Broadband wireless access systems can be used to deliver a variety of high data rate applications and services. Many of the channels being considered for such applications exhibit multipath propagation coupled with large delay spreads. Cur- rently, orthogonal frequency division multiplexing is employed in these channels to compensate the effect of dispersion. Single carrier (SC) modulation in conjunc- tion with frequency-domain equalization (FDE) at the receiver has been shown to be a practical alternate solution as it has lower peak to average power ratio and is less sensitive to frequency offsets and phase noise compared to OFDM. The effect of multipath propagation increases with increasing data rate for SC systems. This leads to larger inter-symbol-interference (ISI) spans. In addition the achievable ca- pacity of SC-broadband systems depends on their ability to accommodate multiple signal transmissions in the same frequency band, which results in co-channel inter- ference (CCI) when detecting the desired data stream. The effects of CCI and ISI are more pronounced at high data rates. The objective of this research is to investi- gate and a develop low-complexity frequency domain receiver architectures capable of suppressing both CCI and ISI and employing practical channel estimation. In this thesis, a linear and a non-linear receiver architecture are developed in the frequency domain for use in highly dispersive channels employing multiple input multiple output (MIMO) antennas. The linear receiver consists of parallel branches each corresponding to a transmit data stream and implements linear equalization and demodulation. Frequency domain joint CCI mitigation and ISI equalization is implemented based on estimated channel parameters and is called space-frequency Broadband wireless access systems can be used to deliver a variety of high data rate applications and services. Many of the channels being considered for such applications exhibit multipath propagation coupled with large delay spreads. Cur- rently, orthogonal frequency division multiplexing is employed in these channels to compensate the effect of dispersion. Single carrier (SC) modulation in conjunc- tion with frequency-domain equalization (FDE) at the receiver has been shown to be a practical alternate solution as it has lower peak to average power ratio and is less sensitive to frequency offsets and phase noise compared to OFDM. The effect of multipath propagation increases with increasing data rate for SC systems. This leads to larger inter-symbol-interference (ISI) spans. In addition the achievable ca- pacity of SC-broadband systems depends on their ability to accommodate multiple signal transmissions in the same frequency band, which results in co-channel inter- ference (CCI) when detecting the desired data stream. The effects of CCI and ISI are more pronounced at high data rates. The objective of this research is to investi- gate and a develop low-complexity frequency domain receiver architectures capable of suppressing both CCI and ISI and employing practical channel estimation. In this thesis, a linear and a non-linear receiver architecture are developed in the frequency domain for use in highly dispersive channels employing multiple input multiple output (MIMO) antennas. The linear receiver consists of parallel branches each corresponding to a transmit data stream and implements linear equalization and demodulation. Frequency domain joint CCI mitigation and ISI equalization is implemented based on estimated channel parameters and is called space-frequency

Offshore floating wind turbine technology is growing rapidly and has the potential to become one of the main sources of affordable renewable energy. However, this technology is still immature owing in part to complications from the integrated design of wind turbines and floating platforms, aero-hydro-servo-elastic responses, grid integrations, and offshore wind resource assessments. This research focuses on developing methodologies to investigate the technical and economic feasibility of a wide range of floating offshore wind turbine support structures. To achieve this goal, interdisciplinary interactions among hydrodynamics, aerodynamics, structure and control subject to constraints on stresses/loads, displacements/rotations, and costs need to be considered. Therefore, a multidisciplinary design optimization approach for minimum levelized cost of energy executed using parameterization schemes for floating support structures as well as a frequency domain dynamic model for the entire coupled system. This approach was based on a tractable framework and models (i.e. not too computationally expensive) to explore the design space, but retaining required fidelity/accuracy. In this dissertation, a new frequency domain approach for a coupled wind turbine, floating platform, and mooring system was developed using a unique combination of the validated numerical tools FAST and WAMIT. Irregular wave and turbulent wind loads were incorporated using wave and wind power spectral densities, JONSWAP and Kaimal. The system submodels are coupled to yield a simple frequency domain model of the system with a flexible moored support structure. Although the model framework has the capability of incorporating tower and blade structural DOF, these components were considered as rigid bodies for further simplicity here. A collective blade pitch controller was also defined for the frequency domain dynamic model to increase the platform restoring moments. To validate the proposed framework, predicted wind turbine, floating platform and mooring system responses to the turbulent wind and irregular wave loads were compared with the FAST time domain model. By incorporating the design parameterization scheme and the frequency domain modeling the overall system responses of tension leg platforms, spar buoy platforms, and semisubmersibles to combined turbulent wind and irregular wave loads were determined. To calculate the system costs, a set of cost scaling tools for an offshore wind turbine was used to estimate the levelized cost of energy. Evaluation and comparison of different classes of floating platforms was performed using a Kriging-Bat optimization method to find the minimum levelized cost of energy of a 5 MW NREL offshore wind turbine across standard operational environmental conditions. To show the potential of the method, three baseline platforms including the OC3-Hywind spar buoy, the MIT/NREL TLP, and the OC4-DeepCwind semisubmersible were compared with the results of design optimization. Results for the tension leg and spar buoy case studies showed 5.2% and 3.1% decrease in the levelized cost of energy of the optimal design candidates in comparison to the MIT/NREL TLP and the OC3-Hywind respectively. Optimization results for the semisubmersible case study indicated that the levelized cost of energy decreased by 1.5% for the optimal design in comparison to the OC4-DeepCwind. / Graduate

Introduction Cerebral autoregulation (CA) refers to the physiological mechanisms in the brain to maintain constant blood flow despite changes in cerebral perfusion pressure (CPP). It plays an important protective role against the danger of ischaemia or oedema of the brain. Over the years, various methods for CA assessment have been proposed, while most commonly used parameters include the autoregulation index (ARI), which grades CA into ten levels; transfer function (TF) analysis, describing CA as a high pass filter; the mean flow index (Mx), that estimates CA through the correlation coefficient between slow waves of mean cerebral blood flow velocity (CBFV) and CPP; and pressure reactivity index (PRx), calculated as a moving correlation coefficient between mean arterial blood pressure (ABP) and intracranial pressure (ICP). However, until now, how these parameters are related with each other is still not clear. A comprehensive investigation of the relationship between all these parameters is therefore needed. In addition, the methods mentioned above mostly assume the system being analysed is linear and the signals are stationary, with the announcement of non-stationary characteristic of CA, a more robust method, in particular suitable for non-stationary signal analysis, needs to be explored. Objectives and Methods This thesis addresses three primary questions: 1. What are the relationships between currently widely used CA parameters, i.e. Mx, ARI, TF parameters, from theoretical and practical point of view? 2. It there an effective method that can be introduced to assess CA, which is suitable for analyses of non-stationary signals? 3. How can bedside monitoring of cerebral autoregulation be improved in traumatic brain injury patients? These general aims have been translated into a series of experiments, retrospective analyses and background studies that are presented in different chapters of this thesis. Results and Conclusions This PhD project carefully scrutinised currently used CA assessment methodologies in TBI patients, demonstrating significant relationships between ARI, Mx and TF phase. A new introduced wavelet-transform-based method, wPRx was validated and showed more stable result for CA assessment than the well-established parameter, PRx. A multi-window approach with weighting system for optimal CPP estimation was described. The result showed a significant improvement in the continuity and stability of CPPopt estimation, which made it possible to be applied in the future clinical management of TBI patients.

Fiber tapers have attracted much attention and have been successfully employed in various applications, ranging from resonators, filters, interferometers to sensors. This thesis studies the properties of fiber tapers for the purpose of making tapered-based devices and sensors in aerospace related application where small size and light weight are critical. This thesis includes theoretical derivation and experimental verifications of distributed mode coupling in tapered single-mode fibers (SMFs) with high-resolution optical frequency-domain reflectometry (OFDR) technique. The studies are realized with OFDR through phase detection of a Mach-Zehnder interferometer (MZI), which measures local refractive index change relative to the reference arm. The wavelength shifts converted by the phase change give the group index differences between the fundamental mode and higher-order modes of fiber tapers. The energy re-distribution is observed in Rayleigh backscatter amplitude as a function of fiber length with a ~13µm resolution over the entire fiber taper, and group index difference between core and cladding modes is measured with a spatial resolution of ~2cm by using autocorrelation data processing. The thermal and mechanical properties of fiber tapers have also been characterized with OFDR. The cross-correlation wavelength shift is related to the refractive index change of the modes. It is shown that residual stress induced by the tapering process results in the inhomogeneous thermal property, which can be significantly reduced by an annealing treatment. A fiber taper with a waist diameter of ~6µm has a force sensitivity of ~620.83nm/N, ~500 times higher than that of SMF. Furthermore, polarization-preserving character of tapered polarization-maintaining fibers (PMFs) is evaluated by OFDR-based distributed birefringence along tapered PMFs. Three tapered-based micro-fiber devices have been used as effective mode selecting components to build narrow-linewidth tunable Erbium-doped fiber ring lasers. The fabrication is easy and at a low cost. 1) a tapered fiber tip forms multimode interference mechanism; 2) a two-taper MZI has been demonstrated by splitting/combining the fundamental mode and higher-order modes through fiber tapers and is tuned by bending one taper waist; 3) a novel tunable fiber Fabry-Perot filter, consisting of a hollow-core photonic bandgap fiber and a micro-fiber, is employed in the reflection mode.

We test the controversial ideas about the role of corridors in fragmented animal habitats. Using simulation studies we analyze how fragmentation affects a simple prey-predator system and how the introduction of openings that connect the habitats changes the situation. Our individual based model consists of 3 levels: renewable prey food, as well as prey and predators that both have a simple economy. We find, in line with intuition, that the fragmentation of a habitat has a strong negative effect especially on the predator population. Connecting the fragmented habitats facilitates predator (and hence prey) survival, but also leads to an important counterintuitive effect: in the presence of a high quality predator, connected fragmented systems fare better in terms of coexistence than do unfragmented systems. Using a frequency domain analysis we explain how corridors between sub-habitats serve as "wave breakers" in the population flow, thus preventing deadly density waves to occur.

Synthetic X-ray or digitally reconstructed radiographs (DRRs) are simulated X-ray images projected from computed tomography (CT) data that are commonly used for CT and real X-Ray image registration. High-quality synthetic X-ray images can facilitate various applications such as guiding images for virtual reality (VR) simulation and training data for deep learning methods such as creating CT data from X-Ray images. It is challenging to generate high-quality synthetic X-ray images from CT slices, especially in various view angles, due to gaps between CT slices, high computational cost, and the complexity of algorithms. Most synthetic X-ray generation methods use fast ray-tracing in a situation where the image quality demand is low. We aim to improve image quality while maintaining good accuracy and use two steps; 1) to generate synthetic X-ray images from CT data and 2) to increase the resolution of the synthetic X-ray images. Our synthetic X-ray image generation method adopts a matrix-based projection method and dynamic multi-segment lookup tables, which shows better image quality and efficiency compared to conventional synthetic X-ray image generation methods. Our method is tested in a real-time VR training system for image-guided intervention procedures. Then we proposed two novel approaches to raise the quality of synthetic X-ray images through deep learning methods. We use a reference-based super-resolution (RefSR) method as a base model to upsampling low-resolution images into higher resolution. Even though RefSR can produce fine details by utilizing the reference image, it inevitably generates some artifacts and noise. We propose texture transformer super-resolution with frequency domain (TTSR-FD) which introduces frequency domain loss as a constraint to improve the quality of the RefSR results with fine details and without apparent artifacts. To the best of our knowledge, this is the first work that utilizes frequency domain as a part of loss functions in the field of super-resolution (SR). We observe improved performance in evaluating TTSR-FD when tested on our synthetic X-ray and real X-ray image datasets. A typical SR network is trained with paired high-resolution (HR) and low-resolution (LR) images, where LR images are created by downsampling HR images using a specific kernel. The same downsampling kernel is also used to create test LR images from HR images. As a result, most SR methods only perform well when the testing image is acquired using the same downsampling kernel used during the training process. We also propose TTSR-DMK, which uses multiple downsampling kernels during training to generalize the model and adopt a dual model that trains together with the main model. The dual model can form a closed-loop with the main model to learn the inverse mapping, which further improves the model’s performance. Our method works well for testing images produced by multiple kernels used during training. It can also help improve the model performance when testing images are acquired with kernels not used during training. To the best of our knowledge, we are the first to use the closed-loop method in RefSR. We have achieved: (i) synthetic X-ray image generation from CT data, which is based on a matrix-based projection and lookup tables ; (ii) TTSR-FD: synthetic X-ray image super-resolution using a novel frequency domain loss ; (iii) TTSR-DMK: an adaptation network to overcome the performance drop for testing data which do not match to downsampling kernels used in training. Our TTSR-FD results show improvements (PSNR from 37.953 to 39. 009) compared to the state-of-the-art methods TTSR. Our experiment with real X-Ray images using TTSR-FD can remove visible artifacts in the qualitative study even though PSNR is similar. Our proposed adaptation network, TTSR-DMK, improved model performance for multiple kernels even with unknown kernel situations.

Silicon photonics has witnessed rapid development in recent years for its fabrication compatibility with the cost-effective CMOS technology. The advancement of relevant simulation tools, however, is at a relatively slow pace. The high index contrast of the usual silicon waveguide that has imposed new challenges to the convergence and accuracy of the solution technique, the growing intricacy in solitary component design, and the increased complexity of their integration, are the impelling factors that motivate us to improve the computer-aided design, modeling, simulation, and optimization methods. The theme of the thesis is on the frequency domain simulation methods supported by the complex mode theory. The complex mode theory is introduced to the simulation domain truncated by the perfectly matching layers (PMLs) enclosed in the perfectly reflected boundaries (PRBs), wherein the discrete complex modes as eigen solutions can represent the continuous radiation fields, thus yields a unified approach for handling both guided (discrete) and radiation (continuous) waves. In this thesis, theoretical investigations have been conducted along a few different lines aiming at improving the efficiency and accuracy in complex mode expansion. Properties of high-order complex Berenger modes are firstly addressed through asymptotic solutions, and it is found that as the mode order increases, the symmetry of the cladding and substrate in the simulation domain, instead of the guiding schemes, plays a more and more decisive role regarding mode classification and modal field distribution. A weighed optical path method is then proposed to unify the high-order Berenger modes, and to enhance the symmetry of high order modes’ field distributions in the asymmetric structures, leading to the improvement in convergence speed and stability in the mode expansion. Next, an improved mode-matching method (MMM) is proposed based on an error-minimizing method instead of the conventional approach relying on the unreliable modal orthogonal property. The newly proposed method is significantly more robust as numerical errors usually jeopardize the modal orthogonality. This claim is exemplified by simulation results on silicon channel waveguide facet, bending waveguide, and silicon-germanium photo-detector waveguide. As a direct application of the improved complex mode theory, a hybrid plasmonic-photonic nano-ribbon waveguide is proposed, standing as a combination of the silicon slot and surface plasmon polariton (SPP) waveguides, is proposed and analyzed. We have found that the fundamental mode is featured at low loss as in optical waveguide as well as high confinement as in plasmonic structure. Simulations have shown that millimeter range propagation can be sustained with strong confinement. We have further studied such waveguide with an extra layer of phase changing material incorporated, attempting to realize the efficient electro-optical phase and/or loss modulation. Finally, an optical switch design is proposed by taking the full advantage of the aforementioned structure. / Thesis / Doctor of Philosophy (PhD)

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