Computer Sciences Commons^™

Prototyping A 3d Reconstruction Of Fly Photoreceptors: From Traditional Computer Vision Techniques To 3d Visualization, Kunal Jain

Graduate Masters Theses

The Drosophila fruit fly is a well-established model organism for studying vision and neural perception. In this research, we focused on segmenting and analyzing photoreceptor cells in the Drosophila retina, specifically rhabdomeres. To facilitate our study, we acquired a comprehensive 3D dataset of Drosophila retina EM images and developed an automated segmentation pipeline using computer vision techniques. We evaluated the performance of our pipeline using automated metrics on Wild Type CS 1 and Nina D1 Mutant Drosophila datasets and prototyped a 3D model of segmented cells. The generated segmentation masks and 3D models of photoreceptor cells contribute to a better …

Universal Back-End Design, Jason Kalili

LMU Theses and Dissertations

Accessibility in back-end development is often overlooked, with the majority of discussions and efforts centered on front-end design. To make applications usable for a wider audience, developers must also prioritize incorporating accessibility from the back-end. Back-end web accessibility encompasses the design and development of web-based systems and applications that are accessible to all users, including those with disabilities. This involves optimizing the underlying code and infrastructure for accessibility and implementing features that enable users with disabilities to navigate and interact with the site or application. Ensuring back-end web accessibility is crucial for creating an inclusive online environment accessible to everyone, …

An Application Risk Assessment Of Werner Enterprises, Nathan Andres

Theses/Capstones/Creative Projects

Risk assessments provide a systematic approach to identifying potential risks that could negatively impact an organization’s operations, financial performance, and reputation. Using a risk assessment, companies can evaluate potential risks and vulnerabilities, prioritize them based on their potential impact, and develop strategies to manage and address these risks effectively.

Werner Enterprises Inc. is a nationally known trucking company headquartered in Omaha, Nebraska. Our cybersecurity capstone project motivation was to partner with Werner to produce an assessment of known application risks in a functional way that can be repeated for all of Werner’s applications. To achieve this, we created a risk …

Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski

Honors Scholar Theses

Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …

Artificial: A Study On The Use Of Artificial Intelligence In Art, Hayden Ernst

Theses/Capstones/Creative Projects

In the past three to five years there have been significant improvements made in AI due to improvements in computing capacity, the collection and use of big data, and an increase in public interest and funding for research. Programs such as ChatGPT, DALL•E, and Midjourney have also gained tremendous popularity in a relatively short amount of time. This led me to this project in which I aimed to gain a deeper understanding of these art generator AI and where they fit into art as a whole. My goal was to give recommendations to museums and exhibits in Omaha on what …

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 …

The State And Use Of Virtual Tutors, Thomas Anthone

Theses/Capstones/Creative Projects

Virtual tutoring is the process by which students and teachers participate in the learning experience in an online, virtual, or networked environment. This process can not only separate the participants from each other in a physical space, but it can also separate them by time. Virtual tutoring can take the form of the group of students coming together synchronously in an online setting and receiving lessons from a single tutor, or by asynchronous learning in which the teacher pre-plans lessons in advance that the students consume on their own time. The advent of online learning technologies and virtual learning environments …

Towards Privacy-Preserving Social Media Networks: Protecting The Facial Privacy Of Images Uploaded On Social Media, Ahsi Lo

Theses and Dissertations

Since the 2000s, social media has allowed individuals the ability to communicate online. As the popularity of social media increased, the sharing of information such as pictures increased as well. Recently, there have been privacy concerns about the information shared online such as cases where third parties were able to gain access to users’ information without being given explicit access through scraping or other means. When user images are scraped from social media, there is a risk that these individuals can be identified o✏ine. Bystanders, who may be captured in images also run this risk of identification. This research investigates …

Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly

School of Computing: Dissertations, Theses, and Student Research

The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …

Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam

School of Computing: Dissertations, Theses, and Student Research

Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS …

Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin

All Dissertations

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …

Integrating Ai-Generative Tools In Web Design Education: Enhancing Student Aesthetic And Creative Copy Capabilities Using Image And Text-Based Ai Generators, Jason Lively, James Hutson, Elizabeth Melick

Faculty Scholarship

Artificial Intelligence (AI) is poised to disrupt all levels of education. The recent advances in the generative capabilities of new chatbots, AI art generators, and large language models have upended the art and design development pipeline. At the same time, the focus has remained on the nature of creativity and the role of humans in the creative process, prompting calls to ban AI art, bring lawsuits over copyright infringement, and demand universal watermarks to identify AI-generative content. Regardless of the outcome of such litigation, AI has already radically altered the workflow for artists and designers. This case study aims to …

Enhancing Institutional Assessment And Reporting Through Conversational Technologies: Exploring The Potential Of Ai-Powered Tools And Natural Language Processing, James Hutson, Daniel Plate

Faculty Scholarship

This study explores the potential of conversational technologies, AI-powered tools, and natural language processing (NLP) in enhancing institutional assessment and reporting processes in higher education. The traditional approach to assessment often involves labor-intensive manual analysis of extensive data and documents, which burdens institutions. To address these challenges, AI-powered tools, such as ChatGPT, LangChain, Poe, Claude, and others, along with NLP techniques, are investigated in relationship to their ability to improve institutional assessment practices and output. By leveraging these advanced technologies, assessment officers and institutional effectiveness, researchers can engage in dynamic conversations with data, transforming spreadsheets and documents from static artifacts …

Predicting The Pebcak: A Quantitative Analysis Of How Cybersecurity Education, Literacy, And Awareness Affect Individual Preparedness., Annie Goodman

Theses/Capstones/Creative Projects

This essay explores the relationship between individuals' cybersecurity education, literacy, awareness, and preparedness. While cybersecurity is often associated with complex hacking scenarios, the majority of data breaches and cyber-attacks result from individuals inadvertently falling prey to phishing emails and malware. The lack of standardized education and training in cybersecurity, coupled with the rapid expansion of technology diversity, raises concerns about individuals' cybersecurity preparedness. As individuals are the first line of defense and the weakest link in cybersecurity, understanding the influence of education, literacy, and awareness on their adherence to best practices is crucial. This work aims to survey a diverse …

Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer

School of Cybersecurity Faculty Publications

The concept of the Internet of Things (IoT) spans decades, and the same can be said for its inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable potential in expanding care. However, the application of the IoT in healthcare is fraught with an array of challenges, and also, through it, numerous vulnerabilities that translate to wider attack surfaces and deeper degrees of damage possible to both consumers and their confidence within health systems, as a result of patient-specific data being available to access. Further, when IoT health devices (IoTHDs) are developed, a diverse range of …

Improving Classification In Single And Multi-View Images, Hadi Kanaan Hadi Salman

Graduate Theses and Dissertations

Image classification is a sub-field of computer vision that focuses on identifying objects within digital images. In order to improve image classification we must address the following areas of improvement: 1) Single and Multi-View data quality using data pre-processing techniques. 2) Enhancing deep feature learning to extract alternative representation of the data. 3) Improving decision or prediction of labels. This dissertation presents a series of four published papers that explore different improvements of image classification. In our first paper, we explore the Siamese network architecture to create a Convolution Neural Network based similarity metric. We learn the priority features that …

Practical Indirect Control Flow Analysis For Binary Executables, Haotian Zhang

Computer Science and Engineering Dissertations - Archive

Resolving indirect control flow is one of the fundamental challenges in binary analysis. Improving the accuracy of the indirect control flow analysis is vital to the binary analysis domain. Many analysis algorithms and security techniques rely on a precise indirect control flow result, such as recursive disassembling, control flow integrity, data-flow analysis, etc. Incorrect or even inaccuracy indirect control flow analysis results can compromise or even break the assumptions of these analyses. This thesis explores this topic from two directions, altering the indirect control flow analysis to make it more suitable for different scenarios and improving the accuracy of indirect …

Neural Network Architecture Optimization Using Reinforcement Learning, Raghav Vadhera

Computer Science and Engineering Dissertations - Archive

Deep learning has emerged as an increasingly valuable tool, employed across a myriad of applications. However, the intricacies of deep learning systems, stemming from their sensitivity to specific network architectures, have rendered them challenging for non-experts to harness, thus highlighting the need for automatic network architecture optimization. Prior research predominantly optimizes a network for a single problem through architecture search, necessitating extensive training of various architectures during optimization.\\ To tackle this issue and unlock the potential for transferability across tasks, this dissertation presents a groundbreaking approach that employs Reinforcement Learning to develop a network optimization policy based on an abstract …

Open Source Intelligence For Cybersecurity Events Via Twitter Data, Dakota Dale

Graduate Theses and Dissertations

Open-Source Intelligence (OSINT) is largely regarded as a necessary component for cybersecurity intelligence gathering to secure network systems. With the advancement of artificial intelligence (AI) and increasing usage of social media, like Twitter, we have a unique opportunity to obtain and aggregate information from social media. In this study, we propose an AI-based scheme capable of automatically pulling information from Twitter, filtering out security-irrelevant tweets, performing natural language analysis to correlate the tweets about each cybersecurity event (e.g., a malware campaign), and validating the information. This scheme has many applications, such as providing a means for security operators to gain …

On The Predictability Of Appropriate Prosody Of Dialog Markers Directly From The Local Context, Anindita Nath

Open Access Theses & Dissertations

Today's state-of-the-art spoken dialog systems lack context-appropriate prosody in their responses, often making them sound unnatural. Better modeling of this contextual dependency would enable natural prosodic responsiveness. Accordingly, this dissertation explores the extent to which the prosody of a dialog marker can be predicted directly from the prosody of its local context. The prediction performance was evaluated in terms of the similarity between the predicted and the observed prosodic features as measured by the reduction of root mean square error from the baseline. This prediction task was accomplished for multiple combinations of various sets of context features and different machine …

Analyzing Software Maintenance Through Machine Learning And Mining Software Repositories Approaches, Sayed Mohsin Reza

Open Access Theses & Dissertations

The rapid growth of software systems demands meticulous planning and maintenance to accommodate the evolution of the code base over extended periods. Without maintenance, software systems will become more complex, low in quality, and hence unsustainable. Software engineers who perform maintenance often strive to optimize code quality or minimize code smells in a timely manner. Several techniques have been used to detect code quality or code smells as a part of software maintenance. Most of these techniques are based on heuristics, which create detection rules using a few metrics. These approaches have reasonable accuracy but do not work in cross-project …

A Framework To Build Secure Microservice Architecture, Wai Yan Elsa Tai Ramirez

Open Access Theses & Dissertations

Microservice architecture has become a popular architecture style in recent years. According to a series of surveys conducted by IBM Market Development & amp; Insights in 2021, microservices are heavily used in many industries worldwide. With an increase in the adoption of microservice architecture in the development of applications, such as Netflix, Amazon, Uber, Ebay, Twitter, DoorDash, Capital One, and Monzo, and the increase in security breaches in microservice based systems (e.g., the DoorDash data breaches in 2019 and 2022, Twitter data breach in 2022, and compromises to Netflixâ??s infrastructure), there is a need to examine and understand security issues …

Detecting Complex Cyber Attacks Using Decoys With Online Reinforcement Learning, Marcus Gutierrez

Open Access Theses & Dissertations

Most vulnerabilities discovered in cybersecurity can be associated with their own singular piece of software. I investigate complex vulnerabilities, which may require multiple software to be present. These complex vulnerabilities represent 16.6% of all documented vulnerabilities and are more dangerous on average than their simple vulnerability counterparts. In addition to this, because they often require multiple pieces of software to be present, they are harder to identify overall as specific combinations are needed for the vulnerability to appear.

I consider the motivating scenario where an attacker is repeatedly deploying exploits that use complex vulnerabilities into an Airport Wi-Fi. The network …

Opportunities And Challenges From Major Disasters Lessons Learned Of Long-Term Recovery Group Members, Eduardo E. Landaeta

Graduate Program in International Studies Theses & Dissertations

Natural hazards caused by the alteration of weather patterns expose populations at risk, with an outcome of economic loss, property damage, personal injury, and loss of life. The unpredictability of disasters is a topic of concern to most governments. Disaster policies need more attention in aligning mitigation opportunities with disaster housing recovery (DHR). The effect of flooding, which primarily impacts housing in coastal areas, is one of the most serious issues associated with natural hazard. Flooding has a variety of causes and implications, especially for vulnerable populations who are exposed to it. DHR is complex, involving the need for effective …

Design, Modeling, And Simulation Of Secure X.509 Certificate Revocation, Sai Medury

Masters Theses and Doctoral Dissertations

TLS communication over the internet has risen rapidly in the last seven years (2015--2022), and there were over 156M active SSL certificates in 2022. The state-of-the-art Public Key Infrastructure (PKI), encompassing protocols, computational resources, and digital certificates, has evolved for 24 years to become the de-facto choice for encrypted communication over the Internet even on newer platforms such as mobile devices and Internet-of-Things (IoT) (despite being low powered with computational constraints). However, certificate revocation is one sub-protocol in TLS communication that fails to meet the rising scalability demands and remains open to exploitation. In this dissertation, the standard for X.509 …

Development Of A Cost-Constrained Intelligent Prosthetic Knee With Real-Time Machine Learning, Predictive Stumble Control, Lucas Jonathan Galey

Open Access Theses & Dissertations

The field of biomechatronics is evolving quickly with advances in computer science, biology, and electrical and mechanical engineering. Coupled with increased interests in machine learning (ML) across all industry sectors, there are opportunities to leverage advanced analytics in uniquely complex problems. This study aimed to deploy real-time ML predictions in a novel microprocessor-controlled prosthetic knee (MPK) device capable of identifying and responding to stumble-events to reduce amputee fall prevalence. Innately, stumbling is a chaotic event. Current MPKs operate by detecting gait characteristics and reacting to preprogrammed states. While these systems are beneficial in significant ways, such as energy expenditure and …

Thermal Behavior Of Plain And Fiber-Reinforced Rigid Concrete Airfield Runways, Arash Karimi Pour

Open Access Theses & Dissertations

The environmental condition and temperature gradient are important factors resulting in concrete airfield runways cracking during the time. Rigid concrete airfield runways experience different thermal gradients during the day and night due to changes in air temperature. Curling and thermal expansion stresses are the main consequences resulting in various types of cracking over the surface and thickness of concrete airfield runways and increasing maintenance costs. The curvature of concrete slabs increases with an increase in the temperature gradient which is amplified when runways open to traffic. Additionally, the combination of the curling and shrinkage stresses, in rare circumstances, can be …

Advancing Iot Security Through Blockchain-Based Decentralized Platform And Ai-Powered Digital Forensics, Ruipeng Zhang

Masters Theses and Doctoral Dissertations

The proliferation of Internet of Things (IoT) devices, from smartphones, smart thermostats to smart home security systems, is revolutionizing our society and daily lives. However, it also has posed significant challenges to IoT security and forensics. To tackle those challenges, innovative solutions are designed to enhancing IoT security and accelerating investigation of cybersecurity incidents by leveraging recent technological advancements in Blockchain and Artificial Intelligence (AI). First, an IoT service platform, called DISP, is proposed to improve the security and interoperability of IoT systems. DISP utilizes the consortium blockchain technology to transform centralized, insecure IoT communications into decentralized, secure, and traceable …

A Brascamp-Lieb–Rary Of Examples, Anina Peersen

Mathematics, Statistics, and Computer Science Honors Projects

This paper focuses on the Brascamp-Lieb inequality and its applications in analysis, fractal geometry, computer science, and more. It provides a beginner-level introduction to the Brascamp-Lieb inequality alongside re- lated inequalities in analysis and explores specific cases of extremizable, simple, and equivalent Brascamp-Lieb data. Connections to computer sci- ence and geometric measure theory are introduced and explained. Finally, the Brascamp-Lieb constant is calculated for a chosen family of linear maps.

Analysis Of Post-Translational Modifications (Ptm) Crosstalk, Amit Das

Theses and Dissertations

Mass spectrometry-based proteomics is a powerful tool for identifying post-translational modifications (PTMs) across the proteome. O-GlcNAcylation and phosphorylation are two PTMs that play crucial roles in regulating cellular processes, including cardiac contractile function. Dysregulation of these PTMs has been implicated in the development and progression of diabetic cardiomyopathy. In this study, we aimed to investigate the interplay between O-GlcNAcylation and phosphorylation in healthy and type 2 diabetic hearts, with a specific focus on the functional relationships between these PTMs and their potential therapeutic implications.

Utilizing mass spectrometry data, we identified and quantified specific PTMs on myofilament proteins, uncovering 1354 O-GlcNAcylated …