Engineering Commons^™

Asynchronous Polymorphic Logic Locking, Kelby Haulmark

Graduate Theses and Dissertations

This work presents Asynchronous Polymorphic Logic Locking (APLL), a logic locking methodology that integrates polymorphic logic within the Multi-Threshold NULL Convention Logic (MTNCL) paradigm. APLL achieves Boolean satisfiability-attack resilience through a fault-based logic stripping approach followed by logic restoration, while leveraging the analog, dual-functionality of polymorphic gates to impede reverse engineering and removal attacks. In contrast to comparable SAT-resistant logic locking techniques, APLL provides inherent resistance to reverse engineering, reducing the viability of a broad class of attacks that rely on access to the locked netlist. A complete automated design flow is developed, enabling the transformation of combinational circuits into …

Development And Characterization Of 1200v And 1700v Sic Schottky Barrier Diode For Power Electronics Applications, Nur-E-Afra Anika

Graduate Theses and Dissertations

The growing demand for energy-efficient, high performance power electronics in applications such as renewable energy systems, electric vehicles, industrial motor drives, and aerospace has accelerated the development of wide bandgap semiconductors like Silicon Carbide (SiC). This thesis focuses on the development and characterization of 1200V and 1700V SiC Schottky Barrier Diodes (SBDs), focusing on their performance optimization for power electronics applications. The key parameters and figure of merits for SiC Schottky barrier diode (SBD) is discussed. Commercially available 1200V and 1700V SBDs are characterized and key design parameters like drift region length, active area, and carrier concentration are extracted. The …

Study On The Effects Of Molecular Layer Deposition Coating And Mechanical Pressure On Lithium Metal Anodes, Cameron Mondl

Graduate Theses and Dissertations

Lithium (Li) metal is a highly promising anode material for next-generation energy storage systems due to its outstanding theoretical capacity and low electrochemical potential. However, its commercialization implementation has been hindered due to interfacial instability and uncontrollable dendrite formation, leading to poor cycling efficiency and thermal runaway. Among the most promising stabilization strategies, protective interfacial coatings have emerged as an effective solution to promote more uniform Li deposition and suppress erratic morphological inconsistencies. In particular, molecular layer deposition (MLD) enables uniform film thickness through layer-by-layer deposits, offering a highly versatile approach to protective interfacial layers. In addition to interfacial engineering, …

An Efficient Implementation Of Gibbs-Duhem Integration For Solid-Liquid Phase Coexistence In Binary Lennard-Jones System With Relevance To Aav Capsid Separation, Muhi Muntaka

Graduate Theses and Dissertations

Gene therapy using adeno-associated viruses (AAVs) holds promise for treating genetic diseases, but high manufacturing costs limit its widespread use. A major challenge is separating functional (full) AAV capsids from non-functional (empty) ones, which are produced in similar amounts and have nearly identical structures. Conventional purification methods, such as density gradient ultracentrifugation and chromatography, face drawbacks like low yield, poor scalability, and high cost, often requiring multi-step processes. Recently, selective crystallization has emerged as a promising alternative, offering improved efficiency, scalability, and product quality. However, optimizing this method requires a deep understanding of thermodynamic phase behavior in multicomponent systems. In …

Recovery And Evaluation Of A Germanium Infrared Camera, Michael Paszek

Graduate Theses and Dissertations

Short-wave infrared imagers made of germanium are a promising way to extend silicon-compatible imaging beyond the visible spectrum. They also use mature CMOS fabrication and readout electronics. This thesis details the recovery, initialization, and evaluation of a germanium focal plane array (FPA) infrared camera system using both a sealed TriWave camera and a modular prototype platform. Functionality was restored to this legacy hardware, and repeatable testing workflows were established for evaluating packaged infrared imagers under controlled indoor and outdoor conditions. The prototype used a custom software interface named Merlott for evaluation, and it followed a standard sequence that included checking …

Design And Evaluation Of A Single-Gate Multi-Threshold Null Convention Logic Architecture For Area Efficiency, John Edward Swaim

Graduate Theses and Dissertations

Asynchronous circuit design paradigms, such as NULL convention logic (NCL) and Multi-Threshold NCL (MTNCL), offer increased energy efficiency over synchronous equivalents and robust pipelines with minimal timing analysis. However, their dependency on dual-rail signal encoding causes significant overhead compared to single-rail equivalents. Previous single-gate and single-rail NCL paradigms have sought to reduce circuit area, but most compromise their quasi-delay-insensitivity and correct-by-construction nature with logic gate and system-level design choices. This thesis presents Single-Gate MTNCL (SG-MTNCL), a register controlled, single-gate, and dual-rail asynchronous architecture to improve the area efficiency of MTNCL without compromising the reliability of previous paradigms. The benefits of …

Faster Than The Speed Of Bram: In-Memory Computing For Next Generation Fpgas On The Edge, Nathaniel Joseph Fredricks

Graduate Theses and Dissertations

Traditional computer systems are hitting the Memory Wall as machine learning applications are bottlenecked by the bandwidth between separate memory and compute units. Current FPGA architectures are able to bypass this bottleneck with block RAMs (BRAMs) that provide on-chip, in-fabric storage. However, their potential as the foundation of computing components is often overlooked; machine learning accelerators implemented on FPGAs face additional delays when transferring data between memory and compute units. These penalties arise from BRAM bandwidth limitations and movement of data through the reconfigurable fabric. To support FPGA-based accelerators on the edge and break the Memory Wall, reconfigurable architectures must …

Design And Optimization To Advance Silicon Carbide Modules For Medium Voltage High Power Applications, Ahmed Ismail

Graduate Theses and Dissertations

The commercial availability of the first 10 kV silicon carbide (SiC) MOSFET removes the principal semiconductor barrier to medium-voltage power conversion, enabling converter topologies that are structurally inaccessible to silicon IGBT solutions at this voltage class. This dissertation presents the characterization infrastructure, device-level data, and preliminary system-level validation needed to advance the deployment of the third-generation 10 kV SiC MOSFET in converter applications. A custom-built 10 kV double-pulse test platform is developed with a fully documented component-sizing methodology, custom medium-voltage magnetics, and a measurement infrastructure capable of high bandwidth waveform capture at kilovolt common-mode potentials. On this platform, the third-generation …

Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar

Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) like quadcopters are widely used in civilian and military applications such as farming, photography, search and rescue missions, and autonomous navigation and motion. The performance and stability of these systems depend on accurate state estimation, which provides real-time information about the vehicle’s position, velocity, and orientation. However, achieving reliable state estimation is challenging due to sensor noise, measurement uncertainty, and inaccurate modeling. Common navigation sensors such as the Global Positioning System (GPS) and Inertial Measurement Units (IMUs) exhibit complementary characteristics. GPS provides absolute position measurements but suffers from noise, multipath effects, and low update rates, while …

Development Of A Metal-Based Catalyst For The Ammonia Dehydrogenation Reaction, Othman Mohammed Abdullah Al-Amodi

Thesis/ Dissertation Defenses

Developing cost-effective and active catalysts that would replace noble metals is desirable for the ammonia decomposition reaction. Hence, this thesis focuses on the development and evaluation of a 10Ni/0.75TiO2-0.25CeO2 catalyst for ammonia decomposition, a promising route to carbon-free hydrogen production. The system parameters investigated include the effect of reaction temperature (550, 650, and 750°C) and the catalyst mass (100, 200, and 300 mg) on the performance of the ammonia decomposition process. The primary objective of this work is to investigate how catalyst composition and metal-support interactions influence activity, hydrogen production, and ammonia conversion. Catalysts were prepared by the incipient wetness …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

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 …

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 …

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. …

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 …

Cylindrical Versus Spherical Self-Similar Capillary Cavity Collapse, Karl Cardin, Christophe Josserand, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Drop tower experiments have been performed to study the capillary collapse of large high-aspect-ratio cavities. Cavities are formed by momentarily impinging the free surface of a liquid bath with a jet of air in the microgravity environment of a drop tower. The collapse may give rise to a jet and three distinct jetting regimes are identified. Simulations are performed to further investigate the phenomena. The abrupt emergence of a thin high velocity jet is observed experimentally and numerically at a specific initial cavity aspect ratio. Different power laws are identified in different regions of the cavity during the collapse providing …

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 …