Digital Commons Network^™

Simulation And Analysis Of Synthetic Aperture Radar Images, Jonathan Blackledge

Books/Book chapters

The principal model for an image, generated by the interaction of an incident wave field with an inhomogeneous medium, is based on the ‘weak scattering approximation’. This approximation forms the basis for image processing, analysis and image understanding associated with applications over a broad range of frequencies. The physical limitations of such a model are typically overcome by introducing an additional stochastic field term that takes into account those effects that do not conform to the weak scattering approximation, coupled with background ‘system noise’. In this chapter, a solution to the scattering problem is presented, which is based on an …

Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos

Academic Posters Collection

The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.

A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …

Synthetic Heart Sound Dataset, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Datasets

The repository contains synthetic heart sound recordings. The publication related to this dataset is "Exploring the impact of noise and degradations on heart sound classification models", Biomedical Signal Processing and Control journal.

Work In Progress: A Virtual Educational Robotics Coding Club Framework To Improve K-6 Students Emotional Engagement In Stem, Kate Carmody, Julie Booth, Jospehine Bleach, Pramod Pathak, Paul Styles

Conference papers

The growing popularity and deployment of Internet of Things (IoT) devices has led to serious security concerns. The integration of a security operations center (SOC) becomes increasingly important in this situation to ensure the security of IoT devices. In this article, we will present a summary of IoT device security issues, their vulnerabilities, a review of current challenges to keep these devices secure, and discuss the role that SOC can bring in protecting IoT devices while considering the challenges encountered and the directions to consider when implementing a reliable SOC for IoT monitoring.

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …

Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto

Williams Honors College, Honors Research Projects

The goal of this senior design/honors project is to create a device that monitors environmental conditions in order to detect a wildfire. This device should notify a user of the status of the environment. The device should also last for 6 months without any human interaction. My role on the team is to design the power supply system that maximizes efficiency and uses renewable energy.

Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil …

Transformer Leakage Inductance Design Methodology, Angshuman Sharma, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The leakage inductance exhibited by a transformer depends on its winding geometry, which generally involves the selection of several key design parameters in addition to the winding structure and the interleaving configuration. With few resources explaining the effects of these design choices on the observed leakage inductance, numerous trial-and-error iterations become necessary to realize the desired leakage inductance. This paper explores more than a hundred winding geometries feasible in a 2- winding transformer comprising the same magnetic core, number of turns, and wire gauge, and finds the leakage inductance for each unique design using 2-D finite element method (FEM) simulations …

Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper discusses a Bond Graph (BG) Structural Analysis Toolbox developed in MATLAB® (MATSAT) that performs causal analysis on the BG and assists the user in the sensor selection process for a multi-domain physical system. MATSAT contains modules for performing the Sequential Causality Assignment Procedure (SCAP) and Causal Path Search (CaPS). The modules can be combined to check for structural properties such as structural observability (SO) for any sensor set. The working of MATSAT is shown for standard systems. Verification of SCAP, CaPS, and necessary and sufficient SO conditions is shown.

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. …

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 …

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 …

Lifelong Learning Control Of Nonlinear Systems With Constraints Using Multilayer Neural Networks With Application To Mobile Robot Tracking, Irfan Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Presents a Novel Lifelong Multilayer Neural Network (MNN) Tracking Approach for an Uncertain Nonlinear Continuous-Time Strict Feedback System that is Subject to Time-Varying State Constraints. the Proposed Method Uses a Time-Varying Barrier Function to Accommodate the Constraints Leading to the Development of an Efficient Control Scheme. the Unknown Dynamics Are Approximated using a MNN, with Weights Tuned using a Singular Value Decomposition (SVD)-Based Technique. an Online Lifelong Learning (LL) based Elastic Weight Consolidation (EWC) Scheme is Also Incorporated to Alleviate the Issue of Catastrophic Forgetting. the Stability of the overall Closed-Loop System is Analyzed using Lyapunov Analysis. the …

Challenges And Prospects Of Vehicle Ota Spherical Near-Field Measurement Probes, Dao Lin, Zhanghua Cai, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Discusses the Issue of Measuring Probe Indicators for Large-Scale Equipment, Such as Automobiles, under Conditions of Offset Configuration. a Simulation of Spherical Near-Field Measurement based on an Offset Configuration is Presented in This Paper. the Measurement Error is Defined According to the Reference Data Calculated by Spherical Wave Expansion Theory. through Comparative Analysis of the Simulation Results, the Main Reason for the Measurement Error is the Insufficient Coverage of the Probe's Beamwidth. by Adjusting the Probe's Radiation Pattern using Simulation Software, an Optimized Probe that Satisfies Near-Field Measurement Requirements under Meter-Level Offset Conditions is Obtained. Finally, based on …

Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …

Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this communication, a novel deep learning (DL)-based solver is proposed for the electromagnetic forward (EMF) process. It is based on the complex-valued deep convolutional neural networks (DConvNets) comprising an encoder network and a corresponding decoder network with pixel-wise regression layer. The encoder network takes the incident EM wave and the contrast (permittivity) distribution of the object as the input. It channels the processed data into the corresponding decoder network to predict the total EM field due to the scatter of the input incident EM wave. The training of the proposed DConvNets is done using the simple synthetic dataset. Due …

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.

Electron Beam Treatment For The Removal Of 1,4-Dioxane In Water And Wastewater, Robert Pearce, Xi Li, John Vennekate, Gianluigi Ciovati, Charles Bott

Electrical & Computer Engineering Faculty Publications

Electron beam (e-beam) treatment uses accelerated electrons to form oxidizing and reducing radicals when applied to water without the use of external chemicals. In this study, electron beam treatment was used to degrade 1,4-dioxane in several water matrices. Removal improved in the progressively cleaner water matrices and removals as high as 94% to 99% were observed at a dose of 2.3 kGy in secondary effluent. 1,4-dioxane removal was confirmed to be primarily through hydroxyl radical oxidation. The calculated electrical energy per order was found to be 0.53, 0.26, and 0.08 kWh/m³/order for secondary effluent (Avg. total organic carbon …

Small Signal Stability Analysis Of Virtual Impedance Control In Islanded Microgrid, Oroghene Oboreh-Snapps, Kartikeya J.P. Veeramraju, Arnold Fernandes, Alvaro Cardoza, Angshuman Sharma, Jonathan Saelens, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper examines the impact of virtual impedance control in an inverter-dominated microgrid (MG) system. the goal is to provide a clear understanding of Virtual Impedance (VI) control toward MG stability. This analysis is performed by developing the system's Small-Signal Model (SSM) and studying the poles' trajectory change when the system's key control parameters are varied. the results indicate that VI will benefit system stability when considering MG with low X/R while negatively affecting MG with high X/R. Also, there is a trade-off between the coupling impedance of the inverter and the VI parameters, which needs to be considered when …

Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This communication proposes a novel deep learning (DL) approach to solve electromagnetic inverse scattering (EMIS) problems in inhomogeneous media. The conventional approaches for solving inhomogeneous EMIS problems generally have to consider inhomogeneous Green’s functions or conduct approximation operations to media, which inevitably introduces various challenges, including complex mathematical derivation, high computation cost, unavoidable nonlinearity, and even strong ill-posedness. To avoid these challenges, we propose a DL approach based on the complex-valued deep convolutional neural networks (DConvNets), which comprise the deep convolutional encoder–decoder (DCED) structure. Its training data are collected based on the simple synthetic dataset. While the scattered fields received …

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 …

A Real-Time Microwave Camera Prototype With Zero-Bias Diode Detectors For Emi Source Imaging, Xin Yan, Liang Liu, Victor Khilkevich

Electrical and Computer Engineering Faculty Research & Creative Works

Emission Source Microscopy (ESM) Could Be Utilized to Localize the Electromagnetic Interference (EMI) Sources that Contribute to the Far-Field Radiation. in Those Cases, the Electrical Field over a Two-Dimensional Plane is Collected by Mechanical Scanning, Resulting in a Long Measurement Time and the Presence of Mechanical Errors. in This Work, a Microwave Camera based on a Two-Dimensional Array of Elliptical Slot Antennas and Diode Detectors is Presented. Multiplexers Are Utilized to Access the Output of Each Detector and the Scanning of the Whole Array Could Be Done Multiple Times Per Second.

Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately …

An Unmanned Aircraft System For Marking Live Power Lines To Prevent Bird Collisions, Mattheuns D. Pretorius, Lourens Leeuwner, Kaajial Durgapersad, Constant Hoogstad, Peter Beckedahl, Michael D. Michael, Kishaylin Chetty

Human–Wildlife Interactions

Collisions with overhead power lines represent a significant cause of mortality for a number of large bird species worldwide. Certain threatened species are severely impacted by power line collisions, particularly those for which there are no other known significant threats. In South Africa, bird collisions with overhead power line cables, including collisions with phase conductors and shield wires, contribute significantly to annual threatened bird species mortalities associated with Eskom power lines. The most practical mitigation measure is to attach bird anti-collision devices as markers on the cables. Current marking methods involve installations by hand, where linemen are hoisted up to …

Automatic Data-Driven Partitioned Modeling Of Power System Dynamics With Smart Power Electronic Inverters, Sunil Subedi

Electronic Theses and Dissertations

The primary aim of this dissertation is to provide an efficient statistical modeling and simulation technique for extracting the dynamics of converter-dominated power systems (CDPS) with the device level details using the least amount of computation time while maintaining a reasonable level of accuracy. These test cases are intended for use by power system researchers that need to develop test cases that can perform accurate dynamic analysis on a high integration of inverter-based resources (IBRs) for stability analysis while speeding up simulation time and reducing computational complexity. Additionally, utilities/grid operators must properly plan, operate, and dispatch. Case studies that can …

Interval Analysis Method For The Uncertainty And Sensitivity Characterization In Transmission Line Systems, Ping Yuan, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Uncertainty in electronic fabrication process could cause serious yield issues and stability concerns. Hence, identifying the resultant range caused by the uncertainty in the system is a critical topic in modern EDA design process. Monte Carlo method is considered as a golden standard but with many drawbacks. In the paper, we propose to use the interval analysis (IA) to analyze the signal integrity and power integrity problems in transmission line (TL) systems. Using the interval representing the uncertainty range of parameters in the system, the uncertainty range of the system can be derived by the derived analytical expression. It is …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya

Dissertations, Master's Theses and Master's Reports

Increased Printed Circuit Board (PCB) route complexity and density combined with the growing demand for low-scale rapid prototyping has increased the desire for Automated Optical Inspection (AOI) that reduces prototyping time and production costs by detecting defects early in the production process. Traditional defect detection method of human visual inspection is not only error prone but is also time-consuming given the growing complex and dense circuitry of modern-day electronics. Electric contact-based testing, either in the form of a bed of nails testing fixture or a flying probe system, is costly for low-rate rapid prototyping. An AOI is a non-contact test …