The major advantages of radio frequency identification (RFID) technology over barcodes are that the RFID-tagged objects do not require to be in line-of-sight with the reader for their identification and multiple objects can be read simultaneously. But when multiple objects are read simultaneously there is always a problem of collision which reduces the efficiency of the system. This thesis presents a comprehensive study of the dynamic framed slotted ALOHA (DFSA)-based anti-collision multi-tag identification algorithms for passive RFID system. Performance of various DFSA algorithms is compared through extensive simulation results. In addition, a number of simple performance improvement techniques have also been investigated in this thesis, including improved estimation techniques for the number of tags in each read cycle and a low-complexity heuristic stopping criterion that can be easily implemented in the practical system.

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.

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 …

This thesis provides an implementation of consensus of multi-agent networked systems. Consensus problem is an important issue of distributed computing and has various algorithms and applications in the field of electronical and computer science. The consensus requests all nodes of a network reach an agreement over a certain measurement. An algorithm of convergent consensus problem is implemented through a small network of Bluetooth communication in the thesis. The connections of the Bluetooth devices are wireless, and the device nodes of the network are driven by C++ software and Winsock API. The simulation results show that the implementation completes all the requirements of the distributed consensus algorithm.

Semiconductor nanowires acts as an emerging class of materials with great potential for applications in future electronic devices. Small size, large surface to volume ratio and high carrier mobility of nanowires make them potentially useful for electronic applications with high integration density. In this thesis, the focus was on the growth of high quality ZnO nanowires, fabrication of field effect transistors and UV- photodetectros based on them. Intrinsic nanowire parameters such as carrier concentration, field effect mobility and resistivity were measured by configuring nanowires as field effect transistors. The main contribution of this thesis is the development of a high gain UV photodetector. A single ZnO nanowire functioning as a UV photodetector showed promising results with an extremely high spectral responsivity of 120 kA/W at wavelength of 370 nm. This corresponds to high photoconductive gain of 2150. To the best of our knowledge, this is the highest responsivity and gain reported so far, the previous values being responsivity=40 kA/W and gain=450. The enhanced photoconductive behavior is attributed to the presence of surface states that acts as hole traps which increase the life time of photogenerated electrons raising the photocurrent. This work provides the evidence of such solid states and preliminary …

The baluns are the key components in balanced circuits such balanced mixers, frequency multipliers, push–pull amplifiers, and antennas. Most of these applications have become more integrated which demands the baluns to be in compact size and low cost. In this thesis, a new approach about the design of planar balun is presented where the 4-port symmetrical network with one port terminated by open circuit is first analyzed by using even- and odd-mode excitations. With full design equations, the proposed balun presents perfect balanced output and good input matching and the measurement results make a good agreement with the simulations. Second, Yagi-Uda antenna is also introduced as an entry to fully understand the quasi-Yagi antenna. Both of the antennas have the same design requirements and present the radiation properties. The arrangement of the antenna’s elements and the end-fire radiation property of the antenna have been presented. Finally, the quasi-Yagi antenna is used as an application of the balun where the proposed balun is employed to feed a quasi-Yagi antenna. The antenna is working in the S-band radio frequency and achieves a measured 36% fractional bandwidth for return loss less than -10 dB. The antenna demonstrates a good agreement between its measurement …

Environmental factors can have a significant impact on an individual's health and well-being, and a primary characteristic of environments is air quality. Air sensing equipment is available to the public, but it is often expensive,stationary, or unusable for persons without technical expertise. The goal of this project is to develop an inexpensive and portable sensor module for public use. The system is capable of measuring temperature in Celsius and Fahrenheit, heat index, relative humidity, and carbon dioxide concentration. The sensor module, referred to as the "sniffer," consists of a printed circuit board that interconnects a carbon dioxide sensor, a temperature/humidity sensor, an Arduino microcontroller, and a Bluetooth module. The sniffer is small enough to be worn as a pendant or a belt attachment, and it is rugged enough to consistently collect and transmit data to a user's smartphone throughout their workday. The accompanying smartphone app uses Bluetooth and GPS hardware to collect data and affix samples with a time stamp and GPS coordinates. The accumulated sensor data is saved to a file on the user's phone, which is then examined on a standard computer.

As science and technology continue to advance, innovative developments in transportation can enhance product safety and security for the benefit and welfare of society. The federal government requires every commercial truck to be inspected before each trip. This pre-trip inspection ensures the safe mechanical condition of each vehicle before it is used. An Unmanned Aerial Vehicle (UAV) could be used to provide an automated inspection, thus reducing driver workload, inspection costs and time while increasing inspection accuracy. This thesis develops a primary component of the algorithm that is required to implement UAV pre-trip inspections for commercial trucks using an android-based application. Specifically, this thesis provides foundational work of providing stable height control in an outdoor environment using a laser sensor and an android flight control application that includes take-off, landing, throttle control, and real-time video transmission. The height algorithm developed is the core of this thesis project. Phantom 2 Vision+ uses a pressure sensor to calculate the altitude of the drone for height stabilization. However, these altitude readings do not provide the precision required for this project. Rather, the goal of autonomously controlling height with great precision necessitated the use of a laser rangefinder sensor in the development of the …

This thesis aims to utilize data analysis and predictive modeling techniques and apply them in different domains for gaining insights. The topics were chosen keeping the same in mind. Analysis of customer interests is a crucial factor in present marketing trends and hence we worked on twitter data which is a significant part of digital marketing. Neuroscience, especially psychological behavior, is an important research area. We chose eye tracking data based on which we differentiated human concentration while watching controllable (video game) videos and uncontrollable (sports) videos. Currently, cities are using data analysis for becoming smart cities. We worked on the City of Lewisville emergency services data and predicted the vehicle-accident-prone areas for development of precautionary measures in those areas.

PM2.5 particle sensing has been done using surface acoustic wave based sensor for two different frequencies. Due to mass loading and elasticity loading on the sensor's surface, the center frequency of the sensor shifts. The particle concentration can be tracked based on that frequency shift. The fit factor test has been conducted using higher frequency SAW sensor. The consist results has been achieved for particle sensing and fit factor test with SAW based sensor.

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.

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.

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 …

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.

Today, there is a growing number of buildings in a neighborhood and business parks that are utilizing renewable energy generation, to reduce their electric bill and carbon footprint. The most current way of implementing a renewable energy generation is to use solar panels or a windmill to generate power; then use a charge controller connected to a battery bank to store power. Once stored, the user can then access a clean source of power from these batteries instead of the main power grid. This type of power structure is utilizing a single module system in respect of one building. As the industry of renewable power generation continues to increase, we start to see a new way of implementing the infrastructure of the power system. Instead of having just individual buildings generating power, storing power, using power, and selling power there is a fifth step that can be added, sharing power. The idea of multiple buildings connected to each other to share power has been named a microgrid by the power community. With this ability to share power in a microgrid system, a catastrophic event which cause shutdowns of power production can be better managed. This paper then discusses the data …

One of the challenges of utilizing higher frequencies in the RF spectrum, for any number of applications, is the hardware constraints of analog-to-digital converters (ADCs). Since mid-20th century, we have accepted the Nyquist-Shannon Sampling Theorem in that we need to sample a signal at twice the max frequency component in order to reconstruct it. Compressive Sampling (CS) offers a possible solution of sampling sub-Nyquist and reconstructing using convex programming techniques. There has been significant advancements in CS research and development (more notably since 2004), but still nothing to the advantage of everyday use. Not for lack of theoretical use and mathematical proof, but because of no implementation work. There has been little work on hardware in finding the realistic constraints of a working CS system used for digital signal process (DSP). Any parameters used in a system is usually assumed based on stochastic models, but not optimized towards a specific application. This thesis aims to address a minimal viable platform to implement compressive sensing if applied to a wireless sensor network (WSN), as well as address certain parameters of CS theory to be modified depending on the application.

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.

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 …

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.

Wireless sensor networks are an indispensable tool in this highly connected world. WSNs have been the focus of research efforts in areas of communication, electronics and control for many years. Advancements in the fields of MEMS, RF and digital circuit technology has led to the development of low cost and extremely power efficient smart sensors. This has led to the need of a fast, reliable and inexpensive method of consensus building for these sensor networks. Basic concepts of graph theory and consensus building are explained in this thesis. This thesis reviews the models and strategies for consensus building present in the literature. The shortcomings of these models are explained through examples and a leader-follower model based consensus building strategy is presented. Algorithm to convert any graph into a bipartite graph by edge removal and a strategy to select effective leaders based on a weighted combination of node centrality, ratio of leaders to the total number of nodes and presence of leaf nodes in the group is presented in this thesis. Proposed leader-follower model is compared against classic models for consensus building are compared and proven to be better. Mobility is studied using deterministic and random mobility models to show the …

This thesis proposes a design of a rapidly deployable cellular network prototype that provides voice and data communications and it is interoperable with legacy devices and the existing network infrastructure. The prototype is based on software defined radio and makes use of IEEE 802.11 unlicensed wireless radio frequency (RF) band for backhaul link and an open source GSM implementation software. The prototype is also evaluated in environments where there is limited control of the radio frequency landscape, and using Voice Over Internet Protocol (VoIP) performance metrics to measure the quality of service. It is observed that in environments where the IEEE 802.11 band is not heavily utilized, a large number of calls are supported with good quality of service. However, when this band is heavily utilized only a few calls can be supported as the quality of service rapidly degrades with increasing number of calls, which is due to interference. It is concluded that in order to achieve tolerable voice quality, unused licensed spectrum is needed for backhaul communication between base stations.

In game based learning, motivating the players to learn by providing them a desirable gameplay experience is extremely important. However, it's not an easy task considering the quality of today's commercial non-educational games. Throughout the gameplay, the player should neither get overwhelmed nor under-challenged. The best way to do so is to monitor the player's actions in the game because these actions can tell the reason behind the player's performance. They can also tell about the player's lacking competencies or knowledge. Based on this information, in-game educational interventions in the form of hints can be provided to the player. The success of such games depends on their interactivity, motivational outlook and thus player retention. UNTANGLED is an online mapping game based on crowd-sourcing, developed by Reconfigurable Computing Lab, UNT for the mapping problem of CGRAs. It is also an educational game for teaching the concepts of reconfigurable computing. This thesis performs qualitative comparative analysis on gameplays of low performing players of UNTANGLED. And the implications of this analysis are used to provide recommendations for improving the gameplay experience for these players by guiding them. The recommendations include strategies to reach a high score and a compact solution, hints in the …

This thesis presents the implementation of some of the basic concepts of digital logic design in a fun and creative way with the help of paper electronics. This involves circuit building on paper using conductive tape or conductive ink and circuit components as electronics craft materials. Paper electronics toolkit called circuit sticker microcontroller which is deployed by a company named Chibitronics and AT89C51 microcontroller were used for the computational functioning of the circuits built on paper. This can be used to teach the fundamentals of digital logic design to the students in their early stage of studies in an attractive way and can help them them gain a better understanding. This thesis can also be helpful in grabbing the attention of high school students and motivate them towards choosing the engineering discipline for their higher studies.

Mobile wireless sensor networks are not widely implemented in the real world, even after years of research carried out in this field. One reason is the lack of understanding of the impact that mobility has on network performance. The simulation and emulation of mobile wireless sensor networks is necessary before they are deployed for the real-world applications. This thesis presents a simulation-based study of different mobility models. The total area coverage that depends on the pattern of node movements is observed through simulations. The spatial distribution of node locations is also studied. Various synthetic mobility models available are explored based on their theoretical descriptions. ‘BonnMotion' is used as the network simulator for investigating different mobility scenarios. The results obtained after simulations are imported to MATLAB and the analysis of node movements is done through various plots and inferences from the data. The comparison of mobility models is also discussed based on their spatial node distribution in the simulated scenarios.