Engineering Commons^™

Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Scalability is essential for next generation blockchain technology to integrate with large mobile networks like Internet of Things (IoT). The IOTA distributed ledger protocol has combined transaction generation and verification to address this, but at the expense of increased reliance on connectivity to resolve conflicts with a novel ledger data structure. Intelligent Ledger Construction (ILC) was proposed as an auditable lightweight reinforcement-learning scheme to address this constraint with proposal of local conflict resolution with machine-learning classification. This effort presents an improved reliability reward model to enhance training for ILC and further reduce adversarial gaming and resource usage. Testing this revision …

Advances In Fiber-Optic Extrinsic Fabry-Perot Interferometric Physical And Mechanical Sensors: A Review, Chen Zhu, Hongkun Zheng, Lingmei Ma, Zheyi Yao, Bo Liu, Jie Huang, Yunjiang Rao

Electrical and Computer Engineering Faculty Research & Creative Works

Fabry-Perot Interferometers Have Found a Multitude of Scientific and Industrial Applications Ranging from Gravitational Wave Detection, High-Resolution Spectroscopy, and Optical Filters to Quantum Optomechanics. Integrated with Optical Fiber Waveguide Technology, the Fiber-Optic Fabry-Perot Interferometers Have Emerged as a Unique Candidate for High-Sensitivity Sensing and Have Undergone Tremendous Growth and Advancement in the Past Two Decades with their Successful Applications in an Expansive Range of Fields. the Extrinsic Cavity-Based Devices, I.e., the Fiber-Optic Extrinsic Fabry-Perot Interferometers (EFPIs), Enable Great Flexibility in the Design of the Sensitive Fabry-Perot Cavity Combined with State-Of-The-Art Micromachining and Conventional Mechanical Fabrication, Leading to the Development of …

Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …

Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Proposes a Decentralized and Coordinated Voltage and Frequency (V-F) Control Framework for Islanded Microgrids, with Full Consideration of the Limited Capacity of Distributed Energy Resources (DERs) and V-F Dependent Load. First, the Concept of DER Inadequacy is Illustrated with the Challenges It Poses. Then, a Decentralized and Coordinated Control Framework is Proposed to Regulate the Output of Inverter-Based Generations and Reallocate Limited DER Capacity for V-F Control. the Control Framework is Composed of a Power Regulator and a V-F Regulator, Which Generates the Supplementary Signals for the Primary Controller. the Power Regulator Regulates the Output of Grid-Forming Inverters …

Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …

Topologically Optimized Electrodes For Electroosmotic Actuation, Jianwen Sun, Jianyu Zhang, Ce Guan, Teng Zhou, Shizhi Qian, Yongbo Deng

Mechanical & Aerospace Engineering Faculty Publications

Electroosmosis is one of the most used actuation mechanisms for the microfluidics in the current active lab-on-chip devices. It is generated on the induced charged microchannel walls in contact with an electrolyte solution. Electrode distribution plays the key role on providing the external electric field for electroosmosis, and determines the performance of electroosmotic microfluidics. Therefore, this paper proposes a topology optimization approach for the electrodes of electroosmotic microfluidics, where the electrode layout on the microchannel wall can be determined to achieve designer desired microfluidic performance. This topology optimization is carried out by implementing the interpolation of electric insulation and electric …

Thermal Diffusivity Materials Characterization Via Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a relatively new nondestructive evaluation method which is proposed in this work for thermal materials characterization. Specifically, AMT is investigated as a single-sided measurement option for out-of-plane thermal diffusivity (a parameter traditionally measured using a two-sided technique). Simulation and measurement results support the use of AMT for such a characterization for materials backed by an electromagnetically absorptive material. Both lossless and lossy materials may be measured, with better accuracy for lossless materials. The effect of heating time was also considered. The results indicate that for the 50 W system used here, 100 seconds of electromagnetic …

Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht

Electrical and Computer Engineering Faculty Research & Creative Works

Wearable medical devices are widely used for monitoring and treatment of patients. Electrostatic discharge can render these devices unreliable and cause a temporary or permanent disturbance in their operation. In a healthcare environment, severe electrostatic discharge (ESD) can occur while a patient, lying down or sitting on a hospital bed with a wearable device, discharges the device via a grounded bedframe. To protect the devices from ESD damage, the worst-case discharge conditions in the usage environment need to be identified. Previous studies by authors revealed that such events could be more severe than the conventional human metal model (HMM). However, …

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 …

Modeling And Mitigation Of Radio Frequency Interference For Wireless Devices, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

This article reviews the electromagnetic framework used to model radio frequency interference (RFI) and the resulting development of mitigation methods. With the rise of IoT devices, wireless devices in which RF antennas are integrated with high-performance digital systems in small form factors suffer from electromagnetic interference, known as RF interference or RF desensitization. The simple yet rigorous framework can be used for a systematic RFI-aware design, saving time and effort for trial-and-error troubleshooting.

Single Image Super Resolution Using Deep Attention Network, Jagrati Talreja

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis introduces two innovative frameworks for Single Image Super Resolution (SISR) that enhances image quality while optimizing computational efficiency. The motivation for this research is driven by the need to overcome the limitations of current SISR techniques like capturing long-range dependencies, enhancing multi-scale feature learning, mitigating over-smoothing, and managing computational demands. The choice to incorporate attention mechanisms in both frameworks is motivated by their proven ability to allow the model to focus on the most relevant parts of the image, thereby improving the reconstruction of high-resolution details from low-resolution inputs. By integrating attention mechanisms with inception blocks, the proposed …

A Review Of Piezoelectric Footwear Energy Harvesters: Principles, Methods, And Applications, Bingqi Zhao, Feng Qian, Alexander Hatfield, Lei Zuo, Tian-Bing Xu

Mechanical & Aerospace Engineering Faculty Publications

Over the last couple of decades, numerous piezoelectric footwear energy harvesters (PFEHs) have been reported in the literature. This paper reviews the principles, methods, and applications of PFEH technologies. First, the popular piezoelectric materials used and their properties for PEEHs are summarized. Then, the force interaction with the ground and dynamic energy distribution on the footprint as well as accelerations are analyzed and summarized to provide the baseline, constraints, potential, and limitations for PFEH design. Furthermore, the energy flow from human walking to the usable energy by the PFEHs and the methods to improve the energy conversion efficiency are presented. …

Panel: Faculty Leadership, Lina Karam, Georges Zissis, Jason Yao, Jill Nelson, Minho Jo, Rafal Sliz, Michele Nogueira, Steve Watkins, Huihui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

This faculty leadership panel will be held jointly by the IEEE Education Society (IEEE EdSoc) and IEEE Educational Activities Board (EAB) Faculty Resources Committee (FRC). The panel intends to provide participants introductory knowledge and skills. Two moderators and four panelists will focus on discussing their various academic leadership experiences and practices. The panel will be held in an interactive way so that the participants will have enough time to ask questions or communicate with the panelists. It is expected that this joint panel may potentially help to build up networks and mentorships.

Highly Sensitive Humidity Sensor Based On Optical Fiber Fabry-Perot Interferometer, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

An ultra-sensitive optical fiber humidity sensor based on an extrinsic Fabry-Perot interferometer is proposed and experimentally demonstrated in this paper. the Fabry-Perot cavity is constructed by a section of humidity-sensitive metal-paper coil and an optical fiber end face. Taking advantage of the hydrophilicity of the metal-paper coil, the cavity length of the Fabry-Perot cavity varies with humidity due to the deflection of the metal-paper section. the fabricated sensor shows a linear response to relative humidity (RH) spanning from 50%RH to 73%RH. More prominently, an ultra-high sensitivity of 32.5 μm%RH (change in cavity length/change in RH) or 63.5 nm%RH (wavelength shift/change …

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 …

Machine Learning Based Pcb/Package Stack-Up Optimization For Signal Integrity, Wenchang Huang, Jiahuan Huang, Minseok Kim, Bumhee Bae, Chulsoon Hwang, Subin Kim

Electrical and Computer Engineering Faculty Research & Creative Works

PCB/package stack-up design optimization is time-consuming and requiring a great deal of experience. Although some iterative optimization algorithms are applied to implement automatic stack-up design, evaluating the results of each iteration is still time-intensive. This paper proposes a combined Bayesian optimization-artificial neural network (BO-ANN) algorithm, utilizing a trained ANN-based surrogate model to replace a 2D cross-section analysis tool for fast PCB/package stack-up design optimization. With the acceleration of ANN, the proposed BO-ANN algorithm can finish 100 iterations in 40 seconds while achieving the target characteristic impedance. To better generalize the BO-ANN algorithm, a strategy of effective dielectric calculation is applied …

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.

Aerial Lidar-Based 3d Object Detection And Tracking For Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa, Hichem Besbes, Yehia Massoud

Electrical and Computer Engineering Faculty Research & Creative Works

The proliferation of Light Detection and Ranging (LiDAR) technology in the automotive industry has quickly promoted its use in many emerging areas in smart cities and internet-of-things. Compared to other sensors, like cameras and radars, LiDAR provides up to 64 scanning channels, vertical and horizontal field of view, high precision, high detection range, and great performance under poor weather conditions. In this paper, we propose a novel aerial traffic monitoring solution based on Light Detection and Ranging (LiDAR) technology. By equipping unmanned aerial vehicles (UAVs) with a LiDAR sensor, we generate 3D point cloud data that can be used for …

Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The intelligent and autonomous learning of patients' activities will lead to an incredible progression toward future smart e-health systems. With the recent advances in artificial intelligence, signal processing, and computational capabilities; light detection and ranging (LiDAR) technology can play a significant role in enhancing the current patients' activity recognition (PAR) systems. In this paper, we propose confidential and accurate patient arms behavior monitoring using a standalone three-dimensional (3D) LiDAR sensor. Due to the unavailability of LiDAR data, we use a computer-programmed 3D simulator to generate virtual-LiDAR (V-LiDAR) 3D point cloud data that simulates real patient movements. These virtual data are …

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 …

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 …

Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …

Intelligent Control Schemes For Maximum Power Extraction From Photovoltaic Arrays Under Faults, Azhar Ul-Haq, Shah Fahad, Saba Gul, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Investigation of power output from PV arrays under different fault conditions is an essential task to enhance performance of a photovoltaic system under all operating conditions. Significant reduction in power output can occur during various PV faults such as module disconnection, bypass diode failure, bridge fault, and short circuit fault under non-uniform shading conditions. These PV faults may cause several peaks in the characteristics curve of PV arrays, which can lead to failure of the MPPT control strategy. In fact, impact of a fault can differ depending on the type of PV array, and it can make the control of …

Advancing Aluminum Casting Optimization With Real-Time Temperature And Gap Measurements Using Optical Fiber Sensors At The Metal-Mold Interface, Bohong Zhang, Abhishek Prakash Hungund, Dinesh Reddy Alla, Deva Prasaad Neelakandan, Muhammad Roman, Ronald J. O'Malley, Laura Bartlett, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

Accurate measurement of interfacial heat transfer during casting solidification is crucial for optimizing metal solidification processes. The gap between the mold wall and the casting surface plays a significant role in heat transfer and cooling rates. In this study, two innovative fiber-optic sensors are employed to measure real-time mold gaps and thermal profiles during the solidification of A356 aluminum in a permanent mold casting. The experimental setup consists of a specially designed mold system made of unheated, uncoated tool steel, which facilitates easy installation of the fiber-optic sensors. An Extrinsic Fabry-Perot interferometric (EFPI) sensor is utilized to monitor the evolving …

In Situ High-Temperature Raman Spectroscopy Via A Remote Fiber-Optic Raman Probe, Bohong Zhang, Hanok Tekle, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

This Study Demonstrated for the First Time an in Situ High-Temperature Fiber-Optic Raman Probe to Study the Structure of Glass and Slag Samples at Temperatures Up to 1400 °C. a Customized External Telescope Was Integrated into a Portable Fiber-Optic Raman Probe to Extend the Optical Working Distance to Allow the Probe to Work in a High-Temperature Environment. Three Samples Were Evaluated to Demonstrate the Functionality of the High-Temperature Fiber-Optic Raman Probe. Room Temperature and High-Temperature Raman Spectra Were Successfully Collected and Analyzed. in Addition, a Deconvolution Algorithm Was Used to Identify Peaks in the Spectrum that Could Then Be Related …

A Methodology For Predicting Improved Dipole Source Configurations From Near-Field Scan Data, Hossein Rezaei, Xin Yan, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Equivalent sources found from near-electric and magnetic field scans are often used to predict and solve interference problems. While there are many ways to represent the source, the user lacks the ability to determine which of the many possible source configurations is more likely to represent the "true" source, and thus accurately represent field data outside the measurement area and in the presence of typical measurement errors. A methodology is proposed for estimating which of many possible dipole source representations of near-field scan data are likely to give better estimates of fields outside the measurement scan plane when utilizing imperfect …

An Extended Generalized Average Modeling Framework For Power Converters, Kartikeya Jayadurga Prasad Veeramraju, Jacob A. Mueller, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Generalized Averaged Modeling (GAM) technique is traditionally employed to capture the dynamic performance of power electronic converters. This paper proposes an improved version of it, named the Extended-GAM (EGAM) technique, which supports the multiplication of two Double Fourier Series (DFS) signals in the time domain. Multiplication of DFS signals in the time domain translates to the 2D-convolution of coefficients of the DFS terms of their equivalent Discrete Fourier Image (DFI) representations. Thus, the proposed EGAM technique, capable of capturing many harmonics present in the output of a power converter, effectively captures the dynamic behavior of power converters excited by …

Filter-Based Fault Detection And Isolation In Distributed Parameter Systems Modeled By Parabolic Partial Differential Equations, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations (PDE). A filter based observer is designed based on the linear PDE representation using which a detection residual is generated. A fault is detected when the magnitude of the detection residual exceeds a detection threshold. Upon detection, several isolation estimators are designed using filters whose output residuals are compared with predefined isolation thresholds. A fault …

Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones

Theses and Dissertations--Electrical and Computer Engineering

There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual …