Other Electrical and Computer Engineering Commons^™

Bearing Health Detector, Natalie N. Tokhmakhian, Alexander J. Davis

Electrical Engineering

Bearings, a common component in rotating machinery, are essential components of modern rotating machines; thus, monitoring their health is crucial when reducing downtime and boosting production efficiency. The Bearing Health Detector (BHD), a hand-held device, captures and processes the sound of a machine under test in real time and estimates the level of wear and tear by comparing the sound to previous tests. The BHD encompasses audiences involved with roller bearings in rotating machinery and is designed to provide the diagnosis of wear through the universal detection of good, satisfactory, and very poor with the following color scheme: green, yellow, …

Enhancing Telecom Churn Prediction: Adaboost With Oversampling And Recursive Feature Elimination Approach, Long Dinh Tran

Master's Theses

Churn prediction is a critical task for businesses to retain their valuable customers. This paper presents a comprehensive study of churn prediction in the telecom sector using 15 approaches, including popular algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, and AdaBoost.

The study is segmented into three sets of experiments, each focusing on a different approach to building the churn prediction model. The model is constructed using the original training set in the first set of experiments. The second set involves oversampling the training set to address the issue of imbalanced data. Lastly, the third set …

A Novel Graph Neural Network-Based Framework For Automatic Modulation Classification In Mobile Environments, Pejman Ghasemzadeh

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Automatic modulation classification (AMC) refers to a signal processing procedure through which the modulation type and order of an observed signal are identified without any prior information about the communications setup. AMC has been recognized as one of the essential measures in various communications research fields such as intelligent modem design, spectrum sensing and management, and threat detection. The research literature in AMC is limited to accounting only for the noise that affects the received signal, which makes their models applicable for stationary environments. However, a more practical and real-world application of AMC can be found in mobile environments where …

The Use Of Scattering Cancellation To Cloak And Decouple Slot Antennas And Antenna Arrays, Daniel Ferro

Honors Theses

The concept of cloaking has been prevalent in emerging research, being able to hide oneself completely from outside observers would be a huge benefit for covert surveillance and other fields. This idea has expanded past optical invisibility into the field of electromagnetic invisibility. To accomplish this form of cloaking, a non-natural material, called metamaterials, must be used. Furthermore, metamaterials can be used in a variety of different techniques including transformation-based cloaking, transmission line cloaking, and scattering cancellation cloaking. One application of cloaking is to use scattering cancellation to decouple two antennas that are placed too closely together such as in …

Design Of High-Power Ultra-High-Speed Permanent Magnet Machine, Md Khurshedul Islam

Theses and Dissertations

The demand for ultra-high-speed machines (UHSM) is rapidly growing in high-tech industries due to their attractive features. A-mechanically-based-antenna (AMEBA) system is another emerging application of UHSM. It enables portable wireless communication in the radio frequency (RF)-denied environment, which was not possible until recently. The AMEBA system requires a high-power (HP) UHSM for its effective communication performance. However, at the expected rotational speed range of 0.5 to 1 million rpm, the power level of UHSM is limited, and no research effort has succeeded to improve the power level of UHSM.

The design of HP-UHSM is highly iterative, and …

Unobtrusive Data Collection In Clinical Settings For Advanced Patient Monitoring And Machine Learning, Walker Arce

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

When applying machine learning to clinical practice, a major hurdle that will be encountered is the lack of available data. While the data collected in clinical therapies is suitable for the types of analysis that are needed to measure and track clinical outcomes, it may not be suitable for other types of analysis. For instance, video data may have poor alignment with behavioral data, making it impossible to extract the videos frames that directly correlate with the observed behavior. Alternatively, clinicians may be exploring new data modalities, such as physiological signal collection, to research methods of improving clinical outcomes that …

Dense & Attention Convolutional Neural Networks For Toe Walking Recognition, Junde Chen, Rahul Soangra, Marybeth Grant-Beuttler, Y. A. Nanehkaran, Yuxin Wen

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are …

Comparison Of Facial Emotion Recognition Models Using Deep Learning, Arsany Hanin

LSU New Orleans Theses and Dissertations

Facial emotion recognition is a widely studied area with applications in diverse domains such as human-computer interaction, affective computing, and social robotics. This thesis aims to improve the accuracy of facial emotion recognition models by incorporating a second neural network trained on original probabilities and probability transformation, while also comparing the performance of different techniques. The thesis begins with a thorough review of available datasets and technologies used for data collection, highlighting the challenges associated with these datasets. A detailed analysis of various facial emotion detection models, including the baseline model and its different architectures, is presented. The thesis also …

Modeling And Visualization Of Competing Escalation Dynamics: A Multilayer Multiagent Network Approach, Josh Allen

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Recent advances in military technology, such as hypersonic missiles, which can travel at more than five times the speed of sound and descend quickly into the atmosphere, give world nuclear superpowers a new edge. These advances up the game for nuclear superpowers with an extremely rapid, intense burst of military striking capability to secure upfront gains before encountering potentially overwhelming military confrontation. However, this so-called fait accompli has not been systematically studied by the United States in the perspective of the escalation philosophies of nuclear power competitors, or the mathematical modeling and visualization of multi-modal escalation dynamics. This gap may …

Procedural City Generation With Combined Architectures For Real-Time Visualization, Griffin Poyck

All Theses

The work and research of this paper sought to build upon traditional city generation and simulation in creating a tool that both realistically simulates cities and their prominent features and also creates aesthetic and artistically rich cities using assets that combine several contemporary or near contemporary architectural styles. The major city features simulated are the surrounding terrain, road networks, individual buildings, and building placement. The tools used to both create and integrate these features were created in Houdini with Unreal Engine 5 as the intended final destination. This research was influenced by the city, town, and road networking of Ghost …

A Study Of Iot-Optimized Low Power Asset Tracking With Cloud-Enabled Lorawan, Fatima Salman

Symposium of Student Scholars

The world of technology is expanding very quickly today, including technologies like cloud-based asset monitoring, but this makes it difficult to keep up with this technology's development and many other things. It is possible to monitor and manage your assets remotely with a cloud-based system thanks to its many features. The lifecycle of any commodity, including inventory, machinery, vehicles, and real estate, can be tracked using this kind of cloud-based system. Wide-area networks can be used to send data with the aid of low-power wide-area network (LPWAN) technologies like LoRa, SigFox, and NB-IoT. This project will examine traditional, cloud-based, LPWAN-based …

Region-Specified Inverse Design Of Absorption And Scattering In Nanoparticles By Using Machine Learning, Alex Vallone, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

Machine learning provides a promising platform for both forward modeling and the inverse design of photonic structures. Relying on a data-driven approach, machine learning is especially appealing for situations when it is not feasible to derive an analytical solution for a complex problem. There has been a great amount of recent interest in constructing machine learning models suitable for different electromagnetic problems. In this work, we adapt a region-specified design approach for the inverse design of multilayered nanoparticles. Given the high computational cost of dataset generation for electromagnetic problems, we specifically investigate the case of a small training dataset, enhanced …

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

A Parametric Numerical Analysis Investigation To Optimize The Performance Of The Ranque-Hilsch Vortex Tube, Muneer Ahmad Sungur

Theses

A vortex tube is a device that separates compressed air into two streams: one with a higher temperature (hot stream) and the other with a lower temperature (cold stream). It is a popular cooling option because it is small, safe, and affordable. The main objective of this thesis is to examine the energy separation performance of RHVT by varying the internal tapering angles of convergent angles (2°, 1.75°, 1.5°, 1.25°, 1°, 0.75°, and 0.5°), straight angles (0°), and divergent angles (0.5°, 1°, 2°, 4°, and 6°), While the cold mass fraction is constant (0.317). Length-to-diameter ratio (Lt/Dt), inlet pressure, and …

Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus

Engineering Faculty Articles and Research

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …

Implementing Commercial Inverse Design Tools For Compact, Phase-Encoded, Plasmonic Digital Logic Devices, Michael Efseaff, Kyle Wynne, Krishna Narayan, Mark C. Harrison

Engineering Faculty Articles and Research

Numerical simulations have become an essential design tool in the field of photonics, especially for nanophotonics. In particular, 3D finite-difference-time-domain (FDTD) simulations are popular for their powerful design capabilities. Increasingly, researchers are developing or using inverse design tools to improve device footprints and performance. These tools often make use of 3D FDTD simulations and the adjoint optimization method. We implement a commercial inverse design tool with these features for several plasmonic devices that push the boundaries of the tool. We design a logic gate with complex design requirements as well as a y-splitter and waveguide crossing. With minimal code changes, …

Utilizing Inverse Design To Create Plasmonic Waveguide Devices, Michael Efseaff, Kyle Wynne, Mark C. Harrison

Engineering Faculty Articles and Research

In modern communications networks, data is transmitted over long distances using optical fibers. At nodes in the network, the data is converted to an electrical signal to be processed, and then converted back into an optical signal to be sent over fiber optics. This process results in higher power consumption and adds to transmission time. However, by processing the data optically, we can begin to alleviate these issues and surpass systems which rely on electronics. One promising approach for this is plasmonic devices. Plasmonic waveguide devices have smaller footprints than silicon photonics for more compact photonic integrated circuits, although they …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Low-Power Redundant-Transition-Free Tspc Dual-Edge-Triggering Flip-Flop Using Single-Transistor-Clocked Buffer, Zisong Wang, Peiyi Zhao, Tom Springer, Congyi Zhu, Jaccob Mau, Andrew Wells, Yinshui Xia, Lingli Wang

Engineering Faculty Articles and Research

In the modern graphics processing unit (GPU)/artificial intelligence (AI) era, flip-flop (FF) has become one of the most power-hungry blocks in processors. To address this issue, a novel single-phase-clock dual-edge-triggering (DET) FF using a single-transistor-clocked (STC) buffer (STCB) is proposed. The STCB uses a single-clocked transistor in the data sampling path, which completely removes clock redundant transitions (RTs) and internal RTs that exist in other DET designs. Verified by post-layout simulations in 22 nm fully depleted silicon on insulator (FD-SOI) CMOS, when operating at 10% switching activity, the proposed STC-DET outperforms prior state-of-the-art low-power DET in power consumption by 14% …

Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi

Electronic Theses and Dissertations

Smart and intelligent devices are being integrated more and more into day-to-day life to perform a multitude of tasks. These tasks include, but are not limited to, job automation, smart utility management, etc., with the aim to improve quality of life and to make normal day-to-day chores as effortless as possible. These smart devices may or may not be connected to the internet to accomplish tasks. Additionally, human-machine interaction with such devices may be touch-screen based or based on voice commands. To understand and act upon received voice commands, these devices require to enhance and distinguish the (clean) speech signal …

The Wideband Tunability Of Double Gunn Diodes, Latarence Butts, Samir M. El-Ghazaly

Electrical Engineering Faculty Publications and Presentations

Gunn diodes use the Ridley–Watkins–Hilsum effect to generate low noise millimeter wave signals for communication and sensing applications. However, Monte Carlo calculations indicate that the velocity–field characteristics of compensated GaAs contain a second peak due to phonon scattering. A novel device that leverages this double Ridley–Watkins–Hilsum effect to achieve ultra-wideband tunability of low-noise millimeter waves is proposed in this article. The second region of negative differential mobility is gradually introduced in seven mobility profiles, which are each simulated in eight device lengths. It is found that a 2.5 μm Gunn diode with a compensation ratio of 0.6 operating at …

Machine Learning Techniques For Stock Price Prediction And Graphic Signal Recognition, Junde Chen, Yuxin Wen, Y. A. Nanehkaran, M. D. Suzauddola, Weirong Chen, Defu Zhang

Engineering Faculty Articles and Research

Stock market analysis is extremely important for investors because knowing the future trend and grasping the changing characteristics of stock prices will decrease the risk of investing capital for profit. Thereupon, the prediction of stock prices and identifying the graphic signals of candlestick charts, which are two crucial tasks in stock price analysis, attract much attention from investors owing to the returns and risks that coexist in financial markets. To introduce a reliable approach for addressing these challenges, this paper proposes the modeling strategies based on machine learning (ML) techniques. A vector autoregression (VAR)-based rolling prediction model is proposed for …

Experimental And Computational Analysis Of Broadband Thz Photoconductive Antennas, Zachary Uttley, Jose Santos Batista, Bilal Pirzada, Magda El-Shenawee

Electrical Engineering Faculty Publications and Presentations

The work presents the fabrication and measurements of four LT-GaAs photoconductive terahertz (THz) antennas with different geometries of metallic electrodes. The goal is to analyze the overall bandwidth of the antennas through a comparison between the spectra of the generated photocurrent in the antenna gap, the radiated electric field THz pulse, and the S₁₁ parameter of the metallic electrodes. The photocurrent density and the S₁₁ parameters are computed using COMSOL multiphysics, while the generated THz pulse was experimentally measured using a time-domain spectroscopy system. The polarizations of the photoconductive antennas are experimentally measured, using x-cut quartz crystal halfwave …

In-Field Solar Panel Assessment And Fault Diagnosis, Muhammad Elgamal

Theses and Dissertations

Photovoltaic energy is a green energy that suit from small houses to high-power stations spanning large areas. In such large areas, monitoring individual panels can be a tedious task, especially if it was required to identify operational faults of these panels. Photovoltaic 4.0 technology depend on collecting data from each station and feeding them to a central processing system that can analyze operation data and hopefully locate when a fault happens. In such method, it is crucial to be accurate as much as possible and for measuring device to be accurate as well to have a clear judgement. In this …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Effects Of Electrodes Layout On Performance Of Millimeter-Wave Transistors, Soheil Nouri, Samir M. El-Ghazaly

Electrical Engineering Faculty Publications and Presentations

This work presents a systematic parameter extraction methodology for modeling of millimeter-wave transistors. The physics-based parameter extraction approach in this study is included in the wave-electron-transport model to improve the accuracy of the simulation results. The effects of extrinsic parameters on the performance of the device are also analyzed in detail. Skin effects and sharp metallization edge effects as the two physical phenomena that impact the current distribution and the resistance of millimeter-wave transistors are studied thoroughly. Two common electrode layout variations, the T configuration and the fork configuration, are compared. The comparison mainly targeted their performance on upper millimeter …

Wireless Kick Pedal, Jacob Wise, Ryan Kinyo, Bradley Toth, Ian Zanath

Williams Honors College, Honors Research Projects

The goal of the project is to build a wireless kick pedal that allows accessibility to drummers that have leg or foot disabilities and add versatility to multi-instrumentalists looking to add percussion while playing another instrument. The proposed pedal is designed in two main parts, a wearable band that tracks the player’s movement, and a hammer mechanism that receives actuation commands from the wearable band to move the hammer and deliver a drumbeat. The band is designed to be worn on several parts of the body, including the ankle, knee, thigh, or even the arm depending on the user’s situation. …

Modeling The Early Visual System, Nicholas Lanning

Theses and Dissertations--Electrical and Computer Engineering

There are two encoding schema present in simple cells in the early visual system of vertebrates: the retinal simple cells activate highly when the receptive field contains a center surround stimulus, while the primary visual cortex’s (V1) simple cells activate highly when the receptive field contains visual edges. Work has been done in the past to enforce constraints on visual machine learning such that the retinal or V1 encoding is learned, but this work is often done to emulate retinal and V1 encoding in a vacuum. Recent work using convolutional neural networks focuses on anatomical constraints along with a supervised …

Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp

Engineering Technology Faculty Publications

The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …

Lidar Remote Sensing Of Aerosol And Ozone Profiles And Application To Air Quality Studies In New York City Area, Dingdong Li

Dissertations and Theses

Ozone (O₃) and PM2.5 (Particulate Matter with a diameter less than 2.5 μm) are the main pollutants in New York City (NYC) due to high levels of anthropogenic emissions, complex urban meteorology, and regional transport. However, vertical distribution observations are still lacking. This thesis utilizes lidar remote sensing techniques to retrieve the vertical distribution of O₃ and aerosols and study air pollution episodes in the NYC metropolitan area.

The thesis includes three parts. The first part analyzes continuous ceilometer observations of aerosols and atmospheric mixed-layer height (ML). We investigate the vertical, diurnal, and seasonal characteristics of the …