Electrical and Computer Engineering Commons^™

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …

Low Loss Plasmon-Assisted Integrated Photonics, Dhruv Fomra

Theses and Dissertations

Photonic integrated circuits (PICs), semiconductor chips with both photonic and electronic elements, are seeing rapid development and have the potential to transform several industries, such as autonomous driving, computing, telecommunication and quantum networks. However, realization and wide adoption of PICs across the various fields faces a key challenge – soze disparity between electronic (~0.01 um) and photonic components (~100’s of um). Plasmonics, a technology which confines light to the interface of metals and dielectrics, has a potential to address challenges. In particular, it has been shown to led to smaller devices (~10 um or less), enabling higher density optical circuits …

Linear And Nonlinear Optical Effects In High Carrier Concentration Oxides And Nitrides At Epsilon-Near-Zero, Ray Secondo

Theses and Dissertations

Nonlinear optics has been an important method for achieving ultrafast light manipulation. Recently, ENZ material have gained interest due to inherent advantages such as slow light, improved confinement, and ideal relaxation times, the nonlinear response of these materials, such as the intensity-dependent-refractive-index, are ultra-large yet remain ultra-fast. This experimental discovery of epsilon-near-zero enhancement has thus opened new avenues in nonlinear optics research in recent years, and while experiments have continued to progress a theoretical understanding of the processes and origins of nonlinear optical enhancement at epsilon-near-zero has lagged.

To fill this gap, the work herein focuses on uncovering the mechanisms …

A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos

Theses and Dissertations

Characterizing the attacker’s perspective is essential to assessing the security posture and resilience of cyber-physical systems. The attacker’s perspective is most often achieved by cyber-security experts (e.g., red teams) who critically challenge and analyze the system from an adversarial stance. Unfortunately, the knowledge and experience of cyber-security experts can be inconsistent leading to situations where there are gaps in the security assessment of a given system. Structured security review processes (such as TAM, Mission Aware, STPA-SEC, and STPA-SafeSec) attempt to standardize the review processes to impart consistency across an organization or application domain. However, with most security review processes, the …

Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu

Theses and Dissertations

Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly …

Perovskite Thin Films Annealed In Supercritical Fluids For Efficient Solar Cells, Gilbert Annohene

Theses and Dissertations

In the field of photovoltaics, scientists and researchers are working fervently to produce a combination of efficient, stable, low cost and scalable devices. Methylammonium lead trihalide perovskite has attracted intense interest due to its high photovoltaic performance, low cost, and ease of manufacture. Their high absorption coefficient, tunable bandgap, low-temperature processing, and abundant elemental constituent provide innumerable advantages over other thin film absorber materials. Since the perovskite film is the most important in the device, morphology, crystallization, compositional and interface engineering have been explored to boost its performance and stability. High temperatures necessary for crystallization of organic-inorganic hybrid perovskite films …

Learning-Based Predictive Control Approach For Real-Time Management Of Cyber-Physical Systems, Roja Eini

Theses and Dissertations

Cyber-physical systems (CPSs) are composed of heterogeneous, and networked hardware and software components tightly integrated with physical elements [72]. Large-scale CPSs are composed of complex components, subject to uncertainties [89], as though their design and development is a challenging task. Achieving reliability and real-time adaptation to changing environments are some of the challenges involved in large-scale CPSs development [51]. Addressing these challenges requires deep insights into control theory and machine learning. This research presents a learning-based control approach for CPSs management, considering their requirements, specifications, and constraints. Model-based control approaches, such as model predictive control (MPC), are proven to be …

Development Of An Anatomically And Electrically Conductive Brain Phantom For Transcranial Magnetic Stimulation, Hamzah A. Magsood

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for diagnostics, prognostic, and treatments of various neurological diseases. However, the lack of anatomically realistic brain phantoms has made the experimental verification of stimulation strength in the form of induced electric fields/voltages in the brain tissues an impediment to developing new TMS coils, stimulators, and treatment protocols. There are significant technological, safety, and ethical limitations to test the potential TMS treatment procedures or develop enhancements and refine them on humans or animals. This work aims to bridge the gap by introducing and developing an innovative manufacturing and fabrications process to produce a …

Reliable Navigation For Suas In Complex Indoor Environments, Andrew J. Fabian

Theses and Dissertations

Indoor environments are a particular challenge for Unmanned Aerial Vehicles (UAVs). Effective navigation through these GPS-denied environments require alternative localization systems, as well as methods of sensing and avoiding obstacles while remaining on-task. Additionally, the relatively small clearances and human presence characteristic of indoor spaces necessitates a higher level of precision and adaptability than is common in traditional UAV flight planning and execution. This research blends the optimization of individual technologies, such as state estimation and environmental sensing, with system integration and high-level operational planning.

The combination of AprilTag visual markers, multi-camera Visual Odometry, and IMU data can be used …

Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar

Theses and Dissertations

With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted …

Mathematical Models Of Cellular Signaling And Supramolecular Self-Assembly, Pratip Rana

Theses and Dissertations

Synthetic biologists endeavor to predict how the increasing complexity of multi-step signaling cascades impacts the fidelity of molecular signaling, whereby cellular state information is often transmitted with proteins diffusing by a pseudo-one-dimensional stochastic process. We address this problem by using a one-dimensional drift-diffusion model to derive an approximate lower bound on the degree of facilitation needed to achieve single-bit informational efficiency in signaling cascades as a function of their length. We find that a universal curve of the Shannon-Hartley form describes the information transmitted by a signaling chain of arbitrary length and depends upon only a small number of physically …

On-Demand Electrically Induced Decomposition Of Thin-Film Nitrocellulose Membranes For Wearable Or Implantable Biosensor Systems, Benjamin M. Horstmann

Theses and Dissertations

Implantable or subcutaneous biosensors used for continuous health monitoring have a limited functional lifetime requiring frequent replacement and therefore may be highly discomforting to the patient and become costly. One possible solution to this problem is use of biosensor arrays where each individual reserve sensor can be activated on-demand when the previous one becomes inoperative due to biofouling or enzyme degradation. Each reserve biosensor in the array is housed in an individual Polydimethylsiloxane (PDMS) well and is protected from exposure to bodily fluids such as interstitial fluid ( ISF) by a thin-film nitrocellulose membrane. Controlled activation is achieved by decomposing …

Improving Grid Hosting Capacity And Inertia Response With High Penetration Of Renewable Generation, Hamidreza Sadeghian

Theses and Dissertations

To achieve a more sustainable supply of electricity, utilizing renewable energy resources is a promising solution. However, the inclusion of intermittent renewable energy resources in electric power systems, if not appropriately managed and controlled, will raise a new set of technical challenges in both voltage and frequency control and jeopardizes the reliability and stability of the power system, as one of the most critical infrastructures in the today’s world. This dissertation aims to answer how to achieve high penetration of renewable generations in the entire power system without jeopardizing its security and reliability. First, we tackle the data insufficiency in …

Optical Spectroscopy And Theoretical Modelling Of Carrier Dynamics In Group-Iv Alloy Quantum Dots, Rahnuma Rahman

Theses and Dissertations

In recent years, Ge_1−xSn_x alloy quantum dots (QDs) have attracted significant interest due to their potential applications in photodetectors and light emitting devices in visible to mid IR spectral range and compatibility with silicon based platforms. While bulk Ge is an indirect bandgap semiconductor (0.66 eV), direct transitions can be made possible by incorporation of α-Sn at concentrations of ~10%, which however lowers the bandgap. Utilizing quantum confinement by reducing the size to below the Bohr radius also promotes direct transitions and more importantly increases the fundamental transition energies in GeSn alloy QDs, making them suitable for …

Multilevel Runtime Verification For Safety And Security Critical Cyber Physical Systems From A Model Based Engineering Perspective, Smitha Muralidhar Gautham

Theses and Dissertations

Advanced embedded system technology is one of the key driving forces behind the rapid growth of Cyber-Physical System (CPS) applications. CPS consists of multiple coordinating and cooperating components, which are often software-intensive and interact with each other to achieve unprecedented tasks. Such highly integrated CPSs have complex interaction failures, attack surfaces, and attack vectors that we have to protect and secure against. This dissertation advances the state-of-the-art by developing a multilevel runtime monitoring approach for safety and security critical CPSs where there are monitors at each level of processing and integration. Given that computation and data processing vulnerabilities may exist …

Electric Field Control Of Fixed Magnetic Skyrmions For Energy Efficient Nanomagnetic Memory, Dhritiman Bhattacharya

Theses and Dissertations

To meet the ever-growing demand of faster and smaller computers, increasing number of transistors are needed in the same chip area. Unfortunately, Silicon based transistors have almost reached their miniaturization limits mainly due to excessive heat generation. Nanomagnetic devices are one of the most promising alternatives of CMOS. In nanomagnetic devices, electron spin, instead of charge, is the information carrier. Hence, these devices are non-volatile: information can be stored in these devices without needing any external power which could enable computing architectures beyond traditional von-Neumann computing. Additionally, these devices are also expected to be more energy efficient than CMOS devices …

Secure State Estimation In The Presence Of False Information Injection Attacks, Maitham Alsalman

Theses and Dissertations

In this dissertation, we first investigate the problem of source location estimation in wireless sensor networks (WSNs) based on quantized data in the presence of false information attacks. Using a Gaussian mixture to model the possible attacks, we develop a maximum likelihood estimator (MLE) to estimate the source location. The Cramer-Rao lower bound (CRLB) for this estimation problem is also derived.

Then, the assumption that the fusion center does not have the knowledge of the attack probability and the attack noise power investigated. We assume that the attack probability and power are random variables which follow certain uniform distributions. We …

Multi-Column Neural Networks And Sparse Coding Novel Techniques In Machine Learning, Ammar O. Hoori

Theses and Dissertations

Accurate and fast machine learning (ML) algorithms are highly vital in artificial intelligence (AI) applications. In complex dataset problems, traditional ML methods such as radial basis function neural network (RBFN), sparse coding (SC) using dictionary learning, and particle swarm optimization (PSO) provide trivial results, large structure, slow training, and/or slow testing. This dissertation introduces four novel ML techniques: the multi-column RBFN network (MCRN), the projected dictionary learning algorithm (PDL) and the multi-column adaptive and non-adaptive particle swarm optimization techniques (MC-APSO and MC-PSO). These novel techniques provide efficient alternatives for traditional ML techniques. Compared to traditional ML techniques, the novel ML …

Sensor Placement For Damage Localization In Sensor Networks, Fereshteh Firouzi

Theses and Dissertations

The objective of this thesis is to formulate and solve the sensor placement problem for damage localization in a sensor network. A Bayesian estimation problem is formulated with the time-of-flight (ToF) measurements. In this model, ToF of lamb waves, which are generated and received by piezoelectric sensors, is the total time for each wave to be transmitted, reflected by the target, and received by the sensor. The ToF of the scattered lamb wave has characteristic information about the target location. By using the measurement model and prior information, the target location is estimated in a centralized sensor network with a …

Straintronic Nanomagnetic Devices For Non-Boolean Computing, Md Ahsanul Abeed

Theses and Dissertations

Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applications. There was relatively little research on straintronic switching in devices built with real nanomagnets that invariably have defects and imperfections, or their adaptation …

Energy Efficient Spintronic Device For Neuromorphic Computation, Md Ali Azam

Theses and Dissertations

Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for non-Von Neumann architectures as well as the energy constraints of wearable technologies and embedded processors. The first device proposal, an energy-efficient voltage-controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling. By controlling the domain wall motion utilizing spin transfer or spin orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii-Moriya interaction (DMI), different positions of the domain wall are realized …

Fabrication And Simulation Of Nanomagnetic Devices For Information Processing, Justine L. Drobitch

Theses and Dissertations

Nanomagnetic devices are highly energy efficient and non-volatile. Because of these two attributes, they are potential replacements to many currently used information processing technologies, and they have already been implemented in many different applications. This dissertation covers a study of nanomagnetic devices and their applications in various technologies for information processing – from simulating and analyzing the mechanisms behind the operation of the devices, to experimental investigations encompassing magnetic film growth for device components to nanomagnetic device fabrication and measurement of their performance.

Theoretical sections of this dissertation include simulation-based modeling of perpendicular magnetic anisotropy magnetic tunnel junctions (p-MTJ) and …

The Application Of Index Based, Region Segmentation, And Deep Learning Approaches To Sensor Fusion For Vegetation Detection, David L. Stone

Theses and Dissertations

This thesis investigates the application of index based, region segmentation, and deep learning methods to the sensor fusion of omnidirectional (O-D) Infrared (IR) sensors, Kinnect sensors, and O-D vision sensors to increase the level of intelligent perception for unmanned robotic platforms. The goals of this work is first to provide a more robust calibration approach and improve the calibration of low resolution and noisy IR O-D cameras. Then our goal was to explore the best approach to sensor fusion for vegetation detection. We looked at index based, region segmentation, and deep learning methods and compared them with a goal of …

Optically Transparent Antennas And Filters For Smart City Communication, Ryan B. Green

Theses and Dissertations

Incremental usage of mobile devices demand a new generation of wireless networks (5G) to provide faster data rates, more reliable coverage, monitor city infrastructure usage, and increase network capacity. The frequencies proposed for the upcoming 5G network would result in shorter broadcast distances and network dead zones, countered by incorporating transparent antennas into glass high rises. Transparent antennas possess, however a major challenge: low gain. This lower gain can be countered by means of employing antennas in an antenna array, boosting the gain and even giving the array the ability to beam form for the upcoming 5G network. The 5G …

Modeling Cascading Failures In Power Systems In The Presence Of Uncertain Wind Generation, Mir Hadi Athari

Theses and Dissertations

One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs.

The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact …

Load Scheduling With Maximum Demand And Time Of Use Pricing For Microgrids, Hayder O. Alwan

Theses and Dissertations

Several demand side management (DSM) techniques and algorithms have been used in the literature. These algorithms show that by adopting DSM and Time-of-Use (TOU) price tariffs; electricity cost significantly decreases, and optimal load scheduling is achieved. However, the purpose of the DSM is to not only lower the electricity cost, but also to avoid the peak load even if the electricity prices low. To address this concern, this dissertation starts with a brief literature review on the existing DSM algorithms and schemes. These algorithms can be suitable for Direct Load Control (DLC) schemes, Demand Response (DR), and load scheduling strategies. …

Electric Load Forecasting Using Long Short-Term Memory Algorithm, Tianshu Yang

Theses and Dissertations

Abstract

Power system load forecasting refers to the study or uses a mathematical method to process

past and future loads systematically, taking into account important system operating

characteristics, capacity expansion decisions, natural conditions, and social impacts, to

meet specific accuracy requirements. Dependence of this, determine the load value at a

specific moment in the future. Improving the level of load forecasting technology is

conducive to the planned power management, which is conducive to rationally arranging

the grid operation mode and unit maintenance plan, and is conducive to formulating

reasonable power supply construction plans and facilitating power improvement, and

improve the …

Resonant Acoustic Wave Assisted Spin-Transfer-Torque Switching Of Nanomagnets, Austin R. Roe

Theses and Dissertations

We studied the possibility of achieving an order of magnitude reduction in the energy dissipation needed to write bits in perpendicular magnetic tunnel junctions (p-MTJs) by simulating the magnetization dynamics under a combination of resonant surface acoustic waves (r-SAW) and spin-transfer-torque (STT). The magnetization dynamics were simulated using the Landau-Lifshitz-Gilbert equation under macrospin assumption with the inclusion of thermal noise. We studied such r-SAW assisted STT switching of nanomagnets for both in-plane elliptical and circular perpendicular magnetic anisotropy (PMA) nanomagnets and show that while thermal noise affects switching probability in in-plane nanomagnets, the PMA nanomagnets are relatively robust to the …

A Rectenna For 5g Energy Harvesting, Panagiotis Efthymakis

Theses and Dissertations

This thesis describes the design of a rectenna that is capable of operating in 5G. 5G’s availability will create the opportunity to harvest energy everywhere in the network’s coverage. This thesis investigates a Rectenna device with a new proposed topology in order to eliminate coupling between input and output lines and increase the rectification efficiency. Moreover, it is designed to charge a rechargeable battery of 3V, 1mA, with a 4.8mm diameter. The current design describes using one antenna for energy harvesting; this could be expanded to use an antenna array, which would increase the input power. This would lead to …