Digital Commons Network^™

Artificial Intelligence In Society: Transformations And Ethical Paradigm, Yashoda Urmilla Itwaru

Selected Full-Text Master Theses 2021-

The recent advancement and adoption of AI (Artificial Intelligence) make it vital to study the effects it has on individuals and communities. Adopting AI into daily life changes interactions such as the decision-making process and task performance. AI algorithms can shape a user’s online experiences, influence their preferences, beliefs, and behavior. However, people raised concerns regarding privacy, autonomy, and manipulation. For these reasons, debates regarding the ethical aspects of AI arose.

AI provides society with more tools to complete tasks. AI can automate data intensive jobs and physical tasks. This brings a sense of job insecurity, which affects the mental …

Edge-Enhanced Yolo V8 Architecture For Accurate Kl Assessment In Knee Osteoarthritis Imaging, Meghana Arikilla

Selected Full-Text Master Theses 2021-

Knee Osteoarthritis (KOA) is a degenerative joint condition characterized by the progressive narrowing of joint space and structural deterioration. The structural degradation of the joint space is evaluated using the Kellgren–Lawrence (KL) grading system, and accurate classification across all grades, specifically in the early stages, remains a challenge owing to subtle radiographic differences. This study presents an automated KL-grade classification framework that integrates joint edge enhancement with deep learning to improve KOA grading using radiographic images.

Edge detection filters, namely Sobel, Scharr, and Canny, were applied to X-ray images to enhance the joint space boundaries and osteoarthritic features. These preprocessed …

A Proof Of Np-Completeness For The K-Means Clustering Algorithm, Brooke C. Feinberg

Scripps Senior Theses

The k-means clustering algorithm is one of the most widely used clustering techniques in data analysis and machine learning, yet its exact computational complexity remains subject to ongoing theoretical investiga- tion. This work establishes the NP-completeness of k-means by proving (1) it is NP-hard and (2) it lies in NP. To demonstrate NP-hardness, we construct a series of polynomial-time reductions from well-known NP-complete problems. Specifically, we reduce 3sat to Vertex Cover, and then reduce Vertex Cover to k-means, thereby establishing the computational hardness of the k-means clustering problem. We then prove k-means is in NP, and thus conclude it is …

Ally With Ai: An Icebreaker To Unlock Career Aspirations For Online Or Hybrid Organizational Behavior Cohorts, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Modern organizational behavior classroom, which are increasing in size, diversity, and complexity, are shifting to online and hybrid learning environments, challenging the use of traditional icebreaker activities. This paper introduces a 15-minute icebreaker designed to address these issues while integrating the principles of Kolb's experiential learning theory and fostering social capital through peerr engagement in an online setting. By leveraging the availability of generative AI, students prompt a template code to unlock their career aspirations and stimulate social connections among their classmates. This provides an innovative teaching model for meeting the foundational icebreaker goal while serving a suitable tool for …

Design And Implementation Of A Low-Cost Raspberry Pi And Ai-Based Intrusion Detection System For Surveillance, Metrine Nyaboke Osiemo

All Graduate Theses, Dissertations, and Other Capstone Projects

As security concerns continue to rise, there is a growing demand for affordable and intelligent surveillance solutions to ensure safety in homes, businesses, and other environments. Many individuals are embracing AI-driven technologies such as Closed-Circuit Television (CCTV), smart doorbells, and automated security systems to protect their properties. This project presents a design and implementation of a cost-effective AI-powered intrusion detection system utilizing Raspberry Pi 5 for home surveillance, with adaptability for broader applications. The system integrates a camera module and an LCD screen running on a Linux-based platform, with Python, and OpenCV as key software components. It employs dlib’s deep …

Teaming With Technology: Adaptive Automation In Joint Cognitive Systems For Industry 5.0, Jessica Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Adaptive automation enables dynamic reallocation of functions between people and autonomous agents to improve performance in complex work. This paper presents a meta-analysis of experimental and quasi-experimental studies (2000-2025) on joint cognitive systems in industrially relevant contexts, quantifying effects on task performance, safety/failure management, workload, trust, and learning. Across studies, adaptive automation reliably reduces operator workload and shows moderate gains in task performance and safety, with healthier trust dynamics when adaptations are triggered by human-state or event cues, made transparent to the user, and remain rapidly overridable. Risks emerge when performance-triggered switching is opaque or poorly timed, which can erode …

Interaction Mechanism Between Health Anxiety And Information Seeking Behavior From The Perspective Of Phenomenology, Yanfeng Zhang, Minqian Yu

Journal of Scientific Information Research

[Purpose/significance]To analyze the evolution characteristics of health anxiety before and after information search behavior from the perspective of phenomenological graph analysis, and to explain the internal mechanism of the interaction between health anxiety and information search behavior. [Method/process]By using the phenomenological qualitative research method, the interactive mechanism between health anxiety and information search behavior was deeply explored. Based on the I-PACE theoretical model framework, the model elements of users' health anxiety and information search behavior were analyzed from the four dimensions of "Person-Affect-Cognition-Execution". To construct a mechanistic relationship model between health anxiety and information search behavior. [Result/conclusion]The research results revealed …

Adding Libraries To The Equation: Mathematical Sciences’ Underutilization Of Academic Librarians, Jennifer Lc Burke, Elizabeth C. Novosel, Daniel G. Kipnis, Rasitha Jayesekere

Scholarship and Professional Work

Academic librarians do not engage with all disciplinary departments equally. Despite equal or even greater efforts, some departments are less responsive to librarian outreach. One such department is mathematics. To understand mathematics departments’ relationships with their academic librarians, three mathematics librarians created a 20-question survey that was disseminated to mathematics faculty, instructors, and instructional staff in the United States and Canada. Of the 188 survey participants, more than a third reported that they never engage with their librarians, approximately half only do so occasionally, and a mere eight percent of participants collaborated with librarians to provide information literacy instruction (IL) …

Deep Learning-Based Ensemble Two-Step Classification Of Medical Images Using Cnn Architectures And Ensemble Methods, Noreliz Alorico

Master's Theses or Doctor of Nursing Practice

Breast cancer remains one of the most common cancers amongst women globally. Early detection is crucial for improving survival rates. While mammography is widely used and an effective imaging technique, it can sometimes yield false positive or false negatives. Mammogram interpretation is highly operator-dependent, introducing variability and the potential for diagnostic errors. Additionally, mammographic images have limitations, such as low contrast in breast tissue and overlapping structures that can obscure lesions or mimic abnormalities. These limitations can lead to unnecessary biopsies or delayed diagnosis. These challenges highlight the needs for advanced and data driven diagnostic tools to support and enhance …

Swosu Research And Scholarly Activity Fair 2025, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) — welcome to the Thirty-Third SWOSU Research and Scholarly Activity Fair!

This year’s event features 99 poster presentations and 9 oral presentations, showcasing the work of over 170 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors. These presentations represent a wide array of scholarly and academic activity from across SWOSU’s academic community, including the Departments of Art, Communication, and Theatre; Allied Health Sciences; Biological Sciences; Business; Chemistry & …

A Study Of User Experiences Of Pediatric Physicians With Electronic Health Record Systems: Encounters With Task Complexity And Efficiency Of User Task Flows, Roseanne Alhindi

CCAC Theses and Dissertations

way patient information is stored, managed, and accessed. This transition to Electronic Health Record (EHR) systems has enhanced the efficiency and accuracy of healthcare delivery by enabling quick access to patient records, reduction of errors, and facilitation of coordination among healthcare providers. In the EHR system, diverse tasks are performed for clinical processes and patient care. These tasks can be considered simple or complex, ranging from documenting patient visits and updating medical histories to ordering tests and managing prescriptions. Although EHR systems have become more prevalent in their use, there are noted challenges associated with the design of the system …

Using A Water Quality Index To Assess The Impacts Of Heavy Metals Contamination For Sustainable Water Management: A Case Study Of The Bang Pakong River, Thailand, Khin Yadana Soe, Pokchat Chutivisut, Wilailuk Niyommaneerat

Applied Environmental Research

Anthropogenic activities such as improper waste disposal, excessive fertilizer use, and industrial effluents cause heavy metal contamination in water, soil, and the atmosphere. Herein, the water quality index (WQI) was used to characterize heavy metal (i.e., cadmium (Cd), arsenic (As), and mercury (Hg)) contamination in the Bang Pakong River, Thailand. Specifically, water samples were collected during the dry season from four stations along the river from 2012–2022. The heavy metal concentrations in the samples were analyzed via atomic absorption spectrophotometry, and WQI values were calculated on the basis of standard water quality parameters. At the four sampling stations, high As …

Public Attention Index Of Air Pollution Exposure From Pm2.5 In Thailand, Pailin Suntigul, Sittidaj Pongkijvorasin

Applied Environmental Research

Thailand faces a persistent PM2.5 challenge, with pollution levels consistently exceeding the World Health Organization’s guidelines. In response, the Thai government has made air pollution a national priority, implementing various policies and city-level plans to reduce exposure. These policies are often temporary and do not fully address root causes, whereas the limited monitoring coverage across Thailand restricts a comprehensive assessment of PM2.5 exposure severity. This study addresses the data gap by constructing a public attention index for PM2.5, using internet search data from Google Trends, to quantify public awareness and concern regarding PM2.5 exposure. This index aims to improve the …

Community Perception And Attitudes Toward Plastics And Microplastic Pollution: A Case Study In The Red River Delta, Vietnam, Dang Hai Mai

Applied Environmental Research

Plastics and microplastic contamination pose increasing threats to human health, food safety, and environmental sustainability. In Vietnam, rapid urbanization, economic growth, and population expansion have contributed to a surge in plastic waste, intensifying pollution across regions such as the Red River Delta. This study adopts the theory of planned behavior (TPB) to explore community perceptions, attitudes, and behavioral intentions regarding plastic and microplastic pollution. A quantitative research design was employed, with data collected through structured questionnaires administered to 1,305 respondents via a stratified multistage sampling strategy across four provinces in the Red River Delta. Descriptive statistics and multiple linear regression …

Examining The Variability In Planetary Boundary Layer Height Over Thailand: Correlations With Enso And Aerosol Optical Depth, Sirapong Sooktawee, Khwanruthai Renuhom, Siriwan Kaewket, Aduldech Patpai, Pramet Kaewmesri, Thongchai Kanabkaew, Pichnaree Lalitaporn

Applied Environmental Research

Thailand has been facing air pollution, e.g., PM2.5, and impacts from climate phenomena, e.g., the El Niño‒Southern Oscillation (ENSO). Both air pollution and climate interact with each other. Changes in the planetary boundary layer height (PBLH) can affect PM2.5, represented by the aerosol optical depth (AOD), and are influenced by ENSO related to changes in the PBLH. The relationships among the PBLH, ENSO, and AOD were investigated via an empirical orthogonal function (EOF), which decomposes the spatiotemporal data of the PBLH into spatial patterns and corresponding time series. Correlation analysis was used to determine the relationships between the PBL variability …

Applying Radom Forest And Support Vector Machine For Land-Use Classification In Phu Giao District Vietnam, Trong Dieu Hien Le, Linh Truong Vinh

Applied Environmental Research

Machine learning algorithms are currently widely used to classify satellite images to create surface maps of the earth. Support vector machines (SVMs) and random forests (RFs) are more effective ML algorithms and more accurate classifications than other methods. The aim of this study is to analyze the performance of these two algorithms in land-use and land cover classification. For this purpose, the Landsat 8 OLI satellite image freely provided by the United States Geological Survey (USGS) was used to classify land use in the Phu Giao District, Binh Duong Province, Vietnam, where forestland is being strongly converted into rubber plantations …

Jack Reacher And The Deployment Of An Airbag, Gregory A. Dilisi, Richard A. Rarick

2025 Faculty Bibliography

No abstract provided.

40 Years Passing By In (A) “Heartbeat”, Christopher Janney

Monsoon: South Asian Studies Association Journal

This article outlines the forty-year history go Christopher Janney’s iconic performance work “HeartBeat.” Trained as an architect and jazz musician, Janney combines these two disciplines to create large interactive light/sound installations and performances. On the one hand, he attempts to make architecture more like music, more “alive” using real-time sensing devices as on his “Harmonic Convergence” installation on the Miami International Airport. On the other hand, he attempts to make music more like architecture, more physical more visual. In his “HeartBeat” performance, a dancer wears a heartbeat device that amplifies his/her heartbeat in “real time.” Over this pulse, live musicians …

Yoga Sūtra Book Four And The Yogabindu, Christopher Key Chapple

Monsoon: South Asian Studies Association Journal

Four themes from the fourth pāda of Patañjali’s Yoga Sūtra are examined here: karma (IV:2-13), individuality (IV:16), humility (IV:20-22), and freedom (IV:29-34). Affirmations and variant interpretations of these four are provided from Haribhadra Virahāṅka’s Yogabindu, most likely composed a century or two later.

Collective Karma: From The Yogasūtra To Taylor Swift, Zoë Slatoff

Monsoon: South Asian Studies Association Journal

The Indian knowledge traditions speak at length about karma, which is divided into three categories—accumulated (saṃcita), ripe (prārabdha), and future (kriyamāṇa). While much is said about our individual karma and how it affects our repeated reincarnation in cyclic existence, how does this affect others and how do others affect us? In other words, as this paper explores, what is our reciprocal and collective karma?

Painting Liberation: A Visual Ontology Of The Interplay Of Mind And Consciousness In Book Four Of The Yoga Sūtras, Melissa Townsend

Monsoon: South Asian Studies Association Journal

This presentation explores how artistic practice can illuminate philosophical questions about the nature of mind, consciousness, and liberation as articulated in Book Four of the Yoga Sūtras of Patañjali. Through a series of paintings that visually translate these sūtras, I propose that art offers a unique, experiential means of engaging with the complex relationship between citta (mind) and puruṣa (consciousness).

The paintings function as a form of “visual ontology,” inviting viewers to engage with abstract philosophical concepts in a sensory, tangible way. By depicting the interplay between the mutable processes of the mind and the unchanging awareness of consciousness, these …

Atomic Physics For Everyone: An Introduction To Atomic Physics, Quantum Mechanics, And Precision Spectroscopy With No College-Level Prerequisites, Will Raven

Open Educational Resources: Textbooks

This open access textbook introduces beginning undergraduate students and high school students to the world of quantum mechanics and atomic spectroscopy. Requiring no previous knowledge of physics and no math beyond basic algebra and sines and cosines, this book focuses on concepts to make the excitement of atomic physics more accessible for learners than ever before. It comes replete with learning goals, exercises and solutions, and an optional experimental component, making this text readily adoptable for both the classroom and the undergraduate lab. The book takes the reader on a lively and engaging tour through topics at the forefront of …

Generation Z’S Perception Of Skin Cancer And How It Relates To Climate Change, Piercen Bogolea

Honors Undergraduate Theses

Skin cancer is the most common cancer worldwide, and climate change has been identified as a significant contributor. Preventative action early on can help reduce occurrence, but it is unknown if Generation Z is aware of this and is taking the necessary action now to protect themselves. This research aims to gauge the perception of Generation Z on the severity of skin cancer, the relationship between climate change and skin cancer, and the prevalence of preventative measures being taken. A survey was distributed to students aged 18 to 27 enrolled at the University of Central Florida through mixed sampling. The …

Beyond Homogeneity: Exploring Causal Heterogeneity In Psychopathology, Philip B. Vinh

Theses and Dissertations

Traditional models in psychiatric research often impose assumptions of causal homogeneity, treating population-level associations as reflective of uniform underlying mechanisms. This dissertation challenges that assumption by introducing statistical and machine learning frameworks designed to detect and model causal heterogeneity in the development of psychopathology. Central to this approach is the advancement of finite mixture structural equation modeling (FM-SEM) to identify latent subgroups characterized by distinct, and sometimes opposing, causal pathways.

The dissertation comprises three integrated empirical studies. The first introduces mixDoC, a finite mixture extension of the classical Direction of Causation (DoC) model applied to twin data, enabling the detection …

Artificial Intelligence And Environmental Sustainability: Review And Research Directions, Troy Strader, Yu-Hsiang (John) Huang, Yu-Ju Tu

Journal of International Technology and Information Management

Environmental sustainability is one of the most important and complex issues currently facing our global society. One solution to some aspects of this problem could come from artificially intelligent systems and data analytics methods. The objective for this study is to identify the range of recently published research that addresses issues involving the convergence of artificial intelligence (AI) and environmental sustainability. A systematic literature review produced a sample of 62 journal articles from 2018-2024 that were each categorized into one of six research themes that included studies of AI and the ways in which it impacted natural resources, energy and …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Psychology Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Predicting Human Steering From Optic Flow Using Deep Convolutional Neural Networks, Katie E. Bernard

Honors Theses

Human driving is a complex visuomotor task and the specific visual clues that guide it remain under investigation. While prior research has emphasized gaze-based strategies such as the Tangent Point and Future Path hypotheses, recent evidence highlights the potential role of optic flow, the visual motion pattern perceived during self-movement, as critical to steering ability. This thesis explores whether raw optic flow alone can support accurate predictions of human steering behavior. We trained a convolutional neural network to map optic flow vector fields to steering angles in a virtual reality driving simulation. The dataset, collected by Giguere et al., included …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Extraction Of Patient Subtypes Using Llm Generated Knowledge Graphs Integrated With A Transformer Architecture, Benjamin Holmes, Cogan Shimizu

Computer Science and Engineering Faculty Publications

Extracting patient subpopulations (clinically relevant cohorts of individuals who share overlapping symptoms, risk factors, or diagnostic criteria) from unstructured medical notes is an ongoing challenge due to the variability of clinical language and the complex nature of patient conditions. We demonstrate a pipeline that combines named entity recognition (NER), transformer embeddings, guided dimensionality reduction, and LLM-mediated knowledge graph integration to enhance patient extraction. The approach begins with NER using the UMLS metathesaurus [1] to extract clinical terms, followed by transformation into vector embeddings using a biomedical transformer. These embeddings are augmented with structured knowledge graph representations generated through an LLM-driven …