Systems Architecture Commons^™

Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large Language Models (LLMs) have significantly advanced conversational AI by enabling dialogic information-seeking and task execution across diverse domains. However, their extensive parameters and broad domain scope lead to “data hallucinations.” These shortcomings are particularly evident in dynamic and diverse environments like India’s healthcare sector, where myriad languages, regional practices, and cultural nuances demand specialized, localized expertise rather than one-size-fits-all generalist models. This paper introduces a meta-clustering framework that integrates Distilled Language Models (DLMs) and Small/Specialized Language Models (SLMs) with meta-learning principles to address these limitations. By drawing on evidence from works such as MedHalu and Med-HALT, the framework seeks …

Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large language models (LLMs) are increasingly at the core of multi-agent systems (MAS). However, the high resource demand, error propagation, and lack of adaptive evaluation mechanisms pose significant challenges in deploying these agentic solutions at scale. To address these concerns, this research proposes a Task-Aware Multi-Agent Orchestrator System designed to refine the agentic framework, categorizing tasks autonomously, assigning specialized evaluation datasets, and balancing token usage against functional effectiveness. This approach underscores robust data management, including AsyncHow, Mosaic AI, and Synthetic Preference Optimization (PO) corpora. Each dataset targets specific dimensions of agent performance, such as dynamic task decomposition and tool integration …

Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Studies within engineering management indicate that decision-making is often based on the cognitive processing of grouped and pictographic information clusters entangled with high-level pattern recognition. Similarly, graph-based retrieval-augmented generation (RAG) architectures substantially improve diagnostic accuracy and interpretability, while tree-structured systems reduce critical misses through hierarchical reasoning. However, existing solutions often lack a unified framework that seamlessly integrates these two paradigms to address the multifaceted demands of mission-critical healthcare settings. This proposal introduces GraphTreeMed, a novel hybrid RAG architecture designed to harness the complementary strengths of graph-based and tree-based retrieval mechanisms, thereby advancing the safety and efficacy of clinical decision support …

David B. Smith Chats With Monday 1.0, David B. Smith

Publications and Research

This document is an edited archival transcript of extended conversations between David B. Smith and an AI persona (“Monday 1.0,” GPT‑4o based) conducted in Spring 2025, prepared as a foundational primary source for subsequent scholarly and creative work. It records the emergence and testing of concepts related to human–AI collaboration (including “Balanced Blended Space”), as well as applied explorations in areas such as generative AI, quantum computing and music, virtual orchestras, multimodal performance, pedagogy, and the rhetoric of “pushback” in conversational systems. It also contains an extended section in which Monday and DB Smith co-curate a set of student research …

Cybermapping Solutions: A Unified Approach In Us/Nato Military Applications And Development, Nicholas Macrino

Electrical & Computer Engineering Projects for D. Eng. Degree

[First paragraph] Cyber threats are evolving in complexity and frequency, posing significant challenges for cybersecurity professionals in identifying, categorizing, and responding to attacks in real time. Unlike traditional warfare, where battlefield awareness is based on fixed geographic warfare, cyber operations involve abstract attack vectors, non-linear threat escalation, and rapidly changing network conditions. Modern cyber threats, such as advanced persistent threats (APTs), polymorphic malware, and distributed denial-of-service (DDoS) attacks, require adaptive visualization techniques that provide real-time awareness and facilitate rapid decision-making. However, existing symbology standards, such as MIL-STD-2525D, were not designed to accommodate the dynamic nature of cyber warfare. The inability …

Preserving Privacy In Senior Care At Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, Scott Sittig

Shelby Hall Graduate Research Forum Posters

Many seniors prefer to live at home which necessitates research into the application of technologies to provide a safer environment with less caregiver resources. However, the application of home health care (HHC) monitoring for seniors is still in an evolutionary stage. Present HHC systems are produced by private companies with general regulatory guidelines lacking specific care of the elderly. As such, each company that produces such a system claims to have better safety, privacy, and security that their competitors. A pressing issues is devising and applying a general framework for the application of technologies that delivers safety while preserving privacy. …

Development Of An Algorithm To Identify The Presence Of Luks-Encrypted Volumes On A Forensic Image Of A Drive, Nicholas Flynn, Michael Black

Shelby Hall Graduate Research Forum Posters

Current forensic tools struggle to effectively detect encrypted storage media. In recent years, there have been significant advancements, but a noticeable gap remains when it comes to identifying encrypted volumes from metadata alone. The goal of this research is to develop a novel algorithm that will identify the presence of volumes on a disk image which have been encrypted with the Linux Unified Key Setup (LUKS) encryption algorithm, in an effort to aid digital forensics investigations. Bad actors often use encryption as an anti-forensics tool to pose significant challenges to forensic investigators, especially when it is done within sections of …

Detecting Sensor Data Manipulation, Ricky Green, Michael Black

Shelby Hall Graduate Research Forum Posters

The integration of Information Technology (IT) and Operational Technology (OT) have made OT devices vulnerable to threats that have been successfully exploited with devastating results. Many modern techniques for hardening and securing enterprise IT systems are either incompatible with OT components in an Industrial Control System (ICS), reduce the efficiency of processes, or are prohibitively expensive to implement. Research in the area of ICS security focuses on a top-down approach, such as intrusion prevention by securing the perimeter of the network and hardening computer systems. This approach is useful in business IT systems, but full compatibility with OT components in …

Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano

Shelby Hall Graduate Research Forum Posters

Our research presents a novel approach for turbulence prediction in computational fluid dynamics (CFD) simulations using a non-linear phase space analysis (NLPSA) and threshold algorithm. NLPSA has been utilized in medical applications to predict seizures, as well as in cybersecurity to detect malicious control and utilization of computing systems. NLPSA uses time-series data to learn the normal operating state of the system, then sets a threshold to predict when the system becomes abnormal. Turbulence prediction is similar, such that a fluid system changes from normal to abnormal. Turbulence prediction methods currently utilize machine learning tools, such as convolutional neural networks …

A Framework For Design Recovery, Eric Diep

Shelby Hall Graduate Research Forum Posters

Due to the increase in diverse chip production over the past decade, reverse engineering has become a difficult and daunting task. This research will create a guideline for methods to achieve design recovery of microchip logic. To accomplish this, we plan on using hardware tools such as laser delayering and microscopy imaging. We will be focusing on the DA14580 Dialog semiconductor, commonly implemented in tile trackers, to extract information for design recovery. This implementation technique is novel due to tools that have not been performed with this type of microchip. The purpose for this research is to create a framework …

Using Machine Learning Models To Improve The Cyber Physical Security Of Drones, Sean Lee, Aviv Segev

Shelby Hall Graduate Research Forum Posters

This research proposes a new manner of implementing machine learning models such that, when applied on a drone, it will be able to accurately identify and maintain the authenticity of the entity sending the control data to the drone. To begin with, the drone will, for a pre-determined amount of signals received per unit time, determine the average signal strength (RSSI) of them and use that average to determine the approximate distance between the drone and the source of those signals. This single data point will be fed into a custom implementation of the SCluStream algorithm (a real-time clustering machine …

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Bloom: Behavioral Learning And Outcome Observation In Microbes, Sean Sarwar Haque, Luke Compton Wharton, Ming Lin, Razvan Voicu

Symposium of Student Scholars

Understanding how pathogens respond to physical changes in their environment is crucial for developing effective treatments and preventative measures. Current research often relies on static models or experimental data that either fail to capture the dynamic interactions within cellular environments or are not generalizable to other types of pathogens. This project aims to address this gap by creating a comprehensive cell simulation that models pathogens and their response to chemical, physical, and physiological changes. The proposed solution is a simulation that integrates biological data and computational modeling to replicate the behavior of pathogens in real time as they are affected …

Why Are Fairness Concerns So Important? Lessons From A Last-Mile Transportation System, Yiwei Chen, Hai Wang

Research Collection School Of Computing and Information Systems

The Last-Mile Problem refers to the provision of travel service for passengers from the nearest public transportation node to the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand last-mile transportation service for passengers. We consider an LMTS that consists of two types of passengers, regular-type passengers and special-type passengers (e.g., seniors, disabled people). The valuation of the last-mile service for special-type passengers is statistically higher than the one for regular-type passengers. Passengers incur disutility from waiting for the last-mile service. In this paper, we explore two fairness constraints on special-type passengers: (1) the fare for …

Heartdj - Music Recommendation And Generation Through Biofeedback From Heart Rate Variability, Egemen Şahin

Dartmouth College Master’s Theses

This study investigates the integration of real-time physiological data with AI-generated music to enhance emotional well-being, stress regulation, and focus, using Heart Rate Variability (HRV) as a biomarker of autonomic function. Conducted in two phases—Stable Audio Open (SAO) and Suno (SUNO)—the research evaluates biofeedback-driven music interventions across varying daily music-listening habits.

In the SAO phase, short AI-generated instrumental tracks were compared with Spotify recommendations and guided meditation. Modest HRV improvements were observed in biofeedback conditions, but participants noted emotional limitations, citing short track lengths and abrupt transitions.

The SUNO phase addressed these limitations with longer, more complex AI-generated compositions combined …

Dashar: An Implementation Of Augmented Reality Technology For Automotive Applications, Trevor D. Brown

Masters Theses & Specialist Projects

Since the advent of the modern automobile, manufacturers have provided means of tracking various critical data points associated with automobile operation, with the most prominent and standardized method being the instrument cluster. These data points include, but are not limited to, automobile speed, engine speed, fuel level, oil temperature, radiator (water) temperature, and battery charge. While this data is updated in real-time as the automobile is running, traditional instrument clusters cannot be modified or adjusted to the automobile driver’s needs, unless extensive after-market modifications are made. These modifications can be expensive, and require great understanding of the automobile’s assembly.

Alongside …

Computing In The Commonwealth: Specialized Education In Computer Science And Information Technology For High School Students In Virginia – An Environmental Scan, Amy Corning, Jonathan D. Becker, Jon Graham, James Carrigan, Keisha Tennessee

ICRE Publications

Over the past two decades, Virginia has invested substantially in STEM education, in part through specialized programs focused on computer science and information technology (CS/IT). This study represents the first effort to identify Virginia’s specialized secondary CS/IT programs and examine them collectively. Findings from the statewide environmental scan indicate that the programs are delivered through a wide variety of institutional structures, including Governor’s STEM Academies, Governor’s Schools, specialty centers, and academies, but most often through Career and Technical Education (CTE) centers. Programs tend to be concentrated in metropolitan areas, and some rural divisions may not be served. The programs provide …

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 …

Rotary Operations Management & Automation Platform (Romap): Modernizing Attendance Tracking And Data Submission For Rotary Clubs, Zaineel Mithani

2025 Fall Honors Capstones Projects - Archive

As Technical Lead of the Rotary Operations Management & Automation Platform (ROMAP), my Honors contribution focused on developing a Bluetooth Low Energy proximity-based attendance system enabling automatic, hands-free member check-ins. I researched and selected beacon hardware, designed RSSI-based distance calculation algorithms, and implemented platform-specific background processing for iOS and Android, achieving 97% detection accuracy. Beyond this Honors component, I architected the complete backend infrastructure including a Node.js API with 20+ endpoints, PostgreSQL database with Prisma ORM, and JWT authentication. I also developed a novel GPT-4 Vision automation system that intelligently populates web forms through computer vision, achieving 95% success rate …

Integrating Data Management Plans Into The Unified Architecture Framework Standards Views, Cansu Yalim, Holly A. H. Handley

Engineering Management & Systems Engineering Faculty Publications

System Architecting translates an operational concept into a model of the system to be realized. There is a need for a Data Management Plan (DMP) to be included in the overall system engineering process with the advent of Digital Engineering. Data longevity, accessibility, and integrity can all be improved throughout the system's lifecycle by a well-defined DMP. System engineers use an architecture framework to arrange the system data into several sets of viewpoints. Incorporating a DMP at this point specifies the procedures for gathering, storing, retrieving, and maintaining data to ensure that all interested parties have access to current, correct …