Computer Engineering Commons^™

Diegetic Sonification For Low Vision Gamers, Jhané Dawes

Master's Theses

There are not many games designed for all players that provide accommodations for low vision users. This means that low vision users may not get to engage with the gaming community in the same way as their sighted peers. In this thesis, I explore how diegetic sonification can be used as a tool to support these low vision gamers in the typical gaming environment. I asked low vision players to engage with a prototype game level with two diegetic sonification techniques applied, without the use of their corrective lenses. I found that participants had more enjoyment and experienced less difficulty …

Orms And Database Design, Kalim Dumas

Honors Program: Senior Projects (Public)

This thesis explores the relationship between database design and Object-Relational Mapping (ORM) design, investigating how they have evolved together and influenced each other. It addresses a theoretical discussion, a practical implementation, and some observations regarding integrating an ORM into my Senior Design project. My Senior Design project was originally built without the intention of implementing an ORM.

There are a lot of complicated discrepancies between Relational Databases (RDBs) and Object-Oriented Programming Languages (OOPLs), called the Impedance Mismatch Problem. The fact that they are both foundational pillars in software engineering means that one cannot simply change to match the other. ORMs …

Text-To-Speech Animation: Generating Visuals Based On Phonetic Spelling, Colin Tomcak

Theses/Capstones/Creative Projects

Speech is a complex field, and remarkably difficult to master. There exist many groups who could use more tools to help improve their pronunciation of English words. The goal of this project was to create a text-to-speech animation program as an addition to our group capstone, Pronunciation Pal. Pronunciation Pal is a web-based application meant to assist those who are deaf or hard of hearing in improving their pronunciation, likely as an addition to therapy with a speech pathologist. This application uses tools like diagrams and references to help users better understand how to pronounce a word. The goal of …

Data Analysis Of Twitter’S Nasdaq100 Sentiments And Topics As Indicators For News Articles Retrieval: Fine-Tuning Roberta And Rag, Kagan Timur

ICT

This study explores the combination of sentiment analysis with vader-lexicon and semantic analysis with latent dirichlet allocation to identify real-life events, particularly in the context of Twitter datasets. While sentiment analysis alone may not provide accurate guidance, the inclusion of semantic analysis enhances the research process by helping to identify relevant news articles and comprehend brand perception on social media. Furthermore, the study fine-tunes the RoBERTa model specifically for question-answering tasks

Cultural Awareness Application, Bharat Gupta

Electronic Theses, Projects, and Dissertations

In an increasingly interconnected global landscape, cultural awareness and competency have become indispensable skills for individuals and organizations alike. This paper introduces a pioneering cultural awareness application, grounded in the Cultural Orientation Model—a comprehensive framework devised by Dr. Walker [8]to guide individuals in understanding, appreciating, and effectively engaging with diverse cultures. The application encompasses ten primary dimensions, each representing fundamental aspects of social life shared by members of any socio-cultural environment. Through a combination of cultural education, interactive learning, guidance on cultural etiquette, and integration of cultural events, the application aims to foster empathy, tolerance, and effective cross-cultural communication skills. …

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 …

Experiment Development And Validation Of A Granular Jamming Robotic Gripper, Jacob R. Dowd

UNLV Theses, Dissertations, Professional Papers, and Capstones

A granular jamming gripper (GJG) is widely known as a Universal Gripper because of the wide range of objects that it can grasp and the simplicity of control, design, and manufacturing. Despite multitude of research improving the GJG, here, we focus on the base version of the GJG and attempt to glean the range of objects that it may reliably grasp. Despite the limited range of objects, which were a sphere, rectangular prism, and cylinder, we gleaned geometric properties as it relates to successful and unsuccessful grasping. This was based on the two types of testing: push and pull testing …

Gamification Of Speech Therapy With Pronunciation Pal, Parker Zbylut

Theses/Capstones/Creative Projects

This capstone report examines the theory and implementation behind applying game design principles to educational applications, and explores their implementation in an educational game through the Pronunciation Pal application. The gamification of learning tools aims to increase learners' engagement and attentiveness with a subject by restructuring content using game design principles of challenges, rewards and feedback. Feedback can be delivered via visuals and/or sounds, as well as regular indicators of player progress and accomplishment. In addition, a successful game implementation establishes challenges to facilitate a player's intrinsic desire to continue playing and improving at the skills presented by the game. …

From Bits To Beds: Design And Implementation Of A Hotel Booking System A Coding Project, Alexa Gilman

University Honors College

This thesis presents a comprehensive hotel booking system designed and implemented to showcase the transition "From Bits to Beds". There are two main motivations behind this project: firstly, to provide users with a user-friendly and efficient platform for booking accommodations. Secondly, it serves as a great learning opportunity, providing hands-on practice with coding, collaboration with teammates, and exposure to real-world challenges. The system utilizes technologies such as JavaScript, Express.js, and HTML/CSS to offer features like browsing hotels, filtering options, user authentication, and booking management. The implementation of this project demonstrates a successful integration of backend and frontend components, ensuring reliability …

In-Training Explainability Frameworks To Make Black-Box Machine Learning Models More Explainable., Asuman Cagla Acun

Electronic Theses and Dissertations

Despite ongoing efforts to make black-box machine learning models more explainable, transparent, and trustworthy, there is growing advocacy for using only inherently interpretable models for high-stake decision-making. Post-hoc explanations have recently been criticized for learning surrogate models that may not accurately reflect the actual mechanisms of the original model and for adding computational burden at prediction time. We propose two novel explainability approaches to address these limitations: pre-hoc explainability and co-hoc explainability. These approaches integrate explanations derived from an inherently interpretable white-box model into the learning stage of the black-box model without compromising accuracy. Unlike post-hoc methods, our approach does …

Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell

Computer Science and Computer Engineering Undergraduate Honors Theses

The management of weeds in crop fields is a continuous agricultural problem. The use of herbicides is the most common solution, but herbicidal resistance decreases effectiveness, and the use of herbicides has been found to have severe adverse effects on human health and the environment. The use of autonomous drone systems for weed elimination is an emerging solution, but challenges in GPS-based localization and navigation can impact the effectiveness of these systems. The goal of this thesis is to evaluate techniques for minimizing localization errors of drones as they attempt to eliminate weeds. A simulation environment was created to model …

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 …

Particle Swarm Optimization For Training Quadrotor Pid Controller, Eric Xavier Rodriguez

Theses and Dissertations

The objective of this research is to establish a fundamental approach to tuning PID (Proportional-Integral-Derivative) parameters for a simulated quadrotor drone. Implementing a PID controller for autonomous flight provides a straightforward and efficient method for monitoring and correcting robotic movement based on the robot's current state. However, applying a PID approach to a quadrotor's flight controller poses challenges, such as assigning multiple parameters to control an inherently under-actuated system. This includes the need to find optimal parameter values that reduce the likelihood of large overshoots and lengthy adjustment times. Ineffectively tuning PID parameters can have detrimental effects on autonomously …

Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, Sakshi Nakashe

Electronic Theses, Projects, and Dissertations

The need for automatic speech recognition in air traffic control is critical as it enhances the interaction between the computer and human. Speech recognition helps to automatically transcribe the communication between the pilots and the air traffic controllers, which reduces the time taken for administrative tasks. This project aims to provide improvement to the Automatic Speech Recognition (ASR) system for air traffic control by investigating the impact of convolution LSTM model on ASR as suggested by previous studies. The research questions are: (Q1) Comparing the performance of ConvLSTM with other conventional models, how does ConvLSTM perform with respect to recognizing …

Deep Learning Using Vision And Lidar For Global Robot Localization, Brett E. Gowling

Master's Theses

As the field of mobile robotics rapidly expands, precise understanding of a robot’s position and orientation becomes critical for autonomous navigation and efficient task performance. In this thesis, we present a snapshot-based global localization machine learning model for a mobile robot, the e-puck, in a simulated environment. Our model uses multimodal data to predict both position and orientation using the robot’s on-board cameras and LiDAR sensor. In an effort to minimize localization error, we explore different sensor configurations by varying the number of cameras and LiDAR layers used. Additionally, we investigate the performance benefits of different multimodal fusion strategies while …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

Understanding The Limits Of Deep Packet Inspection For Network Traffic Classification, Herman Ramey

Open Access Theses & Dissertations

We present our human network application labeling system that contributes a new level of distinction between the network traffic that should be labeled from the network traffic that should not be labeled. This distinction improves the label accuracy of the training data set produced from the human labeled data and will subsequently improve the performance of supervised machine learning classifiers used for network traffic classification. This system also allows for the human network user to label traffic, with little effort, in a manner consistent with normal network usage, i.e., no need for a contrived experiment. Lastly, we use human supplied …

Mav Localization In Gps-Denied Environments And Synthetic Data Collection In Challenging Simulated Conditions, Julio A. Reyes Munoz

Open Access Theses & Dissertations

The development of unmanned aerial systems presents an opportunity for conducting industrial inspections in environments where traditional navigation systems, such as the Global Navigation Satellite System (GNSS), are compromised. This dissertation investigates the implementation of a micro aerial vehicle (MAV) capable of autonomous data acquisition in complex, GNSS-degraded industrial settings. The primary challenge addressed is the robust localization of MAVs, a critical aspect in ensuring reliable operation under varying and uncertain environmental conditions.

The work is divided into two main parts. The first part focuses on the design and integration of a MAV system specifically for power plant inspections in …

Geometric Multi-Resolution Analysis Across Signals, Images, And Networks, Felicia Schenkelberg

Dartmouth College Master’s Theses

This research delves into the transformative potential of Geometric Multi-Resolution Analysis (GMRA) as a robust tool for dimensionality reduction and data analysis in the context of high-dimensional graphs. Statistical techniques for classification have historically been tailored for scenarios wherein the number of observations significantly exceeds the number of features, a paradigm characteristic of low-dimensional datasets. However, recent advancements in technologies have ushered in a transformative era in data collection practices across diverse domains, resulting in the acquisition of extensive feature measurements. As a result of this shift, datasets have transitioned into a high-dimensional realm wherein the number of features significantly …

High-Altitude Ballooning And Payload Design, Matthew Smith

Honors College Theses

The Icarus project began in 2017 where a team performs high-altitude balloon (HAB) launches to conduct atmospheric and payload design research. The project involves sending a data-collecting payload containing recording equipment to high altitudes (~100,000 feet). This paper outlines the Icarus project as well as the efforts to design a payload that will remain stable throughout flight while also protecting the equipment housed within the payload shell. SOLIDWORKS computer-aided design (CAD) software was used to design a unique payload system. The payload parts were manufactured with PLA filament using a Prusa MK4 3D printer. The secondary goal of this thesis …

Design And Application Of Smart Systems To Address Analytical Problems, Lucas B. Ayres

All Dissertations

This dissertation is a multidisciplinary effort that integrates low-cost analytical instrumentation, redox chemistry, and artificial intelligence to overcome existing limitations in the fields of wearable sensing technology, Deep Eutectic Solvents (DES), and antioxidant chemistry. The overall goal behind each implemented strategy is to enhance the accuracy, efficiency, and accessibility of analytical processes and technologies. A general overview of the thesis, along with the research outcomes is included in Chapter One. The theoretical framework of this dissertation is presented in Chapter Two. Chapter Three describes the development of a wearable platform (sensor and instrumentation) to rapidly detect (~20 minutes) S. aureus …

Hardware Trojan Detection Utilizing Graph Neural Networks And Structural Checking, Hunter Nauman

Graduate Theses and Dissertations

The integrated circuit (IC) industry has experienced exponential growth, particularly in the complexity and scale of hardware designs. To sustain this growth, faster development cycles and cost-effective solutions have been the focus for many companies. One strategy to maintain this growth is through the incorporation of third-party intellectual property (IP) into the IC design process. Outsourcing the production of sub-components reduces development time and enables faster time-to-market, however, this approach also introduces the threat of Hardware Trojans. Hardware Trojans, defined as any malicious modification or addition to an IC, pose significant security risks due to their small size, low activation …

Recommender System Design And Multi-Channel Pricing: Personalization Strategies For Online Platforms, Hao Zhang

Dissertations and Theses Collection (Open Access)

The advancement of mobile technology and rising consumer demands have contributed to the unprecedented growth of online platforms. In online platforms, recommender systems connect with multistakeholders who have different interests. Designing recommender systems to balance the benefit of multistakeholders is important for these platforms. In addition, price is an important factor influencing consumers’ purchase decisions. An increasing number of online platforms introduce multiple sales channels. Optimizing multiple-channel prices is vital for these platforms. Thus, this thesis designs multistakeholder recommender systems and multi-channel pricing strategies for online platforms through the following two works.

The first work focuses on designing multistakeholder recommender …

Investigating Factors Influencing Blockchain Adoption In Saudi Healthcare Data Management, Noura Mohammad Alkhalifah

Theses and Dissertations

Blockchain technology can potentially address security and privacy issues concerning the collection, storage, and sharing of healthcare data. However, its adoption within the healthcare sector is nascent in Saudi Arabia. This underutilization prompted our investigation into the determinants influencing blockchain adoption, intending to fully empower the Saudi healthcare sector to leverage blockchain capabilities. To achieve this, an extensive literature review was conducted to identify the pivotal factors encompassing technology, organization, and environment (TOE) that affect the successful implementation of blockchain technologies in managing healthcare data within the Saudi context. Utilizing the TOE framework, this study formulated three hypotheses concerning the …

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 …

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

Development Of A Multi-Use Modular Microfluidic Platform Using 3d Printing, Carson Emeigh

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Microfluidic lab-on-a-chip (LoC) technology has driven numerous innovations due to their ability to perform laboratory-scale experiments on a single chip using microchannels. Although LoC technology has been innovative, it still suffers from limitations related to its fabrication and design flexibility. Typical LoC fabrication, with photolithography, is time consuming, expensive, and inflexible. To overcome the limitations of LoC devices, modular microfluidic platforms have been developed where multiple microfluidic modules, each with a specific function or group of functions, can be combined on a single platform. Modular microfluidics have overcome some of the limitations of LoC devices, but currently, their fabrication is …

Attention Guided Data Augmentation For Improving The Classification Performance Of Vision Transformers., Nada Baili

Electronic Theses and Dissertations

For over a decade, Deep Neural Networks (DNNs) have been rapidly progressing and achieving great success, forming a robust foundation of state of the art machine learning algorithms that impacted various domains. The advances in data acquisition and processing have undeniably played a major role in these breakthroughs. Data is a crucial component in building successful DNNs, as it enables machine learning models to optimize complex architectures, necessary to perform certain difficult tasks. However, acquiring large-scale data sets is not enough to learn robust models with generalizable features. Instead, an ideal training set should be diverse enough and contain enough …

Multithreaded Applications On The Heterogeneous Research Computing Environment., Sungbo Jung

Electronic Theses and Dissertations

Bioinformatics is a domain that has experienced rapid research growth in recent years, as evidenced by the increasing number of articles in biomedical databases such as PubMed, which adds over a million publications every year. However, this also poses a challenge for researchers who need to find relevant citations for their work. Therefore, developing efficient indexing and searching methods for text data is crucial for Bioinformatics. One key technique for information retrieval is document inversion, which involves creating an inverted index to enable efficient searching through vast collections of text or documents. This Ph.D. research aims to design the research …

Cloud Computing Integration Into Mixed-Reality: Physical To Abstraction, Yassine Chahid, Patrick Slattery

Publications and Research

This research evaluates the progression of cloud computing and mixed-reality technologies, and to identify how these technologies influence advancements in the latter. Both cloud computing and mixed reality have significantly impacted the IT field and the services available to the public and various institutions. Cloud computing provides a valuable way to process information or allocate computational resources on otherwise limited hardware. Augmented or virtual reality hardware would greatly benefit from this by offloading resource-intensive tasks to other machines. The research methodology involves analyzing essential components of both innovations, divided into multiple categories. These components range from physical, hardware-based elements to …