Digital Commons Network^™

Research Synthesis Of Predicting Part 135 Accident Probability In Aviation: How The Bayesian Brain Ignores Declining Safety Standards, Jonathan R. Clarke

Journal of Aviation Technology and Engineering

Technological innovation has had an enormous effect on safety in aviation. However, in Part 135 operations, where technology is not as ubiquitous, the accident rates have plateaued. Human error is constantly misrepresented as being responsible for 70–80 percent of accidents, when it is clearly only one of several contributing factors. In commercial aviation, all accidents should be considered organizational failures, because by definition all defensive layers have been breached. Organizational failure, as it affects safety, should be identifiable and predictable from organizational behavior. Inevitably, in the aftermath of accidents the warning signs of poor behavior are seemingly obvious, yet there …

Recent Progress And Scientific Challenges In Wire-Arc Additive Manufacturing Of Metallic Multi-Material Structures, Sainand M. Jadhav, Sambhaji Kusekar, Akash Belure, Satyavan Digole, Abhijeet Mali, Muralimohan Cheepu, Manoj Mugale, Suhas Alkunte, Duckbong Kim

Faculty Articles

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by …

Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye

Faculty Publications

Stable and reproducible reference electrodes (REs) are essential for electrochemical systems operating in high-temperature molten salts, where consistent control of potential is required. This study uses three different solutes to investigate the development and evaluation of REs in eutectic LiCl-KCl at 773 K. The solutes tested were NiCl2, AgCl, and NiO, each prepared at multiple concentrations to assess stability, reproducibility, and saturation. Electrochemical stability was measured over three days using chronopotentiometry (CP), followed by open circuit potential (OCP), with cyclic voltammetry (CV) also integrated to monitor changes in electrochemical behavior over time. The CP-OCP approach established a Li+/Li redox potential, …

Dissolution Mechanism Of Nonionic Polyether Surfactants In Supercritical Co2, Ning Xu, Yanling Wang, Baojun Bai, Shizhang Cui, Zan Gao, Yu Zhang, Di Li, Wenjing Shi, Wenhui Ding, Peixu Ma

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polyoxyethylene ether is an efficient CO₂-philic compound with significant potential applications in CO₂ flooding, which requires CO₂-philic surfactants with high solubility in supercritical CO₂ (scCO₂). This study elucidates the molecular and atomic-level dissolution mechanism of the fatty alcohol polyoxyethylene ether (AEO) in scCO₂ by combining phase-behavior experiments and molecular dynamics simulations. The solubility of AEO in scCO₂ is measured using a semiconductor laser. AEO containing three polyoxyethylene (EO) groups exhibited the highest solubility in scCO₂.The solubility of AEO in scCO₂ decreased with an increase in the number …

Investigation Of A Stable And Saturated Reference Electrode Using Metal Chlorides And Oxides In Eutectic Licl-Kcl Molten Salts, Carlos Mejia, Devin Rappleye

Faculty Publications

Stable and reproducible reference electrodes (REs) are essential for electrochemical systems operating in high-temperature molten salts, where consistent control of potential is required. This study uses three different solutes to investigate the development and evaluation of REs in eutectic LiCl-KCl at 773 K. The solutes tested were NiCl₂, AgCl, and NiO, each prepared at multiple concentrations to assess stability, reproducibility, and saturation. Electrochemical stability was measured over three days using chronopotentiometry (CP), followed by open circuit potential (OCP), with cyclic voltammetry (CV) also integrated to monitor changes in electrochemical behavior over time. The CP-OCP approach established a Li …

Retracted: Efficient Multi-User Computation Offloading And Reducing Latency In Mobile-Edge Computing For Iot Applications, Sarmad T. Abdul-Samad, Osamah Al-Hwaidi, Ali Abd Al-Rasool Muslem

Iraqi Journal for Computer Science and Mathematics

Mobile Edge Computing (MEC) is an inventive paradigm for computing that has the potential to notably diminish latency and energy consumption by transferring computationally demanding jobs to edge clouds near intelligent mobile users. This investigation aims to reduce offloading and latency between multiple users and edge computing in the context of Internet of Things (IoT) applications in the fifth generation (5G) by utilizing an optimization algorithm called the Bald Eagle Search Optimization Algorithm. Although employing deep learning methods might increase time consumption and computational complexity, an edge computing system enables devices to transfer their demanding jobs to edge servers, decreasing …

Polymeric Nanocarriers Functionalized With Peptides For Improved Glioblastoma Targeting And Blood–Brain Barrier Permeability, Cristian Antonio Wieczorek Villas Boas, Aaron Priester, Buck E. Rogers, Anthony J. Convertine

Materials Science and Engineering Faculty Research & Creative Works

We report the synthesis of polymeric conjugates designed to penetrate the blood–brain barrier (BBB) and selectively bind glioblastoma (GBM) cells through reversible addition–fragmentation chain transfer (RAFT) polymerization. The resulting materials were engineered to contain peptide macromonomers for cell-specific targeting and integrated DOTA units to facilitate radiolabeling with copper-64 (⁶⁴Cu), yielding radiolabeled conjugates with greater than 95% radiochemical purity. In biodistribution assessments conducted in mice, C1C2 peptide-conjugated polymers showed significantly improved accumulation in brain tissue, supported by brain perfusion analyses confirming efficient BBB penetration. Additionally, flow cytometry evaluations demonstrated specific affinity of GBM-targeted polymer formulations toward U87 glioblastoma cells. …

Carbon-Infiltrated Carbon Nanotube Coated Ti6al4v Substrate Tensile And Torsion Raw Data, Jacquelyn Monroe, Brian Jensen

ScholarsArchive Data

This data set contains the raw tensile and torsional Instron measurements reported in Carbon-Infiltrated Carbon Nanotube Coating Effect on Bacterial Resistance and Ti6Al4V Substrate Material Properties. The data in these files was used to generate the stress–strain curves presented in the study.

U.S News & World Report 2025 Graduate Program Rankings, Unlv & Unr, Dre Boyd-Weatherly, Caitlin J. Saladino, William E. Brown Jr.

Higher Education

This fact sheet presents 2025 graduate program rankings for the University of Nevada, Las Vegas (UNLV) and for the University of Nevada, Reno (UNR) based on the data published in spring 2025 by U.S. News & World Report. The graduate program categories reported include business, education, engineering, fine arts, law, medicine and health care, sciences and mathematics, and social sciences and humanities.

Re-Engaging Driver Attention Using Chatgpt: A Multimodal Study On Stress Impact And Driving Performance, Alaa Zaki Elfiqi

Theses and Dissertations

Driving is considered a complex task that requires continuous focus and attention from the driver. Driving performance can also be impacted by changes in the driver’s stress level. However, limited research explores methods to address this challenge. With the current advances in Large Language Models (LLMs) and their ability to engage in human-like interaction, this study investigates the potential of using ChatGPT, designed to speak Egyptian Arabic, in re-engaging driver attention under different driving scenarios for low-stress and high-stress conditions within a virtual reality (VR) environment driving simulator. Drivers were asked to follow a leading car into two scenarios with …

Design And Evaluation Of An Electromagnetic Band Gap Structure For Self-Interference Reduction In Mmwave Full-Duplex Systems, Adewale Kehinde Oladeinde

Dissertations and Theses

Full-duplex (FD) wireless is a new technology that allows a device to transmit and receive at the same time and on the same frequency band. It has the potential to double the capacity and spectral efficiency of a wireless link compared to the family of conventional half-duplex wireless systems. The key challenge in implementing FD wireless communication is self-interference (SI): a node's transmitting signal generates significant interference to its receiver. Several previous studies have demonstrated the potential to reduce SI and develop FD radios; however, these studies are mostly limited to sub-6 GHz systems. Previous and on-going research explored various …

Development Of Turbulence Models For Prediction Of Hypersonic Flows Using Compressibility Corrections And Uncertainty Quantification With Emphasis On The Wray-Agarwal Model, Aidan Robert Murphy

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate prediction of high-speed compressible turbulent flows remains one of the most significant challenges in Computational Fluid Dynamics (CFD), especially in the realm of hypersonic vehicle design. These flow regimes involve significant aerodynamic heating and shock-wave boundary layer interactions (SBLI) which remain a significant challenge for the current CFD prediction capabilities. While Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES) provide high-fidelity solutions, their computational demands limit their usability, making the Reynolds-Averaged Navier-Stokes (RANS) equations an efficient alternative for many industrial aerodynamic applications. Traditional RANS techniques, while computationally efficient, often provide limited accuracy in high-speed flows due to the presence …

Photolysis Of Emerging Agricultural Applications Under Environmental Conditions, Kun-Pu Ho

McKelvey School of Engineering Graduate Student Theses & Dissertations

Novel agricultural applications are rapidly emerging to protect crops from weeds or pests in the US and worldwide. Isoxaflutole is a proherbicide considered agriculturally significant because it controls weeds that have developed resistance to other commonly used herbicides. In addition, RNA interference (RNAi) technology is regarded as a next-generation biopesticide because the technology has less toxicity to humans and more specificity to pests than traditional pesticides, which pose risks to the environment and the health of humans and livestock. However, we cannot disregard the possible risks of the emerging proherbicides and biopesticides to humans or non-target organisms. Therefore, the study …

Multi-Layer Support For Component-Based Cyber-Physical Systems Applications, Oren Bell

McKelvey School of Engineering Graduate Student Theses & Dissertations

Component-based design is a paradigm meant to aid in development of software applications by modularizing different functionalities of a system. This building-block approach is used extensively in cyber–physical and robotic systems. Common and established solutions to specific problems, such as perception nodes, state estimators, and motion planners, can be developed, verified, and reused as off-the-shelf modules. These modules may be integrated atop today’s heterogeneous hardware platforms, where an application can be distributed across GPUs, FPGAs, and CPU cores. When heterogeneous computational devices share the workload of a collection of components, the very act of integration may inject timing uncertainty. For …

Moment Ensemble Approaches For Estimation And Robust Quantum Control, Andre Luiz Paes De Lima

McKelvey School of Engineering Graduate Student Theses & Dissertations

Large-scale population dynamics governed by ensemble systems present significant challenges due to their inherently high dimensionality. Recent advances have demonstrated the effectiveness of moment-based methods (particularly those employing polynomial bases such as Legendre and Chebyshev polynomials) when integrated with optimization techniques for control design in ensemble systems. However, these methods have not been extensively explored for enhancing robustness against systematic noise, nor have they been widely applied to complex quantum systems involving multi-parameter configurations and entanglement phenomena. In this work, we extend the application of moment methods in ensemble systems through two projects. Initially by developing a Kalman filter analogue, …

Developing Aerosol Representation In Atmospheric Modeling, Inderjeet Singh

McKelvey School of Engineering Graduate Student Theses & Dissertations

Ambient aerosols affect climate and air quality in the Earth system. Global chemical transport models used to study these impacts require an accurate representation of aerosols in terms of shape, composition, and vertical distribution. For example, despite having a complex morphology, mineral dust is often treated as spherical particles in these models. This can lead to errors in optical properties calculations, trace gas retrievals, and heterogeneous chemistry. Similarly, inaccurate representation of the vertical distribution of smoke particles in these models can lead to uncertainties in air quality assessments. Aerosol composition also plays a critical role in determining radiative forcing and …

Development, Numerical Simulation, And Optimization Of Quiet Supersonic Transport Aircraft And Extension Of The Wray-Agarwal Algebraic Transition Model To Include Compressibility And Crossflow Effects, Dean Ryan-Simmons

McKelvey School of Engineering Graduate Student Theses & Dissertations

In the first part of this thesis, the goal of the research is to implement and extend multi fidelity methods for conceptual design and optimization of a commercial supersonic transport (SST). Most modern commercial aircraft operate at a cruise condition between Mach 0.7 and 0.9, as this is the optimal trade-off of flight efficiency, operational cost, and adherence of noise regulations for overland travel. Advancements in aviation propulsion fuel efficiency and design materials suggests a primary restraint on commercial supersonic transport is noise regulations. At speeds above Mach 1, the shock waves generated by the airframe are strong enough to …

A Control Theoretic Approach To The Stochastic Multi-Armed Bandit Problem With Applications In Hyperparameter Optimization, Jonathan Gornet

McKelvey School of Engineering Graduate Student Theses & Dissertations

Decision-making under uncertainty is a fundamental problem encountered frequently in many real-world applications. This challenge has been rigorously formulated as the Stochastic Multi-Armed Bandit (SMAB) problem, which consists of a learner interacting with an environment. For each interaction, the learner selects an action and then receives a reward from the environment based on the chosen action. The learner's objective is to maximize the accumulated reward over a set number of rounds. This thesis addresses the SMAB problem by leveraging the field of Control Theory and dynamical systems. We specifically focus on a SMAB environment where the rewards are the output …

Investigation Of Dependency Parsing Techniques For Digital Document Analysis Through Deep Learning Approach, Rekah D Ms

Theses and Dissertations

Digital document dependency parsing is a significant task in natural language processing. Dependency parsing supports verification of the grammatical correctness of a sentence besides enabling extraction of relevant documents. Inappropriate extraction of features may result in falsely parsing a document, leading to decreased accuracy. Machine learning methods have been employed to perform feature extraction. However, selecting pertinent features was never achieved which minimizes the time consumption and overhead.

Hence, novel machine learning and deep learning techniques have been designed in our work for accurate and computationally efficient digital document analytics through dependency parsing. Four different contributions have been proposed for …

Investigations Of Secure Memory For Vlsi Based Crypto System, Vijay Sai R Mr

Theses and Dissertations

Semiconductor technology is growing very rapidly in their architectural developments, involving the usage of processor and memory. Presence of memory, in general is a vital commodity in various devices which are almost embedded into human activity, from robust work stations to handy mobile phones. Security of data stored in memory is very important, and hence, observation must be made that these valuable data should not be thwarted by malicious means. Security in cache memory is a major issue in memory related applications such as smart cards and bio-metric implementations.

Cache, is a small and limited memory located between central processing …

Exploring Different Metal-Oxide Cathode Materials For Structural Lithium-Ion Batteries Using Dip-Coating, David Petrushenko, Thomas Burns, Paul Ziehl, Ralph E. White, Paul T. Coman

Faculty Publications

In this study, a selection of active materials were coated onto commercially available intermediate modulus carbon fibers to form and analyze the performance of novel composite cathodes for structural power composites. Various slurries containing polyvinylidene fluoride (PVDF), active material powders, 1-methyl-2-pyrrolidone (NMP) and carbon black (CB) were used to coat carbon fiber tows by immersion. Four active materials—lithium cobalt oxide (LCO), lithium iron phosphate (LFP), lithium nickel manganese cobalt oxide (NMC), and lithium nickel cobalt aluminum oxide (NCA)—were individually tested to assess their electrochemical reversibility. The cells were prepared with a polymer separator and liquid electrolytes and assembled in 2025-coin …

Beyond Single Metrics: A Holistic Benchmarking Framework For Low-Power Embedded Systems, Hassan Adam

UNLV Theses, Dissertations, Professional Papers, and Capstones

Modern embedded systems encounter a notable challenge in evaluation. While devices may meet traditional benchmarks, they often underperform in real-world applications due to neglected interactions at the system level. Current benchmarking suites, such as MLPerf Tiny and EEMBC ULPMark, evaluate specific metrics including computational throughput, energy efficiency, and memory usage. However, they do not consider the complex interdependencies that affect real-world performance. This thesis presents a benchmarking framework that concurrently evaluates multiple performance dimensions under realistic workloads, revealing system behaviors that are often hidden in conventional benchmarks.Through the comprehensive evaluation of three representative algorithms: Fast Fourier Transform, quantized neural network …

Integrated Uav Platform For Multi-Spectral, Thermal, And Eos Imaging In Wildfire Monitoring And Modeling, Md Shariful Islam

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents the design and development of a modular unmanned aerial vehicle (UAV) system based on a quadcopter platform for flexible and efficient wildfire-related multimodal image acquisition. Addressing key limitations in ecological UAV monitoring such as sensor inflexibility, time-consuming reconfiguration, and imprecise image georeferencing, the system introduces a versatile payload integration framework supporting three distinct imaging sensors: MicaSense Altum-PT, FLIR Vue Pro R, and Sony Alpha 6000.All onboard components, including the flight controller, autopilot software, GNSS module, motors and ESCs, were selected to optimize stability and payload performance. A gimbal-free, downward-facing mount simplifies field deployment, while custom integration enables …

Functional Biopolymers Applied To Sustainable Technologies In The Environment And Healthcare, Fengjie He

UNLV Theses, Dissertations, Professional Papers, and Capstones

Biodegradable polymeric materials (biopolymers) are naturally derived materials known for their excellent biocompatibility, biodegradability, sustainability, and versatile chemical functionality. They have attracted increasing attention in various applications as alternative to synthetic materials ranging from food packaging to tissue engineering. Meanwhile, with intrinsic advantages, biopolymers have also emerged as promising materials in addressing contemporary challenges in both biomedical and environmental fields. Motivated by the significant potential of biopolymers and the growing need for sustainable materials, my research focuses on the design and engineering of biodegradable polymers with novel modification methods and application directions. In this work, two representative biopolymers are selected: …

Bio-Inspired Electroactive Polymer (Eap) Sensors For Surface And Canal Flow Sensing In Dynamic Environments, Nazanin Minaian

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nature can often create some of the most efficient and elegant solutions to complex problems, and engineering stands to benefit greatly from these time-tested designs. One of the more sophisticated examples of this is the lateral line system in fish: a distributed network of superficial and canal neuromasts that enables aquatic species to detect fluid disturbances with remarkable precision. This dissertation leverages that biological framework to explore the potential of electroactive polymers (EAPs), aiming not just to replicate structure, but to emulate function.Two classes of EAPs form the basis of this work: electroactive plasticized polymer gels (EPPGs) and ionic polymer-metal …

Investigating Information Extraction And Language Models In Medical Domain Text Processing, Pouyan Nahed

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation demonstrates that carefully adapted language-model pipelines can transform unstructured clinical-trial and pharmacological prose into reliable, low-latency structured data. Four interconnected studies support this claim.Tri-AL platform. An open-source dashboard ingests all 440 k+ ClinicalTrials.gov records—including every historical revision—into a normalized schema and parses the 20 GB XML archive over 10x faster than a BeautifulSoup baseline, while exposing hooks for demographic analytics and supporting integration of user-defined modules. Clinical trial summarization. An encoder–decoder model is trained on 57k description–summary pairs to condense clinical trials into a few sentences. ROUGE evaluation shows a 20% improvement over the baseline, while graph-based evaluation …

Autonomous Uav Swarm Formation Utilizing Gradient-Driven Contour Mapping For Radiation Source Localization, Edgar Amalyan

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents a drone swarm for radiation mapping to aid source localization. The Department of Energy advocates employing UAVs for this task, but existing approaches remain inefficient and impractical in real-world scenarios. Three custom drones are built and flight-tested. A control algorithm to follow a contour, a constant-intensity path, is designed using a gradient fit. By knowing the source’s direction, the drone swarm can fly in the optimal trajectory at every step, leaving nothing to assumption. A program is created that implements formation flight and autonomous navigation. It is tested via a software-in-the-loop simulation utilizing radiation sources and detectors …

The Dropbot: Design And Development Of A Custom Drone For Precision Water Drop Penetration Time (Wdpt) Testing, Mugundan Prakash

UNLV Theses, Dissertations, Professional Papers, and Capstones

Assessing the hydrophobic characteristics of soil is vital for understanding soil wettability or soil-water interactions, particularly in post-wildfire environments where water repellency can significantly impact ecosystem recovery, water infiltration, and erosion control. One key metric in soil wettability studies is the Water Drop Penetration Time (WDPT) test, which evaluates the hydrophobicity of soil and guides land treatment strategies. This thesis presents the design and development of DropBot, a custom-built drone platform engineered for the precise delivery and analysis of water droplets in WDPT tests.The DropBot, a custom drone, integrates a lightweight, 3D-printed frame with a self-leveling platform, enabling consistent droplet …

Development Of An Access Charge Framework For High-Speed Rail Incorporating Rail Replacement Costs And Dynamic Train Characteristics, Nitesh Kumar Yadav

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis develops a framework to determine track access charges for shared high-speed rail corridors, with a focus on rail replacement cost driven by train-induced loads. The method explicitly accounts for both static loads, resulting from axle weights, and dynamic loads that arise from train speed and track geometry, particularly curvature. Train characteristics such as axle load, operating speed, frequency of service, and number of wheels are integrated with track parameters, including curve radius, to calculate the total vertical load. These loads are used to estimate the cumulative tonnage threshold for rail replacement and the resulting service life of the …

Nanofluid-Enhanced Hvac&R Systems (2015–2025): Experimental, Numerical, And Ai-Driven Insights With A Strategic Roadmap, Aung Myat, Md Mashiur Rahman, Muhammad Akbar

Mechanical and Manufacturing Engineering Faculty Research

Heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems account for a significant share of global energy demand, prompting intensive research into advanced thermal enhancement techniques. Among these, nanofluids—colloidal suspensions of nanoparticles in base fluids—have shown promise in boosting heat transfer performance. This review provides a structured and critical evaluation of nanofluid applications in HVAC&R systems, synthesizing research published from 2015 to 2025. A total of 200 peer-reviewed articles were selected from an initial pool of over 900 through a systematic filtering process. The selected literature was thematically categorized into experimental, numerical, hybrid, and AI/ML-based studies, with further classification by fluid …