Electrical and Computer Engineering Commons^™

Enhancing Situational Awareness For Rotorcraft Pilots Using Virtual And Augmented Reality, Ardit Pranvoku

Theses and Dissertations

Rotorcraft pilots often face the challenge of processing a multitude of data, integrating it with prior experience and making informed decisions in complex, rapidly changing multisensory environments. Virtual Reality (VR), and more recently Augmented Reality (AR) technologies have been applied for providing users with immersive, interactive and navigable experiences. The research work described in this thesis demonstrates that VR/AR are particularly effective in providing real-time information without detracting from the pilot's mission in both civilian and military engagements. The immersion of the pilot inside of the VR model provides enhanced realism. Interaction with the VR environment allows pilots to practice …

The Distributed Trust Model Applied To The Energy Grid Of Things, Narmada Sonali Fernando

Dissertations and Theses

Electric power system operators can manage distribution system utilization and usage by coordinating end customer usage of distributed energy resources. The end customers in this regard are Service Provisioning Customers, who provide their energy resources to a Grid Service Provider, which in turn dispatches large aggregations of distributed energy resources to provide reliable service to the power system. The security of this system relies upon information protection mechanisms, as described in IEEE 2030.5. However, in addition to preventive security measures, a monitoring function is required to ensure trustworthiness.

Trust models are a method to detect and respond to both expected …

Optimum Implementation Of Compound Compression Of A Computer Screen For Real-Time Transmission In Low Network Bandwidth Environments, Conor Paxton

Masters

Remote working is becoming increasingly more prevalent in recent times. A large part of remote working involves sharing computer screens between servers and clients. The image content that is presented when sharing computer screens consists of both natural camera captured image data as well as computer generated graphics and text. The attributes of natural camera captured image data differ greatly to the attributes of computer generated image data. An image containing a mixture of both natural camera captured image and computer generated image data is known as a compound image. The research presented in this thesis focuses on the challenge …

System, Method And Apparatus For Recovering Polarization Radar Data, Julie A. Jackson, Forest Lee-Elkin

AFIT Patents

A method and apparatus that measure M coupled channels of radar polarization data (ỹ), that is a subset, which is less than the full set of received coupled channels. Sparse recovery operations are performed on the measured M coupled channels of radar polarization data (ỹ) and a representation of a set of more than M channels of radar polarization data is generated from the sparse recovery performed on the subset of coupled channels.

Artificial Intelligence-Based Power System Stabilizers For Frequency Stability Enhancement In Multi-Machine Power Systems, Aliyu Sabo, Noor Izzri Abdul Wahab, Mohammad Lutfi Othman, Mai Zurwatul Ahlam Mohd Jaffar, Hakan Acikgoz, Hamed Nafisi, Hossein Shahinzadeh

Articles

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently …

Uptpu: Improving Energy Efficiency Of A Tensor Processing Unit Through Underutilization Based Power-Gating, Pramesh Pandey, Noel Daniel Gundi, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

The AI boom is bringing a plethora of domain-specific architectures for Neural Network computations. Google's Tensor Processing Unit (TPU), a Deep Neural Network (DNN) accelerator, has replaced the CPUs/GPUs in its data centers, claiming more than 15 × rate of inference. However, the unprecedented growth in DNN workloads with the widespread use of AI services projects an increasing energy consumption of TPU based data centers. In this work, we parametrize the extreme hardware underutilization in TPU systolic array and propose UPTPU: an intelligent, dataflow adaptive power-gating paradigm to provide a staggering 3.5 ×-6.5× energy efficiency to TPU for different input …

Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …

Hiv/Aids After The Crisis: The Evolution Of An Epidemic, Emma Paras

Honors Projects

HIV and AIDS has affected the world for over four decades. In the past, a positive HIV diagnosis could very well be a death sentence, as well as signal that an individual was a social outcast. In the past ten years, however, treatments for HIV/AIDS allow a person to live a long and relatively healthy life. In addition to examining current and future trends in HIV treatment, this paper will also discuss how the virus affects different regions of the world. Particularly in certain parts of Africa, HIV/AIDS remains deadly for many who don’t have proper access to health care …

Low-Noise, Low-Power Analog Front End For Dual Detector, Event-Driven Radioactive Isotope Identification, Joseph Medinger

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

An analog front end (AFE) design for a low-noise, low-power, event-driven radioactive spectroscopy system is implemented in a 65 nm CMOS technology. The AFE is optimized for use with two scintillation based detectors, CsI(Na) and LaBr3(Ce), that utilize photo-multiplier tubes for charge amplification. The amplification within the AFE is accomplished through charge sensitive amplifier designs that are tailored to each detector type. The AFE includes adjustable bias generation circuits to allow amplifier tuning for process, voltage, and temperature variations. The presented AFE is implemented along with analog to digital acquisition circuits and a microcontroller to provide a single-chip radioactive spectroscopy …

Improving Noise Immunity And Efficiency Using High-Precision Iterative Codes, Sherzod Shukhratovich Atadjanov, Aziza Ahmadjanovna Tursunova

Bulletin of TUIT: Management and Communication Technologies

The article discusses the issues of ensuring noise immunity in digital broadcasting systems, shows the importance of the transition to the optimal code and the need to use it in the field of noiseless coding in various areas of telecommunication transmission and reception of digital signals. The previous algorithms and error-correcting coding methods based on the Gray code, which are used in multi-level digital broadcast modulation schemes to minimize the intensity of bit errors, are highlighted. A model of error-correcting coding by the Gray method and methods for estimating the probability of error for the Gray code are presented. Based …

Nonmetallic Jet Impingement Thermal Management For Power Electronics Via Additive Manufacturing, Reece Whitt

Graduate Theses and Dissertations

The increase in energy demanded by transportation and energy sectors has necessitated highly efficient thermal management for reliable power electronics operations. Conventional cooling techniques are limited by their inability to target switching location hot spot temperatures, leading to non-uniform thermal gradients. These devices, such as cold plates and heat sinks, also utilize heavy metallic structures that can accentuate electromagnetic interferences generated by high voltage switching processes. This work proposes a non-metallic jet impingement cooler for more customized thermal management, while simultaneously reducing the harmful effects of electromagnetic interferences. Additive manufacturing is utilized to enable jet impingement zones to target individual …

Mission Profile Effects On Automotive Drivetrain Electronics Reliability: Modeling And Mitigation, Bakhtiyar Mohammad Nafis

Graduate Theses and Dissertations

The reliability of electronic devices is dependent upon the conditions to which they are subject. Temperature variations coupled with differences in thermal expansion between bonded materials results in thermomechanical stresses to build up, which can instigate failure in the interconnects or other critical regions. With the move towards electrification in the automotive industry, there is the increasingly important consideration of powertrain electronics reliability, the pertinent conditions being governed by the drive cycle or mission profile of the vehicle. The mission profile determines the power dissipated by the electronic devices, which determines the peak and mean temperature, temperature swing and the …

Thermometry Via Diffusion In Ferrous Core-Shell Nanoparticles For Induction Heating Applications, Hayden Carlton

Graduate Theses and Dissertations

Induction heating causes the release of enormous amounts of heat from dispersed magnetic nanoparticles. While the rate of heat transfer can be easily quantified calorimetrically, measuring the temperature of the nanoparticles on the nanoscale presents experimental challenges. Fully characterizing the temperature and thermal output of these magnetic particles is necessary to gauge overall heating efficiency and to provide a more holistic understanding of heat transfer on the nanoscale. Herein, this dissertation seeks to develop a novel nanoparticle thermometry technique, which correlates diffusion behavior in core-shell nanoparticles to local temperature. Initial measurements suggested that heating silica capped ferrous nanoparticles (SCNPs) via …

Scalable Optimization Method For Generator Scheduling Under Uncertainty, Edward Arthur Quarm Jnr

Electrical Engineering Dissertations - Archive

Scalable optimization methods for power system operation has been subject of research over the last 60 years. State-of-the-art methods in this research area is yet to yield the scalability desired by system operators for practical operation of electric grids. This article-based dissertation makes three significant contributions. A scalable computational method is developed to tackle a mixed-integer problem commonly referred to as Stochastic Security-Constrained Unit Commitment (SSCUC), the output of which will be beneficial to Independent System Operators to manage electric grids. Secondly, an improved model for time-progressive contingencies in security-constrained optimization problems is presented. This modeling approach is more realistic …

Active Compensation Of Radiation Effects On Optical Fibers For Sensing Applications, Sohel Rana, Austin Fleming, Nirmala Kandadai, Harish Subbaraman

Electrical and Computer Engineering Faculty Publications and Presentations

Neutron and gamma irradiation is known to compact silica, resulting in macroscopic changes in refractive index (RI) and geometric structure. The change in RI and linear compaction in a radiation environment is caused by three well-known mechanisms: (i) radiation-induced attenuation (RIA), (ii) radiation-induced compaction (RIC), and (iii) radiation-induced emission (RIE). These macroscopic changes induce errors in monitoring physical parameters such as temperature, pressure, and strain in optical fiber-based sensors, which limit their application in radiation environments. We present a cascaded Fabry–Perot interferometer (FPI) technique to measure macroscopic properties, such as radiation-induced change in RI and length compaction in real time …

A Multi-Dimensional Child-Langmuir Law For Any Diode Geometry, N. R. Sree Harsha, Marcus Pearlman, Jim Browning, Allen L. Garner

Electrical and Computer Engineering Faculty Publications and Presentations

While prior theoretical studies of multi-dimensional space-charge limited current (SCLC) assumed emission from a small patch on infinite electrodes, none have considered emission from an entire finite electrode. In this paper, we apply variational calculus (VC) and conformal mapping, which have previously been used to derive analytic solutions for SCLC density (SCLCD) for nonplanar one-dimensional geometries, to obtain mathematical relationships for any multi-dimensional macroscopic diode with finite cathode and anode. We first derive a universal mathematical relationship between space-charge limited potential and vacuum potential for any diode and apply this technique to determine SCLCD for an eccentric spherical diode. We …

Attenuation Of Several Common Building Materials: Millimeter-Wave Frequency Bands 28, 73, And 91 Ghz, Mahfuza Khatun, Changyu Guo, Hani Mehrpouyan

Electrical and Computer Engineering Faculty Publications and Presentations

Future cellular systems will make use of millimeter-wave (mm-wave) frequency bands. Many users in these bands are located indoors, i.e., inside buildings, homes, and offices. The typical building material attenuations in these high-frequency ranges are of interest for link budget calculations. In this article, we report on a collaborative measurement campaign to find the attenuation of several typical building materials in three potential mm-wave bands (28, 73, and 91 GHz). Using directional antennas, we took multiple measurements at multiple locations using narrow-band and wideband signals and averaged out residual small-scale fading effects. The materials include clear glass, drywall (plasterboard), plywood, …

Distributed And Optimal State Estimation For Heterogeneous Dynamic Systems Operating Within A Strongly Connected Network, Matthew Howard

Electronic Theses and Dissertations, 2020-2023

This dissertation is aimed at developing optimal and distributed state estimation algorithms for a team of cooperating nodes with the goal of improving accuracy through local sharing of relevant information. The nodes are assumed to be individually equipped with heterogeneous sensors for measuring a common target which can be dynamic and time-varying. Additionally, the nodes are assumed to be connected through a dynamically changing communication network modeled as a sequence of strongly connected digraphs allowing for local communication and distributed interactions. Using the data sharing afforded by the communication network, a weighted average state estimate consensus can be found across …

Reconfigurable Antennas & Matching Networks For Cubesats, Marios Patriotis

Electrical and Computer Engineering ETDs

Telecommunication has rapidly evolved in the past decades, quickly becoming one of the most expansive industries, especially with the presence of new attractive eras like 5Gnetworks, automotive radars, and CubeSats. The use of miniaturized satellites such as CubeSats for cheaper and wider communication coverage has opened the possibilities for cluster satellite communication. These units exist in a continuously varying environment as much physical as electromagnetic. Hence, the establishment of a successful communication link among the space units but also ground stations becomes challenging. This new situation can be confronted with the installation of new reconfigurable antennas. These are emitting units …

Design Of Miniaturized Antipodal Vivaldi Antennas And A Microwave Head Imaging System For The Detection Of Blood Clots In The Brain, Farhana Parveen

Electronic Theses and Dissertations, 2020-2023

Traditional brain imaging modalities, for example, MRI, CT scan, X-ray, etc. can provide precise and high-resolution images of the brain for diagnosing lesions, tumors or clots inside the brain. However, these modalities require bulky and expensive test setups accessible only at specialized diagnostic centers, and hence may not be suitable or affordable to many patients. Furthermore, the inherent health risks limit the usability of these modalities for frequent monitoring. Microwave imaging is deemed a promising alternative due to its being cost-effective, portable, non-ionizing, non-intrusive. Therefore, this work aims to design an effective microwave head imaging system for the detection of …

Nevr: Learning Continuous Neural Video Representation With Local Feature Codes For Video Interpolation, Wentao Shangguan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Video frame interpolation aims to synthesis a non-exists intermediate frame guided by two successive frames. Recently, some work shows excellent results in learning continuous representation of temporally-varying 3D objects with neural field (NF), which could be used for interpolating the original video. However, these methods require several videos from different viewing angles, the information of camera poses, learning for each specific scene, and achieving sub-optimal results for video frame interpolation. To this end, we propose a new learning neural field representation-based model, Neural Video Representation (NeVR) to learn a continuous representation of videos for high-quality video interpolation. Unlike the traditional …

Distributed Estimation And Inverse Reinforcement Learning For Multi-Agent Systems, Bosen Lian

Electrical Engineering Dissertations - Archive

Consensus-based distributed Kalman filters for estimation with multiple targets have attracted considerable attention. Most of the existing Kalman filters use the average consensus approach, which tends to have a low convergence speed. They also rarely consider the impacts of limited sensing range and target mobility on the information flow topology. The robustness properties, i.e., gain margins and phase margins of distributed Kalman filtering algorithms are still open problems. In the interactions of controlled dynamical agents, it is often assumed that the agents are "rational" in the sense of attempting to act in such a way as to optimize some prescribed …

Fast And Parallelizable Numerical Algorithms For Large Scale Conic Optimization Problems, Muhammad Adil

Electrical Engineering Dissertations - Archive

Many real world problems from various application areas such as engineering, finance and operation research can be cast as optimization problems. Generally, the goal is to optimize an objective function under a set of constraints. Traditionally, convex optimization problems are solved by an interior point method (IPM). Interior point methods proved to achieve high accuracy for moderate size problems. However, the computation cost of iterations of these iterative algorithms grows non-linearly with the dimension of the problem. Although interior-point methods are robust and theoretically sound, they do not scale well for very large conic optimization programs. Computational cost, memory issues, …

Study Of Mos2/High-K Interface And Implementation Of Mos2 Based Memristor For Neuromorphic Computing Applications, Durjoy Dev

Electronic Theses and Dissertations, 2020-2023

The scientific world is witnessing an unprecedented triumph of artificial neural network (ANN)- a computing system inspired by the biological neural network. With the enthralling quest for Internet of Everything (IoE), it is expected to have an unparalleled dominance of ANN in our day-to-day life. In recent times, memristor has come as an emerging candidate to realize ANN through emulating biological synapse and neuron behavior. Molybdenum disulfide (MoS2), one well-known two-dimensional (2D) transition metal dichalcogenides (TMDCs), has drawn interest for high speed, flexible, low power electronic devices since it has a tunable bandgap, reasonable carrier mobility, high Young's modulus, and …

Spectral Dependence Of Deep Subwavelength Metallic Apertures In The Mid-Wave Infrared, Heath Gemar

Electronic Theses and Dissertations, 2020-2023

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength cavities for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns (i.e., mid-wave infrared or MWIR). We explore the trade space of deep subwavelength cavities and its impact on resonant enhancement of the electromagnetic field. The studies provide fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on cavity geometry and material properties. …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

All Dissertations

Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang

All Dissertations

Material microstructure prediction based on processing conditions is very useful in advanced manufacturing. Trial-and-error experiments are very time-consuming to exhaust numerous combinations of processing parameters and characterize the resulting microstructures. To accelerate process development and optimization, researchers have explored microstructure prediction methods, including physical-based modeling and feature-based machine learning. Nevertheless, they both have limitations. Physical-based modeling consumes too much computational power. And in feature-based machine learning, low-dimensional microstructural features are manually extracted to represent high-dimensional microstructures, which leads to information loss.

In this dissertation, a deep learning-guided microstructure prediction framework is established. It uses a conditional generative adversarial network (CGAN) …

An Analysis Of Camera Configurations And Depth Estimation Algorithms For Triple-Camera Computer Vision Systems, Jared Peter-Contesse

Master's Theses

The ability to accurately map and localize relevant objects surrounding a vehicle is an important task for autonomous vehicle systems. Currently, many of the environmental mapping approaches rely on the expensive LiDAR sensor. Researchers have been attempting to transition to cheaper sensors like the camera, but so far, the mapping accuracy of single-camera and dual-camera systems has not matched the accuracy of LiDAR systems. This thesis examines depth estimation algorithms and camera configurations of a triple-camera system to determine if sensor data from an additional perspective will improve the accuracy of camera-based systems. Using a synthetic dataset, the performance of …

Printed Circuit Board Design And Layout For Hobbyists, Engineers, And Students, Michael A. Derrenbacher

Master's Theses

Printed Circuit Boards (PCBs) are a ubiquitous element of virtually every electronic system manufactured world-wide. It is not a stretch of the imagination to say that if it’s electronic, there is a PCB in it. PCBs are necessary tools for electronics work, and tools need to have instructions. For better or worse, PCB knowledge is a deep and wide ocean. There is much to cover for even a surface level understanding, and there are deep areas rich in technical expertise. Navigating the ocean of knowledge is treacherous; common knowledge of yore can be downright dubious now. PCB manufacturing and electronics …

Adopting Accessibility Guidelines For Videogames To Collectible Card Games, Cooper Biancur

Electrical Engineering Master’s Theses

The development of accessible video games has been discussed through multiple publications in the 21st century; however, little to no attention has been given to non-electronic gaming. Like video games, Collectible Card Games (CCG) have also gained massive popularity, but no accessible guidelines have been created to help the disabled better play them. The need for inclusion in gaming is critical because it can act as a medium for social interaction and a learning tool for teaching. Today offers numerous technologies that can help those with disabilities, such as microcomputers, Artificial Intelligence (AI), Optical Character Recognition (OCR), and Text to …