Engineering Commons^™

Transition And Instability Characteristics Of The Separated Shear Layer Formed At Low Reynolds Number Over Three-Dimensional Irregular Rough Surface, Ganesh Kt Mr

Theses and Dissertations

The present experimental work investigates the effects of irregularly roughened surfaces and imposed streamwise pressure gradients on the topological, transitional, and instability characteristics of the laminar separated shear layer (SSL). Experiments are conducted in the low-speed wind tunnel for 𝑅𝑒𝑡=30000, based on the thickness of the airfoil model, t, and freestream turbulence intensity, fst = 0.8%. The airfoil model used in this study features a semicircular leading edge followed by a constant-thickness flat portion and a pitchable trailing-edge flap. Test conditions include two rough surfaces: sandblasted (SB) and sand-deposited (SD), and flap deflections: 𝛽=−30° and 𝛽=+30°, imposing adverse (APG) and …

A Contemporary Approach For Exploring The Influence Of Detoxification And Standardization Of Traditional Metallopharmaceutical Product Pharmacological And Toxicological Aspects, Malarvizhi K

Theses and Dissertations

Polyherbomineral formulation possess unique medicinal properties due to the presence of metals and minerals as integral part, as processed in addition to specific herbals. There is an increased interest in metallopharmaceuticals in clinical and research areas, because of their immense therapeutic efficiency towards multiple diseases and evidence for non-toxic claim. Sivanar Amirtham is one of the polyherbomineral Siddha medicine recommended for the treatment of various respiratory diseases and other ailments including antidote therapy for poisonous bites. The present research work attempted for standardization of Sivanar Amirtham preparation as per the traditional standard protocols (including the detoxification process of raw materials) …

Magnetic Molecularly Imprinted Polymers For Quercetin Adsorption: Fabrication, Characterization, And Application, Vinitha Ug

Theses and Dissertations

A highly selective Magnetic Molecularly Imprinted Polymer (MMIP) was developed for the detection and purification of Quercetin. The Density Functional Theory was utilized for the selection of suitable monomers based on binding energy interaction between quercetin and monomers (Acrylamide, Acrylonitrile, Methacrylic Acid). From computational studies, Acrylamide was selected as a suitable monomer for the synthesis of MMIP. Under ultrasound irradiation both quercetin and naringin imprinted materials MMIP-Q and MMIP-N were fabricated.

Compared to ultrasound-assisted synthesis, Microwave Synthesis provides uniform heat transfer throughout the reaction solution, which enables uniformity in the size of synthesised material, increases the yield of material and …

Design And Development Of Deep Learning Based Generic Platform For Promoting Precision Agriculture, Srilakshmi A

Theses and Dissertations

Precision agriculture also referred as precision farming or smart farming, is an innovative approach to agricultural management that leverages technology and data to optimize various aspects of the farming process. This approach aims to make farming more effective, sustainable, and profitable by affording farmers with the application tools and information they need to make more informed decisions.

Precision agriculture combines elements of agriculture, technology, and data science to enhance crop production, and resource utilization. Precision agriculture techniques can be highly effective in leaf disease detection within crop fields. Machine learning has been developed incredibly across multiple domains and shown it …

Facile Fabrication Of Protein-Polysaccharide Conjugate Multifilament Nerve Guidance Conduit For Peripheral Nerve Regeneration, Preethy Amruthavarshini R

Theses and Dissertations

Long segmental defects in peripheral nerves impair sensory and motor function by disrupting neural impulse transmission. End-to-end autologous grafting with proper fascicular complementation has demonstrated functional recovery per the Medical Research Council Classification (MRCC). However, obtaining donor nerve tissue exceeding 30 mm remains a significant challenge. Artificial hollow conduits serve as an alternative but are limited to defects smaller than 30 mm due to inadequate innervation across the lumen.

Multichannel nerve guidance conduits (mNGCs) have emerged as a promising solution by enhancing fascicular complementation similar to autografts. This study presents a two-step approach for fabricating nerve conduits with precise fascicular …

Structural Response Of Rc Columns Strengthened Using Bfrp Based Bfegc System – Under Fire And Cooling Regime, Ruba P

Theses and Dissertations

Retrofitting fire-damaged columns is essential for restoring structural integrity. This study evaluates the effectiveness of BFRP based Basalt fiber Engineered Geopolymer Composites (BFEGC). The performance of basalt fiber wrapping and BFEGC was tested for fire protection system and retrofitted system. An optimal BFEGC mix achieved a compressive strength of 55.34 MPa, with split tensile strength, flexural strength, and strain hardening behaviour of 15.5 MPa, 5.13 MPa, and 6% respectively.

Microstructural analysis was accessed for the optimum mix. Durability tests include water absorption, sorptivity, and RCPT which confirmed compliance with standards. Thermo gravimetry analysis (TGA) shows the minimal weight loss of …

Encountering And Mitigating Selfish Mining In Bitcoin Mining Pools, Jeyasheela Rakkini M J

Theses and Dissertations

Blockchain, an innovative decentralized distributed, disrupting programming paradigm embodies key principles such as decentralization, data provenance, immutability, and transparency. At its core blockchain begins with the genesis block and progresses with each subsequent block containing the hash of the previous block, Merkle root, timestamp, a coin base transaction address, and a nonce. Miners compete to discover a target hash value (hash value of the previous block and nonce) for the current block, that is less than or equal to the difficulty value set by the system, a process known as mining.

This work encounters selfish mining attacks in bitcoin mining …

Computational Studies On The Major Antioxidant Enzymes Of Wuchereria Bancrofti Towards The Development Of Anti Filarial Leads, Sureshan M

Theses and Dissertations

Lymphatic filariasis (LF), or elephantiasis, is a mosquito-borne parasitic disease affecting the lymphatic system, primarily in tropical and subtropical regions. It is the second leading cause of long-term disability and a neglected tropical disease. According to WHO, LF threatens 882 million people in 44 countries, with over 9 billion treatments administered. The disease is caused by three nematodes: Wuchereria bancrofti (90% of cases worldwide, including India), Brugia malayi (10% in Southeast and Eastern Asia), and Brugia timori (found in Timor and nearby islands). Lymphatic filariasis (LF) is an ancient disease that continues to challenge scientists and physicians. Current treatments include …

Impact Of Ionic Liquids On The Treatment Of Various Derivatives Of Prosopis Juliflora For Removing Toxic Pollutants From Wastewater, Karthikeyan A

Theses and Dissertations

Water resources are increasingly contaminated by toxic pollutants, particularly industrial effluents, posing significant environmental concerns. Addressing the toxicity of these pollutants, especially those released from textile industries, presents challenges due to their harmful effects on living organisms. Various treatment methods are employed to mitigate this issue, including coagulation, flocculation, membrane filtration, photocatalytic degradation, adsorption, anaerobic processes, and chemical oxidation. Among these, adsorption emerges as an effective and economical method due to its minimal secondary contamination, negligible sludge production, and the use of inexpensive agricultural and marine waste materials.

This study examines the ability of Prosopis juliflora treated with imidazolium-based ionic …

Artificial Intelligence-Based Adaptive Data-Driven Techniques For Disruption Prediction In Tokamak, Priyanka M

Theses and Dissertations

Tokamaks are nuclear fusion reactors designed to generate sustainable energy by confining plasma, yet plasma disruptions remain a major obstacle as they can damage reactor components and interrupt fusion reactions. Addressing this challenge requires reliable models that can classify plasma discharges and predict disruptions in advance. This thesis develops machine learning and deep learning approaches to improve both classification and forecasting.The first contribution is a semi-supervised active learning framework, Nearest Margin-Ranked Batch Mode Active Learning (NM-RBMAL), integrated with an ensemble model.

Unlike traditional classifiers that operate on static training data, this approach continuously adapts to new plasma conditions, reducing model …

Ai Based Early Detection Of Hormonal Imbalance And Poly-Cystic Ovary Syndrome In Young Women, Reka S

Theses and Dissertations

A hormonal disorder, Poly-Cystic Ovary Syndrome (PCOS) usually affects women during the reproductive age. It is characterised by imbalances in hormones, particularly a rise in the female body's androgen level (male hormone) and enlarged ovaries with small cysts. PCOS can cause ovarian cysts, weight gain, acne, excessive hair growth, insulin resistance, and irregular menstrual cycles along with other health problems. While the exact origin of PCOS is uncertain and its symptoms are unclear, diagnosing PCOS in real-world conditions is a difficult task. Therefore, prompt and precise PCOS diagnosis is essential for efficient treatment and for averting long-term issues.

Clinicians typically …

Bioprospecting Of Wheat Straw Pyrolysis Aqueous Phase To Combat Multi-Drug Resistant Pathogens, Srividhya K

Theses and Dissertations

Hospital-acquired infections (HAIs) significantly contribute to the emergence and spread of antimicrobial resistance (AMR), primarily through the contamination of high-touch surfaces. Current disinfectants have drawbacks like high environmental persistence, ecotoxicity, and resistance development, prompting the need for environmentally friendly alternatives.

One potential approach is pyrolysis, during which the biomass components are broken down into solid, liquid, and pyro-gas. The aqueous phase of the liquid fraction is usually discarded as waste, but it contains a variety of organic compounds that have the potential for antibacterial and antifungal activity. The present study assessed the anti-infective and anti-biofilm properties of wheat straw pyrolysis …

Fabrication Of Transparent Conducting Electrodes By Chemical Approaches & Their Application Towards Sensing And Energy Storage, Namuni Sneha

Theses and Dissertations

In the intelligent era, there is a growing demand for developing highly efficient and robust wearable electrodes through simple chemical approaches. We developed highperforming transparent electrodes using interconnected Au nanoparticle networks via a simple liquid-liquid interface approach that offers high conductivity, transparency (>85%), and mechanical durability. Additionally, the prepared electrodes exhibit tunable transmittance and sheet resistance, and the method was also adaptable to various substrates without harsh chemical or thermal treatments.

Furthermore, using Au 1L (1-layer) nanonetwork, a highly transparent breath sensor is fabricated with short response and recovery times (1.1 s and 1.3 s). The Au-1L sensor is …

Design And Investigation Of Deep Eutectic Solvent-Assisted Extractive Fermentation Of Biomolecules, Ramya M

Theses and Dissertations

The increasing demand for sustainable and efficient bioprocessing techniques has prompted the development of novel separation strategies integrating bioproduction with downstream processing. Extractive fermentation has emerged as a promising process intensification to overcome product inhibition and enhance productivity by constantly removing target biomolecules from the fermentation medium. Although the extractive fermentation of acids and alcohols has been extensively studied, less attention has been focused on green solvents and their compatibility, phase-forming abilities, and reactor configurations.

Therefore, advancing extractive fermentation technology necessitates comprehensive studies on solvent systems and the development of modified bioreactor configurations to aid future optimization. Initially, 22 DESs …

Investigation Of Dependency Parsing Techniques For Digital Document Analysis Through Deep Learning Approach, Rekah D Ms

Theses and Dissertations

Digital document dependency parsing is a significant task in natural language processing. Dependency parsing supports verification of the grammatical correctness of a sentence besides enabling extraction of relevant documents. Inappropriate extraction of features may result in falsely parsing a document, leading to decreased accuracy. Machine learning methods have been employed to perform feature extraction. However, selecting pertinent features was never achieved which minimizes the time consumption and overhead.

Hence, novel machine learning and deep learning techniques have been designed in our work for accurate and computationally efficient digital document analytics through dependency parsing. Four different contributions have been proposed for …

Cyclone Intensity Prediction In The Bay Of Bengal Using Deep Learning Methods, Senthil Kumar J

Theses and Dissertations

The Bay of Bengal region's coastlines have been badly devastated by tropical cyclones, as the region experiences an average of five to six cyclones per year, with about two to three of these intensifying into tropical storms or severe cyclones. Thus it necessitates to study the accurate and efficient forecasting of their intensity to improve preparedness and response to natural disasters. The present study compares and examines three distinct approaches to cyclone intensity prediction using historical datasets from 1998 to 2020: hybrid optimisation, deep learning-based, and empirical approaches.The predicted accuracy, computational effectiveness, and feasibility for real-time scenarios of each model …

Development Of Powder Activator From Agro-Industrial Waste And Its Application In The Preparation Of One-Part Alkali Activated Concrete, Anoop Kn

Theses and Dissertations

The environmental concerns associated with the traditional ordinary Portland cement (OPC) such as CO2 emission and high energy demand along with resource depletion as binder has led to the development of alkali activated binders (AABs). Even with the reduction in environmental issues, the implementation of AAB in practice is hindered by the handling issues of liquid activators. Hence, it is required to develop AAB with powdered activators to address the handling issues and to further reduce the environmental issues related to the production of activators. This research investigates the development of one-part alkali-activated concrete (OAAC) system utilising wastederived materials as …

Design Of An Integrated Lightweight Cryptographic Algorithm For Device Level Security And Fraternal Cryptographic Algorithm For Communication Security In Medical Cyber Physical Systems, Vimala Devi P

Theses and Dissertations

Healthcare involves detecting symptoms, diagnosing conditions and giving treatment to patients. It is one of the fundamental human rights, and it might be difficult to provide healthcare to those with chronic illnesses, elderly people with disabilities and those under distant observation. The World Health Organisation (WHO) states that Cardio Vascular Disease (CVD) is the leading cause of death worldwide.

According to the prediction, CVD-related causes such as heart attacks and strokes, could result in 23.3 million deaths by 2030. In addition, the number of people with diabetes will reach 246 million; thereby, the prevalence of CVD patients and diabetics will …

Investigations Of Secure Memory For Vlsi Based Crypto System, Vijay Sai R Mr

Theses and Dissertations

Semiconductor technology is growing very rapidly in their architectural developments, involving the usage of processor and memory. Presence of memory, in general is a vital commodity in various devices which are almost embedded into human activity, from robust work stations to handy mobile phones. Security of data stored in memory is very important, and hence, observation must be made that these valuable data should not be thwarted by malicious means. Security in cache memory is a major issue in memory related applications such as smart cards and bio-metric implementations.

Cache, is a small and limited memory located between central processing …

Exploring Longitudinal Stability Of Spatiotemporal Sequential Patterns By Means Of Autoencoder Schemes For Eeg Based Personal Identification, Muhammed E. Oztemel

LSU Doctoral Dissertations

Robust personal identification remains a critical and challenging task in the digital era. Electroencephalography (EEG) offers a unique biometric modality that captures individual brain dynamics through complex neural signals. This dissertation proposes autoencoder (AE) based feature extraction and subject identification through these features. EEG recordings are first transformed into topographic maps to represent spatial brain activity. Consecutive topomaps are then concatenated to capture temporal transitions across frames. Convolutional autoencoders (CAEs) are used to learn spatial and temporal patterns, while domain-adaptive AEs are designed to model evoked potential based responses. Additionally, self-attention mechanism is incorporated to enhance feature representation. To analyze …

Beyond Single Metrics: A Holistic Benchmarking Framework For Low-Power Embedded Systems, Hassan Adam

UNLV Theses, Dissertations, Professional Papers, and Capstones

Modern embedded systems encounter a notable challenge in evaluation. While devices may meet traditional benchmarks, they often underperform in real-world applications due to neglected interactions at the system level. Current benchmarking suites, such as MLPerf Tiny and EEMBC ULPMark, evaluate specific metrics including computational throughput, energy efficiency, and memory usage. However, they do not consider the complex interdependencies that affect real-world performance. This thesis presents a benchmarking framework that concurrently evaluates multiple performance dimensions under realistic workloads, revealing system behaviors that are often hidden in conventional benchmarks.Through the comprehensive evaluation of three representative algorithms: Fast Fourier Transform, quantized neural network …

Integrated Uav Platform For Multi-Spectral, Thermal, And Eos Imaging In Wildfire Monitoring And Modeling, Md Shariful Islam

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents the design and development of a modular unmanned aerial vehicle (UAV) system based on a quadcopter platform for flexible and efficient wildfire-related multimodal image acquisition. Addressing key limitations in ecological UAV monitoring such as sensor inflexibility, time-consuming reconfiguration, and imprecise image georeferencing, the system introduces a versatile payload integration framework supporting three distinct imaging sensors: MicaSense Altum-PT, FLIR Vue Pro R, and Sony Alpha 6000.All onboard components, including the flight controller, autopilot software, GNSS module, motors and ESCs, were selected to optimize stability and payload performance. A gimbal-free, downward-facing mount simplifies field deployment, while custom integration enables …

Functional Biopolymers Applied To Sustainable Technologies In The Environment And Healthcare, Fengjie He

UNLV Theses, Dissertations, Professional Papers, and Capstones

Biodegradable polymeric materials (biopolymers) are naturally derived materials known for their excellent biocompatibility, biodegradability, sustainability, and versatile chemical functionality. They have attracted increasing attention in various applications as alternative to synthetic materials ranging from food packaging to tissue engineering. Meanwhile, with intrinsic advantages, biopolymers have also emerged as promising materials in addressing contemporary challenges in both biomedical and environmental fields. Motivated by the significant potential of biopolymers and the growing need for sustainable materials, my research focuses on the design and engineering of biodegradable polymers with novel modification methods and application directions. In this work, two representative biopolymers are selected: …

Bio-Inspired Electroactive Polymer (Eap) Sensors For Surface And Canal Flow Sensing In Dynamic Environments, Nazanin Minaian

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nature can often create some of the most efficient and elegant solutions to complex problems, and engineering stands to benefit greatly from these time-tested designs. One of the more sophisticated examples of this is the lateral line system in fish: a distributed network of superficial and canal neuromasts that enables aquatic species to detect fluid disturbances with remarkable precision. This dissertation leverages that biological framework to explore the potential of electroactive polymers (EAPs), aiming not just to replicate structure, but to emulate function.Two classes of EAPs form the basis of this work: electroactive plasticized polymer gels (EPPGs) and ionic polymer-metal …

Investigating Information Extraction And Language Models In Medical Domain Text Processing, Pouyan Nahed

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation demonstrates that carefully adapted language-model pipelines can transform unstructured clinical-trial and pharmacological prose into reliable, low-latency structured data. Four interconnected studies support this claim.Tri-AL platform. An open-source dashboard ingests all 440 k+ ClinicalTrials.gov records—including every historical revision—into a normalized schema and parses the 20 GB XML archive over 10x faster than a BeautifulSoup baseline, while exposing hooks for demographic analytics and supporting integration of user-defined modules. Clinical trial summarization. An encoder–decoder model is trained on 57k description–summary pairs to condense clinical trials into a few sentences. ROUGE evaluation shows a 20% improvement over the baseline, while graph-based evaluation …

Learning Structure With Multivariate Information Bottleneck And Exploration Of New Methods In Sequential Decision Making, Volodymyr Makarenko

Master's Theses

Research in useful information extraction has been motivated by the increasing demand to extract insights from unstructured data, and by the need to store and transmit great volumes of information, often originating in unstructured data such as videos. Research in rate distortion and information bottleneck paved the path for understanding and guiding the design of lossy encoders, capable of extracting relevant information. Independently, research in deep representation learning has enabled numerous applications for unstructured high-dimensional data such as images. However, the interpretability of the deep learning methods remained limited. Several desired properties of learned representations have been suggested, including disentanglement. …

Development Of An Access Charge Framework For High-Speed Rail Incorporating Rail Replacement Costs And Dynamic Train Characteristics, Nitesh Kumar Yadav

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis develops a framework to determine track access charges for shared high-speed rail corridors, with a focus on rail replacement cost driven by train-induced loads. The method explicitly accounts for both static loads, resulting from axle weights, and dynamic loads that arise from train speed and track geometry, particularly curvature. Train characteristics such as axle load, operating speed, frequency of service, and number of wheels are integrated with track parameters, including curve radius, to calculate the total vertical load. These loads are used to estimate the cumulative tonnage threshold for rail replacement and the resulting service life of the …

Autonomous Uav Swarm Formation Utilizing Gradient-Driven Contour Mapping For Radiation Source Localization, Edgar Amalyan

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents a drone swarm for radiation mapping to aid source localization. The Department of Energy advocates employing UAVs for this task, but existing approaches remain inefficient and impractical in real-world scenarios. Three custom drones are built and flight-tested. A control algorithm to follow a contour, a constant-intensity path, is designed using a gradient fit. By knowing the source’s direction, the drone swarm can fly in the optimal trajectory at every step, leaving nothing to assumption. A program is created that implements formation flight and autonomous navigation. It is tested via a software-in-the-loop simulation utilizing radiation sources and detectors …

The Dropbot: Design And Development Of A Custom Drone For Precision Water Drop Penetration Time (Wdpt) Testing, Mugundan Prakash

UNLV Theses, Dissertations, Professional Papers, and Capstones

Assessing the hydrophobic characteristics of soil is vital for understanding soil wettability or soil-water interactions, particularly in post-wildfire environments where water repellency can significantly impact ecosystem recovery, water infiltration, and erosion control. One key metric in soil wettability studies is the Water Drop Penetration Time (WDPT) test, which evaluates the hydrophobicity of soil and guides land treatment strategies. This thesis presents the design and development of DropBot, a custom-built drone platform engineered for the precise delivery and analysis of water droplets in WDPT tests.The DropBot, a custom drone, integrates a lightweight, 3D-printed frame with a self-leveling platform, enabling consistent droplet …

Improving Particle-Phase Nitrate Measurement In Pm2.5 Filter Sampling: Evaluation Of A Denuder–Nylon Filter Modification In The Spartan Network, Wenyu Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate measurement of PM_2.5 composition is of global importance. Evaporation-induced mass loss introduces potential bias in filter-based PM_2.5 measurements, with ammonium nitrate volatilization from Teflon filters being a major contributor to negative mass artifacts. Previous studies have demonstrated that using an acid gas denuder in combination with nylon filters can help recover the nitrate mass. This study evaluates design modifications to the AirPhoton sampling station setup within the globally distributed Surface Particulate Matter Network (SPARTAN) incorporating an additional acid gas denuder upstream and a nylon filter downstream of the existing Teflon filter.

Two co-located AirPhoton Sampling stations were …