Digital Commons Network^™

The Role Of Artificial Intelligence In Reducing Internet Crimes Against Children, Malyssa Shaw

Student Scholar Symposium Abstracts and Posters

When generative artificial intelligence (AI) first surfaced and broke into the public sphere, my immediate concern was in its development, implementation, and harmful applications. I was not surprised when deepfake technology rapidly advanced alongside these new developments and impacted women and children worldwide. Disproportionately, they have been made victims of intimate media forgery as early as the 1990s, with an unprecedented uptick in recent years as a direct result of these developments. In response, I wrote "Deepfake, Real Harm: Protecting Children in the Age of AI", analyzing data specifically regarding child sexual abuse material (CSAM) created with artificial intelligence while …

Business Financial Information Systems, Lirie Koraqi, James Jolovski Prof.

International Journal of Business and Technology

An information system is a combination of software, hardware, and telecommunication networks to collect useful data, especially in an organisation. Many businesses use information technology to complete and manage their operations, interact with their consumers, and stay ahead of their competition. Some companies today are completely built on information technology.

Well designed and implemented business information systems should provide the information management and outside parties need to make informed and timely decisions about the operating health of the company. Business considers the need to have information available to assess the profitability of a new product they are selling or their …

Comparative Evaluation Of Microcontrollers For Real-Time Heart Rate Monitoring And Tachycardia/Bradycardia Detection, Arxhend Jetullahu, Luan Mulaku, Saranda Demolli

International Journal of Business and Technology

The growing demand for portable healthcare devices has led to combining microcontrollers with machine learning models to enable real-time health monitoring. It's quite paramount, specifically in the context of identifying irregularities in heart rate, like tachycardia—where the heart races unusually fast—and bradycardia, an instance of a sluggish heartbeat. The neat thing is that this study takes a stab at contrasting the effectiveness among three popular microcontroller types—the ESP32, the Raspberry Pi, and the Arduino Nano 33 BLE Sense—in terms of real-time tracking of heartbeats and spotting any oddities (using, of course, a model developed with some machine learning elements). At …

Study On The Use Of Mechanized-Fired Clay Bricks As A Supplementary Cementitious Material, Esra Elsheikh

International Journal of Business and Technology

The current global tendency is to replace a portion of the cement in the concrete mix with materials of cementitious properties to mitigate the cement industry’s negative environmental impact. This study explores using finely milled Fired Clay Brick debris to replace cement in the production of mortars partially. The aim is to create a more cost-effective mortar while tackling the problem of disposing of waste bricks. Two samples of it were collected from two factories, pulverized into a powder, and added to the cement mortar mixtures in 10%, 15%, and 20% by cement mass. Mortars were examined for their chemical …

Building Enveloperetrofitting Innovation: Recycled Materials Role In Digital Fabrication And 3d Printing, Amr Soliman Elgohary, Haytham M. Elbadrawy, Ahmed Elsamanoudi

HBRC Journal

Traditional construction methods are one of the main causes of resource depletion. This research explores the intersection of digital fabrication methods using recycled materials and eco-friendly construction through retrofitting the building envelope to achieve sustainability. Traditional methods of retrofitting existing building elements consume many resources (materials-energy) and produce a lot of waste. In this context, 3D printing, a modern digital manufacturing method, stands out as a promising alternative, offering innovative ways to reduce material and energy consumption and reduce waste in the building construction process. This technique can be used to produce innovative modules that may improve the environmental performance …

Building A Data-Driven Security Ai Framework Using Machine Learning Models, Christopher Chan Vi

Master's Theses

This research project explores a modern approach to Intrusion Detection System (IDS) anomaly detection by leveraging Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLM), and Explainable AI (XAI). The purpose is to assess the effectiveness of these technologies in enhancing the understanding of intrusion events. This research study addresses the challenges of threshold determination and the interpretability of anomaly detection results. The proposed solution involves an LLM-based framework with XAI capabilities, integrated with a Retrieval Augmented Generation (RAG) architecture, to provide clear explanations for detected anomalies, utilizing both custom and pre-trained datasets. The study navigated inherent challenges, including …

Siamese: Stealing Fine-Tuned Visual Foundation Models Via Diversified Prompting, Madhureeta Das, Gaurav Bagwe, Miao Pan, Kaichen Yang, Xiaoyong Yuan, Lan Zhang

Michigan Tech Publications

Visual foundation models, characterized by their robust generalization and adaptability, serve as the basis for a wide array of downstream tasks. When fine-tuned for specific tasks, these models encapsulate confidential and valuable task-specific knowledge, making them prime targets for model stealing (MS) attacks. While recent efforts have exposed MS threats in practical scenarios such as data-free and hard-label contexts, these attacks predominantly target traditional victim models trained from scratch. Fine-tuned visual foundation models, pre-trained on vast and diverse datasets and then fine-tuned on downstream tasks, present significant challenges for traditional MS attacks to extract task-specific knowledge. In this paper, we …

Viability Of Widely Used Encryption Schemes In Drone Transmission, Emanuel Yasir Nelson

Cybersecurity Undergraduate Research Showcase

This paper presents throughout research on the security issues related to drone transmission. These topics were addressed and explained, in particular the aspects relating to cybersecurity, for utmost clarity. These include threats and vulnerabilities, drone transmission the impact of encryption on latency, and the details of the encryption methods AES-128, AES-256, and ChaCha20 that were used in the experiment described in the paper. Each encryption method performance was measured and outputted by the Python code developed and used in the experiment. Afterwards, the performance of each method was analyzed in relation to their decryption time, encryption time, end to end …

Artificial Intelligence In Higher Education: Opportunities And Challenges, Maytha Al-Ali, Adam Marks, Jasur Umirzokov, Noura Metawa

Iraqi Journal for Computer Science and Mathematics

While AI is often presented as a panacea for the challenges facing higher education, there is limited empirical evidence supporting its effectiveness in improving student learning and institutional performance. This gap between expectation and reality emphasizes the need for rigorous research, realistic goal-setting, and careful planning to ensure that AI technologies deliver on their promises in higher education. This study contrasts the potential utilization of AI technologies in Higher Education from the literature, against actual utilization in universities. The study also investigates the key barriers of AI implementation in higher education. This study uses a mixed-research methods approach, including case …

Retracted: Ai-Driven Flood Prediction, Monitoring, And Warning Systems: Design, Evaluation, And Simulation, Abdel Rahman A. Alkharabsheh, Lina M. Momani

Iraqi Journal for Computer Science and Mathematics

The Climate is becoming increasingly unpredictable, while the incidence of extreme weather is on the rise — both are contributing to surging global demand for advanced flood forecasting and monitoring services. This paper introduces an AI-powered Flood Monitoring and Warning System (FMWS) through an IoT sensor network, scalable real-time data analytics, and Machine Learning (ML) models to enhance the accuracy of prediction, risk analysis, and early warning dissemination in the notified areas. Hydrological and meteorological data would be collected by an ultrasonic sensor, a radar sensor, and a pressure sensor interfacing via GSM/GPRS, Wi-Fi, LoRa, or satellite network links. Machine …

Detection Of Breath, Phonation And Cough Sounds Using Sound Feature Vectors And Artificial Neural Networks By Calculating Lung Forced Vital Capacity With Mobile Infrastructures, Edmond Hajrizi

International Journal of Business and Technology

Objective: In this study, it is aimed to calculate the tidal volume capacity with mobile infrastructures and to determine the O2 and CO2 values from breath, phonation and cough sounds with the help of artificial neural networks using voice feature vectors. In addition, it is aimed to develop a method that will enable computation of forced expiratory volume via mobile devices.

Materials and Methods: Since sound disease diagnosis is basically a classification problem, tidal volume classification is considered as a pattern recognition problem. Our automatic O2 and CO2 classification study as a pattern recognition function includes three subcomponents; Identifying and …

Fabrication And Evaluation Of Large Alumina Crucibles By Vat Photopolymerization Additive Manufacturing For High-Temperature Actinide Chemistry, R. Joey Griffiths, Christy Santoyo, Jean-Baptise Forien, Bradley Childs, Andrew J. Swift, Andrew Cho, Alexander Wilson-Heid, George Ankrah, Devin Rappleye, Aiden A. Martin, Jason Jeffries, Kiel Holliday

Faculty Publications

Additive manufacturing (AM) offers opportunities to advance the design and function of ceramic tooling in high temperature actinide pyrochemistry. In technical ceramics such as alumina, conventional forming techniques often restrict design flexibility and can limit experimental progress. In this study, we investigate the use of vat photopolymerization (VP) with commercial resins to fabricate large-scale alumina crucibles, reaching dimensions up to 125 mm, which is significantly larger than typically reported for dense VP ceramics. Notably, these additively manufactured components are produced using consumer-grade hardware, which limits process control, but offers significant upside in scalability and accessibility. Using microscopy and X-ray computed …

The Impact Of Infrastructure Construction And Remodeling Of Cities On Its People' Quality Of Life Miraj District-(Madi-Cairo) As A Geological Heritage Area, Ahmed M.E. Hammad

Mansoura Engineering Journal

Rapid urbanization is increasing globally, the urbanization rate expected to rise to more than 66% by 2050. (According to UN estimates) the increasing rates of urbanization in the world means adding 2.5 billion people to the urban population within a short period. Which necessitates increasing the traffic axes and the rest of the networks in terms of lengths and widths within the existing cities, and with the presence of the population during these works - despite their inevitability - the quality of their urban life is affected socially, naturally and economically. the research monitors these effects and the extent of …

Kinship Infrastructure Design: Evaluating Diversity And Resilience In Emergency Response Systems Through Agent-Based Modeling, Fayruz Maysha

Doctoral Dissertations and Master's Theses

Traditional infrastructure systems are often designed for predictable scenarios, making them vulnerable to disruption when real-world conditions change unexpectedly. This research addresses that limitation by introducing Kinship Infrastructure Design (KID), a bioinspired framework based on the kinship coefficient (Φ). Adapted from studies of genetic relatedness in eusocial insects, the kinship coefficient (Φ) measures similarity and diversity among system components by calculating the degree to which their functional traits—encoded as a synthetic genome—match. This research investigates whether a system design can achieve a “Goldilocks Zone” of functional diversity where systems achieve optimal adaptability and coordination under uncertainty."

Rather than relying on …

Confidential, Attestable, And Efficient Inter-Cvm Communication With Arm Cca, Sina Abdollahi, Amir Al Sadi, Marios Kogias, Hamed Haddadi, David Kotz

Other Faculty Materials

Confidential Virtual Machines (CVMs) are increasingly adopted to protect sensitive workloads from privileged adversaries such as the hypervisor. While they provide strong isolation guarantees, existing CVM architectures lack first-class mechanisms for inter-CVM data sharing due to their disjoint memory model, making inter-CVM data exchange a performance bottleneck in compartmentalized or collaborative multi-CVM systems. Under this model, a CVM's accessible memory is either shared with the hypervisor or protected from both the hypervisor and all other CVMs. This design simplifies reasoning about memory ownership; however, it fundamentally precludes plaintext data sharing between CVMs because all inter-CVM communication must pass through hypervisor-accessible …

Bridging Modalities: Enhancing Multimodal Sentiment Analysis For Social Media Networks, Misbah Ul Hoque

LSU Doctoral Dissertations

Social media platforms like X (formerly Twitter) serve as rich sources of textual and visual information, making multimodal sentiment analysis essential for understanding complex human emotions. This dissertation aims to advance multimodal sentiment analysis by improving the semantic alignment and fusion of textual and visual features, thereby enabling more accurate and context-aware sentiment interpretation of social media content.

To address challenges in multimodal integration, this work proposes two complementary MSA approaches. The first approach introduces a similarity-based multi-layer attention neural network (SiMANN) that enhances modality integration through cosine-based similarity fusion and modality-specific attention to emphasize salient features in text and …

Evaluating Kansai Airport's Ppp: Grounded Ambitions, Concession Of Financial, Geotechnical, And Climate Risk, Edmund Cho, Dimitrios V. Siskos

International Journal of Aviation, Aeronautics, and Aerospace

This study critically examines the Kansai Airports Group’s 44-year Public-Private Partnership (PPP) monopoly-type concession encompassing Kansai International (KIX), Osaka Itami (ITM), and Kobe (UKB) airports. The research uses financial analysis, Monte Carlo simulation, and NPV-at-risk modeling to evaluate how Japan’s fixed-term private monopoly model allocates financial, operational, and environmental risks. In 2015, there were significant developments in the promotion of the Private Finance Initiative (PFI) Act. It was revised in 2015; as a result, it finds that the underestimated long-term maintenance liabilities, especially Kansai airport (KIX) foundation subsidence, and lacked flexibility to manage exogenous shocks like COVID-19 and Typhoon Jebi. …

A Transition Framework For Hybrid Tls In Enterprise-Level Systems, William Hadd

Cybersecurity Undergraduate Research Showcase

Enterprises face an immediate need to protect long-lived data against harvest-now, decrypt-later threats while maintaining interoperability across layered systems. With NIST’s first post-quantum standards finalized (ML-KEM, ML-DSA, SLH-DSA) and TLS hybridization drafts defining concrete ECDHE + ML-KEM groups, adoption can begin at the TLS termination layer even before full ecosystem support for post-quantum signatures arrives (NIST, 2024; IETF, 2025). In this paper, we propose an enterprise-oriented transition framework and maturity model for hybrid TLS across email, internal API gateways, and object storage. We specify where to enforce, which hybrid groups to select, and how to prevent silent downgrade with policy …

Changes In The Structure And Properties Of Titanium In The Process Of Pressure Treatment, Sardor S. Abriev, Nasiba U. Abduraimova, Zokir R. Akramov, Yulbarskhon N. Mansurov

CHEMISTRY AND CHEMICAL ENGINEERING

Titanium is classified as a critical metal. It serves as a raw material for a wide range of industries owing to its unique properties – high strength at low density, corrosion resistance, and biocompatibility makes it indispensable. Uzbekistan and China possess primary resources for titanium production. However, the complexity of extraction and particularly processing, combined with high production costs, limits its large-scale use and increases the risk of shortages in industrial manufacturing. In this study, the structural and property evolution of titanium during pressure-based processing was investigated. Technology for producing powder titanium by metal forming methods is proposed. The results …

Fully Integrated Slippage Detection System For Lower Limb Amputees, Christopher E. Miglio

Master's Theses

Lower limb amputees face significant challenges in maintaining a proper prosthetic fit, as improper fit can lead to slippage at the limb-socket interface, resulting in discomfort, pressure sores, and long-term musculoskeletal complications. To address this issue, a fully integrated slippage detection system was developed to monitor an amputee’s daily activities and slippage occurrences to understand their prosthetic fit over time. The system consists of a prosthetic sock embedded with Interlink 406 flexible piezoresistive force-sensing resistors (FSRs). The sock, worn directly on the residual limb, continuously measures pressure at the limb-socket interface. Sensor data from six FSRs is sampled at approximately …

Applicability Of Syntropic Agriculture To A Semi-Arid Continental Climate: Alentejo To New Mexico, Arielle Nathan, Joana Dionisio Msc, João Serra, Joseph Lanning, Cátia Magro Dr.

Journal of Critical Global Issues

Conventional industrial agriculture has detrimental effects on the environment including pollution and overconsumption of water, soil degradation, and biodiversity reduction. An environmentally sustainable future of food production requires alternative methods that limit negative environmental consequences. Syntropic Agriculture (SA) is a promising farming alternative especially for arid systems at risk of desertification. New Mexico, USA, is a semi-arid continental climate in a prolonged period of drought and predicted to experience worsening agricultural conditions including desertification, wildfire intensification, and exacerbated water scarcity. The Alentejo region of Portugal has a Mediterranean climate with similar agricultural challenges. The agroecological transition project, Terra Sintrópica, located …

Water Rights Accounting And Distribution In Utah, Sarah Null, Bethany Neilson, Eileen Lukens, Eryn Turney, Utah Division Of Water Rights

Watershed Sciences Faculty Publications

This white paper summarizes how the Utah Division of Water Rights (WRi) administers water rights through the coordinated processes of water distribution and accounting. Water distribution involves apportioning divertible flow in river systems by adjusting diversions and reservoir storage. To account for and distribute water effectively, WRi must first determine the amount of water available for diversion each day, then prioritize water rights when water supply is insufficient to satisfy all demands. WRi has developed specialized tools and models to support this process.

This paper was developed through a collaboration between WRi and Utah State University to produce a report …

(R2120) Flexible Group Service Map/Ph/1 Queueing Model With Working Vacation And Optional Service, G. Ayyappan, S. Kalaiarasi

Applications and Applied Mathematics: An International Journal (AAM)

There are many uses of queues, where services are provided in groups; these types of queues are widely studied in the literature. In this paper we examine a particular queueing model wherein the services are provided in groups and the group size may be less than or equal to the size initially fixed. The arrival follows a Markovian arrival process. The service time of each individual customer follows phase type distribution. The maximum of each customer’s individual service time within a group is defined as the group’s service time. At the service completion moment if there are fewer customers than …

The Equity Implications Of Pecuniary Externalities On An Electric Grid, Charles Sims, Gasser G. Ali, J Scott Holladay, Tim Roberson, Chien-Fei Chen, Islam H. El-Haddad

Civil Engineering Faculty Publications

The adoption of rooftop photovoltaic (PV) systems can create upward pressure on retail electricity rates as utilities are forced to spread their fixed costs of generation and transmission across a smaller customer base. Since high-income households are more likely to purchase PV systems, low-income households may be disproportionately impacted by these rate increases. Using a novel combination of agent-based computational economic modeling and a choice experiment of rooftop solar adoption, we show how this pecuniary externality between low- and high-income customers increases low-income electricity bills by 10% in an area with some of the highest poverty rates in the United …

Using Composable Nfts And Blockchain For The Creation Of Ev Battery Digital Passports With Sustainability And Traceability Features, Haya R. Hasan, Khaled Salah, Ahmad Mayyas, Ahmad Musamih, Ibrar Yaqoob, Mohammed Omar, Raja Jayaraman

Industrial Engineering: Faculty & Staff Publications

Greenhouse gas emissions and carbon footprints have surged dramatically, with the transportation industry being a major contributor. While the UN aims to adopt zero-emission vehicles by 2040, the demand for electric vehicles (EVs) raises sustainability concerns about sourcing earth metals for batteries. Digital passports have emerged to track a product's lifecycle, composition, certifications, origin, and recyclability. However, existing EV battery passport systems lack sufficient traceability, immutability, auditability, and are prone to manipulation due to their centralized nature. In this paper, we propose a decentralized blockchain-based digital passport for EV batteries using composable Non-Fungible Tokens (NFTs) to ensure traceable, tamper-proof records …

Zero-Knowledge Proofs For Anonymous Authentication Of Patients On Public And Private Blockchains, Mohammad Madine, Khaled Salah, Raja Jayaraman, Ibrar Yaqoob

Industrial Engineering: Faculty & Staff Publications

In recent years, the healthcare sector has been increasingly challenged in securing patient identities and medical records on blockchain due to rising privacy demands and strict regulatory requirements. Although advanced techniques like self-sovereign identity and zero-knowledge proofs (ZKPs) show promise, these solutions fail to limit unwarranted patient data disclosure effectively. In this paper, we propose a ZKP-based solution that combines STARKs and anonymous credentials to enable anonymous authentication and enhance privacy across both public and private blockchains. Leveraging transparent ZKP schemes and anonymous credentials, our approach ensures unlinkability by preventing the correlation of multiple patient interactions. We present sequence diagrams …

Integrating Due Process Into Large Language Models., Joshua Paul Johnson

Electronic Theses and Dissertations

This research investigates the ability of large language models (LLMs) to recognize due process issues. Due process is a legal concept focused on the protection of the individual during interactions with government when life, liberty, or property are being impacted. Due process presents both substantive and procedural aspects that are challenging to incorporate into generative artificial intelligence. Through assessing model performance, creating benchmarking techniques, retrieval-augmented generation (RAG), and fine-tuning, this work seeks to measure due process recognition performance and improve performance in identifying due process issues. The results of evaluating larger parameter LLMs such as from Google, Meta, and OpenAI …

Isolated Dc-Dc Converter For An Ev Microgrid, Oscar Yu, William Leiker

Electrical Engineering

This product is a redesign of a DC-DC buck-boost converter which utilizes a new topology, the flyback converter, for use in an electric vehicle (EV) as a microgrid. The main driver behind the redesign is to provide electrical isolation between elements in the microgrid. The EV microgrid consists of the battery, motor, external DC and AC ports, and the power electronics (DC-DC converter and AC-DC inverter) which were designed and built in previous senior projects. Using EV’s as microgrids can help relieve stress from the main power grid caused by charging electric vehicles. Implementing EV’s as a microgrid enables the …

Ai-Optimized Resource Management In Next-Gen Wireless Networks, Fatemeh Lotfi

All Dissertations

Next-generation wireless networks must deliver highly adaptive, scalable, and intelligent connectivity to satisfy the heterogeneous demands of emerging services, including enhanced mobile broadband, massive machine-type communications, and ultra reliable low latency applications. The Open Radio Access Network (O-RAN) paradigm has emerged as a key enabler of this vision, introducing openness, virtualization, and artificial intelligence (AI)-driven control into the RAN ecosystem. O-RAN’s disaggregated architecture facilitates multi-vendor interoperability and empowers intelligent management through the RAN Intelligent Controller (RIC). However, achieving real-time, autonomous, and generalized optimization in such a dynamic environment remains a significant challenge due to its distributed nature, non-stationary traffic, and …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …