Physical Sciences and Mathematics Commons^™

Novel Primitive Decompositions For Real-World Physical Reasoning, Mackie Zhoou, Bridget Duah, Jamie C. Macbeth

Computer Science: Faculty Publications

In this work, we are concerned with developing cognitive representations that may en- hance the ability for self-supervised learning systems to learn language as part of their world explorations. We apply insights from in-depth language understanding systems to the problem, specifically representations which decompose language inputs into language-free structures that are complex combinations of primitives representing cognitive abstractions such as object permanence, movement, and spatial relationships. These decompositions, performed by a system traditionally called a conceptual analyzer, link words with complex non-linguistic structures that engender the rich relations between language expressions and world exploration that are a familiar aspect of …

Interleaving A Symbolic Story Generator With A Neural Network-Based Large Language Model, Jingwen Xiang, Zoie Zhao, Mackie Zhou, Megan Mckenzie, Alexis Kilayko, Jamie C. Macbeth, Scott Carter, Katharine Sieck, Matthew Klenk

Computer Science: Faculty Publications

Research in deep learning has recently produced models of natural language that are capable of generating natural language output which, at a glance, has strong similarities to that written by intelligent humans. However, the texts produced by deep learning-based large language models (LLMs), upon deeper examination, reveal the challenges that they have in producing outputs that maintain logical coherence. One specific application area of interest for LLMs is in fictional narrative generation, a mode of operation in which stories are generated by the model in response to a prompt text that indicates the start of a story or the desired …

The Future Of Ai Accountability In The Financial Markets, Gina-Gail S. Fletcher, Michelle M. Le

Faculty Scholarship

Consumer interaction with the financial market ranges from applying for credit cards, to financing the purchase of a home, to buying and selling securities. And with each transaction, the lender, bank, and brokerage firm are likely utilizing artificial intelligence (AI) behind the scenes to augment their operations. While AI’s ability to process data at high speeds and in large quantities makes it an important tool for financial institutions, it is imperative to be attentive to the risks and limitations that accompany its use. In the context of financial markets, AI’s lack of decision-making transparency, often called the “black box problem,” …

A Framework For Inland Cities To Prevent Marine Debris: A Case Study From Durham, North Carolina, Nancy Lauer, Michelle B. Nowlin

Faculty Scholarship

Land-based sources of litter are increasingly recognized as significant contributors to marine debris, and rivers can carry debris to the coast from far-inland sources. In this paper, we demonstrate the important role inland cities can play in the marine debris crisis by reducing their own marine debris contributions. Given this role, we provide a framework for inland cities to prevent plastic pollution along with the lessons learned from introducing these strategies in Durham, North Carolina, a mid-sized, inland city that drains to the ocean through the Cape Fear and Neuse River watersheds. This framework guides city officials, resource managers, and …

Blockchain And Distributed Ledger Technologies For Iot Security: A Survey Paper, Suleiman Abdulrahman, Maroning Useng

Mesopotamian Journal of Computer Science

As the Internet of Things (IoT) continues to grow, the security concerns associated with this technology become increasingly important. Blockchain and Distributed Ledger Technologies (DLTs) are emerging as potential solutions for IoT security due to their decentralized and immutable nature. In this survey paper, we provide a comprehensive overview of the state-of-the-art research in the use of blockchain and DLTs for IoT security. We begin by introducing the basic concepts of blockchain and DLTs, followed by a discussion of their potential applications in IoT security. We then review the existing literature on the topic, including both academic and industrial research. …

Current Cutting-Edge Research In Computer Science, Mohanad Ghazi Yaseen, Mohammad Aljanabi, Ahmed Hussein Ali, Saad Abbas Abd

Mesopotamian Journal of Computer Science

Computer science research is a rapidly evolving field that is shaping the future of technology. From artificial intelligence and machine learning to image processing and cybersecurity, researchers are constantly pushing the boundaries of what is possible. In this editorial, we will explore some of the current trends in computer science research and their potential impact on society. After searching the most prestigious academic databases, we settle on a list of subjects widely recognized as cutting-edge in the field of computer science.

Security And Privacy In Iot-Based Healthcare Systems: A Review, Omar Ibrahim Obaid, Saba Abdul-Baqi Salman

Mesopotamian Journal of Computer Science

IoT-based healthcare solutions have transformed patient care and improved results. These technologies capture and store sensitive patient data, raising security and privacy concerns. The paper first discusses IoT-based healthcare system security issues. It evaluates cyber threats, system unavailability, and vulnerabilities attackers can use to get patient data. The report also tackles IoT-based healthcare system privacy issues such illegal data access and sharing and patient data breach concerns. The study proposes numerous frameworks and solutions to protect patient data in IoT-based healthcare systems. Blockchain technology can increase data security and privacy by offering a transparent, decentralized, tamperresistant database. The report also …

Anomaly Detection In Encrypted Https Traffic Using Machine Learning: A Comparative Analysis Of Feature Selection Techniques, Hind Raad Ibraheem, Nashwan Dheyaa Zaki, Mohammed Ibrahim Al-Mashhadani

Mesopotamian Journal of Computer Science

With the increasing use of encryption in network traffic, anomaly detection in encrypted traffic has become a challenging problem. This study proposes an approach for anomaly detection in encrypted HTTPS traffic using machine learning and compares the performance of different feature selection techniques. The proposed approach uses a dataset of HTTPS traffic and applies various machine learning models for anomaly detection. The study evaluates the performance of the models using various evaluation metrics, including accuracy, precision, recall, F1-score, and area under the curve (AUC). The results show that the proposed approach with feature selection outperforms other existing techniques for anomaly …

Towards Exchanging Wearable-Pghd With Ehrs: Developing A Standardized Information Model For Wearable-Based Patient Generated Health Data, Abdullahi Abubakar Kawu, Dympna O'Sullivan, Lucy Hederman

Articles

Wearables have become commonplace for tracking and making sense of patient lifestyle, wellbeing and health data. Most of this tracking is done by individuals outside of clinical settings, however some data from wearables may be useful in a clinical context. As such, wearables may be considered a prominent source of Patient Generated Health Data (PGHD). Studies have attempted to maximize the use of the data from wearables including integrating with Electronic Health Records (EHRs). However, usually a limited number of wearables are considered for integration and, in many cases, only one brand is investigated. In addition, we find limited studies …

Phototrophy And Carbon Fixation In Chlorobi Postdate The Rise Of Oxygen, L. M. Ward, Patrick M. Shih

Geosciences: Faculty Publications

While most productivity on the surface of the Earth today is fueled by oxygenic photosynthesis, for much of Earth history it is thought that anoxygenic photosynthesis—using compounds like ferrous iron or sulfide as electron donors—drove most global carbon fixation. Anoxygenic photosynthesis is still performed by diverse bacteria in niche environments today. Of these, the Chlorobi (formerly green sulfur bacteria) are often interpreted as being particularly ancient and are frequently proposed to have fueled the biosphere during late Archean and early Paleoproterozoic time before the rise of oxygenic photosynthesis. Here, we perform comparative genomic, phylogenetic, and molecular clock analyses to determine …

Lidar-Landsat Covariance For Predicting Canopy Fuels, Margaret D. Epstein

Graduate Student Theses, Dissertations, & Professional Papers

Managing wildfires in the western United States is becoming increasingly complex. Visualizing and quantifying canopy structures allows fire managers to both plan for fire and track recovery. Light detecting and ranging, or LiDAR can measure forests in three dimensions, but has limited spatial and temporal coverage. LiDAR-Landsat covariance uses machine learning to fill in the spatial and temporal gaps of LiDAR coverage with supplemental Landsat imagery. However, in order to capture real forest dynamics, a model needs to be stable enough to detect long term trends, sensitive to episodic disturbance, and general enough to work on multiple landcovers. The purpose …

Hydrogeomorphic Response Of Steep Streams Following Severe Wildfire In The Western Cascades, Oregon, David Matthew Busby

Graduate Student Theses, Dissertations, & Professional Papers

Severe wildfire may alter the morphologic resilience of steep mountain streams by increasing peak discharges, elevating inputs of sediment and wood into channels, and increasing susceptibility to landslides and debris flows. In the Pacific Northwest, where mean annual precipitation is high and mean fire return intervals range from decades to centuries, understanding of steep stream response to fire is limited. In 2020, the Western Cascade Range, Oregon, experienced wildfire of historic magnitude and severity. The objective of this study was to evaluate the hydrologic and geomorphic response of steep streams to the 2020 fires. I assessed streamflow, instream wood, and …

A Non-Deterministic Deep Learning Based Surrogate For Ice Sheet Modeling, Hannah Jordan

Graduate Student Theses, Dissertations, & Professional Papers

Surrogate modeling is a new and expanding field in the world of deep learning, providing a computationally inexpensive way to approximate results from computationally demanding high-fidelity simulations. Ice sheet modeling is one of these computationally expensive models, the model used in this study currently requires between 10 and 20 minutes to complete one simulation. While this process is adequate for certain applications, the ability to use sampling approaches to perform statistical inference becomes infeasible. This issue can be overcome by using a surrogate model to approximate the ice sheet model, bringing the time to produce output down to a tenth …

Development Of Nanodisc Affinity Capillary Electrophoresis To Study The Interaction Of Giα Protein With Cell Membranes, Bethany R. Emeigh

Graduate Student Theses, Dissertations, & Professional Papers

Guanine nucleotide-binding proteins, or G-proteins, are crucial to cell signaling by acting as molecular switches through interactions with membrane-bound receptors. G-proteins have become of greater interest due to the possibility of novel drug targets. The G-protein alpha subunit, Gα, binds GTP before localizing to the membrane to interact with other G-protein subunits and G-protein-coupled receptors (GPCRs). Gi lacks a hydrophobic region to promote localization to the membrane, but a co-translational lipidation of the N-terminal residue stabilizes this interaction.

Protein interactions with biological membranes are challenging to study due to the complex structure of membranes and the often-limited quantities of the …

Trading Financial Instruments Like A Video Game: Searching For Profit Using Deep Reinforcement Learning., Sebastian Coombs

Graduate Student Theses, Dissertations, & Professional Papers

Buying and selling Stocks, Foreign Currencies (FOREX), Commodities, and Cryptocurrencies have been a source of wealth generation, and more often, wealth loss for many brave enough to enter the financial markets. In this paper, the author builds on the work of Williams, J. 2022 and develops an agent-based method to solve this wealth generation problem with the use of neural networks. The author points out some assumptions made by Williams, J. 2022 that were sound in theory, but made the implementation of the algorithm presented in their paper diverge from the theory. The author proposes a fundamentally different algorithmic method, …

Development Of Regional Landslide Susceptibility Models: A First Step Towards Model Transferability, Gina M. Belair

Graduate Student Theses, Dissertations, & Professional Papers

Landslides are a globally pervasive problem with the potential to cause significant fatalities and economic losses. Although landslides are widespread, many at-risk regions may not have the high-quality data or resources used in most landslide susceptibility analyses. This study aims to develop regional susceptibility relationships that are versatile and use publicly available data and open-sourced software. Logistic Regression and Frequency Ratio susceptibility relationships were developed in 23 regions in Washington, Utah, North Carolina, and Kentucky, with a region referring to a unique area and data combination. Regions were diverse in their geology, morphology, climate, and nature and quality of their …

Voices Of The Often Unheard: The Environmental Impacts Of Catastrophic Wildfire Events On Individuals With Developmental Disabilities, Mary Madison Mckenzie

Graduate Student Theses, Dissertations, & Professional Papers

The Thomas Fire for a time was the largest wildfire in California history, burning 281,893 acres and destroying 1,063 structures. Within three years, the August Complex Fire, at 1,032,649 acres, almost quadrupled that record. Climate related disasters such as these have impelled social science researchers to heed calls for a paradigm shift in understanding the risks climate change poses to the social world, in particular, disaster risks for vulnerable groups. Existing research tends to focus on disasters such as hurricanes, featuring risks for vulnerable populations by race, class, and/or individuals with disabilities in general, but not for individuals with developmental …

1-D Crustal Seismic Velocity Models For West-Central And Western Montana, Courtenay Duzet

Graduate Student Theses, Dissertations, & Professional Papers

In seismically active areas with infrequent, large-magnitude earthquakes, high-quality seismic data are critical for determining high-resolution, accurate seismic velocity models. Here, we present a new local-scale seismic velocity model for the crust in west-central Montana as well as a new regional-scale seismic velocity model for the crust and upper mantle across broader western Montana. The new models are constrained by phase arrivals from several passive seismic networks, including the University of Montana Seismic Network (UMSN), the Montana Regional Seismic Network (MRSN), the Advanced National Seismic System (ANSS), temporary deployments by the United States Geological Survey (USGS), and the USArray Transportable …

Catch My Drift? Perceptions And Experiences Of Pesticide Contamination Of Organic Crops In Montana, Sarah Rodgers

Graduate Student Theses, Dissertations, & Professional Papers

Pesticide drift and inadvertent contamination pose particular risks to organic production. Some organic producers have lost their crops, certification, and/or organic markets because of contamination events. Through this thesis research, I explain the perceptions and experiences that certified organic farmers in Montana have about drift and inadvertent pesticide contamination. I conducted semi-structured interviews with eleven certified organic farmers from various regions of Montana. Along with one-on-one interviews with organic farmers, interviews with industry and regulatory officials were conducted to better understand the policies and procedures that control what happens when drift occurs at the state level. Industry and regulatory official …

Combined Effects Of Temperature And Heavy Metals On The Performance Of The Giant Salmonfly., James Frakes, Amanda Andreas, Benjamin P. Colman, Aurthur Woods

Graduate Student Theses, Dissertations, & Professional Papers

In many freshwater ecosystems, communities of aquatic insects are facing the combined stresses of warmer waters due to climate change and increased exposure to heavy metal toxicants. Although each stressor may threaten aquatic insects independently, they also likely interact in important ways to affect insect physiology and performance. Here we investigate this potential interaction using two populations of aquatic nymphs of the giant salmonfly, Pteronarcys californica, collected from adjacent rivers in Montana: naïve individuals from Rock Creek, a relatively pristine stream, and individuals from the Upper Clark Fork River, which has a history of heavy metal pollution and higher …

A Machine Learning Algorithm Improves Surface Freeze-Thaw Classification, Fredrick Bunt

Graduate Student Theses, Dissertations, & Professional Papers

The frozen or thawed state of the land surface is an important factor affecting a wide range of natural processes such as surface water movement, the carbon cycle, and ecosystem development. It is also important for human endeavors such as permafrost engineering and agricultural planning. This makes having an accurate record important. The Freeze-Thaw (FT) Earth System Data Record (FT-ESDR) is a global, daily product that strives to be a reliable record of the FT ground state. In its current form, the FT-ESDR uses annual regression analysis of reanalysis surface air temperatures (SAT) and brightness temperatures (Tb) at each grid …

Lasso: Listing All Subset Sums Obediently For Evaluating Unbounded Subset Sums, Christopher N. Burgoyne, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

In this study we present a novel algorithm, LASSO, for solving the unbounded and bounded subset sum problem. The LASSO algorithm was designed to solve the unbounded SSP quickly and to return all subsets summing to a target sum. As speed was the highest priority, we benchmarked the run time performance of LASSO against implementations of some common approaches to the bounded SSP, as well as the only comparable implementation for solving the unbounded SSP that we could find. In solving the bounded SSP, our algorithm had a significantly faster run time than the competing algorithms when the target sum …

Determining Spatial Controls On Snow Isotopic Signature And Tracing The Snowmelt Pulse As It Moves Through Two Montane Catchments, Jenna K. Rolle

Graduate Student Theses, Dissertations, & Professional Papers

In this study, we investigate the spatial and temporal distribution of stable isotopes of oxygen and hydrogen in water across two mountainous catchments in west-central Montana to trace the input of snow to local soil, bedrock aquifers, and streams. Snowpack and snowmelt samples were collected throughout the winter season at ten sites selected to encompass a range of elevation, aspect, slope angle and hillslope position. Soil and bedrock wells at five of the ten sites were sampled after the initial snowmelt pulse and stream samples were collected weekly at the outlets of both catchments to trace the timing and partitioning …

Sensitivity Of Lidar Derived Fuel Cells To Fire Modeling At Laboratory Scale, Anthony Albert Marcozzi

Graduate Student Theses, Dissertations, & Professional Papers

Computational models of wildfires are an important tool for fire managers and scientists. However, fuel inputs to wildfire models can be difficult to represent with sufficient detail to be both computationally efficient and representative of observations. Recent advances in fuel mapping with airborne and terrestrial laser scanning (LIDAR) techniques present new opportunities to capture variation in fuels within a tree canopy and on a landscape. In this paper, we develop a technique for building 3D representations of vegetation from point clouds created by Terrestrial Laser Scans (TLS). Our voxel based approach can be extended to represent heterogeneous crown fuels as …

Re-Modeling The Interior: Spatial Methods And Policy Revisions To Improve Inventory And Designation Of Blm’S Areas Of Critical Environmental Concern, Amy H. Katz

Graduate Student Theses, Dissertations, & Professional Papers

The Bureau of Land Management (BLM) manages a vast amount of public land in the western United States, most of which they currently manage for multiple uses. Specific conservation and management of these lands could mitigate climate change impacts and contribute to the global initiative to conserve 30 percent of lands and waters by 2030. Particularly, the agency can achieve this through more effective administration of Areas of Critical Environmental Concern (ACEC), a designation that is prioritized under the Federal Land Policy and Management Act (FLPMA). To do so requires updated regulations that set clear parameters around inventory and designation, …

Relationships Between Water, Sediment, Basal Resources, And Aquatic Insects In A Mine-Contaminated River On A Longitudinal And Habitat Patch Scale, Chelsea A. Wisotzkey

Graduate Student Theses, Dissertations, & Professional Papers

It is well established that aqueous exposure and dietary exposure both lead to the accumulation of metals and metalloids in aquatic organisms living in a contaminated environment, but the relative contribution of each remains unclear. To examine how a contamination gradient affects patterns of metal(loid)s among periphyton, BPOM (benthic particulate organic matter), water, and sediment, we collected samples from multiple sites across a 210km stretch of the mine-contaminated Upper Clark Fork River, Montana. To investigate metal(loid) accumulation patterns among basal resources and aquatic insects, we collected samples of periphyton, BPOM, and larval insects from discrete habitat types at a single …

Causes And Consquences Of Fire In Forest Ecosystems Of The Selway-Bitterroot Wilderness, Melissa Jaffe

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

Factors Affecting The Production Of Berries Of The Red Huckleberry Plant In The Redwood Experimental Forest, Kagat G. Mcquillen

Cal Poly Humboldt theses and projects

Vaccinium parvifolium (red huckleberry) is a culturally and commercially valued food for different coastal tribes of northwestern California.

Today some tribes are regaining access to ancestral lands, and Indigenous researchers are working to document information about culturally significant plant species and their management to reclaim traditional ecological knowledge and restore food sovereignty.

The present study, focused on red huckleberry, Vaccinium parvifolium, took place in the ancestral territory of the Yurok Tribe, currently managed by the US Forest Service as the Redwood Experimental Forest (REF) in Klamath, CA. Geographic Information Systems-based mapping, forest ecological field data collection, and a literature …

Assessing Soil Disturbance From Tethered Logging On Steep Slopes In Northern California, Karolyn Marie Fagundes

Cal Poly Humboldt theses and projects

The implementation of tethered harvesting allows for the expansion of mechanized logging onto steeper slopes. Recent updates to the California Forest Practice Rules have explicitly removed the slope limitation for logging equipment, provided it’s tethered. California is now witnessing the reintroduction of ground-based logging equipment on steep slopes. Previously, operating equipment on steep slopes was considered detrimental due to the potential for soil disturbance. However, tethered equipment interacts with the soil in a new way due to the use of a winch. Relatively few studies have attempted to quantify soil disturbance with this new practice. The goal of this study …

Sediment Production From Forest Roads In Areas Affected By The August Complex Fire In Northern California, Zachary J. Gigone

Cal Poly Humboldt theses and projects

Wildfire activity is increasing in California and is an important factor affecting erosion rates. Landscapes recently affected by wildfire, areas that have been salvage logged after a fire, and unpaved forest roads are all major sources of sediment which can impair water quality and negatively impact many aquatic species. Therefore, this study was conducted to quantify erosion rates from native and gravel surfaced forest road segments after the August Complex fire, evaluate the impact of salvage logging activities on sediment production from roads, and understand the effect of soil burn severity on sediment production from these road segments. Finally, this …