Engineering Commons^™

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

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

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

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

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

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 …

Valorization Of Spent Vetiver Roots For Biochar Generation, Sameer Neve, Dibyendu Sarkar, Manas Warke, Teresa Bandosz, Rupali Datta

Michigan Tech Publications

Vetiver root is widely used to produce essential oils in the aromatherapy industry. After the extraction of oil, the roots are disposed of as waste. The central objective of this research was to explore the conversion of this waste into a resource using a circular economy framework. To generate biochar, vetiver roots were pyrolyzed at different temperatures (300, 500, and 700 °C) and residence times (30, 60, and 120 min). Analysis showed the root biochar generated at 500 °C and held for 60 min had the highest surface area of 308.15 m2/g and a yield of 53.76%, in addition to …

Radiation Force Modeling For A Wave Energy Converter Array, Salman Husain, Gordon Parker, David Forehand, Enrico Anderlini

Michigan Tech Publications

The motivation and focus of this work is to generate passive transfer function matrices that model the radiation forces for an array of WECs. Multivariable control design is often based on linear time-invariant (LTI) systems such as state-space or transfer function matrix models. The intended use is for designing real-time control strategies where knowledge of the model’s poles and zeros is helpful. This work presents a passivity-based approach to estimate radiation force transfer functions that accurately replace the convolution operation in the Cummins equation while preserving the physical properties of the radiation function. A two-stage numerical optimization approach is used, …

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

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 …

Gamma Amplitude-Envelope Correlations Are Strongly Elevated Within Hyperexcitable Networks In Focal Epilepsy, Manoj Raghavan, Jared Pilet, Chad Carlson, Christopher T. Anderson, Wade Mueller, Sean Lew, Candida Ustine, Priyanka Shah-Basak, Vahab Youssofzadeh, Scott A. Beardsley

Biomedical Engineering Faculty Research and Publications

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40–200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that …

Designing A Use-Error Robust Machine Learning Model For Quantitative Analysis Of Diffuse Reflectance Spectra, Allison Scarbrough, Keke Chen, Bing Yu

Biomedical Engineering Faculty Research and Publications

Significance

Machine learning (ML)-enabled diffuse reflectance spectroscopy (DRS) is increasingly used as an alternative to the computation-intensive inverse Monte Carlo (MCI) simulation to predict tissue’s optical properties, including the absorption coefficient,μaand reduced scattering coefficient, μs′.

Aim

We aim to develop a use-error-robust ML algorithm for optical property prediction from DRS spectra.

Approach

We developed a wavelength-independent regressor (WIR) to predict optical properties from DRS data. For validation, we generated 1520 simulated DRS spectra with the forward Monte Carlo model, where μa=0.44 to 2.45cm−1, and μs′=6.53 to 9.58cm−1. We introduced common use-errors, such as wavelength miscalibrations and intensity fluctuations. Finally, we …

Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches Da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak

Faculty, Staff and Student Publications

Genetically modified (GM) crops that have been engineered to express transgenes have been in commercial use since 1995 and are annually grown on 200 million hectares globally. These crops have provided documented benefits to food security, rural economies, and the environment, with no substantiated case of food, feed, or environmental harm attributable to cultivation or consumption. Despite this extensive history of advantages and safety, the level of regulatory scrutiny has continually increased, placing undue burdens on regulators, developers, and society, while reinforcing consumer distrust of the technology. CropLife International held a workshop at the 16th International Society of Biosafety Research …

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

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

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

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

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

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

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

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

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

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

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

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 …

Highly Sensitive Liquid-Level Sensing Based On Microwave Frequency Domain Reflectometry And Interferometry, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency domain reflectometry (FDR) and interferometry are two widely used investigative techniques that have been instrumented using optical and microwave devices for a diverse array of sensing applications. In this paper, we present a highly sensitive liquid-level sensor using a custom hollow coaxial cable transmission line. Measurements of liquid levels with high sensitivity and resolution can be achieved by both FDR and interferometry-based measurements using the same sensor device. We show that FDR-based measurements are more straightforward for liquid-level sensing and are suitable for both small and large variations of liquid level, while interferometry-based measurements provide slightly higher measurement resolution …

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 …

On The Feasibility Of A Direct Injection Probe With A Capacitively Coupled Return And Integrated Voltage Monitor, Aaron Harmon, Daniel Szanto, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Characterizing the susceptibility of an IC while it is integrated within a system can be challenging. Characterization is even harder if one wants to know the waveform at the target IC pin when injecting a signal on the pin. In this work, the feasibility of a direct injection probe with a capacitively coupled return and integrated voltage monitor is proposed. This probe is advantageous because it does not need to be soldered to the test device and its ability to provide a measurement of the waveform on the target IC pin during the injection. Methods for reconstructing the pin waveform …

Evaluating Electromagnetic Interference Effects On Gnss Receivers, Giorgi Tsintsadze, Haran Manoharan, Arushi Sahai, Daryl G. Beetner, Brian Booth

Electrical and Computer Engineering Faculty Research & Creative Works

Electromagnetic interference can be highly disruptive to global navigation satellite system (GNSS) receivers. Interference can be intentional but can also occur from electronics modules placed within the same system, where these modules may create sufficient unintended radiated emissions to disrupt GNSS operation. In this paper, GNSS receiver performance is evaluated in the presence of multi-tone interference. An expression for the GNSS correlator output in the presence of continuous wave interference (CWI) is derived and is extended to predict the carrier to noise density ratio, C/N0, of the receiver in the presence of multi-tone interference. C/N0 is widely used for characterizing …

Design Of Experiment Analysis On Multiple Pim Sources In An Rf Antenna System, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Passive intermodulation (PIM) has been identified as one of the common root causes for receiving sensitivity degradation (desense) on radiofrequency (RF) antennas working in frequency-division duplex mode. The component-level PIM characterization and simulation have been well-established over the years. However, the study has been using an ideal 50 Ω transmission line system while antenna modules are more complicated than a simple transmission line structure. Moreover, the metallic contacts can exist in multiple locations with different connection topologies in real applications. This paper provides a method to simulate the PIM performance caused by the metallic contacts in a practical environment. In …