Computer Sciences Commons^™

Low-Complexity Three-Dimensional Aoa-Cross Geometric Center Localization Methods Via Multi-Uav Network, Baihua Shi, Yifan Li, Guilu Wu, Riqing Chen, Shihao Yan, Feng Shu

Research outputs 2022 to 2026

The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. …

Oriented Crossover In Genetic Algorithms For Computer Networks Optimization, Furkan Rabee, Zahir M. Hussain

Research outputs 2022 to 2026

Optimization using genetic algorithms (GA) is a well-known strategy in several scientific disciplines. The crossover is an essential operator of the genetic algorithm. It has been an active area of research to develop sustainable forms for this operand. In this work, a new crossover operand is proposed. This operand depends on giving an elicited description for the chromosome with a new structure for alleles of the parents. It is suggested that each allele has two attitudes, one attitude differs contrastingly with the other, and both of them complement the allele. Thus, in case where one attitude is good, the other …

Sprout: Using A Garden Metaphor To Visualize And Support Customizable And Collaborative Health Tracking, Pape Sow Traoré

Dartmouth College Master’s Theses

Self-tracking tools have become increasingly popular, especially with the advent of wearable technology and smartphone applications. However, traditional tracking tools often display data in a quantitative format that can be overwhelming and cause users to abandon their tracking efforts. Additionally, these tools typically provide a generic user experience and are designed from a single-user perspective, lacking external support. To overcome these limitations, we develop Sprout, a mobile data-tracking application that offers a more qualitative, customizable, and collaborative experience for health monitoring and management. Sprout uses a garden metaphor to visually represent health information and allows users to tailor their …

Brif: A Novel And Efficient Implementation Of Random Forests Based On Bit Packing And Parallel Computing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Random forests are powerful and popular machine learning methods. While general principles of tree induction are straightforward and well-understood, the numerous algorithmic treatments implemented in software tools, as well as their impacts on performance, are less familiar to most users. This paper introduces a new random forest toolkit (the ‘brif’ package in R and Python) along with its key algorithmic design features, and demonstrates the effects of the forest’s hyper-parameters such as the split search method, tree depth and the voting mechanism, on the classification performance. Summaries of benchmarking experiments are also presented. Results show that ‘brif’ stands out among …

Using Immersive Technology To Improve Mechanical Design: Use Cases, A Review Of Current Technology, And An Experiment In Requirement Elicitation In Virtual Reality, William Hawthorne

All Theses

There has been a growing trend in the use of immersive technologies within engineering design. This research is focused on understanding how Virtual Reality (VR) technologies support design reviews. Modern tools including virtual reality hardware and software were tested for current capabilities and challenges. In a review of literature, two key gaps are identified: the rapid advancements of VR and AR technology and limited formal studies to determine the costs and benefits of immersive technology within engineering design reviews. This research has resulted in three key outcomes. First, use cases of immersive reality technologies are identified, through the lens of …

Modeling And Predicting Emerging Threats Using Disparate Data, Ismael Villanueva Miranda

Open Access Theses & Dissertations

Early detection is crucial to mitigate the impact of emerging threats. This work proposes four innovative frameworks that build machine learning and deterministic epidemiological models using multiple domain-specific datasets to detect the onset of emerging threats in two domains: infectious diseases and cybersecurity. Our models are designed to detect infectious disease outbreaks, model their spread, detect malware activity, and analyze the relationship between software/hardware weaknesses and attack techniques.

First, we present a novel framework to detect multiple infectious disease outbreaks by integrating standardized disease-specific domain knowledge and public search trend data. Our framework showed high performance in identifying infectious disease …

Enhancing Basic Geology Skills With Artificial Intelligence: An Exploration Of Automated Reasoning In Field Geology, Perry Ivan Quinto Houser

Open Access Theses & Dissertations

This thesis explores the use of Artificial Intelligence, specifically semantics, ontologies, and reasoner techniques, to improve field geology mapping. The thesis focuses on two use cases: 1) identifying a geologic formation based on observed characteristics; and 2) predicting the geologic formation that might be expected next based upon known stratigraphic sequence. The results show that the ontology was able to correctly identify the geologic formation for the majority of rock descriptions, with higher search results for descriptions that provided more detail. Similarly, the units expected next were correctly given and if incorrect, would provide a flag to the field geologist …

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

Turkish Journal of Electrical Engineering and Computer Sciences

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

Multiple Sequence Alignment Guided By Clam, Emily Light

Senior Honors Projects

For my honors project, I am continuing my research with my academic advisor, Dr. Daniels on creating an approach to the Multiple Sequence Alignment problem in the Rust programming language. This approach will be attached to Dr. Daniels’ CLAM (Clustered Learning for Approximate Manifolds) to enable it to globally and locally align DNA sequences. This research was divided into three separate parts: building the algorithms, implementing them into CLAM’s metric, and measuring and improving the performance of the algorithms. This project includes two separate but related algorithms; Needleman-Wunsch algorithm and the Smith-Waterman algorithm.

The Needleman-Wunsch algorithm takes in two DNA …

Modeling User Behavior For Cyber Security With Formal Methods And Agent Based Simulation, Hamdah Albalawi

Theses and Dissertations

Despite society’s positive outlook, technology poses real cyber security threats. Technology’s benefits can sometimes make it difficult to believe that potential threats lurk behind every device and platform. As cybercrime rises, we have come to rely increasingly on flawed devices and services. As cyberattacks become more prevalent, security professionals are committed to developing more robust and dependable security solutions. In cyber security, human error is regarded as the weakest link since all technical security solutions are vulnerable to human error. Among other human characteristics, risk-taking, logical decision-making, extraversion, and gender can significantly affect cyber security. However, there still is the …

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

Master's Theses

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

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

The Identification Of Rogue Access Points Using Channel State Information, Irene Mcginniss

Theses, Dissertations and Culminating Projects

Today's wireless networks (Wi-Fi) handle more significant numbers of connections, deploy efficiently, and provide increased reliability and high speeds at low cost. The ability of rogue access points (RAPs) to mimic legitimate APs makes them the most critical threat to wireless security. APs are found in coffee shops, supermarkets, stadiums, buses, trains, airports, hospitals, theaters, and shopping malls.

Rogue access points (RAP) are unauthorized devices that connect to legitimate access points and networks and bypass authorized security procedures. RAP detection has been attempted using hardware and software-based solutions requiring the developing of dedicated tools or beacon frame modification. (Arisandi, 2021). …

The Construction Of A Static Source Code Scanner Focused On Sql Injection Vulnerabilties In Java, Carla Zurita Rubin De Celis

Theses, Dissertations and Culminating Projects

SQL injection attacks are a significant threat to web application security, allowing attackers to execute arbitrary SQL commands and gain unauthorized access to sensitive data. Static source code analysis is a widely used technique to identify security vulnerabilities in software, including SQL injection attacks. However, existing static source code scanners often produce false positives and require a high level of expertise to use effectively. This thesis presents the design and implementation of a static source code scanner for SQL injection vulnerabilities in Java queries. The scanner uses a combination of pattern matching and data flow analysis to detect SQL injection …

Internet Programming, Kwame A. Baffour

Open Educational Resources

CSC 31800 – Internet Programming

The design and implementation of websites from a Human-Computer Interaction point of view. Covers client-side technologies such as HTML, CSS and JavaScript and server-side technologies including Node.js and relational databases. Responsiveness, inclusion and accessibility by persons with mobility and vision impairment is necessary and must be addressed in the final project.

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 …

Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks

Faculty Publications

Machine learning and computational processing have advanced such that automated driving systems (ADSs) are no longer a distant reality. Many automobile manufacturers have developed prototypes; however, there exist numerous decision support issues requiring resolution to ensure mass ADS adoption. In the coming decades, it is likely that production ADSs will only be partially autonomous. Such ADSs operate within predetermined conditions and require driver intervention when they are violated. Since forecasts of their 20-year market penetration are relatively low, ADSs will likely operate in heterogeneous traffic characterized by vehicles of varying autonomy levels. Under these conditions, effective decision support must consider …

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 …

Time Varied Self-Reliance Aerial Ground Traffic Monitoring System With Pre-Recognition Collision Avoidance, Seungheyon Lee, Sooeon Lee, Yumin Choi, Jalel Ben-Othman, Lynda Mokdad, Hyunbum Kim

All Works

In this letter, we introduce a time varied self-reliance aerial ground traffic monitoring system which provides pre-recognition collision avoidance among mobile robots and smart UAVs for virtual emotion security. Then, with ILP (Integer Linear Programming), we make a formal definition of the problem whose objective is to minimize a total spent time by smart UAVs (Unmanned Aerial Vehicles) and mobile robots without conflicts on condition that the demanded number of self-reliance security barriers are formed. To solve the defined problem, we develop two approaches, time-differentiated pre-stop movement and approximated equal segments movement. Then, those schemes are implemented through expanded experiments …

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 …