Engineering Commons^™

Wettability Evaluation Via Contact Angle And Data Mining For Enhanced Oil Recovery, Syasya Wadihah Md. Ja’Afar, Bashir Busahmin

Journal of Sustainable Mining

The oil industry has used many enhanced oil recovery (EOR) strategies to increase crude oil production from reservoirs, particularly as production begins to fall. With a significant quantity of hydrocarbon reserves still existing in the reservoirs, improved oil recovery techniques have the potential to increase oil production, with wettability alteration playing a significant role. To date, there has been no comprehensive investigation of wettability in Brunei's sandstone reservoir. The goal of this research is to determine wettability by contact angle measurement and data mining approaches based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. …

Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.

The Stability Study Of Dna-Polymer Hybrids For Nanotechnology Applications, Ethan Kuehn, Milan Jebaraj

Miners Solving for Tomorrow Research Conference

DNA nanostructures have garnered increasing interest in their application as drug delivery vehicles. However, DNA is susceptible to degradation under physiological conditions. To remedy this, we have devised a novel method to coat DNA nanostructures with the polysaccharide chitosan (a natural derivative of chitin). Chitosan binds to DNA electrostatically and inhibits nuclease activity that would normally degrade DNA in a physiological environment. We used both agarose gel electrophoresis (AGE) and atomic force microscopy (AFM) to determine the stability of DNA before and after immersion in a simulated biological environment. Physiological conditions were mimicked by incubating the DNA in cell culture …

Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark

Miners Solving for Tomorrow Research Conference

Autonomous vehicles rely on low-latency, high-reliability data exchange for real-time perception and control. Disruptions such as packet loss, latency variation, protocol-level errors, and malicious interference can pose significant safety risks to both passengers and surrounding environments. This project aims to evaluate, quantify, and predict the survivability of autonomous vehicle systems to communication errors, with focus on 5G network environments. The impact of these communication impairments on vehicle stability and control will be investigated through high-fidelity cyber-physical simulation of the vehicle and its surrounding environment. Experiments designed to capture varying network conditions will be used to assess a broad range of …

A Wearable Mxene-Based Sweat Sensor For Real-Time Monitoring Of Inflammatory Biomarkers, Ariel Pilger

Miners Solving for Tomorrow Research Conference

Many conventional biosensing approaches rely on invasive sampling or bulky benchtop instrumentation, limiting their use in continuous and portable applications. This project focuses on the development of wearable sweat-based biosensors that enable non-invasive, continuous, and portable monitoring of physical, chemical, and biological markers. The system will be designed to target markers present in sweat and transduce the biochemical interactions into measurable electrical signals. These signals will be processed through integrated electronics to produce clear, interpretable outputs for users and medical professionals. Supporting circuitry including filters, amplifiers, and an independent power supply will be implemented as necessary to ensure signal accuracy, …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Theses

Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …

A Model Intercomparison Study To Investigate Mixing Characteristics In Non-Precipitating Stratocumulus Clouds, Fan Yang, Kyoung Ock Choi, Kamal Kant Chandrakar, Fabian Hoffmann, Pei Hou, Steve Krueger, Chunsong Lu, Mikhail Ovchinnikov, Yangze Ren, Shin Ichiro Shima, Peng Wu, Chongzhi Yin, Zeen Zhu, Seong Soo Yum

Michigan Tech Publications

Recent aircraft observations of marine stratocumulus clouds consistently showed that cloud microphysical relationships vary with altitude, indicating inhomogeneous mixing characteristics near cloud top and homogeneous mixing characteristics in mid-levels of clouds. Here, we conduct model intercomparison of an idealized, non-precipitating stratocumulus cloud to evaluate model consistency and examine whether simulations can reproduce the observed mixing characteristics. The results show that eleven large-eddy simulations with various dynamics and microphysics schemes show good agreement on the thermodynamical, microphysical, and dynamical properties of the stratocumulus-topped boundary layer in a steady state. The inter-model spread in steady-state liquid water path is significantly reduced compared …

Antimicrobial Performance Of Amorphous Vs. Crystalline La1-Xsrxcoo3 Perovskites, S. M. Au Shohag, Fahmida Akhter, Ahmed Touhami, Swati Mohan, Md. Wasikur Rahman, Mohammed Jasim Uddin

Physics & Astronomy Faculty Publications

Perovskite materials, with their unique crystal structure and chemical properties, are emerging as promising antimicrobial agents for potential biomedical applications. In this research, different weight percentages of Sr2 + doped amorphous and crystalline Lanthanum Cobaltite (La1-xSrxCoO3 defined as LSCO) (x = 0, 0.025, 0.05, 0.1, and 0.15) perovskite was synthesized by using a simple combination of sol-gel and molten-salt processes and characterized by X-ray diffraction (XRD), and scanning electron microscopy (SEM) ensures the uniform morphology of the materials. During antimicrobial study using the Kirby Bauer method, amorphous LSCO showed much better activity than crystalline LSCO against Escherichia coli, Vibrio …

Ecovoltaic Solar Energy Development Creates Novel Microclimate, Temperature, And Soil Moisture Patterns Under Solar Panels In A Warm Desert, Juan Pinos, Seth M. Munson, Claire C. Karban, Matthew D. Petrie

Life Sciences Faculty Research

Background As solar energy development expands in desert regions, new installation practices and solar technologies seek to balance ecosystem conservation and energy generation (ecovoltaics). The Gemini Solar Project, a large ecovoltaic facility located in the northeastern Mojave Desert, employed low impact installation methods to reduce disturbance of the desert ecosystem within arrays of bifacial panels mounted on solar tracking systems. We evaluated microclimate and environmental conditions across five locations: four within-facility microsites (underneath solar panels, east and west panel driplines, and interspaces between panel rows) and one in the undisturbed desert outside the facility. Results Under panel microsites experienced lower …

Downstream Effects Of Post Aerobic Digestion And Divalent Cation Treatment: Dewaterability, Phosphorus Mitigation, And Process Odors, Maya Marisol Quijano Garcia

Civil & Environmental Engineering Theses & Dissertations

This study evaluated post-aerobic digestion (PAD) with aeration, mixing, and divalent cation addition to improve phosphorus capture, dewaterability, and odor control in thermal hydrolysis process (THP)–treated anaerobic digestate at the Hampton Roads Sanitation District’s Atlantic Treatment Plant. A three-day PAD process was operated under constant air flow (5 LPM) and dissolved oxygen (DO)-setpoint (0.2 mg/L) aeration conditions with Ca(OH)₂ or Mg(OH)₂ dosing. Aeration and mixing alone increased polymer demand by 14–46 % relative to untreated influent, indicating enhanced extracellular polymeric substance release. Chemical conditioning partially mitigated this increase but did not restore polymer demand to baseline levels. Dewatered cake total …

Biocrude From Organic Waste And Its Conversion To Hard Carbon: Experimental And Modeling Study, Isamu Umeda

Civil & Environmental Engineering Theses & Dissertations

This study establishes a technical and theoretical foundation for the efficient conversion of organic waste into biocrude and high-value carbon materials, aiming to facilitate the industrialization of hydrothermal and solvothermal liquefaction. The dissertation research is structured as follows:

Chapter 2 developed a novel chemical kinetic model for the HTL of corn stover based on elemental balances (C, H, N, and O). By incorporating temperature, residence time, solid loading as an independent variable, the model successfully predicted product yields and properties, revealing that there was non-pseudo-first-order reaction pathways in the conversion of water soluble organics in aqueous phase (AP) to hydrochar. …

Dendrimer Nanogels With Built-In Free Radical Scavenging Enable Efficient Topical Delivery Of A Hydrophilic Antioxidant To Restore Lens Redox Balance For Cataract Treatment, Lin Qi, Huari Kou, Anna Chernatynskaya, Da Huang, Vimalin Jeyalatha Mani, Humeyra Karacal, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

Cataract is a leading cause of vision impairment worldwide and are primarily caused by oxidative stress that damages and aggregates lens proteins, leading to lens opacification. However, the eye's anatomical barriers limit the penetration and bioavailability of antioxidant therapies. To address this challenge, a dendrimer-based nanogel with a built-in reactive oxygen species (ROS)-scavenging capability developed by us was employed to deliver the antioxidant N-acetylcysteine (NAC) to the lens. NAC was loaded into a generation-5 PEGylated poly(amidoamine) dendrimer (G5-PEG-TK, termed the GPT) nanogel. The resulting NAC-GPT was characterized for its ROS-scavenging activity, bioavailability, and corneal permeability. The efficacy of NAC-GPT was …

Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Wednesday, April 1, 2026, Wright State University

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on April 1, 2026.

Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti

Doctoral Dissertations and Master's Theses

Mechanical loading is known to regulate bone remodeling by driving interstitial fluid flow which stimulates cells and drives nutrient transport within the trabecular network. In microgravity, the absence of mechanical stimulation or loading suppresses convective flow processes, causing diffusion-driven nutrient mixing and renewal, and accelerated bone loss. This thesis investigates how oscillation frequency and trabecular bone density jointly control nutrient mixing and wall shear stress within trabecular cavities.

A computational fluid dynamics (CFD) framework is developed in STAR-CCM+ using a soft-cap oscillation model that mimics cyclic compression. Three idealized trabecular morphologies are simulated across different frequencies to represent microgravity or …

Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla

Doctoral Dissertations and Master's Theses

While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and doubt induction, affects linguistic tone, objective accuracy, and internal calibration. A 1,080-trial experimental matrix evaluated six diverse models across factual, logical, coding, and cyber security domains. Analysis using the Kruskal-Wallis H-test revealed highly significant behavioral shifts across all measured dimensions, providing conclusive evidence that the applied frames exert a substantial influence on model performance.

The findings identify a distinct cognitive …

Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting, Madison Gleydura

Doctoral Dissertations and Master's Theses

Flash flood nowcasting in Central and Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at long range and signal blockage by mountains. GNSS-meteorology offers an established alternative for measuring precipitable water vapor and is currently integrated into several numerical weather models. Recent research demonstrates that commercial-grade GNSS receivers can produce tropospheric products comparable to those from geodetic-grade equipment. The gaps in mountain coverage can be addressed by developing a low-cost, self-contained embedded system that …

Competitive Reaction Pathways In The Fully Green Synthesis And Surface Modification Of Silver Nanowires Under L-Ascorbic Acid-Limited Conditions, Finley Neal

Honors Theses

Silver nanowires (AgNWs) are critical building blocks for transparent conductive films (TCFs) in flexible electronics, yet their commercial viability is hindered by environmentally hazardous, energy-intensive synthesis methods and limited intrinsic chemical stability. This study investigated a fully green, room-temperature (25℃) batch synthesis of pristine AgNWs using tannic acid as a biodegradable dual reducing and capping agent under strict kinetic pH control (pH 1.25). To enhance oxidative resistance, a subsequent surface modification protocol was evaluated to deposit a protective palladium (Pd) shell using L-ascorbic acid (LAA) as a secondary reducing agent. The pristine green synthesis yielded one-dimensional Ag nanostructures with a …

Aiw26s: Machine Learning Of Structured Data, Moumita Saha

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.

The Psychology Behind Ai-Generated Phishing And Social Engineering Attacks, A’Shya Reynolds

School of Cybersecurity Master's Level Projects and Papers

Cybercrime has evolved significantly with the integration of artificial intelligence (AI), transforming traditional phishing and social engineering attacks into highly sophisticated and personalized threats. While early phishing attempts relied on generic messaging and low success rates, modern AI-driven attacks leverage advanced data analytics, natural language processing, and behavioral prediction to manipulate victims more effectively.

This research examines how cybercriminals utilize AI to enhance psychological manipulation techniques in phishing and social engineering attacks, increasing victim susceptibility. Drawing from interdisciplinary literature in cybersecurity and psychology, this study explores key psychological mechanisms, including cognitive biases, emotional triggers, and decision-making processes that influence victim …

Construction Of A Deffi Sprayer: Using 3d Printer Methodology And Techniques For Cost-Effective Analysis Using Desi Mass Spectrometry Imaging, Ryan Karst, Savvy Stevens, Luke Amos, Logan Koester, Ethan Newbold, Karson Whitaker

Symposium Projects

Using 3D Printer Methodology and Techniques for Cost-Effective Analysis using DESI Mass Spectrometry Imaging

Agglomeration Of Particles Streaming Down A Zigzag, Juan Llamas

Posters - 2026

Zigzags or “letdown ladders” limit the flow speed of dry grains as they flow downward by gravity when loading silos, ships, barges, railcars, or trucks.

• Reduce cracking and shattering of grains.

• Increase grain shelf life.

• Increase grain resale value. • Increase ability of grain to germinate.

• Reduce generation of grain dust, an explosion and environmental hazard.

How can we design a zigzag that we know will not plug?

Ultra-High Vacuum Outgassing Characterization Of Thermally Processed Low-Carbon Steel For Advanced Particle Accelerator And Gravitational Wave Detector Applications, Aiman H. Al-Allaq

Mechanical & Aerospace Engineering Theses & Dissertations

This dissertation investigated AISI 1020 low-carbon steel as an alternative vacuum chamber material to conventional stainless steel for ultra-high vacuum (UHV) and extreme-high vacuum (XHV) applications. After a 400 °C/48 h bake, AISI 1020 tube chambers achieved a hydrogen outgassing rate of 2.4 × 10⁻¹⁶ Torr·L·s⁻¹·cm⁻², approximately 2,300 times lower than the prebaked 316L stainless-steel comparator, among the lowest hydrogen outgassing rates ever reported for an uncoated metallic vacuum chamber. Bare and magnetite-coated AISI 1020 chambers were then compared using throughput and rate-of-rise methods. The magnetite coating yielded 5× lower water outgassing at room temperature, but this advantage disappeared after …

Observations Of An Oscillatory Mechanochemical Reaction Between Tetrathiafulvalene And Chloranilic Acid, Alastair Deans

Physics Theses & Dissertations

Mechanochemistry is the study of chemical reactions driven by the input of mechanical en ergy in addition to thermal activation. Mechanochemical reactions from powders are carried out by manual grinding or milling using various types of ball mills, or in twin extruders. While mechanochemistry has great potential affording economically and environmentally advantageous “green” synthetic methods, a drawback is that its chemical mechanisms are not well understood. One example of such a reaction currently under study involves tetrathiafulvalene, an organic elec tron donor with two polymorphs (orange and brown), and chloranilic acid, an electron acceptor. Previous results show that neat grinding …

Optimization Of Niobium Film For Particle Accelerators And Quantum Applications, Bektur Abdisatarov

Electrical & Computer Engineering Theses & Dissertations

Niobium (Nb) films play a central role in superconducting technologies used in particle accelerators and superconducting quantum circuits. Optimizing the physical properties of Nb films is therefore critical for improving both radiofrequency (RF) performance in superconducting radiofrequency (SRF) cavities and coherence in superconducting qubits. This thesis investigates the relationship between Nb film microstructure, impurity content, and electromagnetic response across these two application domains.

For particle accelerator applications, we studied Nb films deposited using high-power impulse magnetron sputtering (HiPIMS) with DC bias onto a 1.3 GHz elliptical SRF cavity. Nb film cavities exhibit a pronounced medium-field Q-slope, limiting their achievable accelerating …

Radiation Protection Factor Research: The Keystone For Conventional-Nuclear Integration (Cni), Andrew W. Decker

Faculty Publications

This article briefly describes Defense Threat Reduction Agency (DTRA) vehicle Radiation Protection Factor (RPF) research and explains its critical role in enabling future Operations in a Nuclear Environment (ONE) and Conventional-Nuclear Integration (CNI) on behalf of the US Department of War (DoW).1 As such, the background and practical utility of RPF values is discussed, as well as the justification for renewed Army and DoW investment into RPF research to enhance Joint military planning, survivability, and lethality on tomorrow’s nuclear battlefields. Advances in DTRA RPF research directly strengthen US strategic and extended deterrence efforts and support all Agencies and Departments responsible …

On The Extreme Complexity Of Certain Nearly Regular Graphs, Gregory P. Constantine, Gregory C. Magda

Theory & Applications of Graphs

The complexity of a graph is the number of its labeled spanning trees. It is demonstrated that the seven known triangle-free strongly regular graphs are graphs of maximal complexity among all graphs of the same order and degree; their complements are shown to be of minimal complexity. A generalization to nearly regular graphs with two distinct eigenvalues of the Laplacian is presented. Conjectures and applications of these results to biological problems on neuronal activity are described.

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

Neutrosophic Sets In Neural Networks: Theory, Applications, And Challenges, Vladimir Simic, Dragan Pamucar, Hafiz Muhammad Athar Farid

Neutrosophic Systems with Applications

The integration of neutrosophic sets into neural networks presents a novel approach to handling uncertainty, indeterminacy, and falsity in data. Traditional neural networks typically operate under the assumption of precise and complete data, but real-world applications often involve noisy, incomplete, or ambiguous information. Neutrosophic sets extend fuzzy logic by incorporating three components: truth, indeterminacy, and falsity, allowing for a more nuanced representation of uncertain data. This paper explores the theoretical foundations of neutrosophic sets and their integration with neural networks, highlighting the challenges in computational complexity, training, and optimization. The paper also discusses the potential applications of neutrosophic neural networks …

Neutrosophic Probability With Dynamic Temporal Uncertainty (Nptu), Bhimraj Basumatary, Ashoke Kumar Brahma

Neutrosophic Systems with Applications

This paper introduces Neutrosophic Probability with Dynamic Temporal Uncertainty (NPTU), an extension of classical neutrosophic probability that incorporates the dimension of time. In classical neutrosophic probability, the degrees of truth, indeterminacy, and falsity are considered static. However, real-world uncertainties evolve, and their degrees change as new information becomes available. NPTU models these uncertainties dynamically, allowing for more accurate decision-making in time-varying environments. The paper explores key mathematical properties of NPTU, including entropy, distance measures, similarity measures, and Kullback-Leibler (KL) divergence, to quantify and compare temporal uncertainty states. The proposed framework is demonstrated through a case study on stock price prediction, …

Emergent Operator Logic: A Foundational Framework For Dynamic Reasoning And Generative Intelligence, Mona Gharib, Abduallah Gamal, Muhammad Nawaz, Basma Nasir

Neutrosophic Systems with Applications

This paper introduces Emergent Operator Logic (EOL), a framework that treats propositions as continuous operators $F_p:X \rightarrow X$ on a complete metric state space $( X,d )$ and evaluates truth after action via a continuous valuation $V:X \rightarrow [ 0,1 ]$. Logical composition is realized by three operator-level connectives: sequential $p \circ q$(causal order), parallel $p\parallel q$(1-Lipschitz cooperative blend), and the emergent synthesis $E( p,q ) = \frac12( F_p \circ F_q + F_q \circ F_p )$, which symmetrizes non-commuting actions. We provide a Hilbert-style proof system (sound), an algebraic semantics via E-algebras, and show that the category of E-algebras is …