Electrical and Computer Engineering Commons^™

Visual Interpretability Of Multimodal Tissue Perfusion Classification Using Grad-Cam And Saliency Maps, Metehan Zorluoglu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate identification of the tissue perfusion phase from hand images can aid doctors in decision-making with non-invasive techniques. The present study proposes a multimodal deep learning model for classifying the tissue perfusion phase using infrared, thermal, and visible spectrum images of the human hand. The proposed model consists of various preprocessing techniques such as manipulation, homography alignments, and masking. The significant contribution of this thesis is the interpretability analysis of deep learning models, achieved through the analysis of saliency maps and the Gradient-weighted Class Activation Mapping (Grad-CAM) methods. The purpose of this method is to find out how the convolutional …

Model Based Control And Hil Verification Of An Integrated Battery Management System, Catalin Sabou

UNLV Theses, Dissertations, Professional Papers, and Capstones

The rapid advancement of electric vehicle technologies necessitates highly reliable Battery Management Systems (BMS); however, validating embedded supervisory logic presents a notable challenge. While physical pack testing is accurate, it is costly and hazardous for early stage software evaluation. This thesis presents the design, implementation, and rigorous validation of an integrated BMS developed for the Battery Workforce Challenge, bridging the gap between model based design and safe hardware execution. The core of this work is a model based supervisory controller, developed in MATLAB/Simulink and executed on an STM32G4 embedded target. To facilitate embedded validation while preserving a representative battery environment, …

An Optimization Method For Near-Linear Phase Analog Frequency Sampling Filter Design, Leonardo Ledesma

UNLV Theses, Dissertations, Professional Papers, and Capstones

Analog frequency sampling filters (FSFs) realize a desired frequency response by interpolating a frequency response through a set of harmonically related frequency samples from the filter’s frequency response and are magnitude and phase coefficients used in the filters transfer function. FSFs can be designed to have exact linear phase which makes the FSF attractive for many applications. A FSF’s system transfer function (STF) shows that the filter can be implemented by a series connection of a comb filter and a parallel array of resonators. However, the FSF requires that the zeros created by the comb filter cancel the imaginary axis …

A Near Linear-Phase Analog Frequency Sampling Filter Design Framework Using A Second-Order Trust-Region Optimization Technique, Edreese Basharyar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Analog frequency sampling filters (FSFs) provide an efficient means of realizing finite impulse response (FIR)-like behavior in continuous-time systems, but their practical implementation is constrained by the requirement for perfect pole-zero cancellation along the imaginary axis. Because exact cancellation is physically unattainable due to component variations, ideal linear-phase Type 1 analog FSFs exhibit uncancelled poles that result in system instability. To address this limitation, this thesis introduces a near-linear-phase design framework for Type 1 analog FSFs that achieves both stability and design flexibility through the inclusion of a damping constant, ρ, which shifts the poles into the left half of …

The Risc-V Fpga (Rvfpga) Teaching Package, Daniel Chaver, Sarah Harris, Luis Pinuel, Olof Kindgren, Zubair Kakakhel, Chris Owen, Jose I. Gomez-Perez, Fernando Castro, Katzalin Olcoz, Julio Villalba-Moreno, Alexander Grinshpun, Freddy Gabbay, Luke Seed, Rui Duarte, Manuel Lopez, Oscar Alonso, Robert Owen

Electrical & Computer Engineering Faculty Research

RISC-V is a free and open-standard ISA based on RISC principles, allowing anyone to design, manufacture, and sell RISC-V chips and software. Its flexibility and growing ecosystem have made it popular in research, education, and industry, increasing the need for educational materials. This paper provides an in-depth description of the RVfpga course, which offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and EL2 cores, developed by Western Digital and hosted by ChipsAlliance. The course targets students and educators in computing-related …

Design And Development Of Biomimetic Hydrogel Interfaces For Enhanced Bioelectrical Signal Acquisition, Daniela Nikoloska

UNLV Theses, Dissertations, Professional Papers, and Capstones

Every second, human skin processes over one million sensory signals while maintaining properties such as electrical conductivity, mechanical adaptability, and regenerative capability that surpass all synthetic materials. Contemporary bioelectronic devices prove inadequate when contacting skin surfaces due to poor adhesion and electrical contact issues that prevent effective sensing. Despite advancements in wearable and bioelectronic technologies, current devices face major drawbacks when interfacing with human skin, particularly in maintaining firm adhesion, conformability, and low-noise electrical signal acquisition.

This research focuses on the development of a biomimetic hydrogel-based interface for bioelectronic sensing. Specifically, a hybrid hydrogel system composed of polydopamine (PDA)- doped …

Quantum Sensing Of Magnetic And Thermal Fields Using Nitrogen-Vacancy Centers On Spoof Surface Plasmon Waveguides, Maxwell Stonham

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nitrogen-vacancy (NV) centers in nanodiamonds are solid-state quantum defects capable of detecting magnetic fields and temperature at the nanoscale with high spatial resolution and optical addressability at room temperature. Their spin-dependent fluorescence enables optically detected magnetic resonance (ODMR), a technique widely used for quantum sensing. However, enhancing optical readout efficiency remains a critical challenge for scalable integration and various methods can be used to improve this.

This thesis explores a hybrid quantum sensing platform that integrates NV-based sensing with spoof surface plasmon waveguides designed to enhance optical excitation and emission efficiency through localized spoof plasmon modes supported by subwavelength corrugated …

Rail Anomalies Dataset For Semantic Segmentation Analysis, Saarah Majid, Arian Izadi, Paul Stanik

Undergraduate Research Symposium Posters

Rail maintenance is a core necessity of upkeep, maintenance, deterioration, and safety implications of large rail systems. Doing so in an orderly and uniform way, however, has proven difficult with the thousands of miles that railways span. Use of computer vision on locomotives during normal operation can allow for a more streamlined process that would eliminate the need for costly specialized equipment and disruptions of normal operations. This project aims to efficiently detect vegetation overgrowth, mud-pumping, and standing water on railways. With the use of machine learning algorithms and dataset curation, models can be trained, allowing them to gain a …

Spatiotemporal Feature Extraction From Vertical Grf Signals For Parkinson’S Disease Severity Assessment Using Physionet And Gaitpd, Nitya Jadeja

Undergraduate Research Symposium Posters

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that impairs motor coordination, often resulting in measurable gait disturbances. Vertical ground reaction force (VGRF) signals provide a quantitative means of capturing these abnormalities and monitoring disease progression. This study focuses on the extraction and analysis of spatiotemporal gait features such as stride variability, stance duration, and force imbalance, from the PhysioNet Gait dataset to better understand their correlation with PD severity. Using gait analysis and machine learning techniques, recent computational models are reviewed and evaluated for their ability to assess PD progression through VGRF data. The analysis compares data-driven approaches with …

Real-Time Ai-Enabled Therapeutic Device For Improving Peripheral Perfusion And Glucose Regulation In Type 2 Diabetes, Torryana Tanis

Undergraduate Research Symposium Posters

Type 2 Diabetes Mellitus is frequently accompanied by peripheral microvascular disease, leading to impaired lower limb perfusion, impaired healing, and vulnerability to ulcers and amputation. The existing medical devices are predominantly aimed at systemic glucose control and do not have local therapeutic intervention to improve circulation or allow muscular glucose delivery. To meet this crucial demand, we have developed a portable, two-in-one biofeedback device that combines non-invasive blood glucose monitoring and Electronic Muscle Stimulation (EMS) therapy for the calf muscle. The glucose monitoring subsystem implements near-infrared (NIR) spectroscopy to measure skin light absorptance on the index finger. Real-time blood glucose …

Digital Twin Of The Unlv Campus For Safe Autonomous Vehicle Simulation, Carlos Funes

Undergraduate Research Symposium Posters

With the rise of artificial intelligence and machine learning algorithms, self-driving cars are becoming increasingly prevalent on our roads. By utilizing these technologies, we can reduce the number of accidents caused by distracted driving. Before implementing these systems in vehicles, however, it is essential to conduct numerous tests. Traditional evaluation of driverless cars on real-world roads can be both expensive and hazardous. To address this, creating a digital twin of an actual road minimizes unexpected hazards, allowing researchers to safely and efficiently test self-driving car programs in high-risk scenarios using computer simulations. This research outlines the process of generating a …

Diving Video Analysis Using Multitask Learning Action Quality Assessment (Mtl-Aqa), Taylor Gauthier

Undergraduate Research Symposium Posters

In many sports, videos are being used to assist in judging. For example, they are being used to review quick actions or confirm the actions being performed. For diving specifically, the videos of a dive can be at most 3 seconds long, and divers can perform a range of somersaults and twists within that time frame, all of which affect the score, classification, and dive number. Using these videos, a Multitask Learning Action Quality Assessment (ML-AQA) program, based on machine learning, from a vast dataset, is able to produce an Action Quality Score out of 100, Factorized Action Recognition (classifications), …

Predicting The Response Of Tendon-Driven Prosthetic Finger With Hyperelastic Joints, Lucas Gallup, Mohamed Trabia, Brendan O'Toole

Mechanical Engineering Faculty Research

Properly designed prosthetics hands can enhance the quality of life for those suffering from limb loss. Recently, 3D-printed prosthetic hands are becoming common. In these prostheses, fingers flex through the tendons that are activated by motion of the wrist. To provide spring action, thermoplastic polyurethane (TPU) hyperelastic joints are used to connect digits to each other as well as to the wrist. While these designs are common, no model for the relationship between tendon tension and joint flexion is available. This work has developed a quasi-static virtual work-based model to predict the relationship between tendon forces and the flexion of …

Integrated Uav Platform For Multi-Spectral, Thermal, And Eos Imaging In Wildfire Monitoring And Modeling, Md Shariful Islam

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents the design and development of a modular unmanned aerial vehicle (UAV) system based on a quadcopter platform for flexible and efficient wildfire-related multimodal image acquisition. Addressing key limitations in ecological UAV monitoring such as sensor inflexibility, time-consuming reconfiguration, and imprecise image georeferencing, the system introduces a versatile payload integration framework supporting three distinct imaging sensors: MicaSense Altum-PT, FLIR Vue Pro R, and Sony Alpha 6000.All onboard components, including the flight controller, autopilot software, GNSS module, motors and ESCs, were selected to optimize stability and payload performance. A gimbal-free, downward-facing mount simplifies field deployment, while custom integration enables …

Functional Biopolymers Applied To Sustainable Technologies In The Environment And Healthcare, Fengjie He

UNLV Theses, Dissertations, Professional Papers, and Capstones

Biodegradable polymeric materials (biopolymers) are naturally derived materials known for their excellent biocompatibility, biodegradability, sustainability, and versatile chemical functionality. They have attracted increasing attention in various applications as alternative to synthetic materials ranging from food packaging to tissue engineering. Meanwhile, with intrinsic advantages, biopolymers have also emerged as promising materials in addressing contemporary challenges in both biomedical and environmental fields. Motivated by the significant potential of biopolymers and the growing need for sustainable materials, my research focuses on the design and engineering of biodegradable polymers with novel modification methods and application directions. In this work, two representative biopolymers are selected: …

The Dropbot: Design And Development Of A Custom Drone For Precision Water Drop Penetration Time (Wdpt) Testing, Mugundan Prakash

UNLV Theses, Dissertations, Professional Papers, and Capstones

Assessing the hydrophobic characteristics of soil is vital for understanding soil wettability or soil-water interactions, particularly in post-wildfire environments where water repellency can significantly impact ecosystem recovery, water infiltration, and erosion control. One key metric in soil wettability studies is the Water Drop Penetration Time (WDPT) test, which evaluates the hydrophobicity of soil and guides land treatment strategies. This thesis presents the design and development of DropBot, a custom-built drone platform engineered for the precise delivery and analysis of water droplets in WDPT tests.The DropBot, a custom drone, integrates a lightweight, 3D-printed frame with a self-leveling platform, enabling consistent droplet …

Beyond Single Metrics: A Holistic Benchmarking Framework For Low-Power Embedded Systems, Hassan Adam

UNLV Theses, Dissertations, Professional Papers, and Capstones

Modern embedded systems encounter a notable challenge in evaluation. While devices may meet traditional benchmarks, they often underperform in real-world applications due to neglected interactions at the system level. Current benchmarking suites, such as MLPerf Tiny and EEMBC ULPMark, evaluate specific metrics including computational throughput, energy efficiency, and memory usage. However, they do not consider the complex interdependencies that affect real-world performance. This thesis presents a benchmarking framework that concurrently evaluates multiple performance dimensions under realistic workloads, revealing system behaviors that are often hidden in conventional benchmarks.Through the comprehensive evaluation of three representative algorithms: Fast Fourier Transform, quantized neural network …

Autonomous Uav Swarm Formation Utilizing Gradient-Driven Contour Mapping For Radiation Source Localization, Edgar Amalyan

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents a drone swarm for radiation mapping to aid source localization. The Department of Energy advocates employing UAVs for this task, but existing approaches remain inefficient and impractical in real-world scenarios. Three custom drones are built and flight-tested. A control algorithm to follow a contour, a constant-intensity path, is designed using a gradient fit. By knowing the source’s direction, the drone swarm can fly in the optimal trajectory at every step, leaving nothing to assumption. A program is created that implements formation flight and autonomous navigation. It is tested via a software-in-the-loop simulation utilizing radiation sources and detectors …

An Edge Computing Device Optimized And Transfer Learning Enhanced Deep Learning Model For Detecting Wildfire Flame And Smoke, Giovanny Vazquez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The integration of autonomous unmanned aerial vehicles (UAVs) with edge computing technology and deep learning (DL)-based object detection offers a groundbreaking solution for real-time wildfire detection, enabling rapid data processing directly on devices and minimizing response delays in critical scenarios. However, although showing early promise, performance is often constrained by limited training data and edge computing devices that lack graphics processing unit (GPU) acceleration. This thesis seeks to address these limitations in two stages.First, this work explores the transformative potential of Transfer Learning (TL) to enhance wildfire object detection model accuracy while also investigating TL’s impact, for DL-based object detection …

High Dynamic Range Actively Quenched Silicon-Germanium Single-Photon Avalanche Diodes, Abraham Castaneda

UNLV Theses, Dissertations, Professional Papers, and Capstones

Single-photon avalanche diodes (SPADs) are solid-state devices capable of providing large current pulses in the milliampere range in response to incident photons. The large gain inherent to SPADs makes them a popular technology for photon-counting applications, but their operation can be hindered by long recharge times, which necessitates the use of active quenching to reduce dead times and increase detection rates. For the prompt gamma/neutron radiation experiments conducted at the Nevada National Security Site, photomultiplier tubes (PMTs) have been the primary photodetector of choice, but their continued use is expected to dwindle as it becomes increasingly difficult to source quality …

Mfgat: Map-Free Trajectory Prediction With Graph Attention Networks For Autonomous Vehicles, Zehra Gunindi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate trajectory prediction is a key component for ensuring safe and efficient navigation of autonomous vehicles in complex traffic scenarios. While traditional methods rely heavily on high-definition (HD) maps, these approaches face significant challenges, including high costs, limited availability, and susceptibility to rapid obsolescence. This thesis proposes an end-to-end, map-free trajectory prediction model that leverages Graph Attention Networks (GAT) to dynamically capture spatial-temporal interactions among road agents, eliminating the need for HD maps.The research introduces UNLVTraj, a novel LiDAR-based dataset collected around the University of Nevada, Las Vegas campus, specifically along Cottage Grove Street, Harmon Avenue, and Maryland Parkway. This …

Improved Electric Load Modeling Of Residential Air Conditioning, Julius Johnson

UNLV Theses, Dissertations, Professional Papers, and Capstones

The recent increase in energy production from renewable resource introduces a new challenge in managing and maintaining balance between electricity supply and demand, due to uncertainty and variability of wind speed and solar irradiance. To address this growing problem, demand-side management, such as Demand Response (DR) programs, is employed to adjust power consumption. Residential air conditioners (ACs) are the most suitable candidates for DR, due to their intensive power consumption and inherent thermal inertia that allows flexibility in their operations (by adjusting their set-point temperatures) without sacrificing customer comfort. Most prior research on AC load models assumes that such a …

El, A Navigational Assistant Based Upon Echolocation, Arthur Mazer

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis investigates the integration of a parametric speaker with a microphone array to enhance the echolocation of objects. A parametric speaker focuses ultrasonic and audible waves in a specified direction. This endows the parametric speaker with the capacity to focus waves across a wide frequency spectrum enabling adaptation of the frequency to environmental considerations.Beam forming allows one to focus a microphone array in a specified direction. The thesis investigates different microphone array configurations for the purpose of enhancing the echolocation ability of an echolocation device. The primary goal of the thesis is the construction and testing of an echolocation …

Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle, Smit R. Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, …

Fast Neutron & Gamma-Ray Scintillation And Broadband Photoluminescence From Gallium Nitride & Gallium Oxide: Developing Radiation-Hard Diagnostic Platforms, Daniel Jesus Valdes

UNLV Theses, Dissertations, Professional Papers, and Capstones

Integrated scintillation and electronics processing materials are of critical importance in environments exposed to high levels of radiation, such as nuclear fusion diagnostics and space missions. This dissertation focuses on the radiation detection capabilities of gallium oxide (Ga2O3) and gallium nitride (GaN), exploring their responses to fast neutrons and gamma rays. Using high-energy neutron beam facilities at Los Alamos Neutron Science Center (LANSCE) Flight Path 4FP60R, we exposed both Ga2O3 and GaN crystals to neutron irradiation spanning an energy spectrum ranging from 1 to 400 MeV. A Pi-Max 4 fast-gated Intensified CCD (ICCD) camera captured the transient scintillation responses for …

Real-Time Predictive Analytics For Healthcare Monitoring And Terrain Classification Using Data Streaming And Online Learning, Ayemon Baraka

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis develops a scalable, real-time predictive framework aimed at improving outcomes in healthcare monitoring and gait classification. Specifically, it addresses two primary applications: early detection of cardiovascular events, myocardial infarction (MI) and arrhythmia, through continuous analysis of ECG data streams; and adaptive terrain classification from gait data. Utilizing data streaming technologies such as Apache Kafka and Apache Spark, coupled with machine learning models, this framework enables near real-time and precise predictions from high-throughput, real-time data. Furthermore, the integration of online learning frameworks, including the River API and TensorFlow I/O, allows for continuous model adaptation, enhancing the system’s responsiveness and …

Integrating Deep Traffic Prediction And Environmental Impact Assessment Using Noisy Real-World Data In Las Vegas, Tarek Bin Zahid

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis introduces an integrated framework for advanced traffic prediction and real-time emission estimation, designed to aid urban planning and environmental monitoring. Utilizing a graph-based transformer model, it predicts traffic conditions across the Las Vegas road network, drawing on spatial and temporal data from a large-scale sensor network. The study significantly expands the dataset from 26 to approximately 900 sensors, enhancing predictive accuracy and regional coverage. Inspired by masking techniques and strategies tailored to incomplete datasets, the model effectively handles real-world, noisy data without relying on resource-intensive imputation. Innovative training approaches enable robust traffic flow predictions despite missing or imperfect …

Control Of X-Delta Arm And Self-Leveling Robot Systems For Uav Applications, Prathibha Sobha

UNLV Theses, Dissertations, Professional Papers, and Capstones

The water droplet penetration test (WDPT) is an environmental assessment method for analyzing soil properties by measuring the penetration of water droplets into soil. This test provides insights into soil moisture retention and resilience, especially valuable in fire-prone or arid regions where soil recovery and erosion control are essential. Although this project does not conduct an actual WDPT, it investigates two key robotic systems designed to support such applications: an X-delta robot arm, which simulates precise droplet delivery patterns, and a self-leveling platform that ensures stability on uneven terrain, where the X-delta robot is mounted. Together, these systems examine the …

Tracking Joint Movement Using Optical Flow, Isabella Paperno

UNLV Theses, Dissertations, Professional Papers, and Capstones

We developed an algorithm that aims to move us closer to detecting early signs of arthritis. The program processes and analyzes X-ray videos using coyote and dog cadavers as models to examine the range of motion around the hip and connecting joints using optical flow techniques that track motion and velocity. We focus on how optical flow techniques track embedded metal markers and verify accuracy through comparisons with XMALab (X-ray motion analysis lab). Once proven as an accurate alternative, the focus will switch to markerless tracking and become a proof-of-concept for optical flow to be used in place of XMALab, …

Alteration Of Peripheral Cytokines In Alzheimer’S Disease, Zhengshi Yang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with the clinical symptoms of gradual cognitive decline and memory loss. Biologically, abnormal accumulation of Aβ (Aβ) plaque and tau tangles in the brain are the core pathological hallmarks in AD. Although inflammatory response is not specific to AD, emerging evidence suggests that the disrupted innate immune system within the central nervous system, particularly microglial activation, might act as the bridge linking Aβ aggregation to pathological phosphorylation and aggregation of tau. The inflammatory response was suggested to initially have a neuroprotective role of attempting to clear Aβ plaques, and then become neurotoxic …