Digital Commons Network^™

Radiation Effects On The Amd Versal Running An Automatic Modulation Classification Model, Allan D. Howe

Theses and Dissertations

With the recent increase of interest into artificial intelligence (AI), graphics processing units (GPUs) have been used as the main hardware architecture for AI computation. Because of their high power consumption and large size, it is necessary to consider other architectures to perform AI computing in outer-space where size, weight, power, and cost (SWaP-C) are tightly constrained. One such architecture is the Advanced Micro Devices (AMD) Versal Adaptive Compute Acceleration Platform (ACAP), which can achieve acceptable AI throughput at a lower power and size compared to a GPU. As the Versal ACAP gets used in space applications, it is necessary …

Chemical Composition Stability Of Cu–Sn And Cu–Zn Journal Bechemical Composition Stability Of Cu–Sn And Cu–Zn Alloys Fabricated By Sand And Permanent Mold Casting With Nickel Alloying, Erwin Erwin, Didik Sugiyanto, Juan Pratama, Trisna Ardi Wiradinata, Abdul Rachmadhan, Muhammad Fikri Andika

Journal of Mechanical Engineering Science and Technology (JMEST)

The processes of moulding and reinforcing chemical elements have a big impact on the balance of chemical composition in copper-based bearing alloys. This has a direct impact on how well the material works. This study examines Cu–Sn alloys produced via sand casting and Cu–Zn alloys fabricated through permanent mould casting, with the incorporation of nickel, which remains uncommon. The objective was to examine the variations in the equilibrium of the chemical composition and the performance potential of the bearing alloy metal when subjected to different casting techniques and nickel concentrations ranging from 0% to 4%. Some of the methods used …

Developing A Natural Language Interface For Knowledge Graphs, Ruth Assefa, Sarah Mendoza, Luke Voinov, Oyku Serap Ogut, Nurcan Yuruk

SMU Journal of Undergraduate Research

This paper proposes to solve the challenge of making databases more user-friendly by interfacing them with OpenAI's ChatGPT-3.5 model. We implemented this solution to assist researchers in easily finding others with similar research interests. Our study involves 184 researchers from 14 departments at Southern Methodist University (SMU). We collected researchers' areas of expertise and biographies and stored them in a Neo4j graph database. We used OpenAI's embedding models to create vector representations of the collected data, allowing for accurate similarity assessments via Neo4j's built-in algorithms. By integrating this system with LangChain, we enabled natural language queries. The results demonstrated high …

Equivocation Analysis Across Continuous And Discrete Memoryless Channels, Md Munibun Billah

Theses and Dissertations

Physical-layer security uses the noise already present in the channel to keep a message secret without making any assumption about the eavesdropper's computing power. In Wyner's wiretap channel model, coset coding uses randomness to map the message to many codewords and protects against information leakage from an active eavesdropper. The secrecy provided by such codes is measured by their equivocation, which is the eavesdropper's remaining uncertainty about the message after she observes her channel. So computing equivocation is an important aspect of analyzing the wiretap channel model. Many channels of practical interest have no closed-form expression for equivocation, and exact …

Instructional Slides From Molten Salt Electrochemistry Symposium (Moses) 2026, Devin Rappleye, Carlos Mejia, Alex Peroff

Faculty Publications

This instructional slide set was developed for the 2026 Molten Salt Electrochemistry Symposium (MoSES) as an introduction and review of fundamental electrochemical concepts and methods used in molten salt systems. The material is intended for students, researchers, and practitioners seeking to better understand and interpret electrochemical measurements in high-temperature molten salts.

Topics include electrochemical thermodynamics, kinetics, mass transfer, electrode potentials, cyclic voltammetry, chronopotentiometry, chronoamperometry, square-wave voltammetry, electrochemical impedance spectroscopy (EIS), and common approaches for analyzing electrochemical data. Emphasis is placed on building physical intuition, understanding underlying assumptions, recognizing common experimental artifacts, and connecting electrochemical signals to real chemical and transport …

Transmogrifying Coding Into A Social Studies Technology Tool: Using Participatory Design With Engineers And Social Studies Educators To Design Data Visualization Tools For Social Studies Data Literacy Education, Bahare Naimipour, Jessica Zhang, Tamara Shreiner, Mark Guzdial

Journal of Pre-College Engineering Education Research (J-PEER)

Our work aims to inform, design, and create data visualization tools that are meant to be integrated specifically into social studies classes. In this essay we discuss the use of participatory design methods to learn what social studies teachers (both pre-service and in-service) want in their classrooms and test the usability of real tools with these participants. Through this approach we iteratively engage our users, and they inform the design and development of learning tools for the learning and instruction of social studies data literacy. Using a social construction of technology lens, we describe the scaffolding embedded in our tools …

Analyzing Energy Use In 2d & 3d Imaging Systems And Workflows, Michael J. Bennett

Published Works

This study examines energy consumption in cultural heritage imaging systems and workflows, addressing a gap in sustainability research that has to date focused primarily on data storage infrastructure estimations. Using Home Assistant edge computing and Z-Wave smart plugs, seven distinct imaging systems were monitored over 203 hours, capturing 55,211 images, and rendering 2,448 objects. Results show an average energy requirement of 11.1 Wh per object, with an annual total of 747 kWh for digitization activities. Findings highlight opportunities to reduce energy demand and improve efficiency, such as automating continuous light shutoff and optimizing postprocessing routines that support institutional sustainability goals …

Provocable Forgiveness In Noisy Brand--Consumer Systems:An Agent-Based Study Of Repeated Interaction, Tahere Ahmadiyan, Hamidreza Navidi, Behbod Keshavarzi

Northeast Journal of Complex Systems (NEJCS)

Repeated brand--consumer exchange is often treated as a managerial problem of loyalty, recovery, and trust. It can also be read as a small complex system: many local decisions about cooperation, retaliation, and forgiveness accumulate into market-level selection. This study uses that perspective to examine which relational rules survive when communication is imperfect. Eight canonical Iterated Prisoner's Dilemma strategies are translated into marketing archetypes and evaluated through round-robin tournaments, a six-level noise sweep, proportional-fitness ecological dynamics, and finite-population Moran invasion tests. The tournament leaderboard is calculated without same-strategy self-play, so that reported payoffs reflect inter-archetype competition rather than homogeneous self-coordination. At …

Privacy-Preserving Intrusion Detection For The Internet Of Medical Things Using Ensemble And Federated Learning, Theyab Alsolami

Electronic Theses and Dissertations 2020 - Present

The rapid proliferation of the Internet of Medical Things (IoMT) has transformed healthcare by enabling continuous monitoring, intelligent diagnostics, and data-driven clinical decision-making. However, this increased connectivity has significantly expanded the attack surface of healthcare systems, exposing sensitive patient data and critical medical devices to cyber threats such as intrusion and data exfiltration attacks. Ensuring both strong security and strict privacy preservation in IoMT environments remains a fundamental and unresolved challenge.

This dissertation investigates the design and evaluation of robust and privacy-preserving intrusion detection systems (IDS) for IoMT networks using advanced machine learning techniques. The research first examines the effectiveness …

Impact Of Asphalt Binder Chemical Composition On The Performance Of Asphalt Mixture., Sagar Parajuli

LSU Master's Theses

Asphalt binder is composed of four chemical fractions, namely, saturates, aromatics, resins, and asphaltenes (SARA). Binders with the same performance grade (PG) can exhibit different chemical compositions due to variability in crude oil sources and refining processes. The objective of this study was to evaluate how such chemical variations influence the mechanical performance of asphalt mixtures at high, intermediate and low temperatures.

Eighteen 12.5-mm nominal Maximum Aggregate Size mixtures were designed using two aggregate types (limestone and gravel), and three binder grades (PG 67-22, PG 70-22m and PG 76-22m), each from three different sources with varying chemical fractions. A suite …

Engineering Fsh-Cer T Cells To Enhance Response To Epithelial Ovarian Cancer, Nolan J. Beatty

USF Tampa Graduate Theses and Dissertations

Ovarian cancer remains a significant cause of cancer-related mortality, with epithelial ovarian cancer (EOC) being the most common subtype. Despite advances in treatment, the 5-year survival rate for late-stage EOC remains low due to factors such as tumor heterogeneity and an immunosuppressive tumor microenvironment (TME). This study investigates the therapeutic potential of chimeric endocrine receptor (CER) T cells engineered to express follicle stimulating hormone (FSH) in a syngeneic mouse model of EOC expressing follicle stimulating hormone receptor (ID8-FSHR). We compared two different co-stimulatory domains—CD28ζ and 4-1BBζ—in FSH-CER T cells and found that FSH-CD28ζ CER T cells exhibited enhanced cytotoxicity, proliferation, …

Case Study: Feasibility Of Creating A Simulated Mobile Data Center For Cross-Disciplinary Academic Programs, Stanley Mierzwa, Christoper J. Schultz, Iassen Christov, Michael Fagioli, Thomas Ikeda, Reinaldo Jaramillo, Giolian Sanagustin

Center for Cybersecurity

This case study examines the potential to envision, create, and deploy a simulated mobile micro data center solution that can be easily replicated and transported between locations and educational settings. The coined term for this solution is the Mobile AI-Centered Data Center (Mobile ACDC), which provides students with a platform to construct, in a hands-on fashion, such a solution and navigate the product to gain greater competencies and understanding of the components found in a data center. Instructor and student feedback assessments from the pilot classroom modules and laboratory experiential learning activities indicate that such a solution helps to improve …

Proceedings: Nownet Arts Conference 2019, Sarah Rose Weaver, Chris Chafe, Scott Oshiro, Margaret Schedel

Journal of Network Music and Arts

Proceedings of the 2nd Annual NowNet Arts Conference 2019 “Social Purpose in Contemporary Network Arts.” The conference was held November 7–10, 2019. The primary in-person site was the Institute for Advanced Computational Science (IACS), Stony Brook University. Satellite in-person sites included Center for Computer Research in Music and Acoustics at Stanford University, Edinburgh Napier University, Orpheus Institute in Belgium, and Electronic Studios at the Technical University, Berlin. More locations participated remotely via the internet.

Proceedings: Nownet Arts Conference 2018, Sarah Rose Weaver, Chris Chafe, Margaret Schedel, Min Xiao-Fen

Journal of Network Music and Arts

Proceedings of the NowNet Arts Conference 2018, “Network Music: Artistic and Technological Strategies for Public and Private Networks.” This was the first of the NowNet Arts Conferences, which have been held annually from 2018 to the present. The conference took place from April 19–22, 2018, at the Institute for Advanced Computational Science (IACS), Stony Brook University, and at multiple remote locations connected via the internet.

Comparing Text Score Strategies For Online Music Making, Craig Pedersen, Lindsay R. Vickery, Stuart James

Journal of Network Music and Arts

This paper investigates a range of approaches to using text scores in online and networked music performance, focusing on their alignment with strategies proposed by Wilson (2020) for aesthetic and technical approaches to networked music performance. Text scores, emerging from the experimental music movement of the 1960s, communicate musical ideas through words rather than traditional notation, taking instructional, allusive, and hybrid forms. Although there are many aesthetic and pragmatic approaches to text score composition, the temporal openness of many such works makes the medium well-suited to the latency-challenged practice of telematic performance. The study evaluates four text scores—Craig Pedersen’s July …

Listening Ahead Ever So Slightly, Chris Chafe, Mike Dickey

Journal of Network Music and Arts

This paper presents a novel packet loss concealment system called “Regulator,” designed for interactive network audio applications, particularly server-mediated “jam rooms” in the cloud, where large ensembles of musicians perform together synchronously. The system addresses the critical challenge of maintaining continuous high-quality audio output while minimizing latency penalties in unreliable network environments including Wi-Fi. The Regulator architecture combines four core components: a central Regulator class orchestrating packet loss concealment operations; a BurgAlgorithm class implementing maximum entropy autoregressive prediction to reconstruct missing audio samples; a Channel class providing per-channel independent modeling for multi-channel streams; and a RegulatorWorker class offering asynchronous processing …

Pulse Before Sound: Reimagining Presence And Liveness In Telematic Music Performance Through Midi-Native Collaboration, Matt C. Bray

Journal of Network Music and Arts

Telematic Music Performance heralds a new paradigm for human creativity, seeking to extend the practical limits imposed by physical co-presence and to permit the cooperative, simultaneous creation of music among geographically remote collaborators. This paper examines how MIDI-native interaction provides a structurally robust alternative to audio-centric telematic systems constrained by latency, bandwidth, and waveform fidelity. Drawing on practice-led research, including over 34 hours of documented improvisation across 91 networked sessions in the SHOALZ series—a longitudinal Telemidi performance research initiative (2022–2024)—the study examines how the Telemidi system employs MIDI as a primary substrate for remote musical collaboration by establishing a synchronized …

Editorial, Sarah Rose Weaver

Journal of Network Music and Arts

No abstract provided.

Cnkg: Harnessing Large Language Models For Cognitive Neuroscience Knowledge Graph Construction, Ali Sarabadani, Kheirollah Rahsepar Fard, Hamid Dalvand

Turkish Journal of Electrical Engineering and Computer Sciences

Textual resources are among the most valuable sources of information in cognitive neuroscience (CN) for understanding and investigating brain activity and cognitive processes. Extracting and constructing knowledge graphs (KGs) from these texts can facilitate medical research by providing deeper insights into neurological diseases and brain function. In recent years, the use of large language models (LLMs) in natural language processing (NLP) has become increasingly widespread, significantly enhancing the extraction of meaningful information from large volumes of text. This study proposes a novel approach for constructing and evaluating a specialized knowledge graph, termed the cognitive neuroscience knowledge graph (CNKG), from scientific …

Robust Variable-Gain Backstepping Control For Nonlinear Systems With Real-Time Application To Induction Motor, Fadi Alyoussef, İbrahi̇m Kaya, Ahmad Akrad, Rabia Sehab, Cristina Morel

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel variable-gain mechanism with a minimal number of tuning parameters to enhance the performance of conventional backstepping controllers for nonlinear systems while avoiding singularity and peaking phenomena. The proposed approach is simple, computationally efficient, and well suited for real-time implementation without imposing a significant computational burden. Its effectiveness is validated through real-time experiments conducted using a dSPACE DS1104 controller board and a 7.5-kW induction motor (IM). Simulation results demonstrate that the proposed controller outperforms the conventional backstepping controller. Robustness analyses under variations in stator resistance, load inertia, and viscous friction coefficient reveal substantial reductions in the …

Enhancement Of Nested Hexagonal Fractal Antenna Performance For Multiband Wireless Applications, Abdelbasset Azzouz, Rachid Bouhmidi, Mohammed Chetioui, Redouane Berber, Ahmed Jamal Abdullah Al-Gburi

Turkish Journal of Electrical Engineering and Computer Sciences

This work focuses on developing a compact multiband antenna to meet the growing demand for versatile and efficient radiating structures in modern wireless communication systems. A hexagonal fractal antenna is proposed and analyzed for applications such as mobile communications, WLAN, industrial, scientific and medical (ISM) bands, Wi-Fi, satellite links, radar systems, and military communications. By iteratively modifying the antenna geometry with larger hexagonal elements, the design enhances multiband behavior and improves key performance parameters including gain, S11, voltage standing wave ratio (VSWR), and radiation characteristics. The antenna is modeled using high-frequency structure simulator (HFSS)® and fabricated on a low-cost 0.8 …

A Revenue-Driven Approach For Enhanced Task Utilization In Vehicular Cloud Computing, Ashish Singh Saluja, Satyabrata Das, Sanjib Kumar Nayak, Sohan Kumar Pande

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicular networks support intelligent transportation through vehicle-to-roadside Units (V2R) and vehicle-to-vehicle (V2V) communication but face challenges from dynamic topologies, limited RSU coverage, and bandwidth scarcity, which impact service delivery and revenue. RDA-ITU addresses these challenges by integrating V2R and V2V paradigms to maximize RSU revenue, enhance service availability, and improve system efficiency. It dynamically allocates services based on real-time network conditions and vehicle mobility, leveraging V2V relays to optimize both RSU-direct and cooperative communication. Through extensive simulations, RDA-ITU significantly outperforms four baselines: RBSM, VVMM-U, VVMM-LW, and VVMM-MA. It achieves 81.1% higher total revenue, 154.8% more completed requests, and 103.6% higher …

Class-Aligned Frequency Augmentation Using Variational Mode Decomposition Forfew-Shot Image Classification, Leila Boussaad

Turkish Journal of Electrical Engineering and Computer Sciences

Few-shot image classification benefits from data augmentation, yet most existing methods operate in pixel space with limited control over spectral semantics. We introduce a lightweight, frequency-guided augmentation strategy based on Variational Mode Decomposition (VMD). Our method constructs an offline, per-class ModeBank by decomposing downsampled luminance patches and retaining midband modes that encode class-specific texture patterns. During episodic training, VMD is never executed online: instead, for each support image, a same-class midband mode is selected and blended using PSNR-targeted scaling with a luminance energy cap, ensuring perceptual consistency. The augmentation is fast, reproducible, class-consistent, and integrates seamlessly into standard metric-based pipelines …

Scalefusion: Hierarchical Feature Aggregation For Unified Multiscale Object Detection, Ayşenur Yaylaci, Berru Kaya, Mehmet Kiliçarslan

Turkish Journal of Electrical Engineering and Computer Sciences

Detecting objects across a wide range of scales, particularly small ones, remains a significant challenge in computer vision. Existing methods often improve small object detection at the cost of performance on larger objects or introduce significant computational overhead through external techniques like image slicing. This paper introduces ScaleFusion, a novel, unified, end-to-end object detection architecture designed to provide robust performance across all scales within a single model. The core of our approach is a hierarchical feature aggregation strategy structured like a tree. ScaleFusion processes an image by running a shared backbone network only on fine-grained patches at the lowest level …

Swindeitvit: A Soft Voting Vision Transformer Ensemble For Accurate And Explainable Solar Panel Fault Detection, Mahe Zabin

Turkish Journal of Electrical Engineering and Computer Sciences

Solar panels are becoming very essential in providing sustainable energy but they are usually affected by defects on the surface like dust, snow, bird droppings, physical damages and electrical faults which interfere with their performance. These faults must be identified accurately and in a timely manner to enhance energy efficiency, lower the maintenance cost, and supplement the traditional manual methods of inspection which are labor-intensive, time-consuming and subject to human errors in judgment. The most common methods, such as traditional CNNs and hybrid architectures tend to be less accurate, less explainable and cannot be properly evaluated to be deployed in …

Influence Of Altitude On The Energy Payback Time Of Grid-Connected Photovoltaic Systems: A District-Level Analysis In Himachal Pradesh, India, Aniket Sharma, Mohinder Singh

Al-Mustaqbal Journal of Sustainability in Engineering Sciences

This study presents a district-level assessment of the influence of altitude on the Energy Payback Time (EPBT) of grid-connected photovoltaic (PV) systems in the Western Himalayan region of Himachal Pradesh, India. Although several studies have examined photovoltaic performance under different climatic conditions, systematic evaluation of altitude-sensitive EPBT using a standardized PV configuration remains limited for mountainous regions. A uniform 14.82 kWp polycrystalline PV system was simulated for twelve district headquarters representing elevations from 360 m to 3025 m above sea level using PVsyst software and Meteonorm meteorological data. Annual energy output and EPBT were evaluated under identical system configuration and …

Contemporary Cybersecurity Challenges In Emerging Technologies: A Systematic Literature Analysis, Faztudo Languisse Prof

Journal of Cybersecurity Education, Research and Practice

The accelerating convergence of artificial intelligence (AI), the Internet of Things (IoT), cloud computing, blockchain, and quantum computing has fundamentally transformed the global threat landscape, introducing cybersecurity challenges of unprecedented complexity and scale. This systematic literature review synthesizes findings from peer-reviewed publications, institutional reports, and regulatory documents published primarily between 2020 and 2025 to provide an integrated analysis of contemporary cybersecurity challenges across five key emerging technology domains. The review identifies critical vulnerabilities inherent to each domain, documents the evolution of threat actors and attack methodologies — including AI-powered ransomware, adversarial machine learning, and harvest-now-decrypt-later quantum attacks — and evaluates …

Cybersecurity Governance Of Industrial Iot In Sub-Saharan Africa: Policy Gaps, Threat Landscape, And Lessons From Comparative African Contexts, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The rapid deployment of Industrial Internet of Things (IIoT) systems across Sub-Saharan Africa's extractive, energy, logistics, and agro-industrial sectors has introduced a cybersecurity challenge of growing urgency: industrial networks that were designed for operational efficiency are increasingly exposed to cyber threats for which neither the organizations nor the regulatory frameworks are adequately prepared. This article examines the cybersecurity governance of IIoT systems in a developing African economy, using Mozambique as a primary case study and drawing comparative lessons from South Africa, Rwanda, and Kenya. Through an integrative literature review and documentary analysis of national digital, cybersecurity, and industrial policies, the …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Direct Measurement Of Stem Position For Gas-Lift Valves While Flowing At High Pressure, Paulo E. Reitz

LSU Master's Theses

The present work challenges the idea of estimating the gas lift valves true dynamic stem position by providing an alternative capable of tracking the real stem position during flow tests. This is of interest for the improvement of performance determination tests and procedures that involve critical safety concerns, complex training and considerable investments, both in time and money. This scenario, together with the strong interest of industry for valve optimization and the scarcity of works available in literature, encouraged this study. An apparatus named Vision System was developed for tracking and measuring the stem position during flow tests. The developed …