Digital Commons Network^™

Efficient Methods And Algorithms For Analyzing Stochastic Systems, Mohammad Ahmadi

USF Tampa Graduate Theses and Dissertations

This dissertation addresses the challenges of stochastic analysis of safety-critical systems with biological components, where unexpected behavior can lead to catastrophic events. Two fundamental challenges hinder the analysis of such systems: their typically large or infinite state spaces, and the extreme rarity of error states of interest. While Monte Carlo simulation can analyze biochemical systems without storing the state space, accurately estimating rare event probabilities becomes computationally prohibitive. Conversely, probabilistic model checking excels at analyzing extremely low probability events but becomes impractical for systems with large or infinite state spaces due to memory constraints.This work proposes two main contributions to …

Price-Based Dispatch In Engineered Truckload Trucking Networks, Don Taylor

International Material Handling Research Colloquium

No abstract provided.

Grid-To-Belt High Throughput Sorter, Yossi Bukchin, Ilan Estrugo, Tal Raviv

International Material Handling Research Colloquium

No abstract provided.

Concepts For The Use Of Knowledge-Based Engineering In Intralogistics System Planning: Dynamic Layouting, Alexander Ortner-Pichler, Christian Landschützer

International Material Handling Research Colloquium

No abstract provided.

Advancements In Human Action Recognition In Manual Material Handling Using Machine Learning, Jesus Jimenez, Joni Mccawley, Francis A. Mendez Mediavilla, Abhimanyu Sharotry

International Material Handling Research Colloquium

No abstract provided.

Thermal Design Overview, Utah State University Space Dynamics Laboratory

Space Dynamics Laboratory Publications

Preface

• Introductions
• Work Based on "Small Satellite Thermal Modeling Guide, Initial Release, July 2022"
• Air Force Research Laboratory Space Vehicles Directorate (AFRL/RVSV)
• Purpose
• Introduce methods/concepts to develop and analyze a small satellite thermal model
• Understand why thermal modeling and thermal analysis are important
• Understand common pitfalls
• Learn about available resources

The Role Of Langmuir Circulation In Coastal Flows Driven By Wind, Waves And Tides, Thathsarani Dilini Herath Herath Mudiyanselage

USF Tampa Graduate Theses and Dissertations

Langmuir Circulation (LC) is a wind and wave-driven process and is a key driver of vertical mixing and transport in the ocean. In coastal shelf regions, LC can span the entire water column, linking surface and bottom boundary layers and amplifying turbulent mixing. However, the influence of LC on vertical mixing and cross-shelf transport in shallow, tidally forced coastal waters remains poorly understood. This dissertation addresses this knowledge gap by developing a novel modeling framework based on the Reynolds-Averaged Navier–Stokes (RANS) equations, offering a computationally efficient alternative to more resource-intensive Large Eddy Simulations (LES).

The proposed RANS-based approach is first …

Construction And Application Of A Tcn-Lstm-Svm-Based Time Series Prediction Model For Water Inflow In Coal Seam Roofs, Liu Xuan, Ji Yadong, Zhu Kaipeng, Zhao Chunhu, Li Kai, Li Chaofeng, Yuan Chenhan, Li Panpan, Yan Pengzhen

Coal Geology & Exploration

Background The accurate prediction of mine water inflow plays a significant role in the prevention and control of water hazards and the safe and efficient production in coal mines. Methods To construct a prediction model of water inflow in mines under threat of water hazards from extremely thick sandstones aquifer in West China, this study investigated a typical mine (also referred to as the studied mine) severely affected by such water hazards in the Binchang mining area of Shaanxi Province. The correlation between the mining footage and water inflow of the mining face was selected as the characteristic variable for …

The Borehol Wall Image Digital Description Method Of The Overlying Rock Structural Planes Evdution Process In Deep Mining, Wang Jinchao, Zou Junpeng, Li Shenghai, Wang Chao, Li Xiaobin

Coal Geology & Exploration

Objective In China, as mineral resource mining is increasingly expanding towards the deep parts of the Earth, the safe and efficient exploitation of deep resources has become a major strategic and technological challenge at the national level to be addressed urgently. Understanding the movement patterns of mining-affected strata in deep environments will assist in improving the intelligent prevention and control of mine disasters, thereby ensuring the safe and efficient exploitation of deep resources. Methods Targeting the complex and diverse forms of the overburden’s structural planes in deep mining, as well as a lack of characterization methods tailored to the evolutionary …

Experimental Investigation Into Waterproofing Performance Of Cement Mortar Incorporating Nano Silicon, Nasiru Zakari Muhammad, Muhd Zaimi Abd Majid, Ali Keyvanfar, Arezou Shafaghat, Ronald Mccaffer, Jahangir Mirza, Muhammad Magana Aliyu, Mujittafa Sariyyu

Faculty Articles

Water ingress and penetration of aggressive fluids undermines the integrity of many concrete structures. For this reason, optimal performance of such structures up to their designed life cannot be guaranteed. This study introduces nano silicon as an alternative waterproofing admixture for increasing life span of cementitious materials, due to its non-vulnerability to deterioration, which is common to traditional surface coating solutions. Therefore, nano silicon was characterized using Field Emission Scanning Electron Microscope (FESEM), Energy Dispersion Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and surface Zeta potential. The Central Composite Design (CCD) tool was adopted to plan the …

Throughput Of Ascon Compared With Popular Iot Encryption Algorithms, Mitchel R. Harvey (Ryan), Andrew M. Kaiser, Garrett W. Hoiness

Military Cyber Affairs

No abstract provided.

Anomaly Detection Of Network Layer Attacks Against Cyber Physical Systems Using Machine Learning And Deep Learning Techniques, James Alger, Michael Tu

Military Cyber Affairs

This research paper presents the analysis of using machine learning and deep learning algorithms on detecting anomalous network traffic in Cyber-Physical Systems (CPS). Using a real PLC CPS-based system, normal and anomalous network traffic will be captured using Wireshark. The research analyzes a DDoS attack. The focus of the research is to identify the most effective feature combinations and evaluate them on ML and DL models. The emphasis is on enhancing detection strategies rather than exploiting device vulnerabilities. The detection of network attacks often involves handling a vast array of high-level features. Previous studies (Li & Chasaki, 2022) apply machine …

The Digital Battlefield: Safeguarding Military Drones Against Cyberattacks, Jason Ashong, Arun Venkitanarayanan, Benjamin Yankson

Military Cyber Affairs

The Internet of Battlefield Things (IoBT) is an advanced network of interconnected devices that significantly enhance military operations through real-time data exchange and situational awareness. While IoBT offers tactical advantages like improved surveillance, reconnaissance, and operational effectiveness, it also introduces substantial cybersecurity risks. Adversaries can exploit vulnerabilities within these networks, potentially compromising mission integrity and national security. This research examines the cybersecurity measures of commercial drone controllers and their correlation with military devices. It aims to enhance future vulnerability assessments with advanced tools and approaches to better secure critical military operations. The study highlights the need for robust security architectures …

Using Blockchain Technology To Help Secure America's Defense Critical Infrastructure, Vimal Buck, Aerin Krebs, Brynn Hillard, Jakob Gerha, Joseph Lutma, Srikar Maduposu, Ted Allen

Military Cyber Affairs

Critical water infrastructure in the United States faces increasing cybersecurity threats from state-sponsored actors, with potentially devastating consequences for national security, economic stability, and public health. (Cybersecurity and Infrastructure Security Agency, 2025). This infrastructure supports defense critical assets and is actively being targeted by various state-sponsored hacking groups, which poses a major concern for civilians and military alike. K. Herath (personal communication, February 24, 2025) reported being aware of two attacks on Ohio water systems during his tenure as Cybersecurity Strategic Advisor to Ohio Governor Mike DeWine.

Water is essential to everyday life and defense and presents as a high-value …

Network And Multipath Traceroute Visualization, Cameron Makowski

Military Cyber Affairs

TraceCam introduces a new paradigm in network path analysis, leveraging GPU-accelerated WebGL visualization, advanced traceroute integrations, and AI-driven insights to transform complex routing data into actionable intelligence. Early prototypes have demonstrated significant improvements in performance, clarity, and multi-path discovery, overcoming traditional limitations in traceroute analysis. By incorporating retrieval-augmented language models and enriched metadata sources like IPinfo.io, TraceCam enables automated anomaly detection, contextual explanations, and rapid root-cause analysis, enhancing operational efficiency. The platform’s architecture ensures scalability and adaptability, supporting deeper investigations and real-time situational awareness. Future development will focus on clustering-based anomaly detection, expanded geographic visualizations, and enhanced AI-generated analysis to …

Characterizing Cyberattacks Against Operational Technology Infrastructures Through The Lens Of Attack Flows, Sherman Kettner, Caleb Chang, Ekzhin Ear, Shouhuai Xu

Military Cyber Affairs

Operational Technology (OT) infrastructures play a critical role in modern society and economy. However, their increasing connectivity with public networks such as the Internet has made them vulnerable to cyberattacks, much like traditional Information Technology (IT) systems. In particular, cyberattacks against OT infrastructures remain relatively underexplored and little understood. In this paper, we aim to deepen our understanding of cyberattacks against OT infrastructures. For this purpose, we propose a methodology, including novel cybersecurity metrics to analyze the attack flows of these attacks in an end-to-end fashion, which allows us to draw useful insights. We demonstrate the utility of the methodology …

The Evolution Of Global Gold And Copper Trade Networks, Oleksandr Hulianskyi

Northeast Journal of Complex Systems (NEJCS)

Gold and copper have emerged as two of the most vital commodities in global trade. Despite serving distinct purposes, their international trade networks reveal interconnected patterns, critical to understanding the dynamics of global economics. This paper studies these attributes and their evolution during the last 36 years for both metals and finds correlations between them. The first part of the research is focused on the sustainability of networks through efficiency and robustness indexes; the second part is dedicated to interconnectedness – the Louvain and Bayesian SBM algorithms, partition, and modularity instruments are used. Community detection algorithms provide valuable insights into …

Tweaking Ml-Kem (Kyber) And Ml-Dsa (Dilithium), Kumar Rahul

Master’s Dissertations

Lattice-based cryptography is the use of conjectured hard problems on point lattices in Rn as the foundation for secure cryptographic systems. Attractive features of lattice cryptography include apparent resistance to quantum attacks (in contrast with most number-theoretic cryptography), high asymptotic efficiency and parallelism, security under worst-case intractability assumptions, and solutions to long-standing open problems in cryptography. This work surveys the structure, security, and optimization potential of two leading lattice-based cryptographic schemes: ML-KEM (Kyber) and ML-DSA (Dilithium). Special attention is given to their applicability in government-oriented post-quantum cryptographic systems, focusing on performance, implementation considerations, and resilience against known quantum threats. In …

Replicating Associative Learning Of Rodents With A Neuromorphic Robot In An Open-Field Arena, Tianze Liu, Kang Jun Bai, Hongyu An

Michigan Tech Publications

This study emulates associative learning in rodents by using a neuromorphic robot navigating an open-field arena. The goal is to investigate how biologically inspired neural models can reproduce animal-like learning behaviors in real-world robotic systems. We constructed a neuromorphic robot by deploying computational models of spatial and sensory neurons onto a mobile platform. Different coding schemes—rate coding for vibration signals and population coding for visual signals—were implemented. The associative learning model employs 19 spiking neurons and follows Hebbian plasticity principles to associate visual cues with favorable or unfavorable locations. Our robot successfully replicated classical rodent associative learning behavior by memorizing …

Limb Light - Interactive Lighting Control, Joseph Pandit, Matthew Tran

Computer Science and Engineering Senior Theses

The progression of stage lighting in the modern age has significantly influenced the immersive experience of the audience. Through events like Daft Punk’s 2006 Cochella performance, lighting has become more pivotal to performances in every genre. However, interactive, customized lighting remains inaccessible to small and mediumscale performers. The cost of hiring a lighting director or pre-programing each song is simply too much. Current cost effective solutions, like sound-activated effects, lack in both quality and real-time emotional responsiveness.

This thesis presents an interactive lighting control system designed to bridge this gap and create a novel creative tool. Our approach integrates MIDI-triggered …

Next-Generation Biomaterials For Load-Bearing Tissue Interfaces: Sensor-Integrated Scaffolds And Mechanoadaptive Constructs For Skeletal Regeneration, Rahul Kumar, Kyle Sporn, Pranay Prabhakar, Phani Paladugu, Akshay Khanna, Alex Ngo, Chirag Gowda, Ethan Waisberg, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

SKMC Student Presentations and Publications

Advancements in load-bearing tissue repair increasingly demand biomaterials that not only support structural integrity but also interact dynamically with the physiological environment. This review examines the latest progress in smart biomaterials designed for skeletal reconstruction, with emphasis on mechanoresponsive scaffolds, bioactive composites, and integrated microsensors for real-time monitoring. We explore material formulations that enhance osseointegration, resist micromotion-induced loosening, and modulate inflammatory responses at the bone-implant interface. Additionally, we assess novel fabrication methods-such as additive manufacturing and gradient-based material deposition-for tailoring stiffness, porosity, and degradation profiles to match host biomechanics. Special attention is given to sensor-augmented platforms capable of detecting mechanical …

Wind Tunnel Experiment On Wind-In Duced Vibration Performance Of Arch-Shaped Inclined Steel Bridge Tower In Construction Free-Standing State Using Ae Roelastic Model, Xu Peijun, Deng Fei Yun, Chen Shixuan, Zhang Jiren

Journal of China & Foreign Highway

This paper presented a wind tunnel experimental study on the wind-induced response characteristics of a rectangular-sectioned arch-shaped inclined steel bridge tower during the construction free-standing stage.A 1:50 scaled aeroelastic model was employed to conduct experiments at different wind yaw angles β (0°‒180°).The experimental results indicate:① under the uniform flow field,the tower in its free-standing state does not experience galloping when the bridge ’s wind speed reaches 60 m/s;② under the uniform flow field,the tower exhibits bending vortex-induced vibrations (VIVs ) along the bridge direction or transverse to the bridge direction.However,the amplitudes of the tower top displacements associated with these VIVs …

Analysis Of Mechanical Properti Es Of Integral Jacking Basket Arch Bridge During C Onstruction, Chen Tao, Qiu Jingkui, Wang Ji

Journal of China & Foreign Highway

Taking the Xindian Bridge in Ni ngbo as the background,this paper analyzed the mechanical properties of the integral jacking basket arch bridge during construction.Midas finite element software was used to establish the spatial model of the main bridge,and the deviation of the suspender force and support reaction force of the completed bridge from the design was 1.84% and 1.8%,respectively.The maximum deviation of the displacement calculation of the tie beam at the bridge completion stage was 22 mm,and the maximum deviation of the displacement of the arch rib at the same stage was ‒ 12 mm,which showed that the finite element …

Technical Communication Instruction Partnership With Engineering Faculty, Ashley S. Mcguire, Michael M. Lipscomb

Libraries Professional Work

Graduate students in STEM fields are often expected to communicate – both in writing and orally – at a professional level by the time they submit their theses and dissertations. Unfortunately, many graduate students lack opportunities to learn how to do that in a STEM setting. An informal review of US programs revealed that many offer writing courses modeled on traditional composition courses, which are not necessarily directed to the needs of STEM students. Further, many of these courses provide a series of isolated learning modules with little continuity or encouragement to revise and in which technological writing assistance is …

Awe Data Status, P.-Dominique Pautet, Anh Phan, Ludger Scherliess, Yucheng Zhao, Jiarong Zhang, Dallin Tucker, Connor Waite, Pedro Sevilla, Russell Kirkham, Harri Latvakoski, Jacob Adams, Keith Paskett

Space Dynamics Laboratory Publications

SDL Presentation on the AWE data status.

Board # 271: Nsf Iuse 2315777: Training Engineering Students To Be Better Learners: A Course-Integrated Approach, Huihui Qi, C. Pilegard, Minju Kim, Saharnaz Baghdadchi, Curt Schurgers, Alex M. Phan, Marko Lubarda

Psychology Faculty Articles and Research

Learning is a lifelong process exercised within and beyond the classroom, and a vital skill in almost all technical professions. Engineers, in particular, are impacted by rapidly evolving technologies and practices that require continuous learning and adaptation long after their training and the initial transition into their professional careers. However, despite the critical role of learning in their academic success and profession, engineering students experience academically rigorous and challenging courses with minimal emphasis or conscious focus on learning strategies that power effective learning. Often-used learning strategies such as rereading, highlighting, repetition, and memorization are intuitive for many students, yet do …

Empowering Engineering Students To Become More Effective And Self-Regulated Learners Through Course-Integrated Learning Strategies Intervention: A Pilot Study In A Solid Mechanics Course, Huihui Qi, Richard Eugene Vallejo Jr., Changkai Chen, Minju Kim, Alex M. Phan, Marko Lubarda, Celeste Pilegard, Curt Schurgers

Psychology Faculty Articles and Research

Learning is a lifelong process exercised within and beyond the classroom and a vital skill in almost all technical professions. Engineers, in particular, are impacted by rapidly evolving technologies and practices that require continuous learning and adaptation long after their training and the initial transition into their professional careers. However, despite the critical role of learning in their academic success and profession, engineering students experience academically rigorous and challenging courses with very little emphasis or conscious focus on learning strategies that power effective learning. Often-used learning strategies such as rereading, highlighting, repetition, and memorization are intuitive for many students, yet …

Context-Switch Attacks: Understanding And Mitigating The Threat To Llm Applications, Sydney Holder, Bivin Sadler

SMU Data Science Review

Large Language Models (LLMs) are transforming conversational AI, yet their dependence on prompt-supplied context exposes them to context-switch attacks that covertly steer dialogue toward sensitive or malicious ends. A 70 one-sided conversation transcript evaluation set was constructed spanning various fraudulent scenarios. Each transcript embeds adversarial patterns drawn while preserving natural conversational flow. We introduce a hybrid defense that pairs a BERT-based semantic-drift detector (cosine-similarity threshold = 0.70) with a curated keyword and hack-phrase scanner to counter these threats. In aggregate, the system delivered 100 % recall, intercepting every simulated phishing or data-harvesting attempt. The keyword layer achieved perfect precision, generating …

Leveraging Genai For Biometric Voice Print Authentication, Erica Brooks, Lijo Jacob, Lani Lewis, Gaurav Mittal, Shivam Negi, Faizan Javed

SMU Data Science Review

This paper presents the development of a secure voice authentication system that delivers an inclusive solution for all users, including those with disabilities. Leveraging a Text-Dependent Active Verification process, the system combines a spoken passphrase with voice biometric coefficients and audio vector embeddings for reliable user verification. A vector database is used to efficiently store data and perform similarity retrieval. Initially, the system achieves a 71% spoof detection accuracy, ensuring that only genuine samples proceed to the embedding stage, where it attains a 55.21% accuracy in vector embedding and similarity retrieval. Furthermore, this approach paves the way for user-specific voice-controlled …

Enhancing Fault Tolerance In Tmr Soft Risc-V Fpga Socs Through Failure-Driven Mitigation Strategies, Andrew Elbert Wilson

Theses and Dissertations

Field-Programmable Gate Arrays (FPGAs) leveraging soft processors, particularly those implementing the open-standard RISC-V Instruction Set Architecture (ISA), are increasingly important for space missions due to their adaptability and reconfigurability. However, their susceptibility to radiation-induced Single Event Upsets (SEUs) presents significant reliability challenges, necessitating robust fault-tolerant strategies such as Triple Modular Redundancy (TMR). This dissertation evaluates the effectiveness of TMR-based mitigation techniques for Linux-capable soft RISC-V System-on-Chip (SoC) implementations deployed on SRAM-based FPGAs operating in high-radiation environments. Using a combination of deterministic fault injection and neutron radiation testing, this work identifies critical residual single-point failure modes that persist in TMR-protected designs. …