Other Electrical and Computer Engineering Commons^™

Technology-Dependent Quantum Logic Synthesis And Compilation, Kaitlin Smith

Electrical Engineering Theses and Dissertations

The models and rules of quantum computation and quantum information processing (QIP) differ greatly from those that govern classical computation, and these differences have caused the implementation of quantum processing devices with a variety of new technologies. Many platforms have been developed in parallel, but at the time of writing, one method of quantum computing has not shown to be superior to the rest. Because of the variation that exists between quantum platforms, even between those of the same technology, there must be a way to automatically synthesize technology-independent quantum designs into forms that are capable of physical realization on ...

Optimal Allocation Of Energy Storage And Wind Generation In Power Distribution Systems, Carlos Mendoza

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

The advent of energy storage technologies applications for the electric power system gives new tools for planners to cope with the operation challenges that come from the integration of renewable generation in medium voltage networks. This work proposes and implements an optimization model for Battery Energy Storage System (BESS) and distributed generation allocation in radial distribution networks. The formulation aims to assist distribution system operators in the task of making decisions on energy storage investment, BESSs' operation, and distributed generation penetration's level to minimize electricity costs. The BESSs are required to participate in energy arbitrage and voltage control. In ...

Amodal Instance Segmentation And Multi-Object Tracking With Deep Pixel Embedding, Yanfeng Liu

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

This thesis extends upon the representational output of semantic instance segmentation by explicitly including both visible and occluded parts. A fully convolutional network is trained to produce consistent pixel-level embedding across two layers such that, when clustered, the results convey the full spatial extent and depth ordering of each instance. Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches.

The model is further extended to produce consistent pixel-level embeddings across two consecutive image frames from a video to simultaneously perform amodal instance segmentation and multi-object tracking. No post-processing ...

Free Space Optical Communication, Anuj Gohil

Electrical Engineering

Communication is key to day to day activities for all companies and people. Wireless communication has made us expect more from our tools. Radio Frequency has been the preferred medium for a couple decades, but there is a need for faster secure communication. Free Space Optical Communication is an alternate wireless communication system which uses optics to create a link. It utilizes low-power and converts an analog signal into digital pulses which are transmitted across space to a receiver. Its only caveat is its vulnerability under atmospheric obstacles. The goal of this project is to create a free space optical ...

Pixel-Level Deep Multi-Dimensional Embeddings For Homogeneous Multiple Object Tracking, Mateusz Mittek

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

The goal of Multiple Object Tracking (MOT) is to locate multiple objects and keep track of their individual identities and trajectories given a sequence of (video) frames. A popular approach to MOT is tracking by detection consisting of two processing components: detection (identification of objects of interest in individual frames) and data association (connecting data from multiple frames). This work addresses the detection component by introducing a method based on semantic instance segmentation, i.e., assigning labels to all visible pixels such that they are unique among different instances. Modern tracking methods often built around Convolutional Neural Networks (CNNs) and ...

Performance Enhancement And Characterization Of An Electromagnetic Railgun, Paul M. Gilles

Master's Theses and Project Reports

Collision with orbital debris poses a serious threat to spacecraft and astronauts. Hypervelocity impacts resulting from collisions mean that objects with a mass less than 1g can cause mission-ending damage to spacecraft. A means of shielding spacecraft against collisions is necessary. A means of testing candidate shielding methods for their efficacy in mitigating hypervelocity impacts is therefore also necessary. Cal Poly’s Electromagnetic Railgun was designed with the goal of creating a laboratory system capable of simulating hypervelocity (≥ 3 km/s) impacts. Due to several factors, the system was not previously capable of high-velocity (≥ 1 km/s) tests. A deficient ...

Effect Of Annealing On The Contact Resistance Of Aluminum On A P-Type Substrate, Shrey Shah, George Patrick Watson

Protocols and Reports

Aluminum contacts are widely used to form both ohmic and rectifying contacts. The process to form these contacts involves annealing, thus it is important to study the effect of annealing on the electrical properties of the contacts. Here, we present a way to measure the contact resistance of aluminum contacts formed on a p-type silicon substrate. It was found the contact resistivity decreased by an average of 18%. It was thus found that annealing at 400°C in a forming gas environment improves the electrical properties of aluminum contacts.

Optimizing Generative Adversarial Network Architecture For Low-Resolution Image Enhancement, Maria Isabel Gonzalez Bocanegra, Justin Matthew Hall

Georgia Undergraduate Research Conference (GURC)

The research focuses on applying Generative Adversarial Networks (GANs) [1] to enhance the clarity of low-resolution images. This research was inspired by a recognized limitation of the capabilities of the current camera and video systems. Systems with higher image resolution require expensively complex equipment and an excessive amount of digital storage to function, effectively limiting their practicality and availability. The capability of GANs to selectively enhance the resolution of the desired image without increasing costs impacts a substantial range of industries and practices. Our research focuses on applying GANs to objects with shared static characteristics such as license plates. Based ...

The Stability Analysis For Wind Turbines With Doubly Fed Induction Generators, Baohua Dong

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

The quickly increasing, widespread use of wind generation around the world reduces carbon emissions, decreases the effects of global warming, and lowers dependence on fossil fuels. However, the growing penetration of wind power requires more effort to maintain power systems stability.

This dissertation focuses on developing a novel algorithm which dynamically optimizes the proportional-integral (PI) controllers of a doubly fed induction generator (DFIG) driven by a wind turbine to increase the transient performance based on small signal stability analysis.

Firstly, the impact of wind generation is introduced. The stability of power systems with wind generation is described, including the different ...

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to ...

Correction Of Pattern Size Deviations In The Fabrication Of Photomasks Made With A Laser Direct-Writer, Ningzhi Xie, George Patrick Watson

Protocols and Reports

When using Heidelberg DWL66+ laser writer to fabricate the photomask, the pattern feature dimensions may have deviations. These deviations can be caused by the lithography process and the undercut in the metal etch process. The same deviation value of 0.8µm was found to appear in all the patterns independent of the pattern original size and local pattern density. To overcome this universal deviation, a universal bias is suggested to be applied to the original patterns during the data preparation for the lithography process. In order to ensure this pre-exposure bias method can work, both the laser direct-write exposure conditions ...

Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala

Publications

Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other drivers, extreme conditions, etc. As a result, the model’s predictions are made at an aggregate level and ...

Combining Virtual Reality And Machine Learning For Enhancing The Resiliency Of Transportation Infrastructure In Extreme Events, Supratik Mukhopadhyay, Yimin Zhu, Ravindra Gudishala

Data

Corresponding data set for Tran-SET Project No. 18ITSLSU09. Abstract of the final report is stated below for reference:

"Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other ...

Elonzo Davis & Houston Smith-Gurc-Abstract, John Smith, Elonzo Davis

John Smith

No abstract provided.

Smart Charging Of Future Electric Vehicles Using Roadway Infrastructure, Sara Ahmed, Ethan Ahn, Mahmoud Reda Taha, Samer Dessouky, Moneeb Genedy, Daniel Fernandez, Ann Sebestian, Patience Raby

Data

Corresponding data set for Tran-SET Project No. 18ITSTSA03. Abstract of the final report is stated below for reference:

"Inspired by the fact that there is an immense amount of renewable energy sources available on the roadways such as mechanical pressure and frictional heat, this study presented the development and implementation of an innovative charging technique for future electric vehicles (EVs) by fully utilizing the existing roadways and the state-of-the-art nanotechnology and power electronics. The project introduced a novel wireless charging system, SIC (Smart Illuminative Charging), that uses LEDs powered by piezoelectric nanomaterials as the energy transmitter source and thin film ...

Vehicle Sensing And Communications Using Led Headlights To Enhance The Performance Of Intelligent Transportation Systems: Proof Of Concept, Implementation, And Applications, Sabit Ekin, Samir Ahmed

Publications

This project investigates the use of vehicle light-emitting diode (LED) headlamp devices for improving the accuracy and reliability of traffic (sensing and communication) data measurements required for developing effective intelligent transportation systems (ITS) technologies and solutions. Vehicular communication and sensing technologies are mainly based on conventional radio frequency (RF) or laser technologies. These systems suffer from several issues such as RF interference and poor performance in scenarios where the incidence angle between the speed detector and the vehicle is rapidly varying. Introducing a new sensing technology will add diversity to these systems and enhance the reliability of the real-time data ...

Cooperative Learning For The Consensus Of Multi-Agent Systems, Qishuai Liu

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Due to a lot of attention for the multi-agent system in recent years, the consensus algorithm gained immense popularity for building fault-tolerant systems in system and control theory. Generally, the consensus algorithm drives the swarm of agents to work as a coherent group that can reach an agreement regarding a certain quantity of interest, which depends on the state of all agents themselves. The most common consensus algorithm is the average consensus, the final consensus value of which is equal to the average of the initial values. If we want the agents to find the best area of the particular ...

Embedded System Design Of Robot Control Architectures For Unmanned Agricultural Ground Vehicles, Ryan Humphrey

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Engineering technology has matured to the extent where accompanying methods for unmanned field management is now becoming a technologically achievable and economically viable solution to agricultural tasks that have been traditionally performed by humans or human operated machines. Additionally, the rapidly increasing world population and the daunting burden it places on farmers in regards to the food production and crop yield demands, only makes such advancements in the agriculture industry all the more imperative. Consequently, the sector is beginning to observe a noticeable shift, where there exist a number of scalable infrastructural changes that are in the process of slowly ...

Residential Electricity Management And Protection System, Ejimonu Kosisochukwu Gabriel

Journal of International Technology and Information Management

The Residential Electricity Monitoring System is an electricity meter connected to the Internet to provide real time data on the power system in your home. The REMS is designed to replace the distribution board allowing it to conduct a series of tests on the quality of the electricity supply to your home/facility and, within your home detect basic wiring faults and allow owners and service providers to identify potential problems with the electrical systems.

The electrical monitoring system finally puts proper electrical control into the hands of the home owner by providing him with the ability to control power ...

Adaptation Of A Deep Learning Algorithm For Traffic Sign Detection, Jose Luis Masache Narvaez

Electronic Thesis and Dissertation Repository

Traffic signs detection is becoming increasingly important as various approaches for automation using computer vision are becoming widely used in the industry. Typical applications include autonomous driving systems, mapping and cataloging traffic signs by municipalities. Convolutional neural networks (CNNs) have shown state of the art performances in classification tasks, and as a result, object detection algorithms based on CNNs have become popular in computer vision tasks. Two-stage detection algorithms like region proposal methods (R-CNN and Faster R-CNN) have better performance in terms of localization and recognition accuracy. However, these methods require high computational power for training and inference that make ...