Physical Sciences and Mathematics Commons^™

Mitigating Cyber Espionage: A Network Security Strategy Using Notifications, Claire Headland

Williams Honors College, Honors Research Projects

Network security and its mitigation of cyber espionage is paramount to the confidentiality, integrity, and availability of data within the intelligence field. With the advancing efficacy of social engineering to execute cyber espionage attacks, further measures and fail-safe mechanisms have become necessary. If a malicious actor successfully penetrates the network, suspending confidential data transmissions over the compromised network becomes crucial. However, connected users need a platform to receive security notifications and, therefore, need to know that their continued network use compromises more data. This project eliminates this by achieving two primary objectives: designing a multi- layered, hardened, and segmented network …

Statistical Modeling Of Bankruptcy Data, Andrew Elsfelder

Williams Honors College, Honors Research Projects

My project uses a dataset of bankrupt and non-bankrupt companies in Taiwan from 1999 to 2009. This data was collected from the Taiwan Economic Journal. The statistical methods I used to model the data are CHAID, CART, and logistic regression. The models created are tools that can predict if a company is bankrupt, or not-bankrupt based on other data about the company. I created multiple models for each of the methods to find the best model for each method. I then analyzed the output from each method. Lastly, I determined which model was the best for this data based on …

Forensic Archaeology Protocols For Wildfires And Fire Related Scenes, Erik Schulz

Nebraska Anthropologist

Forensic Archaeology Protocols for Wildfires and Fire-Related Scenes

Forensic archaeology is a relatively new area of study and focuses on the medical legal aspects of archaeology. This paper will focus on how forensic archaeology should be used for wildfire and other fire-related fatalities or investigations, what happens to bone when exposed to heat, what protocols should be in place and how an excavation should look, and finally the challenges of fire-related investigations. This report will focus on the larger scale of the investigation and will be using several sources from different wildfire and fire fatality reports.

Modeling Health Insurance Premium Using Bayesian Hierarchical Models, Bennedict Kongyir, Emil Agbemade

Data Science and Data Mining

Insurance pricing requires pragmatism and creativity due to the unpredictable nature of risk [3]. This paper explores Bayesian hierarchical models to model health insurance premiums using individual and group predictors like demographics, health status, and geography. Data from Kaggle on health insurance policyholders was utilized, with prior distributions enhanc­ing model interpretability and credibility. Bayesian models improve predictive accuracy and provide valuable insights for actuaries and policymakers, highlighting the signifcant impact of factors such as age and BMI on premium pricing.

Advancements In Glitch Subtraction Systems For Enhancing Gravitational Wave Data Analysis: A Brief Review, Mohammad Abu Thaher Chowdhury

Physics and Astronomy Faculty Publications and Presentations

Glitches are transitory noise artifacts that degrade the detection sensitivity and accuracy of interferometric observatories such as LIGO and Virgo in gravitational wave astronomy. Reliable glitch subtraction techniques are essential for separating genuine gravitational wave signals from background noise and improving the accuracy of astrophysical investigations. This review study summarizes the main glitch subtraction methods used in the industry. We talk about the efficacy of classic time-domain techniques in real-time applications, like matched filtering and regression methods. The robustness of frequency-domain approaches, such as wavelet transformations and spectral analysis, in detecting and mitigating non-stationary glitches is assessed. We also investigate …

Extraction Of Capsaicin Using The Polyol Induced Extraction (Pie) Method, Orlando Herrera

All Student Theses and Dissertations

Polyol-induced extraction (PIE) is an extraction technique for separating organic solvents from water, using glycerol and polyol as separating agents. Glycerol binds water releasing the organic solvent as a separate liquid phase. this thesis, investigates how the PIE process may be used to separate caffeine and capsaicin. When acetonitrile and water are used as a 1:1 solvent mixture, two immiscible phases are created upon addition of the polyol, glycerol. Initially, for purposes of training on the PIE method, the studies primarly began with the extraction of pure caffeine. Using a 1:1 mixture of acetonitrile and water, 20 m/v % glycerol, …

Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang

Civil & Environmental Engineering Faculty Publications

Sites located in the Sacramento-San Joaquin Delta region of California typically have peaty-organic soils near the ground surface, which are characteristically soft, with shear wave velocities as low as 30 m/s. These unusually soft geotechnical conditions, which are outside the range of applicability of existing ergodic site amplification models, can be anticipated to produce significant site effects during earthquake shaking. We evaluate site response for 36 seismic stations in the Delta region using non-ergodic methods with low-amplitude ground motion data. We model first-order site effects using a period-dependent relation conditioned on the 30 m time-averaged shear wave velocity (V …

A Review Of Hybrid Cyber Threats Modelling And Detection Using Artificial Intelligence In Iiot, Yifan Liu, Shancang Li, Xinheng Wang, Li Xu

Information Technology & Decision Sciences Faculty Publications

The Industrial Internet of Things (IIoT) has brought numerous benefits, such as improved efficiency, smart analytics, and increased automation. However, it also exposes connected devices, users, applications, and data generated to cyber security threats that need to be addressed. This work investigates hybrid cyber threats (HCTs), which are now working on an entirely new level with the increasingly adopted IIoT. This work focuses on emerging methods to model, detect, and defend against hybrid cyber attacks using machine learning (ML) techniques. Specifically, a novel ML-based HCT modelling and analysis framework was proposed, in which regularisation and Random Forest …

Characterizing Climatic Socio-Environmental Tipping Points In Coastal Communities: A Conceptual Framework For Research And Practice, Julie Elizabeth Shortridge, Anamaria Bukvic, Molly Mitchell, Jesse Goldstein, Tom Allen

Political Science & Geography Faculty Publications

The concept of climate tipping points in socio-environmental systems is increasingly being used to describe nonlinear climate change impacts and encourage social transformations in response to climate change. However, the processes that lead to these tipping points and their impacts are highly complex and deeply uncertain. This is due to numerous interacting environmental and societal system components, constant system evolution, and uncertainty in the relationships between events and their consequences. In the face of this complexity and uncertainty, this research presents a conceptual framework that describes systemic processes that could lead to tipping points socio-environmental systems, with a focus on …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

A Benchmark Framework For Data Visualization And Explainable Ai (Xai), Murat Kuzlu, Gokcen Ozdemir, Umut Ozdemir

Engineering Technology Faculty Publications

This research introduces a benchmark framework, called EDUMX, designed for machine learning (ML)- based forecasting and XAI tasks, leveraging the Streamlit open-source Python library. The framework offers a comprehensive suite of functionalities, including data loading, feature selection, relationship analysis, data preprocessing, model selection, metric evaluation, training, and real-time monitoring. Users can easily upload data in diverse formats, explore relationships between variables, preprocess data using various techniques, and assess the performance of the ML model using customizable metrics. With its user-friendly interface, this framework offers invaluable insights for forecasting tasks in various domains, catering to the evolving needs of predictive analytics. …

Targeting Ocean Conservation Outcomes Through Threat Reduction, Joseph A. Turner, Malcolm Starkey, Nicholas K. Dulvy, Frank Hawkins, Louise Mair, Adeline Serckx, Thomas Brooks, Beth Polidoro, Stuart H. M. Butchart, Kent Carpenter, Minna Epps, Rima W. Jabado, Nicholas B. W. Macfarlane, Leon Bennun

Biological Sciences Faculty Publications

Nations have committed to reductions in the global rate of species extinctions through the Sustainable Development Goals 14 and 15, for ocean and terrestrial species, respectively. Biodiversity loss is worsening despite rapid growth in the number and extent of protected areas, both at sea and on land. Resolving this requires targeting the locations and actions that will deliver positive conservation outcomes for biodiversity. The Species Threat Abatement and Restoration (STAR) metric, developed by a consortium of experts, quantifies the contributions that abating threats and restoring habitats in specific places offer towards reducing extinction risk based on the IUCN Red List …

Beach Erosion And Recovery Since Hurricane Ivan In 2004 Along A Headland-Bay Coast In Treasure Beach, Jamaica, Elandé Engelbrecht

MSU Graduate Theses

Anthropogenic climate change is causing sea-level rise and shoreline changes that threaten the environment and economy of coastal communities in Caribbean Island nations. To assess this risk, this study quantifies shoreline changes at Treasure Beach in St. Elizabeth Parish on the south coast of Jamaica from 2001 to 2023. The effects of storm events on erosion were also assessed. Over 10 km of shoreline are assessed with about half being sandy pocket beaches ranging from 300 to 900 m in length, separated by rocky headlands and beach rock outcrops. Sand beach erosion trends since 2001 are assessed for seven sandy …

Phase Dependence Of Kerr-Based Parametric Amplification, Nathan G. Drouillard, Tj Hammond

Physics Publications

Kerr instability amplification can amplify over an octave of spectrum, a broad bandwidth supporting few-cycle pulses. However, dispersion management in this regime is crucial, and we explore the parameters required to maintain the ultrashort pulse undergoing amplification. At low pump intensities, we experimentally observe an interference between the strongly chirped supercontinuum seed and weakly amplified pulse, reproduced in our model by manipulating the seed dispersion. Extending our model to cases of high gain, our simulation predicts the dispersion is near zero, and the phase can be compensated preamplification to generate near-transform-limited amplified few-cycle pulses.We discuss chirping the seed pulse to …

Supercontinuum Amplification By Kerr Instability, Sagnik Ghosh, Nathan G. Drouillard, Tj Hammond

Physics Publications

The versatility of optical parametric amplifiers makes them excellent sources for ultrashort visible and infrared pulses that drive strong-field physics experiments. We extend four-wave optical parametric amplification to the strong-field regime, known as Kerr instability amplification, and experimentally verify the modified noncollinear conditions for optimum amplification. We confirm that Kerr instability amplification can be used to amplify spectra that span nearly an octave in a single beam. We also amplify the near-infrared portion of the spectrum to generate the third harmonic downstream.

From Normal Distribution To What? How To Best Describe Distributions With Known Skewness, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we only have partial information about the probability distribution -- e.g., all we know is its few moments. In such situations, it is desirable to select one of the possible probability distributions. A natural way to select a distribution from a given class of distributions is the maximum entropy approach. For the case when we know the first two moments, this approach selects the normal distribution. However, when we also know the third central moment -- corresponding to skewness -- a direct application of this approach does not work. Instead, practitioners use several heuristic techniques, techniques …

Integrating Climatological-Hydrodynamic Modeling And Paleohurricane Records To Assess Storm Surge Risk, Amirhosein Begmohammadi, Christine Y. Blackshaw, Ning Lin, Avantika Gori, Elizabeth Wallace, Kerry Emanuel, Jeffrey P. Donnelly

OES Faculty Publications

Sediment cores from blue holes have emerged as a promising tool for extending the record of long-term tropical cyclone (TC) activity. However, interpreting this archive is challenging because storm surge depends on many parameters including TC intensity, track, and size. In this study, we use climatological-hydrodynamic modeling to interpret paleohurricane sediment records between 1851 and 2016 and assess the storm surge risk for Long Island in The Bahamas. As the historical TC data from 1988 to 2016 is too limited to estimate the surge risk for this area, we use historical event attribution in paleorecords paired with synthetic storm modeling …

Nsea Community Program Intern, Payton M. Bovee

College of the Environment Internship Reports

The community program internship was designed to support NSEA’s program team by facilitating community and student opportunities to engage with salmon and restoration activities throughout Whatcom County. The goal is to provide Whatcom County residents with hands-on experience in restoration and the tools/knowledge to act as stewards of salmon habitat. This is accomplished through several outreach opportunities including NSEA’s Students for Salmon program, community work parties, Salmon Club, and salmon sighting events.

Applying The Disaster Risk Assessment Framework To Sargassum Inundation In Barbados, A. Karima Degia, Micaela Small, Hazel A. Oxenford

Gulf and Caribbean Research

Episodic influxes of pelagic Sargassum into the Caribbean result in inundation of coastlines with significant negative impacts to the environment, society, and economy. The spatial complexities of this issue demand a strategy that combines spatial planning with an analytical framework that can systematically unpack the underlying factors to inform effective management. We test the application of the United Nations Disaster Risk Reduction (UNDRR) conceptual framework for disaster risk assessment to Sargassum inundation, with a focus on the hazard and exposure components of risk, using Barbados, a Caribbean Small Island Developing State (SIDS), as a case study. We first consider in …

Editorial: The Marine Iodine Cycle, Past, Present, And Future, Rosie Chance, Gregory A. Cutter, Dalton S. Hardisty, Anoop S. Mahajan

OES Faculty Publications

In this Research Topic, we bring together ten articles from the diverse research communities interested in the marine iodine cycle, including paleoceanographers, atmospheric chemists, and biogeochemists. The physical chemistry underpinning iodine’s chemical speciation and transformations in the ocean is reviewed by Luther; this paper provides a theoretical basis for the field observations presented in this Research Topic.

Intercalibration: A Cornerstone Of The Success Of The Geotraces Program, Ana Aguilar-Islas, Hélène Planquette, Maeve C. Lohan, Walter Geibert, Gregory Cutter

OES Faculty Publications

The international GEOTRACES program was developed to enhance knowledge about the distribution of trace elements and their isotopes (TEIs) in the ocean and to reduce the uncertainty about their sources, sinks, and internal cycling. Recognizing the importance of intercalibration from the outset, GEOTRACES implemented intercalibration efforts early in the program, and consensus materials were generated that included the full range of TEIs dissolved in seawater, in suspended particles, and from aerosols. The GEOTRACES section cruises include “crossover station(s)” that are occupied by two or more sections and whereby all aspects of sample collection, preservation, and processing can be compared and …

Assessing The Spatiotemporal Variability Of Dissolved Organic Matter Fluorescence Composition In The Lake George, Ny Watershed, Aleksandar I. Goranov, Mark W. Swinton, David A. Winkler, Jeremy L. Farrell, Sandra A. Nierzwicki-Bauer, Sasha Wagner

Chemistry & Biochemistry Faculty Publications

Lake George (LG) is a temperate, oligotrophic, medium-sized lake (114 km²) located in northeastern New York State (U.S.). Lakes are highly understudied environments where extensive dissolved organic matter (DOM) processing occurs. With this study we establish the foundation for researching the organic biogeochemistry of the LG watershed, in particular, the numerous tributaries flowing into the lake. Collected were 213 samples from 64 tributaries and 12 lake locations. Some of the tributaries had unique wastewater, agricultural, or wetland influences. We employed fluorescence spectroscopy, a common biogeochemical technique, to characterize the fluorescent DOM (FDOM) component. We developed a parallel factor …

Green Oxidation Of Aromatic Hydrazide Derivatives Using An Oxoammonium Salt, Nidheesh Phadnis, Jessica A. Molen, Shannon M. Stephens, Shayne M. Weierbach, Kyle M. Lambert, John A. Milligan

Chemistry & Biochemistry Faculty Publications

Aromatic diazenes are often prepared by oxidation of the corresponding hydrazides using stoichiometric quantities of nonrecyclable oxidants. We developed a convenient alternative protocol for the oxidation of aromatic hydrazides using Bobbitt's salt (1), a metal-free, recyclable, and commercially available oxoammonium reagent. A variety of aryl hydrazides were oxidized within 75 min at room temperature using the developed protocol. Computational insight suggests that this oxidation occurs by a polar hydride transfer mechanism.

Complex Dynamics Of Coral Gene Expression Responses To Low Ph Across Species, Veronica Z. Radice, Ana Martinez, Adina Paytan, Donald C. Potts, Daniel J. Barshis

Biological Sciences Faculty Publications

Coral capacity to tolerate low pH affects coral community composition and, ultimately, reef ecosystem function. Low pH submarine discharges (‘Ojo’; Yucatán, México) represent a natural laboratory to study plasticity and acclimatization to low pH in relation to ocean acidification. A previous >2‐year coral transplant experiment to ambient and low pH common garden sites revealed differential survivorship across species and sites, providing a framework to compare mechanistic responses to differential pH exposures. Here, we examined gene expression responses of transplants of three species of reef‐building corals (Porites astreoides, Porites porites and Siderastrea siderea) and their algal endosymbiont communities …

Deconstructing The Mangrove Carbon Cycle: Gains, Transformation, And Losses, M. F. Adame, N. Cormier, P. Taillardat, N. Iram, A. Rovai, T. M. Sloey, E. S. Yando, J. F. Blanco-Libreros, M. Arnaud, T. Jennerjahn, C. E. Lovelock, D. Friess, G. M. S. Reithmaier, C. A. Buelow, S. M. Muhammad-Nor, R. R. Twilley, R. A. Ribeiro

Biological Sciences Faculty Publications

Mangroves are one of the most carbon-dense forests on the Earth and have been highlighted as key ecosystems for climate change mitigation and adaptation. Hundreds of studies have investigated how mangroves fix, transform, store, and export carbon. Here, we review and synthesize the previously known and emerging carbon pathways in mangroves, including gains (woody biomass accumulation, deadwood accumulation, soil carbon sequestration, root and litterfall production), transformations (food web transfer through herbivory, decomposition), and losses (respiration as CO₂ and CH₄, litterfall export, particulate and dissolved carbon export). We then review the technologies available to measure carbon fluxes in …

Analysis Of Sir Model With Optimal Control Strategy For A Simple Traffic Congestion Process, Ratna Herdiana, Zani Anjani Rafsanjani, R. Heru Tjahjana, Yogi Ahmad Erlangga, Moch Fandi Ansori

All Works

Traffic analysis on highways at the macroscopic level is very similar to the analysis of the spread of infectious diseases, namely the susceptible-infected-recover (SIR) model. We propose the SIR model with a control variable. The dynamics with fixed control and stability of the model are analyzed. Sensitivity analysis was also carried out. Variable control is applied as an effort to regulate or change the duration of the green light at an intersection. We obtain an optimal control strategy when the control is time-dependent. Numerical results show the positive impacts of implementing the control to susceptible vehicles and treatment for congested …

Non-Carathéodory Analytic Functions With Respect To Symmetric Points, Daniel Breaz, Kadhavoor R. Karthikeyan, Elangho Umadevi

All Works

The authors introduce new classes of analytic function with respect (Formula presented.) -symmetric points subordinate to a domain that is not Carathéodory. To use the existing infrastructure or framework, usually, the study of analytic function have been limited to a differential characterization subordinate to functions which are Carathéodory. Here, we try to obtain various interesting properties of functions which are not Carathéodory. Integral representation, interesting conditions for starlikeness and inclusion relations for functions in these classes are obtained.

Advancing Temporal Sepsis Biomarking: Covariate Vascular Endothelial Growth Factor A And B Gene Expression Profiling In A Murine Model Of Sars-Cov Infection, Asrar Rashid, Feras Al-Obeidat, Kesava Ramakrishnan, Wael Hafez, Nouran Hamza, Zainab A. Malik, Raziya Kadwa, Muneir Gador, Govind Benakatti, Rayaz A. Malik, Ibrahim Elbialy, Hekmieh Manad, Guftar Shaikh, Ahmed Al-Dubai, Amir Hussain

All Works

The limited specificity of standard inflammatory biomarkers poses a challenge for the diagnosis and monitoring of sepsis. The differential gene expression patterns of Vascular Endothelial Growth Factor A and B (VEGF-A and B) are promising candidates. This study aimed to elucidate variations in VEGF-A/B gene expression following SARS-CoV MA15 disease initiation. Biomarker tracking was examined in a murine C57BL wild-type (WT) genotype MA15 (SARS-CoV) nasal instillation model. In [GSE40824], the expression of TNF and VEGF-A significantly differed between the groups (p = 1.53e-07, and 0.0043) and over time. In [GSE40827], [GSE51386], [GSE51387], and [GSE40840], the expression of TNF, VEGF-A, and …

Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan

Masters Theses

"Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such as lack of ground truth labels, presence of complex temporal patterns, and generalizing over different datasets. In this work, we propose TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. To achieve these goals, we convert each input time-series into a sequence of 2D images using two encoding techniques with …

Big Code Search: A Bibliography, Kisub Kim, Sankalp Ghatpande, Dongsun Kim, Xin Zhou, Kui Liu, Tegawende F. Bissyande, Jacques Klein, Traon Yves Le

Research Collection School Of Computing and Information Systems

Code search is an essential task in software development. Developers often search the internet and other code databases for necessary source code snippets to ease the development efforts. Code search techniques also help learn programming as novice programmers or students can quickly retrieve (hopefully good) examples already used in actual software projects. Given the recurrence of the code search activity in software development, there is an increasing interest in the research community. To improve the code search experience, the research community suggests many code search tools and techniques. These tools and techniques leverage several different ideas and claim a better …