Engineering Commons^™

Creating Open Educational Resources With Artificial Intelligence, Serena Scalzi

UNLV Best Teaching Practices Expo

The adoption of artificial intelligence is becoming widespread in higher education. AI-driven technology has the ability to support academic and administrative faculty in designing and delivering course content. As a Part-Time Instructor in the College of Education, I used AI to enhance my teaching practice by creating course resources for my class, CIT 647 Creating Online Learning Environments. These open educational resources, developed through a reflective teaching practice facilitated by the UNLV Teaching and Learning Commons, promote equitable, inclusive education.

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Enhanced Parametric Approach For Solving Interval-Valued Trapezoidal Neutrosophic Linear Fractional Programming Problems, Hamiden Abd El- Wahed Khalifa H.A.Khalifa, Moodi Abdulrahman Abdullah Al-Rajeh, Sultan S. Alodhaibi

Neutrosophic Systems with Applications

Neutrosophic sets (NSs) generalize the classical versions, by providing a flexible framework capable of representing incomplete, inconsistent, and unclassified data that frequently arises in practical decision frameworks. In this study, a linear fractional programming (LFP) problem with uncertain parameters is investigated. All coefficients in the objective function (OF) as well as the left- and right-hand sides of the constraints are represented using fully trapezoidal neutrosophic numbers (NNs). By employing a suitable score function, the proposed neutrosophic LFP model is transformed into an equivalent scalar LFP problem. Subsequently, a parametric solution procedure is established to regulate the neutrosophic optimum solution. This …

Gauss Elimination Method For Solving The System Of Neutrosophic Linear Equations, Elsayed Badr, Shokry Nada, Saeed Ali, Aya Rabie

Neutrosophic Systems with Applications

This paper proposes a unified computational framework for solving linear systems under trapezoidal Neutrosophic uncertainty. The system is formulated as A( I )x = b( I ), where both the coefficient matrix and the right-hand side vector incorporate an indeterminacy parameter I, expressed as A( I ) = A₀ + IA₁ and b( I ) = b₀ + Ib₁. A decomposition strategy is developed to separate the model into deterministic and indeterminacy components, yielding a solution of the form x( I ) = x₀ + Ix₁. The deterministic component is obtained via …

Implementation Of Kansei Engineering Method In Designing Spreadable Cheese Packaging, Novi Purnama Sari, Mega Analisa, Suci Puji Lestari, Khofifah Nur Amalia

Makara Journal of Technology

Some spreadable cheese packaging uses flexible plastic without additional features and easily damaged boxes. This packaging causes several problems, such as difficulty in re-storage, loss of product information due to damaged box packaging, wasteful use of packaging materials, and making the product less hygienic. The purpose of this study is to develop packaging that focuses on consumer emotions. The packaging was developed using the Kansei Engineering method, supported by Principal Component Analysis (PCA) as a determinant of the design concept, and Quantification Theory Type 1 (QTT1) to identify design elements. This study produced 46 packaging samples and 40 Kansei words. …

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Thesis/ Dissertation Defenses

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …

The Impact Of People Interests In Evaluating The Open Public Spaces' Quality In The City Centre, Hasan Hadi, Adil Al-Saidi, Haitham Alshamari

HBRC Journal

The quality of open public spaces in city centres significantly affects people's satisfaction and responses to their built environment. The significance of these areas allow people to assess their performance. this paper addresses the issue of People's interests that affect their evaluation of public urban spaces in city centres. The research applied an ontological methodology that is people's experiences determine the spatial quality of the public spaces in city centres. In order to discover and assess the seven value variables, it recommended diagnosing a random sample of users as a group (A) and (B). The urban space in the historic …

Mapping The Void In Electric Vehicle (Ev) Adoption Research: Uncovering Lack Of Socio-Economic Study In The Global South, Satvik Pandey, Rahul Tiwari, Rajat Soni

Mansoura Engineering Journal

Electric Vehicles (EVs) are considered an effective contemporary alternative to Internal Combustion Engine (ICE) vehicles. Research in the domain of EV is being conducted globally across a variety of fields; among them, our study explored research on consumer adoption. Going through the bibliometric analysis of the data taken from the Scopus database, what came to our attention is the minimal amount of work that is done on understanding consumers of EVs. From the literature, we found that consumer preferences are shaped through the influence of several parameters related to EVs, and this influence varies according to the consumer’s socio-economic and …

Study Of Complex Biological Systems Through Ai-Empowered Metabolomic Analysis And Modeling, Runyu Zhao

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation establishes an integrated framework that leverages artificial intelligence (AI) and advanced metabolomics to overcome the "complexity bottleneck" in microbial engineering, specifically addressing the global crises of plastic waste and carbon emissions. By framing the research within the complex biosystems for effective bioproduction and bioremediation, this work develops novel strategies to engineer and analyze biological systems for a circular bioeconomy. In the "Build" phase (Chapter 2), the study addresses the instability of synthetic microbial consortia. By utilizing calcium-alginate hydrogel compartmentalization, the research successfully decouples the growth of the phototroph Synechococcus elongatus from its heterotrophic partners (P. putida and Y. …

Inference-Time Scaling For Robust And Adaptive Computational Imaging, Yuyang Hu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging has transformed fields such as medical imaging, computational photography, and remote sensing by combining physical measurement models with advanced image reconstruction algorithms. Two major paradigms have driven significant progress: model-based deep learning (MBDL), which integrates learned priors with physics-based data consistency, and generative models, especially diffusion models, which capture complex image distributions and enable posterior sampling for uncertainty quantification. Despite their success, most existing methods still operate under static inference: they rely on fixed pretrained priors, predetermined sampling procedures, and a fixed forward model during reconstruction. This rigidity limits their robustness in the presence of distribution shift, complex …

Individualized Models For Perception And Cognition, Dominic Marticorena

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation develops individualized models of perceptual and cognitive behavior, inferring latent capacities from limited data with sufficient efficiency, precision, and generality for person-level prediction. In perception, a nonparametric Bayesian framework for adaptive psychophysics is extended from audition to vision, producing an estimator that recovers dense individualized contrast sensitivity profiles through variational inference, a generalized kernel, and information-guided stimulus selection. A multitask extension enables simultaneous estimation of multiple psychometric fields by exploiting shared latent structure. Transferring this inferential logic to cognition, where relevant dimensions must be supplied by task design rather than physics, requires new measurement infrastructure. A Minecraft-based platform …

Optimization Of A Point Absorber Wave Energy Converter (Wec), Rutwa Dilipkumar Nagar

Electronic Theses and Dissertations

This study examines the performance and optimization of a point absorber wave energy converter with a partially submerged spherical float. A comprehensive open-source computational framework integrates frequency-domain hydrodynamic analysis with time-domain simulation using Capytaine, BEMIO, and WEC-Sim. Hydrodynamic coefficients such as added mass, radiation damping, and excitation forces are calculated and integrated into the governing equation of motion using the Cummins formulation. A parametric analysis varies the float diameter and geometric configurations across several cases. Hydrodynamic coefficients and response amplitude operators are assessed to analyze system behavior and resonance characteristics. Results indicate consistent trends in normalized added mass, with radiation …

Multicriteria Analysis Of Vehicle Exhausts Emission Using Fuzzy Analytic Hierarchy, Sunday Ayoola Oke, Ibraheem Adedotun Abdul, Ismaila Badmus, John Rajan, Swaminathan Jose, Adekunle Adetayo Yekinni, Kabiru Alani Olaiya, Mofoluwaso Kehinde Adeniran, Pandiaraj Benrajesh

Makara Journal of Technology

This study employs the fuzzy analytic hierarchy process (FAHP) to identify the critical factors and their degree of relevance to the vehicle emission process. Its innovation lies in the potential to blend ambiguity and uncertainty with the established AHP. FAHP transforms information into a defuzzification state through signal-to-noise ratios, normalization, and pairwise comparison. The principal parameters considered are revenue, sold packing units, CAGR, packing materials, consumption, and CO2 emissions (A, B, C, D, E, and F, respectively). From the normalized defuzzified weight result, consumption (Parameter E) is the best (normalized weight, 0.8685917), while CO2 emissions (Parameter F) was the worst …

Improving Transfer Portal Decision-Making Through A Microsoft Excel Optimization Model, Peyton Steffes

Honors Projects

The creation of the transfer portal has increased the mobility of collegiate athletes, giving players the autonomy to switch teams throughout their career. As a result, the roster development process has become more complex, as coaches are tasked with the challenge of recruiting from the transfer portal, which involves an extensive decision-making process. Coaches not only have to evaluate a substantial pool of players, but they also must consider the following constraints they are under: scholarship budget, roster spots available, and positional needs. To simplify this decision-making process, this analysis includes the results of a Microsoft Excel data optimization model …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

Optimized Bombax Ceiba/Jute Hybrid Epoxy Composites For Enhanced Thermal Insulation Performance, Shadman Ahmed Khan, Naeem Ahmmed, Md Tanvir Hossain, Abdullah Ibn Asheque, Md Ariful Islam, Md Abdul Kader, Md Sohel Rana, Sakib Masud

Michigan Tech Publications

The development of sustainable hybrid natural-fiber composites provides a practical way toward lightweight materials with tailored mechanical and thermal performance. In this study, Bombax ceiba (BC)/jute hybrid epoxy composites were fabricated using a stacked preform followed by compression molding, and the effect of fiber blending ratio on mechanical, thermal, and microstructural properties was systematically investigated. Three compositions-40/60, 50/50, and 60/40 BC/jute by weight-were evaluated. Mechanical testing showed that the J50 composite, with a balanced fiber ratio, exhibited superior flexural strength and impact resistance, indicating effective hybrid synergy and improved stress transfer between fibers and the matrix. Thermogravimetric analysis showed that …

Problems With Small Drinking Water Systems In Developing And Developed Countries: How Do They Compare?, Kurt Kesteloot

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation compares the factors that drive the long-term functionality of small drinking water systems (serving fewer than 10,000 people) in developing and developed country contexts, with a focus on groundwater supplies. Using regression analysis in SAS and complementary fuzzy-set Qualitative Comparative Analysis (fsQCA) for developing countries, the study integrates two datasets: 23 Engineers Without Borders project surveys (90+ variables across 14 countries) and a multi-year National Park Service inspection dataset (approximately 1,561 systems; 7,460 recorded deficiencies, enriched with U.S. Census ZIP-code aggregates). In developing countries, statistically significant predictors of success include government cash contributions (odds ratio [OR] ≈ 67.6), …

Quantitative Study Of The Predictive Correlational Relationship Between Passenger Knowledge, Attitudes, And Behaviors In Aviation Ground Safety Events, Nikkolas Howard Kraay

Doctoral Dissertations and Projects

This study examined the relationships between passenger cabin safety knowledge, attitude, and behavior using the Knowledge-Attitude-Behavior (KAB) framework as the guiding theoretical model. Although prior aviation safety research has demonstrated a linear progression from knowledge to attitudes to behaviors, these studies were conducted primarily in Asian cultural contexts. The present study investigated whether this linear sequence would hold within a larger cultural passenger population. A predictive correlational design was used, and data was collected through an online survey completed by 194 adult airline passengers. The instrument measured cabin safety knowledge, attitudes, and behavioral intent, along with demographic characteristics.

Data was …

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Thesis/ Dissertation Defenses

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being user-friendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …

Anchorage And Bond Behavior Of Smoothsurfaced Nitinol-Sma Rebars, Mostafa Basha

Thesis/ Dissertation Defenses

The anchorage and bond behavior of smooth-surfaced Shape Memory Alloys (SMAs) is investigated in this thesis, but specifically, the focus will be on Nitinol (Ni-Ti). Nitinol has distinctive properties, including Superelasticity Effect (SE) and Shape Memory Effects (SME). These properties make Nitinol bars suitable for civil and seismic engineering applications that require resilience and durability. However, Nitinol rebars possess a smooth surface, making it difficult to achieve adequate bonding and anchorage, potentially altering their load-carrying abilities. This inadequate anchorage and bonding restrict their use in the field of structural and seismic engineering. The main aim of this study is to …

Project Management Practices In Manufacturing: An Analytical Case Study, Margaret Randle, Robert Reynolds

Honors Capstones

Global industries are undergoing significant transitions in organizational models, technological innovation, and non-economic indicators of product quality, including sustainability and operational efficiency. The current workforce needs to not only develop competency of these technical skills, but also an adaptive, system-oriented approach to problem-solving as well. This case study, which highlights a manufacturing company’s project of increasing production efficiency, presents concepts learned through the textbook Project Management: Achieving Competitive Advantage by Jeffrey K. Pinto. The study thoroughly breaks down the full project lifecycle and the integration of systems of people, data, and initiatives in a framework that can be used to …

Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens

Senior Honors Theses

One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …

Dynamic Cushioning Performance And Sustainability Implications Of Recycled-Content Expanded Polyethylene Foams, Jay Singh, Pratish Patel, Emily Recinos, Paulina Goncharov

Industrial Technology and Packaging

The transition toward circular materials in protective packaging requires empirical evidence that recycled-content foams can satisfy stringent shock-attenuation requirements. This study evaluates the dynamic cushioning performance of expanded polyethylene (EPE) foams formulated with 0%, 30% and 40% recycled content under controlled impact conditions following ASTM D1596. A total of 1100 drop tests were conducted across combinations of density, thickness, static load and drop height representative of distribution hazards in parcel and freight supply chains. Peak transmitted acceleration (G) was measured as the primary performance response variable.

Across the configurations evaluated, recycled-content EPE foams exhibited cushioning performance comparable to virgin materials. …

Molecular Catalysts For Electrochemical Nitrogen Activation Toward Sustainable Ammonia Synthesis, Jin-Xiu Han, Hao Xue, Xian-Biao Fu

Journal of Electrochemistry

Homogeneous electrocatalytic nitrogen reduction reaction (NRR) provides a powerful framework to interrogate molecular nitrogen-fixation pathways under mild conditions. By tuning the metal center, ligand architecture, and reaction medium, these systems enable capturing key intermediates and delivering mechanistic insight at the molecular-level resolution. Nevertheless, advances remain constrained by highly reduced operating potentials, intense competition from the hydrogen evolution reaction (HER), limited durability in turnover, and inadequate long-term stability.

In this review, we take electron delivery to the molecular active site as the guiding principle for organizing homogeneous electrochemical N₂ activation and transformation. We classify reported systems into direct electron transfer …

Water-Driven Solid Electrolyte Interphase Governs Continuous-Flow Ammonia Electrosynthesis, Peng-Bo Liu, Sheng-Liang Zhai, Ji Huang, Zhong-Shuo Zhang, Jie Zeng, Shao-Feng Li

Journal of Electrochemistry

Flow-cell architectures have emerged as a powerful platform for continuous and stable lithium-mediated nitrogen reduction (Li-NRR), enabling ambient-condition electrochemical ammonia synthesis and offering a promising alternative to Haber-Bosch processes. However, Li-NRR is exceptionally sensitive to trace water, and even minor variations in water content can profoundly alter interfacial chemistry. Here, we systematically investigate how initial water concentration affects Li-NRR performance in a continuous-flow cell. Excess water drives the formation of a thick solid electrolyte interphase (SEI) layer, which may impede nitrogen access to metallic lithium and hinder lithium-ion transport. As a result, the ammonia Faradaic efficiency collapses from ~61% to …

Insertion Of Noble Metal Free Cathodic Catalyst Layer With Fe-N-C Catalyst For Boosted Performance Of Pemfc, Shi Zhou, Muhammad Tariq, Asif Nadeem Tabish, Muhammad Salman, Fan-Di Ning, Muhammad Rayyan Tayyab, Ran-Ran Peng, Meng-Geng Hao, Wen-Mu Li, Xiao-Chun Zhou

Journal of Electrochemistry

Economical Fe-N-C catalysts are considered as promising alternatives to platinum group metal catalysts for proton exchange membrane fuel cells (PEMFCs). Despite exhibiting robust activity on rotating disk electrodes, their performance within membrane electrode assemblies often experiences limitations, such as decreased O₂ diffusion, high H₂O₂ formation, low proton conduction, and a lower electron transfer number. In this study, key factors, including proton transport, electron conduction, and gas diffusion within air-breathing PEMFCs, have been investigated by adjusting cathode catalyst layer (CCL) compositions. From the experimental results, the optimal peak power density was obtained when the loading of Fe-N-C …

Electrospun Pan-Derived Carbon Nanofibers Embedded With Nicofew-Based High-Entropy Oxides For Electrocatalytic Oxygen Evolution Reaction, Alireza Noroozi, Mahdavi, M. Baris Yagci, Mohammad Mahdi A. Shirazi, Saeed Bazgir, Hadi Jahangiri, Uğur Ünal

Research outputs 2022 to 2026

High-entropy oxides composed of Ni, Co, Fe, W, and a fifth transition element (Mo, Mn, or Cu) were integrated into electrospun polyacrylonitrile nanofibers to form porous nitrogen-doped carbon membranes for the oxygen evolution reaction. Gas-assisted electrospinning enabled uniform dispersion of high-entropy oxide nanoparticles within the polyacrylonitrile matrix, while calcination at 800°C produced conductive carbon frameworks embedding crystalline high-entropy oxides with homogeneous elemental distribution. Structural and surface analyses confirmed the preservation of high-entropy oxide phases, catalytic graphitization of the carbon matrix, and strong interfacial bonding between metal oxides and carbon. Among all compositions, Mo-HEO@NC exhibited the lowest overpotential (≈240 mV at …

Quantifying Evapotranspiration From The Wetlands In The Peripheral Area Between The Most Downstream Stream Gages And The Open Water Body Of The Great Salt Lake, Motasem S. Abualqumboz, David G. Tarboton

Publications

Study region: The eastern peripheral area between the most downstream stream gages and the open water body of the Great Salt Lake (GSL), located in northern Utah within the semiarid western United States (US). 

Study focus: As GSL levels decline, the eastern peripheral area is expanding, exposing former lakebed, much of which has transitioned into natural and managed wetlands. Evapotranspiration (ET) from these wetlands consumes water that would otherwise reach the open-water lake body, yet these losses remain poorly quantified and directly affect the GSL water balance. This study compares a water-balance-based ET estimate for the wetlands in the peripheral …