frequent targets of cyber threats due to a lack of cybersecurity awareness. This paper proposes a strategic roadmap for assessing university student bodies and employee populations through cybersecurity domains that directly affect personal cyber hygiene awareness and practice.

Our proposed roadmap was validated in a U.S. university by using a domain-focused survey and simulated phishing campaigns. After the identification …

Sau Physical Activity Website (Paw)*, Lisbette Sanchez, Alberto Elizondo, Caleb Tenold, Evelyn Shtereva, Siegwart Mayr

Campus Research Month

Problem: Southern’s Physical Activity Website (PAW) used to track physical activity from students and faculty was no longer functional. Aside from unsupported API versions, there was also an issue with authorization and role assignments.

Solution: Southern’s Center for Innovation and Research in Computing (CIRC) adopted the assignment of restructuring a new web application to track physical activity. This project focuses on building a secure and scalable architecture that connects user devices, third-party fitness APIs, and a centralized database to support activity tracking, workout analysis, and fitness history. By combining modern web development practices with API integration and backend data processing, …

Towards Physics-Informed Neural Networks For Simulating Multiphase Geothermal Convection​*, Daniel C. Patton, Andrew Harrison Eno

Campus Research Month

Water and steam flow through porous rock, transferring heat via conduction and buoyancy-driven convection caused by density differences. Traditional numerical methods (finite-volume/finite-element) model this well but can become memory-intensive and unstable for long, high-detail simulations. This work demonstrates a Physics-Informed Neural Network (PINN) using a finite-difference approach within the NVIDIA PhysicsNeMo framework to simulate magma chambers in 2D. Tested on the Rio Pisco pluton in Peru, results are compared with the USGS HYDROTHERM model. PINNs learn from physical laws, offering accurate, flexible solutions with less data and development effort.

Mass-Imaging Computers Over A Network For Southern's Information Technology Office*, Zane C. Meyers, Nicolas R. Goslee

Campus Research Month

Our research was meant to save time for Southern's IT department by researching and documenting a way to mass image computers in batches at a time over the network. The poster includes a introduction to our project, the research and testing process, and the results and conclusions drawn from this.

Chat Component For Php Web Apps*, Linton W. Feitosa, Caleb N. Hoffman

Campus Research Month

Chat rooms are a common feature in much of today's software. While many web applications could benefit from them, developing individual chat implementations can be repetitive and time consuming. Furthermore, publicly available and integrable chat components are difficult to find.

We created a general-use chat component for PHP web applications using the Yii2 framework. Our component features chat rooms, asynchronous messaging, and contact management. It is widely applicable, customizable, documented, and can be easily extended by future developers.

The Cake Is A Lie: Hid Wireless Adapter*, Andrew J. Patton, Benjamin Chant

Campus Research Month

This project explores converting wired Human Interface Devices (HID) into wireless devices by creating an adapter. Devices without wireless chips or dongles are hindered when flexibility is required, creating electrical waste. Our solution consists of a Transmitter (TX) and Receiver (RX) device pair and is designed to wirelessly bridge USB input from an HID device to a target host.

Towards Smaller Artificial Neural Network Using Mean Compression*, Michael D. Burks, Matthew K. Chuhng

Campus Research Month

Artificial Neural Networks (ANNs) require substantial memory and computational resources, limiting their deployment on resource-constrained devices. Our contribution is a compression method using Mean Compression (MC) to reduce ANN size while preserving functionality and accuracy. MC consolidates connections with similar edge weights into meta-nodes with averaged values. Unlike traditional pruning that only removes connections among neurons, MC restructures networks by recomputing weights and creating meta-nodes. Additionally, unlike fixed pruning thresholds, MC uses flexible weight range patterns. Applied to multilayer perceptron (MLP), ANNs are made more accessible for deployment on constrained devices as proven in several experiments. Specifically, across five classification …

Code Visualizer: An Interactive Code Visualization Tool, Tadd Trumbull

Campus Research Month

Code Visualizer is a web-based, interactive algorithm visualization tool designed to help introductory computer science students develop a deeper understanding of array searching and sorting algorithms. Code Visualizer presents a step-by-step simulation environment built on a restricted Python subset, which allows students to observe array traversal, index manipulation, and algorithmic operations in real time. The tool features two learning modes: View Mode and Predict Mode. The underlying architecture utilizes a behavioral software design pattern called command pattern.

Spatial Future Ahead! Augmented Reality And Anticipated Life Consequences, Sergio Barta, Reto Felix, Chris Hinsch, Mahdokht Kalantari, Nina Krey, Philipp A. Rauschnabel

Marketing Faculty Publications

Purpose: This study explores how initial exposure to immersive spatial computing experiences using AR headsets generates lasting inspiration and shapes consumers expected long-term life consequences (i.e., enhancement of reality, perceived substitutability and social impact).

Design/methodology/approach: The study uses a time-lagged research design based on 148 first-time users of spatial computing devices (AR headsets). Respondents were interviewed once shortly after being exposed to AR and a few days later. Data is analyzed using partial least squares structural equation modeling (PLS-SEM).

Findings: Users' immediate “inspired-by” experiences predict increased “inspired-to” intentions days later. Such inspiration translates into anticipated consequences such as virtually customizing …

Adopting Artificial Intelligence: Cross-Sector Analysis Of Ai Adoption Risks, Brandon Saari, Yona Berger, Yanett Munoz, Alex Agnick, Paul Wagner, Robert J. Honomichl

Journal of Cybersecurity Education, Research and Practice

Artificial intelligence (AI) is rapidly being adopted across public and private sectors. This offers significant gains in efficiency, decision making, and access to information. At the same time, AI introduces complex risks related to cybersecurity, privacy, bias, transparency, accountability, and equity that existing governance and security frameworks do not fully address. This paper presents a cross-sector literature review and comparative analysis of AI adoption risks and mitigation strategies across four critical domains: the federal government, libraries, K–12 education, and healthcare. Drawing on peer-reviewed research, institutional frameworks, and policy guidance, the study identifies sector-specific challenges alongside shared systemic gaps, including insufficient …

Innovations And Applications Of Virtual Private Networks And Sustainable Security In Society 5.0 Libraries, Stella Chinnaya Nduka Dr., Adeyinka Tella Prof, Petros Dlamini Dr

Journal of Cybersecurity Education, Research and Practice

In order to improve digital resilience, privacy, and access equity in contemporary library environments, this study investigates the role of Virtual Private Networks (VPNs) in fostering sustainable cybersecurity within the framework of Society 5.0 libraries. It does this by looking at the latest developments, applications, difficulties, moral dilemmas, and tactical methods associated with VPN deployment. Using peer-reviewed journal articles, conference proceedings, white papers, and policy documents published between 2010 and 2024, a methodical approach to literature review was used. The literature that bridges the fields of cybersecurity, library science, and Society 5.0 concepts was the main focus of the review. …

The Intricate Dance Of Emotions And Psychophysiology: Unveiling The Secrets Of Microexpressions, Jaiteg Singh, Deepika Sharma, Babar Shah, Sukhjit Singh Sehra, Farman Ali, Irfan Hussain

All Works

Background: Emotion recognition plays a pivotal role in behavioral analysis, mental health assessment, and human-computer interaction. Micro-expressions, which are brief and involuntary facial movements, offer valuable insights into concealed emotions. However, validating micro-expressions remains a challenge due to their subtlety and short duration. This study aims to enhance the validation and classification of micro-expressions by integrating electromyogram (EMG) signals with facial action units (AUs). Methods: EMG data was collected using the EMG Muscle Sensor Module V3.0, interfaced with an Arduino Mega 2560 microcontroller. To ensure signal clarity, various data filtration techniques were applied to eliminate noise, motion artifacts, and baseline …

Cloud-Based Lightweight Spatiotemporal Deep Learning Sign Language Recognition Model With Digital Twin Avatar, Mohammed Zuhair Abduljabbar

Thesis/ Dissertation Defenses

This dissertation proposes a full framework for sign language recognition (SLR). This study introduces Meta AI concept and a cloud-based framework that integrates a spatial detection and recognition model for sign language alphabet, and a spatiotemporal Transformer model for word-level SLR. The framework design also integrates a 3D digital twin that acts as a sign language interpreter on real time enhancing user friendliness and human computer interaction with the system. The major focus is finding the balance between performance accuracy and computation complexity efficiency starting with the framework communication between AI agents and the SLR models and digital twin efficiency. …

Dna Barcoding Of Eight Freshwater Fish Species (Order Siluriformes) From The River Ravi, Pakistan, Hafiz Muhammad Ashraf, Hafiz Abdullah Shakir, Muhammad Irfan, Shaukat Ali, Chaman Ara, Noor Khan, Muhammad Khan, Abdul Qadir, Muhammad Zafar Saleem

Karbala International Journal of Modern Science

Pakistan's freshwater bodies host significant fish species, but molecular identification is still in its infancy, necessitating the use of morphological and molecular DNA barcoding techniques. The study confirmed the species of the order Siluriformes found in the River Ravi, Pakistan, using DNA extracted from muscle tissue, sequenced for the COI gene, and obtained accession and Barcode Index Numbers from GenBank and BOLD databases. In the BLAST search, identities ranged from 99.23–100% and 99.52–100% in the GenBank and BOLD databases, respectively. The study revealed that the Kimura 2-Parameter genetic distance increased from lower to higher taxonomic levels: within species (0.00%) < within genus (15.17%) < within family (19.77%). The study estimated average nucleotide differences (104.964) and nucleotide diversity (0.16099) but found Tajima's neutrality test to be statistically insignificant. The neighbor-joining tree displayed closely linked species under a node, whereas divergent species were grouped under distinct nodes. The COI gene-based DNA barcoding aids in Pakistan's fish resource inventory, monitoring, and management, providing valuable input for traditional methods.

Eco-Assisted Ultrasonic Synthesis, Characterization, And Electrical Conductivity Study Of Polyaniline/ Silica@Fe3o4 Q1 Nanocomposites, Ali Salim Shaway, Kholoud Dham Khamkheem, Jawad Kadhim Abaies, Athra G. Sager

Karbala International Journal of Modern Science

وفي هذه الدراسة الصوتية، أصبحت السيليكا المُنتجة بأكسيد الحديد (Fe₃O₄) ومركبات نانوية قائمة على البولي أنيلين مُطعّم بنسبة 5-15% من السيليكا المُعزز للحديد (Fe₃O₄). وأكملت نهائيا ماء أنيلين والمركبات العلمية المتنوعة الارتباط باستخدام تقنيات FT-IR وUV-Vis وXRD وSEM وTEM. وأحدثت نتائج XRD أن حجم جسيمات البولينج أنيلين الناي (PANI) يبلغ 55.5. مكثف هذا الحجم إلى 45.2 عند تطعيم بولي أنيلين بنسبة 15% وزناً من السيليكا المُغلفة بأكسيد الحديد (Fe₃O₄) مُحضّرة بطريقة جيدة بشكل جيد، مما يميل إلى التمدد بشكل ثابت في تشكيل المركب المتباين المنظم. ضاقت النطاق البصري من 3.2 إلى 2.5 إلكترون فولت مع زيادة نسبة المطعّم، مما يشير …

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

The Expanding Digital Border: Ai, Surveillance, And The Fight For Justice, James Chesser

Immigration and Human Rights Law Review

As artificial intelligence transforms the mechanisms of immigration control, the modern border has become a digital filter—one governed less by geography and more by code. This Article examines the legal, technical, and ethical implications of AI-driven systems now central to global border enforcement, including biometric surveillance, algorithmic risk scoring, and predictive profiling. It explores how states use these technologies not only to manage irregular migration, but to compete for global talent—constructing migration regimes that reward capital and compliance while eroding transparency, due process, and equality.

Through an international and comparative lens, the piece highlights the expansion of algorithmic decision-making across …