Digital Commons Network^™

Insights From Diverse Environments: Investigating The Fate And Transport Of Semivolatile Organic Contaminants In Alpine, Arctic, And Arid Regions, Jeffrey Perala-Dewey

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation investigates the fate and transport of pollutants through four field-based studies in a diverse array of environments. These pollutants travel through the atmosphere and end up in places far from their original sources. In this work I explore how chemical properties of the pollutants and the environmental processes that are present change the way the pollutants travel through the environment. In the first study, pollutants from car engines were quantified in the vegetation along transects in three alpine valleys. Using these measurements, I investigated how the chemical properties of the pollutants impacted their interplay with wind systems in …

Debtor Eligibility Prediction Using Deep Learning With Chatbot-Based Testing, Reski Noviania, Enny Itje Sela, Luther Alexander Latumakulita, Steven R. Sentinuwo

Knowledge Engineering and Data Science

Predicting debtor eligibility is essential for effective risk management and minimizing lousy credit risks. However, financial institutions face challenges such as imbalanced data, inefficient feature selection, and limited user accessibility. This study combines Recursive Feature Elimination (RFE) and Deep Learning (DL) to improve prediction accuracy. It integrates a chatbot interface for user-friendly testing. RFE effectively identifies critical features, while the DL model achieves a validation accuracy of 97.62%, surpassing previous studies with less comprehensive methodologies. The chatbot's novel design not only ensures accessibility but also enhances user engagement through flexible input options, such as approximate values, enabling non experts to …

Deep Learning Approach For Dental Anomalies X-Ray Imaging Using Yolov8, Amelia Ritahani Ismail, Md Salim Sadman Taseen

Knowledge Engineering and Data Science

Dental X-ray imaging is a critical diagnostic tool for identifying various dental anomalies. However, manual interpretation is time-consuming, prone to human error, and requires specialized expertise. Deep learning models, particularly object detection frameworks like YOLO, have demonstrated promising results in automating medical image analysis. This study aims to develop and evaluate a YOLOv8-based deep learning model for automated detection and classification of 14 dental anomaly categories, including Caries, Crowns, Fillings, Implants, and Periapical lesions. The proposed approach addresses limitations in previous YOLO versions by leveraging anchor-free detection and enhanced feature extraction for improved accuracy. The model was trained on a …

A Hierarchical Density-Based Spatial Clustering Of Applications With Noise (Hdbscan) Approach For Identifying Potential Villages In Buleleng Regency, Dina Nur Amalina, Achmad Fauzan

Knowledge Engineering and Data Science

Buleleng Regency, located in Bali Province, possesses diverse village potential, including agricultural production and tourist attractions. However, this potential has not been fully optimized. Therefore, it is important to enhance village potential by clustering villages based on their specific characteristics to identify and prioritize those requiring special attention. This approach aims to promote equitable village development and reduce poverty levels. This study clusters villages in Buleleng Regency based on their potential using the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) method. The data utilized in this study comprises village potential data obtained from the Buleleng Regency Statistics Office …

Mimicking To Dominate: Imitation Learning Strategies For Success In Multiagent Competitive Games, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

Training agents in multi-agent games presents significant challenges due to their intricate nature. These challenges are exacerbated by dynamics influenced not only by the environment but also by strategies of opponents. Existing methods often struggle with slow convergence and instability. To address these challenges, we harness the potential of imitation learning (IL) to comprehend and anticipate actions of the opponents, aiming to mitigate uncertainties with respect to the game dynamics. Our key contributions include: (i) a new multi-agent IL model for predicting next moves of the opponents --- our model works with hidden actions of opponents and local observations; (ii) …

Sampdetox : Black-Box Backdoor Defense Via Perturbation-Based Sample Detoxification, Yanxin Yang, Chentao Jia, Dengke Yan, Ming Hu, Tianlin Li, Xiaofei Xie, Xian Wei, Mingsong Chen

Research Collection School Of Computing and Information Systems

The advancement of Machine Learning has enabled the widespread deployment of Machine Learning as a Service (MLaaS) applications. However, the untrustworthy nature of third-party ML services poses backdoor threats. Existing defenses in MLaaS are limited by their reliance on training samples or white-box model analysis, highlighting the need for a black-box backdoor purification method. In our paper, we attempt to use diffusion models for purification by introducing noise in a forward diffusion process to destroy backdoors and recover clean samples through a reverse generative process. However, since a higher noise also destroys the semantics of the original samples, it still …

Exploring Post-Covid-19 Health Effects And Features With Advanced Machine Learning Techniques, Muhammad N. Islam, Md S. Islam, Nahid H. Shourav, Iftiaqur Rahman, Faiz A. Faisal, Md M. Islam, Iqbal H. Sarker

Research outputs 2022 to 2026

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and …

Automating Maritime Risk Data Collection And Identification Leveraging Large Language Models, Donghao Huang, Xiuju Fu, Xiaofeng Yin, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Maritime risk research is crucial yet challenging for improving safety, efficiency, and sustainability in maritime operations. This paper presents an innovative method for automating the collection and identification of risk data related to global maritime risks from news sources, addressing the limitations of traditional manual methods. To evaluate the proposed method, different learning-based models, including conventional machine learning approaches and advanced Large Language Models (LLMs) such as GPT-4 and LLaMA-3.1, are comprehensively studied for comparison. In addition, not only do we use popular evaluation metrics to assess the proposed method, but we also introduce a new evaluation metric, called the …

Revisiting Masked Auto-Encoders For Ecg-Language Representation Learning, Hung Manh Pham, Aaqib Saeed, Dong Ma

Research Collection School Of Computing and Information Systems

We propose C-MELT, a novel framework for multimodal self-supervised learning of Electrocardiogram (ECG) and text encoders. C-MELT pre-trains a contrastive-enhanced masked auto-encoder architecture using ECG-text paired data. It exploits the generative strengths with improved discriminative capabilities to enable robust cross-modal alignment. This is accomplished through a carefully designed model, loss functions, and a novel negative sampling strategy. Our preliminary experiments demonstrate significant performance improvements with up to 12% in downstream cardiac arrhythmia classification and patient identification tasks. Our findings demonstrate C-MELT's capacity to extract rich, clinically relevant features from ECG-text pairs, paving the way for more accurate and efficient cardiac …

User Acceptance Of Advice By Ai Agents: Expectation-System Fit Perspective, Jingyuan Cai, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Algorithms have increasing influence on our daily decisions, especially when the recommendations are presented by human-like AI agents. This study applies the Theory of Effective Use to investigate how the fit between the user’s role expectation for an AI agent and the agent’s interaction style impacts AI advice adoption. We proposed a new concept termed Perceived Expectation-System Fit (PESF) and empirically examined its impact on user perceptions and advice acceptance. We found that low PESF reduces advice acceptance by diminishing cognitive and affective trust in the AI agent. Furthermore, increased algorithm transparency increases PESF's impact on decision-making. Our findings provide …

Enhancing Water Sustainability In North Africa: Literature Review And Synthesis Of Current Knowledge Gaps In Sudan, Osman M. A. Adam

Department of Agricultural and Biological Systems Engineering: Masters Project Reports

This study delves into the critical role of groundwater in addressing global water challenges, with a focus on the Nubian Sandstone Aquifer System (NSAS) in north Africa. Groundwater constitutes a source of potable water, irrigation, and industrial use, especially in arid regions where surface water is limited. We analyzed the status of water quantity, withdrawals, recharge, and geological characteristics in the NSAS, specifically in Sudan, Egypt, and Libya. Though the NSAS is largely an untapped resource, water withdrawals from the NSAS in Egypt, Sudan, and Libya are projected to increase substantially from 2000 to 2100 due to population growth, with …

Not All Samples Are Created Equal: Task-Aware Informative Sampling And Adaptive Inference For Efficient Edge Ai, Rebati Gaire

School of Computing: Dissertations, Theses, and Student Research

The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented influx of data generated at the edge by billions of sensors. Traditional approaches relying on cloud-based processing are increasingly inadequate due to constraints in bandwidth, latency, and privacy. Edge computing has emerged as a transformative paradigm, enabling real-time data processing and decision-making by decentralizing computation to the edge. While the integration of deep learning into edge environments—termed edge intelligence—promises autonomous and personalized operations, it is hindered by challenges such as limited computational resources, energy constraints, and data redundancies.

This thesis addresses these challenges by presenting three …

Exploring The Cognitive Sense Of Self In Ai: Ethical Frameworks And Technological Advances For Enhanced Decision-Making, Emily Barnes, James Hutson

Faculty Scholarship

The burgeoning field of Artificial Intelligence (AI) increasingly focuses on developing systems capable of self-awareness, merging technological innovation with deep ethical and philosophical considerations. This article explores the cognitive sense of self within AI, examining mechanisms through which AI systems may mirror human-like consciousness and self-perception. Despite significant advances, substantial gaps remain in the understanding and practical implementation of self-aware characteristics in AI, particularly in applying theoretical models and ethical frameworks to real-world scenarios. There is a pressing need for comprehensive research to explore these theoretical underpinnings and translate them into operational systems capable of ethical and adaptable behaviors. This …

Meta-Entrepreneurship: An Analysis Theory On Integrating Generative Ai, Agentic Ai, And Metaverse For Entrepreneurship, Yingying Zhang, Keng Siau

Research Collection School Of Computing and Information Systems

Metaverse entrepreneurship has emerged as an innovative topic alongside the development of generative AI, agentic AI and metaverse. This study conceptualizes meta-entrepreneurship as a novel form of entrepreneurial activity that enables value creation within virtual and physical realms and proposes an analytical theoretical framework based on a systematic literature review, observations, and focus group study. Our framework is structured around three layers (infrastructure, content, and experience) and two domains (metaverse-based operational domain and AI-based production domain), aims to conceptualize “what is meta-entrepreneurship” and identify new possibilities. The research highlights the multifaceted impact of meta-entrepreneurship on individuals, corporations, industries, societies, and …

The Impact Of Wild Pigs (Sus Scrofa) On Avian Occupancy And Vegetation Structure, Kenneth Wilson

Graduate Theses and Dissertations

Invasive species, particularly wild pigs (Sus scrofa), pose a significant threat to native ecosystems through both direct and indirect impacts. Wild pigs are large-bodied omnivorous species that can consume a wide variety of plants and animals and are known for destructive foraging behaviors, which likely threatens avian communities through habitat alteration and can impact the long term structure of ecosystems where they are present.

In chapter 1, we used a combination of avian point count surveys, vegetation assessments, and camera trap surveillance to quantify how the occupancy of breeding birds in bottomland hardwood forests changed in relation to …

Recreational Fishing For Western Rock Lobster: Estimates Of Participation, Effort And Catch In 2023/24, Claire B. Smallwood, Karina L. Ryan, Alissa C. Tate

Fisheries Research Reports

The Western Rock Lobster (WRL) (Panulirus cygnus) is the most commonly caught Rock Lobster (RL) species in Western Australia. Catches from the commercial and recreational sectors are required to determine and monitor Total Allowable Commercial Catch (TACC), Total Allowable Recreational Catch (TARC) and the proportion of Allowable Harvest Level (AHL) achieved. The TARC is set at 5% of the AHL and evaluated in the harvest strategy based on a 5-year average.

Data for the recreational sector are obtained using phone-recall surveys to provide annual estimates of participation, fishing effort and retained catch (by numbers) from recreational fishers who hold a …

Analysis Of Impulsive Differential Equation Models Of Cell Populations Undergoing Radiation Therapy, Abigail D'Ovidio Long

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Radiation therapy is a mode of treatment which is implemented for approximately 50% of cancer patients. Treatment needs to be able to kill cancer cells, but also do minimal damage to surrounding healthy tissue. We propose two main impulsive differential equation models of radiation therapy to capture the periodic nature of the treatment. These models build off of previous studies using clinical data to ensure biological relevance. The first model incorporates only cancer cell populations, and we provide parameter relationships which theoretically ensure treatment outcomes of cancer eradication, cancer approaching a carrying capacity, and cancer approaching a periodic solution. We …

Spatial Ecology Of American Bison On Vermejo Park Ranch, New Mexico, Kate Ann Asmus

School of Natural Resources: Dissertations, Theses, and Student Research

American bison (Bison bison) are a keystone species that impact grassland productivity, plant diversity, and landscape heterogeneity. We used GPS telemetry and a replicate herbivore grazing experiment on Vermejo Park Ranch in northeastern New Mexico to advance understanding of bison spatial ecology and grazing dynamics. First, we evaluated the potentially disparate influences of forage productivity and site fidelity on the size and selection of home ranges of bison. Home range size was strongly negatively influenced by forage productivity. However, home range selection was influenced more strongly by site fidelity than spatial variation in forage, as bison selected home …

Regulating Robo-Advisors In An Age Of Generative Artificial Intelligence, Daniel Schwarcz, Tom Baker

Law & Economics Working Papers

New generative Artificial Intelligence (AI) tools can increasingly engage in personalized, sustained and natural conversations with users. This technology has the capacity to reshape the financial services industry, making customized expert financial advice broadly available to consumers. However, AI’s ability to convincingly mimic human financial advisors also creates significant risks of large-scale financial misconduct. Which of these possibilities becomes reality will depend largely on the legal and regulatory rules governing “robo-advisors” that supply fully automated financial advice to consumers. This Article consequently critically examines this evolving regulatory landscape, arguing that current U.S. rules fail to adequately limit the risk that …

From Classroom To Career: Preparing Future Geoscientists For Workforce Success, Gregory Shafer

Boise State University Theses and Dissertations

The wide range of career opportunities for geoscience students, combined with a changing workforce, makes it more challenging for undergraduate programs to adequately prepare students for their careers. Therefore, it is important for geoscience programs to have a comprehensive view of the workforce needs and what barriers students may encounter when transitioning to the workforce. This dissertation identifies key skills and competencies essential for bachelor-level geoscientists, as well as potential barriers for recent graduates entering the workforce. The study analyzed entry-level geoscience job advertisements using a case-insensitive code matching function in MATLAB and conducted interviews with geoscience employers to identify …

Environmental Impact Assessments (Eia): Analysis Of Transboundary Environmental Impact Assessments For The Development Of A Uniform Teia Model, Nicolas Chapa

Open Access Theses & Dissertations

This dissertation investigates the evolution, processes, and importance of Environmental Impact Assessments (EIAs), focusing on transboundary EIAs and the need for a uniform framework. Originating from the National Environmental Policy Act (NEPA) of 1969 in the U.S., EIAs have become globally adopted instruments for assessing and mitigating environmental impacts of development projects. This work reiterates historical milestones, strengths, and current limitations of EIAs. Research also included a review of environmental regulations from Mexico, such as the General Law on Ecological Equilibrium and Environmental Protection (LGEEPA). Through several case studies requiring the use of transboundary EIAs, where shared resources and concerns …

Cmos-Based Rotational Spectroscopy: Massive Spectral Fingerprint Generation And Molecular Detection With Deep Learning, Yasamin Fozouni

Computer Science and Engineering Theses and Dissertations

Rotational Spectroscopy is a powerful spectral fingerprinting approach that can be used for identifying different gas molecules in a sample. Gas molecules are free to rotate, with inertia, in fixed states of quantized energy. In Rotational Spectroscopy, radiative beams are shown onto a sample to cause an energy-based transition between quantized rotational states. By sweeping the frequency of the radiative beams and monitoring the absorption with a sensor, one can profile the different rotational states, monitoring for energy based transitions. These transitions are dependent on unique properties of the molecules, thus presenting a unique molecular identification fingerprint (in the form …

Investigation Of Social Networks Upon Academic Performance And Mental Health, Rachel Izenson

Master's Theses

It has been shown that computing students have a statistically significantly lower overall sense of belongingness compared to other science students. A sense of community is important for many reasons. For example, there are studies that show that a student's sense of belonging correlates with improved academic performance. Our research aims to analyze the sense of belonging among computing students at Cal Poly San Luis Obispo through a network science lens. We surveyed for their sense of belonging, as well as their social network, to understand how friendships impact one's sense of belonging. When student responses were split by gender, …

Front Matter

The Synapse: Intercollegiate science magazine

No abstract provided.

Aars Online: A Collaborative Database On The Structure, Function, And Evolution Of The Aminoacyl-Trna Synthetases, Jordan Douglas, Haissi Cui, John J. Perona, Oscar Vargas-Rodriguez, Henna Tyynismaa, Claudia Alvarez Carreno, Jiqiang Ling, Lluis Ribas De Pouplana, Xiang-Lei Yang, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

The aminoacyl-tRNA synthetases (aaRS) are a large group of enzymes that implement the genetic code in all known biological systems. They attach amino acids to their cognate tRNAs, moonlight in various translational and non-translational activities beyond aminoacylation, and are linked to many genetic disorders. The aaRS have a subtle ontology characterized by structural and functional idiosyncrasies that vary from organism to organism, and protein to protein. Across the tree of life, the 22 coded amino acids are handled by 16 evolutionary families of Class I aaRS and 21 families of Class II aaRS. We introduce AARS Online, an interactive Wikipedia-like …

Landscaping Impacts On Urban Soil Development, Fry Lundgren

University Honors Theses

Urban soils can play a key role in flood mitigation, water filtration, and supporting urban plant communities, however many are highly disturbed due to development and management practices. Although full recovery will take time (centuries), in the short term managing soils in ways that conserve organic matter inputs and promote nutrient cycling can support important soil functions and likely promote long term development. To understand how landscaping impact soil development on PSU campus, organic matter content, moisture content, and respiration rates were measured in soils from four area types with different long term weed management strategies (mulch- M; sustained plant …

Assessing Reproducibility Challenges In Clinical Metabolics, Darcy Lin Cochran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Current metabolomics research is expanding to be multiplatform and interdisciplinary. Metabolomic analysis has the potential to provide detailed insight into any biological system of interest to analyze the underlying molecular mechanisms of variables like environment, disease, and genetics. Human clinical metabolomics is a major research area that is often focused on finding biomarkers or panels of biomarkers for different diseases. However, results are difficult to compare across different laboratories since the field of metabolomics has yet to widely adopt best practices for sample preparation, data acquisition and data processing, results are difficult to compare across different laboratories.

This thesis focuses …

Effect Of Fathers In Preemie Prep For Parents (P3) Program On Couple’S Preterm Birth Preparedness, Mir A. Basir, Siobhan M. Mcdonnell, Ruta Brazauskas, U. Olivia Kim, Sheikh Iqbal Ahamed, Jennifer J. Mcintosh, Kris Pizur-Barnekow, Michael B. Pitt, Abbey Kruper, Steven R. Leuthner, Kathryn E. Flynn

Computer Science Faculty Research and Publications

Objective

Evaluate the effect of fathers’ participation in the Preemie Prep for Parents (P3) program on maternal learning and fathers’ preterm birth knowledge.

Methods

Mothers with preterm birth predisposing medical condition(s) enrolled with or without the baby’s father and were randomized to the P3 intervention (text-messages linking to animated videos) or control (patient education webpages). Parent Prematurity Knowledge Questionnaire assessed knowledge, including unmarried fathers’ legal neonatal decision-making ability.

Results

104 mothers reported living with the baby’s father; 50 participated with the father and 54 participated alone. In the P3 group, mothers participating with the father (n = 33) had greater …

A Machine Learning Approach For Survival Analysis Of Transplanted Kidneys Based On Donors’ And Recipients’ Factors., Alain Edward Despeignes

Theses and Dissertations

Over seven thousand people on average die each year in the United States waiting for an organ transplant due to the shortage of donated organs. With this alarming concern, efforts from the health organizations like the United Network Organ Sharing (UNOS) and government officials have considered avenues to remedy this distress, one of which is to investigate the characteristics among donors and recipients that affects the longevity of donated organs. The goal of this project is to investigate the survival time of transplanted kidneys from 1987 to 2018 with regards to the donors’ and the recipients’ characteristics including gender, ethnicity, …

Oceano Dunes Community Survey Results, Michele Romolini, Eric G. Strauss, Marni Goldenberg, Keri Schwab

Center for Urban Resilience Reports

This report presents the findings of a 42-question survey conducted by Loyola Marymount University and Cal Poly San Luis Obispo from June 2023-May 2024 among visitors and local residents regarding their perceptions and experiences at California’s Oceano Dunes State Vehicular Recreation Area (SVRA). The survey aimed to gather insights into visitor and community demographics, frequency and types of use, barriers to use, environmental awareness and perceptions of use, and familiarity with park opportunities. In particular, we sought to seek responses from communities local to the parks, especially from the community of Oceano itself, and Latino and Hispanic community members. In …