Digital Commons Network^™

Enabling Iov Communication Through Secure Decentralized Clustering Using Federated Deep Reinforcement Learning, Chandler Scott

Electronic Theses and Dissertations

The Internet of Vehicles (IoV) holds immense potential for revolutionizing transporta- tion systems by facilitating seamless vehicle-to-vehicle and vehicle-to-infrastructure communication. However, challenges such as congestion, pollution, and security per- sist, particularly in rural areas with limited infrastructure. Existing centralized solu- tions are impractical in such environments due to latency and privacy concerns. To address these challenges, we propose a decentralized clustering algorithm enhanced with Federated Deep Reinforcement Learning (FDRL). Our approach enables low- latency communication, competitive packet delivery ratios, and cluster stability while preserving data privacy. Additionally, we introduce a trust-based security framework for IoV environments, integrating a central authority …

Enhancing Monthly Streamflow Prediction Using Meteorological Factors And Machine Learning Models In The Upper Colorado River Basin, Saichand Thota

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding and predicting streamflow along river basins is vital for planning future developments and ensuring safety, especially with climate change challenges. Our study focused on forecasting streamflow at Lees Ferry, a key location along the Colorado River in the Upper Colorado River Basin. We employed four machine learning models - Random Forest Regression, Long short-term memory, Gated Recurrent Unit, and Seasonal Auto-Regressive Integrated Moving Average; and combined historical streamflow data with meteorological factors such as snow water equivalent, temperature, and precipitation. Our analysis spanned 30 years of data from 1991 to 2020.

Our findings revealed that the Random Forest Regression …

Creating A Virtual Hierarchy From A Relational Database, Yucong Mo

All Graduate Theses and Dissertations, Fall 2023 to Present

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational …

An Empirical Study On Detecting And Explaining Global Structural Change In Evolving Graph Using Martingale, Tarun Teja Kairamkonda

Theses and Dissertations

There is a growing interest in practical applications involving networks of interacting entities such as sensor networks, social networks, urban traffic networks, and power grids, all of which can be represented using evolving graphs. Changes in these evolving graphs can signify shifts in the behavior of interacting entities or alterations in the patterns of their interactions. Identifying and detecting these changes is crucial for addressing potential challenges or opportunities in various domains. In this study, we propose an approach for detecting structure change in evolving graphs based on the martingale change detection framework on multiple graph features extracted over time. …

Reinforcement Learning For Robotic Tasks: Analyzing And Understanding The Learning Process Using Explainable Artificial Intelligence Methods, Brian J. Campana

Theses and Dissertations

As deep reinforcement learning (RL) models gain traction across more industries, there is a growing need for reliable agent-explanation techniques to understand these models. Researchers have developed explainable artificial intelligence (XAI) methods to help understand these 'black boxes'. While these models have been tested on many supervised learning tasks, there is a lack of examination of how these well these methods can explain hard reinforcement learning problems like robotic control. The sequential nature of learning RL policies and testing episodes create fundamentally different policies over time compared to more traditional supervised learning models. In this thesis, two important questions are …

Henna Chatbot Capstone Review, Kobe Norcross

University Honors Theses

This thesis reviews the development of the Henna Chatbot, an AI-powered DEI consultant designed to provide personalized feedback to organizations. Sponsored by DEI consultant Arsh Haque, the project aims to address gaps in current DEI software, which often lacks team-specific feedback. The Henna Chatbot leverages GPT-3.5 Turbo to create an affordable SaaS platform where organizations can train Henna with their DEI values, and Henna will help organizations stay aligned with those values. The project spanned twenty weeks and was completed by a team of eight computer science students at Portland State University. The development process followed Agile methodologies, emphasizing effective …

Cards With Class: Formalizing A Simplified Collectible Card Game, Dan Ha

University Honors Theses

Collectible card games (CCGs) have been a wildly popular game genre since the release of Wizards of the Coast's Magic: The Gathering. These games revolve around their thousands of cards and the hundreds of thousands of interactions they can create with their many effects. For designers, it is an incredibly demanding task to ensure that every single card works properly and that each card's text unambiguously conveys its intended behavior in all cases. The task only grows more difficult over time as the number of cards in the game grows and card effects become more complex or experimental. If the …

The Institutional Challenges Of A Quantified Self Study: An Attempt To Ascertain How Data Collected From A Mobile Device Can Be An Indicator Of Personal Mental Health Over Time, Julian Lazaras

University Honors Theses

The adoption of an application of new technology always comes with a bias, this is never more true for the case of human behavioral analytics within higher education. While movements such as the quantified self movement make strides to reinterpret the realm of data analytics, psychology, and computer science, there are inevitably limitations to the adoption and application of such approaches within the standard realm of research. Herein is presented a case where an effort to evaluate the prospect of use of mobile phone data as secondary indicators of personal mental health through the lens of data analysis was put …

Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo

Theses and Dissertations

New technologies are being introduced at a rate faster than ever before and smaller in size. Due to the size of these devices, security is often difficult to implement. The existing solution is a firewall-segmented “IoT Network” that only limits the effect of these infected devices on other parts of the network. We propose a lightweight unsupervised hybrid-cloud ensemble anomaly detection system for malware detection. We perform transfer learning using a generalized model trained on multiple IoT device sources to learn network traffic on new devices with minimal computational resources. We further extend our proposed system to utilize federated learning …

The Robot On The Hill, James Ryan

College of Computing and Digital Media Dissertations

“The Robot on the Hill” is a rogue-like autobattler that procedurally models the state of the individual in the information age. The game abruptly transitions between diverse framings - a hill, a bedroom, a pond, a chessboard, the void - in order to highlight the disjointedness that is present in the informationalizing of self and reality. It dialogues with Byung Chul Han and Heidegger to portray what Han describes as a ‘narrative crisis’ in modernity and the devaluation of experience. When the value of experience diminishes and disintegrates, “all that is left is bare life, a kind of survival.” …

Machines Of The Absurd: Leveraging Generative Ai For Creativity, Humor, And Playfulness, Tyler Sanders

College of Computing and Digital Media Dissertations

Machines of The Absurd is a collection of four projects exploring how generative AI can be leveraged for creativity, humor and playfulness.

1. neverOS — A node-based visual playground for interacting with large language models.

2. Other Calc — An iOS app with a calculator interface, where players can “calculate” text instead of numbers.

3. What Must Burn — An experiment where players type in text that can be dragged into a campfire to produce contextually appropriate sound effects.

4. Jazz vs Waffles — A turn-based comedy game, where players battle anything they type in.

Together, these projects make the …

Back To The Future: A Case For The Resurgence Of Approximation Theory For Enabling Data Driven “Intelligence”, Michael Dominic Ciocco

Theses and Dissertations

Artificial Intelligence (AI) has exploded into mainstream consciousness with commercial investments exceeding $90 billion in the last year alone. Inasmuch as consumer-facing applications such ChatGPT offer astounding access to algorithms that were hitherto restricted to academic research labs, public focus of attention on AI has created an avalanche of misinformation. The nexus of investor-driven hype, “surprising” inaccuracies in the answers provided by AI models – now anthropomorphically labeled as “hallucinations”, and impending legislation by well-meaning and concerned governments has resulted in a crisis of confidence in the science of AI. The primary driver for AI’s recent growth is the convergence …

Context In Computer Vision: A Taxonomy, Multi-Stage Integration, And A General Framework, Xuan Wang

Dissertations, Theses, and Capstone Projects

Contextual information has been widely used in many computer vision tasks, such as object detection, video action detection, image classification, etc. Recognizing a single object or action out of context could be sometimes very challenging, and context information may help improve the understanding of a scene or an event greatly. However, existing approaches design specific contextual information mechanisms for different detection tasks.

In this research, we first present a comprehensive survey of context understanding in computer vision, with a taxonomy to describe context in different types and levels. Then we proposed MultiCLU, a new multi-stage context learning and utilization framework, …

Assessing Job Vulnerability And Employment Growth In The Era Of Large Language Models (Llms), Prudence P. Brou

Dissertations, Theses, and Capstone Projects

This paper explores the impact of Large Language Models (LLMs) and artificial intelligence (AI) on white-collar occupations in the context of job vulnerability and employment growth. Utilizing the Kaggle dataset "Occupation Salary and Likelihood of Automation," the study employs a data-driven approach to analyze trends across states. Through interactive data visualization, the project aims to provide actionable insights for affected workers, businesses, and policymakers navigating the changing dynamics of the workforce amidst technological advancements.

The Efficacy Of Using Machine Learning Techniques For Identifying And Classifying “Fake News”, Muhammad Islam

Dissertations, Theses, and Capstone Projects

In today's digital world, detecting fake news has emerged as a critical challenge, one that has significant effects on democracy and public discourse at large both regionally and globally. This research studies how diversity of news sources in training datasets affects how well machine learning models can classify fake vs true news. I used the Linear Support Vector Classification (LinearSVC) to create and compare two classification models: one was trained on a dataset that only had real news from a singular source, Reuters (Dataset 1), and the other was trained on a dataset that contained real news from Reuters, The …

The Core Of It All: From The Forest To The Concrete Jungle, Ayo Andra J. Deas

Dissertations, Theses, and Capstone Projects

The Core of It All is a component of principle within Fasaha. The mission of Fasaha is to implement programming directed toward development of one’s Core through self-actualization. Self-Actualization is defined as bringing forth the total essential qualities of one’s own consciousness, character, and identity through positive behavior. Throughout this manuscript, principle is defined as the standard of natural essential qualities determining intrinsic consciousness, character and identity. Programming is defined as providing with intrinsic instructions for the automatic performance of a task.

Fasaha is a support service that enhances the existing organization’s service. Throughout this dissertation, it will be apparent …

Combining Cloud Architecting With Education, Sharon P. Pagidipati

Liberal Arts and Engineering Studies

I pursued the AWS Solutions Architect Professional Certification while applying my knowledge to build and revise technical solutions for an educational company known as EDFX.

Impact Of Similarities In Gender And Physical Appearance Between User And Embodied Conversational Agents On Trustworthiness, Empathy, And Service Evaluation, Sookyoung Park

Dartmouth College Master’s Theses

Embodied conversational agents (ECAs) have significantly enhanced human-machine interactions and show considerable potential in various industries such as customer service, education, healthcare, entertainment, and finance [1, 2]. This study explores the impact of similarities in gender and physical appearance between ECAs and users on the perceptions of trustworthiness, empathy, and service evaluation within the context of counselor ECAs. We conducted a within-subject experiment (n=50), using a 2x2 factorial arrangement, that varied the gender and the physical appearance of four distinct AI avatars. Participants interacted with each avatar, completing a post-experiment survey and participating in semi-structured interviews. Our findings indicate that …

Auditory Ace Mobile Application Capstone Review, Layla Smith

University Honors Theses

This paper describes the development process and outcomes of my 2023-2024 Capstone Project, Auditory Ace, a self-directed auditory training mobile application for individuals with cochlear implants. Recognizing the limitations of current market offerings, Dr. Timothy Anderson created a Capstone project proposal to develop an accessible auditory training mobile application. The Capstone team that took on this proposal consisted of Darya Haines, Dustin Huynh, Jordan Nguyen, Nihar Koppolu, Scott Thorkelson, Sienna Day, and myself, Layla Smith. This paper is structured to follow the Agile software development methodology, which we used to develop Auditory Ace, reviewing in detail every major choice we …

Virtual Field Environments Capstone Software Review, Ashton Sawyer

University Honors Theses

This is a review of the Virtual Field Environments computer science capstone project, sponsored by geology professor Rick Hugo. The tool aims to create and render VFEs, interactable 360° environments hosted on the web that are used as virtual field trips for K-12 students. This essay discusses the development process, including understanding requirements, tool and technology selection, problem-solving, and decision-making strategies. It also highlights the differences between the capstone and the other core computer science courses, and how those differences help to prepare students for the workforce. The project was completed over the course of twenty weeks by a team …

The Cascading Effects Of Database Design, Liam Mccracken

University Honors Theses

This paper details how a relational database influenced the design of the rest of a software project. The software project in question is WonderTix, an open-source ticketing and donation platform for the use of Portland Playhouse under continuous development by teams of Portland State students as their computer science capstone project. The paper, a capstone review thesis, examines WonderTix as an instantiation of the Model-View-Controller design pattern, noting how the model, a relational database based on the SQL standard, influenced the design of the view and controller components. This influence is explored from three angles. First, when the implementation of …

Enhancing Robustness Of Machine Learning Models Against Adversarial Attacks, Ronak Guliani

University Honors Theses

Machine learning models are integral for numerous applications, but they remain increasingly vulnerable to adversarial attacks. These attacks involve subtle manipulation of input data to deceive models, presenting a critical threat to their dependability and security. This thesis addresses the need for strengthening these models against such adversarial attacks. Prior research has primarily focused on identifying specific types of adversarial attacks on a limited range of ML algorithms. However, there is a gap in the evaluation of model resilience across algorithms and in the development of effective defense mechanisms. To bridge this gap, this work adopts a two-phase approach. First, …

Lang2views Capstone: The Importance Of A Conscientious Team Lead, Joseph Wornath

University Honors Theses

This review essay reflects the Lang2views capstone project from the perspective of a team lead. The Lang2views capstone project was a web-based user interface designed to simplify how the Lang2views corporation localizes videos into other languages for their clients. Our capstone group was split into three subgroups: front-end, back-end, and DevOps. The strategy for completing the project went through a major change midway through development wherein we changed our software development methodology from a more rigid Waterfall-type approach to a more flexible Agile methodology. Because of this, many of the initially planned features had to be reevaluated as out of …

Design And Test Of Asynchronous Systems Using The Link And Joint Model, Ebelechukwu Esimai

Dissertations and Theses

Asynchronous circuits offer numerous advantages, including low energy consumption and good composability and scalability. However, they remain meagerly adopted in the mainstream semiconductor industry. One reason is the limited number of design tools available to help designers navigate design complexity, particularly the myriad of asynchronous implementation styles.

This dissertation focuses on managing the myriad of asynchronous implementation styles by utilizing a circuit-neutral model, called Links and Joints, and embedding this Link-Joint approach into a design flow. Although years of past work have already laid the groundwork, the work in this dissertation identifies and addresses key missing pieces.

First, the …

Supporting South Korea’S Aging Population: How Ai And Iot Acceptance Connects The Young And Old, Bobby Im

Master's Projects and Capstones

In 2024, South Korea surpassed every other nation by becoming the country with the lowest fertility rate (below 0.7%). Population decline will hinder future ability to care for their aging population and although the government and private corporations are investing millions of dollars on developing Artificial Intelligence-Internet of Things (AI-IoT) devices to support the aging, the acceptance levels and the amount of family support required is undervalued. By examining AI-IoT’s current use and role in South Korea’s public health system this paper shows how intergenerational support helps optimize existing procedures and equipment, increases the level of acceptance and use, and …

Embodied Visions: Interactive Installations That Reimagine Bodily Presence In Digital Imaging Apparatuses As Shadows, Yunzi Shi

Dartmouth College Master’s Theses

Contextualized within a history of technological development, the evolution of imaging devices and technologies is accompanied by the abstraction of spatial relationships between the body of the observer, the apparatus, and physical reality, which leads to disembodying experiences for the observing subject. Compared with devices and interactive experiences, critical reflection on the epistemological impact of digital imaging devices has less priority in computational imaging and human-computer interaction research. Taking an artistic approach, this thesis describes Embodied Visions, an exhibition featuring three interactive installations exploring the technical infrastructure for imaging and reflecting on the (dis)embodied experiences in the digital age. …

Mending Trust In Ai: Trust Repair Policy Interventions For Large Language Models In Visual Data Journalism, Hangxiao Zhu

McKelvey School of Engineering Theses & Dissertations

Trust in Large Language Models (LLMs) emerged as a pivotal concern. This is because, despite the transformative potential of LLMs in enhancing the interpretability and interactivity of complex datasets, the opacity of these models and instances of inaccuracies or biases have led to a significant trust deficit among end-users. Moreover, there is a tendency for people to personify AI tools that utilize these LLMs, attributing abilities and sensibilities that they do not truly possess. This thesis exploits this personification and proposes a comprehensive framework of trust repair policies tailored to address the challenges inherent in LLM annotations within data journalism …

On Multi-Sensor Adaptive Birth Theory For Labeled Random Finite Sets Tracking, Anthony Trezza

Dissertations - ALL

This dissertation provides a scalable, multi-sensor measurement adaptive track initiation technique for labeled random finite set filters. The lack of a well-defined, systematic approach is problematic for many applications, especially when fusing ambiguous sensor measurements. We begin by showing that a naive solution leads to an exponential number of newborn components in the number of sensors. An efficient solution is derived by formulating a ranked assignment truncation problem. A truncation criterion is established for a labeled multi-Bernoulli random finite set birth density that has a bounded L1 error in the generalized labeled multi-Bernoulli posterior density. This criterion is used to …

Companionship, Romance, And Self-Perception With Conversational Chatbots, Jonathan Windsor

Student Research Submissions

Serving as a metaphorical gateway transcending the communicative barriers of physical relationships in interpersonal dialogues, artificial imators of human behavior and speech, also known as conversational chatbots; a simulation of human knowledge and existence in a bi-directional conversation, functions as a rhetor of expression. Spanning from contexts of professional to romantic, I serve to dissect and critically analyze the nuances of human-machine relationships based on pre-established literature, inviting ethical considerations and biases in their design and marketing. Corporate influences spark pre-established servitude-esque relationships with conversational agents. Professional applications, both task-oriented and emotionally based alike, paint a mixed picture of …

A Nlp Approach To Automating The Generation Of Surveys For Market Research, Anav Chug

Honors College Theses

Market Research is vital but includes activities that are often laborious and time consuming. Survey questionnaires are one possible output of the process and market researchers spend a lot of time manually developing questions for focus groups. The proposed research aims to develop a software prototype that utilizes Natural Language Processing (NLP) to automate the process of generating survey questions for market research. The software uses a pre-trained Open AI language model to generate multiple choice survey questions based on a given product prompt, send it to a targeted email list, and also provides a real-time analysis of the responses …