Digital Commons Network^™

Polarimetry Based Radar Estimation Of Extreme Rainfall: Case Studies, Bong Chul Seo, Witold F. Krajewski, James A. Smith

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The study evaluated radar-derived polarimetric rainfall estimates for extreme rain events that occurred in the Kansas City Metropolitan area in the United States. To derive quantitative precipitation estimates (QPE), we implemented two polarimetric algorithms based on specific attenuation (A) and specific differential phase (KDP), along with the reflectivity (Z) based one using data from two radars in the study area. The analysis to assess radar-rainfall estimates (R) utilizes ground observations from a dense network of about 170 rain gauges. Based on our analysis results, the two polarimetric estimates from R(A) and R(KDP) outperform the conventional estimation R(Z). R(A) appeared to …

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a unified framework for the safe and optimal control of heterogeneous quadrotor unmanned aerial vehicles (QUAVs) in formation, enabling multitask missions without requiring precise system dynamics. To address partial state observability, a multilayer neural network (MNN) observer is designed to estimate unmeasured states. Reinforcement learning (RL) is employed for optimal control utilizing an MNN ensuring adaptability. Barrier Lyapunov Functions (BLFs) are integrated into the RL framework to enforce safety by maintaining QUAVs within predefined constraints. An enhanced continual learning (ECL) method is proposed to improve the adaptability of MNNs. This method enables effective multitask learning while mitigating …

Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Structural Observability (SO) and Structural Monitorability (SM) are structural properties utilized to determine the state and fault-free operation of components, respectively, in a bond graph (BG) model. BGs enable qualitative system analysis, evaluating whether existing sets of sensors and actuators ensure Structural Observability (SO) and Structural Controllability (SC) without knowledge of parametric values. Furthermore, the analysis determines whether there are sufficient sensors available to identify component faults accurately. This work provides a framework for automated sensor placement in a multi-domain physical system while analyzing the SO and SM properties. The MATLAB Structural Analysis Toolbox (MATSAT) conducts sensor placement in a …

An Extendable Soft-Switched Step-Up Interleaved Converter Integrated With Voltage Multiplier Cells, Amir Hasan Babanezhad, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a multiphase high step-up interleaved converter is introduced, which ensures low-input current ripple, low-component currents, and voltage stresses. The proposed circuit guarantees ZVS operation for power switches and ZCS operation for power diodes, which significantly reduce converter switching losses and EMI emission and improve its efficiency. Therefore, its passive components volume can be reduced by using high switching frequencies. In addition, the interleaved technique reduces input current ripple and input filter volume and provides high-power density. High-voltage gain and low-voltage stresses on the components are also achieved due to the integration of the converter structure with the …

Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortex beams with helical phase fronts have immense potential to enhance data capacity due to the unbounded values of orbital angular momentum. Chip-scale platforms for producing vortex beams are of paramount importance for a variety of applications. On the other hand, 2D materials with unique optical properties are essential for developing multifunctional ultrathin photonic devices. Here, anisotropic and temperature-tunable second-harmonic vortex beam generation is demonstrated with ultrathin ferroelectric niobium oxide dichloride (NbOCl₂) fork holograms. The polarization-resolved Raman measurements are performed on the NbOCl₂ crystal to understand the anisotropic behavior of the Raman modes. It is demonstrated …

Optimizing Uav Swarm Deployment For Efficient Communication Signal Strength Alignment In Disaster Scenarios, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In disaster scenarios, establishing reliable communication infrastructure is critical, and unmanned aerial vehicle (UAV) swarms offer a promising solution as temporary base stations. This study models communication demand in disaster-affected areas by applying Gaussian kernels to building data, forming a spatial demand distribution. Signal strength is estimated using the normalized inverse Free Space Path Loss (FSPL) to account for realistic attenuation. To guide UAV placement, we extract high-demand regions from the demand distribution using a gradient-based thresholding method. Based on this information, we develop a greedy algorithm to iteratively position UAVs for optimal coverage in areas with the greatest communication …

Fast Demodulation Of Ofdr-Based Distributed Sensing Based On Enhanced Buneman Frequency Estimation, Zhaopeng Zhang, Bo Liu, Xiao Liu, Caiyun Li, Osamah Alsalman, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Aiming at realizing high-efficiency distributed strain sensing through optical frequency domain reflectometry (OFDR), this paper introduces a fast demodulation algorithm to determine strain-induced spectral shifts from coarse Rayleigh backscattering (RBS) cross-correlation spectra. The proposed approach employs an enhanced Buneman frequency estimation (BFE) algorithm, enabling direct spectral shift analysis across coarse signals. By applying this algorithm, the need for dense interpolation in the conventional cross-correlation demodulation process - typically required for a finer spectral sampling interval but at the cost of demodulation efficiency - can be eliminated. Both theoretical analysis and experimental investigation reveal the equivalence of the BFE and conventional …

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, …

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.

Keep Family Business Innovating: Revisit The Relationship Between Succession And Innovation From Ownership Succession, Yuan Chen, Weize Huang, Chevy-Hanqing Fang, Ling Chen

Business and Information Technology Faculty Research & Creative Works

This study examines how family owner-manager successors' ownership influences R&D investment in family businesses. Drawing on the socioemotional wealth (SEW) perspective, we theorize that successors with higher family ownership prioritize extended SEW, leading to stronger R&D investment, while those with lower family ownership prioritize restricted SEW, resulting in weaker R&D investment. Additionally, we explore how family dynamics—specifically, the number of family directors and asymmetric salary favoring family members—moderate this relationship. Our findings enhance the understanding of successor heterogeneity and its impact on innovation, offering insights for succession planning that support the long-term sustainability of family businesses.

A Tribute To The Life And Work Of Jess Chua, James J. Chrisman, Zhenyu Wu, Alfredo De Massis, Pramodita Sharma, Lloyd P. Steier, Franz W. Kellermanns, Josip Kotlar, Emanuela Rondi, Bingbing Ge, Chevy-Hanqing Fang

Business and Information Technology Faculty Research & Creative Works

Jess Chua was a leading scholar in the field of family business and a major contributor to Entrepreneurship Theory and Practice both as an author and editor. His significant contributions to the field were acknowledged by the Web of Science, which listed him among the world's most highly cited researchers in Economics and Business in 2017, 2019, and 2020. In this memorial editorial, we pay tribute to him by discussing his influence on the field through his academic work, mentoring, long-term collaborations with other scholars, and the kindness he and his wife, Eva Kan, showed to his colleagues and students.

Electrochemical Observation And Ph Dependence Of All Three Expected Redox Couples In An Extremophilic Bifurcating Electron Transfer Flavoprotein With Fused Subunits, Debarati Das, Wassim El Housseini, Monica Brachi, Shelley D. Minteer, Anne Frances Miller

Chemistry Faculty Research & Creative Works

Bifurcating enzymes employ energy from a favorable electron transfer to drive unfavorable transfer of a second electron, thereby generating a more reactive product. They are therefore highly desirable in catalytic systems, for example, to drive challenging reactions such as nitrogen fixation. While most bifurcating enzymes contain air-sensitive metal centers, bifurcating electron transfer flavoproteins (bETFs) employ flavins. However, they have not been successfully deployed on electrodes. Herein, we demonstrate immobilization and expected thermodynamic reactivity of a bETF from a hyperthermophilic archaeon, Sulfolobus acidocaldarius (SaETF). SaETF differs from previously biochemically characterized bETFs in being a single protein, representing a concatenation of the …

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 …

Leveraging Deep Learning Models And Social Media Data For Enhanced Situation Awareness In Disaster Management, Ademola Abdulganiyu Adesokan

Doctoral Dissertations

"In recent years, social media has become a crucial source of real-time data for disaster management, supporting emergency responses when traditional channels like 911 are overcrowded and overwhelmed. It offers authorities valuable data for developing effective strategies, especially when swift actions are essential to save lives. However, the informal language, ambiguous meanings, and irrelevant content on social media pose challenges to accurate classification and hinder the efficient extraction of disaster-relevant information, leading to inefficiencies in emergency response efforts.

This research focuses on seven key questions: i) How can we detect, classify, and analyze hate and offensive tweet emotions during large-scale …

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 …

Enhanced Biofuel Cells Based On A Hybrid Enzymatic/Bimetallic Composite For Complete Lactate Catalytic Electrooxidation, Jefferson Honorio Franco, João Victor Bonaldo, Shelley D. Minteer, Adalgisa R. De Andrade

Chemistry Faculty Research & Creative Works

We describe complete lactate electrooxidation in an enzymatic biofuel cell that combines the catalytic action of the bimetallic composite Ru@Pt-CNT and the enzyme oxalate oxidase (OxOx). The Ru@Pt-CNT/OxOx hybrid electrode was 2.0-fold more catalytically active than the electrode containing the bimetallic composite only. During chronoamperometric experiments, the hybrid electrode achieved a 35% higher maximum current density (2.65 ± 0.15 mA cm^-2) than the Ru@Pt-CNT electrode. Electrochemical impedance spectroscopy showed that the hybrid electrode had lower charge transfer resistance than the Ru@Pt-CNT electrode, confirming that OxOx had a high affinity for lactate during the bioelectrocatalytic reaction on the electrode …

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 …}

Apocalyptic Technical Communication From Clockface To Briefcase: Revealing The Spurious Coin Of Nuclear-Security Rhetoric, Ryan Cheek

English and Technical Communication Faculty Research & Creative Works

This article the Doomsday Clock and the Nuclear Football as interconnected technical communication artifacts that function as two sides of a "spurious coin" in the securitization of nuclear deterrence. While the Clock externalizes existential risk through apocalyptic rhetoric, the Football internalizes it within exclusive military command structures—together legitimizing perpetual nuclear crisis. Drawing on technical communication scholarship and critical security studies, the analysis argues that both artifacts sustain nuclearist ideology by reinforcing deterrence as common sense. The Clock's ominous countdown and the Football's ever-present launch capability are mutually validating and together normalize nuclear brinkmanship as the price of global security.

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 …

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Gadolinium-doped gallium nitride implanted with oxygen and carbon show carrier-mediated spin mechanisms at room temperature. As-grown Gd-doped GaN grown by metal-organic chemical vapor deposition using a tris(cyclopentadienyl) gadolinium precursor shows Ordinary Hall Effect and no ferromagnetism at room temperature. Upon O or C implantation in Gd-doped GaN, Anomalous Hall Effect that is indicative of carrier-mediated spin and ferromagnetism is observed. A good crystal quality is maintained even after implantation. O and C favor interstitial sites and occupy deep-level acceptor-type states in Gd-doped GaN. Room-temperature spin and ferromagnetism that is induced by gadolinium in Gd-doped GaN is activated by O and …