Digital Commons Network^™

Three-Terminal Noise Source Extraction From A Qi-Based Wireless Power Transfer System For Predicting Conducted Emissions, Srinath Penugonda, Siqi Bai, Varittha Sanphuang, Nevin Altunyurt, Hongseok Kim, Daryl G. Beetner, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

An equivalent method to extract a three-terminal noise source from a Qi-based wireless power transfer system is proposed in this article. This method is capable of extracting a source for both the positive (P) and negative (N) lines with respect to the third terminal (the ground chassis or reference plane). The extracted sources are independent of the setup configuration and can be used to predict currents or voltages on the P and N lines on a setup that is different from the extraction setup. In the following article, a three-terminal model independent of the setup configuration is first extracted. The …

Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel hybrid learning-based optimal tracking method to address zero-sum game problems for partially uncertain nonlinear discrete-time systems. An augmented system and its associated discounted cost function are defined to address optimal tracking. Three multi-layer neural networks (NNs) are utilized to approximate the optimal control and the worst-case disturbance inputs, and the value function. The critic weights are tuned using the hybrid technique, whose weights are updated once at the sampling instants and in an iterative manner over finite times within the sampling instants. The proposed hybrid technique helps accelerate the convergence of the approximated value functional …

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani

Electrical and Computer Engineering Faculty Research & Creative Works

The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a data-driven approach that adaptively tunes the parameters of a virtual synchronous generator to achieve optimal frequency response against disturbances. In the proposed approach, the control variables, namely, the virtual moment of inertia and damping factor, are transformed into actions of a reinforcement learning agent. Different from the state-of-the-art methods, the proposed study introduces the settling time parameter as one of the observations in addition to the frequency and rate of change of frequency (RoCoF). In the reward function, preset indices are considered to simultaneously ensure bounded frequency deviation, low RoCoF, fast response, and quick settling time. …

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed in this article. While based on physics, the number of parameters and components is minimized, so the model can be tuned easily from available measurements of the packaged TVS. SPICE convergence issues seen in previous snapback device models are eliminated by adding nonlinear damping components to the model. No convergence issues were seen among any of the simulations performed for this study, which includes transmission-line pulse tests with multiple levels and rise times. The proposed model was used to represent two different TVS devices and was validated in …

Optimal Adaptive Tracking Control Of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, Behzad Farzanegan, Rohollah Moghadam, Sarangapani Jagannathan, Pappa Natarajan

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses a multilayer neural network (MNN)-based optimal adaptive tracking of partially uncertain nonlinear discrete-time (DT) systems in affine form. By employing an actor–critic neural network (NN) to approximate the value function and optimal control policy, the critic NN is updated via a novel hybrid learning scheme, where its weights are adjusted once at a sampling instant and also in a finite iterative manner within the instants to enhance the convergence rate. Moreover, to deal with the persistency of excitation (PE) condition, a replay buffer is incorporated into the critic update law through concurrent learning. To address the vanishing …

Coaxial Cable Sensing: Review And Perspective, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

The development of sensors has been a hot research topic in both scientific and industrial communities over the past decades. In recent years, a new sensing technology based on coaxial cables has emerged. Inspired by the fiber Bragg grating and motivated by the demand for structural health monitoring, coaxial cable Bragg gratings were first proposed and demonstrated with superior large strain capability ($>$ 5%). Mimicking the mature sensing modalities in fiber-optic sensors, coaxial cable sensors are developed to be promising alternatives for fiber-optic sensors in harsh-environment applications involving heavy duty, large strains, high pressures, and high temperatures. Over the …

The Partial Elements Equivalent Circuit Method: The State Of The Art, Giulio Antonini, Albert E. Ruehli, Daniele Romano, Fabrizio Loreto

Electrical and Computer Engineering Faculty Research & Creative Works

This year marks about half a century since the birth of the technique known as the partial element equivalent circuit modeling approach. This method was initially conceived to model the behavior of interconnect-type problems for computer-integrated circuits. An important industrial requirement was the computation of general inductances in integrated circuits and packages. Since then, the advances in methods and applications made it suitable for modeling a large class of electromagnetic problems, especially in the electromagnetic compatibility (EMC)/signal and power integrity (SI/PI) areas. The purpose of this article is to present an overview of all aspects of the method, from its …

Suppressing Aluminum/Silica Exchange Reaction Between High Aluminum Steel And Mold Flux During Continuous Casting Process, Kuanysh Nurbekuly Yermukhanbetov

Masters Theses

"Mold flux plays one of the critical roles in continuous casting of steel. It performs five primary functions: thermal and chemical insulation, lubrication between the steel strand and mold, absorption of inclusions, and promotion of even heat flux. The aluminum/silica exchange reaction occurring between steel and mold flux during the continuous casting process poses significant challenges in the steel industry. This reaction can lead to various defects in the cast product and adversely affect its surface quality, as well as downstream processing.

In this work, effectiveness of two approaches, namely slag dopant additions and electrochemical techniques, in suppressing the exchange …

Designing Exterior Lighting For Safety And Comfort While Minimizing Light Pollution, Energy Consumption, And Cost, Stephen Michael Simmons

Masters Theses

"Artificial light at night brings many benefits to society. However, these benefits do not come without costs. One environmental issue that is often overlooked in the design of public spaces and infrastructure is light pollution. At the expense of large amounts of energy, light pollution causes numerous harmful effects on human health, ecosystems, and the night sky. Today, the problem is becoming more widespread, especially with the increasing use of bright, white LED luminaires. Thus, it is imperative for designers and engineers to create smarter lighting designs that not only allow for safety and comfort at night but also promote …

Optimizing The Placement Of Multiple Uav--Lidar Units Under Road Priority And Resolution Requirements, Zachary Michael Osterwisch

Masters Theses

"Real-time road traffic information is crucial for intelligent transportation systems (ITS) applications, like traffic navigation or emergency response management, but acquiring such data is tremendously challenging in practice because of the high costs and inefficient placement of sensors. Some modern ITS applications contribute to this problem by equipping vehicles with multiple light detection and ranging (LiDAR) sensors, which are expensive and gather data inefficiently; one solution that avoids vehicle-mounted LiDAR acquisition has been to install elevated LiDAR instruments along roadways, but this approach remains unrefined. The eventual development of sixth-generation (6G) wireless communication will enable new, creative solutions to solve …

Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula

Masters Theses

"Ridesharing platforms rely on connecting available taxi drivers to potential passengers to maximize their revenue. However, predicting the stopping decision made by every driver, i.e., the final task performed during a given day, is crucial to achieving this goal. Unfortunately, little research has been done on predicting drivers’ stopping decisions, especially when they deviate from expected utility maximization behavior. This research proposes a Dynamic Discounted Satisficing (DDS) heuristic to model and learn the task at which human agents will stop working for that day, assuming that the human agents are taking sequential decisions based on their preference order. We apply …

Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric

Masters Theses

"Vulnerability to adversarial attacks is a recognized deficiency of not only deep neural networks (DNNs) but also multi-task deep neural networks (MT-DNNs) that attracted much attention in the past few years. To the best of our knowledge, all multi-task deep neural network adversarial attacks currently present in the literature are non-targeted attacks that use gradient descent to optimize a single loss function generated by aggregating all loss functions into one. On the contrary, targeted attacks are sometimes preferred since they give more control over the attack. Hence, this paper proposes a novel targeted multi-objective adversarial ATtack (MAT) based on genetic …

Temperature Dependence Of The Electronic Absorption Spectrum Of No2, Steve Ndengué, Ernesto Quintas Sánchez, Richard Dawes, Christopher C. Blackstone, David L. Osborn

Chemistry Faculty Research & Creative Works

The nitrogen dioxide (NO₂) radical is composed of the two most abundant elements in the atmosphere, where it can be formed in a variety of ways including combustion, detonation of energetic materials, and lightning. Relevant also to smog and ozone cycles, together these processes span a wide range of temperatures. Remarkably, high-resolution NO₂ electronic absorption spectra have only been reported in a narrow range below about 300 K. Previously, we reported [ J. Phys. Chem. A 2021, 125, 5519−5533 ] the construction of quasi-diabatic potential energy surfaces (PESs) for the lowest four electronic states (X̃, Ã, B̃, …

Nuclear Magnetic Resonance Study Of Co2 Capture By Fluoroalkylamines: Ammonium Ion Pka Depression Via Fluorine Modification And Thermochemistry Of Carbamylation, Brian Jameson, Kari Knobbe, Rainer Glaser

Chemistry Faculty Research & Creative Works

We are developing energy-efficient and reversible carbon capture and release (CCR) systems that mimic the Lys201 carbamylation reaction in the active site of ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO). The multiequilibria scenario ammonium ion Xa ⇌ amine Xb ⇌ carbamic acid Xc ⇌ carbamate Xd requires the presence of both free amine and CO2 for carbamylation and is affected by the pKa(Xa). Two fluorination strategies aimed at ammonium ion pKa depression and low pH carbamylation were analyzed with (2,2,2-trifluoroethyl) butylamine 2b and 2,2-difluoropropylamine 3b and compared to butylamine 1b. The determination of K1 and ΔG1 of the carbamylation reactions requires the solution of …

Inter-Rater Agreement For The Annotation Of Neurologic Signs And Symptoms In Electronic Health Records, Chelsea Oommen, Quentin Howlett-Prieto, Michael D. Carrithers, Daniel B. Hier

Chemistry Faculty Research & Creative Works

The extraction of patient signs and symptoms recorded as free text in electronic health records is critical for precision medicine. Once extracted, signs and symptoms can be made computable by mapping to signs and symptoms in an ontology. Extracting signs and symptoms from free text is tedious and time-consuming. Prior studies have suggested that inter-rater agreement for clinical concept extraction is low. We have examined inter-rater agreement for annotating neurologic concepts in clinical notes from electronic health records. After training on the annotation process, the annotation tool, and the supporting neuro-ontology, three raters annotated 15 clinical notes in three rounds. …

Using Catalysis To Control The Morphology And Stiffness Of Shape Memory Poly(Isocyanurate-Urethane) (Pir-Pur) Aerogels, A. B.M. Shaheen Ud Doulah, Chandana Mandal, Hojat Majedi Far, Vaibhav A. Edlabadkar, Rushi U. Soni, Stephen Y. Owusu, Nicholas Leventis, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

A large array of anhydrous metal ions were tested as catalysts in the preparation of shape memory poly(isocyanurate-urethane) (PIR-PUR) aerogels from the reaction of 1,3,5-tris(6-isocyanatohexyl)-1,3,5-triazinane-2,4,6-trione (Desmodur N3300A: a well-known isocyanurate-based aliphatic triisocyanate) and triethylene glycol (TEG) in anhydrous acetonitrile. The reaction yielded wet gels that were dried into aerogels in an autoclave with supercritical fluid CO2. The catalytic activity was mostly identified among CH3CN-soluble salts (mainly chlorides) of third-row d-block elements from iron to zinc, group 13 elements from aluminum to thallium, as well as cadmium, bismuth, and tin. Tin (119Sn) NMR indicated that the metal ion complexes with TEG, …

Topology Driven And Soft Phonon Mode Enabled Na-Ion Diffusion In Quaternary Chalcogenides, Na3zngax4 (X = S, And Se), Sajan Kumar, Mayanak K. Gupta, Ranjan Mittal, Santhoshkumar Sundaramoorthy, Amitava Choudhury, Naresh C. Osti, Alexander I. Kolesnikov, Matthew B. Stone, Yongqiang Cheng, Samrath L. Chaplot

Chemistry Faculty Research & Creative Works

The compounds Na3ZnGaX4 (X = S, Se) are potential solid electrolyte materials in sodium-based batteries, which have certain advantages over oxide materials and have shown significant ionic conductivity at ambient temperature. In this paper, we bring out atomic-level features of the diffusion process in these new materials using the microscopic techniques of inelastic neutron scattering (INS), Quasi elastic neutron scattering (QENS), and ab initio molecular dynamics (AIMD) simulations. The insights obtained from these techniques are unique and not available from other macroscopic experiments. Neutron scattering experiments have been performed at temperatures from 100 to 700 K. The simulations have been …

Rovibrational States Calculations Of The H2o-Hcn Heterodimer With The Multiconfiguration Time Dependent Hartree Method, Hervé Tajouo Tela, Ernesto Quintas-Sánchez, Marie Lise Dubernet, Yohann Scribano, Richard Dawes, Fabien Gatti, Steve Ndengué

Chemistry Faculty Research & Creative Works

Water and hydrogen cyanide are two of the most common species in space and the atmosphere with the ability of binding to form dimers such as H₂O-HCN. In the literature, while calculations characterizing various properties of the H₂O-HCN cluster (equilibrium distance, vibrational frequencies and rotational constants) have been done in the past, extensive calculations of the rovibrational states of this system using a reliable quantum dynamical approach have yet to be reported. In this work, we intend to mend that by performing the first calculation of the rovibrational states of the H₂O-HCN van der …

Extracellular Poly(Hydroxybutyrate) Bioplastic Production Using Surface Display Techniques, Kevin Beaver, Ashwini Dantanarayana, Willisa Liou, Markus Babst, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Poly(hydroxybutyrate) is a biocompatible, biodegradable polyester synthesized naturally in a variety of microbial species. A greener alternative to petroleum-based plastics and sought after for biomedical applications, poly(hydroxybutyrate) has failed to break through as a leading material in the plastic industry due to its high cost of production. Specifically, the extraction of this material from within bacterial cells requires lysis of cells, which takes time, uses harsh chemicals, and starts the process again with growing new living cells. Recently, surface display of enzymes on bacterial membranes has become an emerging technique for extracellular biocatalysis. In this work, a fusion protein lpp-ompA-phaC …

Tweetace: A Fine-Grained Classification Of Disaster Tweets Using Transformer Model, Ademola Adesokan, Sanjay Madria, Long Nguyen

Computer Science Faculty Research & Creative Works

Disaster management teams play a crucial role in responding to catastrophic events with speed and efficiency. However, when faced with large data of disaster-related information, manual systems can struggle to classify the information accurately, especially when they are unavailable. This challenge highlights the need for integrating social media and implementing machine learning models to address the issue. However, the development of such models is dependent on the availability of adequately annotated data, which presents a significant obstacle in the field of crisis management. to address this challenge, our study focuses on the need for disaster event classification through social media. …

Supervised Deep Tree In Alzheimer's Disease, Xiaowei Yu, Lu Zhang, Yanjun Lyu, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

As a progressive neurodegenerative disorder, the pathological changes of Alzheimer's disease (AD) might begin as much as two decades before the manifestation of clinical symptoms. Since the nature of the irreversible pathology of AD, early diagnosis provides a more tractable way for disease intervention and treatment. Therefore, numerous approaches have been developed for early diagnostic purposes. Although several important biomarkers have been established, most of the existing methods show limitations in describing the continuum of AD progression. However, understanding this continuous development is essential to understand the intrinsic progression mechanism of AD. In this work, we proposed a supervised deep …

Representative Functional Connectivity Learning For Multiple Clinical Groups In Alzheimer's Disease, Lu Zhang, Xiaowei Yu, Yanjun Lyu, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Mild cognitive impairment (MCI) is a high-risk dementia condition which progresses to probable Alzheimer's disease (AD) at approximately 10% to 15% per year. Characterization of group-level differences between two subtypes of MCI - stable MCI (sMCI) and progressive MCI (pMCI) is the key step to understand the mechanisms of MCI progression and enable possible delay of transition from MCI to AD. Functional connectivity (FC) is considered as a promising way to study MCI progression since which may show alterations even in preclinical stages and provide substrates for AD progression. However, the representative FC patterns during AD development for different clinical …

Stability And Dynamics Across Magnetic Phases Of Vortex-Bright Type Excitations In Spinor Bose-Einstein Condensates, Garyfallia C. Katsimiga, Simeon I. Mistakidis, K. Mukherjee, P. G. Kevrekidis, P. Schmelcher

Physics Faculty Research & Creative Works

The Static Properties, I.e., Existence And Stability, As Well As The Quench-Induced Dynamics Of Vortex-Bright Type Excitations In Two-Dimensional Harmonically Confined Spin-1 Bose-Einstein Condensates Are Investigated. Linearly Stable Vortex-Bright-Vortex And Bright-Vortex-Bright Solutions Arise In Both Antiferromagnetic And Ferromagnetic Spinor Gases Upon Quadratic Zeeman Energy Shift Variations. Their Deformations Across The Relevant Transitions Are Exposed And Discussed In Detail, Evincing Also That Emergent Instabilities Can Lead To Pattern Formation. Spatial Elongations, Precessional Motion, And Spiraling Of The Nonlinear Excitations When Exposed To Finite Temperatures And Upon Crossing The Distinct Phase Boundaries, Via Quenching Of The Quadratic Zeeman Coefficient, Are Unveiled. Spin-Mixing …

Quantum Electrodynamics Of Dicke States: Resonant One-Photon Exchange Energy And Entangled Decay Rate, Ulrich D. Jentschura, Chandra M. Adhikari

Physics Faculty Research & Creative Works

We calculate the fully retarded one-photon exchange interaction potential between electrically neutral, identical atoms, one of which is assumed to be in an excited state, by matching the scattering matrix (S matrix) element with the effective Hamiltonian. Based on the Feynman prescription, we obtain the imaginary part of the interaction energy. Our results lead to precise formulas for the distance-dependent enhancement and suppression of the decay rates of entangled superradiant and subradiant Dicke states (Bell states), as a function of the interatomic distance. The formulas include a long-range tail due to entanglement. We apply the result to an example calculation …

2022 Scholarly Productivity Report, Missouri University Of Science And Technology

Civil, Architectural and Environmental Engineering Scholarly Productivity Reports

No abstract provided.

Predicting Convection Configurations In Coupled Fluid-Porous Systems, Matthew Mccurdy, Nicholas J. Moore, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

A ubiquitous arrangement in nature is a free-flowing fluid coupled to a porous medium, for example a river or lake lying above a porous bed. Depending on the environmental conditions, thermal convection can occur and may be confined to the clear fluid region, forming shallow convection cells, or it can penetrate into the porous medium, forming deep cells. Here, we combine three complementary approaches - linear stability analysis, fully nonlinear numerical simulations and a coarse-grained model - to determine the circumstances that lead to each configuration. the coarse-grained model yields an explicit formula for the transition between deep and shallow …

Enhanced Neurologic Concept Recognition Using A Named Entity Recognition Model Based On Transformers, Sima Azizi, Daniel B. Hier, Donald C. Wunsch

Chemistry Faculty Research & Creative Works

Although Deep Learning Has Been Applied to the Recognition of Diseases and Drugs in Electronic Health Records and the Biomedical Literature, Relatively Little Study Has Been Devoted to the Utility of Deep Learning for the Recognition of Signs and Symptoms. the Recognition of Signs and Symptoms is Critical to the Success of Deep Phenotyping and Precision Medicine. We Have Developed a Named Entity Recognition Model that Uses Deep Learning to Identify Text Spans Containing Neurological Signs and Symptoms and Then Maps These Text Spans to the Clinical Concepts of a Neuro-Ontology. We Compared a Model based on Convolutional Neural Networks …

The Bridge Newsletter Winter 2022, Missouri University Of Science And Technology

The Bridge Newsletter

-Missouri S&T CO2 research is rock solid
-Bringing circular economy to construction projects
-Ph.D. graduate wins Fellowship for solar farm protection research
-Rockne presents 2022 Mathes Lecture on ways to evolve engineering education
-Missouri S&T Ph.D. graduate wins $70,000 Laegeler Fellowship for solar farm protection research