Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Missouri University of Science and Technology

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1441 - 1470 of 21777

Full-Text Articles in Engineering

Water Vapor Oxidation Of Sic Layer Of Tristructural Isotropic Particles, Visharad Jalan, Adam Bratten, Matthew Luebbe, Haiming Wen Jan 2024

Water Vapor Oxidation Of Sic Layer Of Tristructural Isotropic Particles, Visharad Jalan, Adam Bratten, Matthew Luebbe, Haiming Wen

Materials Science and Engineering Faculty Research & Creative Works

Tri structural isotropic (TRISO) fuel particles, developed for use in high-temperature gas-cooled nuclear reactors, can be subjected to oxidizing environments in off-normal accident scenarios. In this study, surrogate TRISO fuel particles were oxidized at 1000–1350°C for 4 h in 20 kPa water vapor atmosphere balanced with ultrahigh-purity helium gas. The oxide scale morphology and thickness were studied via scanning electron microscopy, focused ion beam, and transmission electron microscopy. The oxide thickness increased as the oxidation temperature was increased. Although the oxide scale at 1000°C was completely amorphous, pockets of crystalline oxide were observed on particles oxidized at 1200 and 1300°C. …


Bipolar Hipims Kick-Pulse For High Hardness In High-Entropy Boride Thin Films, Nathaniel S. Mcilwaine, Nestor O.Marquez Rios, Eva Zurek, Donald W. Brenner, William G. Fahrenholtz, Stefano Curtarolo, Douglas E. Wolfe, Jon Paul Maria Jan 2024

Bipolar Hipims Kick-Pulse For High Hardness In High-Entropy Boride Thin Films, Nathaniel S. Mcilwaine, Nestor O.Marquez Rios, Eva Zurek, Donald W. Brenner, William G. Fahrenholtz, Stefano Curtarolo, Douglas E. Wolfe, Jon Paul Maria

Materials Science and Engineering Faculty Research & Creative Works

We report a microhardness indentation study for multicomponent refractory metal boride thin films that belong to the family of high-entropy ceramics exhibiting superior hardness and high temperature properties. We focus on the nominally equimolar composition (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2) B2, which we refer to as HEB3, on c-plane sapphire substrates. Thin films are prepared using bipolar high power impulse magnetron sputtering (HiPIMS), where the positive kick pulse is optimized to produce films with high density, high crystallinity, and a microstructure that is isometric in nature as revealed by cross-sectional fracture surface imaging, X-ray diffraction, and X-ray reflectometry. Low-load Knoop indentation is used to …


Sic Addition To A Dual Phase High Entropy Ultra-High Temperature Ceramic, Rubia Hassan, William G. Fahrenholtz, Kantesh Balani, Gregory E. Hilmas, Jeremy Watts Jan 2024

Sic Addition To A Dual Phase High Entropy Ultra-High Temperature Ceramic, Rubia Hassan, William G. Fahrenholtz, Kantesh Balani, Gregory E. Hilmas, Jeremy Watts

Materials Science and Engineering Faculty Research & Creative Works

Dual phase (Hf,Ta,Ti,W,Zr)B2-(Hf,Ta,Ti,W,Zr)C high entropy ultra-high temperature ceramics were processed from commercial diboride and carbide powders with and without SiC additions. A 30-min hold at a maximum temperature of 1850 °C in spark plasma sintering resulted in a relative density of ∼95 %, which increased to ∼100 % with the addition of 7.5 wt.% SiC. The compositions did not reach chemical equilibrium under the given sintering conditions resulting in an inhomogeneous distribution of transition metals in both the boride and carbide phases. The addition of SiC improved densification by inhibiting grain growth, which reduced the grain size from 9.0 ± …


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 Jan 2024

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 …


Cascaded Weak Reflector Coaxial Cable Structure For Point And Distributed Large-Strain Sensing, Chen Zhu, Osamah Alsalman, Jie Huang Jan 2024

Cascaded Weak Reflector Coaxial Cable Structure For Point And Distributed Large-Strain Sensing, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we present a truly distributed sensing modality based on a cascaded weak reflector coaxial cable structure (CWR-CCS) for large strain measurements. Compared to an optical fiber, a coaxial cable is much more robust and has a larger strain capability to survive harsh conditions, which may enable important applications in structural health monitoring. By drilling serial shallow holes into a commercial flexible coaxial cable perturbing the local impedance along its axial direction, CWRs along the coaxial cable are introduced due to impedance mismatch, forming the CWR-CCS. Gating a certain number of sequential reflectors in the time-domain reflection signal …


Segmented Fiber Optic Sensors Based On Hybrid Microwave-Photonic Interrogation, Wassana Naku, Osamah Alsalman, Jie Huang, Chen Zhu Jan 2024

Segmented Fiber Optic Sensors Based On Hybrid Microwave-Photonic Interrogation, Wassana Naku, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we propose and demonstrate a novel concept of segmented fiber optic sensors by integrating the fiber Bragg grating (FBG) reflector modality and a hybrid interrogation technique enabled by microwave photonics. As a proof of concept, a radiofrequency Fabry-Perot interferometer (FPI) based on an optical fiber with two FBGs as the two reflectors of the Fabry-Perot (FP) cavity is constructed. By measuring the frequency response of the FPI device followed by a joint-time-frequency-domain analysis, the interferogram of the FPI in the microwave domain and the time-domain signal of the FBGs can be unambiguously reconstructed. Thus, the two elements …


Statistical Eye Diagrams For High-Speed Interconnects Of Packages: A Review, Junyong Park, Donghyun Kim Jan 2024

Statistical Eye Diagrams For High-Speed Interconnects Of Packages: A Review, Junyong Park, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

An eye diagram, a critical metric in signal integrity analysis for high-speed interconnects such as packages, interposer, and printed circuit boards (PCBs), is generated by superposition of the received waveform. Obtaining an eye diagram is time-consuming, thus signal integrity analysis is inefficient. This article reviews that have been proposed to overcome this limitation. The statistical eye diagram provides a probability distribution depending on a sampling time and voltage, therefore it can be expanded to other metrics, such as the bit-error rate and shmoo plot. This article introduces previous research on statistical eye diagrams applied to complementary metal-oxide-semiconductors (CMOSs), noise, and …


A Segmentation Approach For Predicting Plane Wave Coupling To Pcb Structures, Shengxuan Xia, James Hunter, Aaron Harmon, Ahmed M. Hassan, Victor Khilkevich, Daryl G. Beetner Jan 2024

A Segmentation Approach For Predicting Plane Wave Coupling To Pcb Structures, Shengxuan Xia, James Hunter, Aaron Harmon, Ahmed M. Hassan, Victor Khilkevich, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Evaluating the far-field radio frequency (RF) susceptibility of electronic devices often depends on extensive testing or full wave simulations. These methods are effective when complete system information is available but require substantial time and resources to evaluate a large number of variations in system configurations, where trace routings, integrated circuit (IC) package styles, trace terminations, arrival angle, and polarization of incoming wave, etc., are varied from one configuration to another. The goal of the following article is to develop simulation techniques for studying the statistical characteristics of coupling to typical printed circuit board (PCB) structures. Simulation time can be reduced …


A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li Jan 2024

A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …


Adaptive Resilient Control For A Class Of Nonlinear Distributed Parameter Systems With Actuator Faults, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan Jan 2024

Adaptive Resilient Control For A Class Of Nonlinear Distributed Parameter Systems With Actuator Faults, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a new model-based fault resilient control scheme for a class of nonlinear distributed parameter systems (DPS) represented by parabolic partial differential equations (PDE) in the presence of actuator faults. A Luenberger-like observer on the basis of nonlinear PDE representation of DPS is developed with boundary measurements. A detection residual is generated by taking the difference between the measured output of the DPS and the estimated one given by the observer. Once a fault is detected, an unknown actuator fault parameter vector together with a known basis function is utilized to adaptively estimate the fault dynamics. A novel …


Investigation Of Intermodal Four-Wave Mixing For Continuous-Wave Photon-Pair Generation, Seyedehnajmeh Montazeri, Md Abu Zobair, Mina Esmaeelpour Jan 2024

Investigation Of Intermodal Four-Wave Mixing For Continuous-Wave Photon-Pair Generation, Seyedehnajmeh Montazeri, Md Abu Zobair, Mina Esmaeelpour

Electrical and Computer Engineering Faculty Research & Creative Works

We Experimentally Demonstrate the Various Intermodal and Intramodal Four-Wave Mixing Processes in a Few-Mode Fiber with Three Modes using Non-Degenerate Pumps. We Distinguish the Processes by Calculating their Phase Mismatch and Identify the Intermodal Spontaneous Four-Wave Mixing Process that Generates Entangled Photon Pairs in Various Modes. We Achieve This using Continuous-Wave Beams and the Seeding Technique Due to the Low Efficiency of the Spontaneous Four-Wave Mixing Effect in the Fiber. We Seeded the Stokes and Anti-Stokes Waves and Measured the Spectral Content of Each Mode While Moving the Seed Away from the Perfect Phase-Matched Condition in the Fiber under Test. …


Enhanced Sensitivity And Robustness In An Embeddable Strain Sensor Using Microwave Resonators, Yan Tang, Yizheng Chen, Qi Zhang, Biyao Shi, Jie Huang Jan 2024

Enhanced Sensitivity And Robustness In An Embeddable Strain Sensor Using Microwave Resonators, Yan Tang, Yizheng Chen, Qi Zhang, Biyao Shi, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Introduces A Novel, Cost-Effective, And Durable Strain Sensor With Exceptional Sensitivity And Resolution, Utilizing An Open-Ended Hollow Coaxial Cable Resonator (OE-HCCR). The OE-HCCR Is Characterized By Two Reflective Elements: A Metal Post That Connects The Inner And Outer Conductors At The Signal's Entrance, And A Terminal Flange Near The Coaxial Line's End, Establishing A Variable Gap. The Sensor Employs A Paired Anchor Ring In Conjunction With The Terminal Flange To Transduce And Direct Strain. Variations In The Gap Alter The Resonant Frequency By Modulating The Phase Of The Reflection Coefficient At The Cable's Terminus. Initial Calibration Revealed A …


Optical Fiber Sensors Based On Advanced Vernier Effect - A Review, Wassana Naku, Jie Huang, Chen Zhu Jan 2024

Optical Fiber Sensors Based On Advanced Vernier Effect - A Review, Wassana Naku, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

The Optical Vernier Effect Has Emerged as a Powerful Tool for Enhancing the Sensitivity of Optical Fiber Interferometer-Based Sensors, Ushering in a New Era of Highly Sensitive Fiber Sensing Systems. While Previous Research Has Primarily Focused on the Physical Implementation of Vernier Effect-Based Sensors using Different Combinations of Interferometers, Conventional Vernier Sensors Face Several Challenges. These Include the Stringent Requirements on the Sensor Fabrication Accuracy to Achieve a Large Amplification Factor, the Necessity of using a Source with a Very Large Bandwidth and a Bulky Optical Spectrum Analyzer, and the Associated Complex Signal Demodulation Processes. This Article Delves into Recent …


Multimode Fiber-Based Interferometric Sensors With Microwave Photonics, Chen Zhu, Shuaifei Tian, Lingmei Ma, Jie Huang Jan 2024

Multimode Fiber-Based Interferometric Sensors With Microwave Photonics, Chen Zhu, Shuaifei Tian, Lingmei Ma, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is one of the most widely used investigative techniques in various fields. With the implementation of interferometry on optical fibers, fiber optic interferometers (FOIs) have gained tremendous growth and advancement in the past four decades and have been explored for measurements of a diverse array of physical, chemical, and biological parameters. FOIs are typically constructed using single-mode fibers (SMFs) and are interrogated in the optical domain using probing light with a tightly controlled state of polarization (SOP), to ensure high-quality interference signals that facilitate sensing applications. The stringent requirement on the single-mode operation, as well as SOP, has hindered …


Electromagnetic-Circuital-Thermal-Mechanical Multiphysics Numerical Simulation Method For Microwave Circuits, Huan Huan Zhang, Zheng Lang Jia, Peng Fei Zhang, Ying Liu, Li Jun Jiang, Da Zhi Ding Jan 2024

Electromagnetic-Circuital-Thermal-Mechanical Multiphysics Numerical Simulation Method For Microwave Circuits, Huan Huan Zhang, Zheng Lang Jia, Peng Fei Zhang, Ying Liu, Li Jun Jiang, Da Zhi Ding

Electrical and Computer Engineering Faculty Research & Creative Works

An electromagnetic-circuital-thermal-mechanical Multiphysics numerical method is proposed for the simulation of microwave circuits. The discontinuous Galerkin time-domain (DGTD) method is adopted for electromagnetic simulation. The time-domain finite element method (FEM) is utilized for thermal simulation. The circuit equation is applied for circuit simulation. The mechanical simulation is also carried out by FEM method. A flexible and unified Multiphysics field coupling mechanism is constructed to cover various electromagnetic, circuital, thermal and mechanical Multiphysics coupling scenarios. Finally, three numerical examples emulating outer space environment, intense electromagnetic pulse (EMP) injection and high-power microwave (HPM) illumination are utilized to demonstrate the accuracy, efficiency, and …


A Robust Demand Regulation Strategy For Ders In A Single-Controllable Active Distribution Network, Shah Fahad, Arman Goudarzi, Rui Bo, Muhammad Waseem, Rashid Al-Ammari, Atif Iqbal Jan 2024

A Robust Demand Regulation Strategy For Ders In A Single-Controllable Active Distribution Network, Shah Fahad, Arman Goudarzi, Rui Bo, Muhammad Waseem, Rashid Al-Ammari, Atif Iqbal

Electrical and Computer Engineering Faculty Research & Creative Works

Over the past decade, pq regulation schemes for a single-controllable active distribution network (adn) using coordination among a network of virtual synchronous generators (vsgs) have been proposed. However, considering the variable nature of intermittent renewable energy sources (iress), coupling a cluster of iress with the point of common coupling (pcc) of adn could inflict transient issues for the power management of the whole adn. To counter these challenges, the proposed study has three main objectives: 1) to propose a modified mathematical model that represents the apparent resistance-reactance at the pcc of adn in relation to the pq coordination among the …


The Mechanism And Effect Of Seismic Source Location Using Double Waves In Three-Dimensional Microseismic Monitoring, Zhigang Wang, Xiaoqing Wang, Shunlin Yin, Maochen Ge Jan 2024

The Mechanism And Effect Of Seismic Source Location Using Double Waves In Three-Dimensional Microseismic Monitoring, Zhigang Wang, Xiaoqing Wang, Shunlin Yin, Maochen Ge

Mining Engineering Faculty Research & Creative Works

Accurate seismic source location has always been the most important purpose of micro seismic and seismic monitoring. The location accuracy inside the existing monitoring networks is generally high, whereas the accuracy in the external area and sensor accessories area tends to be low. This scenario contributes to an overall limitation in the effective monitoring area. The seismic source location was performed in this study using P waves and S waves to improve the location accuracy outside the monitoring networks and in the adjacent area and enlarge the high-accuracy control area of the monitoring networks. Moreover, the mechanism of seismic source …


Spatiotemporal Variance Image Reconstruction For Thermographic Inspections, Logan M. Wilcox, Emily M. Johnson, Emma T. Bohannon, Catherine E. Johnson, Kristen M. Donnell Jan 2024

Spatiotemporal Variance Image Reconstruction For Thermographic Inspections, Logan M. Wilcox, Emily M. Johnson, Emma T. Bohannon, Catherine E. Johnson, Kristen M. Donnell

Mining Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a nondestructive testing and evaluation (NDT&E) technique that utilizes a radiating antenna to induce a thermal increase on or within a specimen under test (SUT). The radiated power density is spatially nonuniform and therefore results in a spatially nonuniform thermal excitation, which may result in missed or false indications of defects. To this end, this work proposes a novel image reconstruction technique for nonuniform excitation/heating and is referred to as Spatiotemporal Variance Reconstruction (STVR). STVR utilizes the spatial and temporal variance of the surface thermal profile. STVR is advantageous in that it does not require …


Prompt, Accurate, And Noncontact Material Identification Using A Single Microwave Sensor With Machine Learning Analysis, Chen Zhu, Osamah Alsalman, Jie Huang Jan 2024

Prompt, Accurate, And Noncontact Material Identification Using A Single Microwave Sensor With Machine Learning Analysis, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Article, a Novel Approach to Microwave Sensors is Proposed and Demonstrated that Allows for Prompt, Accurate, and Noncontact Material Identification Even with Arbitrary Lift-Off Distances between the Sensor and the Material under Test (MUT). a Multilayer Perceptron (MLP) is Trained to Directly Learn the Relation of the Measured Reflection Spectra of a Homemade Open-Ended Coaxial Cable Resonator Probe with Respect to Different MUTs and Then Achieve One-To-One Mapping between a Measured Spectrum and the MUT. as a Proof-Of-Concept Demonstration, the Performance of the MLP Model is Tested using Easily Accessible Materials, Including Wood, Glass, Water, and Metal. Reflection …


Improved Peec Modeling Of Antennas Through Time-Dependent Partial Elements, Fabrizio Loreto, Giuseppe Pettanice, Martin Stumpf, Albert E. Ruehli, Jonas Ekman, Giulio Antonini Jan 2024

Improved Peec Modeling Of Antennas Through Time-Dependent Partial Elements, Fabrizio Loreto, Giuseppe Pettanice, Martin Stumpf, Albert E. Ruehli, Jonas Ekman, Giulio Antonini

Electrical and Computer Engineering Faculty Research & Creative Works

Over the Last Twenty Years, the Evolution of Communications Has Extended the Systems' Operating Frequency Range to the Tens of GHz. in This Framework, Time Domain Integral Equation-Based (TDIE) Methods for Antenna Modeling Have Gained Increasing Interest. among Them, the Partial Elements Equivalent Circuit (PEEC) Method Turns Out to Be Attractive for its Capability to Provide Compact Circuit Models. Similarly to Other Integral Equation-Based Methods, Like the Method of Moments (MoM) in the Time Domain (TD), the PEEC Method Can Suffer from Late-Time Instabilities. This Work Shows that a Rigorous Computation of the Time-Dependent Partial Elements Leads to an Improved …


Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan Jan 2024

Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Introduces a Novel Optimal Trajectory Tracking Control Scheme Designed for Uncertain Linear Discrete-Time (DT) Systems. in Contrast to Traditional Tracking Control Methods, Our Approach Removes the Requirement for the Reference Trajectory to Align with the Generator Dynamics of an Autonomous Dynamical System. Moreover, It Does Not Demand the Complete Desired Trajectory to Be Known in Advance, Whether through the Generator Model or Any Other Means. Instead, Our Approach Can Dynamically Incorporate Segments (Finite Horizons) of Reference Trajectories and Autonomously Learn an Optimal Control Policy to Track Them in Real Time. to Achieve This, We Address the Tracking Problem …


Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang Jan 2024

Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

We consider the time-restricted double-spending attack (TR-DSA) on the Proof-of-Work-based blockchain, where an adversary conducts a DSA within a finite timeframe and simultaneously launches multiple types of attacks on the blockchain. To be specific, the adversary can conduct attacks to isolate some honest miners and cause block propagation delays among miners to enhance the success probability of the TR-DSA. We first develop the closed-form expression for the success probability of a TR-DSA with the aid of multiple types of attacks, which is leveraged to develop the closed-form expression for the expected profit of a TR-DSA. The numerical analysis reveals that …


Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan Jan 2024

Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel lifelong integral reinforcement learning (LIRL)-based optimal trajectory tracking scheme using the multilayer (MNN) or deep neural network (Deep NN) for the uncertain nonlinear continuous-time (CT) affine systems subject to state constraints. A critic MNN, which approximates the value function, and a second NN identifier are together used to generate the optimal control policies. The weights of the critic MNN are tuned online using a novel singular value decomposition (SVD)-based method, which can be extended to MNN with the N-hidden layers. Moreover, an online lifelong learning (LL) scheme is incorporated with the critic MNN to mitigate …


A Hybrid Model-Based Data-Driven Framework For The Electromagnetic Near-Field Scanning, Yanming Zhang, Lijun Jiang Jan 2024

A Hybrid Model-Based Data-Driven Framework For The Electromagnetic Near-Field Scanning, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel hybrid approach for electromagnetic near-field scanning, combining model-based, i.e., Gaussian processes regression, and data-driven, i.e., dynamic mode decomposition, techniques. We first leverage the Latin hypercube sampling technique to achieve spatially sparse measurements. Subsequently, dynamic mode decomposition is applied to analyze the resulting spatiotemporal data with sparse spatial sampling, enabling the extraction of both frequency information and sparse dynamic modes. Finally, the Gaussian processes regression, also known as the Kriging method, is adopted for the full-state reconstruction. The proposed hybrid approach is benchmarked by an example of the crossed dipole antennas. The obtained results demonstrate that …


Impact Of Ai On The Hri Dynamic In Search And Rescue Operations Using Uav Swarms, Jordan Morrow, Maciej Jan Zawodniok, Anhar Sami Mohammed Jan 2024

Impact Of Ai On The Hri Dynamic In Search And Rescue Operations Using Uav Swarms, Jordan Morrow, Maciej Jan Zawodniok, Anhar Sami Mohammed

Electrical and Computer Engineering Faculty Research & Creative Works

Artificial intelligence (AI) offers significant benefits in search and rescue applications by enhancing the efficiency and effectiveness of the search. However, an over-reliance on AI can hinder the operation due to biases embedded in the underlying algorithms. This partiality, if left un-monitored, can pose a risk to the safety of those in need of disaster relief. Typically manifests into inaccuracies in the decision-making processes and if not carefully monitored can cause larger issues. This paper extends the knowledge presented in a previous work, which presents the design and modeling of search and rescue operations using unmanned aerial vehicle (UAV) swarms. …


Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria Jan 2024

Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) are advertised as great tool that benefits society and humanity. However, UAVs also pose significant security threats ranging from privacy invasions, to interfering with commercial aircraft landing and takeoff, to accidently crashing into vehicles or people, to military or terrorist attacks. Consequently, there is a pressing need to detect and identify UAVs to mitigate such potential risks. While image-based methods are crucial for UAV detection, radio frequency (RF) emissions offer additional valuable insights. Analyzing RF signals, such as those used in UAV-ground station communications, can provide information about UAV types based on distinct frequency usage or …


High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu Jan 2024

High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Optical fiber sensors have emerged as vital tools in various applications. Among them, Fabry-Perot interferometers (FPIs), have gained prominence due to their compactness and versatility in sensor design. Microwave photonics (MWP) techniques offer enhanced performance and flexibility for developing optical sensor interrogation methods. This paper proposes and experimentally demonstrates a novel MWP interrogation technique based on phase measurement for short-cavity FPI sensors. The technique utilizes the phase response of the FPI sensor within an MWP-assisted single radio frequency bandpass filter, providing improved sensitivity and dynamic sensing capabilities compared to traditional methods. Simulation and experimental results validate the effectiveness of the …


Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan Jan 2024

Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, a leader-follower tracking and formation control strategy for mobile robots (MRs) with uncertain dynamics is proposed. This strategy utilizes a continual lifelong safe reinforcement learning (CLSRL) framework based on multilayer neural networks (MNNs). The proposed design employs actor-critic MNNs, incorporating a barrier function. This function is derived from the Bellman optimality principle. It addresses the state constraints throughout the control design process. A novel online continual lifelong learning (CLL) method is introduced for MR formation. This method leverages the Bellman residual error for weight significance in MNNs. It addresses catastrophic forgetting and interlayer dependence through layer-specific regularizers. …


Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa Jan 2024

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 …


Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson Jan 2024

Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson

Electrical and Computer Engineering Faculty Research & Creative Works

This research introduces a recommendation system designed to enhance student success by intelligently personalizing the semester schedules and graduation path based on the student's performance, interests, and background; and inspired by the academic journeys of similar students who have successfully graduated in the past. The proposed recommender system leverages a combination of Markov decision processes, Q-Learning, and collaborative filtering techniques to identify graduation paths with a higher likelihood of success for the student. The proposed model is versatile and generic and can be adapted to various disciplines if sufficient past historical data is available. The proposed model has been prototyped …