Precision agriculture requires detailed and timely information about field condition. In less than the short flight time a UAV (Unmanned Aerial Vehicle) can provide, an entire field can be scanned at the highest allowed altitude. The resulting NDVI (Normalized Difference Vegetation Index) imagery can then be used to classify each point in the field using a FIS (Fuzzy Inference System). This identifies areas that are expected to be similar, but only closer inspection can quantify and diagnose crop properties. In the remaining flight time, the goal is to scout a set of representative points maximizing the quality of actionable information about the field condition. This quality is defined by two new metrics: the average sampling probability (ASP) and the total scouting luminance (TSL). In simulations, the scouting flight plan created using a GA (Genetic Algorithm) significantly outperformed plans created by grid sampling or human experts, obtaining over 99% ASP while improving TSL by an average of 285%.

Electron Beam Induced Deposition (EBID) is a direct write fabrication process with applications in circuit edit and debug, mask repair, and rapid prototyping. However, it suffers from significant drawbacks, most notably low purity. Work over the last several years has demonstrated that deposition from bulk liquid precursors, rather than organometallic gaseous precursors, results in high purity deposits of low resistivity (LPEBID). In this work, it is shown that the deposits resulting from LP-EBID are only highly conductive when deposited at line doses below 25μC/cm. When the dose exceeds this value, the resulting structure is highly porous providing a poor conductive pathway. It is also shown that beam current has no significant effect on the resistivity of the deposits. Nanowires with resistivity significantly lower than the previous best result of 67μΩ•cm were achieved, with the lowest resistivity being only 6.6μΩ•cm, only a factor of 4 higher than that bulk copper of 1.7μΩ•cm.

Renewable energy is one of the most reliable resource that can be used to generate the electricity. It is expected to be the most highly used resource for electricity generation in many countries in the world in the next few decades. Renewable energy resources can be used in several purposes. It can be used for electricity generation, water desalination and mining. Using renewable resources to desalinate the water has several advantages such as reduce the emission, save money and improve the public health. The research described in the thesis focuses on the analysis of using the renewable resources such as solar and wind turbines for desalination plant. The output power from wind turbine is connected through converter and the excess power will be transfer back to the main grid. The photo-voltaic system (PV) is divided into several sections, each section has its own DC-DC converter for maximum power point tracking and a two-level grid connected inverter with different control strategies. The functions of the battery are explored by connecting it to the system in order to prevent possible voltage fluctuations and as a bu er storage in order to eliminate the power mismatch between PV array generation and load demand. Computer models of the system are developed and implemented using the PSCADTM / EMTDCTM software.

The work presented in this thesis is a frequency adaptive tracking filter that can be used in exact tracking of power frequencies and rejection of unwanted harmonics introduced during power disturbances. The power synchronization process includes power converters and other equipment that have many non-linear components that introduce unwanted harmonics. This new design is motivated by the requirement of a filter that can filter all the harmonics and exactly track a rapidly varying fundamental frequency with little time delay and phase error. This thesis analyzes the proposed filter mathematically based on Lyapunov theory and simulations are presented to show the performance of the design in rapid frequency variations.

Acoustic analysis of animal vocalizations has been widely used to identify the presence of individual species, classify vocalizations, identify individuals, and determine gender. In this work automatic identification of speaker and gender of mice from ultrasonic vocalizations and speaker identification of meerkats from their Close calls is investigated. Feature extraction was implemented using Greenwood Function Cepstral Coefficients (GFCC), designed exclusively for extracting features from animal vocalizations. Mice ultrasonic vocalizations were analyzed using Gaussian Mixture Models (GMM) which yielded an accuracy of 78.3% for speaker identification and 93.2% for gender identification. Meerkat speaker identification with Close calls was implemented using Gaussian Mixture Models (GMM) and Hidden Markov Models (HMM), with an accuracy of 90.8% and 94.4% respectively. The results obtained shows these methods indicate the presence of gender and identity information in vocalizations and support the possibility of robust gender identification and individual identification using bioacoustic data sets.

Power electronics have a significant role in modern electrical devices, for instance, hybrid electric vehicles. Power electronics are the technology in between the source and the load circuits and can convert the power from dc to ac or from dc to ac. There are also many types of dc-dc converters, like such as boost and buck converters, which exhibit switching ripple behavior. A boost converter increases the output voltage (with respect to the input voltage) and reduces the output current. A buck converter decreases the output voltage and increases the output current. Many models are used to predict the behavior of the boost and buck converters. The detailed (DET), state-space averaged (SSA), and generalized averaging method (GAM) models are capable of predicting the average behavior of dc-dc converters. For DET and GAM models, the rippling behavior can also be predicted. These models differ in terms of required run time, existence of constant equilibrium points, and accuracy. The DET model has a long run time and does not have constant equilibrium, but it is very accurate. The SSA technique is a mathematical and time-invariant model that capable of describing the behavior of a dc-dc boost converters. It can derive the small signal ac equations of a switching converter and is used to illustrate the average behavior of any linear or nonlinear system in converters. The SSA does not take extensive runtime simulation and has constant equilibrium points, and can be applied to continuous, discrete and sample data systems. The GAM model can predict the average and ripple behavior in power electronic systems and has constant equilibrium and fast run time. However, it has a numerical stability issue. The integrator stabilized multifrequency averaging (ISMFA) model is employed to solve the stability issue in the GAM model, but it is a complicated dynamic method and has restrictions in its process. In the present study, a simplified but stable GAM model is introduced to predict the average and ripple behavior of boost dc-dc converters and to overcome the limitations of other methods. In this work, the stabilized GAM model has been used for a dc-dc boost converters. The stability of the proposed model is analyzed. The performance of the improved GAM model is compared with the DET, SSA, and GAM models. The results show that the stabilized GAM model is stable with the additional poles created by the GAM assignable by parameter choice. The new GAM model predicts the same results as the existing GAM method without the underlying stability concerns. The stabilized GAM model exhibits constant ii equilibrium point and requires significantly lower run times than the DET model, but it is also able to predict the ripple performance of the converter. The stabilized GAM model does not take a long run time, is less complicated, has fewer restrictions, has constant equilibrium and internal stability, and has more straightforward implementation than other models, like the ISMFA model. It represents a suitable alternative to DET models when high accuracy simulations are desired without long simulation run times.

The growing applications for IoT devices have caused an increase in the study of low power consuming circuit design to meet the requirement of devices to operate for various months without external power supply. Scaling down the conventional CMOS causes various complications to design due to CMOS properties, therefore various non-conventional CMOS design techniques are being proposed that overcome the limitations. This thesis focuses on some of those emerging and novel low power design technique namely Adiabatic logic and low power devices like Magnetic Tunnel Junction (MTJ) and Carbon Nanotube Field Effect transistor (CNFET). Circuits that are used for large computations (multipliers, encryption engines) that amount to maximum part of power consumption in a whole chip are designed using these novel low power techniques.

In manual control, the welding gun’s moving speed can significantly influence the welding results and critical welding operations usually require welders to concentrate consistently in order to react rapidly and accurately. However, human welders always have some habitual action which can have some subtle influence the welding process. It takes countless hours to train an experienced human welder. Using vision and IMU sensor will be able to set up a system and allow the worker got more accurate visual feedback like an experienced worker. The problem is that monitor and measuring of the control process not always easy under a complex working environment like welding. In this thesis, a new method is developed that use two different methods to compensate each other to obtain accurate monitoring results. Vision sensor and IMU sensor both developed to obtain the accurate data from the control process in real-time but don’t influence other. Although both vision and IMU sensor has their own limits, they also have their own advantage which can contribute to the measuring system.

Structured Light Imaging (SLI) is a means of digital reconstruction, or Three-Dimensional (3D) scanning, and has uses that span many disciplines. A projector, camera and Personal Computer (PC) are required to perform such 3D scans. Slight variances in synchronization between these three devices can cause malfunctions in the process due to the limitations of PC graphics processors as real-time systems. Previous work used a Field Programmable Gate Array (FPGA) to both drive the projector and trigger the camera, eliminating these timing issues, but still needing an external camera. This thesis proposes the incorporation of the camera with the FPGA SLI controller by means of a custom printed circuit board (PCB) design. Featuring a high speed image sensor as well as High Definition Multimedia Interface (HDMI) input and output, this PCB enables the FPGA to perform SLI scans as well as pass through HDMI video to the projector for Spatial Augmented Reality (SAR) purposes. Minimizing ripple noise on the power supply by means of effective circuit design and PCB layout, realizes a compact and cost effective machine vision sensing solution.

Magneto-optical materials such as permalloy can be used to create artificial spin- ice (ASI) lattices with antiferromagnetic ordering. Magneto-optical materials used to create diffraction lattices are known to exhibit magnetic scattering at the half- order Bragg peak while in the ground state. The significant drawbacks of studying the magneto-optical generation of OAM using x-rays are cost, time, and access to proper equipment. In this work, it is shown that the possibility of studying OAM and magneto-optical materials in the spectrum of visible light at or around 2 eV is viable. Using spectroscopic ellipsometry it is possible to detect a change in the magnetization of thin permalloy films with thicknesses between 5 and 20 nm. Patterns consistent with OAM were found at 1.95 eV using a square lattice with a 4𝜋 radial phase shift in the antiferromagnetic ground state. Evidence of magnetic scattering at the half-order Bragg peak using 1.95 eV was also found.