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Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Spectral Modeling Of Electromagnetic Radiation From Power Converters, Regan A. Varner

Theses and Dissertations

Switching power converters are increasingly utilized in contemporary electronics. They are becoming more compact and operate at higher frequencies, which contributes to radiated electromagnetic interference (EMI). This EMI is important to quantify for electromagnetic compatibility of the converters with other nearby systems. In this thesis, analytical models have been developed for both ideal and non-ideal switching waveforms, employing piecewise functions to describe time-domain waveforms, with their corresponding frequency spectra derived and compared to empirical spectra. The results demonstrate that the comparisons with measured frequency data exhibit agreement with the analytical models up to approximately 25 MHz. Additionally, our analysis indicates …

Towards Robust Bmocz Schemes For Non-Coherent Wireless Communication, Anthony Joseph Perre

Theses and Dissertations

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical …

Dissociation Of Subjective And Objective Measures Of Trust In Vehicle Automation: A Driving Simulator Study, Samuel Petkac, Tetsuya Sato, Kun Xie, Yusuke Yamani

Psychology Faculty Publications

Trust is a crucial factor that influences human-automation interaction in surface transportation. Previous research indicates that participants tend to display higher levels of subjective trust toward lower-level automated systems compared to high-level automated systems. However, administering subjective trust measures via questionnaires can interfere with primary task performance, limiting researchers' ability to measure trust continuously in a real-world manner. In the current driving simulator study, 25 drivers using an advanced driving system (ADS) were randomly assigned to either an active (L2) or passive (L3) automated driving condition. Participants experienced eight near-miss driving scenarios with or without obstructions in a distributed driving …

0894: G. W. “Jerry” Sutphin River Transportation Collection, 1832-2024, Marshall University Special Collections

Guides to Manuscript Collections

Gerald W. “Jerry” Sutphin was a nationally recognized river historian from Huntington. He graduated from Mullens High School and Marshall University and became an army officer. Sutphin worked for and retired from the United States Army Corps of Engineers before spending twenty years operating his own business, Visual Information Ltd. The author of Sternwheelers on the Great Kanawha River, he also wrote a number of articles and contributed to numerous publications with words and/or photographs. Sutphin provided historical presentations on the Delta Queen and other large sternwheel excursion boats and served as a consultant for several documentaries and exhibits. Sutphin …

Ai-Driven Autonomous Manufacturing: A Novel Taxonomy, Vision-Guided Planning, And Diversity-Aware Active Learning Frameworks, Ibrahim Yousif

Theses and Dissertations

Manufacturers face two opposing challenges: the escalating demand for customized products and the pressure to reduce lead times. Current manufacturing equipment, although reliable, operates at the limits of its technology and lacks adaptability to dynamic environments. This trade-off has been described as the optimal degree of automation, a threshold beyond which further automation incurs more cost than benefit. Smart manufacturing has introduced adaptive, data-driven systems, but many deployments still lack the contextual adaptability and autonomous decision-making required to handle unplanned disruptions. This underscores the need for intelligent, autonomous systems capable of real-time adaptation without costly reconfiguration, minimizing human intervention during …

Rate-Dependent Interlaminar Shear Characterization In Solid-State Extruded Ultrahigh Molecular Weight Polyethylene Film Composites, Frank David Thomas Jr.

Theses and Dissertations

Ultrahigh Molecular Weight Polyethylene (UHMWPE) cross-ply [0o/90o] thin film composites are emerging as an effective material for impact applications due to their high axial strength-to-weight ratio and favorable delamination properties. Mode-II interlaminar shear (ILS) fracture-driven delamination has been shown to be a significant energy absorption mechanism. Therefore, accurately characterizing ILS behavior as a function of strain rate in these composites is essential to inform computational models. Since these composites are significantly thinner and weaker in both interlaminar shear and transverse tension than traditional carbon fiber epoxy composites, standard ILS Mode II test methods/specimens such as end-notched flexure (ENF) are expected …

Calculating Surface Current Velocities From Video Generated From A Near Forward-Facing Camera, Colby James Weeks

Theses and Dissertations

This work presents a camera system for estimating surface currents. A combined camera and IMU system provide high resolution images and high precision orientation information, respectively. This eliminates the need for leveling and enables forward looking operation. The hardware stack includes a Lucid Vision Triton TRT162S monochrome camera, an SBG Ellipse D with dual antenna GNSS for precise pose, and an Nvidia Jetson Orin for acquisition and processing. The Ellipse D provides a hardware trigger at 10 Hz to time stamp each frame and to synchronize images with inertial measurements.

A camera calibration step estimates the intrinsic camera parameters and …

Ge0.95sn0.05 On Si Avalanche Photodiode With Spectral Response Cutoff At 2.14 Μm, Justin Michael Rudie, Xiaoxin Wang, Rajesh Kumar, Grey Abernathy, Sylvester Amoah, Steven Akwabli, Hryhorii Stanchu, Perry C. Grant, Bao-Hua Li, Wei Du, Jifeng Liu, Shui-Qing Yu

Electrical Engineering and Computer Science Faculty Publications and Presentations

GeSn-based avalanche photodiode operating in shortwave infrared wavelength was demonstrated in this work. A separate absorption and charge multiplication structure was employed to take advantage of long wavelength absorption in GeSn and low impact ionization ratio of Si. Due to lattice mismatch between Si and GeSn that would degrade GeSn material quality if with direct growth, a 240-nm-thick Ge buffer was utilized, which simultaneously allows for the transporting photo generated electrons from the GeSn absorber to Si multiplication layer. Spectral response showed the cutoff wavelength beyond 2.1 mu m at room temperature. Dark current and capacitance-voltage measurements indicated a punch-through …

Air Traffic–Collegiate Training Initiative Program Feasibility In Kentucky, Gayle Marks, Bryan Gibson

Kentucky Transportation Center Research Report

Each day, Federal Aviation Administration (FAA) air traffic control specialists (ATCSs) handle over 44,000 flights and oversee 29 million square miles of the United States National Airspace System. However, staffing shortages have grown more acute over the past 10 years, which has led to delayed and cancelled flights, a higher number of close misses over a short period of time, and frustrating air travel experiences. While the FAA has redoubled its efforts to recruit more ATCSs, it has limited training capacity. To expand training options available to prospective ATCSs, the FAA is working with postsecondary educational institutions to expand its …

Investigation Of Its-Cvo Technologies, Mallory Brown, Andrew Martin, Valerie Keathley-Helil, Jennifer Walton

Kentucky Transportation Center Research Report

Staff shortages and reduced budgets have made transportation agencies increasingly reliant on intelligent transportation systems (ITS) for commercial motor (CMV) vehicle enforcement activities. Technologies such as license plate readers, US Department of Transportation (USDOT) number readers, weigh-in-motion scales, static scales, and preclearance systems like PrePass and Drivewyze help automate enforcement and free up personnel to focus on inspecting those vehicles most likely to pose compliance and/or safety risks. To document adoption rates of different technologies, researchers surveyed transportation agencies, vendors, and law enforcement agencies. Surveys responses provided useful insights into how jurisdictions are approaching the use of advanced technologies to …

Aligning Aviation Safety Reporting System Anomaly Codes For Crew Communication And Coordination With Human Factors Taxonomies, Jennifer Rose Herr

Doctoral Dissertations and Master's Theses

This study addresses the lack of theoretical grounding and definitions for the Aviation Safety Reporting System (ASRS) anomaly codes, particularly those related to pilot communication and coordination errors. To improve the conceptual consistency and analytical usability of ASRS data, the research developed a framework that maps ASRS codes to three established theory-based human factors taxonomies: the Human Factors Analysis and Classification System (HFACS), Threat and Error Management (TEM), and Aviation Causal Contributors for Error Reporting Systems (ACCERS). The study used qualitative text mining to systematically code communication and coordination errors submitted by Part 121 pilots for a stratified sample of …

A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane

Doctoral Dissertations and Master's Theses

This research presents a quantitative performance comparison between light detection and ranging (LiDAR) and vision-based sensing for real-time maritime object detection on autonomous surface vessels. Using Embry-Riddle Aeronautical University’s (ERAU) Minion platform and 2024 Maritime RobotX Challenge data, this study evaluates the detection of six maritime object categories using two representative models. YOLOv8 provides a neural network vision-based method, and GB-CACHE provides a deterministic LiDAR-based method. Both models have been previously demonstrated to run in real time on uncrewed surface vessels (USVs). The evaluation methodology encompasses multi-sensor calibration, real-time performance analysis, and the introduction of a late-fusion strategy in the …

Adaptive Control For Spacecraft With Flexible Appendages With Unknown Parameters, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed …

Research On The Construction Of Domain Knowledge Graph For Assisted Decision Making And Its Scenario-Oriented Application, Hao Xu, Linlin Ge, Yan Zhang, Sanhong Deng

Journal of Scientific Information Research

[Purpose/significance] This research constructed a domain knowledge graph and its scenario-oriented application framework for decision support at four levels: the data foundation layer, the key technology layer, the domain knowledge graph construction layer, and the scenario-oriented application layer. This framework aims to provide systematic support for knowledge discovery.

[Method/process] Based on the construction of a domain knowledge graph and its scenario-oriented application framework for decision support, this research focuses on the improvement of models and performance evaluation for fine-grained entity and relationship extraction at the discourse level within texts. The optimal model is selected to construct a domain knowledge graph. …

Freer Arrows And Why You Need Them In Haskell, Grant Vandomelen, Gan Shen, Lindsey Kupur, Yao Li

Computer Science Faculty Publications and Presentations

Freer monads are a useful structure commonly used in various domains due to their expressiveness. However, a known issue with freer monads is that they are not amenable to static analysis. This paper explores freer arrows, a relatively expressive structure that is amenable to static analysis. We propose several variants of freer arrows. We conduct a case study on choreographic programming to demonstrate the usefulness of freer arrows in Haskell.

Defective Mil-88b(Fe) Metal-Organic Frameworks: Peculiar Photocatalysts For Enhanced Degradation Of Organic Pollutants, Samira Sadeghi, Ahmad Najafidoust, Seyedeh Zahra Haeri, Masoumeh Zargar

Research outputs 2022 to 2026

Environmental pollution, particularly water contamination from organic compounds like synthetic dyes, poses a major global challenge. In this study, defective MIL-88B(Fe) MOFs under varying solvothermal conditions (70–150 °C) for 12 and 24 h were synthesized to enhance methylene blue (MB) and methyl orange (MO) dye degradation. The MOF synthesized at 100 °C for 24 h showed the highest efficiency, achieving 97 % and 40 % degradation of MB and MO, respectively, in 60 min due to increased porosity, surface area, and optimized crystal growth along the [100] direction. A 24-h synthesis produced well-formed particles with the highest surface area and …

Reengineering Resilience: Bio-Resilience Bonds For Financing Microbial Infrastructure And Climate Equity, Reece Buckley

COP30

This policy proposal introduces Bio-Resilience Bonds (BRBs), a performance-based financial instrument designed to monetise microbial ecosystem services as measurable climate infrastructure. Microbial ecosystems are crucial for climate resilience, yet they are often overlooked in mainstream adaptation f inance frameworks. Their ability to regulate carbon and nitrogen cycles, reduce methane emissions and enhance soil and water stability (Delgado-Baquerizo et al., 2016) makes them essential assets for climate mitigation and adaptation. With global adaptation needs exceeding £2.7 trillion (UNEP, 2024), this oversight indicates a systemic failure to recognise biology as a form of infrastructure. BRBs transform microbial outputs into localised key performance …

Impacto De La Inteligencia Artificial En La Educación Superior. Guía Reflexiva, Jairo Eduardo Márquez Díaz

Ingeniería

La inteligencia artificial (IA) está revolucionando la educación superior en diversas formas como, por ejemplo, la personalización del aprendizaje, la creación de tutorías inteligentes y el análisis de aprendizaje. Este libro se presenta como una herramienta valiosa para todos aquellos interesados en comprender y aprovechar las oportunidades que la ia ofrece en el campo de la educación superior. Con un enfoque equilibrado y exhaustivo, esta publicación pretende servir como una guía integral para profesores y estudiantes que buscan entender cómo la ia está transformando la enseñanza y el aprendizaje en la actualidad. A lo largo de sus páginas, aborda diversos …

Stabilized Weak-Gradient Discontinuous Finite Elements With Optimal Error Estimates For Second-Order Elliptic Pdes, Aymen Laadhari

Mathematical Modelling and Numerical Simulation with Applications

This work introduces an accurate finite element approach employing a new stabilized discrete weak gradient, designed for second-order elliptic problems on arbitrary conforming meshes. We formulate the approach within a discontinuous Galerkin framework and derive a consistent and coercive bilinear form. Appropriate error analysis on a model problem confirms optimal convergence. Building on the core analysis, we extend the method to more challenging settings, including time-dependent heterogeneous scenarios and a biophysically realistic optimal-control model of photobleaching in the budding yeast cell. We further illustrate the versatility of the weak-gradient construction by applying it to an unsteady level-set equation relevant to …

Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa

Neutrosophic Systems with Applications

A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …

Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal

Neutrosophic Systems with Applications

Owing to integrate GenAI chatbots to enhance productivity across various tasks, this research presents T2NN-RANCOM-MARCOS multi-attribute decision-making model, which employs Type-2 Neutrosophic Number (T2NN) to handle uncertain data, the RANCOM method, distinguished by its easy, highly repeatable, less time consuming, more appropriate to deal with problems exceeds 5 criteria with expert errors to assign subjective weights to criteria and MARCOS method to evaluate and rank eight GenAI chatbots against six main criteria are included 23 sub-criteria: Quality of Information, Understanding and Reasoning, Expression Style and Persona, Safety and Harm, Trust and Confidence and Economic are primarily derived from QUEST evaluation …

Use Matters: How Different Ways Of Using Chatgpt Drive Ai Acceptance And Solutionism, Florian Golo Flaßhoff, Fabian Anicker, Frank Marcinkowski

Human-Machine Communication

Artificial intelligence is central to solutionism—the vision of a world where all major problems are solved through technology. This study theorizes about how human–AI communication shapes attitudes toward AI and influences the formation of public opinion, sparking solutionist imaginaries. We empirically examine the attitude formation resulting from the non-simulated use of an unmanipulated conversational model in a controlled laboratory experiment. Using a between-subjects design, participants engaged in three semi-structured 20-minute sessions with ChatGPT, providing a novel perspective on the effects of its use. The findings reveal that mere use of ChatGPT causally increases AI acceptance; however, its impact significantly depends …

Generative Ai: Another Chapter Of Human-Machine Communication, Seungahn Nah, Patric R. Spence

Human-Machine Communication

This editorial introduces a special issue of Human-Machine Communication that explores how generative AI reshapes the communicative relationship between humans and machines. It highlights emerging research on technology use, education, interpersonal dynamics, and trust in AI-generated content, emphasizing that generative AI’s significance lies not in novelty but in the social negotiations it provokes around meaning, authority, and credibility.

Retracted: Adaptive Crossover And Mutation Mechanisms For Enhanced Lpb Algorithm Performance, Abbas M. Ahmed, Tarik A. Rashid

Iraqi Journal for Computer Science and Mathematics

This study proposes a more effective concept of Learner Performance-based Behavior (LPB). It is a new metaheuristic algorithm based on how the university admission process is done for high school students in various departments. The adaptive crossover and mutation methods were incorporated into the LPB algorithm as part of an investigation. The goal is to enhance convergence and significantly improve the quality of the solutions. The aLPB (adaptive-learner performance-based Behaviour) method stands out because it sets the crossover and mutation parameters based on the performance of the parent solutions. Thus, the proposed technique achieves a balance between exploration and exploitation …

Iot-Enabled Machine Learning Framework For Prediction Of Eutrophication, Hocine Dai, Akli Abbas, Houssam Eddine-Othman Lachemat, Aicha Aid

Iraqi Journal for Computer Science and Mathematics

This study presents an innovative predictive monitoring framework that integrates the Internet of Things (IoT) with advanced machine learning (ML) techniques to model the relationship between oxidized nitrate (NOX)—employed as the sole predictor—and chlorophyll a (CHLA), a key proxy for algal biomass. By utilising a single optimally selected parameter, the approach significantly reduces sensor deployment complexity and instrumentation costs, while minimising data acquisition and computational requirements. Logarithmic and Yeo-Johnson transformations were applied to the predictor and target variables, respectively, to address distributional skewness and enhance variance homogeneity. An optimised Random Forest model demonstrated strong predictive performance, achieving a coefficient of …

A New Approach For Multiprocessor System-On-Chip Application Scheduling In Multi-Objective Flow Shops, Tahani Jabbar Khraibet, Bayda Atiya Kalaf, Ahmed Abbas Jasim

Iraqi Journal for Computer Science and Mathematics

The flow shop scheduling problem in Multiprocessor-System-on-Chip (MPSoC) architectures presents challenges for traditional optimization algorithms, especially when addressing multiple conflicting objectives. Hence, advanced optimization approaches are required to tackle these objectives simultaneously. Therefore, this research aims to propose and evaluate a new optimization approach based on the integration of the Fire Hawk Optimizer with the Smart Battery Scheduling Algorithm (FHO-SBSA) to address the multi-objective (make span, CPU time, global average delay, network throughput, and total energy consumption) flow shop scheduling problem in MPSoC systems. To evaluate the performance of the FHO-SBSA optimization approach, two benchmark applications were selected, with ten …

Engineering, Innovation, And God’S Creation, Fred Haan

University Faculty Publications and Creative Works

Took place at YPPH Annual Retreat 2025 Coram Deo In the Presence of God Reflections on Biblical Christian Worldview at Pelita Harapan University on 9/26/2025 in Jakarta, Indonesia.

Wmu Maritime Affairs Conference 2025 : Transforming A Maritime Future : Digitalization And Decarbonization, World Maritime University

Books

No abstract provided.