Computer Engineering Commons^™

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …

Watch: A Distributed Clock Time Offset Estimation Tool On The Platform For Open Wireless Data-Driven Experimental Research, Cassie Jeng

McKelvey School of Engineering Theses & Dissertations

The synchronization of the clocks used at different devices across space is of critical importance in wireless communications networks. Each device’s local clock differs slightly, affecting the times at which packets are transmitted from different nodes in the network. This thesis provides experimentation and software development on POWDER, the Platform for Open, Wireless Data-driven Experimental Research, an open wireless testbed across the University of Utah campus. We build upon Shout, a suite of Python scripts that allow devices to iteratively transmit and receive with each other and save the collected data. We introduce WATCH, an experimental method to estimate clock …

Cyberinet: Integrated Semi-Modular Sensors For The Computer-Augmented Clarinet, Matthew Bardin

LSU Doctoral Dissertations

The Cyberinet is a new Augmented instrument designed to easily and intuitively provide a method of computer-enhanced performance to the Clarinetist to allow for greater control and expressiveness in a performance. A performer utilizing the Cyberinet is able to seamlessly switch between a traditional performance setting and an augmented one. Towards this, the Cyberinet is a hardware replacement for a portion of a Clarinet containing a variety of sensors embedded within the unit. These sensors collect various real time data motion data of the performer and air fow within the instrument. Additional sensors can be connected to the Cyberinet to …

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Enhancing Traffic Safety In Unpredicted Environments With Integration Of Adas Features With Sensor Fusion In Intelligent Electric Vehicle Platform With Implementation Of Environmental Mapping Technology, David S. Obando Ortegon

Electronic Theses and Dissertations

A major objective on society is to reduce the number of accidents and fatalities on the road for drivers, and pedestrians. Therefore, the automotive engineering field is working on this problem through the development and integration of safety technologies such as advanced driving assistance systems. For this reason, this work was intended to develop and evaluate the performance of different ADAS features and IV technologies under unexpected scenarios. This by the development of safety algorithms applied to the intelligent electric vehicle designed and built in this work, through the use of ADAS sensors based on sensor fusion. Evaluation of AEB, …

Device Free Indoor Localization Of Human Target Using Wifi Fingerprinting, Prasanga Neupane

LSU Master's Theses

Indoor localization of human objects has many important applications nowadays. Proposed here is a new device free approach where all the transceiver devices are fixed in an indoor environment so that the human target doesn't need to carry any transceiver device with them. This work proposes radio-frequency fingerprinting for the localization of human targets which makes this even more convenient as radio-frequency wireless signals can be easily acquired using an existing wireless network in an indoor environment. This work explores different avenues for optimal and effective placement of transmitter devices for better localization. In this work, an experimental environment is …

Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia

Doctoral Dissertations

Research studies show that sleep deprivation causes severe fatigue, impairs attention and decision making, and affects our emotional interpretation of events, which makes it a big threat to public safety, and mental and physical well-being. Hence, it would be most desired if we could continuously measure one’s drowsiness and fatigue level, their emotion while making decisions, and assess their sleep quality in order to provide personalized feedback or actionable behavioral suggestions to modulate sleep pattern and alertness levels with the aim of enhancing performance, well-being, and quality of life. While there have been decades of studies on wearable devices, we …

Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda

Electronic Thesis and Dissertation Repository

Emergence of new applications, industrial automation and the explosive boost of smart concepts have led to an environment with rapidly increasing device densification and service diversification. This revolutionary upward trend has led the upcoming 6th-Generation (6G) and beyond communication systems to be globally available communication, computing and intelligent systems seamlessly connecting devices, services and infrastructure facilities. In this kind of environment, scarcity of radio resources would be upshot to an unimaginably high level compelling them to be very efficiently utilized. In this case, timely action is taken to deviate from approximate site-specific 2-Dimensional (2D) network concepts in radio resource utilization …

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …

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, …

Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire

Graduate Theses, Dissertations, and Problem Reports

Facial recognition systems play a vital role in our everyday lives. We rely on this technology from menial tasks to issues as vital as national security. While strides have been made over the past ten years to improve facial recognition systems, morphed face images are a viable threat to the reliability of these systems. Morphed images are generated by combining the face images of two subjects. The resulting morphed face shares the likeness of the contributing subjects, confusing both humans and face verification algorithms. This vulnerability has grave consequences for facial recognition systems used on international borders or for law …

Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey

Williams Honors College, Honors Research Projects

In the realm of rapid, small-scale prototyping, there are a few main factors that drive decisions to invest resources in technology to make that prototyping possible. Cost and ease of use are two of the most influential when looking at most SMEs (Small to Medium-sized Enterprises). The U.S. Small Business Administration defines an SME as smaller than 1,250 employees. According to An Assessment of Implementation of Entry-Level 3D Printers from the Perspective of Small Businesses, 59% of small manufacturers had implemented 3D printers as of 2014. However, no matter what technology is used in rapid prototyping, there are common …

Adapting Deep Learning For Underwater Acoustic Communication Channel Modeling, Li Wei

Dissertations, Master's Theses and Master's Reports

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work.

Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and …

An Experimental Study Towards Underwater Propulsion System Using Structure Borne Traveling Waves, Shreyas Suhas Gadekar

Dissertations, Master's Theses and Master's Reports

The method of generating steady-state structure-borne traveling waves underwater in an infinite media creates abundant opportunities in the field of propulsive applications, and they are gaining attention from several researchers. This experimental study provides a framework for harnessing traveling waves in a 1D beam immersed under quiescent water using two force input methods and providing a motion to an object floating on the surface of the water.

In this study, underwater traveling waves are tailored using structural vibrations at five different frequencies in the range of 10Hz to 300Hz. The resulting fluid motion provides a propulsive thrust that moves a …

Removing Physical Presence Requirements For A Remote And Automated World - Api Controlled Patch Panel For Conformance Testing, Hunter George Wells

Honors Theses and Capstones

Quality assurance test engineers at the UNH-InterOperability Lab must run tests that require driving and monitoring a selection of DC signals. While the number of signals is numerous, there are limited ports on the test equipment, and only a few signals need patching for any given test. The selection of signals may vary between the 209 different tests and must be re-routed frequently. Currently, testers must leave their desk to manually modify the test setup in another room. This posed a considerable issue at the onset of the COVID-19 Pandemic when physical access was not possible. In order to enable …

Multimodal Adversarial Learning, Uche Osahor

Graduate Theses, Dissertations, and Problem Reports

Deep Convolutional Neural Networks (DCNN) have proven to be an exceptional tool for object recognition, generative modelling, and multi-modal learning in various computer vision applications. However, recent findings have shown that such state-of-the-art models can be easily deceived by inserting slight imperceptible perturbations to key pixels in the input. A good target detection systems can accurately identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a background or a potential target pixel. However, prior research still confirms that such state of the art targets models …

A Tool For Biometric Interpretation Of Forensic Str Dna Profiles, Ahmad Jamal Baroudi

Graduate Theses, Dissertations, and Problem Reports

Rapid DNA biometric identification applications are becoming more essential and widely used in human identity validation processes. Despite their powerful identification capabilities, processing a sample to generate a forensic DNA profile still takes longer compared with other rapid biometric technologies. Methods used to speed up the analysis could lead to signal artifacts similar to those arising from low copy or degraded DNA samples, making the electropherogram unsuitable for forensic interpretation and analysis. The goal of this research effort is to apply biometrics and mathematical approaches to forensic STR (Short Tandem Repeat) profiles. To accomplish this goal, a multi-function software tool …

Detecting User Emotions From Audio Conversations With The Smart Assistants, Sunanda Guha

MSU Graduate Theses

With the proliferation of smart home devices like Google Home or Amazon Alexa, significant research endeavors are being carried out to improve the user experience while interacting with these smart assistants. One such dimension in this endeavor is ongoing research on successful emotion detection from short voice commands used in smart home environment. Besides facial expression and body language, etc., speech plays a pivotal role in the classification of emotions when it comes to smart home application. Upon successful implementation of accurate emotion recognition, the smart devices will be able to intelligently and empathetically suggest appropriate actions based on the …

Machine Learning Techniques For Network Analysis, Irfan Lateef

Dissertations

The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.

A new method that uses the joint time-frequency interpretation of eigensubspace representation for network statistics …

Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor

Computer Science and Engineering Theses and Dissertations

The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

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 …

Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese

Electronic Theses and Dissertations

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …

Development Of A Wearable Haptic Feedback Device For Upper Limb Prosthetics Through Sensory Substitution, Marco B.S. Gallone

Electronic Thesis and Dissertation Repository

Haptics can enable a direct communication pipeline between the artificial limb and the brain; adding haptic sensory feedback for prosthesis wearers is believed to improve operation without drawing too much of the user's attention. Through neuroplasticity, the brain can become more cognizant of the information delivered through the skin and may eventually interpret it as inherently as other natural senses. In this thesis, a wearable haptic feedback device (WHFD) is developed to communicate prosthesis sensory information. A 14-week, 6-stage, between subjects study was created to investigate the learning trajectory as participants were stimulated with haptic patterns conveying joint proprioception. 37 …

Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li

Doctoral Dissertations

In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern.

In this dissertation, we study the security of employing DNNs in CPSs from both the data domain …

Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi

Computer Science and Computer Engineering Undergraduate Honors Theses

Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …

Distance-Based Formation Control Using Decentralized Sensing With Infrared Photodiodes, Steven Williams

LSU Master's Theses

This study presents an onboard sensor system for determining the relative positions of mobile robots, which is used in decentralized distance-based formation controllers for multi-agent systems. This sensor system uses infrared photodiodes and LEDs; its effective use requires coordination between the emitting and detecting robots. A technique is introduced for calculating the relative positions based on photodiode readings, and an automated calibration system is designed for future maintenance. By measuring the relative positions of their neighbors, each robot is capable of running an onboard formation controller, which is independent of both a centralized controller and a global positioning-like system (e.g., …

Simulating A Mobile Wireless Sensor Network Monitoring The Air Force Marathon, Matthew D. Eilertson

Theses and Dissertations

This thesis explores the feasibility of deploying a mobile Wireless Sensor Networks (WSN) to the Air Force (AF) Marathon in support of Air Force Research Laboratory (AFRL) research of sensor and networking infrastructure in denied or degraded environments. A simulation called MarathonSim is developed in the Objective Modular Network Testbed in C++ (OMNeT++) Discrete Event Simulator to test the performance of a mobile WSN. A full factorial design using numbers of runners, transmission powers, and routing protocols is executed to measure Packet Delivery Ratio (PDR) to a central database, average end-to-end delay of application packets, and average power consumed per …