Physical Sciences and Mathematics Commons^™

Predictable Differences In Surface Soil Organic Carbon Storage Across Landcover Types Around Ísafjörður, Iceland, Tess Mooney

Iceland: Climate Change and The Arctic

It is unclear how soil carbon varies by landcover type in areas with discontinuous and heterogenous vegetation cover in the Icelandic subarctic. Understanding which landcover types store the most C is important for understanding regional surface C inventory and for making decisions about optimal land use for C sequestration and storage. This study investigates the differences in soil C storage between different vegetation cover types in the Westfjords of northwestern Iceland. The three dominant landcover types in the Westfjords include heathlands, wetlands, and unvegetated areas. When compared across these three landcover types, surface soil C, bulk density, and soil moisture …

Immigrant Integration In Akureyri, Iceland: Identifying Ways To Cultivate A ‘Sense Of Belonging,’ From The Perspective Of Foreigners, Eliana Goldstein

Iceland: Climate Change and The Arctic

Iceland has experienced significant demographic changes since the 1990s. As climate change intensifies, raising the global temperature, migration to cooler climates such as Iceland will increase. To minimize ‘othering’ and rhetoric conducive to anti-immigrant environments, Iceland must work on integration issues, especially while opportunities and perceptions of other groups are still manageable. Through a series of interviews and discussions with foreigners in Akureyri and a focus group with employees from the University Centre of the Westfjords, integration was defined as a ‘sense of belonging’ and the ability to communicate with the native majority. To aid integration, this study identified a …

Assessing Geospatial Modeling In Determining Optimal Afforestation Locations For Carbon Sequestration In The Isafjord Region, Kyle Pellerin

Iceland: Climate Change and The Arctic

Iceland was once a country with large forests that covered over a third of the island's total landmass. Over the course of the past thousand years of settlement, the percentage of the country covered in forest dwindled, at some points dropping to less than one percent. Based on this deforestation history, and the potential of reforesting the land to help reduce the impact of carbon emissions, afforestation efforts in Iceland have been underway for the better half of a century. Despite the many years of effort, a lack of data and mapping exists on ideal planting locations, and the factors …

Estimating “Peak Water” Runoff And Power Production For Hydropower-Relevant Icelandic Glaciers Under Future Climate Scenarios, Anna Geldert

Iceland: Climate Change and The Arctic

Glaciers are important water resources in Iceland, in part because glacial runoff powers the country’s largest hydropower stations, which produce a large portion of the nation’s electricity. However, glaciers around Iceland are retreated at unprecedented rates due to climate change and are projected to continue to do so over the course of the 21st century. Glacial retreat plays a complex role in the water cycle, most often following a “peak water” curve marked by initial increases in total annual runoff as melt accelerates followed by eventual declines as the glacier continues to shrink. This holds important implications for the hydropower …

Modeling Permittivity Measurements Of Thin Film Materials Versus Film Thickness, Jr Dennison, Cameron Eggleston

Journal Articles

Measured permittivity of thin film polymeric samples were substantially less for thin samples, asymptotically approaching bulk values above ~500 μm. For ~25 μm samples the observed permittivities were as much as 50% less than for bulk measurements. This behavior has been studied for four common homogeneous polymeric materials for sample thickness in the range of ~10 μm to > 1000 μm. To quantify these observations, an empirical single-parameter model was developed to correct measured permittivity of thin samples based on an effective stray capacitance in series with the samples to compensate for effects attributed to instrumentation.

Applying Data-Limited Assessment Methods To Charter Logbook Length Data, Brett Crisafulli, Sybrand Alex Hesp, David Fairclough, Emily A. Fisher, Paul D. Lewis, Jeffrey V. Norriss, Corey B. Wakefield, Fabian Trinnie, Stephen J. Newman

Fisheries Research Reports

Marine waters along the Western Australian coastline are characterised by low ecosystem productivity and high species diversity of fishes. With over 3,000 known species comprising estuarine, nearshore, demersal and pelagic fishes in the region, many contribute to important commercial and recreational fisheries (Lenanton et al. 1991; Molony et al. 2011; Newman et al. 2018). As it is logistically and economically infeasible to conduct intensive monitoring and high-level stock assessments of all exploited fish species in Western Australia, indicator species are used to assess the sustainability of suites of species of biological and ecological similarity, for optimal use of available resources …

Using Machine Learning To Predict State Compliance With International Legal Obligations For Registration Of Space Objects: Comparative Performance Of Logistic Regression And Dense Neural Network Models, Jonathan K. Sawmiller

Student Publications

Approximately 12% of satellites and other objects launched into outer space have not been registered with the United Nations (UN) as required by international law. To predict whether States will register a launched space object and understand what factors influence a registration decision, data from a UN online index of space objects was used to train and select the best machine learning model. After preparation, the dataset had 1938 datapoints with 11 features, with categorical features simplified and converted to binary.

Multiple variations of classical logistic regression models were compared to multiple variations of dense neural network models. The best …

A Study On The Polarity Of Generalized Neutrosophic Ideals In Bck-Algebra, Bavanari Satyanarayana, Shake Baji

Neutrosophic Systems with Applications

In this study, we apply k-polar generalized neutrosophic logic to the ideal of BCK-algebra and consequently introduce the notion of a k-polar generalized neutrosophic ideal in BCK-algebra with an example. We provide conditions for a k-polar generalized neutrosophic set to be a k-polar generalized neutrosophic ideal. We prove that every k-polar generalized neutrosophic ideal is a k-polar generalized neutrosophic subalgebra, but the converse is not true, which can be illustrated with an example. Furthermore, we prove that a k-polar generalized neutrosophic set is a k-polar generalized neutrosophic ideal if and only if its corresponding cut sets are ideals of the …

Unveiling Similarities In The Code Of Life: A Detailed Exploration Of Dna Sequence Matching Algorithm, Mahmoud Y. Shams, Romany M. Farag, Dalia A. Aldawody, Huda E. Khalid, Ahmed K. Essa, Hazem M. El-Bakry, A. A. Salama

Neutrosophic Systems with Applications

Identifying similar DNA sequences is crucial in various biological research endeavors. This paper delves into the intricate workings of a specific algorithm designed for this purpose. We provide a systematic explanation, exploring how the algorithm handles user input, reads stored DNA sequences, utilizes the Word2Vec model for vector representation, and calculates sequence similarity using diverse metrics like Cosine Similarity and Neutrosophic Distance. Additionally, the paper explores the incorporation of neutrosophic values to account for uncertainty in the comparisons. Finally, we discuss the extraction of results, including matched sequences, similarity scores, and accuracy measures. This in-depth exploration provides a clear understanding …

Evaluation Of Renewable Energy Sources For A Sustainable Future: A Multi-Criteria Decision-Making Approach, Mai Mohamed, Asmaa Elsayed

Neutrosophic Systems with Applications

The urgent global challenges of climate change, energy security, and environmental degradation highlight the need for sustainable energy solutions. Renewable energy sources (RES) present a viable pathway towards sustainability by mitigating greenhouse gas emissions, reducing reliance on fossil fuels, and fostering economic resilience. Purpose: The purpose of this paper is to propose an advanced Multi-Criteria Decision-Making (MCDM) approach to evaluate various RES by integrating environmental, economic, technological, social acceptance, and resource availability criteria, to identify the most suitable RES for sustainable energy solutions. Methodology: The study employs a hybrid method combining Type-2 Neutrosophic Numbers (T2NN) with LOPCOW (Logarithmic Percentage Change …

Neutrosophic Approach To Water Quality Assessment: A Case Study Of Gomati River, The Largest River In Tripura, India, Ajoy Kanti Das, Nandini Gupta, Carlos Granados, Rakhal Das, Suman Das

Neutrosophic Systems with Applications

This study addresses the complexity of assessing river water quality, a multifaceted process influenced by numerous water quality parameters (WQPs) characterized by inherent uncertainties and diverse judgment information from decision-makers. These uncertainties and diverse judgment information can be effectively represented and simulated using Neutrosophic sets. In this study, we propose an effective water pollution rating system, the Neutrosophic water quality index (NWQI), to derive a water pollution score (NWQI-score) for rating water pollution levels. We demonstrate the application of our methodology through an assessment of water quality indices for rating pollution in the Gomati River, the largest river in Tripura, …

An Approach To Multi-Attribute Decision-Making Based On Single-Valued Neutrosophic Hesitant Fuzzy Aczel-Alsina Aggregation Operator, Raiha Imran, Kifayat Ullah, Zeeshan Ali, Maria Akram

Neutrosophic Systems with Applications

A single-valued Neutrosophic hesitant fuzzy set (SVNHFS) is a combination of a single-valued neutrosophic set (SVNS) and hesitant fuzzy set (HFS) that has been developed to address insufficient, unreliable, and vague environments in which each element has several possible options determined by the truthiness, indeterminacy and falsity value. By considering this, in this paper, we have proposed the Aczel-Alsina aggregation operator (AAAO) for SVNHFS, which is more flexible t-norm and t-conorm than the other and due to the flexible nature of parameters to solve Multi-Attribute decision making (MADM) problems. Further, the score function, accuracy function, and certainty function of SVNHFS …

Water Quality Of The Napo River Basin: A Comparative Study Of Streams In Polycultures And Oil Palm Monocultures, Eva C. Andersen

Ecuador: Comparative Ecology and Conservation

Oil palm cultivation has grown rapidly in recent years in Ecuador, resulting in significant economic and environmental changes to the country. In the Northeast Ecuadorian Amazon, a hotspot for both petroleum extraction and oil palm production, poor water quality has been a persistent issue for decades. However, knowledge gaps exist regarding to what extent intensive monocultures, such as oil palm, contribute to poor water quality in this region, and how they compare to other forms of agriculture. This investigation compared water quality in streams of the Napo River watershed running through oil palm monocultures and traditional polycultures. Water quality was …

The Psychological Impacts Of Algorithmic And Ai-Driven Social Media On Teenagers: A Call To Action, Sunil Arora, Sahil Arora, John Hastings

Research & Publications

This study investigates the meta-issues surrounding social media, which, while theoretically designed to enhance social interactions and improve our social lives by facilitating the sharing of personal experiences and life events, often results in adverse psychological impacts. Our investigation reveals a paradoxical outcome: rather than fostering closer relationships and improving social lives, the algorithms and structures that underlie social media platforms inadvertently contribute to a profound psychological impact on individuals, influencing them in unforeseen ways. This phenomenon is particularly pronounced among teenagers, who are disproportionately affected by curated online personas, peer pressure to present a perfect digital image, and the …

Transforming Information Systems Management: A Reference Model For Digital Engineering Integration, John Bonar, John Hastings

Research & Publications

Digital engineering practices offer significant yet underutilized potential for improving information assurance and system lifecycle management. This paper examines how capabilities like model-based engineering, digital threads, and integrated product lifecycles can address gaps in prevailing frameworks. A reference model demonstrates applying digital engineering techniques to a reference information system, exhibiting enhanced traceability, risk visibility, accuracy, and integration. The model links strategic needs to requirements and architecture while reusing authoritative elements across views. Analysis of the model shows digital engineering closes gaps in compliance, monitoring, change management, and risk assessment. Findings indicate purposeful digital engineering adoption could transform cybersecurity, operations, service …

Confronting The Reproducibility Crisis: A Case Study Of Challenges In Cybersecurity Ai, Richard H. Moulton, Gary A. Mccully, John D. Hastings

Research & Publications

In the rapidly evolving field of cybersecurity, ensuring the reproducibility of AI-driven research is critical to maintaining the reliability and integrity of security systems. This paper addresses the reproducibility crisis within the domain of adversarial robustness—a key area in AI-based cybersecurity that focuses on defending deep neural networks against malicious perturbations. Through a detailed case study, we attempt to validate results from prior work on certified robustness using the VeriGauge toolkit, revealing significant challenges due to software and hardware incompatibilities, version conflicts, and obsolescence. Our findings underscore the urgent need for standardized methodologies, containerization, and comprehensive documentation to ensure the …

Setc: A Vulnerability Telemetry Collection Framework, Ryan Holeman, John Hastings, Varghese Mathew Vaidyan

Research & Publications

As emerging software vulnerabilities continuously threaten enterprises and Internet services, there is a critical need for improved security research capabilities. This paper introduces the Security Exploit Telemetry Collection (SETC) framework - an automated framework to generate reproducible vulnerability exploit data at scale for robust defensive security research. SETC deploys configurable environments to execute and record rich telemetry of vulnerability exploits within isolated containers. Exploits, vulnerable services, monitoring tools, and logging pipelines are defined via modular JSON configurations and deployed on demand. Compared to current manual processes, SETC enables automated, customizable, and repeatable vulnerability testing to produce diverse security telemetry. This …

Network Analysis Of Virginia’S Mineralogical Systems, Cadence M. Boucher, Ahmed M. Eleish, Robert M. Hazen, Shaunna M. Morrison

Virginia Journal of Science

The principal objective of this study was to use network analysis to identify spatial, geomorphic, physical, and chemical patterns in Virginia’s mineralogical systems. Mineralogical and locality data from mindat.org were visualized as a bipartite force- directed network of the minerals and the counties of Virginia in which they occur. Mineral nodes were sized to represent the number of counties the minerals are found in (i.e., frequency of occurrence) and county nodes were sized to represent the number of minerals found in that county (i.e., mineral diversity). Furthermore, the nodes were colored to display selected attributes of the mineral-county data. County …

Electrochemistry At Work: Bouncing Batteries, Bryant Corbin, James Daniel, Jade Riddle

Fall Showcase for Research and Creative Inquiry

No abstract provided.

2024 Celebration Of Scholarship, Creativity, And Engagement, Todd Bruns, Anna Nelson

Programs

Annually, Eastern Illinois University honors faculty achievements in the areas of research, creativity, and engagement. The list of faculty accomplishments is truly impressive, reflective of an engaged faculty committed to excellence and the ongoing pursuit and creation of knowledge. Many of these accomplishments occurred in collaboration with our students, who serve as co-authors, research assistants and partners in bringing these activities to fruition. In some cases, these professional ambitions transpired over many years and are a testament to persistence and tenacity. We extend a sincere message of congratulations for this diverse range of achievements, which bring distinction to our departments, …

Weed Seed Wizard Case Study - Don't Stop Harvest Weed Management Because It’S A Dry Year, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

• applies to all Australian grain growing areas

• helps growers understand and manage weed seedbanks on their farms

• uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields

• uses farm-specific management and site-specific weather

• is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This case …

Measuring The Misplacement Of Data From Multidimensional Scaling, Lucy Liu

Holster Scholar Projects

Multidimensional scaling (MDS), in which high-dimensional data is projected to a lower dimensional map, is often followed by clustering in the reduced plot. To examine the effect of MDS on clustering, we simulate several data structures and apply clustering methods, including topological data analysis. We first perform clustering using the data in the original, high-dimensional space, then perform MDS to scale the data down to a lower dimension, cluster on this scaled data, and compare differences in the results. We found that MDS can often decrease clustering performance, and is unable to correctly represent data structures with unique shapes or …

Two Is Enough, But Three (Or More) Is Better: In Ai And Beyond, Olga Kosheleva, Vladik Kreinovich, Victor L. Timchenko, Yury P. Kondratenko

Departmental Technical Reports (CS)

At present, the most successful AI technique is deep learning -- the use of neural networks that consist of multiple layers. Interestingly, it is well known that neural networks with two data processing layers are sufficient -- in the sense that they can approximate any function with any given accuracy. Because of this, until reasonably recently, researchers and practitioners used such networks. However, recently it turned out, somewhat unexpectedly, that using three or more data processing layers -- i.e., using what is called deep learning -- makes the neural networks much more efficient. In this paper, on numerous examples from …

Assessing Synergy With Curcumin & 5-Fu In Breast Cancer, Sa'maira L. Davis, Zeen Ari, Andrea Florian

Science University Research Symposium (SURS)

One in eight women in the United States will be diagnosed with breast cancer in their lifetime. 5-Fluorouracil (5-FU) is the most common chemotherapy drug used to treat breast cancer. As an antimetabolite, 5-FU interferes with cancer cells' ability to replicate DNA, ultimately targeting and killing these cells prior to division. However, 5-FU alone has limitations due to its high toxicity and propensity to induce multidrug resistance. To enhance its efficacy, 5-FU was combined with curcumin, a compound derived from turmeric that has shown potential in reducing cancer cell proliferation. A single-dose response curve, a Singer assay, and western blot …

Decomposition Rates Between Monocotyledon And Dicotyledon Plant Species In A Green Roof Setting, Roma C. Brassell, Sa'maira Davis, Molly Kiwan, Grace Adams, Darlene Panvini

Science University Research Symposium (SURS)

Decomposition is a vital part of ecological regulation that goes hand in hand with nutrient recycling. In this study, an experiment was performed to research the leaf litter decomposition rates between two plants - a monocotyledon, Allium schoenoprasum (Chives), and a dicotyledon, Acalypha virginica var rhomboidei (Virginia Three-seed Mercury), on the Belmont green roofs. Eight litter bags of each plant species were placed on the green roof close to each other and strung together in four bag samples. For four three-week periods, the litter bags containing Chives and Virginia Three-seed Mercury were collected, two bags per species at a time, …

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft 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.

Measurement And Prediction Of Transit System Performance Using Probe Data Generated Through Dsrc And Non-Dsrc Technologies, Gregory L. Newmark

Mineta Transportation Institute

This research explores the application of two different probe data standards to transit performance measurement. The first section chronicles the proposed and implemented transit uses of dedicated short-range communication (DSRC) technologies during the two decades between the standard’s emergence and its announced sunset. The research finds that, despite proposed applications across safety, operation, and information domains, DSRC never became embedded in transit operations. By contrast, the general transit feed specification (GTFS) standard with its real-time (RT) extension has been widely embraced and offers the potential to use the associated VehiclePosition messages as probe data to generate detailed transit performance metrics. …

Exploring The Roles Of Genetics, Gender, Nurturing, And Learning Methods In Mathematical Skills Development, Laura Alinani, Jana Shyti

Honors Projects

This research explores the multifaceted factors influencing the development of mathematical competence through a combination of cognitive, psychological, and sociocultural frameworks. The study aims to address how genetic predispositions, nurturing environments, teaching methods, and societal influences interact to shape mathematical abilities. Using insights from genetic research, cognitive psychology, and education theory, we analyze the role of effective teaching methods, such as active knowledge construction and differentiated instruction, in fostering mathematical skills. The study also examines how societal biases, particularly gender stereotypes, impact students' confidence and interest in math. The findings highlight the importance of promoting gender-inclusive practices and early exposure …

Climate Prediction Center Analogs As Extended Range Predictors For Severe Convective Storms, Sean Phipps

Honors Capstones

Increasing the predictability of severe convective storms (SCSs) over extended time ranges (i. e. >8 days) is of utmost importance to forecasters, as modern numerical weather prediction (NWP) models exhibit little skill at this lead time. Analogs have been used to predict temperature and rainfall anomalies at this time range for decades, though modern developments in analog forecasting uses techniques such as analog ensembles to increase the skill of analog models. This study employs a simple analog ensemble (AnEn) method using the Climate Prediction Center (CPC) 6-10 Day 500hPa analogs and uses the Storm Prediction Center (SPC)’s report database to …

Reducing Selection Bias In The Training Data Of Asl Champ! To Improve The Sign Language Recognition (Slr) System, Nushla Pradhan '26, Laine Silverman

Annual Student Research Poster Session

American Sign Language (ASL) is a natural language that is critical for effective communication within the Deaf community and also to bridge the gap between hearing and Deaf or Hard-of-Hearing individuals. Conventional methods of ASL learning apart from in person classroom instruction provide foundational knowledge but often lack the immersive and interactive elements. People often opt to learn ASL through textbooks and videos due to the limited availability of proficient ASL instructors, lack of other educational resources and limited time. This creates challenges of replicating real-life conversational scenarios and lack of real time feedback. To address these limitations, Virtual Reality …