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.

This study compares independent use of two known algorithms (Kalmar filter with background subtraction and Particle Filter) that are commonly deployed in object tracking applications. Object tracking in general is very challenging; it presents numerous problems that need to be addressed by the application in order to facilitate its successful deployment. Such problems range from abrupt object motion, during tracking, to a change in appearance of the scene and the object, as well as object to scene occlusions, and camera motion among others. It is important to take into consideration some issues, such as, accounting for noise associated with the image in question, ability to predict to an acceptable statistical accuracy, the position of the object at a particular time given its current position. This study tackles some of the issues raised above prior to addressing how the use of either of the aforementioned algorithm, minimize or in some cases eliminate the negative effects

In large-scale civil structures, a limited number of sensors are placed to monitor the health of civil structures to reduce maintenance, communication and energy costs. In this thesis, the problem of optimal sensor location placement to infer the health of civil structures is explored. First, a comparative study of approaches from the fields of control engineering and civil engineering is conducted . The widely used civil engineering approaches such as effective independence (EI) and modal assurance criterion (MAC) have limitations because of the negligence of modes and damping parameters. On the other hand, control engineering approaches consider the entire system dynamics using impulse response-type sensor measurement data. Such inference can be formulated as an estimation problem, with the dynamics formulated as a second-order differential equation. The comparative study suggests that damping dynamics play significant impact to the selection of best sensor location---the civil engineering approaches that neglect the damping dynamics lead to very different sensor locations from those of the control engineering approaches. In the second part of the thesis, an initial attempt to directly connect the topological graph of the structure (that defines the damping and stiffness matrices) and the second-order dynamics is conducted.

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.

Formation control is a classical problem and has been a prime topic of interest among the scientific community in the past few years. Although a vast amount of literature exists in this field, there are still many open questions that require an in-depth understanding and a new perspective. This thesis contributes towards exploring the wide dimensions of formation control and implementing a formation control scheme for a group of multi-agent systems. These systems are autonomous in nature and are represented by double integrated dynamics. It is assumed that the agents are connected in an undirected graph and use a leader-follower architecture to reach formation when the leading agent is given a velocity that is piecewise constant. A MATLAB code is written for the implementation of formation and the consensus-based control laws are verified. Understanding the effects on formation due to a fixed formation geometry is also observed and reported. Also, a link that describes the functional similarity between desired formation geometry and the Laplacian matrix has been observed. The use of Laplacian matrix in stability analysis of the formation is of special interest.

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.

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.

This thesis investigates the design and implementation of wireless communication system over the GNU Radio. Wireless applications are on the rise with advent of new devices, therefore there is a need to transfer the hardware complexity to software. This development enables software radio function with minimum hardware dependency. the purpose of this thesis is to design a system that will transmit compressed data via Software Defined Radio (SDR). Some parameters such as modulation scheme, bit rate can be changed to achieve the desired quality of service. in this thesis GNU (GNU’s not unix) radio is used while the hardware structure is Universal Software Radio Peripheral (USRP). in order to accomplish the goal, a compression technique called H264 (MPEG_4) encoding is applied for converting data into compressed format. the encoder was implemented in C++ to get compressed data. After encoding, the transmitter reads the compressed data and starts modulation. After modulation, the transmitter put the packets into USRP and sends it to the receiver. Once packets are received they are demodulated and then decoded to recover the original data.

This research discusses how the design of a tornado forward error correcting channel code (FEC) sends digital data stream profiles to the receiver. The complete design was based on the Tornado channel code, binary phase shift keying (BPSK) modulation on a Gaussian channel (AWGN). The communication link was simulated by using Matlab, which shows the theoretical systems efficiency. Then the data stream was input as data to be simulated communication systems using Matlab. The purpose of this paper is to introduce the audience to a simulation technique that has been successfully used to determine how well a FEC expected to work when transferring digital data streams. The goal is to use this data to show how FEC optimizes a digital data stream to gain a better digital communications systems. The results conclude by making comparisons of different possible styles for the Tornado FEC code.

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.

This paper describes a procedure to find the transfer function for the Lego Mindstorms Ev3. Lego Mindstorms Ev3 can serve as the platform for a system modeling and a controller design course. It is economical and accessible. It is also very compatible with Matlab and Simulink. This platform can be used for concepts of modeling, feedback, and controller design. The main approach in this work focuses on the closed loop instead of open loop. Although this approach turns the problem into a more complicated puzzle, it reveals more details. In this work, different techniques have been used, such as time domain, root locus, and least square estimation. Different tools have also been utilized such as Matlab SISO tool, the Matlab System Identification tool, and Simulink. These methods and implementations assisted to acquire different types of transfer functions for the system. By simulating the transfer functions and comparing them with experimental studies, the matching scores were calculated to decide on the best transfer function. Finding the finest transfer function for this gadget enables us to prepare diverse practical undergraduate and graduate curricula.

An economically reliable technique for the synthesis of silicon nanowire was developed using silicon chloride as source material. The 30-40 micron long nanowires were found to have diameters ranging from 40 – 100 nm. An amorphous oxide shell covered the nanowires, post-growth. Raman spectroscopy confirmed the composition of the shell to be silicon-dioxide. Photoluminescence measurements of the as-grown nanowires showed green emission, attributed to the presence of the oxide shell. Etching of the oxide shell was found to decrease the intensity of green emission. n-type doping of the silicon nanowires was achieved using antimony as the dopant. The maximum dopant concentration was achieved by post-growth diffusion. Intrinsic nanowire parameters were determined by implementation of the as-grown and antimony doped silicon nanowires in field effect transistor configuration.

A wireless sensor network (WSN) is a spatially distributed network used to monitor the physical and environmental conditions such as temperature, pressure, sound, humidity, heat, etc. WSNs can be modeled using different simulation frameworks like OMNeT++, Prowler, Atarraya, PiccSIM, Network Simulator, etc. In this research, Simulink framework was used to model WSN system. The complete WSN consisting of transmitting nodes, communication channel, and receiver nodes are built in the Simulink framework. Orthogonal frequency division multiplexing technique was used to transmit the information. The implemented wireless sensor system behavior is studied using temperature as the measurement parameter at different values of signal to noise ratio. The plots of bit error rate versus signal to noise ratio and frame error rate versus signal to noise ratio are generated in the Simulink framework. It is easy to study the effect of different physical layer parameters on the performance of wireless sensor networks by implementing WSN in the Simulink framework.

ZigBee is a substandard of IEEE 802.15 family that is specially designed to take care of factors such as power, data rate and area that primarily affect network performance. This has controlling and monitoring capability, which finds potential applications in different sectors. ZigBee allows the concept of hybrid networks and mobility. A comprehensive analysis of ZigBee networks was carried out by constructing and simulating the networks to evaluate the performance in terms of throughput, delay, network load, and packets dropped. This research is aimed at evaluating the effect of network topology on the system performance. A careful review of simulation platforms brought the conclusion of using OPNET Modeler which has the required frame work. Different network topologies of simple and hybrid were built and simulated. Throughout the simulations, the best-case scenarios were drawn to the conclusion by the graphical analysis of parameters of evaluation. Mobile networks were constructed and simulated to investigate the effect of mobility on communication.

The goal of the proposed device and software architecture is to apply the functionality of mixed reality (MR) in order to make a virtual environment that is more accessible to the visually-impaired. We propose a glove-based system for MR that will use finger and hand movement tracking along with tactile feedback so that the visually-impaired can interact with and obtain a more detailed sense of virtual objects and potentially even virtual environments. The software architecture makes current MR frameworks more accessible by augmenting the existing software and extensive 3D model libraries with both the interfacing of the glove-based system and the audibly navigable user interface (UI) of a virtual environment we have developed. We implemented a circuit with finger flexion/extension tracking for all 5 fingers of a single hand and variable vibration intensities for the vibromotors on all 5 fingertips of a single hand. The virtual environment can be hosted on a Windows 10 application. The virtual hand and its fingers can be moved with the system's input and the virtual fingertips touching the virtual objects trigger vibration motors (vibromotors) to vibrate while the virtual objects are being touched. A rudimentary implementation of picking up and moving virtual objects inside …

The ways that people use libraries have changed drastically over the past few decades. Proliferation of computers and the internet have led to the purpose of libraries expanding from being only places where information is stored, to spaces where people teach, learn, create, and collaborate. Due to this, the ways that people occupy the space in a library have also changed. To keep up with these changes and improve patron experience, institutions collect data to determine how their spaces are being used. This thesis involves the development a system that collects, stores, and analyzes data relevant to occupancy to learn how a space is being utilized. Data is collected from a temperature and humidity sensor, passive Infrared sensor, and an Infrared thermal sensor array to observe people as they occupy and move through a space. Algorithms were developed to analyze the collected sensor data to determine how many people are occupying a space or the directions that people are moving through a space. The algorithms demonstrate the ability to track multiple people moving through a space as well as count the number of people in a space with an RMSE of roughly 0.39 people.

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.

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.

In the world of networked system, average consensus is an important dimension of co-ordinate control and cooperation. Since the communication medium is digital, real value cannot be transmitted and we need to perform quantization before data transmission. But for the quantization, error is introduced in exact value and initial average is lost. Based on this limitation, my 16 bit quantization method (sending MSB in 1-4 cycle and MSB+LSB in 5th cycle) reduces error significantly and preserves initial average. Besides, it works on all types of graphs (star, complete, ring, random geometric graph). My other algorithm, distributing averaging algorithm (PQDA) with probabilistic quantization also works on random geometric graph, star, ring and slow co-herency graph. It shows significant reduced error and attain strict consensus.

Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for self-partitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the Lego® Mindstorms’ NXT on a graphical programming platform using National Instruments’ LabVIEW™ forming a team of communicating agents via NXT-Bee radio module. We single out mobility, …

This thesis discusses the design, fabrication, and testing of a high efficiency, dual band radio frequency power amplifier. While it is difficult to demonstrate an exact mode of operation for power amplifiers at radio frequencies, based on the characteristics of the transistor itself, the argument can be made that our high efficiency performance is due to an approximation to class E operation. The PA is designed around a CGH40025 transistor manufactured by Cree, Inc, which has developed a very useful nonlinear model of its transistor, which allows use of software load/source pull methods to determine optimum impedances to be presented to the gate and drain (hereafter referred to as source and load) of the transistor at each band of operation. A recent work on dual-band impedance matching is then used to design distributed element networks in order to present conjugate matches of these impedances to the transistor. This is followed by a careful layout, after which the PA is then fabricated on a low-impedance substrate using a LPKF Protomat S63 rapid prototyping machine. Measurements of gain and drain current provide values for power-added-efficiency. Simulated gains were 21 and 18 dB at 800 MHz and 1.85 GHz, respectively, with PAE around …

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.

A conventional RF power amplifier will convert the low powered radio frequency signals into high powered signals. Along with the expected ability to increase the communication distance, data transfer rates, RF power amplifiers also have many applications which include military radar system, whether forecasting, etc. The main objective of any power amplifier research is to increase the efficiency while maintaining linearity and broadening the frequency of operation. The main motivation for the renewed interest in PA technology comes from the technical challenges and the economics of modern digital communication systems. Modern communications require high linear power amplifiers and in order to reduce the complete system cost, it is necessary to have a single broadband power amplifier, which can amplify multiple carriers. The improvement in the efficiency of the power amplifier increases the battery life and also reduces the cooling requirements for the same output power. In this thesis, I aim to design and build a wideband class J power amplifier suitable for modern communications. For wideband operation of the GaN technology PA, a bandwidth extension design method is studied and implemented. The simulation results are proved to have a good argument with the theoretical calculations.

Electrocardiography (ECG) monitor is a medical device for recording the electrical activities of the heart using electrodes placed on the body. There are many ECG monitors in the market but it is essential to find the accuracy with which they generate results. Accuracy depends on the processing of the ECG signal which contains several noises and the algorithms used for detecting peaks. Based on these peaks the abnormality in the functioning of the heart can be estimated. Hence this thesis characterizes the ECG signal which helps to detect the abnormalities and determine the accuracy of the system.