Fast and reliable Spectrum Sensing (SS) plays a crucial role in the cognitive radio (CR) technology in order to prevent unwanted interference to the primary users (PU) and to reliably and quickly detect the white spaces in the spectrum for opportunistic access by the secondary users (SU). Spectrum Sensing must often be performed in the absence of information such as PU signaling scheme, noise level and channel fading coefficients. While these parameters can be estimated in the SU, estimation errors significantly deteriorates the performance of SS techniques. In this thesis, we introduce and evaluate the performance of two novel blind spectrum sensing algorithms which do not rely on knowledge of these parameters. The first is a SS technique for signaling schemes which introduce controlled intersymbol interference in the transmitter. The second is for cases when the receiver of the SU is equipped with a multiantenna system. This approach exploits the path correlation among the signals received at different antennas. Next we analyze the performance of Spectrum Monitoring (SM), an new technique which allows the SU to detect the presence of the PU using its own receiver statistics. In contrast to SS, with SM, the SU does not need to interrupt its own transmission in order to detect the presence of the PU. We carefully construct the decision statistics for SM and evaluate its performance. The performance of a hybrid SM/SS system shows a significant improvement over SS alone.

This dissertation is concentrated mainly on the newest PMTF machine topology proposed and patented by Jacek F. Gieras in March 4, 2010. Such a topology (topology of 2010) is an object of this dissertation. A prototype that was built with 3D Finite Element Method (FEM) modeling of PMTF generator proves that the generator that was built on the basis of topology of 2010 has several significant disadvantages among which the greatest impact have high leakage flux losses. Applying FEM modeling, various steps to improve machine performance have been undertaken. Results obtained from modeling show, that keeping the same diameter and lengths of the machine as well as number of turns of the winding, output power of the machine can be two times higher and the negative flux linkage that is established by inactive PMs significantly reduced. This was achieved by introducing magnetic shunts to the stator structure. These shunts also reduce cogging torque. Modifications include changing machine stator structure, slot shape, and implementation of magnetic shunts which play a vital role in preventing flux leakage losses and reducing cogging torque. During modifications a big attention was paid to simplifying a manufacturing process. Modifications do not complicate machine design and count all aspects which may arise when manufacturing. Modified version of the PMTF machine was built by Polish manufacturer Komel for University of Nevada-Reno. This project was supported by National Science Foundation. The prototype results prove that the magnetic shunts block almost 70% of negative magnetic flux coming from inactive magnets. The induced voltage of the machine calculated using 3D FEM model is the same what was obtained during prototype laboratory test. However, the laboratory test also shows that if magnetic shunts are made of pure iron, generator has significant power losses. These power losses are caused by eddy currents induced on the magnetic shunts. To prevent eddy currents flowing on the magnetic shunts surface, instead of pure iron, laminated steel or magnetic powder has to be selected as a material for shunts. Combining the ideas of topologies [1-3] a new version of PMTF machine is introduced in this dissertation. Its electromechanical parameters are calculated. Three different designs of PMTF generator are compared in terms of output power to volume ratio.

The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact within an environment. The agents are considered to be autonomous entities. MAS can be used to solve problems that are difficult or impossible for an individual agent to solve. The main feature which is achieved when developing MAS, if they work, is flexibility, since MAS can be added to, modified and reconstructed, without the need for detailed rewriting of the application. MAS can manifest self-organization as well as self-steering related complex behaviors even when the individual strategies of all their agents are simple. The goal of MAS research is to find methods that allow us to build complex systems composed of autonomous agents who, while operating on local knowledge and possessing only limited abilities, are nonetheless capable of enacting the desired global behaviors. We want to know how to take a description of what a system of agents should do and break it down into individual agent behaviors. This thesis investigates the problem when discrete-time MAS are consensusable under undirected graph. A discussion is provided to show how the problem differs from continuous time system. Then a consensusability condition is derived in terms of the Mahler measure of the agent system for single input single out systems (SISO) and result shows that there is an improved consensusability by a power of two. An algorithm is proposed for distributed consensus feedback control law when the consensusability holds. Also the case of output feedback is considered in which the consensusability problem becomes more complicated. To solve this we decompose the problem into two parts i.e. state feedback and state estimation. Simulation results demonstrate the effectiveness of the established results.

Reliability is one of the key aspects of power system operation and therefore reliability analysis techniques are well developed. However reliability analysis conventionally takes into account active power and limited attention has been given to reactive power. Reactive power is very essential in maintaining voltage stability of power systems. The voltage constraint at network can restricts active power delivery to the loads and could result in forced load curtailment. This research investigates the effect of reactive power shortage on reliability of power systems with significant penetration of PV cells. The reactive power issues become more significant in distributed generation using renewable energy sources such as photovoltaic (PV) Cells, which operate mostly at unity power factor. The IEEE 14-Bus system is utilized to perform this study. Twenty four state PV generation model was developed based on 24-hour solar radiation trend. Reliability indices are calculated analytically and verified through simulation without considering reactive power shortage. Next, a measure of Expected Energy Not Supplied (EENS) on account of reactive power shortage and voltage violation in network is calculated. Monte Carlo simulation was performed in MATLAB environment, where simulation results are compared with the case without taking into account reactive power and voltage violation. This research suggests that placement of the PV in the network can greatly reduce active and reactive power shortage during the contingencies. The reactive power is studied here from design and planning perspectives for reliable and stable power system operation when high penetrations of PV energy sources are present.

Storage devices can be used in a power gird to store the excess energy when the energy production is high and the demand is low and utilize the stored energy when the produced energy cannot meet the high demands of the consumers. This thesis represents a micro grid consisting of a conventional synchronous generator, as well as renewable energy sources, energy storage, and loads in order to investigate the effective energy flow control and transient stability improvement by employing thermal storage. Thermal storage, unlike electrical one (such as battery) is more environmental friendly, has longer life span, and is more effective in power flow control. In this thesis, resistive and heat pump type thermal storage are proposed and its stability effects on micro grids are evaluated. A suitable model is developed for the thermal storage and the grids stability analysis is adopted by using linearization methods. Consequently, by designing an optimal controller for the storage the stability of the micro grid is improved as verified through the simulations.

This thesis focuses on the present state of electrical vehicles (EVs) in the market and the effects that these vehicles could have on residential distribution systems. The current EVs available on the market and the current level of market penetration were investigated. Advantages and disadvantages of EVs from a consumer and governmental perspective were identified. The efficiencies of the whole energy delivery process of electrical vehicles and gasoline vehicles were estimated. Efficiency estimation was used to estimate the impact of EVs on the consumption of fossil fuels and emission of greenhouse gases. Measurement of an EV battery charging cycle and modeling of a residential power system with EV battery charger loads was performed. A computer model was programmed in Matlab to perform harmonic analysis using data from a real residential system. Using this computer model a worst case study was performed, and the level of EV penetration in the system required to cause excessive harmonic distortion was obtained.

This dissertation developed novel microfabrication techniques of conductive polymer nanocomposite and utilized this material as a functional element for various physical sensor applications. Microstructures of nanocomposite were realized through novel microcontact printing and laser ablation assisted micropatterning processes. Prototype devices including large-strain strain sensor and highly-sensitive pressure sensor were demonstrated showing distinct advantages over existing technologies. The polymer nanocomposite used in this work comprised elastomer poly(dimexylsiloxane) (PDMS) as polymer matrix and multi-walled carbon nananotubes (MWCNTs) as a conductive nanofiller. To achieve uniform distribution of carbon nanotubes within the polymer, an optimized dispersion process was developed, featuring a strong organic solventchloroform, which dissolved PDMS base polymer easily and allowed monodispersion of MWCNTs. Following material preparation, three novel approaches were employed to pattern microstructures of polymer nanocomposite, each of which held respective advantages over previous fabrication techniques. For example, microcontact printing, by using a pre-defined stamp, directly transfers nanocomposite patterns from the ink reservoir to a substrate. Therefore, it eliminates the need of repeated photolithography process for every sample, saving time and cost. For another example, two variations of the laser assisted screen printing technique with micropatterns defined by the programmable laser ablation of a thin polymer film, allowed direct filling of nanocomposite and required only a CAD drawing for each design of sensor sample. Two variations of this fabrication protocol realized both fully embedded nanocomposite structures in a bulk polymer, as well as protruding relief-patterns of the nanocomposite on a polymer surface. The sensing capability of the polymer nanocomposite is attributed to the unique combination of mechanical flexibility and electrical piezoresistivity. To demonstrate feasibility for practical sensor applications, two sensor prototypes were constructed. The strain sensor, for example, showed significant resistive response while sample withheld large range tensile strain of over 45%. Also, the fabricated pressure sensor indicated high sensitivity of differential pressure. Each prototype showed distinctive advantages over conventional technologies. Complex hysteresis effects were observed and analyzed regarding the resistance and stress of the nanocomposite, which was followed by discussions of potential polymeric mechanisms.

In this work, we are computing the matching between 2D manifolds and 3D manifolds with temporal constraints, that is we are computing the matching among a time sequence of 2D/3D manifolds. It is solved by mapping all the manifolds to a common domain, then build their matching by composing the forward mapping and the inverse mapping. At first, we solve the matching problem between 2D manifolds with temporal constraints by using mesh-based registration method. We propose a surface parameterization method to compute the mapping between the 2D manifold and the common 2D planar domain. We can compute the matching among the time sequence of deforming geometry data through this common domain. Compared with previous work, our method is independent of the quality of mesh elements and more efficient for the time sequence data. Then we develop a global intensity-based registration method to solve the matching problem between 3D manifolds with temporal constraints. Our method is based on a 4D(3D+T) free-from B-spline deformation model which has both spatial and temporal smoothness. Compared with previous 4D image registration techniques, our method avoids some local minimum. Thus it can be solved faster and achieve better accuracy of landmark point predication. We demonstrate the efficiency of these works on the real applications. The first one is applied to the dynamic face registering and texture mapping. The second one is applied to lung tumor motion tracking in the medical image analysis. In our future work, we are developing more efficient mesh-based 4D registration method. It can be applied to tumor motion estimation and tracking, which can be used to calculate the read dose delivered to the lung and surrounding tissues. Thus this can support the online treatment of lung cancer radiotherapy.

In this dissertation, I explore new plasmonic structures and devices for manipulating light at the nanoscale: slow-light waveguides and compact couplers. I first introduce a plasmonic waveguide system, based on a plasmonic analogue of electromagnetically induced transparency (EIT), which supports a subwavelength slow-light mode, and exhibits a small group velocity dispersion. The system consists of a periodic array of two metal-dielectric-metal (MDM) stub resonators side-coupled to a MDM waveguide. Decreasing the frequency spacing between the two resonances increases the slowdown factor and decreases the bandwidth of the slow-light band. I also show that there is a trade-off between the slowdown factor and the propagation length of the slow-light mode. I next consider Mach-Zehnder interferometer (MZI) sensors in which the sensing arm consists of a slow-light waveguide based on a plasmonic analogue of EIT. I show that a MZI sensor using such a waveguide leads to approximately an order of magnitude enhancement in the refractive index sensitivity, and therefore in the minimum detectable refractive index change, compared to a MZI sensor using a conventional MDM waveguide. I also introduce compact wavelength-scale slit-based structures for coupling free space light into MDM subwavelength plasmonic waveguides. I first show that for a single slit structure the coupling efficiency is limited by a trade-off between the light power coupled into the slit, and the transmission of the slit-MDM waveguide junction. I next consider a two-section slit structure, and show that for such a structure the upper slit section enhances the coupling of the incident light into the lower slit section. The optimized two-section slit structure results in ¡­ 2.3 times enhancement of the coupling into the MDM plasmonic waveguide compared to the optimized single-slit structure. I finally consider a symmetric double-slit structure, and show that for such a structure the surface plasmons excited at the metal-air interfaces are partially coupled into the slits. Thus, the coupling of the incident light into the slits is greatly enhanced, and the optimized double-slit structure results in ¡­ 3.3 times coupling enhancement compared to the optimized single-slit structure. In all cases the coupler response is broadband.

Interest point detection is an important low-level image processing technique with a wide range of applications. The point detectors have to be robust under affine, scale and photometric changes. There are many scale and affine invariant point detectors but they are not robust to high illumination changes. Many affine invariant interest point detectors and region descriptors, work on the points detected using scale invariant operators. Since the performance of those detectors depends on the performance of the scale invariant detectors, it is important that the scale invariant initial stage detectors should have good robustness. It is therefore important to design a detector that is very robust to illumination because illumination changes are the most common. In this research the illumination problem has been taken as the main focus and have developed a scale invariant detector that has good robustness to illumination changes. In the paper [6] it has been proved that by using contrast stretching technique the performance of the Harris operator improved considerably for illumination variations. In this research the same contrast stretching function has been incorporated into two different scale invariant operators to make them illumination invariant. The performances of the algorithms are compared with the Harris-Laplace and Hessian-Laplace algorithms [15].