Engineering Commons^™

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi

Theses and Dissertations--Electrical and Computer Engineering

The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …

Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan

Theses and Dissertations--Mechanical Engineering

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …

Life Cycle Assessment Of Air Classification As A Sulfur Mitigation Technology In Pine Residue Feedstocks, Ashlee Edmonson

Theses and Dissertations--Biosystems and Agricultural Engineering

Sulfur accumulation during biofuel production is pollutive, toxic to conversion catalysts, and causes the premature breakdown of processing equipment. Air classification is an effective preprocessing technology for ash and sulfur removal from biomass feedstocks. A life cycle assessment (LCA) sought to understand the environmental impacts of implementing air classification as a sulfur-mitigation technique for pine residues. Energy demand and material balance for preprocessing were simulated using SimaPro and the Argonne National Laboratory’s GREET model, specifically focusing on comparing the global warming potential (GWP) of grid electricity versus bioelectricity scenarios. Overall, the grid electricity scenario had a GWP impact over 7 …

Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our comprehension of the three-dimensional precision of meteorological measurements obtained using small unmanned aircraft systems (UAS). Two complimentary experiments were conducted to achieve this objective.

The first experiment entailed the development and implementation of a system to determine the global navigation satellite system (GNSS) position accuracy on a UAS platform. This system was utilized to assess the static and dynamic accuracy of L1 and L1/L2 GNSS receivers in real-time kinematic (RTK) and non-RTK fix modes. Adjusted two-sample t-tests revealed significant differences in horizontal and vertical error between RTK and non-RTK receivers …

Modeling The Early Visual System, Nicholas Lanning

Theses and Dissertations--Electrical and Computer Engineering

There are two encoding schema present in simple cells in the early visual system of vertebrates: the retinal simple cells activate highly when the receptive field contains a center surround stimulus, while the primary visual cortex’s (V1) simple cells activate highly when the receptive field contains visual edges. Work has been done in the past to enforce constraints on visual machine learning such that the retinal or V1 encoding is learned, but this work is often done to emulate retinal and V1 encoding in a vacuum. Recent work using convolutional neural networks focuses on anatomical constraints along with a supervised …

Surface Properties, Work Function, And Thermionic Electron Emission Characterization Of Materials For Next-Generation Dispenser Cathodes, Antonio Mantica

Theses and Dissertations--Chemical and Materials Engineering

A dispenser cathode’s ability to thermionically emit electrons is highly dependent on its material properties, especially those of the surface. Understanding the relationship between surface properties and electron emission, therefore, is vital to reach the next generation of the many vacuum electron devices (VEDs) that rely on the physics of electron emission. In the past century, many techniques have been developed to characterize material surfaces and quantify thermionic emission. These techniques are based on a wide range of different physical phenomena, including measuring photoemission via the photoelectric effect, measuring the electrostatic potential between metals in electrical contact, and current collection …

Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael

Theses and Dissertations--Electrical and Computer Engineering

Classical neural networks such as feedforward multilayer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. This research investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to mitigate challenges in power distribution system state estimation and forecasting based upon conventional analytic methods. The ability of MLPs to perform regression to perform power system state estimation will be investigated. MLPs are considered based upon their promise to learn …

Establishing The Foundation To Robotize Complex Welding Processes Through Learning From Human Welders Based On Deep Learning Techniques, Rui Yu

Theses and Dissertations--Electrical and Computer Engineering

As the demand for customized, efficient, and high-quality production increases, traditional manufacturing processes are transforming into smart manufacturing with the aid of advancements in information technology, such as cyber-physical systems (CPS), the Internet of Things (IoT), big data, and artificial intelligence (AI). The key requirement for integration with these advanced information technologies is to digitize manufacturing processes to enable analysis, control, and interaction with other digitized components. The integration of deep learning algorithm and massive industrial data will be critical components in realizing this process, leading to enhanced manufacturing in the Future of Work at the Human-Technology Frontier (FW-HTF).

This …

Optimal Design Of Special High Torque Density Electric Machines Based On Electromagnetic Fea, Murat G. Kesgin

Theses and Dissertations--Electrical and Computer Engineering

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, electric vehicles, and industrial automation. Permanent magnet (PM) machines that incorporate a magnetic gearing effect are particularly useful for these applications due to their potential for achieving extremely high torque density. However, when the number of rotor polarities is increased, there is a corresponding need to increase the number of stator slots and coils proportionally. This can result in manufacturing challenges. A new topology of an axial-flux vernier-type machine of MAGNUS type has been presented to address the mentioned limitation. These machines can …

Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina

Theses and Dissertations--Computer Science

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid.

Trading energy among users in a decentralized fashion has been referred …

Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones

Theses and Dissertations--Electrical and Computer Engineering

There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual …

A Phase Change Memory And Dram Based Framework For Energy-Efficient And High-Speed In-Memory Stochastic Computing, Supreeth Mysore

Theses and Dissertations--Electrical and Computer Engineering

Convolutional Neural Networks (CNNs) have proven to be highly effective in various fields related to Artificial Intelligence (AI) and Machine Learning (ML). However, the significant computational and memory requirements of CNNs make their processing highly compute and memory-intensive. In particular, the multiply-accumulate (MAC) operation, which is a fundamental building block of CNNs, requires enormous arithmetic operations. As the input dataset size increases, the traditional processor-centric von-Neumann computing architecture becomes ill-suited for CNN-based applications. This results in exponentially higher latency and energy costs, making the processing of CNNs highly challenging.

To overcome these challenges, researchers have explored the Processing-In Memory (PIM) …

The Effects Of Reference-Command Preview On The Strategies That Humans Use In Command-Following Tasks, Amelia J. S. Sheffler

Theses and Dissertations--Mechanical Engineering

This thesis presents results from an experiment in which 22 human subjects each interact with a dynamic system 40 times over a one-week period. For each interaction, a subject performs a command-following task, where the reference command is the same for all 22 subjects but different on each trial. The subjects are divided into 2 groups of 11 subjects. One group performs the command-following task without reference-command preview. The other group is provided with 1-s preview of the reference command. The experimental results are used to examine the effects of reference-command preview. For the group with 1-s reference-command preview, the …

Experimental Comparison Of Two Sampled-Data Adaptive Control Algorithms For Rejecting Sinusoidal Disturbances, William Grayson Woods

Theses and Dissertations--Mechanical Engineering

We review two adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. We present modifications to the algorithms that address the problems of sensor noise and actuator saturation. We demonstrate the effectiveness of the algorithms and compare the performance of the algorithms via numerical simulation and experimental testing.

Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini

Theses and Dissertations--Electrical and Computer Engineering

Fault location remains an extremely pivotal feature of the electric power grid as it ensures efficient operation of the grid and prevents large downtimes during fault occurrences. This will ultimately enhance and increase the reliability of the system. Since the invention of the electric grid, many approaches to fault location have been studied and documented. These approaches are still effective and are implemented in present times, and as the power grid becomes even more broadened with new forms of energy generation, transmission, and distribution technologies, continued study on these methods is necessary. This thesis will focus on adopting the artificial …

Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay

Theses and Dissertations--Mechanical Engineering

This dissertation presents new results on multi-agent formation control and applies the new control algorithms to quadrotor unmanned air vehicles. First, this dissertation presents a formation control algorithm for double-integrator agents, where the formation is time varying and the agents’ controls satisfy a priori bounds (e.g., the controls accommodate actuator saturation). The main analytic results provide sufficient conditions such that all agents converge to the desired time-varying relative positions with one another and the leader, and have a priori bounded controls (if applicable). We also present results from rotorcraft experiments that demonstrate the algorithm with time-varying formations and bounded controls. …

Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour

Theses and Dissertations--Electrical and Computer Engineering

Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems may help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech is required, which is not readily available for dysarthric talkers.

In this dissertation, we investigate dysarthric speech augmentation and synthesis methods. To better understand differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels, a comparative study between typical and dysarthric speech was conducted. These characteristics are important components for dysarthric speech modeling, …

Parametric Average-Value Modeling, Simulation, And Characterization Of Machine-Rectifier Systems, Isuje Ojo

Theses and Dissertations--Electrical and Computer Engineering

There are many techniques for modeling and simulation of synchronous machine-rectifier systems. The more common approaches are the detailed and average-value modeling techniques. The detailed simulation technique takes into account the details of the diode switching and is both very accurate and very expensive in terms of computational resources. To alleviate this disadvantage, the average-value modeling technique is often utilized. In this approach, the details of diode switching are neglected or averaged. In that light, the work presented herein proposes a unique saliency-sensitive parametric average-value model (SSPAVM) of the synchronous machine-rectifier system. This model extends existing parametric average-value models to …

An Electrochemical-Mechanical Investigation Of Next Generation Lithium Metal Electrode And Solid Electrolyte, Andrew Meyer

Theses and Dissertations--Chemical and Materials Engineering

Lithium-ion batteries (LIBs) are a staple in today’s society. From our cellphones, laptops, power tools, the ever-growing electric vehicle, and many more application, LIBs are more important to us than most realize. They provide the best combination of both high-energy and high-power density compared to other battery types such as Ni-Cd, Ni-MH, or the lead acid batteries used in our cars. Plus, LIBs are much safer. However, as new technologies grow and are developed, the demand for higher energy and power density, better safety, lower costs, and longer life increases. One way to achieve the ever-increasing demands is to replace …

Laptop Recycling Case Study: Estimating The Contained Value And Value Recovery Process Feasibility Of End-Of-Life Consumer Electronics, Zebulon Hart

Theses and Dissertations--Mining Engineering

Work has been done to establish, through the development and use of novel assay techniques and analysis metrics, the contained value of a sampling of laptop computers (as an analog for myriad e-waste sources). This work has conceptualized e-waste as an alternative to geologic-origin complex metallic ores and has likewise evaluated the feasibility of value recovery from e-waste sources in a similar manner to an ore. The application of conventional and novel mineral separation techniques to e-waste recycling processes has been evaluated and positive results are demonstrated. Further, this work has demonstrated the ability to identify the presence of base …

Three Dimensional Photonics Structures: Design And Applications, Mansoor Sultan

Theses and Dissertations--Electrical and Computer Engineering

Photonics is an emerging technology for light control, emission, and detection. Photonic devices control photons the same way electronic circuits control electrons in active or passive mode depending on the energy requirement of the device. This dissertation will discuss the design, fabrication, testing of photonic structures with applications including imaging and renewable energy. First, we developed a novel lithography method for fluoropolymer resist based on variable pressure electron beam lithography (VP-EBL). VP-EBL proves to be an efficient method for patterning a widely used, but challenging to process, fluoropolymer, Teflon AF. However, rather than solely mitigating charging, the ambient gas is …

A Computational Exploration Of The Scandate Cathode Surface, Shankar Miller-Murthy

Theses and Dissertations--Chemical and Materials Engineering

The exact surface configuration of scandate cathodes has been a point of contention for the materials community for a long time. Without proper understanding of it and the related structures and emission mechanisms, scandate cathodes remain patchy and unreliable emitters. Thus, density functional theory techniques were applied to various potential surface arrangements and found that there are several low-energy surfaces with low work functions that incorporate a scandium interlayer between tungsten and oxygen or otherwise have a scandium-on-tungsten structure. Furthermore, it was discovered that adding a monolayer of scandium directly to a tungsten surface is surprisingly favorable, thermodynamically. While none …

Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni

Theses and Dissertations--Computer Science

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out …

Models And Optimal Controls For Smart Homes And Their Integration Into The Electric Power Grid, Huangjie Gong

Theses and Dissertations--Electrical and Computer Engineering

Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) …

Modeling Human Control Behavior In Command-Following Tasks, Sajad Koushkbaghi

Theses and Dissertations--Mechanical Engineering

Humans interact with a variety of complex dynamic systems on a daily basis. However, they are often the lesser understood component of human-in-the-loop (HITL) systems. In this dissertation, we present the results of two HITL experiments to investigate the control strategies that humans use when performing command-following tasks. The first experiment is designed to investigate the control strategies that humans use to interact with nonlinear dynamic systems. Two groups of human subjects interact with a dynamic system and perform a command-following task. One group interacts with a linear time-invariant (LTI) dynamic system and the other group interacts with a Wiener …

Development Of Dc Circuit Breakers For Medium-Voltage Electrified Transportation, Trevor Morgan Arvin

Theses and Dissertations--Electrical and Computer Engineering

Medium-voltage DC (MVDC) distribution is an enabling technology for the electrification of transportation such as aircraft and shipboard. One main obstacle for DC distribution is the lack of adequate circuit fault protection. The challenges are due to the rapidly rising fault currents and absence of zero crossings in DC systems compared to AC counterparts. Existing DC breaker solutions lack comprehensive consideration of energy efficiency, power density, fault interruption speed, reliability, and implementation cost.

In this thesis, two circuit topologies of improved DC circuit breakers are developed: the resonant current source based hybrid DC breaker (RCS-HDCB) and the high temperature superconductor …

Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi

Theses and Dissertations--Computer Science

Computer networks are becoming more complex and challenging to operate, manage, and protect. As a result, Network policies that define how network operators should manage the network are becoming more complex and nuanced. Unfortunately, network policies are often an undervalued part of network design, leaving network operators to guess at the intent of policies that are written and fill in the gaps where policies don’t exist. Organizations typically designate Policy Committees to write down the network policies in the policy documents using high-level natural languages. The policy documents describe both the acceptable and unacceptable uses of the network. Network operators …

Energy-Efficient And Secure Hardware Using Adiabatic Logic And Non-Volatile Mtj Devices, Zachary Kahleifeh

Theses and Dissertations--Electrical and Computer Engineering

Internet of Things (IoT) is a collection of devices that exchange data through a network to implement complex applications. IoT devices increase the quality of life of their user base which has a wide variety such as the medical field, consumer electronics, and the manufacturing sector. However, IoT devices have several challenges that need to be overcome namely, security and energy consumption. The threat vector that IoT devices face is growing and includes the following threats, the leakage of information through a side-channel attack known as the Correlation Power Analysis (CPA), authentication, piracy, etc. A side-channel attack is an attack …

Explainable Data-Driven Motor Condition Monitoring And Fault Disgnosis, Yuming Wang

Theses and Dissertations--Electrical and Computer Engineering

Industrial motors are widely used in various fields such as power generation, mining, and manufacturing. Motor faults and time-consuming maintenance process will lead to serious economic losses in this context. To monitor motor faults and detect motor conditions, different types of sensors that can test vibration and current signals are mounted on motors. However, the main challenge was how to use information gained by sensors to analyze or diagnose motor conditions.

Machine learning is a popular technology in recent years, and it's very suitable for crunching and analyzing data. As an important subset of machine learning, deep learning is suitable …