Digital Commons Network^™

Toward Automated Knowledge Discovery In Case-Based Reasoning, Sherri Weitl-Harms, John Hastings, Jay H. Powell

Research & Publications

Automated Case Elicitation (ACE) enables case-based reasoning (CBR) systems to automatically acquire knowledge through real-time exploration and interaction with environments. CBR is an explainable AI methodology, where decisions are based on previous encounters. ACE combined with CBR continues learning as it is being deployed, and produces specific cases that can be reviewed by humans, unlike pretrained large language models (LLMs) that learn by training offline on prior data. ACE and CBR may be useful methods to gather training data for use with generative AI, or to help them to adapt on the fly. This research explores ACE's potential by applying …

Towards Robust Iot Security: A Blockchain Design With Attribute-Based Encryption, Bryan Ikei, Hanna Thiry, Shengjie Xu

Research & Publications

Internet of Things (IoT) data and devices face significant security concerns. It is well-known that IoT security standards and frameworks have yet to be established due to variations with IoT developers and manufacturers agreeing on fundamental design methods to address IoT security and its limited computational resources. This research aims to determine how security standards and frameworks can be better implemented to enhance IoT security. Specifically, this research investigates whether implementing an encryption scheme such as attribute-based encryption (ABE) along with blockchain, a distributed ledger technology (DLT), strengthens the security of IoT data and devices. In this context, an encryption …

Assessing Security Flaws In Modern Precision Farming Systems, Joseph Boyd, Robert Richardson

Annual Research Symposium

The increasing interconnectivity of the digital age brings new vulnerabilities for cyber criminals and nation state threat actors alike. Every day, threat actors make millions of at-tacks against a variety of systems. Though not all these attacks prove successful, they all share the same goal of manipulating or extracting data from their targets. The dawn of digitalization in the agricultural industry finds itself under the same threats. Because agriculture sits within the category of critical infrastructure, digitizing this industry should be accompanied with special concern for implementing good security practices. At a basic level, good cyber security practice includes ensuring …

Artificial Intelligence Usage And Data Privacy Discoveries Within Mhealth, Jennifer Schulte

Research & Publications

Advancements in artificial intelligence continue to impact nearly every aspect of human life by providing integration options that aim to supplement or improve current processes. One industry that continues to benefit from artificial intelligence integration is healthcare. For years now, elements of artificial intelligence have been used to assist in clinical decision making, helping to identify potential health risks at earlier stages, and supplementing precision medicine. An area of healthcare that specifically looks at wearable devices, sensors, phone applications, and other such devices is mobile health (mHealth). These devices are used to aid in health data collection and delivery. This …

Do Online Test Proctoring Services Abide By Standard Data Protections?, Tristan Stapert, Andrew Kramer

Annual Research Symposium

In the aftermath of the COVID-19 pandemic, schools adopted new software to allow for online learning. Online exam proctoring has seen rapid growth in both K-12 and higher education. The security of these suites is critical due to their extensive access. Online proctoring suites have the capabilities to assess and configure student devices, access the microphone and cam-era, and view student information in the scope of the exam. This case study investigates the security of data sent over the network using dynamic software analysis and network monitoring while using the Respondus Lockdown Browser.

Natural Language Processing: Understanding Slang And Colloquial Speech, Beau Miller

Annual Research Symposium

Within the field of Natural Language Processing, slang and colloquial language provide a unique challenge for the training and use of language models. This speech holds an odd, transient space with public consciousness, as each instance has a variable time of relevancy and popularity, amongst other factors such as their fluid definition, usage amongst certain groups, and relative lack of information and training data concerning new or evolving terms. These characteristics make it difficult for models to learn these phrases in a timely manner. This project focuses on how a NLP model could learn new additions to colloquial language in …

The Impact Of Family Business Ownership And Involvement On Entrepreneurial Self-Identification, Ephrata Yared Feyissa, Robert Girtz

Annual Research Symposium

In this study I analyze the impact that family business ownership has on the tendency of individuals to identify as being entrepreneurial. Drawing data from the 1979 cohort of the National Longitudinal Survey of Youth, I use two-sample t-tests and logistic regression models to explore the relationship between personal entrepreneurial aspirations and having come from an environment involving a family business. As part of this analysis, I control for several demographic factors, such as cognition, gender, and ethnicity. The outcomes from this research highlight the importance of family business as a key factor in fostering entrepreneurial mindsets, suggesting that the …

Exploring The Antimicrobial Potential Of Honey From Alfalfa (Medicago Sativa) Against Both Human And Plant Pathogens, Denyce Bravo, Andrew Santhoff

Annual Research Symposium

Alfalfa (Medicago sativa) is the third most valuable crop in the United States. It produces a large amount of nectar from which honeybees and other types of bees produce a high yield of honey. It is estimated that around 416 to 1,933 pounds of nectar per acre is produced by alfalfa (Kropacova, 1963). However, even with the great antimicrobial features that honey offers, there is still limited research on the antimicrobial properties of specific types of honey, such as alfalfa honey. Topical honey application clears wounds swiftly, aiding rapid healing, even in infections resistant to typical antibiotics like methicillin-resistant Staphylococcus …

Assessing Security Vulnerabilities In Wireless Iot Devices, John Brumels

Annual Research Symposium

This research project aims to systematically assess and analyze security vulnerabilities in accessibility technology, specifically devices related to the American Disabilities Act (ADA), such as wheelchair lifts, ADA buttons, and light switches. The project focuses on the potential risks associated with radio frequency (RF) replay attacks, a well-documented threat in IoT security. By examining the vulnerabilities and consequences of RF replay attacks in these critical areas, the research seeks to enhance the security and safety of individuals with disabilities and the broader public. The project also explores potential countermeasures and ethical considerations for responsible vulnerability disclosure, contributing to the fields …

Micromouse - Maze Solving Robot, Aiden Schramm, David Medin, Andrew Kramer

Annual Research Symposium

A Micromouse is a path-finding robot designed to traverse and map a maze to determine the shortest path possible. These robots are typically entered in annual Micromouse competitions to compete against other teams for achieving the best possible time in solving the maze in the most efficient manner.

Resonant Landscapes, Tate Carson, Cater Gordon

Annual Research Symposium

Immersive ambisonics field recordings of 13 South Dakota State Parks. Used for: interactive smartphone-based sound art exhibit and immersive soundscape compositions. Goal: by studying a park's soundscape through immersive recording, we can gain a deeper understanding and appreciation for its unique sonic characteristics.

Divergent Detection: A Comprehensive Study Of Dgas Using Fnns For Original, Noise-Modified, And Linear Recursive Sequences(Lrs), Anthony Rizi

Masters Theses & Doctoral Dissertations

This comprehensive research endeavors to address a pressing issue within the realm of cybersecurity—the challenge posed by malicious activities utilizing Domain Generation Algorithms (DGAs). These algorithms, numbering at least 84 traditional malware families as of late 2023, dynamically generate domain names to facilitate nefarious operations while evading conventional detection mechanisms. The study generated over 159,750 domains and studied more than 1.27 million data points. Existing studies have predominantly focused on surface-level aspects of DGAs, including domain lengths, alphanumeric values, and top-level domains (TLDs). In response to this challenge, the research question at the core of this study aims to investigate …

Surveying For Ophidiomyces Ophidiicola, The Causal Agent Of Snake Fungal Disease In South Dakota., Adam Peak, Brandon Daniels, Andrew E. Sathoff

Annual Research Symposium

For the past decade there has been an emerging disease plaguing wild snakes across the Eastern United States and Europe. In 2006, researchers started investigating the decline of Timber rattlesnake populations in New Hampshire. They discovered a fungal infection killing off the young to mid-juvenal snakes, thus know as Snake Fungal Disease or Ophidiomycosis. In 2011, San Deigo State University, identified the pathogen that causes infection, the fungus Ophidiomyces ophiodiicola. O. ophiodiicola has now affected 30 different snakes from six families within at least 20 different states since it’s discovery. This study pertains to determining the prevalence of Snake Fungal …

An Nlp-Based Knowledge Extraction Approach For It Tech-Support/Helpdesk Transcripts, Gary Yu Zhao

Masters Theses & Doctoral Dissertations

In the realm of IT support, it is crucial to extract valuable information from various support channels, such as telephone, web chat, email, and social media. This extracted knowledge can help organizations prioritize customer-centric approaches and improve customer service. It also has broader applications, from decision support to product development and human resources policies. Traditionally, extracting knowledge from unstructured text was time-consuming and inefficient, but natural language processing (NLP) techniques demonstrated potential for extracting valuable insights in a variety of application contexts. However, their efficacy and potential in the context of domain-specific IT support transcripts remain primarily limited.

This research …

Weed Detection Using Lightweight Deep Learning Models With Transfer Learning And Hyperparameter Optimization, Ali Shaheen

Masters Theses & Doctoral Dissertations

In agriculture, the presence of weeds adversely impacts yield. Confronting this challenge manually requires continuous and labor-intensive field monitoring processes. Artificial intelligence, notably deep learning is one the most promising for weed detection, particularly when deployed to edge devices. However, these edge devices have limited computational resources, making it challenging to deploy large Deep Learning (DL) models often resulting in a performance-size trade-off. This research proposes a three-pronged approach that leverages DL lightweight architectures (LWA) to optimize for size and minimize computational resources at the edge, transfer learning to mitigate constraints associated with limited data commonly encountered in this domain, …

Implementing A Zero Trust Architecture For Ics/Scada Systems, Raven Sims

Masters Theses & Doctoral Dissertations

The American people depend significantly on Industrial Control Systems (ICS), which help enable critical infrastructures worldwide. These systems can deliver vital infrastructure services to provide essential capabilities worldwide. These Industrial Control Systems also contain many associated vulnerabilities that go unmitigated due to the complex nature of the systems. To strengthen and improve that cyber posture, a more proactive cyber approach utilizing a Zero Trust Architecture was analyzed as a solution to mitigate the risk. The ICS Purdue Model was interpreted as a potential framework for ICS architecture during the analysis. The ICS Purdue Model was then enhanced with Zero Trust …

A Cross-Architecture Framework For Anti-Debugging Techniques, Austin Norby

Masters Theses & Doctoral Dissertations

Anti-debugging techniques are often used in malware samples and software protection frameworks. From the malware perspective, the malware author includes these checks to hinder the analysis of the sample to increase the time to affect their target. Software protection frameworks on the other hand do this to protect sensitive information such as intellectual property, music, movies, and other proprietary information. The anti-debugging techniques serve to deter reverse engineers from compromising the sensitive data in this case. Modern anti-debugging research focuses on creating new techniques or defeating techniques during analysis. Additionally, modern anti-debugging research is paired with other anti-analysis techniques and …

Digital Divide In Rural Native American Homes: A Student Perspective, Chad R. Fenner, Cherie Noteboom, Omar El-Gayar

Research & Publications

Native American homes located in rural western North Dakota have seen increased availability of broadband and fiber optic Internet but continue to have low access numbers. Native American homes in the region located outside population centers continue to have difficulty accessing the Internet. Many households continue to struggle with economic factors compounded by the cost of a device to access the Internet for personal, educational, or employment use. A qualitative study with semi-structured interviews and the grounded theory method investigated the Native American home environment. Interviews were conducted with Native American students attending a state university with insight into diverse …

An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr.

Research & Publications

This research investigates the problem of assigning pre-scheduled trips to multiple drones to collect hazardous waste from different sites in the minimum time. Each drone is subject to essential restrictions: maximum flying capacity and recharge operation. The goal is to assign the trips to the drones so that the waste is collected in the minimum time. This is done if the total flying time is equally distributed among the drones. An algorithm was developed to solve the problem. The algorithm is based on two main ideas: sort the trips according to a given priority rule and assign the current trip …

Optimal Algorithm For Managing On-Campus Student Transportation, Youssef Harrath Dr.

Research & Publications

This study analyzed the transportation issues at the University of Bahrain Sakhir campus, where a bus system with an unorganized and fixed number of buses allocated each semester was in place. Data was collected through a survey, on-site observations, and student schedules to estimate the number of buses needed. The study was limited to students who require to move between buildings for academic purposes and not those who choose to ride buses for other reasons. An algorithm was designed to calculate the optimal number of buses for each time slot, and for each day. This solution could improve transportation efficiency, …

Getting The Best Out Of Joint Warfighter Development, Charls Davis, Jeffrey Turner, Mary Bell

Research & Publications

Is the Department of Defense (DOD) producing the best joint warfighters possible? During strategic competition that increasingly ebbs toward conflict, joint warfighting and joint warfighter development are more important than ever. Joint warfighter development is the catalyst necessary for the U.S. military to conduct joint operations. Joint operations, where forces from different military departments are interoperable and interdependent, convey a marked advantage over potential adversaries and leave them with few military options to counter. Joint operations leverage the unique capabilities of each DOD Service, but they require joint-minded leaders—joint warfighters—who can collaboratively orient toward common objectives rather than fighting separate …