Engineering Commons^™

From Cyclones To Cybersecurity: A Call For Convergence In Risk And Crisis Communications Research, Ann Marie Reinhold, Ross J. Gore, Barry Ezell, Clemente I. Izurieta, Elizabeth A. Shanahan

VMASC Publications

Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard types (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the “lessons learned” from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to academic disciplines at the detriment to the advancement of the field of risk communications research writ …

Age Of Information-Based Optimal Scheduling With Energy Cost Trade-Off For Smart Warehouse: A Deep Reinforcement Learning-Based Approach, Sandip Roy, Abhishek Bisht, Ashok Kumar Das, Sachin Shetty

VMASC Publications

Recent advances in the integration of high-speed mobile networks and real-time IoT devices have facilitated in building of smart warehouses, where a set of beacons and Internet of Things (IoT) devices (or source nodes) can monitor the status of various physical processes in a time-critical way. In real-time status monitoring systems, like smart warehouses, quantifying the freshness of the Internet of Things (IoT) data based on the age of information (AoI) metrics becomes quite crucial. As source nodes are battery-constrained, a balanced trade-off between AoI minimization and preservation of source node battery energy is essential. In this paper, in a …

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

Phase-Variation Microwave Resonator For Highly Sensitive Dynamic Sensing, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

High-precision dynamic sensing is critical in fields, such as industrial automation, structural health monitoring, and environmental sensing, where real-time responses to minuscule changes can prevent system failures or optimize performance. In this work, we introduce and demonstrate a phase-variation coaxial cable resonator (CCR) as a highly sensitive sensor for dynamic sensing applications. As a proof of concept, a prototype device based on a custom-designed CCR is thoroughly investigated for dynamic displacement measurements, as displacement is a fundamental quantity essential to numerous applications. The sensor consists of two components: a static CCR device and a movable conducting plate. As the conducting …

Adaptive Nussbaum Design For Nonholonomic Systems With Asymptotic Stabilization Against False Data Injection, Guilong Liu, Yongliang Yang, Weinan Gao, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses the stabilization challenges of nonholonomic systems under the threat of false data injection (FDI) attacks, which compromise the integrity of state information. A novel adaptive control strategy using Nussbaum-type gains is proposed to ensure the asymptotic stability of the closed-loop system while maintaining signal boundedness. The approach extends conventional Nussbaum designs to handle multiple unknown control directions. It integrates online learning mechanisms to mitigate the impact of FDI attacks. Additionally, adaptive backstepping and fuzzy-logic systems are utilized to approximate and compensate for unknown nonlinear dynamics. The methodology transforms nonholonomic systems into equivalent cascade structures to address inherent …

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper identifies and studies five match-tracking (MT) methods in the adaptive resonance theory (ART) literature and conducts a detailed comparative analysis of these in ARTMAP applications. We focus on model performance for each MT method with respect to time and space efficiency as well as classification accuracy. Experimental results indicate that one MT variant, used in ARTMAP applications for the first time in this work, provides significant improvements in computational efficiency: depending on the ARTMAP variant, it was able to achieve up to one order of magnitude reduction in both time and space requirements, albeit with a compromise in …

A Data-Driven Adaptive Control Approach For Enhancing The Dynamic Response Ff Vsgs In Varying Grid Conditions, Shah Fahad, Buxin She, Junjie Yin, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Conventionally, a virtual synchronous generator (VSG) is designed for islanded mode (IM) operation to meet specific operational requirements such as the rate of change of frequency (RoCoF). However, the operation of VSG designed for IM may not meet the operational and control criteria in grid connected mode (GCM) when the grid conditions vary. In addition, conventional VSG control technology does not consider the influence of the presynchronization scheme when connected to a weak grid, which degrades the RoCoF in IM. To overcome the aforementioned challenges, the proposed study presents a twin-delayed deep deterministic policy gradient (TD3) algorithm to improve the …

Performance-Based Approach To Characterize External Sulfate Attack For Reactive Powder Concrete, Umut Bakhbergen, Chang Seon Shon, Dichuan Zhang, Jong Ryeol Kim, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Reactive powder concrete (RPC) is a relatively new type of high-performance concrete, offering enhanced load-bearing capacity, mechanical strength, and durability. The enhanced microstructural density of RPC with the incorporation of reinforcing fibers significantly increases its resistance to durability challenges, particularly against external sulfate attack (ESA). However, conventional laboratory testing methods for evaluating the resistance of RPC to ESA are limited. Hence, a new performance-based approach was developed to evaluate the durability of RPC exposed to ESA. Expansion of nine RPC mixtures designed by Taguchi L9 orthogonal array method with four factors (steel fiber content, water-to-binder ratio (w/b), silica fume content, …

Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young

Williams Honors College, Honors Research Projects

It is not uncommon for most public spaces to offer Wi-Fi, while it is convenient and affordable, there are significant security risks due to its open nature. Rogue access points pose a security threat to many networks because they have the potential to bypass security measures and intercept traffic containing sensitive information. The attempt to formulate a method that one hundred percent guarantees the detection of a rogue access point has proven to be an intricate and complex problem for many to tackle, as there are numerous ways a rogue access point can be configured. This project aims to demonstrate …

Design And Development Of A Rapid Tensile Quench Rig, Tyler Jewell, Justin Naylor

Williams Honors College, Honors Research Projects

This report outlines the design process and implantation of a tensile quenching rig that incorporated forced convection and a frequency generator. When any metal is quenched, a vapor barrier forms around it. When this happens, it limits the heat flux that may occur until the barrier turns into just nucleate boiling. The vapor barrier acts as an insulator and causes the heat flux to fluctuate, causing uneven hardening which would limit the use of some materials. To combat this effect, we are trying to use forced convection, and something new, which is adding high frequency waves into the quenching process. …

Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a framework for real-time cognitive fatigue detection among shift workers using an integrated approach that combines photoplethysmography (PPG) data and reaction time analysis with advanced deep learning models, including Long Short-Term Memory (LSTM) networks and Feedforward Neural Networks (FNNs). The system leverages heart rate variability (HRV) and reaction time data to identify fatigue indicators. The results demonstrate significant performance, with the first FNN model achieving a test accuracy of 98.94% and a loss of 0.2928, while the second FNN model achieved the same accuracy with a slightly higher loss of 0.3089. The LSTM model, designed for sequential …

Guest Editorial, Li Ai, Xiao Tan, Arslan Akbar, Guirong Yan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Deep Learning For Computer Vision Applications In Medical Diagnostics And Wildlife Monitoring, Mostapha Al Saidi

Electronic Theses and Dissertations 2020 - Present

This dissertation explores innovative applications of deep learning and computer vision techniques across three distinct domains: medical imaging, dermatological diagnostics, and wildlife monitoring. The research addresses critical challenges in each field through the development and optimization of convolutional neural networks and other deep learning architectures.

The first study examines COVID-19 classification from X-ray images, comparing one-shot versus two-stage classification approaches using transfer learning with pre-trained models such as VGG16 and VGG19. The initial hypothesis was that breaking down the classification task into two optimized tasks would yield better results than one-shot classification. Results demonstrated that the single-stage approach achieved superior …

The Effect Of Huntington’S Disease On The Mechanical And Electrical Properties Of Red Blood Cells, Liliana Ponkratova

Electronic Theses and Dissertations 2020 - Present

Huntington’s disease (HD) has an impact on brain tissues and can alter the biochemical properties of the peripheral blood. Evidence in existing literature suggests that peripheral mutant Huntingtin protein may be involved and deteriorate HD. Red blood cells (RBCs), being the most abundant type of cells in the peripheral blood, can show detectable changes in their biophysical properties due to subtle changes in cell membranes. These changes can offer a minimally invasive means to track the progression of the disease. The transgenic line R6/2 is used as the disease model. Utilizing the electro-deformation spectroscopy, we measured membrane permittivity, cytoplasm conductivity, …

Movie Genre Classification Using Script Texts, Michael Roman Cuomo

Electronic Theses and Dissertations 2020 - Present

Genres are used to classify movies so that they can be grouped with others that have similar themes and structures. These classifications are categories created by humans. In the process of creating a movie, a script is often the first creation to write and share ideas about a topic. The script contains large amounts of text that is used to describe the dialog, setting and direction of the film. Although the script contains important information for the film, the amount of text can present a challenge for machine learning algorithms. Often in studies on film classification, if text is used, …

Innovative Biomechanical And Engineering-Based Assessments Of Hip Mechanics In Individuals With Hip-Related Pain, Holly M. Stanze

Theses and Dissertations--Kinesiology and Health Promotion

Individuals with hip-related pain exhibit altered movement patterns, and worse fear of movement (kinesiophobia), compared to asymptomatic controls. Exacerbation of hip pain during movement and the role of hip symptom duration may help further our understanding of specific movement patterns that are associated with hip-related pain. A better understanding of the potential connections between hip-related symptom duration, kinesiophobia, hip pain during movement, and lower limb mechanics in those with hip-related pain may allow for more efficient referrals to clinicians and lead to more effective rehabilitation. In addition, the impact of hip-related pain on intra-articular hip loading patterns is not well …

Utilizing Information Technology And Hands-On Learning Practices To Improve Student Learning Outcomes In A High Failure Rate Introductory Programming Course, Todd Edward Thomas

Theses and Dissertations

The purpose of this study was to introduce and examine the impact that two interventions have on a high failure rate introductory programing course: a pedagogical approach of introducing Live Coding instruction technique to the in-person lecture portion, and a technological approach of introducing remote collaboration software (VS Code Liveshare) to the online lab portion. This study used convergent parallel mixed methods approach for both data collection and analysis; utilizing four data collection methods: 1) online survey questionnaires 2) in-depth interviews 3) in class observations and 4) quantifiable data collection (ie., student demographic, IT experience, GPA data). The Live Coding …

Scalable Fabrication Of High-Payload Dendrimer-Based Nanoparticles For Targeted Atherosclerosis Therapy, Huari Kou, Lin Qi, Da Huang, Jiandong Wu, Honglan Shi, Hu Yang

Chemistry Faculty Research & Creative Works

Nanoparticle-based therapeutics hold promise for the treatment of atherosclerosis, but challenges such as low drug-loading capacity and a lack of scalable, controllable production hinder their clinical translation. Flash nanoprecipitation, a continuous synthesis method, offers a potential solution for scalable and reproducible nanoparticle production. In this study, we employed a custom-designed multi-inlet vortex mixer to perform cross-linking reaction-enabled flash nanoprecipitation, facilitating controlled and scalable synthesis of cross-linked Poly amidoamine (PAMAM) dendrimer nanoparticles. Notably, this approach allows simultaneous nanoparticle cross-linking and drug loading in a single step. The mannose moiety enabled specific targeting of macrophages via mannose receptors, enhancing the localization of …

Oxidation Behavior Of Silicon Carbide, Matrix Graphite, And Refractory Multi-Principal Element Alloy, Visharad Jalan

Doctoral Dissertations

"The present study focuses on the investigation of the oxidation behavior of silicon carbide, matrix graphite in a water vapor environment. It also examines the oxidation behavior of refractory multi-principal element alloys when exposed to air. The oxidation behavior of silicon carbide and matrix graphite were investigated in conditions pertaining to off-normal incidents in high-temperature gas-cooled nuclear reactors. Understanding this is crucial for the prediction of their performance in such accidents and ensuring that the nuclear reactor is accident tolerant. Upon exposure to water vapor, the two A3-based matrix graphite exhibited different behaviors. The A3-27 type showed oxidation in all …

Mitigating Frost Heave And Thaw Weakening In Roads Using Wicking Geotextile, Javad Galinmoghadam

Doctoral Dissertations

"Excess water is known to be the primary cause of soil and foundation problems. In cold regions, water-related problems are exacerbated by seasonal freezing and thawing cycles. Frost heave and thaw weakening is the leading cause of premature pavement failure and consume considerable budgets of the Department of Transportations in cold regions. The first step to designing mitigation measures is the ability to predict frost heave under different conditions. This study aims to introduce a new method for quantifying frost heave using a prediction model based on the state surface approach. This proposed model addressed many inconsistencies and limitations of …

Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …

Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Abstract: This study examines the impact of equipping a real heat exchanger in a slurry bubble column SBC on instantaneous and local heat transfer coefficients IHTC and LHTC, as well as the overall heat transfer coefficient U, employing advanced heat transfer techniques. The experiments were conducted in a 0.15 m inner diameter Plexiglas SBC with varying gas flowrates Ug (0.14–0.35) m/s at several radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74) and three axial locations (H/D = 2, 3 and 4). To simulate the industrial Fischer–Tropsch bubble column reactor FT-BCR, a real heat exchanger consisting of 18 …

Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody

Chemical and Biochemical Engineering Faculty Research & Creative Works

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 …

Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) can efficiently recycle waste PET, but achieving high conversion efficiency through smart reaction design remains challenging. To develop a robust and accurate machine learning (ML) model for the in-depth understanding and intelligent design of PET hydrolysis, we compiled a new dataset comprising 942 data points and comprehensive information of 44 variables involved in heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent (CS), phase transfer catalyst (PTC), and operational conditions. The developed Neural Network model demonstrated the best performance in predicting PET conversion, with a testing determination coefficient (R^{2 …}

Integrating Sustainability Into Aviation Training: Perspectives From Industry Professionals, Eva Maleviti, Sarah Talley

Publications

This paper is part of a broader research project aimed at identifying the most appropriate training materials, formats, and delivery methods for aviation sustainability content for future aviation professionals, starting from the early stages of their training. The current paper presents the data analysis and results of a short online survey targeting aviation professionals. Specifically, it provides preliminary data on sustainability perspectives from global aviation professionals. Through qualitative analysis, the creation of a baseline from a random sample of aviation professionals offers insight into their perspectives and how they could be influenced toward a more sustainable pathway. Additionally, the paper …

Lorawan-Enabled Iot Solution For Smart Farming, Talha Khan

Electronic Theses and Dissertations

The rising global demand for food, driven by population growth, alongside a declining rural workforce, presents a great challenge for agriculture. Precision agriculture, which relies on the widespread adoption of smart farming technologies, is anticipated to enhance agricultural productivity and sustainability. Emerging technologies, such as machine vision, artificial intelligence (AI), and the Internet of Things (IoT), offer innovative and promising solutions to address these challenges. This study focuses on LoRaWAN, a prevalent Low-Power Wide-Area-Network (LPWAN) IoT technology, examining its application in crop and livestock farming as well as its associated cybersecurity challenges. LoRaWAN IoT systems were constructed for three application …

3d Printing Of A Solid-State Battery, Maurizio A. Brozzi

Honors Undergraduate Theses

Solid-state battery research has gained significant attention in recent years, as it provides a unique solution for several common issues in conventional Li-ion batteries. Additionally, as additive manufacturing technologies continue to advance, they have the potential to fabricate solid-state batteries with new materials. The objective of this study is to explore the feasibility of 3D printing of a solid-state battery. By creating an initial PEO-PSF hybrid polymer matrix dissolved in DMSO and adding a lithium salt, the base electrolyte ink was formed. With the addition of conductive additives and active material, electrode inks were also produced. Super P was used …

Salinity Effects On Cu(Ii) Bioremediation By Chlamydomonas Reinhardtii Microalgae, Jennifer Hughes

Honors Undergraduate Theses

Microalgae offer a sustainable approach to wastewater treatment by removing pollutants such as excess nutrients, CO₂, and heavy metals. Among various species, Chlamydomonas reinhardtii shows strong potential in removing Cu(II) ions from wastewater. In addition, salinity stress in C. reinhardtii has been linked to morphological and metabolic changes that enhance lipid and phytochemical production. While salinity stress has been studied for enhancing biofuel production, its impact on microalgal removal of heavy metals, particularly Cu(II), remains largely unexplored. Understanding how varying salinity conditions affect both algal growth and the efficiency of Cu(II) remediation could provide critical insights for improving integrated wastewater …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …