Digital Commons Network^™

Using Game Theory To Model Tripolar Deterrence And Escalation Dynamics, Grace Farson

Honors Program: Senior Projects (Public)

The study investigated how game theory can been utilized to model multipolar escalation dynamics between Russia, China, and the United States. In addition, the study focused on analyzing various parameters that affected potential conflict outcomes to further new deterrence thought in a tripolar environment.

A preliminary game theoretic model was created to model and analyze escalation dynamics. The model was built upon framework presented by Zagare and Kilgour in their work ‘Perfect Deterrence’. The model is based on assumptions and rules set prior to game play. The model was then analyzed based upon these assumptions using a form of mathematical …

Climate Change And Environmental Justice, Clement Loo

Environmental Studies Publications

This chapter provides a broad overview of the relationship between climate change and environmental justice. It provides (1) a brief review of the concept of environmental justice, (2) discussion about how environmental justice applies to climate change, and (3) several examples of how environmental justice has been integrated into climate governance.

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

Generations Of Reason: A Family’S Search For Meaning In Post-Newtonian England (Book Review), Calvin Jongsma

Faculty Work Comprehensive List

Reviewed Title: Generations of Reason: A Family's Search for Meaning in Post-Newtonian England by Joan L. Richards. New Haven, CT: Yale University Press, 2021. 456 pp. ISBN: 9780300255492.

Air Force Digital Badges, Jacob Chan

Theses and Dissertations

The Air Force talent management and force development systems are antiquated. Airmen records are often stored on different Air Force information systems. Existing records sometimes lack granularity and context to recognize Airmen skills. Digital badges are a newer technology utilized by academia and industry to recognize member skills. However, military badging research is sparse and existing studies do not provide sufficient evidence on the value of digital badging to the Air Force. The studies: (1) lack background research on badging; (2) do not provide quantitative data on the effects of badging; and (3) issued badges through commercial entities which may …

Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore

Theses and Dissertations

As the threat of near-peer adversaries has increased, the DoD has increased its emphasis on Joint All-Domain Operations (JADO). This emphasis on JADO highlights the need for hands-on training that can engage military members at all levels. The serious game Battlespace Next (BSN) was designed to teach high-level JADO concepts by modeling real-world military assets in the context of a strategic card game. To keep pace with the evolving landscape of warfare as well as fit the needs of a variety of Department of Defense (DoD) communities, this research introduces the Battlespace Next Education Framework (BSNEF). The BSNEF allows JADO …

Cellphone-Acoustics Based Suas Detection And Tracking, Ryan D. Clendening

Theses and Dissertations

Small Unmanned Aerial Systems (sUAS) are an easily accessible technology that has become an increasingly large threat to US critical systems. This threatening technology demands using fault-tolerant, low-cost, replaceable, and accurate sensing resources, which counter the ubiquitous nature of sUAS [1]. Therefore, the methods developed in this thesis detect and track sUAS using easily accessible sensing resources, such as cellphones. First, we develop an acoustics sensor network-based sUAS detection methodology. In the latter effort, a deep learning model is trained using the acoustics data from the data collection to predict sUAS range from a cellphone. Combined, these two efforts demonstrate …

Strategic Action Execution Through Regret Matching In Press Diplomacy, Leif D. White

Theses and Dissertations

To take most advantage of collaboration, negotiation is paramount to succeed in press Diplomacy. Humans use this construct to work towards self victory or sometimes towards an alternative strategic objective undefined in the game’s rules. To emulate this behavior, this thesis examines how to use communication to enable the victory or defeat of any other player in the game. This research develops a press Diplomacy agent, Lyre, that can work to attain these specific objectives in Diplomacy through the regret matching algorithm (RM). We also study how Lyre can begin Diplomacy with the goal to win, then shift strategies to …

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

Cascading Effects Of Cover Crops On The Subsequent Cash Crop Defense Against The Polyphagous Herbivore Fall Armyworm (Spodoptera Frugiperda), Adegboyega Fajemisin, Alexis Racelis, Rupesh R. Kariyat

School of Earth, Environmental, & Marine Sciences Faculty Publications

Simple Summary

Although studies have started to show that the effects of cover crops can translate into the cash cropping season, there is little information on the cascading effects of cover crops on the subsequent cash crop defenses, especially against polyphagous herbivores. To bridge this information gap, we conducted a field and laboratory study to investigate the cascading effects of different cover crop species on the subsequent cash crop defense against the polyphagous herbivore fall armyworm (Spodoptera frugiperda) across three fields in the Lower Rio Grande Valley in south Texas. Our field and laboratory results revealed that cover crop treatments …

Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle

SDSU Data Science Symposium

In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …

National Development And The Sustainability Of Mining In The Atacama Desert, Chile, Dakota Soleil Osgood

Capstone Collection

As climate change continues to intensify on a global scale, efforts have been made to implement renewable energies and progressive technologies. These tools are critical in the shift towards a more sustainable practice, and yet analysis of localized impacts from the development of these mechanisms is inadequate. Chile has been and continues to be a leading country in mineral extraction, with an economic history founded in the mining industry. The establishment of mining in Chile as a progressive tool has aided the social and economic development of the nation. Consequences of mining extraction, however, include intensive environmental degradation, human rights …

An Efficient Hash-Based Assessment And Recovery Algorithm For Distributed Healthcare Systems, Sanaa Kaddoura, Ramzi Haraty, Sultan Al Jahdali, Mohamad Jaber

All Works

The enhancement of the information technology in many domains has had a positive impact on the healthcare sector. The ability to share medical data is one of the positive outcomes. However, this improvement comes with a number of threats. Although many threat preventive measures have been applied yet, no one can be confident that the system is safe from attacks. Thus, an algorithm needs to assess the damage occurring as a result of an attack before recovering the database. In this work, we present a distributed algorithm that uses hash tables to deal with the “information warfare” problem in healthcare …

The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii

Browse all Theses and Dissertations

The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …

Towards Explainable Ai Using Attribution Methods And Image Segmentation, Garrett J. Rocks

Honors Undergraduate Theses

With artificial intelligence (AI) becoming ubiquitous in a broad range of application domains, the opacity of deep learning models remains an obstacle to adaptation within safety-critical systems. Explainable AI (XAI) aims to build trust in AI systems by revealing important inner mechanisms of what has been treated as a black box by human users. This thesis specifically aims to improve the transparency and trustworthiness of deep learning algorithms by combining attribution methods with image segmentation methods. This thesis has the potential to improve the trust and acceptance of AI systems, leading to more responsible and ethical AI applications. An exploratory …

Landmark Stereo Dataset For Landmark Recognition And Moving Node Localization In A Non-Gps Battlefield Environment, Ganesh Sapkota, Sanjay Madria

Computer Science Faculty Research & Creative Works

In this paper, we have proposed a new strategy of using the landmark anchor node instead of a radio-Based anchor node to obtain the virtual coordinates (landmarkID, DISTANCE) of moving troops or defense forces that will help in tracking and maneuvering the troops along a safe path within a GPS-denied battlefield environment. the proposed strategy implements landmark recognition using the Yolov5 model and landmark distance estimation using an efficient Stereo Matching Algorithm. We consider that a moving node carrying a low-power mobile device facilitated with a calibrated stereo vision camera that can capture stereo images of a scene containing landmarks …

The Geology Of El Paso, William Cornell, Diane Doser, Richard Langford, Joshua Villalobos, Jason Ricketts

Books & Monographs

The Geology of El Paso describes the history of El Paso, Texas and its surrounding region from the Precambrian formation of the continent to the modern use of geologic resources. This book is written in an easy to digest format, with definitions or links for specific geologic terms and references for further reading. It reviews the formation and evolution of local landmark features such as the Franklin Mountains, Cerro Cristo Rey, and the Sierra de Juarez. Fossils and stratigraphic units of the El Paso area are described as well as important geologic features. The book puts the events that shaped …

Journal Of The Arkansas Academy Of Science Volume 77, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Cloud Seeding, Wildfire Smoke Emissions, And Solar Geoengineering: Why Is Climate Modification Unregulated?, Karen Bradshaw, Monika U. Ehrman

Faculty Journal Articles and Book Chapters

This Article is the first to identify that companies and agencies systemically modify climatic airspaces through wildfire smoke emissions, weather modification (cloud seeding to cause rain), and solar geoengineering. Climate modification is not a conspiracy theory or a hypothetical: it is happening, and it is changing weather patterns. Yet, climate modification is almost wholly unregulated. Further, it is also not recorded or tracked in systemic ways. That is to say, even government agencies do not have comprehensive records of whether; how often; or how much climate modification is occurring. The data is simply not gathered, aggregated, or stored. As a …

Identification And Modeling Social Media Influence Pathways: A Characterization Of A Disinformation Campaign Using The Flooding-The-Zone Strategy Via Transfer Entropy, Jasser Jasser

Electronic Theses and Dissertations, 2020-2023

The internet has made it easy for narratives to spread quickly and widely without regard for accuracy or the harm they may cause to society. Unfortunately, this has led to the rise of bad actors who use fake and misleading articles to spread harmful misinformation. These actors flood the information space with low-quality articles in an effort to disrupt opposing narratives, sow confusion, and discourage the pursuit of truth. In societies that prioritize free speech, maintaining control over the information space remains a persistent challenge. Achieving this requires strategic planning to protect the dissemination of information in ways that promote …

Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

This paper expands the authors’ prior work[1], which focuses on developing a convolutional neural network (CNN) model capable of mapping time-averaged, unsteady Reynold’s-averaged Navier-Stokes (URANS) simulations to higher resolution results informed by time-averaged detached eddy simulations (DES). The authors present improvements over the prior CNN autoencoder model that result from hyperparameter optimization, increased data set augmentation through the adoption of a patch-wise training approach, and the predictions of primitive variables rather than vorticity magnitude. The training of the CNN model developed in this study uses the same URANS and DES simulations of a transonic flow around several NACA 4-digit airfoils …

Development Of New Mass Spectrometric Approaches For Biomarker Discovery: Application To Complex Biological Matrices For Tissue Characterization And Disease Diagnosis, Allix Marie Coon

Legacy Theses & Dissertations (2009 - 2024)

In this work, the newly developed technique laser ablation direct analysis in real – time high-resolution imaging mass spectrometry (LADI-MS) and the more established methods direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) and two-dimensional gas chromatography – mass spectrometry (GC×GC-MS), were used to interrogate challenging plant- and human-derived complex matrices that have proven difficult to analyze by conventional methods, in order to extract heretofore inaccessible information that can be applied to the understanding of wood systems biology, ecophysiology, dendrochronology and natural product isolation of biologically relevant compounds (on the plant side), and explore the potential for discovery …

Development Of Ambient Ionization Mass Spectrometry Approaches For The Characterization And Quantification Of Psychoactive Small-Molecule Constituents In Complex Plant Matrices, Megan Isabella Chambers

Legacy Theses & Dissertations (2009 - 2024)

Drug chemistry sections of forensic crime laboratories are tasked with analyzing a variety of unknown materials, a subset of which are derived from plants. In comparison to the analysis of small-molecule drugs, these plant matrices are incredibly complex and present unique challenges. When traditional chromatographic approaches are used to interrogate these materials in forensic investigations, large amounts of time, resources, and funds are directed towards the extensive sample preparation steps required. Exacerbating the issue is that the matrix characteristics often result in instrument downtime to accomplish the maintenance required to address ingredients adhering to columns or clogging syringes, which are …

Comprehensive Analysis And Forensic Investigation Of Cyanide, Thiocyanate, And 2-Amino-2-Thiazoline-4-Carboxylic Acid In-Ante- And Postmortem Blood Utilizing Advanced Analytical Techniques, Abdullah Hamad Alluhayb

Electronic Theses and Dissertations

Cyanide (CN), present as cyanide anion (CN-) or hydrogen cyanide (HCN), is a deadly poison. The main mechanism of CN toxicity is blocking terminal electron transfer, leading to cellular hypoxia, cytotoxic anoxia, and potential death. Determining blood CN concen-trations along with its major metabolite, thiocyanate (SCN-), is crucial. A sensitive method for concurrent detection of CN and SCN- from human ante- and post-mortem blood via liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis was devel-oped. The method involved active microdiffusion with chemical modification using naph-thalene-2,3-dicarboxaldehyde (NDA) and taurine, while monobromobimane (MBB) mod-ification was used for SCN-. The method showed good sensitivity for …

Anti-American Stance In Turkey: A Twitter Case Study, Gowri Prathap, Alex Korb, Luke Palmieri, Ekrem Kaya, Saltuk Karahan, Hamdi Kavak

School of Cybersecurity Faculty Publications

The availability of social media and biased actors exacerbated Anti-American and Anti-Western views to extremes. In this paper, we report our efforts in analyzing anti-American views on Twitter. We have collected over three years of Turkish tweets related to the US, translated them into English, and analyzed these tweets using various computational social science tools. We found that Turkish tweets related to the US are significantly negative, and emotions reflect disgust and anger. Furthermore, we found that the source of the negative views stems from political actors like Trump or Biden rather than general hatred. Our results shed light on …

Underwater Communication Acoustic Transducers: A Technology Review, Laila Shams, Tian-Bing Xu, Zhongqing Su (Ed.), Branko Glisic (Ed.), Maria Pina Limongelli (Ed.)

Mechanical & Aerospace Engineering Faculty Publications

This paper provides a comprehensive review on transducer technologies for underwater communications. The popularly used communication transducers, such as piezoelectric acoustic transducers, electromagnetic acoustic transducers, and acousto-optic devices are reviewed in detail. The reasons that common air communication technologies are invalid die to the differences between the media of air and water are addresses. Because of the abilities to overcome challenges the complexity of marine environments, piezoelectric acoustic transducers are playing the major underwater communication roles for science, surveillance, and Naval missions. The configuration and material properties of piezoelectric transducers effects on signal output power, beamwidth, amplitude, and other properties …

Commentary On Healthcare And Disruptive Innovation, Hilary Finch, Affia Abasi-Amefon, Woosub Jung, Lucas Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Exploits of technology have been an issue in healthcare for many years. Many hospital systems have a problem with “disruptive innovation” when introducing new technology. Disruptive innovation is “an innovation that creates a new market by applying a different set of values, which ultimately overtakes an existing market” (Sensmeier, 2012). Modern healthcare systems are historically slow to accept new technological advancements. This may be because patient-based, provider-based, or industry-wide decisions are tough to implement, giving way to dire consequences. One potential consequence is that healthcare providers may not be able to provide the best possible care to patients. For example, …

Explainable Ai For Android Malware Detection, Maithili Kulkarni

Master's Projects

Android malware detection based on machine learning (ML) is widely used by the mobile device security community. Machine learning models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to understand how such models make decisions. As a result, popular malware detection strategies remain black box models, which may result in a lack of accountability and trust in the decisions made. The field of explainable artificial intelligence (XAI) attempts to shed light on such black box models. In this research, we apply XAI techniques to ML-based Android malware detection systems. We train classic ML models …

The Future Between Quantum Computing And Cybersecurity, Daniel Dorazio

Williams Honors College, Honors Research Projects

Quantum computing, a novel branch of technology based on quantum theory, processes information in ways beyond the capabilities of classical computers. Traditional computers use binary digits [bits], but quantum computers use quantum binary digits [qubits] that can exist in multiple states simultaneously. Since developing the first two-qubit quantum computer in 1998, the quantum computing field has experienced rapid growth.

Cryptographic algorithms such as RSA and ECC, essential for internet security, rely on the difficulty of complex math problems that classical computers can’t solve. However, the advancement of quantum technology threatens these encryption systems. Algorithms, such as Shor’s, leverage the power …