Latest content added for UNT Digital Library Partner: UNT Librarieshttps://digital.library.unt.edu/explore/partners/UNT/browse/?fq=str_degree_department:Department+of+Electrical+Engineering&start=202022-06-16T09:57:39-05:00UNT LibrariesThis is a custom feed for browsing UNT Digital Library Partner: UNT LibrariesPrisoner's Dilemma in Quantum Perspective2022-06-16T09:57:39-05:00https://digital.library.unt.edu/ark:/67531/metadc1944244/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944244/"><img alt="Prisoner's Dilemma in Quantum Perspective" title="Prisoner's Dilemma in Quantum Perspective" src="https://digital.library.unt.edu/ark:/67531/metadc1944244/small/"/></a></p><p>It is known that quantum strategies change the range of possible payoffs for the players in the prisoner's dilemma. In this paper, we examine the effect of the degree of entanglement in determining the payoffs. When both players play quantum strategies, we show that the payoff for both players is unaffected by the entanglement value and it leads to a new Nash equilibrium.</p>Emotion Recognition Using EEG Signals2022-06-16T09:56:47-05:00https://digital.library.unt.edu/ark:/67531/metadc1944242/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944242/"><img alt="Emotion Recognition Using EEG Signals" title="Emotion Recognition Using EEG Signals" src="https://digital.library.unt.edu/ark:/67531/metadc1944242/small/"/></a></p><p>Emotions have significant importance in human life in learning, decision-making, daily interaction, and perception of the surrounding environment. Hence, it has become very essential to detect and recognize a person's emotional states and to build a connection between humans and computers. This process is called brain-computer interaction (BCI) and is a vast field of research in neuroscience. Hence, in the past few years, emotion recognition has gained adequate attention in the research community. In this thesis, an emotion recognition system is designed and analyzed using EEG signals. Several existing feature extraction techniques are studied, analyzed, and implemented to extract features from the EEG signals. An SVM classifier is used to classify the features into various emotional states. Four emotional states are detected, namely, happy, sad, anger, and relaxed state. The model is tested, and simulation results are presented with an interpretation. Furthermore, this study has mentioned and discussed the efficacy of the results achieved. The findings from this study could be beneficial in developing emotion-sensitive technologies, such as augmented modes of communication for severely disabled individuals who are unable to communicate their feelings directly.</p>Small-Scale Dual Path Network for Image Classification and Machine Learning Applications to Color Quantization2022-06-16T09:55:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1944241/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944241/"><img alt="Small-Scale Dual Path Network for Image Classification and Machine Learning Applications to Color Quantization" title="Small-Scale Dual Path Network for Image Classification and Machine Learning Applications to Color Quantization" src="https://digital.library.unt.edu/ark:/67531/metadc1944241/small/"/></a></p><p>This thesis consists of two projects in the field of machine learning. Previous research in the OSCAR UNT lab based on KMeans color quantization is further developed and applied to individual color channels and segmented input images to explore compression rates while still maintaining high output image quality. The second project implements a small-scale dual path network for image classifiaction utilizing the CIFAR-10 dataset containing 60,000 32x32 pixel images ranging across ten categories.</p>An Analysis of Compressive Sensing and the Electrocardiogram2022-06-16T09:55:31-05:00https://digital.library.unt.edu/ark:/67531/metadc1944240/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944240/"><img alt="An Analysis of Compressive Sensing and the Electrocardiogram" title="An Analysis of Compressive Sensing and the Electrocardiogram" src="https://digital.library.unt.edu/ark:/67531/metadc1944240/small/"/></a></p><p>As technology has advanced, data has become more and more important. The more breakthroughs are achieved, the more data is needed to support them. As a result, more storage is required in the system's memory. Compression is therefore required. Before it can be stored, the data must be compressed. To ensure that information is not lost, efficient compression is necessary. This also makes sure that there is no redundancy in the data that is being kept and stored. Compressive sensing has emerged as a new field of compression thanks to developments in sparse optimization. Rather than relying just on compression and sensing formulations, the theory blends the two. The objective of this thesis is to analyze the concept of compressive sensing and to study several reconstruction algorithms. Additionally, a few of the algorithms were put into practice. This thesis also included a model of the ECG, which is vital in determining the health of the heart. For the most part, the ECG is utilized to diagnose heart illness, and a modified synthetic ECG can be used to mimic some of these arrhythmias.</p>Wireless Surface Acoustic Wave Sensor for PM2.5 Detection2022-06-16T09:55:24-05:00https://digital.library.unt.edu/ark:/67531/metadc1944239/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944239/"><img alt="Wireless Surface Acoustic Wave Sensor for PM2.5 Detection" title="Wireless Surface Acoustic Wave Sensor for PM2.5 Detection" src="https://digital.library.unt.edu/ark:/67531/metadc1944239/small/"/></a></p><p>Currently, there is no equipment to measure the real-time fit of EHMR or N-95masks which are used in harsh environments. Improper fit of these EHMRs or N-95 masks exposes the personnel to hazardous environments. Surface acoustic wave (SAW) sensors have been around for few decades and are being used in various applications. In this work, real-time PM2.5 detection using passive wireless SAW sensors is presented. The design of meander antenna at 433MHz for wireless interrogation of SAW sensor using HFSS and ADS is also presented in this thesis. This works also includes the design of YZ-lithium niobate SAW sensor including COMSOL simulation.</p>Localization of UAVs Using Computer Vision in a GPS-Denied Environment2022-06-16T09:54:50-05:00https://digital.library.unt.edu/ark:/67531/metadc1944237/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944237/"><img alt="Localization of UAVs Using Computer Vision in a GPS-Denied Environment" title="Localization of UAVs Using Computer Vision in a GPS-Denied Environment" src="https://digital.library.unt.edu/ark:/67531/metadc1944237/small/"/></a></p><p>The main objective of this thesis is to propose a localization method for a UAV using various computer vision and machine learning techniques. It plays a major role in planning the strategy for the flight, and acts as a navigational contingency method, in event of a GPS failure. The implementation of the algorithms employs high processing capabilities of the graphics processing unit, making it more efficient. The method involves the working of various neural networks, working in synergy to perform the localization. This thesis is a part of a collaborative project between The University of North Texas, Denton, USA, and the University of Windsor, Ontario, Canada. The localization has been divided into three phases namely object detection, recognition, and location estimation. Object detection and position estimation were discussed in this thesis while giving a brief understanding of the recognition. Further, future strategies to aid the UAV to complete the mission, in case of an eventuality, like the introduction of an EDGE server and wireless charging methods, was also given a brief introduction.</p>Notch Filter Design for Power Line Interference Artifact Reduction of ECG Signal and Feature Extraction in LabVIEW2022-06-16T09:46:52-05:00https://digital.library.unt.edu/ark:/67531/metadc1944225/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1944225/"><img alt="Notch Filter Design for Power Line Interference Artifact Reduction of ECG Signal and Feature Extraction in LabVIEW" title="Notch Filter Design for Power Line Interference Artifact Reduction of ECG Signal and Feature Extraction in LabVIEW" src="https://digital.library.unt.edu/ark:/67531/metadc1944225/small/"/></a></p><p>Electrocardiogram (ECG) is a biological signal that represents the heart's electrical activity. Interference from power lines introduces a frequency component of 50 to 60 Hz into the signal, which is the principal cause of ECG corruption. By using the Cadence Virtuoso Spectre circuit simulator and typical TSMC RF 180 nm CMOS technology, a notch filter was created to reduce powerline interference. The advantage of utilizing a notch filter for PLI is that noise at 60 Hz is completely eliminated without sacrificing any important information. Additionally, this study contains a MATLAB-based model for, which is used to compute the power spectral density for the obtained time-domain signal. By incorporating power spectral density into data gathering procedures, it is feasible to enhance data collection methodologies, construct models that appropriately account for observed power and aid in the removal of undesired components.
NI LabVIEW is used to extract features. The advantage of ECG feature extraction is that it provides information that assists in the identification of cardiac rhythm issues, and gives information about the occurrence of heart attack. In this study, several patient data sets are utilized to extract characteristics and provide information regarding heart condition abnormalities.</p>Analysis of the Integration of LEO Satellite Constellations into 5G Networks2022-01-08T16:20:41-06:00https://digital.library.unt.edu/ark:/67531/metadc1873868/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1873868/"><img alt="Analysis of the Integration of LEO Satellite Constellations into 5G Networks" title="Analysis of the Integration of LEO Satellite Constellations into 5G Networks" src="https://digital.library.unt.edu/ark:/67531/metadc1873868/small/"/></a></p><p>Low Earth orbit (LEO) satellite systems have been proposed as a resource for combating the challenges in 5G network coverage and expanding connectivity to a global realm. This research focuses on the current architecture of LEO satellite constellations, with an emphasis on satellite coverage, visibility patterns and coordination schemes. Key-elements of integrating LEO satellites into the eMBB component of 5G are presented and a breakdown of potential link channel characteristics and physical layer performance metrics are described. The produced information allows for a justified analysis on the conceptualized integration.</p>Air Corridors: Concept, Design, Simulation, and Rules of Engagement2022-01-08T16:19:11-06:00https://digital.library.unt.edu/ark:/67531/metadc1873865/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1873865/"><img alt="Air Corridors: Concept, Design, Simulation, and Rules of Engagement" title="Air Corridors: Concept, Design, Simulation, and Rules of Engagement" src="https://digital.library.unt.edu/ark:/67531/metadc1873865/small/"/></a></p><p>Air corridors are an integral part of the advanced air mobility infrastructure. They are the virtual highways in the sky for transportation of people and cargo in the controlled airspace at an altitude of around 1000 ft. to 2000 ft. above the ground level. This paper presents fundamental insights into the design of air corridors with high operational efficiency as well as zero collisions. It begins with the definitions of air cube, skylane or track, intersection, vertiport, gate, and air corridor. Then, a multi-layered air corridor model is proposed. Traffic at intersections is analyzed in detail with examples of vehicles turning in different directions. The concept of capacity of an air corridor is introduced along with the nature of distribution of locations of vehicles in the air corridor and collision probability inside the corridor are discussed. Finally, the results of simulations of traffic flows are presented.</p>The Convolutional Recurrent Structure in Computer Vision Applications2022-01-08T16:17:03-06:00https://digital.library.unt.edu/ark:/67531/metadc1873860/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1873860/"><img alt="The Convolutional Recurrent Structure in Computer Vision Applications" title="The Convolutional Recurrent Structure in Computer Vision Applications" src="https://digital.library.unt.edu/ark:/67531/metadc1873860/small/"/></a></p><p>By organically fusing the methods of convolutional neural network (CNN) and recurrent neural network (RNN), this dissertation focuses on the application of optical character recognition and image classification processing. The first part of this dissertation presents an end-to-end novel receipt recognition system for capturing effective information from receipts (CEIR). The main contributions of this research part are divided into three parts. First, this research develops a preprocessing method for receipt images. Second, the modified connectionist text proposal network is introduced to execute text detection. Third, the CEIR combines the convolutional recurrent neural network with the connectionist temporal classification with maximum entropy regularization as a loss function to update the weights in networks and extract the characters from receipt. The CEIR system is validated with the scanned receipts optical character recognition and information extraction (SROIE) database. Furthermore, the CEIR system has strong robustness and can be extended to a variety of different scenarios beyond receipts. For the convolutional recurrent structure application of land use image classification, this dissertation comes up with a novel deep learning model for land use classification, the convolutional recurrent land use classifier (CRLUC), which further improves the accuracy in classifying remote sensing land use images. Besides, the convolutional fully-connected neural networks with hard sample memory pool structure (CFMP) is invented to tackle the remote sensing land use image classification tasks. The CRLUC and CFMP algorithm performances are tested in popular datasets. Experimental studies show the proposed algorithms can classify images with higher accuracy and fewer training episodes compared to popular image classification algorithms.</p>Group Testing: A Practical Approach2022-01-08T16:10:06-06:00https://digital.library.unt.edu/ark:/67531/metadc1873848/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1873848/"><img alt="Group Testing: A Practical Approach" title="Group Testing: A Practical Approach" src="https://digital.library.unt.edu/ark:/67531/metadc1873848/small/"/></a></p><p>Broadly defined, group testing is the study of finding defective items in a large set. In the medical infection setting, that implies classifying each member of a population as infected or uninfected, while minimizing the total number of tests.</p>Algebraic Trait for Structurally Balanced Property of Node and Its Applications in System Behaviors2022-01-08T15:59:05-06:00https://digital.library.unt.edu/ark:/67531/metadc1873825/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1873825/"><img alt="Algebraic Trait for Structurally Balanced Property of Node and Its Applications in System Behaviors" title="Algebraic Trait for Structurally Balanced Property of Node and Its Applications in System Behaviors" src="https://digital.library.unt.edu/ark:/67531/metadc1873825/small/"/></a></p><p>This thesis targets at providing an algebraic method to indicate network behaviors. Furthermore, for a signed-average consensus problem of the system behaviors, event-triggering signed-average algorithms are designed to reduce the communication overheads. In Chapter 1, the background is introduced, and the problem is formulated. In Chapter 2, notations and basics of graph theory are presented. It is known that the terminal value of the system state is determined by the initial state, left eigenvector and right eigenvector associated with zero eigenvalue of the Laplacian matrix. Since there is no mathematical expression of right eigenvector, in Chapter 3, mathematical expression of right eigenvector is given. In Chapter 4, algebraic trait for structurally balanced property of a node is proposed. In Chapter 5, a method for characterization of collective behaviors under directed signed networks is developed. In Chapter 6, dynamic event-triggering signed-average algorithms are proposed and proved for the purpose of relieving the communication burden between agents. Chapter 7 summarizes the thesis and gives future directions.</p>Asynchronous Level Crossing ADC for Biomedical Recording Applications2021-08-26T21:20:38-05:00https://digital.library.unt.edu/ark:/67531/metadc1833565/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833565/"><img alt="Asynchronous Level Crossing ADC for Biomedical Recording Applications" title="Asynchronous Level Crossing ADC for Biomedical Recording Applications" src="https://digital.library.unt.edu/ark:/67531/metadc1833565/small/"/></a></p><p>This thesis focuses on the recording challenges faced in biomedical systems. More specifically, the challenges in neural signal recording are explored. Instead of the typical synchronous ADC system, a level crossing ADC is detailed as it has gained recent interest for low-power biomedical systems. These systems take advantage of the time-sparse nature of the signals found in this application. A 10-bit design is presented to help capture the lower amplitude action potentials (APs) in neural signals. The design also achieves a full-scale bandwidth of 1.2 kHz, an ENOB of 9.81, a power consumption of 13.5 microwatts, operating at a supply voltage of 1.8 V. This design was simulated in Cadence using 180 nm CMOS technology.</p>Estimation of Drone Location Using Received Signal Strength Indicator2021-08-26T20:46:20-05:00https://digital.library.unt.edu/ark:/67531/metadc1833507/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833507/"><img alt="Estimation of Drone Location Using Received Signal Strength Indicator" title="Estimation of Drone Location Using Received Signal Strength Indicator" src="https://digital.library.unt.edu/ark:/67531/metadc1833507/small/"/></a></p><p>The main objective of this thesis is to propose a UAV (also called as drones) location estimation system based on LoRaWAN using received signal strength indicator in a GPS denied environment. The drones are finding new applications in areas such as surveillance, search, rescue missions, package delivery, and precision agriculture. Nearly all applications require the localization of UAV during flight. Localization is the method of determining a UAVs physical position using a real or virtual coordinate system. This thesis proposes a LoRaWAN-based UAV location method and presents experimental findings from a prototype. The thesis mainly consists of two different sections: one is the distance estimation and the other is the location estimation. First, the distance is estimated based on the mean RSSI values which are recorded at the ground stations using the path loss model. Later using the slant distance estimation technique, the path loss model parameters L and C are estimated whose values are unknown at the beginning. These values completely depend on the environment. Finally, the trilateration system architecture is employed to find the 3-D location of the UAV.</p>Group Testing with Greedy Algorithm2021-08-26T20:43:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1833502/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833502/"><img alt="Group Testing with Greedy Algorithm" title="Group Testing with Greedy Algorithm" src="https://digital.library.unt.edu/ark:/67531/metadc1833502/small/"/></a></p><p>Group testing is all about identifying properties of a set of elements by testing them.</p>Design of Low-Power Front End Compressive Sensing Circuitry and Energy Harvesting Transducer Modeling for Self-Powered Motion Sensor2021-08-26T20:40:36-05:00https://digital.library.unt.edu/ark:/67531/metadc1833492/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833492/"><img alt="Design of Low-Power Front End Compressive Sensing Circuitry and Energy Harvesting Transducer Modeling for Self-Powered Motion Sensor" title="Design of Low-Power Front End Compressive Sensing Circuitry and Energy Harvesting Transducer Modeling for Self-Powered Motion Sensor" src="https://digital.library.unt.edu/ark:/67531/metadc1833492/small/"/></a></p><p>Compressed sensing (CS) is an innovative approach of signal processing that facilitates sub-Nyquist processing of bio-signals, such as a neural signal, electrocardiogram (ECG), and electroencephalogram (EEG). This strategy can be used to lower the data rate to realize ultra-low-power performance, As the count of recording channels increases, data volume is increased resulting in impermissible transmitting power. This thesis work presents the implementation of a CMOS-based front-end design with the CS in the standard 180 nm CMOS process. A novel pseudo-random sequence generator is proposed, which consists of two different types of D flip-flops that are used for obtaining a completely random sequence. This thesis work also includes the (reverse electrowetting-on-dielectric) REWOD based energy harvesting model for self-powered bio-sensor which utilizes the electrical energy generated through the process of conversion of mechanical energy to electrical energy. This REWOD based energy harvesting model can be a good alternative to battery usage, particularly for the bio-wearable applications. The comparative analysis of the results generated for voltage, current and capacitance of the rough surface model is compared to that of results of planar surface REWOD.</p>Formation Control and Path Planning Strategies for Unmanned Aerial Vehicle Swarms2021-08-26T20:38:14-05:00https://digital.library.unt.edu/ark:/67531/metadc1833487/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833487/"><img alt="Formation Control and Path Planning Strategies for Unmanned Aerial Vehicle Swarms" title="Formation Control and Path Planning Strategies for Unmanned Aerial Vehicle Swarms" src="https://digital.library.unt.edu/ark:/67531/metadc1833487/small/"/></a></p><p>This dissertation focuses on the path planning of unmanned aerial vehicle (UAV) swarms under distributed and hybrid control scenarios. It presents two such models and analyzes them both from theory and practice. In the first method, a distributed formation control strategy for UAV swarm based on consensus law is presented. This model makes use of the fundamental concepts of leader-follower structure, social potential functions, and algebraic graph theory to jointly address flocking and de-confliction in the formation control problem. The impact of network topology on formation control is analyzed. It is shown that the degree distribution of the network representing the multi-agent system defines the rate at which formation is attained. Conditions for convergence and stability are derived. In the second method, a hybrid framework for path planning and coverage area by UAV swarms is presented. This strategy significantly improves the current labor-intensive and resource-constraint operations in aquaculture farms. To monitor the farms periodically, an optimized back-and-forth flight path based on the Shamos algorithm is utilized. A trajectory tracking strategy for UAV swarms under uncertain wind conditions is presented.</p>Electrical Equivalent Modeling of the Reverse Electrowetting-on-Dielectric (REWOD) Based Transducer along with Highly Efficient Energy Harvesting Circuit Design towards Self-Powered Motion Sensor2021-08-26T20:30:43-05:00https://digital.library.unt.edu/ark:/67531/metadc1833471/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833471/"><img alt="Electrical Equivalent Modeling of the Reverse Electrowetting-on-Dielectric (REWOD) Based Transducer along with Highly Efficient Energy Harvesting Circuit Design towards Self-Powered Motion Sensor" title="Electrical Equivalent Modeling of the Reverse Electrowetting-on-Dielectric (REWOD) Based Transducer along with Highly Efficient Energy Harvesting Circuit Design towards Self-Powered Motion Sensor" src="https://digital.library.unt.edu/ark:/67531/metadc1833471/small/"/></a></p><p>Among various energy harvesting technologies reverse electrowetting-on-dielectric energy harvesting (REWOD) has been proved to harvest energy from low frequency motion such as many human motion activities (e.g. walking, running, jogging etc.). Voltage rectification and DC-DC boosting of low magnitude AC voltage from REWOD can be used to reliably self-power the wearable sensors. In this work, a commercial component-based rectifier and DC-DC converter is designed and experimentally verified, for further miniaturization standard 180 nm CMOS process is used to design the rectifier and the DC-DC boost converter.This work also includes the MATLAB based model for REWOD energy harvester for various REWOD models. In REWOD energy harvesting, a mechanical input during the motion causes the electrolyte placed in between two dissimilar electrodes to squeeze back and forth thereby periodically changing the effective interfacial area, hence generating alternating current. The alternating current is given to the rectifier design. There is no realistic model that has been developed yet for this technique. Thereby, a MATLAB based REWOD model is developed for the realistic simulation of the REWOD phenomenon. In the work, a comparison of different REWOD models such as planar surface, rough surface and porous models are performed demonstrating the variations in capacitance, current and voltage.</p>Development and Application of Novel Computer Vision and Machine Learning Techniques2021-08-26T20:10:41-05:00https://digital.library.unt.edu/ark:/67531/metadc1833435/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833435/"><img alt="Development and Application of Novel Computer Vision and Machine Learning Techniques" title="Development and Application of Novel Computer Vision and Machine Learning Techniques" src="https://digital.library.unt.edu/ark:/67531/metadc1833435/small/"/></a></p><p>The following thesis proposes solutions to problems in two main areas of focus, computer vision and machine learning. Chapter 2 utilizes traditional computer vision methods implemented in a novel manner to successfully identify overlays contained in broadcast footage. The remaining chapters explore machine learning algorithms and apply them in various manners to big data, multi-channel image data, and ECG data. L1 and L2 principal component analysis (PCA) algorithms are implemented and tested against each other in Python, providing a metric for future implementations. Selected algorithms from this set are then applied in conjunction with other methods to solve three distinct problems. The first problem is that of big data error detection, where PCA is effectively paired with statistical signal processing methods to create a weighted controlled algorithm. Problem 2 is an implementation of image fusion built to detect and remove noise from multispectral satellite imagery, that performs at a high level. The final problem examines ECG medical data classification. PCA is integrated into a neural network solution that achieves a small performance degradation while requiring less then 20% of the full data size.</p>Traditional and Deep Learning Approaches to Color Image Compression and Pattern Recognition Problems2021-08-26T20:08:23-05:00https://digital.library.unt.edu/ark:/67531/metadc1833432/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1833432/"><img alt="Traditional and Deep Learning Approaches to Color Image Compression and Pattern Recognition Problems" title="Traditional and Deep Learning Approaches to Color Image Compression and Pattern Recognition Problems" src="https://digital.library.unt.edu/ark:/67531/metadc1833432/small/"/></a></p><p>This thesis includes three separate research projects focusing on computer vision principles and deep learning pattern recognition problems. Chapter 3 entails color quantization applications using traditional Kmeans clustering techniques and random selection of color techniques within the red, green, blue (RGB) color space to maintain a high-quality image while significantly reducing image file size. Chapter 4 consists of a handwriting character recognition algorithm using backpropagation to classify 70,000 handwritten values from US Census Bureau employees and high school students. Chapter 5 proposes a novel classification technique for 109,446 unique heartbeat samples to identify areas of interest and assist medical professionals in diagnosing heart problems.</p>Object Detection for Aerial View Images: Dataset and Learning Rate2021-05-26T22:01:42-05:00https://digital.library.unt.edu/ark:/67531/metadc1808467/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1808467/"><img alt="Object Detection for Aerial View Images: Dataset and Learning Rate" title="Object Detection for Aerial View Images: Dataset and Learning Rate" src="https://digital.library.unt.edu/ark:/67531/metadc1808467/small/"/></a></p><p>In recent years, deep learning based computer vision technology has developed rapidly. This is not only due to the improvement of computing power, but also due to the emergence of high-quality datasets. The combination of object detectors and drones has great potential in the field of rescue and disaster relief. We created an image dataset specifically for vision applications on drone platforms. The dataset contains 5000 images, and each image is carefully labeled according to the PASCAL VOC standard. This specific dataset will be very important for developing deep learning algorithms for drone applications. In object detection models, loss function plays a vital role. Considering the uneven distribution of large and small objects in the dataset, we propose adjustment coefficients based on the frequencies of objects of different sizes to adjust the loss function, and finally improve the accuracy of the model.</p>Efficient Linear Secure Computation and Symmetric Private Information Retrieval Protocols2021-01-26T00:27:57-06:00https://digital.library.unt.edu/ark:/67531/metadc1752381/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1752381/"><img alt="Efficient Linear Secure Computation and Symmetric Private Information Retrieval Protocols" title="Efficient Linear Secure Computation and Symmetric Private Information Retrieval Protocols" src="https://digital.library.unt.edu/ark:/67531/metadc1752381/small/"/></a></p><p>Security and privacy are of paramount importance in the modern information age. Secure multi-party computation and private information retrieval are canonical and representative problems in cryptography that capture the key challenges in understanding the fundamentals of security and privacy. In this dissertation, we use information theoretic tools to tackle these two classical cryptographic primitives. In the first part, we consider the secure multi-party computation problem, where multiple users, each holding an independent message, wish to compute a function on the messages without revealing any additional information. We present an efficient protocol in terms of randomness cost to securely compute a vector linear function. In the second part, we discuss the symmetric private information retrieval problem, where a user wishes to retrieve one message from a number of replicated databases while keeping the desired message index a secret from each individual database. Further, the user learns nothing about the other messages. We present an optimal protocol that achieves the minimum upload cost for symmetric private information retrieval, i.e., the queries sent from the user to the databases have the minimum number of bits.</p>Light Matter Interactions in Two-Dimensional Semiconducting Tungsten Diselenide for Next Generation Quantum-Based Optoelectronic Devices2021-01-26T00:24:16-06:00https://digital.library.unt.edu/ark:/67531/metadc1752376/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1752376/"><img alt="Light Matter Interactions in Two-Dimensional Semiconducting Tungsten Diselenide for Next Generation Quantum-Based Optoelectronic Devices" title="Light Matter Interactions in Two-Dimensional Semiconducting Tungsten Diselenide for Next Generation Quantum-Based Optoelectronic Devices" src="https://digital.library.unt.edu/ark:/67531/metadc1752376/small/"/></a></p><p>In this work, we explored one material from the broad family of 2D semiconductors, namely WSe2 to serve as an enabler for advanced, low-power, high-performance nanoelectronics and optoelectronic devices. A 2D WSe2 based field-effect-transistor (FET) was designed and fabricated using electron-beam lithography, that revealed an ultra-high mobility of ~ 625 cm2/V-s, with tunable charge transport behavior in the WSe2 channel, making it a promising candidate for high speed Si-based complimentary-metal-oxide-semiconductor (CMOS) technology. Furthermore, optoelectronic properties in 2D WSe2 based photodetectors and 2D WSe2/2D MoS2 based p-n junction diodes were also analyzed, where the photoresponsivity R and external quantum efficiency were exceptional. The monolayer WSe2 based photodetector, fabricated with Al metal contacts, showed a high R ~502 AW-1 under white light illumination. The EQE was also found to vary from 2.74×101 % - 4.02×103 % within the 400 nm -1100 nm spectral range of the tunable laser source. The interfacial metal-2D WSe2 junction characteristics, which promotes the use of such devices for end-use optoelectronics and quantum scale systems, were also studied and the interfacial stated density Dit in Al/2D WSe2 junction was computed to be the lowest reported to date ~ 3.45×1012 cm-2 eV-1.
We also examined the large exciton binding energy present in WSe2 through temperature-dependent Raman and photoluminescence spectroscopy, where localized exciton states perpetuated at 78 K that are gaining increasing attention for single photon emitters for quantum information processing. The exciton and phonon dynamics in 2D WSe2 were further analyzed to unveil other multi-body states besides localized excitons, such as trions whose population densities also evolved with temperature. The phonon lifetime, which is another interesting aspect of phonon dynamics, is calculated in 2D layered WSe2 using Raman spectroscopy for the first time and the influence of external stimuli such as temperature and laser power on the phonon behavior was also studied. Furthermore, we investigated the thermal properties in 2D WSe2 in a suspended architecture platform, and the thermal conductivity in suspended WSe2 was found to be ~ 1940 W/mK which was enhanced by ~ 4X when compared with substrate supported regions.
We also studied the use of halide-assisted low-pressure chemical vapor deposition (CVD) with NaCl to help to reduce the growth temperature to ∼750 °C, which is lower than the typical temperatures needed with conventional CVD for realizing 1L WSe2. The synthesis of monolayer WSe2 with high crystalline and optical quality using a halide assisted CVD method was successfully demonstrated where the role of substrate was deemed to play an important role to control the optical quality of the as-grown 2D WSe2. For example, the crystalline, optical and optoelectronics quality in CVD-grown monolayer WSe2 found to improve when sapphire was used as the substrate. Our work provides fundamental insights into the electronic, optoelectronic and quantum properties of WSe2 to pave the way for high-performance electronic, optoelectronic, and quantum-optoelectronic devices using scalable synthesis routes.</p>The Role of Eigenvalues of Parity Check Matrix in Low-Density Parity Check Codes2020-09-07T10:29:05-05:00https://digital.library.unt.edu/ark:/67531/metadc1707297/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1707297/"><img alt="The Role of Eigenvalues of Parity Check Matrix in Low-Density Parity Check Codes" title="The Role of Eigenvalues of Parity Check Matrix in Low-Density Parity Check Codes" src="https://digital.library.unt.edu/ark:/67531/metadc1707297/small/"/></a></p><p>The new developments in coding theory research have revolutionized the application of coding to practical systems. Low-Density Parity Check (LDPC) codes form a class of Shannon limit approaching codes opted for digital communication systems that require high reliability. This thesis investigates the underlying relationship between the spectral properties of the parity check matrix and LDPC decoding convergence. The bit error rate of an LDPC code is plotted for the parity check matrix that has different Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. It is found that for a given (n,k) LDPC code, large SSEM has better error floor performance than low SSEM. The value of SSEM decreases as the sparseness in a parity-check matrix is increased. It was also found from the simulation that long LDPC codes have better error floor performance than short codes. This thesis outlines an approach to analyze LDPC decoding based on the eigenvalue analysis of the corresponding parity check matrix.</p>Adaptive Slot Location in the Design of Slotted Microstrip Multi-Frequency Antenna for Radionavigation and Radiolocation Applications2020-09-07T10:29:05-05:00https://digital.library.unt.edu/ark:/67531/metadc1707319/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1707319/"><img alt="Adaptive Slot Location in the Design of Slotted Microstrip Multi-Frequency Antenna for Radionavigation and Radiolocation Applications" title="Adaptive Slot Location in the Design of Slotted Microstrip Multi-Frequency Antenna for Radionavigation and Radiolocation Applications" src="https://digital.library.unt.edu/ark:/67531/metadc1707319/small/"/></a></p><p>In light of incidents and concerns regarding the vulnerability of the global positioning system (GPS), the main purpose of the thesis is to look at alternative systems for radio guidance and to put up a serious study on such alternatives with receive and transmit antenna. There is also the need to design such antennas with multiple frequencies to offer robustness in the unlikely event that such adversarial attacks on the GPS happen. The basis on which such alternative antennas are designed is a slotted microstrip. The characteristics of the slot or slots on the microstrip are analyzed by mapping their exact locations on the patch and then noting the resultant center frequencies, the return losses, and the bandwidth. The activities associated with this also focus on the design, fabrication, validation, and characterization of one or more slotted antennas prototypes. The measurement of the antenna prototypes does confirm several frequencies that coexist to see applications, in aeronautical radionavigation, fixed-mobile radionavigation, and radiolocation. The antennas could also feature in a wide-area augmentation system (WAAS), satellite ground link system (SGLS) as well as in surveillance and precision approach radars. Some variations of the antenna are deployed in the areas of law enforcement, surveillance, and unmanned aerial vehicle (UAV). Applications of the antenna in an unmanned ground vehicle (UGV) are feasible due to its multiple resonant frequencies. Radiolocation and radionavigation antennas have also been known to be mounted in UAVs or on tethered balloons along the borders of the United States to detect low-flying aircraft in support of drug interdiction programs.</p>Assistive Navigation Technology for Visually Impaired Individuals2020-09-07T10:29:05-05:00https://digital.library.unt.edu/ark:/67531/metadc1707284/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1707284/"><img alt="Assistive Navigation Technology for Visually Impaired Individuals" title="Assistive Navigation Technology for Visually Impaired Individuals" src="https://digital.library.unt.edu/ark:/67531/metadc1707284/small/"/></a></p><p>Sight is essential in our daily tasks. Compensatory senses have been used for centuries by visually impaired individuals to navigate independently. The help of technology can minimize some challenges for visually impaired individuals. Assistive navigation technologies facilitate the pathfinding and tracing in indoor scenarios. Different modules are added to assistive navigation technologies to warn about the obstacles not only on the ground but about hanging objects. In this work, we attempt to explore new methods to assist visually impaired individuals in navigating independently in an indoor scenario. We employed a location estimation algorithm based on the fingerprinting method to estimate the initial location of the user. We mitigate the error of estimation with particle filter. The shortest path has been calculated with an A* algorithm. To provide the user with an accident-free experiment, we employed an obstacle avoidance algorithm capable of warning the users about the potential hazards. Finally, to provide an effective means of communication with the user, we employed text-to-speech and speech recognition algorithms. The main contribution of this work is to glue these modules together efficiently and affordably.</p>Inkjet Printed Transition Metal Dichalcogenides and Organohalide Perovskites for Photodetectors and Solar Cells2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703403/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703403/"><img alt="Inkjet Printed Transition Metal Dichalcogenides and Organohalide Perovskites for Photodetectors and Solar Cells" title="Inkjet Printed Transition Metal Dichalcogenides and Organohalide Perovskites for Photodetectors and Solar Cells" src="https://digital.library.unt.edu/ark:/67531/metadc1703403/small/"/></a></p><p>This dissertation is devoted to the development of novel devices for optoelectronic and photovoltaic applications using the promise of inkjet printing with two-dimensional (2D) materials. A systematic approach toward the characterization of the liquid exfoliated 2D inks comprising of graphene, molybdenum disulfide (MoS2), tungsten diselenide (WSe2), and 2D perovskites is discussed at depth. In the first study, the biocompatibility of 2D materials -- graphene and MoS2 -- that were drop cast onto flexible PET and polyimide substrates using mouse embryonic fibroblast (STO) and human esophageal fibroblast (HEF) cell lines, was explored. The polyimide samples for both STO and HEF showed high biocompatibility with a cell survival rate of up to ~ 98% and a confluence rate of 70-98%. An inkjet printed, biocompatible, heterostructure photodetector was constructed using inks of photo-active MoS2 and electrically conducting graphene, which facilitated charge collection of the photocarriers. The importance of such devices stems from their potential utility in age-related-macular degeneration (AMD), which is a condition where the photosensitive retinal tissue degrades with aging, eventually compromising vision. The biocompatible inkjet printed 2D heterojunction devices were photoresponsive to broadband incoming radiation in the visible regime, and the photocurrent scaled proportionally with the incident light intensity, exhibiting a photoresponsivity R ~ 0.30 A/W. Strain-dependent measurements were also conducted with bending, that showed Iph ~ 1.16 µA with strain levels for curvature up to ~ 0.262 cm-1, indicating the feasibility of such devices for large format arrays printed on flexible substrates. Alongside the optoelectronic measurements, temperature-dependent (~ 80 K to 573 K) frequency shifts of the Raman-active E12g and A1g modes of multilayer MoS2 exhibited a red-shift with increasing temperature, where the temperature coefficients for the E12g and A1g modes were determined to be ~ - 0.016 cm-1/K and ~ - 0.014 cm-1/K, respectively. The phonon lifetime τ was determined to be in the picosecond range for the E12g and A1g modes, respectively, for the liquid exfoliated multilayer MoS2.
Secondly, an all inkjet printed WSe2-graphene hetero-structure photodetector on flexible polyimide substrates is also studied, where the device performance was found to be superior compared to the MoS2-graphene photodetector. The printed photodetector was photo responsive to broadband incoming radiation in the visible regime, where the photo responsivity R ~ 0.7 A/W and conductivity σ ~ 2.3 × 10-1 S/m were achieved at room temperature.
Thirdly, the synthesis of solution-processed 2D layered organo-halide (CH3(CH2)3NH3)2(CH3NH3)n-1PbnI3n+1 (n = 2, 3, and 4) perovskites is presented here, where inkjet printing was used to fabricate heterostructure flexible photodetector devices on polyimide substrates. The ON/OFF ratio was determined to be high, ~ 2.3 × 103 while the photoresponse time on the rising and falling edges was measured to be rise ~ 24 ms and fall ~ 65 ms, respectively. The strain-dependent measurements, conducted here for the first time for inkjet printed perovskite photodetectors, revealed the Ip decreased by only ~ 27% with bending (radius of curvature of ~ 0.262 cm-1). This work demonstrates the tremendous potential of the inkjet printed, composition tunable, organo-halide 2D perovskite heterostructures for high-performance photodetectors, where the techniques are readily translatable toward flexible solar cell platforms as well.
Fourthly, metal contacts and carrier transport in 2D (CH3(CH2)3NH3)2(CH3NH3)n-1PbnI3n+1 (n = 4) perovskites is a critical topic, where the use of silver (Ag) and graphene (Gr) inks as metallic contacts to 2D perovskites was investigated. The all inkjet printed Gr-perovskite and Ag-perovskite photodetectors were found to be photo-responsive to broadband incoming radiation where measurements were conducted from λ ~ 400 nm to 2300 nm. The photoresponsivity R and detectivity D were compared between the Gr-perovskite and Ag-perovskite photodetectors, which revealed the higher performance for the Ag-perovskite photodetector. The superior performance of the Ag-perovskite photodetector was also justified with the Schottky barrier analysis using the thermionic emission model through temperature-dependent transport measurements.
Finally, this dissertation ends with the description of the first steps for using solution-processed, inkjet printed perovskites for solar cells. The preliminary investigations include the discussion of the chemical formulations for the carrier separation layers, dispersion route, and the variation of solar cell figures of merit with processing.</p>Interference Alignment through Propagation Delay2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703337/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703337/"><img alt="Interference Alignment through Propagation Delay" title="Interference Alignment through Propagation Delay" src="https://digital.library.unt.edu/ark:/67531/metadc1703337/small/"/></a></p><p>With the rapid development of wireless communication technology, the demands for higher communication rates are increasing. Higher communication rate corresponds to higher DoF. Interference alignment, which is an emerging interference management technique, is able to substantially increase the DoF of wireless communication systems. This thesis mainly studies the delay-based interference alignment technique. The key problem lies in the design of the transmission scheme and the appropriate allocation of the propagation delay, so as to achieve the desired DoF of different wireless networks. In addition, through delay-based interference alignment, the achievability of extreme points of the DoF region of different wireless networks can be proved.</p>Design of a Wearable Flexible Resonant Body Temperature Sensor with Inkjet-Printing2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703340/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703340/"><img alt="Design of a Wearable Flexible Resonant Body Temperature Sensor with Inkjet-Printing" title="Design of a Wearable Flexible Resonant Body Temperature Sensor with Inkjet-Printing" src="https://digital.library.unt.edu/ark:/67531/metadc1703340/small/"/></a></p><p>A wearable body temperature sensor would allow for early detection of fever or infection, as well as frequent and accurate hassle-free recording. This thesis explores the design of a body-temperature-sensing device inkjet-printed on a flexible substrate. All structures were first modeled by first-principles, theoretical calculations, and then simulated in HFSS. A variety of planar square inductor geometries were studied before selecting an optimal design. The designs were fabricated using multiple techniques and compared to the simulation results. It was determined that inductance must be carefully measured and documented to ensure good functionality. The same is true for parallel-plate and interdigitated capacitors. While inductance remains relatively constant with temperature, the capacitance of the device with a temperature-sensitive dielectric layer will result in a shift in the resonant frequency as environmental or ambient temperature changes. This resonant frequency can be wirelessly detected, with no battery required for the sensing device, from which the temperature can be deduced. From this work, the optimized version of the design comprises of conductive silver in with a temperature-sensitive graphene oxide layer, intended for inkjet-printing on flexible polyimide substrates. Graphene oxide demonstrates a high dielectric permittivity with good sensing capabilities and high accuracy. This work pushes the state-of-the-art in applying these novel materials and techniques to enable flexible body temperature sensors for future biomedical applications.</p>High-Performance Detectors Based on the Novel Electronic and Optoelectronic Properties of Crystalline 2D van der Waals Solids2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703294/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703294/"><img alt="High-Performance Detectors Based on the Novel Electronic and Optoelectronic Properties of Crystalline 2D van der Waals Solids" title="High-Performance Detectors Based on the Novel Electronic and Optoelectronic Properties of Crystalline 2D van der Waals Solids" src="https://digital.library.unt.edu/ark:/67531/metadc1703294/small/"/></a></p><p>In this work, we study the properties and device applications of MoS2, black phosphorus, MoOx, and NbSe2. We first start with the design, fabrication, and characterization of ultra-high responsivity photodetectors based on mesoscopic multilayer MoS2. The device architecture is comprised of a metal-semiconductor-metal (MSM) photodetector, where Mo was used as the contact metal to suspended MoS2 membranes. The dominant photocurrent mechanism was determined to be the photoconductive effect, while a contribution from the photogating effect was also noted from trap-states that yielded a wide spectral photoresponse from UV-to-IR with an external quantum efficiency (EQE) ~ 104. From time-resolved photocurrent measurements, a fast decay time and response time were obtained with a stream of incoming ON/OFF white light pulses. Another interesting semiconductor 2D material that has attracted special attention due to its small bandgap and ultra-high hole mobility is the black phosphorus. An analysis of the optoelectronic properties and photocurrent generation mechanisms in two-dimensional (2D) multilayer crystallites of black phosphorus (BP) was conducted from 350 K down to cryogenic temperatures using a broad-band white light source. The Mo-BP interface yielded a low Schottky barrier "φ" _"SB" ~ -28.3 meV and a high photoresponsivity R of ~ 2.43 x 105 A/W at a source-drain bias voltage of ~ 0.5 V (300 K, and incident optical power ~ 3.16 μW/cm2). Our report is the first to highlight the empirical use of Mo as a contact metal with BP. From the analysis conducted on the BP devices, the thermally driven photocurrent generation mechanism arising from the photobolometric effect (PBE) dominated the carrier dynamics for T > 181 K since the photocurrent Iph and the bolometric coefficient β undergo a transition in polarity from positive to negative. Our results show the promise of BP to potentially advance thermoelectric and optoelectronic devices stemming from this mono-elemental, direct bandgap 2D van der Waals solid. Another intriguing metallic 2D material is superconducting 2H-NbSe2. Here we present the temperature-dependent Raman spectroscopy and electronic transport on bulk NbSe2, carried out to investigate the scattering mechanisms. We report on the photoresponse of direct probed mesoscopic 2H-NbSe2 as a function of laser energy for lasers at 405 nm, 660 nm, and 1060 nm wavelengths used to irradiate the device, where the modulation from the superconducting-to-normal-state is detected through photomodulation. Additionally, the various oxidation levels of molybdenum oxide have interesting optical and electrical properties as a function of the oxygen vacancy and stoichiometry. The substoichiometric MoOx (2 < x < 3) behaves as a high work function conductor due to its metallic defect band. As a result, one of the potential applications of MoOx is for electrical contacts providing high hole injection or extraction. In this work, we have synthesized MoOx nanosheets via chemical vapor deposition and a four-terminal device was fabricated via e-beam lithography and electronic transport was measured as a function of temperature. Outstanding properties were obtained from our MoOx nanosheets, including a high conductivity of ~ 6,680.3 S cm-1, a superior temperature coefficient of resistance ~ -0.10%, and a high sensitivity based on the bolometric coefficient β of ~ 0.152 mS K-1. In summary, this work pushes the state-of-the-art in enabling 2D van der Waals materials for next-generation high-performance detectors.</p>Efficient Solar Energy Harvesting and Management for Wireless Sensor Networks under Varying Solar Irradiance Conditions2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703345/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703345/"><img alt="Efficient Solar Energy Harvesting and Management for Wireless Sensor Networks under Varying Solar Irradiance Conditions" title="Efficient Solar Energy Harvesting and Management for Wireless Sensor Networks under Varying Solar Irradiance Conditions" src="https://digital.library.unt.edu/ark:/67531/metadc1703345/small/"/></a></p><p>Although wireless sensor networks have been successfully used for environmental monitoring, one of the major challenges that this technology has been facing is supplying continuous and reliable electrical power during long-term field deployment. Batteries require repetitive visits to the deployment site to replace them once discharged; admittedly, they can be recharged from solar panels, but this only works in open areas where solar radiation is unrestricted. This dissertation introduces a novel approach to design and implement a reliable efficient solar energy harvester to continuously, and autonomously, provide power to wireless sensor nodes for long-term applications. The system uses supercapacitors charged by a solar panel and is designed to reduce power consumption to very low levels. Field tests were conducted for more than a year of continuous operation and under a variety of conditions, including areas under dense foliage. The resulting long-term field data demonstrates the feasibility and sustainability of the harvester system for challenging applications. In addition, we analyzed solar radiation data and supercapacitor charging behavior and showed that the harvester system can operate battery free, running on the power provided by supercapacitors. A battery is included only for backup in case the supercapacitor storage fails. The proposed approach provides continuous power supply to the system thereby significantly minimizing data loss by power failure and the frequency of visits to the deployment sites.</p>Gamification to Solve a Mapping Problem in Electrical Engineering2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703330/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703330/"><img alt="Gamification to Solve a Mapping Problem in Electrical Engineering" title="Gamification to Solve a Mapping Problem in Electrical Engineering" src="https://digital.library.unt.edu/ark:/67531/metadc1703330/small/"/></a></p><p>Coarse-Grained Reconfigurable Architectures (CGRAs) are promising in developing high performance low-power portable applications. In this research, we crowdsource a mapping problem using gamification to harnass human intelligence. A scientific puzzle game, Untangled, was developed to solve a mapping problem by encapsulating architectural characteristics. The primary motive of this research is to draw insights from the mapping solutions of players who possess innate abilities like decision-making, creative problem-solving, recognizing patterns, and learning from experience. In this dissertation, an extensive analysis was conducted to investigate how players' computational skills help to solve an open-ended problem with different constraints. From this analysis, we discovered a few common strategies among players, and subsequently, a library of dictionaries containing identified patterns from players' solutions was developed. The findings help to propose a better version of the game that incorporates these techniques recognized from the experience of players. In the future, an updated version of the game that can be developed may help low-performance players to provide better solutions for a mapping problem. Eventually, these solutions may help to develop efficient mapping algorithms, In addition, this research can be an exemplar for future researchers who want to crowdsource such electrical engineering problems and this approach can also be applied to other domains.</p>Design of Ultra Wideband Low Noise Amplifier for Satellite Communications2020-06-15T19:38:58-05:00https://digital.library.unt.edu/ark:/67531/metadc1703346/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1703346/"><img alt="Design of Ultra Wideband Low Noise Amplifier for Satellite Communications" title="Design of Ultra Wideband Low Noise Amplifier for Satellite Communications" src="https://digital.library.unt.edu/ark:/67531/metadc1703346/small/"/></a></p><p>This thesis offers the design and improvement of a 2 GHz to 20 GHz low noise amplifier (LNA) utilizing pHEMT technology. The pHEMT technology allows the LNA to generate a boosted signal at a lower noise figure (NF) while consuming less power and achieving smooth overall gain. The design achieves an overall gain (S21) of ≥ 10 dB with an NF ≤ 2 dB while consuming ≤ 30 mA of power while using commercial off-the-shelf (COTS) components.</p>Deep Learning Approach for Sensing Cognitive Radio Channel Status2020-01-24T06:07:59-06:00https://digital.library.unt.edu/ark:/67531/metadc1609087/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1609087/"><img alt="Deep Learning Approach for Sensing Cognitive Radio Channel Status" title="Deep Learning Approach for Sensing Cognitive Radio Channel Status" src="https://digital.library.unt.edu/ark:/67531/metadc1609087/small/"/></a></p><p>Cognitive Radio (CR) technology creates the opportunity for unlicensed users to make use of the spectral band provided it does not interfere with any licensed user. It is a prominent tool with spectrum sensing functionality to identify idle channels and let the unlicensed users avail them. Thus, the CR technology provides the consumers access to a very large spectrum, quality spectral utilization, and energy efficiency due to spectral load balancing. However, the full potential of the CR technology can be realized only with CRs equipped with accurate mechanisms to predict/sense the spectral holes and vacant spectral bands without any prior knowledge about the characteristics of traffic in a real-time environment. Multi-layered perception (MLP), the popular neural network trained with the back-propagation (BP) learning algorithm, is a keen tool for classification of the spectral bands into "busy" or "idle" states without any a priori knowledge about the user system features. In this dissertation, we proposed the use of an evolutionary algorithm, Bacterial Foraging Optimization Algorithm (BFOA), for the training of the MLP NN. We have compared the performance of the proposed system with the traditional algorithm and with the Hybrid GA-PSO method. With the results of a simulation experiment that this new learning algorithm for prediction of channel states outperforms the traditional BP algorithm and Hybrid GA-PSO method with respect to classification accuracy, probability of misdetection, and Probability of false alarm.</p>A Feasibility Study of Cellular Communication and Control of Unmanned Aerial Vehicles2020-01-24T06:07:59-06:00https://digital.library.unt.edu/ark:/67531/metadc1609109/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1609109/"><img alt="A Feasibility Study of Cellular Communication and Control of Unmanned Aerial Vehicles" title="A Feasibility Study of Cellular Communication and Control of Unmanned Aerial Vehicles" src="https://digital.library.unt.edu/ark:/67531/metadc1609109/small/"/></a></p><p>Consumer drones have used both standards such as Wi-Fi as well as proprietary communication protocols, such as DJI's OcuSync. While these methods are well suited to certain flying scenarios, they are limited in range to around 4.3 miles. Government and military unmanned aerial vehicles (UAVs) controlled through satellites allow for a global reach in a low-latency environment. To address the range issue of commercial UAVs, this thesis investigates using standardized cellular technologies for command and control of UAV systems. The thesis is divided into five chapters: Chapter 1 is the introduction to the thesis. Chapter 2 describes the equipment used as well as the test setup. This includes the drone used, the cellular module used, the microcontroller used, and a description of the software written to collect the data. Chapter 3 describes the data collection goals, as well as locations in the sky that were flown in order to gather experimental data. Finally, the results are presented in Chapter 4, which draws limited correlation between the collected data and flight readiness Chapter 5 wraps up the thesis with a conclusion and future areas for research are also presented.</p>Optimization of RSA Cryptography for FPGA and ASIC Applications2020-01-24T06:07:59-06:00https://digital.library.unt.edu/ark:/67531/metadc1609146/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1609146/"><img alt="Optimization of RSA Cryptography for FPGA and ASIC Applications" title="Optimization of RSA Cryptography for FPGA and ASIC Applications" src="https://digital.library.unt.edu/ark:/67531/metadc1609146/small/"/></a></p><p>RSA cryptography is one of the most widely used cryptosystems in the world. FPGA/ASIC implementations for the classic RSA cryptosystem have high resource utilization due to the use of the Extended Euclid's algorithm for MOD inverse generation, the MOD exponent operation for encryption and decryption, and through non finite-field arithmetic. This thesis translates the RSA cryptosystem into the finite-field domain of arithmetic which greatly increases the range of encryption and decryption keys and replaces the MOD exponent with a multiplication. A new algorithm, the SPX algorithm, is presented and shown to outperform Euclid's algorithm, which is the most widely used mechanism to compute the GCD in FPGA implementations of RSA. The SPX algorithm is then extended to support the computation of the MOD inverse and supply decryption keys. Lastly, a finite-field RSA system is created and shown to support character encryption and decryption while being designed to be integrated into any larger system.</p>Modeling and Design of Antennas for Loosely Coupled Links in Wireless Power Transfer Applications2019-08-29T10:25:12-05:00https://digital.library.unt.edu/ark:/67531/metadc1538705/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1538705/"><img alt="Modeling and Design of Antennas for Loosely Coupled Links in Wireless Power Transfer Applications" title="Modeling and Design of Antennas for Loosely Coupled Links in Wireless Power Transfer Applications" src="https://digital.library.unt.edu/ark:/67531/metadc1538705/small/"/></a></p><p>Wireless power transfer (WPT) systems are important in many areas, such as medical, communication, transportation, and consumer electronics. The underlying WPT system is comprised of a transmitter (TX) and receiver (RX). For biomedical applications, such systems can be implemented on rigid or flexible substrates and can be implanted or wearable. The efficiency of a WPT system is based on power transfer efficiency (PTE). Many WPT system optimization techniques have been explored to achieve the highest PTE possible. These are based on either a figure-of-merit (FOM) approach, quality factor (Q-factor) maximization, or by sweeping values for coil geometries. Four WPT systems for biomedical applications are implemented with inductive coupling. The thesis later presents an optimization technique for finding the maximum PTE of a range of frequencies and coil shapes through frequency, geometry and shape sweeping. Five optimized TX coil designs for different operating frequencies are fabricated for three shapes: square, hexagonal, and octagonal planar-spirals. The corresponding RX is implemented on polyimide tape with ink-jet-print (IJP) silver. At 80 MHz, the maximum measured PTE achieved is 2.781% at a 10 mm distance in the air for square planar-spiral coils.</p>Realization of LSTM Based Cognitive Radio Network2019-08-29T10:25:12-05:00https://digital.library.unt.edu/ark:/67531/metadc1538697/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1538697/"><img alt="Realization of LSTM Based Cognitive Radio Network" title="Realization of LSTM Based Cognitive Radio Network" src="https://digital.library.unt.edu/ark:/67531/metadc1538697/small/"/></a></p><p>This thesis presents the realization of an intelligent cognitive radio network that uses long short term memory (LSTM) neural network for sensing and predicting the spectrum activity at each instant of time. The simulation is done using Python and GNU Radio. The implementation is done using GNU Radio and Universal Software Radio Peripherals (USRP). Simulation results show that the confidence factor of opportunistic users not causing interference to licensed users of the spectrum is 98.75%. The implementation results demonstrate high reliability of the LSTM based cognitive radio network.</p>A Cognitive MIMO OFDM Detector Design for Computationally Efficient Space-Time Decoding2019-08-29T10:25:12-05:00https://digital.library.unt.edu/ark:/67531/metadc1538696/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1538696/"><img alt="A Cognitive MIMO OFDM Detector Design for Computationally Efficient Space-Time Decoding" title="A Cognitive MIMO OFDM Detector Design for Computationally Efficient Space-Time Decoding" src="https://digital.library.unt.edu/ark:/67531/metadc1538696/small/"/></a></p><p>In this dissertation a computationally efficient cognitive multiple-input multiple-output (MIMO) orthogonal frequency division duplexing (OFDM) detector is designed to decode perfect space-time coded signals which are able maximize the diversity and multiplexing properties of a rich fading MIMO channel. The adaptive nature of the cognitive detector allows a MIMO OFDM communication system to better meet to needs of future wireless communication networks which require both high reliability and low run-time complexity depending on the propagation environment. The cognitive detector in conjunction with perfect space-time coding is able to achieve up to a 2 dB bit-error rate (BER) improvement at low signal-to-noise ratio (SNR) while also achieving comparable runtime complexity in high SNR scenarios.</p>Quantile Regression Deep Q-Networks for Multi-Agent System Control2019-06-09T21:09:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1505241/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1505241/"><img alt="Quantile Regression Deep Q-Networks for Multi-Agent System Control" title="Quantile Regression Deep Q-Networks for Multi-Agent System Control" src="https://digital.library.unt.edu/ark:/67531/metadc1505241/small/"/></a></p><p>Training autonomous agents that are capable of performing their assigned job without fail is the ultimate goal of deep reinforcement learning. This thesis introduces a dueling Quantile Regression Deep Q-network, where the network learns the state value quantile function and advantage quantile function separately. With this network architecture the agent is able to learn to control simulated robots in the Gazebo simulator. Carefully crafted reward functions and state spaces must be designed for the agent to learn in complex non-stationary environments. When trained for only 100,000 timesteps, the agent is able reach asymptotic performance in environments with moving and stationary obstacles using only the data from the inertial measurement unit, LIDAR, and positional information. Through the use of transfer learning, the agents are also capable of formation control and flocking patterns. The performance of agents with frozen networks is improved through advice giving in Deep Q-networks by use of normalized Q-values and majority voting.</p>Mesh Networking for Inter-UAV Communications2019-06-09T21:09:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1505208/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1505208/"><img alt="Mesh Networking for Inter-UAV Communications" title="Mesh Networking for Inter-UAV Communications" src="https://digital.library.unt.edu/ark:/67531/metadc1505208/small/"/></a></p><p>Unmanned aerial systems (UASs) have a great potential to enhanced situational awareness in public safety operations. Many UASs operating in the same airspace can cause mid-air collisions. NASA and the FAA are developing a UAS traffic management (UTM) system, which could be used in public safety operations to manage the UAS airspace. UTM relies on an existing communication backhaul, however natural disasters may disrupt existing communications infrastructure or occur in areas where no backhaul exists. This thesis outlines a robust communications alternative that interfaces a fleet of UASs with a UTM service supplier (USS) over a mesh network. Additionally, this thesis outlines an algorithm for vehicle-to-vehicle discovery and communication over the mesh network.</p>Proximal Policy Optimization in StarCraft2019-06-09T21:09:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1505267/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1505267/"><img alt="Proximal Policy Optimization in StarCraft" title="Proximal Policy Optimization in StarCraft" src="https://digital.library.unt.edu/ark:/67531/metadc1505267/small/"/></a></p><p>Deep reinforcement learning is an area of research that has blossomed tremendously in recent years and has shown remarkable potential in computer games. Real-time strategy game has become an important field of artificial intelligence in game for several years. This paper is about to introduce a kind of algorithm that used to train agents to fight against computer bots. Not only because games are excellent tools to test deep reinforcement learning algorithms for their valuable insight into how well an algorithm can perform in isolated environments without the real-life consequences, but also real-time strategy games are a very complex genre that challenges artificial intelligence agents in both short-term or long-term planning. In this paper, we introduce some history of deep learning and reinforcement learning. Then we combine them with StarCraft. PPO is the algorithm which have some of the benefits of trust region policy optimization (TRPO), but it is much simpler to implement, more general for environment, and have better sample complexity. The StarCraft environment: Blood War Application Programming Interface (BWAPI) is open source to test. The results show that PPO can work well in BWAPI and train units to defeat the opponents. The algorithm presented in the thesis is corroborated by experiments.</p>Design of Voltage Boosting Rectifiers for Wireless Power Transfer Systems2019-06-09T21:09:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1505212/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1505212/"><img alt="Design of Voltage Boosting Rectifiers for Wireless Power Transfer Systems" title="Design of Voltage Boosting Rectifiers for Wireless Power Transfer Systems" src="https://digital.library.unt.edu/ark:/67531/metadc1505212/small/"/></a></p><p>This thesis presents a multi-stage rectifier for wireless power transfer in biomedical implant systems. The rectifier is built using Schottky diodes. The design has been simulated in 0.5µm and 130nm CMOS processes. The challenges for a rectifier in a wireless power transfer systems are observed to be the efficiency, output voltage yield, operating frequency range and the minimum input voltage the rectifier can convert. The rectifier outperformed the contemporary works in the mentioned criteria.</p>Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters2019-06-09T21:09:49-05:00https://digital.library.unt.edu/ark:/67531/metadc1505139/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1505139/"><img alt="Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters" title="Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters" src="https://digital.library.unt.edu/ark:/67531/metadc1505139/small/"/></a></p><p>DC to DC converters stabilize the voltage obtained from voltage sources such as solar power system, wind energy sources, wave energy sources, rectified voltage from alternators, and so forth. Hence, the need for improving its control algorithm is inevitable. Many algorithms are applied to DC to DC converters. This thesis designs fuzzy adaptive dynamic programming (Fuzzy ADP) algorithm. Also, this thesis implements both adaptive dynamic programming (ADP) and Fuzzy ADP on DC to DC converters to observe the performance of the output voltage trajectories.</p>Improving Photovoltaic Panel Efficiency by Cooling Water Circulation2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404617/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404617/"><img alt="Improving Photovoltaic Panel Efficiency by Cooling Water Circulation" title="Improving Photovoltaic Panel Efficiency by Cooling Water Circulation" src="https://digital.library.unt.edu/ark:/67531/metadc1404617/small/"/></a></p><p>This thesis aims to increase photovoltaic (PV) panel power efficiency by employing a cooling system based on water circulation, which represents an improved version of water flow based active cooling systems. Theoretical calculations involved finding the heat produced by the PV panel and the circulation water flow required to remove this heat. A data logger and a cooling system for a test panel of 20W was designed and employed to study the relationship between the PV panel surface temperature and its output power. This logging and cooling system includes an Arduino microcontroller extended with a data logging shield, temperature sensing probes, current sensors, and a DC water pump. Real-time measurements were logged every minute for one or two day periods under various irradiance and air temperature conditions. For these experiments, a load resistance was chosen to operate the test panel at its maximum power point. Results indicate that the cooling system can yield an improvement of 10% in power production. Based on the observations from the test panel experiments, a cooling system was devised for a PV panel array of 640 W equipped with a commercial charge controller. The test data logger was repurposed for this larger system. An identical PV array was left uncooled and monitored simultaneously to compare the effect of cooling, demonstrating that the cooled array provided up to an extra 132W or 20% of maximum power for sunny weather conditions. Future expansion possibilities of the project include automated water level monitoring system and water filtration systems.</p>Development and Integration of a Low-Cost Occupancy Monitoring System2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404589/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404589/"><img alt="Development and Integration of a Low-Cost Occupancy Monitoring System" title="Development and Integration of a Low-Cost Occupancy Monitoring System" src="https://digital.library.unt.edu/ark:/67531/metadc1404589/small/"/></a></p><p>The world is getting busier and more crowded each year. Due to this fact resources such as public transport, available energy, and usable space are becoming congested and require vast amounts of logistical support. As of February 2018, nearly 95% of Americans own a mobile cell phone according to the Pew Research Center. These devices are consistently broadcasting their presents to other devices. By leveraging this data to provide occupational awareness of high traffic areas such as public transit stops, buildings, etc logistic efforts can be streamline to best suit the dynamics of the population. With the rise of The Internet of Things, a scalable low-cost occupancy monitoring system can be deployed to collect this broadcasted data and present it to logistics in real time. Simple IoT devices such as the Raspberry Pi, wireless cards capable of passive monitoring, and the utilization of specialized software can provide this capability. Additionally, this combination of hardware and software can be integrated in a way to be as simple as a typical plug and play set up making system deployment quick and easy. This effort details the development and integration work done to deliver a working product acting as a foundation to build upon. Machine learning algorithms such as k-Nearest-Neighbors were also developed to estimate a mobile device's approximate location inside a building.</p>Smart Microgrid Energy Management Using a Wireless Sensor Network2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404560/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404560/"><img alt="Smart Microgrid Energy Management Using a Wireless Sensor Network" title="Smart Microgrid Energy Management Using a Wireless Sensor Network" src="https://digital.library.unt.edu/ark:/67531/metadc1404560/small/"/></a></p><p>Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.</p>Distributed Consensus, Optimization and Computation in Networked Systems2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404555/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404555/"><img alt="Distributed Consensus, Optimization and Computation in Networked Systems" title="Distributed Consensus, Optimization and Computation in Networked Systems" src="https://digital.library.unt.edu/ark:/67531/metadc1404555/small/"/></a></p><p>In the first part of this thesis, we propose a distributed consensus algorithm under multi-layer multi-group structure with communication time delays. It is proven that the consensus will be achieved in both time-varying and fixed communication delays. In the second part, we study the distributed optimization problem with a finite-time mechanism. It is shown that our distributed proportional-integral algorithm can exponentially converge to the unique global minimizer when the gain parameters satisfy the sufficient conditions. Moreover, we equip the proposed algorithm with a decentralized algorithm, which enables an arbitrarily chosen agent to compute the exact global minimizer within a finite number of time steps, using its own states observed over a successive time steps. In the third part, it is shown the implementation of accelerated distributed energy management for microgrids is achieved. The results presented in the thesis are corroborated by simulations or experiments.</p>The Chief Security Officer Problem2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404557/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404557/"><img alt="The Chief Security Officer Problem" title="The Chief Security Officer Problem" src="https://digital.library.unt.edu/ark:/67531/metadc1404557/small/"/></a></p><p>The Chief Security Officer Problem (CSO) consists of a CSO, a group of agents trying to communicate with the CSO and a group of eavesdroppers trying to listen to the conversations between the CSO and its agents. Through Lemmas and Theorems, several Information Theoretic questions are answered.</p>Real-Time Finger Spelling American Sign Language Recognition Using Deep Convolutional Neural Networks2019-01-19T21:34:31-06:00https://digital.library.unt.edu/ark:/67531/metadc1404616/<p><a href="https://digital.library.unt.edu/ark:/67531/metadc1404616/"><img alt="Real-Time Finger Spelling American Sign Language Recognition Using Deep Convolutional Neural Networks" title="Real-Time Finger Spelling American Sign Language Recognition Using Deep Convolutional Neural Networks" src="https://digital.library.unt.edu/ark:/67531/metadc1404616/small/"/></a></p><p>This thesis presents design and development of a gesture recognition system to recognize finger spelling American Sign Language hand gestures. We developed this solution using the latest deep learning technique called convolutional neural networks. This system uses blink detection to initiate the recognition process, Convex Hull-based hand segmentation with adaptive skin color filtering to segment hand region, and a convolutional neural network to perform gesture recognition. An ensemble of four convolutional neural networks are trained with a dataset of 25254 images for gesture recognition and a feedback unit called head pose estimation is implemented to validate the correctness of predicted gestures. This entire system was developed using Python programming language and other supporting libraries like OpenCV, Tensor flow and Dlib to perform various image processing and machine learning tasks. This entire application can be deployed as a web application using Flask to make it operating system independent.</p>