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Articles 1 - 30 of 51
Full-Text Articles in Engineering
Robust Visual Observer And Controller Design For System Modeled On Se(3) With Camera Measurements, Tong Zhang
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. …
Memristor-Based Digital Circuit Design, Khalid Mohammed Alammari
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 …
Skin Cancer Detection By Deep Learning Algorithms, Faezeh Mohammadi Aydoghmishi
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 …
Anisotropic Mechanical Material Investigation On Moisture And Strain Rate Sensitivity Of Direct Compounded Compression Moulded Glass/Pa6 Lfts, Pouya Mohammadkhani
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 …
Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi
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 …
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 …
Variability Of Noise Exposure Forecast Outputs Due To The Selection Of Input Parameters, Junxian Zhao
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 …
Digital Realization Of Spiking Neural Network, Mahsasadat Seyedbarhagh
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 …
A Reinforcement Learning Algorithm For Training A Spiking Neural Network Agent, Seyede Narjes Zamani
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 …
New Memristive Architecture For Digital Circuits Design, Farzad Mozafari
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 …
Mitigation Of Asymmetrical Currents In Permanent Magnet Synchronous Machine With Unbalanced Stator Winding Impedance For Electric Vehicle Application, Khagendra Thapa
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 …
Investigation Of Solar Assisted Water Heating System Integrated With Pcm Storage Tank, Sohrab Saadat Pour
Investigation Of Solar Assisted Water Heating System Integrated With Pcm Storage Tank, Sohrab Saadat Pour
Major Papers
This study discusses the importance of integrating renewable energy sources, particularly Solar Water Heating Systems (SWHSs) with Thermal Energy Storage (TES) technology, to address the growing energy consumption in residential buildings, aligning with the United Nations' Sustainable Development 2030 agenda. The combination of SWHSs and TES helps reduce building energy consumption by storing excess solar energy, which can be used for Domestic Hot Water (DHW) needs during peak periods and nighttime. The study proposes a dynamic model using TRNSYS software to simulate a SWHS over a 30-hour period in a residential apartment. Additionally, a novel MATLAB component simulates an encapsulated …
Studying The Influential Parameters Of An Office Building’S Energy Consumption In North America, Naveen Raghava Krishnan Bhoopal
Studying The Influential Parameters Of An Office Building’S Energy Consumption In North America, Naveen Raghava Krishnan Bhoopal
Major Papers
The study of building energy consumption has gained immense significance in recent times due to the burgeoning global population and the rapid depletion of energy resources. The present research focuses on analyzing individual parameters that impact building energy usage and devising methods and strategies to reduce energy consumption. An existing office building in Philadelphia was chosen as a reference for simulation in TRNSYS. The factors that affect the building, such as ambient temperature, solar radiation, building envelope, wind speed, and internal gains, were studied and defined according to the existing building standards. Predictive modeling is performed with these inputs for …
Prediction And Management Of Aircraft Noise Annoyance Around Canadian Airports, Julia Georgieva Jovanovic
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 …
Microstructure, Mechanical Properties And Electrical Conductivities Of As-Cast Al-0.3mn Alloy, Wutian Shen
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 …
Cognitive Load Detection Based On Speech In Automation Driving Systems, Obiajuru Onwunamoghor Ninduwezuor
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 …
Reducing Energy Usage For Residential Furnace Blowers: Blade Re-Design And Assessment Of The Impact Of Flow Non-Uniformity Elimination, Mohammad Mirmohammadi
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 …
Multi-Period, Multi-Platform Design And Lot-Sizing For Hybrid Manufacturing Considering Stochastic Demand And Processing Time, Md Sadman Sakib
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 …
Improvement To An Existing Multi-Level Capacitated Lot Sizing Problem With Setup Carryover, Backlogging, And Emission Control, Rifat Bin Hasan
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 …
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 …
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 …
Parametric Automobile And Open-Jet Wind Tunnel Models And Their Application To Improved Drag Coefficient Corrections, Matthew Fujs
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 …
Machine Learning Approaches For Healthcare Analysis, Bashier Omar Elkarami
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 …
Model-Guided Extremum Seeking Control For Mechanical Ventilators, Ryan Keith Wardell
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 …
Real-Time On-Site Opengl-Based Object Speed Measuring Using Constant Sequential Image, Aiming Deng
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 …
Strategies To Improve The Electrochemical Performance Of Aluminum Anodes In Primary Alkaline Aluminum-Air Batteries, Razieh Kiani Harchegani
Strategies To Improve The Electrochemical Performance Of Aluminum Anodes In Primary Alkaline Aluminum-Air Batteries, Razieh Kiani Harchegani
Electronic Theses and Dissertations
Passivation layers and self-corrosion developed on the Aluminum anodes in alkaline Aluminum-air batteries can significantly reduce the widespread application and capacity density of the batteries. Most corrosion prevention techniques focus on changing the electrode and electrolyte, including electrode alloying, additives for the electrolyte, and nonaqueous electrolytes. This thesis concentrates on some novel approaches like application of ultrasonic waves, as well as cold working to prevent the formation of passivation layers and hydrogen evolution. Furthermore, a conventional strategy of adding different inhibitors, including cerium chloride, a hybrid inhibitor of sodium vanadate and nanoclay is investigated. Experimental analyses were performed using ultrasonication …
Multicriteria Consensus Models To Support Intelligent Group Decision-Making, Hossein Hassani
Multicriteria Consensus Models To Support Intelligent Group Decision-Making, Hossein Hassani
Electronic Theses and Dissertations
The development of intelligent systems is progressing rapidly, thanks to advances in information technology that enable collective, automated, and effective decision-making based on information collected from diverse sources. Group decision-making (GDM) is a key part of intelligent decision-making (IDM), which has received considerable attention in recent years. IDM through GDM refers to a decision-making problem where a group of intelligent decision-makers (DMs) evaluate a set of alternatives with respect to specific attributes. Intelligent communication among DMs aims to give orders to the available alternatives. However, GDM models developed for IDM must incorporate consensus support models to effectively integrate input from …
Experimental Study On The Behaviour Of A Magnetorheological (Mr) Damper And Evaluation Of Numerical Models, Shelair Sinjari
Experimental Study On The Behaviour Of A Magnetorheological (Mr) Damper And Evaluation Of Numerical Models, Shelair Sinjari
Electronic Theses and Dissertations
MR dampers are smart dampers that improve structural performance through vibration control. Vibration of tall or flexible structures and structural elements induced by dynamic loads such as wind and earthquakes can cause severe damage to the structure and discomfort for individuals. Therefore, dampers are commonly installed to increase the energy dissipation capacity and mitigate large amplitude vibrations. MR dampers are gaining recognition because of the unique rheological properties offered by the magnetically sensitive MR fluid. Changes to the current level, along with the frequency and amplitude of vibration, affect the force-displacement and force-velocity hysteresis relationship and thus the amount of …
Dynamic Mode Decomposition As A Tool For Reducing Computational Time In Numerical Simulation Of Complex Flows, Laura Amelia George
Dynamic Mode Decomposition As A Tool For Reducing Computational Time In Numerical Simulation Of Complex Flows, Laura Amelia George
Electronic Theses and Dissertations
The length of simulation time for unsteady computational fluid dynamics (CFD) is often based on intuition or best practices, as there is no established convergence criteria to guarantee that sufficient flow time has elapsed to resolve all spatio-temporal content. Thus, these simulations are often run longer than necessary, but this increases the run time and computational resources required. This thesis first introduces an algorithm, based on dynamic mode decomposition (DMD), that can determine when continuing an unsteady CFD computation no longer yields additional spatio-temporal information. This algorithm is demonstrated on an analytical dataset as well as two CFD test cases: …
Energy Efficient Spectrum Sensing By Wireless Sensor Networks, Seyedehmarieh Mirzaaghaeianamiri
Energy Efficient Spectrum Sensing By Wireless Sensor Networks, Seyedehmarieh Mirzaaghaeianamiri
Electronic Theses and Dissertations
Today, due to the increase in the number of users and the need to provide high-rate multimedia services, cognitive radio techniques can be a promising practical solution. In cognitive networks, the unlicensed (secondary) users sense a spectrum utilized by the licensed (primary) users. Due to the interference of the primary users, fast and reliable spectrum sensing is an important challenge in cognitive radio networks. In this dissertation, the resource allocation problem is investigated under min-max optimization framework for establishing fair energy efficiency in wireless sensor networks (WSNs). In fact, we study the sensor selection and power allocation problem in a …