Digital Commons Network^™

Instantaneous Current And Average Power Flow Characterization Of A Dc-Dc-Dc Triple Active Bridge Converter, Jonathan Saelens, Lauryn Morris, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Triple Active Bridge (TAB) is a Three-Port Power Converter that Facilitates Bi-Directional Power Flow and Provides Galvanic Isolation, Making It a Subject of Significant Research Attention. This is Attributed to its Diverse Applications in High-Frequency DC-DC Conversion, Electric Vehicles, Renewable Energy Integration, and Micro-Grids. Controlling the System at Run-Time Involves Modification of the Two Phase-Shift Parameters between Respective Bridges. by Analyzing the Fundamental Converter Operating Equations, Future Control Designers Can Use This Framework to Optimize Control Schemes to Mitigate the Under-Determined Nature of the TAB Converter. in This Paper, We Elucidate the Foundational Operational Principles of the TAB and …

Addressing Reactive Power Sharing In Parallel Inverter Islanded Microgrid Through Deep Reinforcement Learning, Oroghene Oboreh-Snapps, Sophia A. Strathman, Jonathan Saelens, Arnold Fernandes, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Parallel Inverter Microgrids (MGs) Present a Significant Challenge in the Form of Inverter-Based Distributed Generators (IBDGs) Connected with Varying Line Impedances, Potentially Leading to Substantial Reactive Power-Sharing Errors (RPSE). This Paper Proposes the Fusion of Data-Driven Control into the Conventional Virtual Synchronous Generator in a Bid to Minimize the Sharing Error. First, All State Variables Associated with Each IBDG in the Microgrid Are Sensed and Used as Input Data for a Deep Reinforcement Learning (DRL) Agent. Next, the DRL Agent, motivated by a Unique Reward Function, is Trained to Satisfy Two Objectives: (1) Ensure the Output Voltage of All IBDGs …

Adaptive Critic Optimal Control Of An Uncertain Robot Manipulator With Applications, Ravi Prakash, Laxmidhar Behera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Realistic manipulation tasks involve a prolonged sequence of motor skills in varying control environments consisting of uncertain robot dynamic models and end-effector payloads. To address these challenges, this article proposes an adaptive critic (AC)-based basis function neural network (BFNN) optimal controller. Using a single neural network (NN) with a basis function, the proposed optimal controller simultaneously learns task-related optimal cost function, robot internal dynamics, and optimal control law. This is achieved through the development of a novel BFNN tuning law using closed-loop system stability. Therefore, the proposed optimal controller provides real-time, implementable, cost-effective control solutions for practical robotic tasks. The …

Evaluation Of Transfer Learning Models On Traumatic Brain Injury Severity Classification, Ngoc Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

After traumatic brain injury (TBI), clinicians use the Glasgow Coma Scale (GCS) to classify patients by severity and radiologists use the Rotterdam score and the Marshall score to classify CT scans by severity. This work investigates a viable efficient low-cost transfer learning model to use MRI images to predict GCS, Rotterdam, and Marshall severity class after TBI. The enhanced transfer learning model architecture integrates multiple fine-tuning steps in which a few layers of the pre-trained model is unfrozen in each iteration so that the neural network is able to learn layer by layer further aspects of the image for better …

Low Noise Wireless Sensing In Termite Detection, Wei Zhang, Xiangshu Qi, Yunlong Luo, Alex Qi, Yihong Qi, Gang Feng

Electrical and Computer Engineering Faculty Research & Creative Works

Termites cause enormous financial damages all around the world every year. The majority of research on wireless sensing is always concerned with the various human-centric applications, however, the vast potential of wireless sensing for termite detection is often disregarded. In this article, a Wireless Intelligent Sensing (WISe) millimeter-wave (mmWave) radar system for termite detection is proposed. Here, we design a three-layer architecture with some intelligent resources to monitor the movement signs of the termites. In addition, we present a low noise sensing architecture that minimizes the noise in hardware and digital signal processing, which can reduce the impact of environment …

A Method For Measuring The Transfer Function Inside A Compact Metallic Enclosure Using A Slot Antenna, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. For modern electronic products, noise sources are often located inside a compact metal enclosure, making it difficult to measure the transfer function using conventional methods. Moreover, opening the metallic enclosure would dramatically change the transfer function, and inserting a near-field probe into the enclosure is challenging and may not even be possible because of the limited space inside. In this article, a novel practical method for measuring the transfer function inside a compact metallic enclosure is proposed and experimentally …

Virtual Inertia Scheduling (Vis) For Microgrids With Static And Dynamic Security Constraints, Buxin She, Fangxing Li, Jinning Wang, Hantao Cui, Xiaofei Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Microgrids feature a high penetration of inverter-interfaced distributed energy resources (DERs). The low inertia characteristic and fast dynamics of DERs pose challenges to conventional decoupled static economic operation and dynamic control design within microgrids. Hence, this paper proposed virtual inertia scheduling (VIS) for microgrids, aiming to ensure both economy and security. First, a unified framework for device-level control and grid-level operation is introduced, with VIS serving as a key application to address low inertia issues. VIS actively harnesses the controllability and flexibility of DERs to effectively manage microgrid inertia. It updates the conventional economic operation framework by incorporating the virtual …

Relative Altitude Estimation Of Infrared Thermal Uav Images Using Sift Features, Shirin Nasr Esfahani, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) have become indispensable in various applications, including surveillance, urban scene analysis, and agricultural monitoring. Accurate altitude estimation is critical for UAV operations, especially in environments where traditional sensors like GPS, pressure altimeters, and radar may fail. This paper explores the use of infrared and thermal imaging for relative altitude estimation of UAVs, highlighting their significant advantages over traditional RGB images. Infrared and thermal imaging offer superior performance in low-light and adverse weather conditions, providing clearer visibility and more reliable feature detection. By leveraging the Scale-Invariant Feature Transform (SIFT) features, this approach utilizes the inherent benefits of …

Lifelong Direct Error-Driven Learning For Uav Altitude Estimation In Different Weather Conditions, Shirin Nasr-Esfahani, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

While deep neural networks achieve remarkable visual perception capabilities for UAV position and orientation estimation, their resilience to different weather conditions still needs improvement. These models often suffer from catastrophic forgetting when adapted to new environments, losing previously acquired knowledge. Lifelong learning methods aim to balance learning flexibility and memory stability. In this paper, we present an image-based approach to estimate the relative altitude of a UAV using 2D images under varying weather conditions, including sunny, sunset, and foggy scenarios. Our experiments demonstrate significant performance degradation when the model is trained sequentially on different weather datasets, especially when new images …

Electrostatic Sorting Of Lunar Regolith Simulants For Sustainable Resource Utilization: Modeling And Characterization Of Particle Size Distribution, Abdullah Al Moinee, Peter Bachle, Kyle Newport, William Schonberg, David Bayless, Jeffrey Smith, Daoru Han, Fateme Rezaei

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

In pursuit of sustainable resource utilization on the Moon, this paper delves into modeling and characterization of particle size distribution (PSD) of lunar regolith simulants in an electrostatic system. A prototype electrostatic sieve was built and tested with four sample simulants mirroring properties of lunar mare and highland regolith. An alternating four-phase (90 degrees, 180 degrees, 270 degrees, 360 degrees) traveling square-wave was utilized for particle-directed transport to model the diverse trajectories of the particles. Numerically, we scrutinized how the distribution functions of the particles are manifested as the electrostatic field propagates, with a focus on three distinct particle ranges …

Electrostatic Sorting Of Lunar Regolith Simulants For Sustainable Resource Utilization: Modeling And Characterization Of Particle Size Distribution, Abdullah Al Moinee, Peter Bachle, Kyle Newport, William Schonberg, David Bayless, Jeffrey Smith, Daoru Han, Fateme Rezaei

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

In pursuit of sustainable resource utilization on the Moon, this paper delves into modeling and characterization of particle size distribution (PSD) of lunar regolith simulants in an electrostatic system. a prototype electrostatic sieve was built and tested with four sample simulants mirroring properties of lunar mare and highland regolith. an alternating four-phase (90 degrees, 180 degrees, 270 degrees, 360 degrees) traveling square-wave was utilized for particle-directed transport to model the diverse trajectories of the particles. Numerically, we scrutinized how the distribution functions of the particles are manifested as the electrostatic field propagates, with a focus on three distinct particle ranges …

Sensor Tasking Strategies For Space-Based Observers In The Cislunar Environment, Smriti Nandan Paul, Roshan Thomas Eapen, Puneet Singla

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The cislunar space environment has witnessed an increase in activities, and future projections indicate significant growth in object population. Consequently, it becomes crucial to monitor these objects for space domain awareness (SDA) purposes. As the number of objects surpasses the available observers, meticulous sensor tasking becomes essential. This paper focuses on designing and exploring strategies for observing and keeping custody of known objects in cislunar space. Optical space-based telescopes, combined with lunar ground-based telescope, are employed for sensor tasking of cislunar objects residing in valuable orbits. The proposed research aims to address the following key points: (1) examination of the …

Enhancing Pricing Practices Of Subcontractors: A Comparative Analysis Using Simulation Modeling, Muaz O. Ahmed, Islam H. El-Adaway, Kalyn T. Coatney

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The construction industry often relies on subcontracting, where subcontractors bid for portions of a project before general contractors bid for the entire project in a process referred to as multi-stage bidding (MSG). MSG can be complex, and winning bidders may be burdened with underestimating their bids and encountering the winner's curse. Despite various studies investigating this issue, further research is necessary to examine bidding strategies for subcontractors. This paper addresses this research need by exploring and comparing how bidding strategies based on reinforcement learning and game theory could aid subcontractors in mitigating the winner's curse in MSG. The authors used …

Exploring The Root Factors Impacting Work Zone Accidents: A Mixed-Methods Study, Bahaa Chammout, Muaz O. Ahmed, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Work Zones Are Vital For Improving Infrastructural Utilities Yet Pose Significant Dangers For Workers And Drivers Who Are Often Unfamiliar With These Areas. Prior Research Examined Various Aspects Of Work Zone Accident Causation; However, The Interrelationships And Critical Combinations Among The Contributing Factors Have Not Been Fully Analyzed. This Study Aims To Identify The Underlying Factors Contributing To Work Zone Accidents And Evaluate The Different Combinations Among Them. To This Purpose, Accident Factors Were Derived From A Total Of 133 Research Articles Addressing Work Zone Safety. Social Network Analysis (SNA) And Clustering Were Used To Comprehensively Model The Identified Factors. …

Borate-Based Bioactive Glasses Properties: Clinical And Biomedical Applications, Sarah Fakher, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

Borate bioactive glasses (BBGs) constitute the recently produced bioactive glasses (BGs) in the domain of bioactive materials, offering enhanced functionalities over conventional silicate and phosphate BGs. This advancement is primarily characterized by BBGs' rapid yet controllable degradation rates, superior bioactivity, and the ability to swiftly form a hydroxyapatite layer (HAP) upon interaction with physiological fluids. A distinguishing feature of BBGs lies in their customizability; doping with therapeutic metal ions tailors their bioactivity towards specific physiological responses, including promoting angiogenesis, antibacterial activity, and osteogenesis. This versatility of BBGs' applications extends to bone regeneration, wound healing, drug delivery systems, and potentially nerve …

Token-Based Reviewer Economies: Proposed Institutions For Managing The Reviewer Shortage Problem, Cecil Eng Huang Chua

Business and Information Technology Faculty Research & Creative Works

This opinion paper presents two proposed token-based systems to fix the information system academy's review system. At present, the review system consumes more human resources than the information systems academy has by an order of magnitude. The cost of this overflow is borne entirely by information systems researchers. I argue this is because the review system is based on a gift economy that cannot handle the currently sized market. Both proposals involve the creation of tokens and a central governing body. The first proposal involves a market built around a review bank (central governing body) that issues review tokens that …

Solar Enhanced Oxygen Evolution Reaction With Transition Metal Telluride, Harish Singh, Taishi Higuchi-Roos, Fabrice Roncoroni, David Prendergast, Manashi Nath

Chemistry Faculty Research & Creative Works

The Photo-Enhanced Electrocatalytic Method of Oxygen Evolution Reaction (OER) Shows Promise for Enhancing the Effectiveness of Clear Energy Generation through Water Splitting by using Renewable and Sustainable Source of Energy. However, Despite Benefits of Photo electrocatalytic (PEC) Water Splitting, its Uses Are Constrained by its Low Efficiency as a Result of Charge Carrier Recombination, a Large overpotential, and Sluggish Reaction Kinetics. Here, We Illustrate that Nickel Telluride (NiTe) Synthesized by Hydrothermal Methods Can Function as an Extremely Effective Photo-Coupled Electrochemical Oxygen Evolution Reaction (POER) Catalyst. in This Study, NiTe Was Synthesized by Hydrothermal Method at 145°C within Just an Hour …

Early Detection Of Driving Maneuvers For Proactive Congestion Prevention, Debasree Das, Shameek Bhattacharjee, Sandip Chakraborty, Bivas Mitra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Road Traffic Congestion Affects Not Only the Commute Delay but Also a city's overall Social, Economic, and Environmental Growth. Existing Approaches for Road Congestion Mitigation Primarily Adopt a Reactive Approach by Detecting Congestion after It Occurs and Recommending Alternate Routes to the Vehicles, Which Fails to Prevent Congestion Cascading. in Contrast, We Propose a Pervasive Platform Called ProCon that Proactively Infers the Driving Micro-Behaviors that Can Contribute to Congestion Formation and Assist the Drivers in Avoiding Such Maneuvers in Real-Time during the Navigation. Thorough Evaluations over Multiple Real-Life and Simulated Datasets Indicate that ProCon Can Reduce Congestion for More Than …

An Ai-Based Conceptual Framework To Improve Program Management Of Complex Systems, Michael D. Parrish, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

With evolving technologies, changing requirements, and limited budgets, governments and industries need to consider new methodologies to help streamline program lifecycle management, from cradle to grave, to ensure projects are delivered on time, on budget, and to the expected performance standards. Traditional approaches fail to adequately address the added complexities of System of Systems programs such as integration, interoperability, and variable lifecycle of subcomponents. The objective of this study is to assess and address the research question - can a new acquisition approach be designed to address and improve program lifecycle management of complex systems? A comparison study, using the …

Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi

Mathematics and Statistics Faculty Research & Creative Works

Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering Aids Disease Subtyping, I.e. Identifying Homogeneous Patient Subgroups, In Medical Data. Missing Data Is A Common Problem In Medical Research And Could Bias Clustering Results If Not Properly Handled. Yet, Multiple Imputation Has Been Under-Utilized To Address Missingness, When Clustering Medical Data. Its Limited Integration In Clustering Of Medical Data, Despite The Known Advantages And Benefits Of Multiple Imputation, Could Be Attributed To Many Factors. This Includes Methodological Complexity, Difficulties In Pooling Results To Obtain A Consensus Clustering, Uncertainty Regarding …

Revisiting The Divergent Multipole Expansion Of Atom-Surface Interactions: Hydrogen And Positronium, Α -Quartz, And Physisorption, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We revisit the derivation of multipole contributions to the atom-wall interaction previously presented in Łach et al. [G. Łach, M. DeKieviet, and U. D. Jentschura, Phys. Rev. A 81, 052507 (2010)10.1103/PhysRevA.81.052507]. A careful reconsideration of the angular momentum decomposition of the second-, third-, and fourth-rank tensors composed of the derivatives of the electric-field modes leads to a modification for the results for the quadrupole, octupole, and hexadecupole contributions to the atom-wall interaction. Asymptotic results are given for the asymptotic long-range forms of the multipole terms, in both the short-range and long-range limits. Calculations are carried out for hydrogen and positronium …

Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

Light detection and ranging (LiDAR) technology's expansion within the autonomous vehicles industry has rapidly motivated its application in numerous growing areas, such as smart cities, agriculture, and renewable energy. In this article, we propose an innovative approach for enhancing aerial traffic monitoring solutions through the application of LiDAR technology. The objective is to achieve precise and real-time object detection and tracking from aerial perspectives by integrating unmanned aerial vehicles with LiDAR sensors, thereby creating a potent Aerial LiDAR (A-LiD) solution for traffic monitoring. First, we develop a novel deep learning algorithm based on pointvoxel-region-based convolutional neural network (RCNN) to conduct …

Deep Reinforcement Learning Based Strategies For Inverter Dominated Microgrids, Oroghene Oboreh-Snapps

Doctoral Dissertations

The integration of inverter-based distributed generators (IBDGs) in modern power systems has ushered in a new era of renewable energy utilization, prompting the rise of Microgrid (MG) architectures. Nevertheless, as IBDG penetration increases, a host of challenges surface. Foremost among these challenges are issues related to frequency stability stemming from the inherent lack of inertia in IBDGs, and inaccurate sharing of reactive and active power, particularly evident in parallel IBDG networks with mismatched feeder impedance. This research presents novel solutions to these challenges by adopting deep reinforcement learning (DRL), specifically, the twin delayed deep deterministic policy gradient (TD3) algorithm, to …

Enhanced Bottom Anode Monitoring In Dc Electric Arc Furnaces Using Fiber Optic Sensors, Yeshwanth Reddy Mekala, Rony Kumer Saha, Ogbole Collins Inalegwu, Muhammad Roman, Farhan Mumtaz, Rex Gerald, Jeffrey D. Smith, Jie Huang, Ronald J. O'Malley

PSMRC Faculty Research

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom …

The Melting Behavior Of Hydrogen Direct Reduced Iron In Molten Steel And Slag: An Integrated Computational And Experimental Study, Fabian Andres Calderon Hurtado, Joseph Govro, Arezoo Emdadi, Ronald J. O'Malley

PSMRC Faculty Research

Direct reduced iron (DRI) and hot briquetted iron (HBI) are essential feedstocks for tramp element control in the electric arc furnace (EAF). Due to greenhouse gas (GHG) concerns related to CO₂ emissions, hydrogen as a substitute for natural gas and a reductant in DRI production is being widely explored to reduce GHG emissions in ironmaking. This study examines the melting behavior of hydrogen DRI (H-DRI) pellets in the EAF containing low-carbon (0.1 wt.%) molten steel and molten slag. A computational heat transfer model was developed to predict the melting behavior of H-DRI pellets. To validate the model, a set …

Message From The Phd Dissertation Showcase Chairs, Panos K. Chrysanthis, Sanjay Madria

Computer Science Faculty Research & Creative Works

No abstract provided.

Improvements In Biomedical Image Analysis With Computational Intelligence And Data Fusion Techniques, Akanksha Maurya

Doctoral Dissertations

"An estimated 2 million new cases of basal cell carcinoma (BCC) are diagnosed each year in the United States, making it one of the most common skin cancers. Earlier detection of these cancers enables less invasive biopsies. Clinical detection consists of a preliminary visual observation of these skin lesions by an experienced dermatologist making it a specialized task highly dependent on their time, availability, and resources. Hence, there is a need for automating this process that can assist healthcare staff. In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. Telangiectasia …

Synthesis And Characterization Of Quantum Materials, Yunsheng Qiu

Doctoral Dissertations

"In this study, attempts were made to grow quantum materials that have recently undergone a profound change of perspective. These materials are involved in intricate macroscopic properties rooted in the subtle nature of quantum physics. To explore our understanding of quantum materials, this study includes three projects: Magnetic Topological Insulators, Topological Superconductors, and high-temperature superconductors.

A Cr-doped Sb₂Te₃ is added to the category for the magnetic topological insulators project. Their transport properties are studied, and the origin of ferromagnetism is studied. Anomalous Hall effect is observed in the Hall measurements, and serval factors (cooling rate, dopant deficiency) …

Re-Evaluating Missouri’S Strategic Element Potential: A Geochemical Study Of The Mesoproterozoic Fe-Cu-Co-Ree Deposits In Southeast Missouri, Usa, Brandon James Sullivan

Doctoral Dissertations

"Iron-oxide-copper-gold (IOCG) deposits are poorly understood mineral systems. For example, we do not know why Cu- and Co-rich IOCG deposits typically occur proximal to Fe ore deposits that are notably Cu and Co-poor, such as Iron Oxide Apatite (IOA) deposits. To better understand the formation of IOA and IOCG deposits in Missouri, USA, this PhD thesis examines the genesis of the Kratz Spring IOA and the Boss Central Dome IOCG deposits. This study presents the first constraints on formation conditions and fluid sources in the studied deposits using integrated petrographic, mineral composition, and Fe isotope analyses of oxide minerals. Observations …

Control And Optimization Of Energy Storage System In Power Distribution System, Waqas Ur Rehman

Doctoral Dissertations

"The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, …