Digital Commons Network^™

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.

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 …

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 …

Picc-Pal: A Support Band For Independent Picc Line Use, Kylie Luker

Honors Theses

This project presents the design and evaluation of PICC-PAL, a wearable assistive device intended to improve independence and usability for patients managing peripherally inserted central catheters (PICC lines) at home. Current at-home PICC line management often requires help due to the fine motor skills needed to connect and secure tubing. This increases reliance on caregivers and introduces potential risks such as infection and dislodgement. Through stakeholder analysis, prior art evaluation, and iterative prototyping, a device was developed to stabilize the PICC line lumen and enable one-handed connection of medical tubing. Throughout the project, multiple design concepts were explored, with the …

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Optimization Of Renewable Energy-Based Alkaline Electrolysis Systems For Sustainable Hydrogen Production, Shokhrukhbek Kozimjon Ugli Bakhramov

Chemical Technology, Control and Management

This paper presents a comprehensive optimization study of hydrogen production systems through alkaline water electrolysis powered by photovoltaic energy sources, with a specific focus on Central Asian applications. The research systematically investigates critical operating parameters including KOH electrolyte concentration (25-30 wt%), temperature effects (25-80°C), current density optimization (100-500 mA/cm²), and electrode material performance using cost-effective 316L stainless steel. Experimental results demonstrate that optimized systems achieve solar-to-hydrogen efficiency of 13-15%, with hydrogen production costs ranging from $2-8/kg depending on system scale. The study reveals that maximum performance occurs at 30 wt% KOH concentration, 60-80°C operating temperature, and 200-400 mA/cm² current density. …

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …

Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova

Chemical Technology, Control and Management

The article deals with the automated design and experimental investigation of reinforced concrete irrigation channels and ditches, their interrelated channel-cleaning mechanisms, which are complex mechatronic systems integrating hydraulic, mechanical, and electronic components. A thorough methodology is suggested, hydrodynamic modeling, combining parametric analysis, and information-based design support to enhance channel concrete cover thickness, geometry, and cleaning system performance. Main structural parameters—involving channel depth, slope, bottom width, and concrete cover—are systematically defined and shown in matrix form to facilitate automated calculation and decision-making. Experimental prototypes and Solid Edge-based digital models are employed to verify the methodology, revealing vital interdependencies between structural parameters, …

Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov

Chemical Technology, Control and Management

This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov

Chemical Technology, Control and Management

One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …

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 …

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 …

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 …

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 …

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), …

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 …

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. …

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 …

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 …

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

Electronic Theses and Dissertations 2020 - Present

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 …