Digital Commons Network^™

Validity Of The Schrage Equation In Prediction Of Evaporation Rate Of Liquid N-Dodecane In High-Pressure Nitrogen Gas: A Molecular Dynamics Study, Wazih Tausif, Jordan Hartfield, Md Amin Haque, Zhi Liang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Evaporation of liquid fuel in a high-pressure air is a process that critically influences fuel–air mixing in advanced propulsion systems. In this work, we use molecular dynamics (MD) simulations to study the validity and accuracy of the Schrage equation in quantifying the evaporation and condensation rates of n-dodecane (a diesel surrogate) in air (approximated as N2 gas) with gas pressure varying from 0 atm to above the critical pressure of n-dodecane. The MD simulation results show that the evaporation coefficient (αe) is higher than the condensation coefficient (αc) at the evaporating n-dodecane surface and is lower than αc at the …

A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Featured Application: The proposed federated learning framework can be applied in distributed smart manufacturing environments where multiple factories or production facilities collaboratively develop predictive maintenance models without sharing sensitive operational data. This approach is particularly useful for industrial networks involving geographically distributed plants, contract manufacturing partners, and multi-site production systems where data sovereignty and avoidance of raw data sharing are critical. Predictive maintenance enables early detection of machine failures and reduces unexpected production downtime. However, conventional approaches typically rely on centralized data collection and model training which introduce challenges related to data sovereignty, communication overhead and data ownership. To address …

Machine Vision For In Situ Measurement And Control Of Wire Stickout In Lwded Process, Braden Mclain, Remy Mathenia, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents a machine-vision–based measurement and control framework for laser wire directed energy deposition (LWDED) processes. A visible-light camera system is used to capture meltpool images, from which a novel vision algorithm extracts the wire–meltpool interface location. By utilizing a camera that is rigidly mounted to the deposition head, the vision algorithm provides a relative measurement of the distance between the nozzle tip and the workpiece, also referred to as wire stickout. A proportional-derivative (PD) control strategy is implemented using the measured stickout as feedback to adjust deposition feedrate. Results show that the control system successfully compensates for improper …

Practicing Conflict Transformation Skills Through Role-Playing Games For Diversity, Equity, And Inclusion In Higher Education, Alexandra Schreiber, Kjell H. Hugaas, Sarah L. Bowman

Journal of Roleplaying Studies and STEAM

No abstract provided.

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 …

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 …

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 …

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.

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 …

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 …

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. …

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.

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. …

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 …

Key Issues For Speed Safety Cameras: Results From A Semi-Structured Interview Of Agencies In The United States, Sophia Semensky, Miguel Figliozzi

Civil and Environmental Engineering Faculty Publications and Presentations

Speed safety cameras (SSCs) are a recognized countermeasure for targeting speeding-related crashes, injuries, and fatalities. SSCs have been introduced in various cities and are steadily expanding in use both in the U.S. and internationally. The extensive literature review of domestic and international documents and research papers reveals that the U.S. has been comparatively slow to adopt SSCs, with some other countries implementing these systems more extensively and earlier. Many local agencies are eager to learn SSC best practices and implementation lessons within the U.S. context. In this research, key issues related to SSC implementation are explored through semi-structured interviews with …

Passenger Autonomy In Airport Systems: Integrating Accessibility, Spatial Design, And Technology To Improve Operational Efficiency, John Michael Schmitz

Honors Projects

Airports are among the most complex operational environments in modern transportation, requiring the coordination of passenger movement, security processes, and infrastructure under significant time constraints. Although there have been many advancements in aviation, most passengers continue to experience high levels of stress and confusion while trying to navigate airport terminals. This paper argues that operational efficiency in airport systems is achieved by increasing  passenger autonomy through the utilization of accessible design, spatial legibility, and new emerging technologies. This paper takes note of some foundational theories that drove urban design and cognitive psychology, including Lynch’s concept of imageability, Passini’s theory of …

Vacuum Modification Of The Surface Properties Of T15k6 Hard Alloy By Plasma–Chemical Synthesis Of Tin-Cu Coatings, Aleksandr Semenov, Dmitriy Tsyrenov, Nikolay Ulakhanov, Irina Semenova, Undrakh Mishigdorzhiyn, Wen Ma, Simon C. Tung, George E. Totten

Mechanical and Materials Engineering Faculty Publications and Presentations

The design and main parameters of a plasma–chemical reactor containing two compartments are presented. One compartment houses a vacuum-arc evaporator, while the other houses a planar magnetron. The compartments are separated by a diaphragm with a dosing slot for injecting copper vapor into the TiN synthesis compartment. The conditions for the synthesis of superhard TiN-Cu composite coatings are experimentally determined. Based on established process parameters for TiN synthesis in a nitrogen-containing plasma by Ti evaporation using a vacuum-arc discharge, it is proposed to apply TiN-Cu coatings by injecting Cu vapor into the TiN synthesis area and sputtering Cu using a …

An Evaluation Of Total Navicular Implants: A Scoping Review, James Mcclure Hughes, Nicholas Belardo Obias, Amanda Killeen

School of Podiatric Medicine - Student Research

The aim of this study is to determine the efficacy and safety profile of total navicular implants based on current literature.

Navicular insults such as high-energy trauma, osteonecrosis, and Muller-Weiss syndrome may result in avascular necrosis or a critical sized bone defect, conditions that are highly difficult to manage given current treatment modalities. Total navicular implants may offer a solution to these problems. While 3D printing of implants remains investigational, its use in highly individualized cases involving the talus has had promising results with conditions like avascular necrosis, tumors, trauma, and arthritis. The navicular is unique in its attachments to …

Optical Mechanisms Behind Vitrinite Reflectance Suppression Caused By Strong Anisotropy: A Case Study Of Contact Metamorphic Coals, An Yanfei, He Shuyang, Chen Kaixin, Gao Junhan

Coal Geology & Exploration

Objective For vitrinite with weak anisotropy, which proves uniaxial and optically negative, replacing random vitrinite reflectance (R_ran) with the maximum vitrinite reflectance (R_max) allows for the accurate correction of vitrinite reflectance suppression induced by anisotropy. However, as its anisotropy intensifies, vitrinite exhibits increasingly complex optical properties, rendering it challenging to reflect the thermal metamorphic temperature of vitrinite using R_max. Methods This study investigated the strongly anisotropic vitrinite in coals and natural coke subjected to magma intrusion in the Shitai coal mine, Huaibei City, Anhui Province. Using a reflected-polarized light microscope (R-PLM), an …

Llm For Clinical Named Entity Recognition: A Study On Rag With Pubmed And Umls, Apoorv Tripathi

Electronic Theses and Dissertations 2020 - Present

The first step of biomedical NLP is recognizing clinical named entities, which consist of identifying and categorizing a variety of clinical entities such as diseases, symptoms, genetics, diagnostic tests, procedures, etc. from a body of unstructured clinical text. This study presents a PubMed and UMLS based Retrieval Augmented Generation framework which improves the performance of the Large Language Models to identify clinical entities by providing context. In particular, the framework consists of a two-stage pipeline, where candidate tokens are identified from initial LLM-based classification and refined with retrieved context from either PubMed or UMLS. The proposed framework is assessed across …

Advanced Studies In Characterization Of Pyrolysis Products From Live Vegetation, Mahsa Alizadeh

Theses and Dissertations

Fire is a naturally occurring element in many ecosystems which can have both positive and negative effects. However, in recent years the frequency of the fires and the area they affect has increased. The rapid spread of wildland fires coupled with the limited resources available to forest services to manage wildland fires highlights the urgency for accurate prediction of fire spread. Fire prediction models enable the fire management services to predict the spread of fire and prioritize firefighting efforts more effectively. Understanding reactions and mechanisms occurring during wildland fires improves the fire prediction models. During wildland fires, the biomass covering …

Advances In The Design Of Bio-Organic Resistive Switching Memory, Muhammad Awais, Yi Sheng Wong, Feng Zhao, Kuan Yew Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

Bio-organic materials have garnered significant attention as sustainable candidates for non-volatile resistive switching memory (RSM) because of their specialized chemical, structural, and environmental advantages. This review presents a design-centered perspective on bio-organic RSM by outlining the key device components required for effective device engineering, including electrode materials, memristive thin films, intermediate layers, substrates, and electrical measurement strategies. Each component is discussed in detail with respect to the material properties and operational parameters that influence overall device performance, such as functional groups, interfacial interactions, and processing conditions. The review further analyses the critical roles of electrode pairing, interfacial chemistry, additive incorporation, …

Mechanism Of Improved Miscibility Of Co2–Oil Systems By Multiester-Headgroup Surfactants, Ning Xu, Yanling Wang, Baojun Bai, Yu Zhang, Wenjing Shi, Zhaonian Zhang, Wenhui Ding, Peixu Ma, Zan Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In the pursuit of carbon neutrality, the CO₂-enhanced oil recovery provides dual benefits by enabling both carbon sequestration and incremental oil production. However, its application is limited by high minimum miscibility pressure. CO₂-philic and oil-affinitive surfactants have emerged as an effective, low-dosage, and cost-efficient strategy to reduce the minimum miscibility pressure. In this study, macroscopic phase behavior experiments combined with molecular dynamics simulations were employed to systematically elucidate the influence of multiester-head surfactants on CO₂–oil miscibility. Using a modified pressure–volume–temperature apparatus equipped with optical power monitoring, we determined that multiester-head surfactants reduced the first-contact …