Digital Commons Network^™

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …

Fixed-Time Consensus Tracking For Nonlinear Multi-Agent Systems Under Aperiodically Intermittent Control, Lei Xue, Tong Wu, Wenwen Jia, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article explores the problem of fixed-time consensus tracking (FT-CT) for nonlinear multi-agent systems utilizing the a periodically intermittent control (AIC) strategy. In contrast to existing control algorithms, the proposed algorithm utilizes the AIC strategy instead of the conventional continuous-time control strategy, effectively reducing the consumption of communication resources. Moreover, the problem of intermittent FT-CT is well handled by proposing the average control rate of the AIC strategy. Two theorems based on the cases of directed and undirected graphs are proposed, respectively. Finally, the validity of these results is confirmed through numerical simulations on a general nonlinear system and a …

Effect Of Process Parameters On Thermal Response Of An Oxy-Fuel Burner/Injector Panel In An Electric Arc Furnace Via Fiber Optic Sensors, Mobashir Ahmed, Rony Kumer Saha, Koustav Dey, Todd Sander, Jie Huang, Ronald J. O'Malley

Electrical and Computer Engineering Faculty Research & Creative Works

Modern oxy-fuel burner/injectors in electric arc furnaces (EAFs) play a critical role in scrap melting, liquid steel refining, and slag foaming. However, varying operational modes, combined with dynamic process conditions, such as arcing and slag behavior, can expose the injector panel surface to intense thermal conditions that can compromise efficiency and safety. Conventional monitoring techniques, including cooling water temperature measurements and thermocouples, fail to capture localized thermal anomalies due to their limited spatial resolution and susceptibility to electromagnetic interference. In this study, four high-resolution Rayleigh backscattering-based fiber optic sensors, interrogated via optical frequency domain reflectometry, were embedded in top and …

Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, …

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …

Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In the above article [1], a wording ambiguity appears in Proposition 4 regarding the description of the missing at random (MAR) mechanism. The published sentence states that the probability of observing the kth sample depends on the realized measurement value. This wording may be interpreted as dependence on the current unobserved value y[tk], which could suggest a missing not at random (MNAR) mechanism. The intended MAR mechanism is that the observation probability for the kth sample depends only on previously observed measurement information, such as y[tk-1], and not on the current unobserved value y[tk]. Therefore, the corrected wording clarifies that …

Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The design of package-level power delivery networks (PDNs) has become increasingly challenging as modern high-performance systems demand higher currents. Existing PDN design flows treat ball map assignment, stackup selection, and power plane routing as separate, largely manual steps, leading to long iteration times and limited scalability. This work proposes a unified and automated package PDN design framework based on multi-agent reinforcement learning (MARL). Each power domain is modeled as an agent, with specialized agents responsible for ball map assignment, routing layer selection, and power plane synthesis. A central controller coordinates agent decisions using a global reward that captures electrical and …

Enhancing Explainable Ai For Medical Imaging: Improved Lime Interpretation With Influence Mapping, Abiha Tahsin Chowdhury, Dhanush Bavisetti, Daniel B. Hier, Rahul Dubey, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

The integration of artificial intelligence (AI) into medical imaging is progressing rapidly. It is essential for these AI tools to be transparent, interpretable, and explainable to gain the trust of clinicians and regulators. Current state-of-the-art explainable AI (XAI) techniques in imaging includes Local Interpretable Model-Agnostic Explanations (LIME), Shapley Additive Explanations (SHAP), and Gradient-weighted Class Activation Mapping (Grad-CAM). Recent studies have shown that LIME often suffers from inconsistency and unreliability which limits their utility in sensitive fields like medical imaging. This paper proposes Influence Map based Explanation (IME), an enhanced variant of the original LIME framework, that aggregates multiple runs to …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …

Longitudinal Associations And Interactions Of Adolescent Religious Deidentification And Parental Sanctification On Parent-Adolescent Relationships, Justin Hendricks, Sam A. Hardy, Michael A. Goodman, Emily De Schweintiz Taylor

Faculty Publications

In many religious families, shared religious identity is a strong source of intergenerational solidarity. However, when adolescents deidentify from their family faith, normative parent-adolescent conflict, which heightens in mid-adolescence and normally subsides in late-adolescence, may intensify and damage parent-adolescent social cohesion. Many religious parents view parenting relationships as sanctified, which typically leads to adaptive parenting, but in the context of deidentification may lead to greater distress. To understand how adolescent religious deidentification influences parentadolescent relationships, we examined the longitudinal associations and interactions of adolescent children’s religious deidentification and parental sanctification on parent-child religious conflict and parental warmth (N = 1,391 …

Developmental Themes Associated With Religious Activity After Early Return From A Latter-Day Saint Mission, Samuel E. Hancock, Sam A. Hardy, Michael Goodman, Camron Angell, Jenae M. Nelson

Faculty Publications

In the Church of Jesus Christ of Latter-day Saints, qualified young men are expected (and young women are given the option) to complete extended missionary service during the transition to adulthood. Some youth end their missionary service short of the anticipated duration, which is associated with markedly lower rates of religious activity post-return. This study is a qualitative inquiry into the developmental themes associated with early returned missionaries from the Church of Jesus Christ of Latter-day Saints who chose to remain active (be consistently involved with the church), sampling from areas with high rates of Latter-day Saint activity, where stigmatization …

A General Algorithm For Assortment Optimization Under Random Utility Choice Models, Tien Mai, Andrea Lodi

Research Collection School Of Computing and Information Systems

This work concerns the assortment optimization problem that refers to selecting a subset of items that maximizes the expected revenue in the presence of the substitution behavior of consumers specified by a random utility choice model. The key challenge lies in the computational difficulty of finding the best subset solution, which often requires exhaustive search. The literature on constrained assortment optimization lacks a practically efficient method that is general to deal with different types of customer choice models (e.g., the multinomial logit, mixed logit or general multivariate extreme value models). In this work, we propose a new approach that allows …

Integrating Symbolic And Waveform Music Into Large Language Models, Teng Tu, Xiaohao Liu, Yunshan Ma, Ji Qi, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Music, as a unique and integral element of human life, is characterized by its complex structures, intricate details, and the fusion of multimodal information. Recent study advance music understanding by leveraging knowledge and reasoning capabilities derived from Large Language Models (LLMs). However, they often lack compatibility and fail to fully utilize the complementary strengths of diverse representations (e.g., ABC, MIDI, Waveform). To address these limitations, we propose a unified music-language model framework, named UniMuLM, transitioning from single-representation approaches to the integration of multiple music representations for LLM. Unifying different music representation formats poses challenges such as patch integrity and boundary …

Decentralized Linear Solvers: Communication Cost And Privacy, Nelson G. Brasil, Vinay A. Vaishampayan

Publications and Research

We consider the problem of multiple parties iteratively solving a system of linear equations in a decentralized manner. Specifically, we solve for $\negr{x} \in \R^n$, the $n \times n$ system of linear equations $M\negr{x} = \negr{b}$ when each party only knows their row of the matrix $M$ and a single component of $\negr{b} \in \R^n$. Our objective is to determine the tradeoff between the accuracy of the solution and the total communication cost measured in bits. A fully connected, reliable mesh network is assumed to connect the different parties. We develop a general formulation that applies to a large class …

The “Green Persuasion Effect” Of Negative Messages: How And When Message Framing Influences Tourists’ Environmentally Responsible Behavior, Xuehuan He, Chengzhi Ye, Songshan Huang, Lujun Su

Research outputs 2022 to 2026

Tourist activities may harm the environment, making tourists’ environmentally responsible behavior particularly important in tourism research. This research investigates the persuasion effect of message framing in environmental protection reminders on environmentally responsible behavior. Through five studies employing both field and controlled experiments and different measures of environmentally responsible behavior across varied tourism scenarios, we demonstrate that negatively (vs. positively) framed messages more effectively increase environmentally responsible behavior. Specifically, negatively framed messages are more effective in enhancing tourists’ environmental awareness, which triggers more environmentally responsible behavior. Furthermore, we identify social class as a moderator of message framing effectiveness, showing that negatively …

Can Environmentally Friendly Hotels Lead Customers To Green Behaviors? Evidence From The Stimulus–Organism–Response Model And Social Cognitive Theory, Saeid Nosrati, Mohtaram Rabbani, Razieh Sharifipur Shirazi, Ilkay Yorganci, Niusha Talebzadeh, Negin Bassirat

Research outputs 2022 to 2026

Purpose Using the stimulus–organism–response model and social cognitive theory, this study aims to examine how environmentally friendly hotels influence customers’ green patronage intention and green word-of-mouth. The study explored the mediating effects of hedonic value and utilitarian value and the moderating role of environmental concern. Design/methodology/approach Data were collected from 200 customers of environmentally friendly hotels in Iran and analyzed using structural equation modeling (SEM) with Mplus (version 8.3) software. Findings The results indicate that environmentally friendly hotels positively influence hedonic and utilitarian values, as well as green patronage intention and green word-of-mouth. Additionally, hedonic and utilitarian values partially mediate …

Master's Recital: Anna Godtland, Anna Godtland

Dissertations and Theses @ UNI

The two purposes of this recital are to partially fulfill the requirements for the Master of Music degree in Jazz Pedagogy and to display proficiency on the drum set, piano, and string bass. Anna Godtland presented her graduate recital on April 27, 2026, at 7:30 PM in Bengtson Auditorium. The recital program included two pieces each on piano, drum set, string bass, and four pieces on trombone. These selections showcased an array of styles and required a variety of skills necessary to fulfill the requirements of the Jazz Pedagogy degree. The recital featured personnel from two UNI jazz combos (Cincopatos …

Echoes Of The Nation: Janáček, Bartók, And The Articulation Of Central European Identity In Opera, Elyse Morris

Dissertations and Theses @ UNI

This thesis examines how opera functioned as a medium for articulating and negotiating national identity in the final decades of the Austro-Hungarian Empire. Focusing on Leoš Janáček’s Jenůfa (1904) and Béla Bartók’s Bluebeard’s Castle (1911), it explores how composers employed dramatic structure, linguistic choice, and musical language to construct culturally specific forms of expression within a rapidly shifting political and social landscape. Drawing on approaches from musicology and cultural history, the study considers how operatic works not only reflect national identity but actively participate in its formation.

Through analysis of libretto, language, and musical style, this thesis demonstrates that both …

Examining Patient Safety Culture Trends In U.S. Healthcare Through A Multi-Year Analysis, Hassan Alabdullah

Graduate Studies Theses and Dissertations 2026

Patient Safety Culture (PSC) is recognized as a cornerstone of healthcare quality and a key determinant of patient outcomes. Despite the Institute of Medicine’s early calls to establish safety-oriented systems, evidence on the long-term stability of PSC in U.S. hospitals has remained limited. This dissertation addresses this gap through a multi-year evaluation of PSC using the Hospital Survey on Patient Safety Culture (HSOPSC v1.0) and advanced statistical methods. Drawing on one of the largest national datasets—comprising over 993,000 healthcare providers from 1,601 U.S. hospitals across three survey cycles (2013–2020)—the study employed a longitudinal repeated cross-sectional design. Analyses combined descriptive statistics, …

Rhetoric Of Opportunity: An Analysis Of Gullah Geechee Histories Through The Lens Of Counterstory, Xaria Arthur

Graduate Studies Theses and Dissertations 2026

Counterstory as a method/ology has been used in a variety of disciplines to share experiences of individuals and communities whose voices have been historically silenced or suppressed. Utilizing this methodological framework, my study shares the stories of six Gullah Geechee descendants with ancestral roots in the unincorporated community of Nesmith in Williamsburg County, SC. Treating these minoritized and individual stories as experiential knowledge, I trace the counterstories as topoi to introduce and develop the theoretical concept that I call the rhetoric of opportunity, which refers to memories or stories that have come to motivate individuals toward or away from …

The Uncanny And Uneasy: An Exploration Into Using Puppets To Share Dark Stories, Grace Auls

Graduate Studies Theses and Dissertations 2026

In this thesis, I will explore the role of puppetry and practical effects in evoking the uncanny and the uneasy as well as questioning the implications they have in dark theater and cinematic contexts. This paper will examine how puppetry and practical effects can contribute to potentially disturbing and dark imagery both on screen and in live theater. I will be focusing on looking at Jim Henson’s The Dark Crystal, as well as at different puppetry performances used in Voyage of the Little Mermaid (1992), Don’t Hug Me I’m Scared, Kirikou and the Sorceress (Kirikou et la Sorciere), and even …

Establishing And Testing Experiential Critical Theory (Ect), Dolores M. Batten Mrs.

Graduate Studies Theses and Dissertations 2026

There is a current gap in academia which has been largely overlooked in both pedagogy and assessment: the value of personal experience as key evidence of interpretation and meaning-making correlation. Aside from narrative writing, most current methods of literary analysis writing do not place a high value on personal experience beyond the inclusion of brief anecdotes. Yet experience is the major pathway by which an individual forms their worldview, which then informs the ways in which they interpret the world—and by extension, text. This dissertation both establishes and examines the use of Experiential Critical Theory (ECT) in pedagogical application for …

It's All The Same, Lauren A. Bedevia

Graduate Studies Theses and Dissertations 2026

It’s All the Same is a collection of short stories that center around lesbian characters. The stories explore themes such as ambition, morality, karma, mental health, exploitation, and relationships. The collection opens with “Forget Her Inc.,” a short story that juggles an ensemble cast of lesbians and examines whether memory eraser therapy is an ethical practice for treating a broken heart. “It’s All the Same,” the titular story, uses lyricism to present the parallels between two women in terms of family dynamics, interests, and attachment styles; the story explores a loving friendship between a lesbian and a straight woman.

“Fun …

An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat

Graduate Studies Theses and Dissertations 2026

Supply chain management has become increasingly critical as transportation costs rise and urban delivery systems place additional pressure on already congested networks. Last-mile delivery—the movement of goods from distribution centers to end users—represents the most expensive and operationally complex segment of the logistics process, particularly in underdeveloped megacities characterized by unpredictable traffic, limited infrastructure, and sparse real-time data. This dissertation proposes an integrated framework for optimizing last-mile delivery in such environments by combining social media–based traffic intelligence, machine learning, and deep reinforcement learning. The framework leverages unstructured, real-time data from social media platforms to enhance traffic prediction and incorporates these …