Other Electrical and Computer Engineering Commons^™

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 …

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

Master's Theses

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 projectile …

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

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

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 additional, …

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

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

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 …

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 drivers, …

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …

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 for a …

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. …

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 distribution …

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

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

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

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

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 …

Alzheimer’S Disease Detection Using Convolutional Neural Netowork & Wavelets, Ean Hendrickson, Gabriel Amancio, Chloe Eusbio, Kaioli Bessert

Electrical Engineering

It is estimated that 5.7 million people in the United States have Alzheimer’s dementia, including about 1 in 10 people above the age of 65. Alzheimer’s disease detection can help doctors to diagnose patients earlier and help them with preventative, proactive treatment. In this project, we attempt to use two different methods to analyze MRI brain images for Alzheimer’s disease detection, one with convolutional neural network and deep learning algorithm, and the other one with discrete wavelet transform. Computer simulation results are presented in the report.

Workload Allocation In Mobile Edge Computing Empowered Internet Of Things, Qiang Fan

Dissertations

In the past few years, a tremendous number of smart devices and objects, such as smart phones, wearable devices, industrial and utility components, are equipped with sensors to sense the real-time physical information from the environment. Hence, Internet of Things (IoT) is introduced, where various smart devices are connected with each other via the internet and empowered with data analytics. Owing to the high volume and fast velocity of data streams generated by IoT devices, the cloud that can provision flexible and efficient computing resources is employed as a smart "brain" to process and store the big data generated from …

Emt 1130 - Electromechanical Manufacturing Lab, Farjana Ferdousy

Open Educational Resources

No abstract provided.

Wireless Channel Characterization Based On Crowdsourced Data And Geographical Features, Rita Enami

Electrical Engineering Theses and Dissertations

To design and plan wireless communication systems, an accurate propagation estimate is required of a deployment region. Propagation prediction models consist of two types of fading: large-scale and small-scale fading. With large-scale fading, the path loss information is crucial for cell planning, coverage estimation, and optimization. With small-scale fading, the statistical fluctuation on the local variations of the average signal level can have a dramatic effect on protocol decisions and resulting performance. To obtain accurate estimates of both types of fading, typically field measurements are needed that use drive testing, which is expensive in terms of time and cost. Recently, …

Counterfeit Detection With Multispectral Imaging, Ian Spatz

Electrical Engineering Undergraduate Honors Theses

Multispectral imaging is becoming more practical for a variety of applications due to its ability to provide hyper specific information through a non-destructive analysis. Multispectral imaging cameras can detect light reflectance from different spectral bands of visible and nonvisible wavelengths. Based on the different amount of band reflectance, information can be deduced on the subject. Counterfeit detection applications of multispectral imaging will be decomposed and analyzed in this thesis. Relations between light reflectance and objects’ features will be addressed. The process of the analysis will be broken down to show how this information can be used to provide more insight …

Methods To Remotely Eliminate Biofilm From Medical Implants Using 2.4 Ghz Microwaves, Brett Glenn

Mechanical Engineering Undergraduate Honors Theses

Infections associated with biofilm growth are usually challenging to eradicate due to their high tolerance toward antibiotics [11, 12]. Biofilms often form on the inert surfaces of medically implanted devices [13]. No matter the sophistication, microbial infections can develop on all medical devices and tissue engineering constructs [12]. Related infections lead to 2 million cases annually in the U.S., costing the healthcare system over $5 billion in additional healthcare expenses [12].

Novel solutions to biofilm’s microbial colonization span the spectrum of engineering and science disciplines. Yet a practical solution still does not exist. The research presented here will explore a …

Characterization Of High Temperature Optocoupler For Power Electronic Systems, David Gonzalez

Electrical Engineering Undergraduate Honors Theses

High-temperature devices have been rapidly increas due to the implementation of new technologies like silicon carbide, high-temperature ceramic, and others. Functionality under elevated temperatures can reduce signal integrity reducing the reliability of power electronic systems. This study presents an ongoing research effort to develop a high-temperature package for optocouplers to operate at higher temperature compared with commercial devices. Low temperature co-fired ceramic (LTCC) was used as the substrate. Bare die commercial LED and photodetectors were attached to the substrate and tested for functionality. Preliminary results show enhanced performance at elevated temperatures compared to a commercial optocoupler device.

A Swimming Open-Water Navigation Assistive Headset And Receiver, Zakk B. Rhodes

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Open water swimming is a common activity dating back to ancient times. One challenge with open water swimming is navigation because while maintaining proper swimming technique suggests the head be in the water, it is difficult to see where one is going. Thus swimmers must bring their head out of the water periodically to sight landmarks. This work describes a solution to this problem by a design for a GPS device to assist swimmers with navigation. The swimmer can plan their own route, send it to the device, and then be guided by the device. They then will not have …