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Electronic Theses and Dissertations

Theses/Dissertations

2023

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Robust Visual Observer And Controller Design For System Modeled On Se(3) With Camera Measurements, Tong Zhang Dec 2023

Robust Visual Observer And Controller Design For System Modeled On Se(3) With Camera Measurements, Tong Zhang

Electronic Theses and Dissertations

This dissertation presents a controlling method that utilizes visual observation to address the challenge of driving an autonomous vehicle with a kinematic model on SE(3), by using the data obtained from the onboard cameras. This controlling framework is applicable when direct retrieval of the vehicle's attitude information is not possible or when precision control of the vehicle is necessary. However, addressing several challenges to attain closed-loop stability for the observer-based control for autonomous vehicles on SE(3) is essential. 1. The analysis is further complicated by the presence of multiple equilibria in the error dynamics associated with the suggested method. 2. …

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Memristor-Based Digital Circuit Design, Khalid Mohammed Alammari Nov 2023

Memristor-Based Digital Circuit Design, Khalid Mohammed Alammari

Electronic Theses and Dissertations

Further miniaturization in CMOS technology has faced severe challenges, such as increased leakage power and reduced circuit reliability, which has caused fundamental restrictions on advancing efficient computing architecture. These problems can be addressed by the new emerging devices known as memristors owing to their nanoscale size and the ability to integrate with the exciting CMOS technology. Memristors are passive devices with variable resistance. The resistance value will remain constant when no electrical field is applied, giving this device a unique behavior by saving its last state. This unique behavior makes this device very appealing to a wide variety of applications …

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Skin Cancer Detection By Deep Learning Algorithms, Faezeh Mohammadi Aydoghmishi Nov 2023

Skin Cancer Detection By Deep Learning Algorithms, Faezeh Mohammadi Aydoghmishi

Electronic Theses and Dissertations

Skin cancer, characterized by the abnormal growth of skin cells, is a globally prevalent and serious condition. Despite advancements in digital diagnosis techniques, many existing skin cancer detection methods often fail to achieve satisfactory accuracy levels. In our first study, we propose a novel superpixel-based segmentation method that significantly surpasses the traditional k-means clustering in performance. After segmentation, we utilize Convolutional Neural Networks such as VGG16, ResNet50, DenseNet, Xception, Inception, and Mobilenet for feature extraction and classification. We also conducted a comparative analysis with other existing techniques. Our results suggest that our superpixel-based segmentation method notably enhances the accuracy of …

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Anisotropic Mechanical Material Investigation On Moisture And Strain Rate Sensitivity Of Direct Compounded Compression Moulded Glass/Pa6 Lfts, Pouya Mohammadkhani Oct 2023

Anisotropic Mechanical Material Investigation On Moisture And Strain Rate Sensitivity Of Direct Compounded Compression Moulded Glass/Pa6 Lfts, Pouya Mohammadkhani

Electronic Theses and Dissertations

In this study the tensile properties at different loading rates as well as shear properties of a direct-compounded compression-moulded Polyamide6 (PA6)/glass long fibre thermoplastic (LFT-D) material with a fibre weight content of 30% were investigated. The effects of moisture on the anisotropic mechanical and material properties of Glass/PA6 LFT materials were examined by testing at four different material directions of 0°, +45°, ˗45°, and 90°. In order to study the effect of tensile loading rate on this material, different nominal strain rates ranging from 0.0001 1/s to 150 1/s were examined. Under quasi-static loading, at a 2% moisture content, the …

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Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi Oct 2023

Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi

Electronic Theses and Dissertations

The most common cancer diagnosed worldwide is breast cancer and early detection is essential for reducing mortality. The best standard for early detection of breast cancer is digital mammography, which can aid physicians in treating the illness when it is still curable. However, inaccurate mammography diagnoses are frequent and can cause patients to undergo unnecessary examinations and therapies. This study aims to explore deep-learning techniques that can be utilized to implement and train a model to identify breast cancer cases in mammograms. Current deep learning-based diagnostic techniques are hindered by two fundamental issues: the expensive and time-consuming task of data …

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Multi-Mode Robust Appointment Scheduling For Uncertain Service Time And Random No-Show Using Min-Max Optimization, Anik Chandra Dash Oct 2023

Multi-Mode Robust Appointment Scheduling For Uncertain Service Time And Random No-Show Using Min-Max Optimization, Anik Chandra Dash

Electronic Theses and Dissertations

The appointment scheduling issue has been widely used in a variety of industries, including those that provide services, healthcare, finance, and legal advice. Uncertainty of processing time and job no-shows make the problem more challenging. The majority of the literature now in existence makes unrealistic assumptions about most real-world scenarios, such as constant service time, and they use a vast quantity of data to view the service time distribution or failure to account for work no-shows. In the research, we address this issue by building a robust appointment scheduling model that uses min-max optimization to generate appointment time for a …

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Residual Stress In Metal Additive Manufacturing Of Thin-Walled Components: Investigation And Development Of Prediction Models With Respect To Path Planning, Bita Mohajernia Sep 2023

Residual Stress In Metal Additive Manufacturing Of Thin-Walled Components: Investigation And Development Of Prediction Models With Respect To Path Planning, Bita Mohajernia

Electronic Theses and Dissertations

This dissertation focuses on the investigation of residual stress in metal additive manufacturing of thin-walled components. Residual stress is a critical issue in additive manufacturing processes as it can lead to structural deformations, reduced mechanical properties, and potential failure of the manufactured parts. The objective of this research is to develop a fast and accurate prediction model for residual stress using numerical and machine learning techniques, with a specific focus on path planning. To achieve the research objectives, the dissertation employs numerical simulations to understand the underlying physics and mechanics of residual stress formation in the additive manufacturing process. These …

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Variability Of Noise Exposure Forecast Outputs Due To The Selection Of Input Parameters, Junxian Zhao Sep 2023

Variability Of Noise Exposure Forecast Outputs Due To The Selection Of Input Parameters, Junxian Zhao

Electronic Theses and Dissertations

The growth of civil aviation and the resulting aircraft noise exposure and noise annoyance have become a serious environmental issue for residents living around airports. Land use planning and management is one method to mitigate noise and annoyance. It is one of four components of the Balanced Approach to Aircraft Noise Management adopted by International Civil Aviation Organization (ICAO). Effective land use and planning tries to remove conflicts between noise and residential communities by keeping noise sensitive functions away from levels of predicted high noise exposure. Authorities typically use noise contours to determine noise exposure around airports. Noise thresholds are …

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Digital Realization Of Spiking Neural Network, Mahsasadat Seyedbarhagh Sep 2023

Digital Realization Of Spiking Neural Network, Mahsasadat Seyedbarhagh

Electronic Theses and Dissertations

Spiking Neural Network which is known as the third generation of artificial neural networks can imitate the same biological patterns of human brain. Neuromorphic Computing is a multidisciplinary research topic which employs digital and analog platforms to implement bio-inspired systems and is able to operate parallelly with low-power consumption. This research study presents the digital design for several bio-inspired systems such as biophysical spiking neuron, calcium signaling astrocyte, and a neuron-astrocyte interaction models using various approximation methodologies. Astrocytes have an essential impact within the neural network and their role is to maintain support for neuron, control the ion hemostasis and …

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A Reinforcement Learning Algorithm For Training A Spiking Neural Network Agent, Seyede Narjes Zamani Sep 2023

A Reinforcement Learning Algorithm For Training A Spiking Neural Network Agent, Seyede Narjes Zamani

Electronic Theses and Dissertations

Over the past two decades, Spiking Neural Networks (SNNs), as the third generation of Artificial Neural Networks, have gained widespread use due to their ability to closely mimic human brain neuron behavior. Being spike-based and resembling biological neurons, SNNs have demonstrated superior energy efficiency compared to conventional counterparts. However, to fully harness their potential, effective training methods are essential. Despite significant progress in the field of biological implementation of SNNs, there remains a need for research to identify the most optimal learning approach. To address this, we employed Policy-based stochastic reinforcement learning to train a spiking neural network using Izhikevich …

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New Memristive Architecture For Digital Circuits Design, Farzad Mozafari Sep 2023

New Memristive Architecture For Digital Circuits Design, Farzad Mozafari

Electronic Theses and Dissertations

Before 1971, all the electronics were based on three basic circuit elements. Until a professor from UC Berkeley reasoned that another basic circuit element exists, which he called memristor; characterized by the relationship between the charge and the flux-linkage. A memristor is essentially a resistor with memory. The resistance of a memristor (Memristance) depends on the amount of current that is passing through the device. In 2008, a research group at HP Labs succeeded to build an actual physical memristor. HP's memristor was a nanometer scale titanium dioxide thin film, composed of two doped and undoped regions, sandwiched between two …

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Mitigation Of Asymmetrical Currents In Permanent Magnet Synchronous Machine With Unbalanced Stator Winding Impedance For Electric Vehicle Application, Khagendra Thapa Sep 2023

Mitigation Of Asymmetrical Currents In Permanent Magnet Synchronous Machine With Unbalanced Stator Winding Impedance For Electric Vehicle Application, Khagendra Thapa

Electronic Theses and Dissertations

The electric drive system of a permanent magnet synchronous machine (PMSM) with stator winding impedance asymmetry draws unbalanced three-phase stator currents if the conventional current control scheme is employed. Due to these asymmetrical stator currents, some issues such as uneven heating of the inverter phases and switches, additional losses in the motor due to skin and proximity effects, vibration and noise, uneven heating of the motor phases, and torque ripple appear in the PMSM drive. These effects reduce the reliability, efficiency, and lifespan of the machine. The conventional proportional-integral (PI) current controller in a PMSM drive is unable to mitigate …

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Prediction And Management Of Aircraft Noise Annoyance Around Canadian Airports, Julia Georgieva Jovanovic Sep 2023

Prediction And Management Of Aircraft Noise Annoyance Around Canadian Airports, Julia Georgieva Jovanovic

Electronic Theses and Dissertations

Noise pollution is a serious environmental problem affecting millions of people world-wide. Aircraft are one source of transportation noise that impacts residents in communities surrounding airports and flight paths. Noise is the biggest nuisance of airport operations and has resulted in complaints, protests, and even legal action. The burden of noise is likely to increase in the coming decades as quieter aircraft technologies lag traffic growth projections, and rapid urbanization narrows the buffer between airports and residential areas. Numerous physical and psychological effects of aircraft noise exposure have been studied, the most common of which is annoyance. Noise annoyance has …

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Microstructure, Mechanical Properties And Electrical Conductivities Of As-Cast Al-0.3mn Alloy, Wutian Shen Sep 2023

Microstructure, Mechanical Properties And Electrical Conductivities Of As-Cast Al-0.3mn Alloy, Wutian Shen

Electronic Theses and Dissertations

Al-0.3Mn was prepared by permanent steel mold casting (PMSC) with three different section thicknesses of 6, 10, 20 mm, and also by squeeze casting (SC) with a cross-sectional thickness of 20 mm under an applied pressure of 90 MPa. The first group of samples was employed to investigate the difference in mechanical and electrical properties between the PSMC Al-0.3Mn Alloy and high-purity (HP) Al (99.9%). The results of tensile testing indicated that the ultimate tensile strength (UTS), yield strength (YS) of the cast HP Al significantly increased to 72.3 and 20.4 MPa from 59.2 and 14.0 MPa. However, the elongation …

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A Comparison Of Battery Equivalent Circuit Model Parameter Extraction Approaches Based On Electrochemical Impedance Spectroscopy, Yuchao Wu Aug 2023

A Comparison Of Battery Equivalent Circuit Model Parameter Extraction Approaches Based On Electrochemical Impedance Spectroscopy, Yuchao Wu

Electronic Theses and Dissertations

This thesis compares three methods for estimating battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS). These methods are referred to as least squares (LS), exhaustive search (ES), and nonlinear least squares (NLS). The ES approach utilizes the LS method to roughly determine the lower and upper bounds of the ECM parameters, while the NLS approach incorporates a Monte Carlo run, allowing for different initial guesses to enhance the accuracy of EIS fitting. The proposed approaches are validated using both simulated and real-world EIS data. When the signal-to-noise ratio (SNR) is high, both the …

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A Multidisciplinary Design Methodology For Cyber-Physical Systems, Haider Al Fedhly Aug 2023

A Multidisciplinary Design Methodology For Cyber-Physical Systems, Haider Al Fedhly

Electronic Theses and Dissertations

Innovation drives the evolutionary solution era, where design is the anchor of its success. Product design is an iterative process of problem-solving and improvements where no matter how good a design is, it is possible to have improvements. Improving the design of a product should follow a systematic procedure to reduce the uncertainty that leads to complexity. Design framework methodology can aid in improving the design process by providing a measurable systematic approach. This research aims to form a comprehensive design framework methodology for cyber-physical products that integrate multiple disciplines. Drawing upon quantitative and qualitative literature meta-analysis, this study examines …

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Cognitive Load Detection Based On Speech In Automation Driving Systems, Obiajuru Onwunamoghor Ninduwezuor Aug 2023

Cognitive Load Detection Based On Speech In Automation Driving Systems, Obiajuru Onwunamoghor Ninduwezuor

Electronic Theses and Dissertations

Driver inattention is one of the leading causes of road accidents and fatal crashes. To mitigate these risk, Driver Monitoring System (DMS) has been developed and extensively experimented by the automobile industry. An overview of DMS is presented in this thesis with specific focus on driver inattention and cognitive state of the drivers. Research on the sources of driver inattention are reviewed, and a comprehensive classification is provided. Various safety systems that measure driver inattention based on driving behavior, hybrid measures and physiological measures are investigated. In particular, a non-invasive speech-based measure of physiological signal for detecting the cognitive load …

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Improving Carbon Nanoparticle Formation Modeling By Incorporating Physical Phenomena Through Advanced Simulation Approaches, Arash Khabazipur Jul 2023

Improving Carbon Nanoparticle Formation Modeling By Incorporating Physical Phenomena Through Advanced Simulation Approaches, Arash Khabazipur

Electronic Theses and Dissertations

Particles are essential components in many natural and human-made processes. Their formation, behavior, and impact on human life and the environment are critical areas of research. One of the most crucial and prevalent examples are carbon nanoparticles, which are typically 10-300 nm in diameter and produced in many processes involving the combustion of hydrocarbons. Carbon nanoparticles are of significant interest due to both their harmful impacts on human health and the environment and their values as nanomaterials. This PhD dissertation is composed of three research studies that aim to develop and implement numerical approaches to understand the phenomena and enhance …

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Reducing Energy Usage For Residential Furnace Blowers: Blade Re-Design And Assessment Of The Impact Of Flow Non-Uniformity Elimination, Mohammad Mirmohammadi Jul 2023

Reducing Energy Usage For Residential Furnace Blowers: Blade Re-Design And Assessment Of The Impact Of Flow Non-Uniformity Elimination, Mohammad Mirmohammadi

Electronic Theses and Dissertations

Residential furnace blowers are widely used in North America, but they often are designed to be low-cost rather than highly efficient. In this study, analysis of the literature yields an estimated adiabatic efficiency for typical furnace blowers of approximately 48%. The geometry of a typical furnace suggests much of the cause of this low efficiency is due to poor flow uniformity entering the blower. While the specific diameter and specific speed of the blower lie far from the Cordier diagram locus, these parameters cannot be dramatically changed due to space constraints. Thus, this study aims to quantify the efficiency gain …

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The Behavior Of Shelf Angles Made With Various Connectors, Aarish Khan Jul 2023

The Behavior Of Shelf Angles Made With Various Connectors, Aarish Khan

Electronic Theses and Dissertations

Masonry veneer is a very successful external wall design, used in almost all kinds of modern buildings and construction. The building code recommends that the self-weight of the brick veneer must be transferred to the structural backing with the help of shelf angles. The shelf angles are attached to the main structure frame through anchors. The Through bolts are an industry favorite anchor but has some persistent problems that do not comply with the requirements of current building codes. These bolts are uneconomical, time-consuming, and create thermal bridges. Although the Lag screw provides a better alternative to the Through bolts …

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Development Of Thermally Stable And Environmentally Robust Microelectromechanical Systems (Mems) Based Accelerometers, Hasnet Eftakher Uddin Ahmed Jun 2023

Development Of Thermally Stable And Environmentally Robust Microelectromechanical Systems (Mems) Based Accelerometers, Hasnet Eftakher Uddin Ahmed

Electronic Theses and Dissertations

Microelectromechanical systems (MEMS) inertial sensors are widely used in many motion sensing applications including acceleration and orientation. Many of these sensors employ a small resonating mass as the main sensing element. Various applications of MEMS resonating sensors require the sensor to endure temperature and dynamic environmental parameters variation, which can cause their resonance performance to degrade. This research focuses on developing understanding of improving thermal stability of MEMS resonating inertial sensor performance improvement and its characterization in dynamic environments. Thermal stability of the resonating structure can be achieved using doping-based passive compensation methods. Analytical and numerical modeling techniques are presented …

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Batch-Sizing And Machinability Data Systems For Milling Operations: An Optimal Sustainable Cost Of Quality Approach, Abdulnasser El-Gaddar Jun 2023

Batch-Sizing And Machinability Data Systems For Milling Operations: An Optimal Sustainable Cost Of Quality Approach, Abdulnasser El-Gaddar

Electronic Theses and Dissertations

Because of globalization and high competition in emerging markets, manufacturers strive to produce products with lower machining costs while maintaining high quality, and sustainability must be considered. This research aims to propose a mathematical optimization model that considers the internal quality cost, environmental impact approach, and the effect of buffering for the micro-computer-aided process planning problem (CAPP). The mathematical model is developed for different milling operations: face, side, and peripheral milling to optimize the machining parameters, namely, cutting speed, feed rate, axial depth of cut, radial depth of cut, and nose radius and batch sizing while maximizing profit and meeting …

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Multi-Period, Multi-Platform Design And Lot-Sizing For Hybrid Manufacturing Considering Stochastic Demand And Processing Time, Md Sadman Sakib Jun 2023

Multi-Period, Multi-Platform Design And Lot-Sizing For Hybrid Manufacturing Considering Stochastic Demand And Processing Time, Md Sadman Sakib

Electronic Theses and Dissertations

During the era of digitalization, customer demand has become more customized than before. For this reason, the variety of products is increasing rapidly. Manufacturing industries are experiencing extraordinary challenges due to frequent updates of customer requirements. Now the manufacturers are focusing more on mass customization than mass production to keep pace with this situation, however, managing variety using the make-to-stock strategy increases holding costs, and the make-to-order strategy increases lead time. Moreover, uncertainty in demand is making mass customization more challenging. Though hybrid manufacturing is a promising concept for variety management, very few works consider stochastic demand. The concept of …

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Improvement To An Existing Multi-Level Capacitated Lot Sizing Problem With Setup Carryover, Backlogging, And Emission Control, Rifat Bin Hasan Jun 2023

Improvement To An Existing Multi-Level Capacitated Lot Sizing Problem With Setup Carryover, Backlogging, And Emission Control, Rifat Bin Hasan

Electronic Theses and Dissertations

This paper presents a multi-level, multi-item, multi-period capacitated lot-sizing problem. The lot-sizing problem studies can obtain production quantities, setup decisions, and inventory levels in each period fulfilling the demand requirements with limited capacity resources, considering the Bill of Material (B.O.M.) structure while simultaneously minimizing the production, inventory, and machine setup costs. The paper proposes an exact solution to Chowdhury et al. (2018)'s[1] developed model, which considers the backlogging cost, setup carryover & greenhouse gas emission control to its model complexity. The problem contemplates the Dantzig-Wolfe (D.W.) decomposition to decompose the multi-level capacitated problem into a single-item uncapacitated lot-sizing sub-problem. To …

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The Importance Of Accurately Predicting Corner Separations In Fan Stall Point Identification With Steady Rans: Computations With The Helicity-Corrected Spalart-Allmaras Turbulence Model, Zhifan Yu Jun 2023

The Importance Of Accurately Predicting Corner Separations In Fan Stall Point Identification With Steady Rans: Computations With The Helicity-Corrected Spalart-Allmaras Turbulence Model, Zhifan Yu

Electronic Theses and Dissertations

This thesis applies a modified Spalart-Allmaras (SA) turbulence model, the helicity-corrected Spalart-Allmaras (HCSA) model, in incompressible steady Reynolds-averaged Navier-Stokes (RANS) computations to reduce the numerical simulation run time for fan stall inception prediction. Computations are carried out using the OpenFOAM package. This manuscript-style thesis contains two main chapters, each stemming from conference papers. First, the HCSA turbulence model is applied to a low-speed axial fan, known as the boundary layer ingestion (BLI) fan, for fan stall behavior simulation. Both RANS and unsteady RANS (URANS) with the HCSA model and RANS with the original SA model are performed, with all results …

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Application Of Equilibrium-Based Pah Adsorption To Modelling Graphene Synthesis In A Microwave-Assisted Plasma Reactor, Jiahai Fan Jun 2023

Application Of Equilibrium-Based Pah Adsorption To Modelling Graphene Synthesis In A Microwave-Assisted Plasma Reactor, Jiahai Fan

Electronic Theses and Dissertations

Graphene is a new material with potential to significantly impact many applications due to its unique physical and chemical properties. However, the commercialization of graphene is impeded by issues in graphene mass production. Recently, a potential production method that uses a microwave-assisted plasma reactor to produce graphene has been developed, and this method might make mass production of graphene possible. To aid in development of this new method, a novel computational model to simulate graphene synthesis in this system was developed. While it was the first attempt at modelling graphene synthesis in such a system, the model required improvement due …

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Model-Guided Extremum Seeking Control For Mechanical Ventilators, Ryan Keith Wardell Jun 2023

Model-Guided Extremum Seeking Control For Mechanical Ventilators, Ryan Keith Wardell

Electronic Theses and Dissertations

Mechanical ventilators are an important lifesaving medical device and because of the COVID-19 pandemic, they were in a massive demand for them to help the patients most severely affected by the disease. A large number of open-source hardware ventilator projects were established during the pandemic, most of which did not provide sufficient information on the design of their control systems. In this thesis, a model-guided extremum seeking control scheme is proposed for use on a open-source hardware ventilator design. The performance of the control scheme is intended to not be significantly affected by changes to the patient, nor to variations …

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Parametric Automobile And Open-Jet Wind Tunnel Models And Their Application To Improved Drag Coefficient Corrections, Matthew Fujs Jun 2023

Parametric Automobile And Open-Jet Wind Tunnel Models And Their Application To Improved Drag Coefficient Corrections, Matthew Fujs

Electronic Theses and Dissertations

The simulation of automotive wind tunnel flow around a vehicle typically relies on the use of simplified models due to the complex, and often proprietary geometries of real test configurations. Current simplified models achieve a low computational cost in computational fluid dynamics (CFD) but fall short at qualitatively capturing a modern vehicle’s complex geometry due to being overly abstract; other models are more accurate but offer only discrete dimensional configurations. The first part of this thesis describes new parametric models for both vehicles and open-jet wind tunnels which aim to represent widely varying geometries through continuous dimensional variability, while remaining …

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Real-Time On-Site Opengl-Based Object Speed Measuring Using Constant Sequential Image, Aiming Deng Jun 2023

Real-Time On-Site Opengl-Based Object Speed Measuring Using Constant Sequential Image, Aiming Deng

Electronic Theses and Dissertations

This thesis presents a method that can detect moving objects and measure their speed of movement, using a constant rate series of sequential images, such as video recordings. It uses the industry standard non-vendor specific OpenGL ES so can be implemented on any platform with OpenGL ES support. It can run on low-end embedded system as it uses simple and basic foundations based on a few assumptions to lowering the overall implementation complexity in OpenGL ES. It also does not require any special peripheral devices, so existing infrastructure can be used with minimal modification, which will further lower the cost …

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Machine Learning Approaches For Healthcare Analysis, Bashier Omar Elkarami Jun 2023

Machine Learning Approaches For Healthcare Analysis, Bashier Omar Elkarami

Electronic Theses and Dissertations

Machine learning (ML)is a division of artificial intelligence that teaches computers how to discover difficult-to-distinguish patterns from huge or complex data sets and learn from previous cases by utilizing a range of statistical, probabilistic, data processing, and optimization methods. Nowadays, ML plays a vital role in many fields, such as finance, self-driving cars, image processing, medicine, and Speech recognition. In healthcare, ML has been used in applications such as the detection, prognosis, diagnosis, and treatment of diseases due to Its capability to handle large data. Moreover, ML has exceptional abilities to predict disease by uncovering patterns from medical datasets. Machine …

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