Digital Commons Network^™

Designing The Power System Of A Robot, Nolan Hays

Honors College Theses

This thesis outlines the acquired skills and knowledge acquired through the course of four years of Murray State University’s School of Engineering. The capstone for students in the department was to team up and complete an interdisciplinary senior design project using skills from various tracks of engineering. For this thesis, there is a greater emphasis on the electrical engineering track. The objective of the project was to build an autonomous robot to complete the various tasks within the scope of the IEEE SoutheastCon 2023 Hardware Competition. The robot was controlled via a Raspberry Pi 4 Model B. There were three …

Sensor Updates For Bigheaded Carp-Tracking Autonomous Boat, Jordan Kaufmann

Honors College Theses

Bigheaded carp are an invasive species that overpopulate and compete with the native species of Kentucky Lake as well as many other North American aquatic ecosystems. The movement patterns of Bigheaded carp are being studied nationwide by the United States Geological Survey and multiple universities. These studies ultimately seek to control their spread and reduce or reverse the ecosystem destabilization caused by this invasive species. Such studies are currently conducted manually on Kentucky Lake by graduate students affiliated with the Murray State University (MSU) Biology Department and Hancock Biological Station, and these manual studies are an arduous and time-consuming effort. …

Relaxing Dc Capacitor Voltage Of Power Electronic Converters To Enhance Their Stability Margins, Ali Zakerian

Theses and Dissertations

Recently, due to the increasing adoption of distributed energy resource (DER) technologies including battery energy storage (BES) and electric vehicle (EV) systems, bidirectional power converters are becoming more popular. These converters are broadly utilized as interface devices and provide a bidirectional power flow in applications where the primary power supply can both supply and receive energy. A dc capacitor, called the dc-link, is an important component of such bidirectional converters. For a wide range of applications, the converter is required to control the dc-link voltage. Commonly, a proportional-integrating (PI) controller is used by the dc capacitor voltage controller to generate …

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 …

Secure And Efficient Federated Learning, Xingyu Li

Theses and Dissertations

In the past 10 years, the growth of machine learning technology has been significant, largely due to the availability of large datasets for training. However, gathering a sufficient amount of data on a central server can be challenging. Additionally, with the rise of mobile networking and the large amounts of data generated by IoT devices, privacy and security issues have become a concern, resulting in government regulations such as GDPR, HIPAA, CCPA, and ADPPA. Under these circumstances, traditional centralized machine learning methods face a problem in that sensitive data must be kept locally for privacy reasons, making it difficult to …

Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest

Theses and Dissertations

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.

Sensitive And Makeable Computational Materials For The Creation Of Smart Everyday Objects, Te-Yen Wu Mr

Dartmouth College Ph.D Dissertations

The vision of computational materials is to create smart everyday objects using the materi- als that have sensing and computational capabilities embedded into them. However, today’s development of computational materials is limited because its interfaces (i.e. sensors) are unable to support wide ranges of human interactions , and withstand the fabrication meth- ods of everyday objects (e.g. cutting and assembling). These barriers hinder citizens from creating smart every day objects using computational materials on a large scale.

To overcome the barriers, this dissertation presents the approaches to develop compu- tational materials to be 1) sensitive to a wide variety of …

Approximate And Sample Entropy Of Center Of Pressure In Unperturbed Tandem Standing: Contribution Of Embedding Dimension And Tolerance, Jayla Mashae Wesley

Masters Theses

Approximate entropy (ApEn) and sample entropy (SampEn) are statistical methods designed to quantify the regularity or predictability of a time series. Although ApEn has been a prominent choice for use, it is currently unclear as to which method and parameter selection combination is optimal for its application in biomechanics. The goal of this thesis was to examine the difference between ApEn and SampEn related to center of pressure (COP) data during standing balance tasks, while also refining tolerance r, to determine entropy optimization. Six participants completed five 30-second, feet together and tandem standing, trials under eyes-open and eyes-closed conditions. Ground …

The Future Is Now In Twisted Coil Polymer Actuators (Tcpa), Ryan Ronquillo

Electronic Theses and Dissertations

This thesis aimed to fabricate and test twisted coiled polymer actuators (TCPA) to understand the mechanical and thermal aspects of this artificial muscle fiber. The purpose of this thesis was to find a linear relationship using the LVDT sensor, fabricating TCPA fibers, and interpreting the data. The project tested whether nylon/polymer could be used as a better artificial muscle fiber.

This research accomplished three goals: (1) designing and fabricating a system capable of creating supercoiled muscle fibers consistently, (2) calibrating the Linear Variable Differential Transformer (LVDT) and Core, and (3) analyzing/interpreting the data of the Twisted Coiled Polymer Actuators (TCPA) …

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 …

An Incremental Based Approach For 3d Multi-Angle Point Cloud Stitching Using Icp And Knn, Pankti K. Patel

Theses and Dissertations

The basic principle of stitching is joining or merging any two materials or objects. 3D point cloud stitching is basically stitching two 3D point cloud together. 3D point cloud stitching is an emerging topic and there are multiple ways to achieve it. There are various methods for stitching which all have changes throughout the time. The existing methods do have shortcomings and have ignored the multiangle stitching of a same model or an object. This shortfall leads to many deficiencies in the ability of a stitching algorithm to maintain accuracy over the period. In this work I have introduced a …

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 …

Fabrication Of Black Phosphorus Terahertz Photoconductive Antennas, Nathan Tanner Sawyers

Physics Undergraduate Honors Theses

Terahertz (THz) photoconductive antennas (PCAs) using 40nm thin-film flakes of black phosphorus (BP) and hexagonal boron nitride (hBN) have been shown computationally to be capable of THz emission comparable to those based on GaAs [2]. In this paper, I briefly describe the scientific and practical interest in THz emissions and explain what warrants research into black phosphorus as a photoconductive semiconductor in THz devices. Furthermore, I outline the basic principle of how these antennas work and mention alternative designs produced by other researchers in the past. Finally, I summarize the fabrication process of these antennas, as well as the measurements …

Design Of A Sigma-Delta Adc In 65nm Cmos Process, Michael Lee Thompson Iii

Electrical Engineering Undergraduate Honors Theses

Analog and digital signals both play a vital role in electrical engineering and the technology of today. As the role of electrical and computer engineers becomes more deeply involved in the development of new technology, an understanding of how these signals are utilized, and what they represent, is a necessity. Due to the inherent limitations involved with analog signals, there is a need for these signals to be accurately and efficiently converted to digital signals for processing. The job of the analog-to-digital converter, or ADC, is to receive this analog input signal (voltage or current) and create a digital representation …

Optical Sensing Of Capillary Waves, Matthew Franklin Reid

Honors College Theses

I relay various topics I learned about this semester and summarize the specialties of Clemson’s Micro-Photonics Laboratory. I report pertinent information for characterizing capillary waves with lasers and one recent method of characterizing them. Lastly, I outline a potential plan for mathematically modeling a laser’s reflection off of capillary waves, and potential plans moving forward.

Enabling Joint Sensing And Communication For Vehicle-To-Everything Networks, Mohammad Alaneed

ETD Archive

This thesis investigates the challenges and opportunities in designing and implementing joint sensing and communication (JSC) systems in vehicle-to-everything (V2X) environments. This emerging concept in vehicular communication connects vehicles to other vehicles, infrastructure, networks, and pedestrians in a smart transportation environment. To address these challenges and seize these opportunities, a new development model is proposed. The primary objective of this work is to enhance the overall performance of the system while leveraging synergies between sensing and communication tasks. To achieve this, advanced methodologies such as the smooth-MUSIC (MUltiple SIgnal Classifcation) algorithm for Angle of Arrival (AoA) estimation, robust beamforming techniques …

Task, Knowledge, Skill, And Ability: Equipping The Small-Medium Businesses Cybersecurity Workforce, Aadithyan Vijaya Raghavan

ETD Archive

With cyberattacks becoming more frequent and targeted, small-medium businesses (SMBs) are forced to adopt a cybersecurity framework to help secure their cyberspace. While these frameworks are a good starting point for businesses and offer critical information on identifying, preventing, and responding to cyber incidents, they can be hard to navigate and implement. To help with this issue, we propose a comprehensive model of Knowledge, Skills, Ability, and Tasks (TKSA) from the National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework) for three of the most frequent attack vectors: Phishing/Social Engineering, Malware, and Web-Based Attacks. SMBs can use the …

Uibee: An Improved Deep Instance Segmentation And Classification Of Ui Elements In Wireframes, Cahi̇t Berkay Kazangi̇rler, Caner Özcan, Buse Yaren Teki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

User Interface (UI) is a basic concept in which individuals interact with any computer program or technological device to create a graphical design. In the initial stages of app development, UI prototype is a must. An automatic analysis system for the basic execution of UI designs will considerably speed up the development of designs according to old-fashioned methods. In this approach, it is aimed at saving cost and time by automating the process. For the aforesaid objective, we present a new approach rather than the traditional methods. For this reason, a high amount of elements in wireframes are detected and …

Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi

All Dissertations

Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …

A Study On Asymmetric Perfect Vortex: Fractional Orbital Angular Momentum And Nonlinear Interaction, Kunjian Dai

All Dissertations

In this work, the manipulation including generation and detection of the asymmetric perfect vortex (APV) carrying fractional orbital angular momentum (OAM) was demonstrated and discussed. All the manipulation of the modes is in real-time which provides a perfect tool for sensing the dynamic properties of complex media. The OAM-involved nonlinear conversion, specifically the second-harmonic generation (SHG) using the APV and asymmetric Bessel-Gaussian (BG) beams was studied in detail.

The generation and detection of the APV are based on the HOBBIT concept which includes acoustic optical deflector (AOD) and log-polar coordinate transformation optics. The RF signal driving the AOD allows the …

State Estimation And Data Fusion With Data-Driven Communication, Xiaolei Bian

LSU New Orleans Theses and Dissertations

This dissertation focuses on the systemic design of proper estimation as well as fusion techniques and data-driven communication schemes to infer the state of a dynamic discrete-time linear system over a wireless network. The goal is to effectively extract and share key information over networks to enhance estimates of system states. Such co-design research is drawn by the need to leverage limited resources (communication bandwidth, energy and computational power) for a multitude of data and data sources in networked systems.

We first build the overarching structure by synthesizing communication and estimator/fuser, and research the collective behaviors of the system.

In …

Effect On Focusing Fields By Ferromagnetic Cell Cores In Linear Induction Accelerators, Cooper Guillaume

Senior Honors Theses

In the Los Alamos National Laboratories DARHT facility, there are two perpendicular linear induction accelerators, LIAs. The LIAs’ solenoids produce magnetic fields which focus the electron beam. Simultaneously, the accelerating pulse creates a magnetic field. These two field intensities act upon a ferromagnetic material in the cells to enhance magnetic flux density. Due to the nonlinearity of the material, this flux density will reach a saturation point. In turn, the magnetic field intensity of the axial solenoidal magnetic field will be affected and slightly altered. The width of the electron beam will increase, causing a decrease in effectiveness. Through simulation, …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …

Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose, Ümi̇t Özsandikcioğlu, Ayten Atasoy

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer has the highest death rates among all types of cancer worldwide. Detection of lung cancer in its early stages significantly increases the survival rate. In this study, the aim is to improve the lung cancer detection performance of electronic noses (e-noses) with breath analysis by using two different types of gas sensor-based e-nose. The developed e-nose system consists of 14 quartz crystal microbalance (QCM) sensors and 8 metal oxide semiconductor (MOS) sensors. Breath samples were collected from a total of 100 volunteers, including 60 patients with lung cancer, 20 healthy nonsmokers, and 20 healthy smokers, and were classified …

Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran

Turkish Journal of Electrical Engineering and Computer Sciences

Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …

Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun

Turkish Journal of Electrical Engineering and Computer Sciences

The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …

Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …

Efficient Modelling Of Random Access Memory Cell: An Approach Using Qca Nanocomputing, Ali Newaz Bahar, Angshuman Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Quantum-dot cellular automata (QCA) is innovative and potentially fruitful nanotechnology that provides a solution for transistor-based circuits with enhanced switching frequency, large-scale integration, and low power consumption. The random-access memory (RAM) cell is a fundamental component that is designed to operate quickly and effectively since memory is a core part of the semiconductor industry, thus the QCA family. The RAM cell design in this work is based on a multiplexer structure and is implemented without using coplanar crossovers of QCA technology. QCADesigner-2.0.3, a standard QCA layout design and verification tool, is used in the simulation and validation processes for the …