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Implementation Of Fuzzy Logic Control Into An Equivalent Minimization Strategy For Adaptive Energy Management Of A Parallel Hybrid Electric Vehicle, Jared Alexander Diethorn Jan 2021

Implementation Of Fuzzy Logic Control Into An Equivalent Minimization Strategy For Adaptive Energy Management Of A Parallel Hybrid Electric Vehicle, Jared Alexander Diethorn

Graduate Theses, Dissertations, and Problem Reports

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Electric vehicles have been introduced by the industry, showing promising signs of reducing emissions production in the automotive sector. However, many consumers may be hesitant to purchase fully electric vehicles due to several uncertainty variables including available charging stations. Hybrid electric vehicles (HEVs) have been introduced to reduce problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in …


Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon Jan 2021

Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon

Graduate Theses, Dissertations, and Problem Reports

With the rise of Connected-and-Automated-Vehicle (CAV) technologies on roadways, transportation networks have become increasingly connected through Vehicle-to-Everything (V2X) systems. With access to the additional data from V2X, modern cruise control systems like Adaptive Cruise Control (ACC) are further improved upon to develop systems like Cooperative ACC (CACC) which reduces traffic congestion and increases driver safety and energy efficiency. With that increased connectivity, previously closed vehicle systems are now vulnerable to new security threats which pose new technical challenges. Significant research has been done to strengthen the network against external threats such as denial-of-service attacks (DoS) or passive eavesdropping attacks using …


Identical Twins As A Facial Similarity Benchmark For Human Facial Recognition, John Andrew Mccauley Jan 2021

Identical Twins As A Facial Similarity Benchmark For Human Facial Recognition, John Andrew Mccauley

Graduate Theses, Dissertations, and Problem Reports

The problem of distinguishing identical twins and non-twin look-alikes in automated facial recognition (FR) applications has become increasingly important with the widespread adoption of facial biometrics. Due to the high facial similarity of both identical twins and look-alikes, these face pairs represent the hardest cases presented to facial recognition tools. This work presents an application of one of the largest twin datasets compiled to date to address two FR challenges: 1) determining a baseline measure of facial similarity between identical twins and 2) applying this similarity measure to determine the impact of doppelgangers, or look-alikes, on FR performance for large …


An End-To-End Face Recognition System Evaluation Framework, James Andrew Duncan Jan 2021

An End-To-End Face Recognition System Evaluation Framework, James Andrew Duncan

Graduate Theses, Dissertations, and Problem Reports

The performance of face recognition system components is traditionally reported using metrics such as the Receiver Operating Characteristic (ROC), Cumulative Match Characteristic (CMC), and Identification Error Tradeoff (IET). Recently, new metrics have been published to take advantage of annotation-dense datasets such as IARPA Janus Benchmark-Surveillance and IARPA Janus Benchmark-Multi Domain Face to describe end-to-end face recognition system performance. Unlike traditional (component-level) analysis, end-to-end analysis of a system produces a metric proportional to the experience of a user of a face recognition system. The End-to-End Cumulative Match Characteristic (E2ECMC) summarizes detection, identity consolidation, and identity retrieval performance. The End-to-End Subject Cumulative …


Re-Design Of Precision Signal Conditioning Circuit For Detecting Schumann Resonance, Rohith Bikkina Jan 2021

Re-Design Of Precision Signal Conditioning Circuit For Detecting Schumann Resonance, Rohith Bikkina

Graduate Theses, Dissertations, and Problem Reports

Extremely low frequencies signals are waves between 3 to 30Hz and corresponding wavelengths between 10,000 to 100,000 kilometers. The specific signals used here are generated from lightning and are excited at frequencies around 8Hz, 14Hz, 20Hz. These are often called Schumann Resonance frequencies. Several stations have been built around the world for identifying ELF waves. All of those required a sparsely populated area that was far away from electric power lines because of interference from electric noise at 50 Hz and 60Hz. This project develops and tests an amplifier and filter circuit that should assist in identifying the Schumann Resonance …


Consensus Based Control Strategy For Virtual Synchronous Generators In Microgrids, Anusha Kandula Jan 2021

Consensus Based Control Strategy For Virtual Synchronous Generators In Microgrids, Anusha Kandula

Graduate Theses, Dissertations, and Problem Reports

Renewable energy sources such as photo-voltaic and wind energy are integrating very rapidly in power systems. These energy-based systems typically adopt power-electronic interfaced inverters to connect to the grid. However, unlike traditional generators, these sources have low inertia, resulting in system stability issues, especially in microgrids where they are the primary sources. To mitigate the low-inertia effect, the inverters are modeled as virtual synchronous generators (VSG), and their control is designed. The VSG emulates the inertia effect of the synchronous generator and maintains the stability of the system. Even though the droop control provides the primary control, it is insufficient …


Analysis Of Millimeter-Wave Networks: Blockage, Antenna Directivity, Macrodiversity, And Interference, Enass Hriba Jan 2021

Analysis Of Millimeter-Wave Networks: Blockage, Antenna Directivity, Macrodiversity, And Interference, Enass Hriba

Graduate Theses, Dissertations, and Problem Reports

Due to its potential to support high data rates at low latency with reasonable interference isolation because of signal blockage at these frequencies, millimeter-wave (mmWave) communications has emerged as a promising solution for next-generation wireless networks. MmWave systems are characterized by the use of highly directional antennas and susceptibility to signal blockage by buildings and other obstructions, which significantly alter the propagation environment. The received power of each transmission depends on the direction the corresponding antennas point and whether the signal’s path is line-of-sight (LOS), non-LOS (i.e., partially blocked), or completely blocked. A key challenge in modeling blocking in mmWave …


Integration Of Deep Hashing And Channel Coding For Biometric Security And Biometric Retrieval, Veeru Talreja Jan 2021

Integration Of Deep Hashing And Channel Coding For Biometric Security And Biometric Retrieval, Veeru Talreja

Graduate Theses, Dissertations, and Problem Reports

In the last few years, the research growth in many research and commercial fields are due to the adoption of state of the art deep learning techniques. The same applies to even biometrics and biometric security. Additionally, there has been a rise in the development of deep learning techniques used for approximate nearest neighbor (ANN) search for retrieval on multi-modal datasets. These deep learning techniques knows as deep hashing (DH) integrate feature learning and hash coding into an end-to-end trainable framework. Motivated by these factors, this dissertation considers the integration of deep hashing and channel coding for biometric security and …


Transform Based Approaches For The Detection Of Astrophysical Signals, Marwan Mahfud Alkhweldi Jan 2021

Transform Based Approaches For The Detection Of Astrophysical Signals, Marwan Mahfud Alkhweldi

Graduate Theses, Dissertations, and Problem Reports

Development of new algorithms for the detection of isolated astrophysical pulses is of interest to radio astronomers. Both Fast Radio Bursts (FRBs) and several Rotating Radio Transients (RRATs) were detected through the application of a single pulse search algorithm. The conventional approach to detect astronomical pulses requires an exhaustive search for the correct dispersion measure. Its accelerated versions involve signal processing in Fourier transform space.

In this dissertation, we present several new transform-based approaches for the detection and analysis of astrophysical signals with the latest being the most effective and advanced of all. It is implemented in several steps. First, …


Application Of Artificial Intelligence In Three Phase Unbalanced Smart Power Distribution Grid, Deepak Tiwari Jan 2021

Application Of Artificial Intelligence In Three Phase Unbalanced Smart Power Distribution Grid, Deepak Tiwari

Graduate Theses, Dissertations, and Problem Reports

Electrification of the transportation sector can play an essential role in curbing fossil fuel scarcity and oil shortages in the world. Electric vehicles (EVs) can significantly reduce CO2 emissions, improve urban pollution. Apart from these advantages of EVs, they may also pose challenges to the distribution grid. Increasing penetration of EVs puts an extra burden and leads to affect the grid severely. Load congestions, voltage drops/regulation, overloading are some of the issues that might incur in the grid because of improper charging of EVs. The uncertain nature of EV owners makes it very difficult to predict the charging pattern. So …


Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani Jan 2021

Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani

Graduate Theses, Dissertations, and Problem Reports

Deep models have provided high accuracy for different applications such as person recognition, image segmentation, image captioning, scene description, and action recognition. In this dissertation, we study the deep learning models and their application in improving the performance and reliability of person recognition. This dissertation focuses on five aspects of person recognition: (1) multimodal person recognition, (2) quality-aware multi-sample person recognition, (3) text-independent speaker verification, (4) adversarial iris examples, and (5) morphed face images. First, we discuss the application of multimodal networks consisting of face, iris, fingerprint, and speech modalities in person recognition. We propose multi-stream convolutional neural network architectures …


Floating-Gate Design And Linearization For Reconfigurable Analog Signal Processing, Steven Michael Andryzcik Ii Jan 2021

Floating-Gate Design And Linearization For Reconfigurable Analog Signal Processing, Steven Michael Andryzcik Ii

Graduate Theses, Dissertations, and Problem Reports

Analog and mixed-signal integrated circuits have found a place in modern electronics design as a viable alternative to digital pre-processing. With metrics that boast high accuracy and low power consumption, analog pre-processing has opened the door to low-power state-monitoring systems when it is utilized in place of a power-hungry digital signal-processing stage. However, the complicated design process required by analog and mixed-signal systems has been a barrier to broader applications. The implementation of floating-gate transistors has begun to pave the way for a more reasonable approach to analog design. Floating-gate technology has widespread use in the digital domain. Analog and …


Real Vs Fake Faces: Deepfakes And Face Morphing, Jacob L. Dameron Jan 2021

Real Vs Fake Faces: Deepfakes And Face Morphing, Jacob L. Dameron

Graduate Theses, Dissertations, and Problem Reports

The ability to determine the legitimacy of a person’s face in images and video can be important for many applications ranging from social media to border security. From a biometrics perspective, altering one’s appearance to look like a target identity is a direct method of attack against the security of facial recognition systems. Defending against such attacks requires the ability to recognize them as a separate identity from their target. Alternatively, a forensics perspective may view this as a forgery of digital media. Detecting such forgeries requires the ability to detect artifacts not commonly seen in genuine media. This work …


Weed Recognition In Agriculture: A Mask R-Cnn Approach, Sruthi Keerthi Valicharla Jan 2021

Weed Recognition In Agriculture: A Mask R-Cnn Approach, Sruthi Keerthi Valicharla

Graduate Theses, Dissertations, and Problem Reports

Recent interdisciplinary collaboration on deep learning has led to a growing interest in its application in the agriculture domain. Weed control and management are some of the crucial tasks in agriculture to maintain high crop productivity. The inception phase of weed control and management is to successfully recognize the weed plants, followed by providing a suitable management plan. Due to the complexities in agriculture images, such as similar colour and texture, we need to incorporate a deep neural network that uses pixel-wise grouping for identifying the plant species. In this thesis, we analysed the performance of one of the most …


Interoperability Of Contact And Contactless Fingerprints Across Multiple Fingerprint Sensors, Brady M. Williams Jan 2021

Interoperability Of Contact And Contactless Fingerprints Across Multiple Fingerprint Sensors, Brady M. Williams

Graduate Theses, Dissertations, and Problem Reports

Contactless fingerprinting devices have grown in popularity in recent years due to speed and convenience of capture. Also, due to the global COID-19 pandemic, the need for safe and hygienic options for fingerprint capture are more pressing than ever. However, contactless systems face challenges in the areas of interoperability and matching performance as shown in other works. In this paper, we present a contactless vs. contact interoperability assessment of several contactless devices, including cellphone fingerphoto capture. During the interoperability assessment, the quality of the fingerprints was considered using the NBIS NFIQ software with the contact-based fingerprint performing the best overall …


The Impact Of Driver Reaction In Cooperative Vehicle Safety Systems, Elwarfalli Ibrahim Jan 2021

The Impact Of Driver Reaction In Cooperative Vehicle Safety Systems, Elwarfalli Ibrahim

Graduate Theses, Dissertations, and Problem Reports

Cooperative Vehicular Safety (CVS) has recently been widely studied in the field of automated vehicular systems. CVS systems help decrease the rates of accidents. However, implementing and testing CVS applications in real world is very costly and risky. Hence, most of the related research studies on CVS applications have relied mainly on simulations. In simulated CVS systems, it is important to consider all critical aspects of used models, and how these models affect one another.

The movement model is a key component in the simulation study of CVS systems, which controls the mobility of vehicles (nodes) and responses to the …