Digital Commons Network^™

Multi-Task Learning For Hybrid Communication Waveforms: Exploring Model Enhancement Techniques And Establishing Task Relationships, Saksham Dewan

Legacy Theses & Dissertations (2009 - 2024)

Wireless communications have become ubiquitous, enabling seamless connectivity and driv- ing innovations across various domains. As we look to the future, visible light communication (VLC) is a promising technology that offers the potential to revolutionize how we transmit and receive data. It seamlessly integrates multiple functionalities, including localization, control/sensing, and high-speed data transmission.This thesis proposes a multi-task learning deep convolutional neural network approach to optimize a hybrid waveform for VLC-enabled networks. By integrating Beacon Posi- tion Modulation (BPM), Beacon Phase Shift Keying (BPSK), and OFDM symbols within a virtual Pulse Width Modulation (PWM) envelope, this waveform supports localization, control/sensing, and …

Radio Frequency Interference (Rfi) Detection In Microwave Radiometry Using Multi-Dimensional Data Mining Techniques, Fathima Imara Mohamed Nazar

Legacy Theses & Dissertations (2009 - 2024)

Measurements of natural electromagnetic radiation from Earth using microwave radiometers provide deep insight into our planet and its environmental conditions. These insights are essential for quantifying, understanding, and predicting various geophysical processes, such as climate patterns, water cycles, carbon cycles, and more. These passive measurements are diverse and cover a wide range of frequencies, depending on the sensitivity of microwave radiation to changes in important geophysical parameters. However, it is important to note that the microwave spectrum is also utilized by active services, such as wireless communication networks and radars. As a result, Radio Frequency Interference (RFI) in the measurements …

Investigation Of Pra For Rapid Part Replacement, John Lazenby

Honors Theses

As the electronics industry transitions to using commercial-off-the-shelf (COTS) devices of increasingly smaller technologies, radiation effects analysis becomes more significant in mission planning. In this work a probabilistic risk assessment (PRA) program, RadSTATS, is used in the analysis of various COTS memories in a radiation environment. The probabilities that the bits in memory will be flipped due to single event upset (SEU) rates are calculated for each memory, volatile and non-volatile. The unavailability of bits was discovered to increase with increasing storage capacity. Methods of error detection and correction (EDAC) between the same manufacturer were seen to decrease at unavailability …

Phasor-Domain Short-Circuit Analysis Of Power Transmission Systems In The Presence Of Inverter-Based Resources, Dol Kunwar

All Theses

Although a power system is nonlinear during healthy operation because of constant power loads and controlled power injections from the sources, a conventional power system fed by synchronous generators is linear during fault, and can be represented by bus impedance matrix (Z-bus), which is useful in power system analyses such as short circuit (SC) analysis. However, With increasing penetration of inverter-based resources (IBRs) in the system, the assumption of linearity of the faulted network does not hold. This impacts the analyses relying on Z-bus and Thevenin’s equivalent impedance (TEI), such as certain protection schemes set using short circuit analysis. Therefore, …

Summonable Construction Delivery Robot, Kevin M. Lewis

Honors Capstones

In many different construction industries, there is a need for tools, parts, and other necessary items to be transported quickly and efficiently over various types of terrain. Human resources have often been used to address these needs, which can become very time and cost inefficient over long periods. The design proposal here is aimed at addressing this need by developing an autonomous outdoor mobile robot based on a quadrupedal robot design. This approach differs by incorporating a wheeled and quadrupedal hybrid actuation system that provides terrain negotiation and speed at the appropriate times. The team uses Robot Operating System (ROS) …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

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

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Design And Optimization Of A Novel Monolithic Spring For High-Frequency Press-Pack Sic Fet Modules, Bogac Canbaz

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

Silicon Carbide (SiC) Field-Effect Transistor (FET) modules lead the way in power electronics, being superior in efficiency and robustness for high-frequency applications. The shift towards SiC from traditional silicon (Si)-based devices is driven by its superior thermal conductivity, higher electric field strength, and operational efficiency at elevated temperatures. These features are critical for the development of next-generation, grid-oriented power converters aimed at enhancing the reliability and sustainability of power systems. This research focuses on high-frequency press-pack (HFPP) SiC FET modules, addressing the primary challenge of miniaturizing SiC FET dies without compromising performance, through an innovative press-contact design essential for increased …

Mems Optical Cavities For Low Power Communication., Jacob Schopp

Electronic Theses and Dissertations

This thesis discusses the use of MEMS (microelectromechanical systems) optical cavities for use in low power communication. MEMS optical cavities are thin air gaps between an actuated MEMS mirror and a fixed glass encapsulation. By moving the MEMS mirror the reflectivity of the MEMS optical cavity can be changed. This change in reflectivity can be used to transmit information passively by modulating reflected light intensity instead of generating new light using a light source. These MEMS optical cavities are demonstrated using optical fibers for illumination delivery and reflected light collection. In addition to being reflected for communication, the illuminating light …

Exploring The Effects Of Dopants On The Opto-Electrical Response Of Ge2Se3-Based Optically Gated Transistor (Ogt), Md Faisal Kabir

Boise State University Theses and Dissertations

In this work, the electrical and optical responses of chalcogenide glass (ChG) Ge₂Se₃-based optically gated transistors (OGTs) were investigated. The device can act as a selector for resistive memory devices and potentially enable the production of functional high-density resistive (and memristive) arrays.

The OGT was developed using a Ge₂Se₃-based material heterostructure and demonstrated to successfully gate a memristor with light. The light intensity provided a built-in compliance current, allowing multi-state programming. By varying the light intensity incident on Ge₂Se₃ material, a family of current-voltage (I-V) curves were measured that …

Traffic Prediction In 5g Networks Using Machine Learning, Hossein Mehri

Boise State University Theses and Dissertations

The advent of 5G technology promises a paradigm shift in the realm of telecommunications, offering unprecedented speeds and connectivity. However, the efficient management of traffic in 5G networks remains a critical challenge. It is due to the dynamic and heterogeneous nature of network traffic, including bursty patterns, varying user behaviors, and diverse applications, all of which demand highly accurate and adaptable prediction models to optimize network resource allocation and management. This dissertation investigates the intricate domain of traffic prediction within 5G networks, addressing the specific challenges posed by both massive machine type communication (mMTC) networks and 5G cellular networks.

The …

4-Channel Spatially Multiplexed Communication System In Single-Core Optical Fibers, Ce Su

Theses and Dissertations

This dissertation delves into exploring and advancing spatial domain / space division multiplexing (SDM) technologies within single-core optical fibers, a frontier in optical fiber communications poised to meet the burgeoning global demand for data transmission. At the heart of this research is the pursuit to significantly enhance the capacity and efficiency of optical fiber communication systems without necessitating additional fiber infrastructure. This work unveils a new paradigm in optical fiber communications characterized by a pioneering 4-channel SDM system through a meticulous process encompassing theoretical modeling, computational simulations, design innovations, and rigorous experimental validations. Theoretical contributions include the development of refined …

An Edge Computing System With Amd Xilinx Fpga Ai Customer Platform For Advanced Driver Assistance System, Tsun Kuang Chi, Tsung Yi Chen, Yu Chen Lin, Ting Lan Lin, Jun Ting Zhang, Cheng Lin Lu, Shih Lun Chen, Kuo Chen Li, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and …

Database And Machine Learning Model For Classifying Autism Spectrum Disorder From Smartphone Based Electroretinography, Rory Harris

Honors Scholar Theses

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that negatively affects a patient’s cognitive and communication aptitude and, therefore, can severely impact that patient’s quality of life. Because of this, early diagnosis is paramount. In recent studies, electroretinography (ERG), which is a measure of the retina’s electrical response to a brief flash of light into the eye, has shown promise in detecting ASD. Access to these scans can provide early diagnosis, improving well-being. Current ERG devices are very expensive due to their on board processing capabilities. This paper aims to create an ERG device using a smartphone as the main …

Developing General Purpose Apps To Automate Image Analysis Of Wave-Augmented-Varicose-Explosion Atomization And Other Multi-Phase Interfacial Flows, Ethan Newkirk

Senior Honors Theses

Atomization involves disrupting a flow of contiguous liquid into small droplets ranging from one submicron to several hundred microns (micrometers) in diameter through the processes of exerting sufficient forces that disrupt the retaining surface tensions of the liquid. Understanding this phenomenon requires high-speed imaging from physical models or rigorous multiphase computational fluid dynamics models. We produce a MATLAB application that utilizes various methods of image analysis to quickly analyze and store mathematical data from detailed image analyses. We present a user with numerous tools and capabilities that provide results that deviate from 1.8% to 8.9% of the original image sequence …

Hand Movement Analysis For Surgical Suturing Skill Assessment, Amir Mehdi Shayan

All Theses

To enhance patient safety, surgical education is increasingly incorporating simulation for formative skills assessment and training. However, many standardized assessment tools rely on human raters for performance assessment, which is resource-intensive and subjective. Simulators that provide automated and objective metrics from sensor data can address this limitation. This thesis presents an instrumented bench suturing simulator, patterned after the Clock Face (CF) radial suturing model from the Fundamentals of Vascular Surgery (FVS), for automated and objective assessment of open suturing skills by particularly focusing on biomechanical analysis of hand movements. For this research, 97 participants (35 attending surgeons and fellows, 32 …

Optical Wavelength Measurement Based On Microwave-Photonics And Fiber Dispersion, Yongji Wu

All Dissertations

In modern photonics, combining microwave techniques with optical measurements has introduced a novel research direction. This study introduces a novel Microwave Photonics Wavelength Measurement System (MP-WMS), integrating microwave photonics with fiber chromatic dispersion to achieve direct wavelength measurement. Utilizing cost effective single mode optical fibers as dispersion devices, this system employs chromatic dispersion to convert optical frequency domain measurements into microwave time domain measurements. We established a mathematical model to describe how different wavelengths are detected, enhancing the system's effectiveness. The MP-WMS system offers an affordable solution with high resolution. In the experiment, we used a 35km long SM-28 single-mode …

Trust Model Measurements For The Energy Grid Of Things, N. Sonali Fernando, John M. Acken, Robert Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Information security is essential for the reliable operation of an Energy Grid of Things (EGoT). In addition to basic information security protocols as defined by published standards, there is a need for a monitoring function that measures the trustworthiness of the various actors participating in an EGoT. We describe in this paper the implementation and evaluation of a Distributed Trust Model that was developed specifically for monitoring communication within an EGoT. We then show how the model parameters are set using statistical measures for hypothesis testing.

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

Selective Transfection Of A Transferrin Receptor-Expressing Cell Line With Dna-Lipid Nanoparticles And Synthesis Of Parasite-Derived Glycans As Biomarkers For Leishmaniasis, Irodiel Vinales Lozano

Open Access Theses & Dissertations

Despite notable progress in lipid nanoparticle (LNP)-mediated gene delivery, achieving selective transfection of specific cell types, such as cancer cells, remains a significant hurdle, hindering the advancement of innovative gene therapies. In this study, we engineered an LNP formulation encapsulating plasmid DNA (pDNA) encoding the monomeric Green Lantern (mGL) fluorescent reporter protein. The DT7 peptide ligand targeting human transferrin receptor 1 (hTfR1) was also conjugated to the LNP surface for targeted delivery to hTfR1-expressing cells. Optimization of LNP composition yielded favorable particle diameter, ζ-potential, yield, and pDNA encapsulation efficiency. Evaluation of transfection selectivity using a panel of two engineered cell …

Biofabrication Of Human Tissue-On-A-Chip Models Using Engineered Biocompatible Electrospun Scaffolds, Zayra Naomi Dorado

Open Access Theses & Dissertations

This study explored the adoption of furfuryl gelatin (F-gelatin) based electrospun scaffolds compared with poly-caprolactone (PCL) as promising biomaterials for tissue engineering applications. Tissue-on-a-chip models, incorporating F-gelatin and PCL electrospun scaffolds, offer promising avenues for healthy and disease-in-vitro tissue models that can be explored to investigate underlying physiological mechanisms involved in disease development. Previous research has demonstrated the cytocompatibility of F-gelatin when used for modifying implant surfaces and tissue repair applications [1]. Our earlier published works have also successfully utilized F-gelatin for in-vitro cardiac tissue engineering [2][3]. We designed F-gelatin and PCL electrospun scaffolds to replicate the native tissue extracellular …

Effect Of Patient Specific Blood Biomarkers On Nanoparticle - Cell Interactions, Veronica Gabriela Contreras

Open Access Theses & Dissertations

Nanoparticles are currently known to be a promising material class for bio-applications in drug delivery and vaccine development. Using gold nanoparticles of varied sizes, in this case 45 and 100 nanometers as a model nanomaterial system, we investigated how patients' blood physiology and chemistry (such as solute, protein, lipid levels) affect the biological response to bionanomaterials. When nanoparticles are injected into the body, biomolecules in the blood adsorb to the nanoparticle's surface to form a biomolecular corona that is specific to the patient's unique blood composition. This biomolecular corona is important because it affects the in vivo fate and biodistribution …

Design And Implementation Of High-Frequency Dc-Dc Converters For Ev Applications, Rahul Biswash

Graduate Theses and Dissertations

The power electronics industry has been revolutionized by introducing wide bandgap semiconductor devices, such as Silicon Carbide (SiC) and Gallium Nitride (GaN). Due to their high frequency, high temperature, and high voltage operating capabilities, wide bandgap devices boast significant improvements in power density, efficiency, and reliability, as evidenced by their ability to decrease the size of power converters by operating at higher frequencies, temperatures and voltages, use of smaller and less passive components, such as transformers, inductors and capacitors, which makes power converters more compact and light-weight, ideal for space and weight-constrained applications, and compatibility with a wide range of …

Robust And Trustworthy Deep Learning: Attacks, Defenses And Designs, Bingyin Zhao

All Dissertations

Deep neural networks (DNNs) have achieved unprecedented success in many fields. However, robustness and trustworthiness have become emerging concerns since DNNs are vulnerable to various attacks and susceptible to data distributional shifts. Attacks such as data poisoning and out-of-distribution scenarios such as natural corruption significantly undermine the performance and robustness of DNNs in model training and inference and impose uncertainty and insecurity on the deployment in real-world applications. Thus, it is crucial to investigate threats and challenges against deep neural networks, develop corresponding countermeasures, and dig into design tactics to secure their safety and reliability. The works investigated in this …

Critical Risk Assessment, Diagnosis, And Survival Analysis Of Breast Cancer, Shamiha Binta Manir, Priya Deshpande

Electrical and Computer Engineering Faculty Research and Publications

Breast cancer is the most prevalent type of cancer in women. Risk factor assessment can aid in directing counseling regarding risk reduction and breast cancer surveillance. This research aims to (1) investigate the relationship between various risk factors and breast cancer incidence using the BCSC (Breast Cancer Surveillance Consortium) Risk Factor Dataset and create a prediction model for assessing the risk of developing breast cancer; (2) diagnose breast cancer using the Breast Cancer Wisconsin diagnostic dataset; and (3) analyze breast cancer survivability using the SEER (Surveillance, Epidemiology, and End Results) Breast Cancer Dataset. Applying resampling techniques on the training dataset …

Texture-Based Classification To Overcome Uncertainty Between Covid-19 And Viral Pneumonia Using Machine Learning And Deep Learning Techniques, Omar Farghaly, Priya Deshpande

Electrical and Computer Engineering Faculty Research and Publications

The SARS-CoV-2 virus, responsible for COVID-19, often manifests symptoms akin to viral pneumonia, complicating early detection and potentially leading to severe COVID pneumonia and long-term effects. Particularly affecting young individuals, the elderly, and those with weakened immune systems, the accurate classification of COVID-19 poses challenges, especially with highly dimensional image data. Past studies have faced limitations due to simplistic algorithms and small, biased datasets, yielding inaccurate results. In response, our study introduces a novel classification model that integrates advanced texture feature extraction methods, including GLCM, GLDM, and wavelet transform, within a deep learning framework. This innovative approach enables the effective …

Bottling Automation System, Dylanie Tippit

Honors College Theses

This report details the complete design of an automated bottling system. Each bottle is 5.97 centimeters tall and has an outer diameter of 3.81 centimeters. The goal of the project is to successfully fill and cap twelve bottles in under three and a half minutes. The system will have two conveyors in series, a water dispenser, an electrolyte dispenser, capping station, Human Machine Interface (HMI) and Allen Bradley programmable logic controller (PLC). The water and electrolyte dispenser will have two ball valves in series, with the desired amount of volume to dispense the designated liquid. The capping station will be …

Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles are becoming increasingly popular, battery limitations (cost, size, and weight) complicate electric vehicle adoption. While important research on battery development is ongoing, this dissertation discusses two main approaches to overcome those limitations within the existing battery technology paradigm. Those thrusts are: improving battery health through an optimal charging strategy and minimizing necessary battery size through dynamic wireless power transfer. In this dissertation, relevant literature is discussed, with opportunities for further development considered. Within the two thrusts, three objectives sharpen the focus of the research presented here. First, a planning tool is defined for a battery electric bus fleet. …

Design And Implementation Of An Accelerated Lifetime Testing Platform For Silicon Carbide Mosfets, Conner Deppe

All Graduate Theses and Dissertations, Fall 2023 to Present

In the last several years, the United States has seen a significant increase in sales of electric vehicles. The increase of electric vehicles brings the need for increased availability of public charging stations. In the last two years, satisfaction levels for public chargers have fallen significantly due to unreliability, which is raising concerns for new potential electric vehicle owners. To mitigate the reliability concerns, chargers must be physically understood so they can be consistently monitored to assess their health status. To understand the electric vehicle charging reliability, electrical components must first be understood. In the cutting-edge charging technology, the relatively …

Spin Disorder Control Of Topological Spin Texture, Hongrui Zhang, Yu-Tsun Shao, Xiang Chen, Binhua Zhang, Tianye Wang, Fanhao Meng, Kun Xu, Peter Meisenheimer, Xianzhe Chen, Xiaoxi Huang, Piush Behera, Sajid Husain, Tiancong Zhu, Hao Pan, Yanli Jia, Nick Settineri, Nathan Giles-Donovan, Zehao He, Andreas Scholl, Alpha N'Diaye, Padraic Shafer, Archana Raja, Changsong Xu, Lane W. Martin, Michael F. Crommie, Jie Yao, Ziqiang Qiu, Arun Majumdar, Laurent Bellaiche, David A. Muller, Robert J. Birgeneau, Ramamoorthy Ramesh

Physics Faculty Publications and Presentations

Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, Fe₃GaTe₂, to modify local anisotropic magnetic interactions. Consequently, we present direct observations of the order-disorder skyrmion lattices transition. In addition, non-trivial topological solitons, such as skyrmioniums and skyrmion bags, are realized at room temperature. Our work highlights …

Artificial Neural Network Based Grain Moisture Measuring Device, Erkin Eljaev, Shohrux Nurali O‘G‘Li Narzullayev, Elyor Faxriddinovich Khudoyberdiev

Chemical Technology, Control and Management

To date, the intellectualization of solving technical issues in managing, controlling, and measuring technological processes in all branches of industrial production is considered an urgent task. In this regard, a class of intelligent devices and sensors has emerged. Intelligent devices and sensors differ from their analog counterparts in that they have functions such as automatic adjustment of the measurement range, self-calibration, data processing, and decision-making. The article discusses the development of intelligent measuring instruments based on a capacitive transducer for measuring the moisture content of grain and grain products.