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Dynamics, Predictability And Impacts Of Multi-Year La Niña Event, Nahid A. Hasan

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation investigates the dynamics, predictability, and impacts of multi-year La Niña events. Multi-year La Niña events are referred to as extended periods of unusually cooler tropical Pacific that persist for two or more consecutive winters. These prolonged events can increase the risk of natural hazards such as droughts, floods, and heatwaves in the western US and around the world. Despite their worldwide significance, questions remain about the mechanisms driving their initiation, their predictability, and regional hydroclimate impacts.

The first chapter of the dissertation introduces what scientists currently believe causes them, and how well different types of climate models can …

A Comparative Study Of Novel Methods For Variances, Taoreed Muritala

Boise State University Theses and Dissertations

Understanding variability is fundamental to knowledge advancement across various disciplines, including manufacturing, clinical research, biology and genetics. Population variances play a crucial role in processes such as quality control, treatment evaluation and the interpretation of biological mechanisms. However, statistical procedures for comparing variances across multiple populations remain less developed than those for comparing means. Classical omnibus tests, such as Bartlett's and Levene's, can detect overall variance heterogeneity but fail to identify which populations differ, thereby limiting their usefulness in multi-population analyses and increasing the risk of inflated family-wise error rates through repeated testing.

This thesis develops and evaluates three multiple …

An Intelligent Healthcare System For Rare Disease Diagnosis Utilizing Electronic Health Records Based On A Knowledge-Guided Multimodal Transformer Framework, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Ankur Pandey

All Works

Rare diseases are a common problem with millions of patients globally, but their diagnosis is difficult because of varied clinical presentations, small sample size, and disparate biomedical data sources. Current diagnostic tools are not able to combine multimodal information effectively, which results in a timely or wrong diagnosis. To fill this gap, this paper suggests a smart multimodal healthcare framework integrating electronic health records (EHRs), genomic sequences, and medical imaging to improve the detection of rare diseases. The framework uses Swin Transformer to extract hierarchical visual features in radiographic scans, Med-BERT and Transformer-XL to learn semantic and long-term temporal relations …

Artificial Intelligence In Waste Management Systems: Applications, Challenges, And Prospects, Imane Belyamani

All Works

Despite global recognition of the climate crisis, greenhouse gas emissions are projected to rise by 8.8 % by 2030, primarily due to inadequate planning, poor implementation, and insufficient financial support. While international initiatives such as the ’Waste to Zero’ coalition launched at the 28th Conference of the Parties to the UNFCCC (COP 28) highlight the urgency of advancing decarbonization and the circularity of waste systems, this review focuses on how artificial intelligence (AI) can accelerate that transformation. It systematically explores the role of AI in advancing waste management practices, with a focus on predictive analytics, route optimization, and machine learning-based …

Embedding-Driven Dual-Branch Approach For Accurate Breast Tumor Cellularity Classification, Hossam Magdy Balaha, Ali Mahmoud, Khadiga M. Ali, Mohammed Ghazal, Norah Saleh Alghamdi, Ashraf Khalil, Ayman El-Baz

All Works

This study proposes a dual-branch framework for precise classification of breast tumor cellularity via histopathological images where it integrates two distinct branches: the Embedding Extraction Branch (embedding-driven) and the Vision Classification Branch (vision-based). The Embedding Extraction Branch uses the Virchow2 transformation to generate dense, structured embeddings, whereas the Vision Classification Branch employs Nomic AI Embedded Vision v1.5 to process image patches and produce classification logits. Both branches’ outputs are combined to form the final classification. The framework also suggests Knowledge Block with fully connected layers, batch normalization, and dropout to improve feature extraction and reduce overfitting. The proposed approach reports …

A Hybrid Fog-Edge Computing Architecture For Real-Time Health Monitoring In Iomt Systems With Optimized Latency And Threat Resilience, Umar Islam, Mohammed Naif Alatawi, Ali Alqazzaz, Sulaiman Alamro, Babar Shah, Fernando Moreira

All Works

The advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enabling real-time health monitoring. However, it introduces critical challenges related to latency and, more importantly, the secure handling of sensitive patient data. Traditional cloud-based architectures often struggle with latency and data protection, making them inefficient for real-time healthcare scenarios. To address these challenges, we propose a Hybrid Fog-Edge Computing Architecture tailored for effective real-time health monitoring in IoMT systems. Fog computing enables processing of time-critical data closer to the data source, reducing response time and relieving cloud system overload. Simultaneously, edge computing nodes handle data preprocessing …

Security Vulnerabilities And Defense Tactics For Generative Ai Application Development, Kyle Klein

University Honors Theses

Generative AI (GenAI) applications such as OpenAI's ChatGPT leverage large language models (LLMs) trained on enormous amounts of data to accomplish tasks such as document editing, summarization, and query response. Chatbots and LLM programs that are equipped with retrieval-augmented generation (RAG) have the ability to draw upon data provided by developers and users to improve the quality of the program's responses. LLM technology has even expanded to generate images, audio, and video from user instructions. Designed around unpredictable user input and typically composed of many opaque components, LLM software products face a paradigm shift of new, constantly evolving security challenges. …

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Final Data Summary Report 2019 Surface Water, Groundwater Seep, And Soil Characterization 2021-2023 Surface Water And Groundwater Seep Evaluation 2023 Waterloo Aps Soil And Groundwater Evaluation, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Wildfire Smoke And Public Health: Comparing 2023 Canadian Wildfire Events With Hospital Admissions In Douglas County, Nebraska, Jeremy Poell

Capstone Experience: Master of Public Health

Wildfires are becoming increasingly common in Canada and the United States. Smoke produced from these fires creates a multitude of air pollution constituents that can cause breathing and other health issues for humans, particularly those with asthma and other respiratory conditions. Of these pollutants, PM2.5 (particulate matter that is 2.5 microns or smaller) is particularly problematic as these particles are inhaled deep into lung tissue, where they create inflammation and oxidative stress. Poor air quality can also trigger asthma and respiratory issues, leading to an increase in emergency department admissions for breathing treatments. The goal of this study is to …

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Gaber, Mohamed Abdelraheem

Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

Evaluation Of Graphite And Activated Carbon As Suitable Water Purification Media For In-Situ Resource Utilisation (Isru) On Mars, Ciaran Archenoul

The Plymouth Student Scientist

Eventual human missions to the red planet will require large-scale in-situ resource utilisation to meet their objectives. Perhaps the most critical element for developing a sustainable architecture is propellant production from the products of water electrolysis and atmospheric carbon dioxide. The purpose of this study was to assess how graphitic materials may be used as porous filters to remove solvated ions from Martian water prior to electrolysis, reducing the overall complexity of ISRU systems. The two materials under study were PG25 graphite and activated carbon powder.

A comprehensive three-technique characterisation of both materials was performed, using helium pycnometry, N_{2 …}

Analysis Of Organic Compounds Extracted From Recycled Polypropylene Via Gc-Fid/Ms And Pyr-Gc-Ms For Future Pharmaceutical Applications, India E. Hateley

The Plymouth Student Scientist

A mandatory target for 30% of plastic packaging to be recycled has been proposed by 2030, in order to mitigate the problem of plastic waste being incinerated or deposited in landfills. However, during the recycling process additives are added and with polypropylene being used for plastic packaging and surgical masks, these additives need to be analysed for the presence of contaminants. Examples include VOCs, PAHs, phthalates, and brominated diphenyl’s, all of which have health issues. Two samples of recycled polypropylene pellets were obtained from a national recycling company, along with a reference pellet purchased through Sigma-Aldrich. All pellets underwent ultrasound-assisted …

A Generational Analysis Of Psychological Motivators Influencing Seafarer Retention, Perisah Tahanci

The Plymouth Student Scientist

Seafarer retention is a growing concern amid increasing global demand for skilled maritime officers. This study investigates the generational differences in psychological motivators influencing seafarer retention, where ‘psychological motivators’ encompass the cognitive factors, including mental and physical wellbeing, work-life balance, compensation, working conditions, and external factors, that shape retention intentions. A cross-sectional survey (n=214) combined quantitative and qualitative analyses to systematically assess how the perceived importance and experience of these factors vary across Generation Z, Millennials, Generation X, and Baby Boomers.

The findings reveal that significant generational differences exist across most factors, particularly in work-life balance and mental wellbeing, in …

Method Optimisation And Environmental Analysis Of Methanesulfonic Acid (Msa) In Rainwater By Ion Chromatography, Thomas Levett

The Plymouth Student Scientist

This research optimised a method of analysis for methanesulfonic acid (MSA) alongside common inorganic anions using ion chromatographic (IC) apparatus developed at the University of Plymouth. The aim was to assess whether MSA could be more easily and routinely monitored alongside common rainwater anions. The method’s analytical quality was evaluated through each development stage of the research and its limitations found. Historical rainwater samples collected at Penlee Point, Plymouth, UK (2015–2018) were also used for testing. The method successfully provided detectable ranges of MSA between 0.001 – 5 mg/L for F^-, Cl^-, NO_2-, Br …

Quantification Of Trace Metal(Loids) In The River Seaton, Cornwall, Uk And The Influence Of The South Caradon Mine On Ecological Risk, Bjorn Piñol

The Plymouth Student Scientist

Freshwater quality is critical to the health of aquatic ecosystems and human water security, yet anthropogenic activities, such as historic mining, continue to degrade aquatic systems. While extensive research has examined metal contamination in major rivers like the River Tamar, smaller tributaries affected by legacy mining remain understudied. This study investigates trace metal contamination and its controlling factors in the River Seaton, Cornwall, a small river influenced by historic mining from the South Caradon Mine. Water samples collected from four study sites along the river gradient and a reference site at Siblyback Lake were subjected to ICP-MS analysis and physico-chemical …

Collective Agency And Community Resilience Among Farmworkers In The Lower Rio Grande Valley, Angel Velazquez

Theses and Dissertations

This research assesses how farmworkers in the Lower Rio Grande Valley of Texas use everyday practices to build resilience and adapt to changes in their lives. I apply two interconnected theories, White’s (2017, 2019) framework of collective agency and community resilience and Castro and Sen’s (2022) framework of everyday adaptation actions, to study these practices. I conducted 19 semi-structured interviews with Latino farmworkers and professionals who work with local farmworker organizations in the Rio Grande Valley (RGV) of Texas. Interview transcripts were analyzed to determine if and how Latino farmworkers in the RGV can work towards community resilience and implement …

Determination Of An Effective Natural Boxelder Bug (Boisea Trivittata) Repellent, Reyna Chavez

Theses and Dissertations

This study investigates the use of ecofriendly repellant alternatives to pest management to control boxelder bugs (Boisea trivittata). This bug gathers by the thousands on warm surfaces of exterior suburban homes during early fall and late spring. I determined bug repellency to turmeric oil (Curcuma longa), catnip (Nepeta cataria), citronella (Cymbopogon nardus), and lavender (Lavandula angustifolia). The treatments consisted of essential oils containing 20% methanol. All treatments demonstrated repellency of Boxelder bugs. Citronella was the most effective and had the highest level of repellency range of 90-99%. Catnip was the least effective with a repellency range of 63-82%.

Clustering 24-Hour Ambulatory Blood Pressure Time Series With Dynamic Time Warping And Time Warp Edit Distance, John Knight

Theses and Dissertations

Ambulatory blood pressure monitoring (ABPM) captures dynamic circadian changes in blood pressure (BP) that are not reflected in static clinic readings. This study applied time-series clustering with two elastic distance measures—Dynamic Time Warping (DTW) and Time Warp Edit Distance (TWED)—to identify distinct phenotypes in 2,155 24-hour ABPM time series from participants in the Maracaibo Aging Study. DTW and TWED both yielded three clusters corresponding to non-dipping, moderate-dipping, and strong-dipping patterns. The non-dipping group showed elevated nighttime BP, associated with greater cardiovascular and cognitive risk, while the strong-dipping group was associated with higher education and younger age in baseline clinic measurements. …

A Picture Tells A Thousand Words—, But Ecg Signals Have More To Say, Ashley N. Gomez

Theses and Dissertations

With the increasing adoption of deep learning classification models in the medical domain, a critical challenge remains: achieving high predictive accuracy while maintaining clinical Inter-pretability. This study examines how model architecture, dataset origin, and the use of full versus subset data affect both classification performance and Interpretability in Electrocardiogram (ECG) signal analysis. ResNet18 is evaluated using an open-source ECG Image Dataset, thus a custom dataset derived from digitized ECG images. Post-hoc explainability methods, such as Integrated Gradients, are applied to determine which time steps have the most significant influence on model decisions. The findings demonstrate that model architecture and dataset …

Interactive Effects Of Nutrient Loading And Hyposalinityon The Physiological Responses Of The Red Macroalga Gracilaria Tikvahiae, Donavuan Vincent Salazar

Theses and Dissertations

Coastal macroalgae face anthropogenic stressors such as nutrient enrichment from nitrogen fertilizers and reduced salinity linked to flooding. The physiological impacts of these combined stressors remain unclear. This study examined interactive effects of nitrogen loading and hyposalinity on Gracilaria tikvahiae through a 9‑day laboratory experiment. Samples experienced declining salinity (35–0 ppt) with nitrate or ammonia enrichment (120 µmol/L). Measurements included primary production, respiration, biomass, nitrate uptake, and chlorophyll‑a. Hyposalinity significantly reduced physiological performance, with gross primary production declining over 100%, chlorophyll‑a content 25–45% lower, biomass loss, and reduced nitrogen uptake. Nitrogen enrichment failed to mitigate the adverse impacts under hyposaline …

Postprocessing Gan-Generated Synthetic Time Series Using Dynamic Time Warping, Md Raisul Islam Roni

Electronic Theses and Dissertations

Generative Adversarial Networks (GANs) are a class of deep learning models capable of producing realistic synthetic data that preserve the statistical and temporal characteristics of real datasets. The DoppelGANger (DGAN) framework extends this approach to time series data by jointly modeling temporal dependencies and contextual metadata. However, synthetic sequences generated by GAN may show temporal misalignment, resulting in inconsistencies when compared with real data. This study presents a postprocessing framework based on Dynamic Time Warping (DTW) and its differentiable extension Soft-DTW to improve the temporal alignment of synthetic time series. The framework is evaluated using quantitative measures of alignment and …

Definition Of The 3d Position And Motion Status Of The Moving Heart Based On 2d Projections, Lawrence D. Orijuela

Electronic Theses, Projects, and Dissertations

This thesis presents a novel application of deep learning to the estimation of pulmonary vein coordinates using X-ray image pairs from a FORBILD Thorax phantom derived motion dataset. A Siamese neural network was developed to predict the 3D coordinates of one pulmonary vein at a time, specifically the Right Superior Pulmonary Vein (RSPV), Left Superior Pulmonary Vein (LSPV), Left Inferior Pulmonary Vein (LIPV), or Right Inferior Pulmonary Vein (RIPV), based on two-dimensional projection images.

The input data consisted of over 1.6 million grayscale X-ray image pairs across 1331 virtual patients, each annotated with ground truth 3D coordinates. To manage memory …

Groundwater Arsenic Contamination In The Oro Grande Wash, Dalila Boice

Electronic Theses, Projects, and Dissertations

This study investigates the distribution of naturally occurring arsenic in groundwater within the Oro Grande Wash in San Bernardino County, California. Depth-discrete groundwater quality data were collected over multiple years using nested and Westbay monitoring wells. Water quality results showed higher levels of arsenic in the deeper aquifers, ranging between 600 feet and 1,000 feet below ground surface. Arsenic levels in these regions reached as high as 66 µg/L. At roughly 800 feet and below, water quality data from the wells reveal that arsenic concentrations exceeded the 10 µg/L maximum contaminant level (MCL) in 87% of cases. These data provide …

A Leslie System For A Demographic Simulation: From An Actuarial Point Of View, David Kings

Electronic Theses and Dissertations

This thesis develops a discrete stochastic linear systems interpretation of age–stage demographic evolution grounded in Leslie operators and realized in a discrete-event simulation implemented with salabim. The central claim is that one annual cycle of the simulation constitutes a cone-preserving, stochastic affine transformation on a high- dimensional population state vector indexed by age, sex, marital status, household type, employment, and education, and that the composition of yearly operators yields a random matrix product whose top Lyapunov exponent is the stochastic counterpart of the Perron–Frobenius growth rate (Caswell, 2001; Tuljapurkar, 1997)[1, 2]. The actuarial bridge is constructed by mapping simulated survival …

Isolation, Chemical Characterization, And In-Vitro Cytotoxic Evaluation Of Novel Polar Flavonoids From Chromolaena Leivensis, Matthew Tohatsu Tetteh

Electronic Theses and Dissertations

This study focuses on isolation, chemical characterization, and in-vitro cytotoxic evaluation of novel polar flavonoids from chromolaena leivensis. A 95% ethanolic extract of c. leivensis shipped by Prof. Ruben Torrenegra from University of Applied and Environmental Sciences, Bogota, Colombia, was dissolved in 1:1 methanol/chloroform mixture and its purity analyzed by TLC. The sample was eluted with toluene/methanol in an increasing order of polarity on silica gel, resulting in 49 fractions labelled CLA1 to CLA49. Among these fractions, CLA10 (1) and CLA19 (2) obtained yellow and white crystals. They were analyzed by GCMS, IR, and …

Precision-Weighted Federated Learning, Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam, Marta Kersten-Oertel

Computer Science Faculty Publications

Federated learning (FL) using the federated averaging (FedAvg) algorithm has shown great advantages for large-scale applications that rely on collaborative learning, especially when the training data is either unbalanced or inaccessible due to privacy constraints. We hypothesize that FedAvg underestimates the full extent of heterogeneity of data when the aggregation is performed. We propose Precision-Weighted Federated Learning (PW) a novel algorithm that takes into account the second raw moment (uncentered variance) of the stochastic gradient when computing the weighted average of the parameters of independent models trained in a FL setting. With PW, we address the communication and statistical challenges …

The Presentation Of Self In Everyday Digital Life: A Study Of Self- Disclosure And Work Environments, Mackenzie Michelle Skiff

Communication & Theatre Arts Theses

The digital age impacts individuals’ lives in many ways. One impact is how and where work is completed across many careers. The work-from-home strategy enables individuals to complete work that is not within a shared space, such as an office. With the absence of this shared space, communication practices within workplaces could be changing. Specifically, self-disclosure while working from home may differ from self-disclosure within the office or hybrid (both in office and remote) work environments. This thesis investigates whether there are differences in self-disclosure practices across three different types of contemporary work environments and offers a digital update to …

Sme Cyber Resilience State Of The Sector 2025, Hazel Murray, Gillian O'Carroll, Aoibheann Brangan, Jason Holland, Stephanie Chevanne Wallace, Miriam Curtain, Glenda Deveney

Department of Computer Science Publications

Ireland's small and medium enterprises (SMEs) face a critical cyber resilience gap. SMEs account for 99.8% of all enterprises in Ireland and employ over 2.29 million people, representing 67.9% of total employment (based on the latest CSO 2022 figures). This cyber resilience assessment reveals that the majority of SMEs remain underprepared for modern cyber threats.

The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden

Milne Open Textbooks

Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.

Demystifying the Machine

This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …