Engineering Commons^™

Examining Physiological Responses To Misophonic Triggers, Christian O'Reilly, Xuan Yang, Sewon Oh, Doug Wedell, Svetlana Shinkareva

Faculty Publications

We collected and analyzed an array of biosignals (face electromyogram, skin electrodermal activity, peripheral temperature, and electrocardiogram) in 60 participants with and without misophonia, a condition characterized by decreased tolerance to innocuous sounds. Our goal was to objectively characterize the physiological response to misophonia triggering sounds. We found that misophonic responses can be objectively identified in some cases through atypical physiological reactions to triggering stimuli, though not all participants exhibited this response. Our analyses suggest a large interindividual variability in response to misophonic triggers and highlights the need for methodological adjustments in future experiments to increase the detectability of misophonic …

Removing Eog Artifacts From Eeg Recordings Using Deep Learning, Christian O'Reilly, Scott Huberty

Faculty Publications

The electroencephalogram (EEG) directly measures the electrical activity generated by the brain. Unfortunately, it is often contaminated by various artifacts, notably those caused by eye movements and blinks (EOG artifacts). Such artifacts are usually removed using an independent component analysis (ICA) or other blind source separation techniques. However, it is difficult to assess whether subtracting EOG components estimated through ICA removes some neurogenic activity. It is crucial to address this question to avoid biasing EEG analyses. Toward that objective, we developed a deep learning model for EOG artifact removal that exploits information about eye movements available through eye-tracking (ET). Using …

A Reliable And Efficient Detection Pipeline For Rodent Ultrasonic Vocalizations, Sabah Shahnoor Anis, Devin Mark Kellis, Kris Ford Kaigler, Marlene A. Wilson, Christian O'Reilly

Faculty Publications

Analyzing ultrasonic vocalizations (USVs) is crucial for understanding rodents' affective states and social behaviors, but the manual analysis is time-consuming and prone to errors. Automated USV detection systems have been developed to address these challenges. Yet, these systems often rely on machine learning and fail to generalize effectively to new datasets. To tackle these shortcomings, we introduce ContourUSV, an efficient automated system for detecting USVs from audio recordings. Our pipeline includes spectrogram generation, cleaning, pre-processing, contour detection, post-processing, and evaluation against manual annotations. To ensure robustness and reliability, we compared ContourUSV with three state-of-the-art systems using an existing open-access USV …

Synergistic Impact Of Entrained Air And Fly Ash On Chloride Ingress In Concrete Pavement: An Electrical Resistivity Model Approach, Youngguk Seo, Jin Hwan Kim

Faculty Articles

Ensuring the durability of concrete pavements against chloride ingress is critical, yet the relationship between electrical resistivity and chloride penetration remains underexplored. This study evaluates the effectiveness of entrained air and fly ash in mitigating chloride ingress using an electrical resistivity model and surface resistivity tests. Concrete samples with varying entrained air contents (0% to 10%) and Class C or Class F fly ash underwent three-year ponding tests in temperature-controlled indoor water baths and outdoor CaCl2-NaCl brine solutions. The results indicate that lower entrained air contents led to a more rapid increase in resistivity, with concrete mixes incorporating Class C …

Open Accessarticle Crystal Plasticity Modeling Of Dislocation Density Evolution In Cellular Dislocation Structures, Md Mahabubur Rohoman, Caizhi Zhou

Faculty Publications

The complex thermal cycles during the solidification process in metal additive manufacturing (AM) lead to the formation of high-density dislocation networks, organizing into submicron-scale cellular structures. These ultrafine structures are recognized as crucial for enhancing the mechanical properties of AM metals. In this study, we investigate the evolution of dislocation density within these cellular structures under plastic deformation and its impact on mechanical response using dislocation density-based crystal plasticity finite element (CPFE) modeling. The model incorporates the evolution of both statistically stored dislocation (SSD) and geometrically necessary dislocation (GND). Our simulations reveal that the yield and flow stresses of dislocation …

Editorial: Intelligent Robots For Agriculture -- Ag-Robot Development, Navigation, And Information Perception, Sierra N. Young

Civil and Environmental Engineering Faculty Publications

Agriculture is undergoing a paradigm shift driven by global challenges such as climate change, labor shortages, and the increasing demand for sustainable food production. In response, intelligent robotics are emerging as a transformative technology, enhancing agricultural efficiency, precision, and sustainability. This Research Topic, “Intelligent Robotics in Agriculture -- Ag-Robot Development, Navigation, and Information Perception,” highlights advancements in agricultural robotics, including breakthroughs in system design, autonomous navigation, multi-sensor fusion, and machine learning applications. The collected works contribute significantly to the evolving landscape of smart farming by addressing critical challenges in agricultural automation.

82 - Characterization Of Manganese Ferrites For Combined Mph/Mpi Treatments, Alana Canty, Robert Ivkov, Hayden Carlton

Undergraduate Research Symposium

Magnetic particle hyperthermia (MPH) is a form of cancer treatment in which cancer cells are made more susceptible to treatments, primarily radiation, through heating. The heat is generated from exciting magnetic nanoparticles (MNPs) within an alternating magnetic field (AMF)—nanoparticles which have been injected into a tumor—and both the heating quality and imaging quality of these MNPs are determined by their magnetic properties, with the primary one being anisotropy. Magnetic nanoparticles have been introduced as both a treatment option as well as a diagnostic tool through magnetic particle imaging (MPI). When used as a diagnostic tool, MNPs act as tracers to …

65 - Evaluating Drone-Based Stem Camps For Enhanced Engagement And Sel Development, David Morgan

Undergraduate Research Symposium

STEM camps are programs designed to promote exposure to learning associated with science, technology, engineering, and math educational outcomes. However, there is a significant gap in participation for Black and Brown individuals in STEM careers. This study seeks to understand how STEM programs during out-of-school time may support students from underrepresented communities and foster future interest in STEM-related careers. This study employs a retrospective qualitative research design investigating program participation in a week-long STEM camp in Hampton, Virginia. Thirty middle and high school students participated in the curriculum, technical drone skills, emphasizing emotional intelligence, self-regulation, and social awareness. These findings …

A Model Predictive Control To Improve Grid Resilience, Joseph Young, David G. Wilson, Wayne Weaver, Rush Robinett

Michigan Tech Publications

The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. This topic is of significant interest to utility power systems where distributed intermittent energy sources will increase significantly and be relied on for electric grid ancillary services. Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. In contrast, this article develops a comprehensive treatment of the construction of an MPC tailored to electric grids and then applies it …

Exploring Credit Loss For Engineering Transfer Students, Amy J. Richardson, David B. Knight

Inquiry: The Journal of the Virginia Community Colleges

One of the issues at the heart of transfer is the mobility of credits across institutions—moving credits from one institution to another is a crucial process for the transfer pathway to be a viable option. Credit loss is a critical issue for transfer students enrolled in highly sequential degrees, such as engineering. A student could be set back a year or more if they miss one required prerequisite course at the time of transfer. Determining who experiences credit loss in engineering could help ease the transfer process, improve graduation rates, and broaden participation in engineering since the transfer pathway has …

04.07.2025 Ored Connect, Liz Williamson

ORED Newsletter

New ORED Website Goes Live

Oxford Pitch Competition

Hughes Miller, Strategic Partnerships

An Effective Genetic Algorithm For Mixed Precision, Wanyu Zhang, Yu Shang, Min Tsao, Yiwei Li, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

The precision of floating-point numbers is a critical task in high-performance computing. Many scientific applications rely on floating-point arithmetic, but excessive precision can lead to unnecessary computational overhead. Reducing precision may introduce unacceptable errors. Addressing this trade-off is essential for optimizing performance while ensuring numerical accuracy. In this paper, we present a genetic algorithm-based approach for tuning the precision of floating-point computations. Our method leverages algorithmic differentiation and first-order Taylor series approximation to assess the impact of precision variations efficiently. We employ stochastic partitioning algorithms with multiple precision combinations that meet the error requirements. Moreover, we present a genetic heuristic …

From Adversarial Attacks To Robust Classifiers - A Study In Social Media Spam Detection - Black Box & White Box, Jonathan Jose Penaloza Rumie

Undergraduate Theses

Adversarial attacks pose a significant threat to the reliability of machine learning-based spam detection systems in social media. This undergraduate thesis, "From Adversarial Attacks to Robust Classifiers: A Study in Social Media Spam Detection – Black Box & White Box," systematically examines the impact of both black-box and white-box adversarial attacks on a range of spam classifiers, including Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Bagging, Gradient Boosting, and Support Vector Machines. Leveraging a novel dataset derived from Twitter spam messages and enhanced with adversarial perturbations such as synonym replacement and character-level modifications, this study evaluates classifier performance under …

40 - Design, Fabrication, And Installation Of Morphing Control Surfaces For Small-Scale Uas, Kyle Purser

Undergraduate Research Symposium

Morphing control surface technology, inspired by organic structures and compliant mechanisms, offers significant potential for enhancing the aerodynamic efficiency and performance of unmanned aerial systems (UAS). Despite these benefits, its adoption has been hindered by complexities in design, manufacturing, and installation, particularly when compared to traditional flap systems. This research explores the design, fabrication, and integration of morphing control surfaces for small-scale UAS using additive manufacturing techniques. To reduce costs and streamline the design process, fused deposition modeling (FDM) additive manufacturing was employed for component fabrication. An off-the-shelf Horizon Sport Cub S2 served as the testing platform, modified with a …

31 - Shaped Adversarial Patches, Huong Quach

Undergraduate Research Symposium

In recent years, the development and deployment of computer vision models have become widespread, with applications ranging from autonomous vehicles to security systems. Among these, object detection algorithms like YOLO are particularly significant due to their real-time performance and accuracy in identifying and localizing objects within an image. However, the robustness of these models is increasingly challenged by adversarial attacks, which are deliberate manipulations designed to deceive the model's predictions.

In this paper, I present an approach to advancing the deception capabilities of adversarial patches, specifically targeting YOLO-based person detectors. The objective is to design and implement shaped adversarial patches …

Neutrosophic Automata And Its Algebraic Properties, Anil Kr. Ram, Anupam K. Singh

Neutrosophic Systems with Applications

This research endeavors to elucidate the interrelationships among various classes of operators, including neutrosophic successor/neutrosophic source/neutrosophic core operators of neutrosophic automata based on neutrosophic resituated lattices. Furthermore, it delves into the characterization of algebraic properties such as neutrosophic subsystem, neutrosophic connectivity, and neutrosophic separability of a neutrosophic automaton using these operators. Finally, we study the concepts of neutrosophic primaries of the given neutrosophic automata using neutrosophic core operators.

An Approach For Hybridizing N-Subalgebra With Quantified Neutrosophic Set Using G-Algebra, Neha Andaleeb Khalid, Muhammad Saeed

Neutrosophic Systems with Applications

Neutrosophic sets are a generalized form of fuzzy sets as well as intuitionistic fuzzy sets, as they address the uncertainty factor as an independent component along with truthfulness and falsity. However, traditional neutrosophic approaches often struggle with effectively managing and quantifying indeterminate elements in complex algebraic structures. To address this limitation, this paper employs an expanded version of the neutrosophic set, incorporating a subalgebra. The proposed research is multifaceted: firstly, the new concept of N-Subalgebra (NSU) is proposed. This is the modified setting in the family of subalgebras whose proposed name is the representation of the author's initial name. Secondly, …

A Neutrosophic Micro Vague Correlation Measure: Application To Multi-Criteria Decision Making Problems, Vargees Vahini T, Trinita Pricilla M

Neutrosophic Systems with Applications

Statistical methods called correlation measures are employed to express the degree of association or relationship between two variables. The correlation coefficient which may be computed in a variety of ways is the most often used kind of correlation measure in many disciplines including biology, psychology, economics, and finance. Knowing the correlations between variables is essential for analysis and decision-making. This paper aims to commence a novel type of correlation measure called Neutrosophic Micro vague Correlation Measure and Neutrosophic Micro Vague Weighted Correlation Measure. Further demonstrates the implementation of the Neutrosophic Micro Vague correlation measure in the MCDM Problem. By adopting …

Improved Estimator For Population Mean Utilizing Known Medians Of Two Auxiliary Variables Under Neutrosophic Framework, Rajesh Singh, Shobh Nath Tiwari

Neutrosophic Systems with Applications

In the context of classical statistics, the estimation of the population mean is done with determinate, precise, and crisp data when auxiliary information is available. However, there are instances where dealing with uncertain, indeterminate, and imprecise data in interval form is required. To overcome this issue, Florentin Smarandache introduced neutrosophic statistics as a novel approach. This paper introduces a neutrosophic modified ratio-cum-product log-type estimator for the estimation of the population mean using known medians of two auxiliary variables in the neutrosophic context. The bias and mean squared error (MSE) for the proposed estimators are computed to the first-order approximation. The …

Enhancing Smart City Management With Ai: Analyzing Key Criteria And Their Interrelationships Using Dematel Under Neutrosophic Numbers And Mabac For Optimal Development, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

Purpose: This paper explores the transformative role of AI across various domains of smart cities, including urban mobility, energy management, public safety, healthcare, environmental monitoring, economic development, and data management. It aims to develop a novel decision-making framework that integrates AI technologies with a hybrid approach to analyze the interrelationships among smart city components.

Methodology: This paper employs a hybrid decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with single-valued trapezoidal neutrosophic numbers (STrNN). This approach is used to analyze the complex relationships among criteria and sub-criteria in smart city contexts, addressing uncertainty and incomplete information …

A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

One of the most powerful tools in graph theory is the classification of graphs into distinct classes based on shared properties or structural features. Over time, many graph classes have been introduced, each aimed at capturing specific behaviors or characteristics of a graph. Neutrosophic Set Theory, a method for handling uncertainty, extends fuzzy logic by incorporating degrees of truth, indeterminacy, and falsity. Building on this framework, Neutrosophic Graphs [9, 84, 135] have emerged as significant generalizations of fuzzy graphs. In this paper, we extend several classes of fuzzy graphs to Neutrosophic graphs and analyze their properties.

Mbj-Neutrosophic Structure Applied To Bp-Algebras: Bp-Subalgebras And Α-Ideals, Bavanari Satyanarayana, Shake Baji, Anjaneyulu Naik K.

Neutrosophic Systems with Applications

In this article, we introduce the concepts of MBJ-neutrosophic BP-subalgebras and MBJ-neutrosophic α-ideals in BP-algebra by applying MBJ-neutrosophic logic to algebraic structure BP-algebra. We prove that the intersection of two MBJ-neutrosophic α-ideals and the inverse image of an MBJ-neutrosophic α-ideal are also MBJ-neutrosophic α-ideals. Furthermore, we prove an MBJ-neutrosophic set is an MBJ-neutrosophic BP-subalgebra if and only if its level sets are BP-subalgebras.

Einstein Aggregate Operators Under Q-Rung Orthopair Fuzzy Hypersoft Sets With Machine Learning, Muhammad Gulistan, Muhammad Abid

Neutrosophic Systems with Applications

Thailand with its impressive 15.5% global share of renewable energy production, has a small 1% share of bitcoin mining. At the same time, the country is dealing with the severe effects of climate change, which emphasizes the necessity of taking proactive steps to solve environmental issues. This research integrates machine learning techniques and Einstein Aggregate Operators under q-rung orthopair fuzzy hypersoft set (q-ROFHS)-based multi-criteria decision-making technique to present a new method for analyzing CO₂ impacts and mitigation solutions in Thailand. We evaluate the environmental impacts of bitcoin mining and the incorporation of renewable energy sources using an interdisciplinary framework, …

Some Graph Parameters For Superhypertree-Width And Neutrosophictree-Width, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

Graph characteristics are often studied through various parameters, with ongoing research dedicated to exploring these aspects. Among these, graph width parameters—such as treewidth—are particularly important due to their practical applications in algorithms and real-world problems. A hypergraph generalizes traditional graph theory by abstracting and extending its concepts [77]. More recently, the concept of a SuperHyperGraph has been introduced as a further generalization of the hypergraph. Neutrosophic logic [133], a mathematical framework, extends classical and fuzzy logic by allowing the simultaneous consideration of truth, indeterminacy, and falsity within an interval. In this paper, we explore Superhypertree-width, Neutrosophic treewidth, and t-Neutrosophic tree-width.

Solving N-Players Continuous Differential Games Under Neutrosophic Environment, M. G. Brikaa

Neutrosophic Systems with Applications

Uncertainty plays a crucial role in decision-making problems, particularly in game theory. Various forms of uncertainty have been explored in the literature, including fuzzy, soft, rough, and interval-based approaches. Game theory has been extensively studied under these uncertainty models, with researchers addressing vagueness, and imprecision from multiple perspectives. More recently, neutrosophic sets have emerged as an alternative framework for handling uncertainty. Neutrosophic numbers effectively incorporate indeterminacy in decision-making by considering factors such as intuition, assumptions, judgment, behavior, evaluation, and preferences of decision-makers. This paper presents a novel approach to solving a new class of n-player continuous differential games within a …

Reconstruction From Variable Aperture Measurements Using Band-Limited Inversion Algorithms, Harrison C. Garrett

Theses and Dissertations

The signal reconstruction process from discrete samples is inherently band-limited due to the limited amount of spectral content in the discrete set of measurements. In the case of 1D sampling using ideal measurements, the maximum bandwidth of regular and irregular sampling is well known using Nyquist and Gröchenig sampling theorems and lemmas, respectively. However, determining the appropriate reconstruction bandwidth becomes difficult when considering 2D sampling geometries, samples with variable apertures, or signal to noise ratio limitations. Instead of determining the maximum bandwidth a priori, this thesis introduces the use of a bandlimited inverse to simultaneously reconstruct a signal and determine …

The Impact Of Visual Stimuli And The Properties Of Green Walls On Human Well-Being In Built And Immersive Virtual Environments, Alireza Sedghikhanshir

LSU Doctoral Dissertations

The built environment significantly influences human well-being, particularly in the context of stress recovery and cognitive restoration. This dissertation investigates the impact of visual stimuli, particularly green walls, on human responses related to stress, restoration, and thermal comfort. The research is guided by three primary objectives: (1) examining the role of visual stimuli and their properties in promoting stress recovery and restoration, (2) evaluating the potential of Immersive Virtual Environments (IVEs) as tools for delivering and studying restorative environments, and (3) investigating the influence of green walls on indoor environmental conditions.

A series of experimental studies were carried out to …

Wind-Resilient Solar: Harnessing Cfd For Enhanced Load Estimation, Aly Mousaad Aly

Faculty Publications

Solar panels are a cornerstone of renewable energy infrastructure, playing a pivotal role in global sustainability efforts. To ensure their resilience and long-term viability, accurate wind load estimations are essential for designing supporting structures, which account for nearly 50% of their total cost. However, traditional building codes lack comprehensive guidance for solar panels, resulting in inconsistent estimations due to discrepancies in scaled wall-bounded wind tunnel testing methodologies. These inaccuracies pose safety risks, increase costs, and hinder adoption. Emerging technologies like computational fluid dynamics (CFD) simulations offer a promising alternative by enabling full-scale analysis under realistic conditions of complete turbulence. This …

Advancing Solar Farm Resilience: Cfd-Driven Wind Load Optimization, Aly Mousaad Aly

Faculty Publications

This study investigates wind load design methods for ground-mounted solar panels and arrays by comparing Computational Fluid Dynamics (CFD) simulations with design standards. A case study of a solar farm impacted by Hurricane Maria examines the effects of elevation height, tilt angle, and variations in the American Society of Civil Engineers (ASCE) standards on wind loads and structural failure. Turbulence models, including Reynolds Stress Model, k–ε Model, and Large Eddy Simulation (LES), are used to analyze wind pressures, lift, drag, and peak pressures. Results show Phase 1 experienced higher wind loads than Phase 2 due to design differences. A cost-benefit …

A Neutrosophic Micro Vague Correlation Measure: Application To Multi-Criteria Decision Making Problems, Vargees Vahini T, Trinita Pricilla M

Neutrosophic Systems with Applications

Statistical methods called correlation measures are employed to express the degree of association or relationship between two variables. The correlation coefficient which may be computed in a variety of ways is the most often used kind of correlation measure in many disciplines including biology, psychology, economics, and finance. Knowing the correlations between variables is essential for analysis and decision-making. This paper aims to commence a novel type of correlation measure called Neutrosophic Micro vague Correlation Measure and Neutrosophic Micro Vague Weighted Correlation Measure. Further demonstrates the implementation of the Neutrosophic Micro Vague correlation measure in the MCDM Problem. By adopting …