Other Computer Engineering Commons^™

Reality Analagous Synthetic Dataset Generation With Daylight Variance For Deep Learning Classification, Thomas Lee, Susan Mckeever, Jane Courtney

Conference papers

For the implementation of Autonomously navigating Unmanned Air Vehicles (UAV) in the real world, it must be shown that safe navigation is possible in all real world scenarios. In the case of UAVs powered by Deep Learning algorithms, this is a difficult task to achieve, as the weak point of any trained network is the reduction in predictive capacity when presented with unfamiliar input data. It is possible to train for more use cases, however more data is required for this, requiring time and manpower to acquire. In this work, a potential solution to the manpower issues of exponentially scaling …

Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile

Electronic Thesis and Dissertation Repository

Corporate networks are constantly bombarded by malicious actors trying to gain access. The current state of the art in protecting networks is deep learning-based intrusion detection systems (IDS). However, for an IDS to be effective it needs to be trained on a good dataset. The best datasets for training an IDS are real data captured from large corporate networks. Unfortunately, companies cannot release their network data due to privacy concerns creating a lack of public cybersecurity data. In this thesis I take a novel approach to network dataset anonymization using character-level LSTM models to learn the characteristics of a dataset; …

Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead

Art Faculty Articles and Research

We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.

Educación Transmoderna Y Translocal Desde El Medit. Visión De La Facultad De Ingeniería, Jairo Eduardo Marquez, Arles Prieto Moreno, Misael Fernando Perilla Benítez, Diana Pilar Quitian Bernal, Dayana Catalina Medina Sandoval, José Manuel Higuera Aparicio

Ingeniería

La Universidad de Cundinamarca dentro de su quehacer académico e investigativo, busca cambiar el paradigma de la educación superior tradicional a través del Modelo Educativo Digital Transmoderno (MEDIT); el cual está acompañado por diversos elementos que contribuyen a una formación integral del educando, viéndolo como una persona para la vida, inculcando valores democráticos, civilidad y libertad, conjugados con lo que se ha llegado a denominar como campos multidimensionales de aprendizaje; que permiten vislumbrar un sinnúmero de posibilidades formativas para una educación contemporánea vista desde la traslocalidad y transmodernidad. Bajo esta mirada, el presente libro muestra los resultados de la colaboración …

Learning With Limited Labeled Data For Image And Video Understanding, Razieh Kaviani Baghbaderani

Doctoral Dissertations

Deep learning-based algorithms have remarkably improved the performance in many computer vision tasks. However, deep networks often demand a large-scale and carefully annotated dataset and sufficient sample coverage of every training category. However, it is not practical in many real-world applications where only a few examples may be available, or the data annotation is costly and require expert knowledge. To mitigate this issue, learning with limited data has gained considerable attention and is investigated thorough different learning methods, including few-shot learning, weakly/semi supervised learning, open-set learning, etc.

In this work, the classification problem is investigated under an open-world assumption to …

A Digital Healthcare Application For Patient Monitoring And Assessment, Brandon Shumin

All Theses

The COVID-19 pandemic strained our healthcare resources and exacerbated the existing issues of primary care shortages and burnout rates for healthcare professionals. Due in part to these factors, telehealth has seen more wide-spread use during this time. However, current asynchronous telehealth applications require stable Internet to function fully. Since many medically underserved populations in the United States lack Internet access in their homes, an application that offers patient monitoring and assessment could extend their access to medical resources. This work proposes such a digital healthcare application for iOS devices and evaluates it based on the system requirements of availability, data …

Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …

Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany

Conference papers

Gender imbalance in computing education is a well-known issue around the world. For example, in the UK and Ireland, less than 20% of the student population in computer science, ICT and related disciplines are women. Similar figures are seen in the labour force in the field across the EU. The term "leaky pipeline"; is often used to describe the lack of retention of women before they progress to senior roles. Numerous initiatives have targeted the problem of the leaky pipeline in recent decades. This paper provides a comprehensive review of initiatives related to techniques used to boost recruitment and improve …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

Generating Reality-Analogous Datasets For Autonomous Uav Navigation Using Digital Twin Areas, Thomas Lee, Susan Mckeever, Jane Courtney

Conference papers

In order for autonomously navigating Unmanned Air Vehicles(UAVs) to be implemented in day-to-day life, proof of safe operation will be necessary for all realistic navigation scenarios. For Deep Learning powered navigation protocols, this requirement is challenging to fulfil as the performance of a network is impacted by how much the test case deviates from data that the network was trained on. Though networks can generalise to manage multiple scenarios in the same task, they require additional data representing those cases which can be costly to gather. In this work, a solution to this data acquisition problem is suggested by way …

Researching The Impact Of Cal Poly Classes On Computing Students Perceptions Of Computer Ethics And Social Responsibility, Annie Joss

Computer Engineering

The importance and impact of socio-technical systems are playing an increasing role in the education of computing students. Discussion of ethics and social responsibility has always been a tenant of computer science education; however, research has shown engineering and computer science students lose focus on these values over their engineering education. Cal Poly computing departments have taken steps to emphasize social responsibility and ethics through required and suggested courses. This project focuses on examining the values and beliefs of Cal Poly computing students, who were surveyed over Winter and Spring Quarters in 2022. This project is inspired by Dr. Cech’s …

Digital Forensics Range, Cody P. Shanahan, Bryson Y. Shishido, Samuel R. Mckee, Justin Siu, Lisa Li, Maxwell Brewer

Computer Engineering

The Digital Forensics Range was developed to serve as an online training for groups interested in computer forensics. This year's team had the goal to expand upon last year, by adding a new forensics image, unity scenario, and additional AWS functionality. The team still wanted to continue with last year's goals of keeping the training easily runnable, quickly deployable, and rapidly scalable through the use of the cloud. Adding to last year's work, this year's team hoped to further increase the educational value of the simulation with more practice, and the addition of feedback. The training is meant to be …

Improving Relation Extraction From Unstructured Genealogical Texts Using Fine-Tuned Transformers, Carloangello Parrolivelli

Master's Theses

Though exploring one’s family lineage through genealogical family trees can be insightful to developing one’s identity, this knowledge is typically held behind closed doors by private companies or require expensive technologies, such as DNA testing, to uncover. With the ever-booming explosion of data on the world wide web, many unstructured text documents, both old and new, are being discovered, written, and processed which contain rich genealogical information. With access to this immense amount of data, however, entails a costly process whereby people, typically volunteers, have to read large amounts of text to find relationships between people. This delays having genealogical …

Strainer: State Transcript Rating For Informed News Entity Retrieval, Thomas M. Gerrity

Master's Theses

Over the past two decades there has been a rapid decline in public oversight of state and local governments. From 2003 to 2014, the number of journalists assigned to cover the proceedings in state houses has declined by more than 30\%. During the same time period, non-profit projects such as Digital Democracy sought to collect and store legislative bill and hearing information on behalf of the public. More recently, AI4Reporters, an offshoot of Digital Democracy, seeks to actively summarize interesting legislative data.

This thesis presents STRAINER, a parallel project with AI4Reporters, as an active data retrieval and filtering system for …

A Machine Learning Approach To Predicting The Onset Of Type Ii Diabetes In A Sample Of Pima Indian Women, Meriem Benarbia

Dissertations, Theses, and Capstone Projects

Type II diabetes is a disease that affects how the body regulates and uses sugar (glucose) as a fuel. This chronic disease results in too much sugar circulating in the bloodstream. High blood sugar levels can lead to circulatory, nervous, and immune systems disorders. Machine learning (ML) techniques have proven their strength in diabetes diagnosis. In this paper, we aimed to contribute to the literature on the use of ML methods by examining the value of a number of supervised machine learning algorithms such as logistic regression, decision tree classifiers, random forest classifiers, and support vector classifiers to identify factors …

Happiness And Policy Implications: A Sociological View, Sarah M. Kahl

Dissertations, Theses, and Capstone Projects

The World Happiness Report is released every year, ranking each country by who is “happier” and explaining the variables and data they have used. This project attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both big data and considering social indicators to make better and lasting policies.

Smartphone Control Of Rc Cars, Weston R. Fitzgerald

Electrical Engineering

The smartphone-controlled RC (remote-controlled) car is an inexpensive remote-controlled car designed to be fast and portable. Instead of manufacturing, packaging, and shipping a separate controller, the remote control is implemented in a phone application, which saves time and money in both the design process and the manufacturing process. Utilizing the user’s smartphone is more cost-effective since mobile devices are a common recurrence, and packaging fewer devices results in overall better portability of the product.

This smartphone-controlled car is speedy and intuitive to learn for typical smartphone users. The user can change the car’s speed and direction wirelessly using their phone; …

Project Metamorphosis: Designing A Dynamic Framework For Converting Musical Compositions Into Paintings, Rao Hamza Ali, Grace Fong, Erik Linstead

Engineering Faculty Articles and Research

The authors present an automated, rule-based system for converting piano compositions into paintings. Using a color-note association scale presented by Edward Maryon in 1919, which correlates 12-tone scale with 12 hues of the color circle, the authors present a simple approach for extracting colors associated with each note played in a piano composition. The authors also describe the color extraction and art generation process in detail, as well as the process for creating “moving art,” which imitates the progression of a musical piece in real time. They share and discuss artworks generated for four well-known piano compositions.

Blockchain Storage – Drive Configurations And Performance Analysis, Jesse Garner, Aditya A. Syal, Ronald C. Jones

Other Student Works

This project will analyze the results of trials implementing various storage methods on Geth nodes to synchronize and maintain a full-archive state of the Ethereum blockchain. The purpose of these trials is to gain deeper insight to the process of lowering cost and increasing efficiency of blockchain storage using available technologies, analyzing results of various storage drives under similar conditions. It provides performance analysis and describes performance of each trial in relation to the others.

Personal Library Organization And Tracking Application (Plot), Katie Honsinger

Honors Projects

This project is inspired by my family's gloriously unmanageable book collection. Its primary goal is to provide a simple way to track your book collection, to avoid double-buying and help disorganized book-lovers everywhere stay sane! You can also track where a particular book is physically (or at least, where it should be!). There are a few features I'd still like to implement, but mainly I want this app to stay simple so it is easy to use and maintain.

Evaluation Of Selected Computer Software For Concussion Recovery And Diagnosis, J.P. Jensen

Honors Theses

Acquired traumatic brain injuries, such as concussions, impact many athletes participating in sports, particularly at the high school, collegiate, and professional levels. The risks posed by concussions – particularly when an athlete suffers repeated injuries – demands that protocols and tools be developed to maximize athlete health and safety. Computer technology can perform critical roles in the analysis and management of concussions. While specialized devices in the areas of imaging and impact sensing, are most associated with concussion management, researchers within the last two decades have increasingly explored the incorporation of various consumer technologies into the identification and treatment of …

Designing A Digital Electronics Lab, Ben Buckwalter

Honors Theses

Hardware electronics tools can be more expensive than a new learner is willing to invest resulting in a barrier to entry. Furthermore, it can be difficult for a new learner to know where to start when learning electronics. To resolve this issue, we first explore current mobile app solutions that provide free electronics tooling. Then, we propose a design for a new mobile app that contains basic function generator and oscilloscope functionality as well as the learning resources necessary in order to guide new learners in the basics of digital electronics.

Comparative Analysis Of Imputation Methods In Real Estate Data, Connor Donlen

Honors Theses

This project involves comparing different methods of missing data imputation in the context of predicting real estate listing prices. These methods are compared against each other in both their ability to recreate the original data and their effects on a final predictive model. In order to evaluate their effectiveness, first, a predictive model is made using the complete dataset to use as a benchmark for the imputed datasets. Then, a complete dataset is split into 80% training and 20% testing datasets, and missing values are created in the training data using two different missing data mechanisms, missing completely at random …

Defensive Industrial Policy: Cybersecurity Interventions To Reduce Intellectual Property Theft, Dr. Chad Dacus, Dr. Carl (Cj) Horn

Military Cyber Affairs

Through cyber-enabled industrial espionage, China has appropriated what Keith Alexander, the former Director of the National Security Agency, dubbed “the largest transfer of wealth in history.” Although China disavows intellectual property (IP) theft by its citizens and has set self-sustained research and development as an important goal, it is unrealistic to believe IP theft will slow down meaningfully without changing China’s decision calculus. China and the United States have twice agreed, in principle, to respect one another’s IP rights. However, these agreements have lacked any real enforcement mechanism, so the United States must do more to ensure its IP is …

Digitalization Of Construction Project Requirements Using Natural Language Processing (Nlp) Techniques, Fahad Ul Hassan

All Dissertations

Contract documents are a critical legal component of a construction project that specify all wishes and expectations of the owner toward the design, construction, and handover of a project. A single contract package, especially of a design-build (DB) project, comprises hundreds of documents including thousands of requirements. Precise comprehension and management of the requirements are critical to ensure that all important explicit and implicit requirements of the project scope are captured, managed, and completed. Since requirements are mainly written in a natural human language, the current manual methods impose a significant burden on practitioners to process and restructure them into …

Monitoring The M-Dwarf Host Stars Of Tess Exoplanet Candidates: Stellar Flares And Habitability, Ashley Lieber

Physics Undergraduate Honors Theses

In the search for life beyond our solar system, the study of M-dwarfs has become increasingly important due to their unique characteristics including their small size, flaring capabilities, and long lifespans. Their small size allows for exoplanet detection due to observable gravitational interactions, and the stellar flares could potentially trigger prebiotic life on exoplanets in the system. Lastly, their long lifespans may provide the conditions necessary to foster prebiotic life and the development of more complex organisms over time. Flare rate is a critical factor in determining the habitability of the exoplanet due to its potential to damage or incubate …

Self-Efficacy Development In Elementary-Aged Learners Through Dance As An Algorithmic Thinking Tool, Niva Shrestha

Honors Theses

The purpose of this research is to demonstrate the effectiveness of a transdisciplinary approach in teaching computational thinking through dance to elementary-aged learners, with primary attention to females. With limited literature available on how pre-adolescents begin to construct conceptions of computer science and other engineering domains, including potential career pathways, the incentive of this project was to leverage a day camp for about 20 rising 3rd - 5th-grade learners to assess their identity development in computer science. Modules that teach computational thinking through dance paired with Unruly splats (block-based programmable electronic gadgets) were implemented. By conducting pre-and post-surveys and a …

A Research Framework And Initial Study Of Browser Security For The Visually Impaired, Elaine Lau, Zachary Peterson

Master's Theses

The growth of web-based malware and phishing attacks has catalyzed significant advances in the research and use of interstitial warning pages and modals by a browser prior to loading the content of a suspect site. These warnings commonly use visual cues to attract users' attention, including specialized iconography, color, and an absence of buttons to communicate the importance of the scenario. While the efficacy of visual techniques has improved safety for sighted users, these techniques are unsuitable for blind and visually impaired users. This is likely not due to a lack of interest or technical capability by browser manufactures, where …

Enter The Battleverse: China's Metaverse War, Josh Baughman

Military Cyber Affairs

No abstract provided.