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Title: REACTIVE ION ENHANCED MAGNETRON SPUTTERING OF NITRIDE THIN FILMS
Creator: Talukder, Al-Ahsan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Magnetron sputtering is a popular vacuum plasma coating technique used for depositing metals, dielectrics, semiconductors, alloys, and compounds onto a wide range of substrates. In this work, we present two popular types of magnetron sputtering, i.e., pulsed DC and RF magnetron sputtering, for depositing piezoelectric aluminum nitride (AlN) thin films with high Young’s modulus. The effects of important process parameters on the plasma I-V characteristics, deposition rate, and the properties...
Show moreMagnetron sputtering is a popular vacuum plasma coating technique used for depositing metals, dielectrics, semiconductors, alloys, and compounds onto a wide range of substrates. In this work, we present two popular types of magnetron sputtering, i.e., pulsed DC and RF magnetron sputtering, for depositing piezoelectric aluminum nitride (AlN) thin films with high Young’s modulus. The effects of important process parameters on the plasma I-V characteristics, deposition rate, and the properties of the deposited AlN films, are studied comprehensively. The effects of these process parameters on Young’s modulus of the deposited films are also presented. Scanning electron microscope imaging revealed a c-axis oriented columnar growth of AlN. Performance of surface acoustic devices, utilizing the AlN films deposited by magnetron sputtering, are also presented, which confirms the differences in qualities and microstructures of the pulsed DC and RF sputtered films. The RF sputtered AlN films showed a denser microstructure with smaller grains and a smoother surface than the pulsed DC sputtered films. However, the deposition rate of RF sputtering is about half of the pulsed DC sputtering process. We also present a novel ion source enhanced pulsed DC magnetron sputtering for depositing high-quality nitrogen-doped zinc telluride (ZnTe:N) thin films. This ion source enhanced magnetron sputtering provides an increased deposition rate, efficient N-doping, and improved electrical, structural, and optical properties than the traditional magnetron sputtering. Ion source enhanced deposition leads to ZnTe:N films with smaller lattice spacing and wider X-ray diffraction peak, which indicates denser films with smaller crystallites embedded in an amorphous matrix.
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Title: Metamodeling in Evolutionary Multi-Objective Optimization for constrained and unconstrained Problems
Creator: Hussein, Rayan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: One of the main difficulties in applying an optimization algorithm to a practical problem is that the evaluation of objectives and constraints often involve computationally expensive procedures. To handle such problems, a metamodel (or surrogate model, or response surface approximations) is first formed from a few exact (high-fidelity) solution evaluations, and then optimized by an algorithm in a progressive manner. However, there has been lukewarm interest in finding multiple trade-off...
Show moreOne of the main difficulties in applying an optimization algorithm to a practical problem is that the evaluation of objectives and constraints often involve computationally expensive procedures. To handle such problems, a metamodel (or surrogate model, or response surface approximations) is first formed from a few exact (high-fidelity) solution evaluations, and then optimized by an algorithm in a progressive manner. However, there has been lukewarm interest in finding multiple trade-off solutions for multi-objective optimization problems using surrogate models. The literature on surrogate modeling for constrained optimization problems is also rare. The difficulty lies in the requirement ofbuilding and solving multiple surrogate models, one for each Pareto-optimal solution. In this study, we propose a taxonomy of different possible metamodeling frameworks for multi-objective optimization and provide a comparative study by discussing advantages and disadvantages of each framework. Also, we argue that it is more efficient to use different metamodeling frameworks at different stages of the optimization process. Thereafter, we propose a novel adaptive method for switching among different metamodeling frameworks. Moreover, we observe the convergence behavior of the proposed approaches is better with a trust regions method applied within the metamodeling frameworks. The results presented in this study are obtained using the well-known Kriging metamodeling approach. Based on our extensive simulation studies on proposed frameworks, we report new and interesting observations about the behavior of each metamodeling framework, which may provide salient guidelines for further studies in this emerging area within evolutionary multi-objective optimization. Results of this study clearly show the efficacy and efficiency of the proposed adaptive switching approach compared to three recently-proposed other metamodeling algorithms on challenging multi-objective optimization problems using a limited budget of high-fidelity evaluations.
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Title: Novel Depth Representations for Depth Completion with Application in 3D Object Detection
Creator: Imran, Saif Muhammad
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Depth completion refers to interpolating a dense, regular depth grid from sparse and irregularly sampled depth values, often guided by high-resolution color imagery. The primary goal of depth completion is to estimate depth. In practice methods are trained by minimizing an error between predicted dense depth and ground-truth depth, and are evaluated by how well they minimize this error. Here we identify a second goal which is to avoid smearing depth across depth discontinuities. This second...
Show moreDepth completion refers to interpolating a dense, regular depth grid from sparse and irregularly sampled depth values, often guided by high-resolution color imagery. The primary goal of depth completion is to estimate depth. In practice methods are trained by minimizing an error between predicted dense depth and ground-truth depth, and are evaluated by how well they minimize this error. Here we identify a second goal which is to avoid smearing depth across depth discontinuities. This second goal is important because it can improve downstream applications of depth completion such as object detection and pose estimation. However, we also show that the goal of minimizing error can conflict with the goal of eliminating depth smearing.In this thesis, we propose two novel representations of depths that can encode depth discontinuity across object surfaces by allowing multiple depth estimation in the spatial domain. In order to learn these new representations, we propose carefully designed loss functions and show their effectiveness in deep neural network learning. We show how our representations can avoid inter-object depth mixing and also beat state of the art metrics for depth completion. The quality of ground-truth depth in real-world depth completion problems is another key challenge for learning and accurate evaluation of methods. Ground truth depth created from semi-automatic methods suffers from sparse sampling and errors at object boundaries. We show that the combination of these errors and the commonly used evaluation measure has promoted solutions that mix depths across boundaries in current methods. The thesis proposes alternate depth completion performance measures that reduce preference for mixed depths and promote sharp boundaries.The thesis also investigates whether additional points from depth completion methods can help in a challenging and high-level perception problem; 3D object detection. It shows the effect of different depth noises originated from depth estimates on detection performances and proposes some effective ways to reduce noise in the estimate and overcome architecture limitations. The method is demonstrated on both real-world and synthetic datasets.
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Title: TENSOR LEARNING WITH STRUCTURE, GEOMETRY AND MULTI-MODALITY
Creator: Sofuoglu, Seyyid Emre
Date: 2022
Collection: Electronic Theses & Dissertations
Description: With the advances in sensing and data acquisition technology, it is now possible to collect datafrom different modalities and sources simultaneously. Most of these data are multi-dimensional in nature and can be represented by multiway arrays known as tensors. For instance, a color image is a third-order tensor defined by two indices for spatial variables and one index for color mode. Some other examples include color video, medical imaging such as EEG and fMRI, spatiotemporal data...
Show moreWith the advances in sensing and data acquisition technology, it is now possible to collect datafrom different modalities and sources simultaneously. Most of these data are multi-dimensional in nature and can be represented by multiway arrays known as tensors. For instance, a color image is a third-order tensor defined by two indices for spatial variables and one index for color mode. Some other examples include color video, medical imaging such as EEG and fMRI, spatiotemporal data encountered in urban traffic monitoring, etc.In the past two decades, tensors have become ubiquitous in signal processing, statistics andcomputer science. Traditional unsupervised and supervised learning methods developed for one- dimensional signals do not translate well to higher order data structures as they get computationally prohibitive with increasing dimensionalities. Vectorizing high dimensional inputs creates problems in nearly all machine learning tasks due to exponentially increasing dimensionality, distortion of data structure and the difficulty of obtaining sufficiently large training sample size.In this thesis, we develop tensor-based approaches to various machine learning tasks. Existingtensor based unsupervised and supervised learning algorithms extend many well-known algorithms, e.g. 2-D component analysis, support vector machines and linear discriminant analysis, with better performance and lower computational and memory costs. Most of these methods rely on Tucker decomposition which has exponential storage complexity requirements; CANDECOMP-PARAFAC (CP) based methods which might not have a solution; or Tensor Train (TT) based solutions which suffer from exponentially increasing ranks. Many tensor based methods have quadratic (w.r.t the size of data), or higher computational complexity, and similarly, high memory complexity. Moreover, existing tensor based methods are not always designed with the particular structure of the data in mind. Many of the existing methods use purely algebraic measures as their objective which might not capture the local relations within data. Thus, there is a necessity to develop new models with better computational and memory efficiency, with the particular structure of the data and problem in mind. Finally, as tensors represent the data with more faithfulness to the original structure compared to the vectorization, they also allow coupling of heterogeneous data sources where the underlying physical relationship is known. Still, most of the current work on coupled tensor decompositions does not explore supervised problems.In order to address the issues around computational and storage complexity of tensor basedmachine learning, in Chapter 2, we propose a new tensor train decomposition structure, which is a hybrid between Tucker and Tensor Train decompositions. The proposed structure is used to imple- ment Tensor Train based supervised and unsupervised learning frameworks: linear discriminant analysis (LDA) and graph regularized subspace learning. The algorithm is designed to solve ex- tremal eigenvalue-eigenvector pair computation problems, which can be generalized to many other methods. The supervised framework, Tensor Train Discriminant Analysis (TTDA), is evaluated in a classification task with varying storage complexities with respect to classification accuracy and training time on four different datasets. The unsupervised approach, Graph Regularized TT, is evaluated on a clustering task with respect to clustering quality and training time on various storage complexities. Both frameworks are compared to discriminant analysis algorithms with similar objectives based on Tucker and TT decompositions.In Chapter 3, we present an unsupervised anomaly detection algorithm for spatiotemporaltensor data. The algorithm models the anomaly detection problem as a low-rank plus sparse tensor decomposition problem, where the normal activity is assumed to be low-rank and the anomalies are assumed to be sparse and temporally continuous. We present an extension of this algorithm, where we utilize a graph regularization term in our objective function to preserve the underlying geometry of the original data. Finally, we propose a computationally efficient implementation of this framework by approximating the nuclear norm using graph total variation minimization. The proposed approach is evaluated for both simulated data with varying levels of anomaly strength, length and number of missing entries in the observed tensor as well as urban traffic data. In Chapter 4, we propose a geometric tensor learning framework using product graph structures for tensor completion problem. Instead of purely algebraic measures such as rank, we use graph smoothness constraints that utilize geometric or topological relations within data. We prove the equivalence of a Cartesian graph structure to TT-based graph structure under some conditions. We show empirically, that introducing such relaxations due to the conditions do not deteriorate the recovery performance. We also outline a fully geometric learning method on product graphs for data completion.In Chapter 5, we introduce a supervised learning method for heterogeneous data sources suchas simultaneous EEG and fMRI. The proposed two-stage method first extracts features taking the coupling across modalities into account and then introduces kernelized support tensor machines for classification. We illustrate the advantages of the proposed method on simulated and real classification tasks with small number of training data with high dimensionality.
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Title: Advancing Field Emission Technology for High Power Injectors Operating in GHz and Beyond
Creator: Schneider, Mitchell E.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: As the next generation of electron injectors pushes to achieve higher gradient fields than ever before (>300 MV/m), they are driven to operate at higher frequencies (C-band through W-band). This shrinks the fabrication dimensions of these cavities, making field emission cathodes (FECs) an electron source of choice. Photoemission and thermionic sources are increasingly less suited as the complex laser transport schemes and heating source powering these injectors cannot provide the necessary...
Show moreAs the next generation of electron injectors pushes to achieve higher gradient fields than ever before (>300 MV/m), they are driven to operate at higher frequencies (C-band through W-band). This shrinks the fabrication dimensions of these cavities, making field emission cathodes (FECs) an electron source of choice. Photoemission and thermionic sources are increasingly less suited as the complex laser transport schemes and heating source powering these injectors cannot provide the necessary beam quality and may cause damage to the cathode or the injector itself. Carbon-based FECs have dominated the field emission sources R&D portfolio at DOD and DOE for the past 30 years across various high-power vacuum electronic device activities. Compared to traditional metal cathode technology, carbon-based technology cathodes are able to produce higher charge at low electric fields. Small intrinsic electron momentum and simple fabrication means these can become a leading technology, e.g., in the case of carbon nanotubes, nanoscale emitters make them attractive for producing high brightness beams. Specifically, diamond-based cathodes can handle extreme temperature and mechanical stresses that can occur under high gradient conditions.Most promising is a unique form of diamond, ultra-nano-crystalline diamond (UNCD) due to its material and electrical properties, which include being the most conductive form of diamond due to having the largest amount of grain boundaries. This cathode material allows us to explore new frontiers of cathode physics research, revealing a new field emission mechanism that diverges from classical Fowler Nordheim, termed space charge dominated Fowler Nordheim. This form of Fowler Nordheim is space charge dominated but can surpass the 1D Child Langmuir limit and approaches the 2D limit. This is not space charge limited Fowler Nordheim. This ability to decouple the extracted current from the space charge effects allows for the production of extremely xiii bright beams. This can be achieved by expanding the current cathode testing facilities beyond L band into C band so as to access these high fields and explore the temporal dynamics of a field emission source. This will yield the new physics knowledge needed to construct the world’s first custom-built injector specifically designed for field emission sources. Furthermore, exploring other forms of diamond cathode such as Diamond Field Emitter Arrays (DFEA) yields insight into the applications of transversely shaped beams for advanced accelerator applications such as emittance exchange beam lines. DFEA’s allow for the exploration of additional materials effects on the cathode performance such as the ballast resistance. This ultimately allows the derivation of a comprehensive concept map for the field emission dynamic regimes needed for the design of RF injectors. Previously, the theoretical assumption was that everything operated under classical Fowler Nordheim without any additional contributions from other materials properties or beam effects.
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Title: Multi-Modality Nondestructive Evaluation Techniques for Inspection of Plastic and Composite Pipeline Networks
Creator: Alzuhiri, Mohand
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The extensive adoption of plastic pipelines is a growing phenomenon in different fields of the industry, with applications that extend from municipal water and sewer systems to the water lines in nuclear reactors. The large-scale adoption is motivated by the unique features of plastics like corrosion and chemical resistance, low cost, and design flexibility. While the dielectric nature of plastic pipelines provides unique design capabilities, it also introduces new challenges for the...
Show moreThe extensive adoption of plastic pipelines is a growing phenomenon in different fields of the industry, with applications that extend from municipal water and sewer systems to the water lines in nuclear reactors. The large-scale adoption is motivated by the unique features of plastics like corrosion and chemical resistance, low cost, and design flexibility. While the dielectric nature of plastic pipelines provides unique design capabilities, it also introduces new challenges for the operators when it comes to inspecting and ensuring the integrity of these pipelines’ networks. In this study, a multi-modal approach is adopted to address the threats affecting the safety of small diameter plastic pipelines and explore possible inspection solutions for emerging materials like composites. Structured light endoscopes with RGB-D inspection capability were developed for the inspection of surface defects in small diameter pipelines with novelties a) Design and miniaturization of RGB-D structured light sensor with electronic stabilization, b) Development of an algorithm to automatically calibrate the sensor when placed in a cylindrical environment, c) Design of a single shot phase measurement SL sensor that employs the sensor movement to improve the 3D reconstruction, and d) Design a stereoscopic SL sensor for 360-degree inspection. EM-based inspection was adopted to inspect subsurface defects and classify materials around the inspected pipelines. An investigative study was performed to test the probability of detecting cold fusion in butt fusion joints by using emerging NDE techniques, and a coplanar capacitive sensor was designed for the detection of legacy crossbores in gas pipelines. Finally, a thermoacoustic imaging system was developed in this study with potential applications for the inspection of composites and medical imaging. The novelties of this work can be summarized as follows: a) Development of a simulation model to study the thermoacoustic waves generation and the effect of multiple experimental parameters on the performance of thermoacoustic imaging systems, b) Improving the signal to noise ratio of pulsed TAI imaging systems by adoption non-coherent pulse compression. In summary, this study presents a multi-modal approach for the inspection of pipeline networks by adopting optical RGB-D imaging sensors for surface inspection, EM-based sensors for subsurface inspection and classification of objects outside the pipe, and finally, a hybrid imaging method with potential applications in medical imaging and inspection of composites.
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Title: Wireless Phase and Frequency Synchronization for Distributed Phased Arrays
Creator: Mghabghab, Serge R.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Distributed microwave wireless systems have the potential to dramatically reshape wireless technologies due to their ability to provide improvements in robustness, transmit power, antenna gain, spatial and temporal resolutions, size, scalability, secrecy, flexibility, and cost compared to single-platform wireless systems. Traditional wireless systems use a platform-centric model, where improving capabilities generally necessitates hardware retrofitting, which in many cases can result in a...
Show moreDistributed microwave wireless systems have the potential to dramatically reshape wireless technologies due to their ability to provide improvements in robustness, transmit power, antenna gain, spatial and temporal resolutions, size, scalability, secrecy, flexibility, and cost compared to single-platform wireless systems. Traditional wireless systems use a platform-centric model, where improving capabilities generally necessitates hardware retrofitting, which in many cases can result in a bulky, expensive, and inefficient system. Nevertheless, distributed microwave wireless systems require precise coordination to enable cooperative operation. The most highly synchronized systems coordinate at the wavelength level, supporting coherent distributed operations like beamforming. The electric states that need to be synchronized in coherent distributed arrays are mainly the phase, frequency, and time; the synchronization can be accomplished using multiple architectures. All coordination architectures can be grouped under two categories: open loop and closed loop. While closed-loop systems use feedback from the destination, open-loop coherent distributed arrays must synchronize their electrical states by only relying on synchronization signals stemming from within the array rather than depending on feedback signals from the target. Although harder to implement, open-loop coherent arrays enable sensing and other delicate communications applications, where feedback from the target is not possible.In this thesis, I focus on phase alignment and frequency synchronization for open-loop coherent distributed antenna arrays. Once the phase and frequency of all the nodes in the array are synchronized, it is possible to coherently beamform continuous wave signals. When information is modulated on the transmitted continuous waves, time alignment between the nodes is needed. However, time alignment is generally less stringent to implement since its requirements are dependent on the information rate rather than the beamforming frequency, such as for phase and frequency synchronization. Beamforming at 1.5 GHz is demonstrated in this thesis using a two-node open-loop distributed array. For the presented architecture, the phases of the transmitting nodes are aligned using synchronization signals incoming from within the array, without any feedback from the destination. A centralized phase alignment approach is demonstrated, where the secondary node(s) minimize their relative phase offsets to that of the primary node by locating the primary node and estimating the phase shift imparted by the relative motion of the nodes. A high accuracy two-tone waveform is used to track the primary node using a cooperative approach. This waveform is tested with an adaptive architecture to overcome the performance degradation due to weather conditions and to allow high ranging accuracy with minimal spectral footprint. Wireless frequency synchronization is implemented using a centralized approach that allows phase tracking, such that the frequencies of the secondary nodes are locked to that of the primary node. Once the phase and frequency of all the nodes are synchronized, it is possible to coherently beamform in the far field as long as the synchronization is achieved with the desired accuracy. I evaluate the required localization accuracies and frequency synchronization intervals. More importantly, I demonstrate experimentally the first two-node open-loop distributed beamforming at 1.5 GHz with multiple scenarios where the nodes are in relative motion, showing the ability to coherently beamform in a dynamic array where no feedback from the destination is needed.
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Title: Design and Analysis of Sculpted Rotor Interior Permanent Magnet Machines
Creator: Hayslett, Steven Lee
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Design of interior permanent magnet electrical machines is complex. Interior permanent magnet machines offer a good balance of cost, efficiency, and torque/power density. Maximum torque and power production of an interior permanent magnet machine is achieved through balancing design choices related to the permanent magnet and salient features. The embedded magnet within the salient structure of the rotor lamination results in an increase in harmonic content. In addition, interaction of the...
Show moreDesign of interior permanent magnet electrical machines is complex. Interior permanent magnet machines offer a good balance of cost, efficiency, and torque/power density. Maximum torque and power production of an interior permanent magnet machine is achieved through balancing design choices related to the permanent magnet and salient features. The embedded magnet within the salient structure of the rotor lamination results in an increase in harmonic content. In addition, interaction of the armature, control angle, and rotor reluctance structure creates additional harmonic content. These harmonics result in increased torque ripple, radial forces, losses, and other unwanted phenomena. Further improvements in torque and power density, and techniques to minimize harmonics, are necessary. Typical interior permanent magnet machine design results at the maximum torque per amp condition are at neither the maximum magnet nor maximum salient torque, but at the best combination of the two. The use of rotor surface features to align the magnet and the reluctance axis allows for improvement of torque and power density. Reduction of flux and torque harmonics is also possible through careful design of rotor sculpt features that are included at or near the surface of the rotor. Finite element models provide high fidelity and accurate results to machine performance but do not give insight into the relationship between design parameters and performance. Winding factor models describe the machine with a set of Fourier series equations, providing access to the harmonic information of both parameters and performance. Direct knowledge of this information provides better insight, a clear understanding of interactions, and the ability to develop a more efficient design process. A new analytical winding function model of the single-V IPM machine is introduced, which considers the sculpted rotor and how this model can be used in the design approach of machines.Rotor feature trends are established and utilized to increase design intuition and reduce dependency upon the lengthy design of experiment optimization processes. The shape and placement of the rotor features, derived from the optimization process, show the improvement in torque average and torque ripple of the IPM machine.
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Title: DOWNLINK RESOURCE BLOCKS POSITIONING AND SCHEDULING IN LTE SYSTEMS EMPLOYING ADAPTIVE FRAMEWORKS
Creator: Abusaid, Osama M.
Date: 2018
Collection: Electronic Theses & Dissertations
Description: The present expansions in size and complexity of LTE networks is hindering their performance and their reliability. This hindrance is manifested in deteriorating performance in the User Equipment’s throughput and latency as a consequence to deteriorating the E-node B downlink throughput. This is leading to the need of smart E Node Base with various capabilities adapting to the changing communication environment. The proposed work aims at developing Self Organization (SO) techniques and...
Show moreThe present expansions in size and complexity of LTE networks is hindering their performance and their reliability. This hindrance is manifested in deteriorating performance in the User Equipment’s throughput and latency as a consequence to deteriorating the E-node B downlink throughput. This is leading to the need of smart E Node Base with various capabilities adapting to the changing communication environment. The proposed work aims at developing Self Organization (SO) techniques and frameworks for LTE networks at the Resource Blocks (RB) scheduling management level. After reviewing the existing literature on Self Organization techniques and scheduling strategies that have been recently implemented in other wireless networks, we identify several contrasting needs that can jointly be addressed. The deployment of the introduced algorithms in the communication network is expected to lead to improved and upgraded overall network performance. The main feature of the LTE networks family is the feed-back that the cell receives from the users. The feedback includes the down link channel assessment based on the User Equipment (UE) measure Channel Quality Indicator (CQI) in the last Transmission Time Interval (TTI). This feed-back should be the main decision factor in allocating Resource Blocks (RBs) among users. The challenge is how could one maps the users’ data onto the RBs based on the CQI. The Thesis advances two approaches towards that end:- the allocation among the current users for the next TTI should be mapped, consistent with historical feed-back CQI received from users over prior transmission durations. This approach also aims at offering a solution to the bottle-neck capacity issue in the scheduling of LTE networks. To that end, we present an implementation of a modified Self Organizing Map (SOM) algorithm for mapping incoming data into RBs. Such an implementation can handle the collective cell enabling our cell to become smarter. The criteria in measuring the E-node Base performance include throughput, fairness and the trade-off between these attributes.- Another promising and complementary approach is to tailor Recurrent Neural Networks (RNNs) to implement optimal dynamic mappings of the Resource Blocks (RBs) in response to the history sequence of the Channel Quality Indicator CQI feedback. RNNs can successfully build its own internal state over the entire training CQI sequence and consequently make the prediction more viable. With this dynamic mapping technique, the prediction will be more accurate to changing time-varying channel environments. Overall, the collective cell management would become more intelligent and would be adaptable to changing environments. Consequently, a significant performance improvement can be achieved at lower cost. Moreover, a general tunability of the scheduling system becomes possible which would incorporate a trade-off between system complexity and QoS.
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Title: AUTOMATED PET/CT REGISTRATION FOR ACCURATE RECONSTRUCTION OF PET IMAGES
Creator: Khurshid, Khawar
Date: 2018
Collection: Electronic Theses & Dissertations
Description: The use of a CT attenuation correction (CTAC) map for the reconstruction of PET image can introduce attenuation artifacts due to the potential misregistration between the PET and CT data. This misregistration is mainly caused by patient motion and physiological movement of organs during the acquisition of the PET and CT scans. In cardiac exams, the motion of the patient may not be significant but the diaphragm movement during the respiratory cycle can displace the heart by up to 2 cm along...
Show moreThe use of a CT attenuation correction (CTAC) map for the reconstruction of PET image can introduce attenuation artifacts due to the potential misregistration between the PET and CT data. This misregistration is mainly caused by patient motion and physiological movement of organs during the acquisition of the PET and CT scans. In cardiac exams, the motion of the patient may not be significant but the diaphragm movement during the respiratory cycle can displace the heart by up to 2 cm along the long axis of the body. This shift can project the PET heart onto the lungs in the CT image, thereby producing an underestimated value for the attenuation. In brain studies, patients undergoing a PET scan are often not able to follow instructions to keep their head in a still position, resulting in misregistered PET and CT image datasets. The head movement is quite significant in many cases despite the use of head restraints. This misaligns the PET and CT data, thus creating an erroneous CT attenuation correction map. In such cases, bone or air attenuation coefficients may be projected onto the brain which causes an overestimation or an underestimation of the resulting CTAC values. To avoid misregistration artifacts and potential diagnostic misinterpretation, automated software for PET/CT registration has been developed that works for both cardiac and brain datasets. This software segments the PET and CT data, extracts the brain or the heart surface information from both datasets, and compensates for the translational and rotational misalignment between the two scans. The PET data are reconstructed using the aligned CTAC, and the results are analyzed and compared with the original dataset. This procedure has been evaluated on 100 cardiac and brain PET/CT data sets, and the results show that the artifacts due to the misregistration between the two modalities are eliminated after the PET and CT images are aligned.
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Title: 3d-printed lightweight wearable microsystems with highly conductive interconnects
Creator: Alforidi, Ahmad Fudy
Date: 2019
Collection: Electronic Theses & Dissertations
Description: There is great demand for mass production of electronics in wide range of applications including, but not limited to, ubiquitous and lightweight wearable devices for the development of smart homes and health monitoring systems. The advancement of additive manufacturing in electronics industry and academia shows a potential replacement of conventional electronics fabrication methods. However, conductivity is the most difficult issue towards the implementation of highperformance 3D-printed...
Show moreThere is great demand for mass production of electronics in wide range of applications including, but not limited to, ubiquitous and lightweight wearable devices for the development of smart homes and health monitoring systems. The advancement of additive manufacturing in electronics industry and academia shows a potential replacement of conventional electronics fabrication methods. However, conductivity is the most difficult issue towards the implementation of highperformance 3D-printed microsystems. As most of 3D printing electronics utilizes ink-based conductive material for electrical connection, it requires high curing temperature for achieving low resistivity (150 °C for obtaining nearly 2.069 x 10-6 .m in copper connects), which is not suitable for most of 3D printing filaments. Thisseriously limits the availability of many lightweight 3D printable materials in microsystem applications because these materials usually have relatively low glass-transition temperatures (< 120 °C). Considering that pristine copper films thicker than 49 nm can offer a very low bulk resistivity of 1.67 x 10-8 .m, a new 3D-printing-compatible connection fabrication approach capable of depositing pristine copper structures with no need of curing processes is highly desirable. Therefore, a new technology with the ability to manufacture 3D-printed structures with high performance electronics is necessary.In this dissertation, novel 3D-printed metallization processes for multilayer microsystems made of lightweight material on planar and non-planar surfaces are presented. The incorporation of metal interconnects in the process is accomplished through evaporating, sputtering and electroplating techniques. This approach involves the following critical processes with unique features: a) patterning of metal interconnects using self-aligned 3D-printed shadow masks, b) fabrication of the temporary connections between isolated metal segments by 3D printing followed with metallization, which host the subsequent electroplating process, and c) fabrication of vertical interconnect access (VIA) features by 3D printing followed with metallization, which enable electrical connections between multilayers of the Microsystem for miniaturization.The presented technique offers approximate bulk resistivity with no curing temperature needed after deposition. Since the ultimate goal is developing lightweight wearable microsystem, this approach demonstrated for two layers and can easily extended for multilayer microsystems enabling realization and miniaturization of complex systems. In addition, the variety of filaments used in 3Dprinters provide opportunities to study implementation of these processes in many electronics fields including flexible electronics. Therefore, the integration of physical vapor deposition systems with 3D printing machines is very promising for the future industry of 3D-printed microsystems.
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Title: A comparison between PMSM rotor designs suitable for using ferrite magnets
Creator: Montalvo-Ortiz, Eduardo E.
Date: 2013
Collection: Electronic Theses & Dissertations
Description: Increasing concerns over costs and supply of rare earth magnets have introduced more attention to Permanent Magnet Synchronous Machine (PMSM) designs that can work with ferrite magnets. Ferrite magnets have a major disadvantage in that they don't produce as much flux density as rare earth magnets do, which leads to lower torque density and thus less power in PMSMs. Several approaches have been taken in design of PMSMs in order to tackle this problem. Two of these designs are presented and...
Show moreIncreasing concerns over costs and supply of rare earth magnets have introduced more attention to Permanent Magnet Synchronous Machine (PMSM) designs that can work with ferrite magnets. Ferrite magnets have a major disadvantage in that they don't produce as much flux density as rare earth magnets do, which leads to lower torque density and thus less power in PMSMs. Several approaches have been taken in design of PMSMs in order to tackle this problem. Two of these designs are presented and compared in this work. The first design is the spoke-type (or Flux squeeze) PMSM which places the magnets radially in the rotor to increase the magnetic flux density in the airgap. The second design is the Permanent Magnet Assisted Synchronous Reluctance Machine (PMASynRM) which produces the majority of its torque from saliency and uses permanent magnets to produce an additional magnet torque component. The main metrics used to evaluate the performance of each design are: maximum torque, operating range, torque ripple, magnet material required, and efficiency. Finite Element Analysis (FEA) is used to simulate and analyze both designs. Experimental characterization results are shown for the spoke-type PMSM and are compared to the same results obtained with FEA in order to have a guideline as to how accurate the FEA results are. A prototype of the PMASynRM design was constructed in the laboratory and some experimental results are presented.
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Title: Asymptotic near-to-far-zone transformation for periodic conformal antennas embedded in canonical stuctures
Creator: Villa-Giron, Jorge M.
Date: 2008
Collection: Electronic Theses & Dissertations

Title: A state model analysis of electric power systems
Creator: Duke, Albert L.
Date: 1963
Collection: Electronic Theses & Dissertations

Title: AN INTEGRATED OF CONTROL AND PROTECTION SCHEME FOR AC MICROGRIDS
Creator: AlZahrani, Saad Atitullah
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Numerous advances have occurred in the area of microgrids (MGs) in the last two decades. Protection is one of the most significant challenges facing the deployment of MGs. With the utilization of renewable energy resources (RES) to reduce emissions and costs, short circuit levels have drooped in comparison to those produced by conventional generating sources. Therefore, traditional protection schemes that apply to distribution system are no longer effective in protecting the microgrid against...
Show moreNumerous advances have occurred in the area of microgrids (MGs) in the last two decades. Protection is one of the most significant challenges facing the deployment of MGs. With the utilization of renewable energy resources (RES) to reduce emissions and costs, short circuit levels have drooped in comparison to those produced by conventional generating sources. Therefore, traditional protection schemes that apply to distribution system are no longer effective in protecting the microgrid against fault currents, either in grid–connected or islanded mode. In microgrid framework, distributed generation (DG) based RES require an interface of power electronic converters to regulate their output voltage, current, and frequency as well as to share the generated power properly. Mitigation the impacts of fault currents in microgrid system is an important aspect of restricting the output current of converters from exceeding their rated value, preventing power discontinuity, enhancing reliability of protection system and improving the stability of the network.For microgrid control and protection challenges, several approaches have been proposed in the last decade. However, the need for efficient and reliable protection schemes of islanded microgrid system still exists. This research thesis develops and synthesizes an adaptive integration of control and protection framework for MGs. The proposed strategy is based on detecting the faults and limiting the fault currents for short periods until the protection devices make a proper decision. A single state observer has been developed to detect the faults that occur within protection zones. Moreover, fault current limiter (FCL) devices have been utilized to achieve rapid switching with instant reduction of fault current contribution. The adaptive integrated protection proposed in this research is achievable using either centralized or decentralized control in MGs. The proposed framework has been applied to islanded microgrid configuration and is demonstrated to be an effective means to protect the system and maintain the voltage and frequency within acceptable range with the capability of power continuity during both transient and persistent faults.
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Title: Theoretical and Experimental Investigations of Arterial Pulse Wave Velocity (PWV)
Creator: Yavarimanesh, Mohammad
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Pulse transit time (PTT) is the time delay for the energy wave to travel between two sites in the arteries. (The energy wave can be visualized as acute dilation of the arterial wall and usually moves much faster than blood.) PTT in the form of pulse wave velocity (PWV = D/PTT, where D is the distance between the two sites) has proven to be a marker of arterial stiffness and a major cardiovascular risk factor based on a large body of epidemiological data. The Bramwell-Hill (BH) equation...
Show morePulse transit time (PTT) is the time delay for the energy wave to travel between two sites in the arteries. (The energy wave can be visualized as acute dilation of the arterial wall and usually moves much faster than blood.) PTT in the form of pulse wave velocity (PWV = D/PTT, where D is the distance between the two sites) has proven to be a marker of arterial stiffness and a major cardiovascular risk factor based on a large body of epidemiological data. The Bramwell-Hill (BH) equation relates arterial stiffness and radius to PWV. Arterial stiffness positively relates to blood pressure (BP); thus, many have pursued BP monitoring via PWV. We investigated PWV from theoretical, experimental, and application prospective.In the first theory study, we investigated the 100-year Bramwell-Hill equation, which relates PWV to BP and thus represents a basis for cuff-less BP monitoring. However, it has long been known that this equation underestimates PWV in a BP-dependent manner. We developed a new equation that accounts for spatial changes in arterial cross-sectional area. This new equation largely corrected this well-known underestimation and predicted PWV better based on experimental data in the literature. In the second experimental study, we examined the most popular PTT (finger PTT). We hypothesize that whole body PTT could be better than finger PTT due to less smooth muscle contraction. We collected data from 32 participants in a near supine position. We placed sensors including electrodes on the chest for an ECG waveform, clips on the ear, finger, and toe for photo-plethysmography (PPG) waveforms, and a cuff on the arm for auscultation BP. We recorded the waveforms and referenced BP before and after mental arithmetic, a cold pressor test, slow breathing, and nitroglycerin. Conventional PTTs were assessed as markers of BP in human subjects undergoing a battery of interventions to change BP. This experimental study concludes that PTTs through the whole body rather than the arm show the best BP change tracking ability. Thirdly, we repeated the previous study for seven subjects in three sessions one year apart to see how much PTTs and other PPG waveform feature models change after one year. While it is known that the PTTs calibration models must be updated periodically to account for aging effects, data on the time period required for these “cuff re-calibrations” are scant. Our experimental finding suggests that the PTTs model through the whole body could hold up after one year, and calibration may occur every year, which is reasonably practical. Finally, because of the inverse relation of PWV and arterial radius in the BH equation, we investigated innovative applications for PTT and other physiology-inspired features of carotid and femoral waveform for screening and surveillance of aortic abdominal aneurysm diameter. We hypothesized that arterial waveform features such as PTT constitute a non-imaging solution for the aneurysm size of the aorta. The features detected AAA with 72-80% accuracy. In conclusion, from a theoretical standpoint, we improved the 100-year PWV equation by relaxing its main assumption. From an experimental perspective, we showed the best body location for measuring PWV in the sense of BP prediction and robustness after one year. Lastly, we found that PWV could be used as markers of the abdominal aortic aneurysm from an application standpoint.
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Title: THEORETICAL MODELING OF ULTRAFAST OPTICAL-FIELD INDUCED PHOTOELECTRON EMISSION FROM BIASED METAL SURFACES
Creator: Luo, Yi
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Laser-induced electron emission from nanostructures offers a platform to coherently control electron dynamics in ultrashort spatiotemporal scales, making it important to both fundamental research and a broad range of applications, such as to ultrafast electron microscopy, diffraction, attosecond electronics, strong-field nano-optics, tabletop particle accelerators, free electron lasers, and novel nanoscale vacuum devices. This thesis analytically studies nonlinear ultrafast photoelectron...
Show moreLaser-induced electron emission from nanostructures offers a platform to coherently control electron dynamics in ultrashort spatiotemporal scales, making it important to both fundamental research and a broad range of applications, such as to ultrafast electron microscopy, diffraction, attosecond electronics, strong-field nano-optics, tabletop particle accelerators, free electron lasers, and novel nanoscale vacuum devices. This thesis analytically studies nonlinear ultrafast photoelectron emission from biased metal surfaces, by solving the time-dependent Schrödinger equation exactly. Our study provides better understanding of the ultrafast control of electrons and offers useful guidance for the future design of ultrafast nanoelectronics. First, we present an analytical model for photoemission driven by two-color laser fields. We study the electron energy spectra and emission current modulation under various laser intensities, frequencies, and relative phase between the two lasers. We find strong modulation for both the energy spectra and emission current (with a modulation depth up to 99%) due to the interference effect of the two-color lasers. Using the same input parameter, our theoretical prediction for the photoemission current modulation depth (93.9%) is almost identical to the experimental measurement (94%). Next, to investigate the role of dc field, we construct an analytical model for two-color laser induced photoemission from dc biased metal surfaces. We systematically examine the combined effects of a dc electric field and two-color laser fields. We find the strong modulation in two-color photoemission persists even with a strong dc electric field. In addition, the dc field opens up more tunneling emission channels and thus increases the total emission current. Application of our model to time-resolved photoelectron spectroscopy is also demonstrated, showing the dynamics of the n-photon excited states depends strongly on the applied dc field. We then propose to utilize two lasers of the same frequency to achieve the interference modulation of photoemission by their relative phase. This is motivated by the easier access to single-frequency laser pairs than two-color lasers in experiments. We find a strong current modulation (> 90%) can be achieved with a moderate ratio of the laser fields (< 0.4) even under a strong dc bias. Our study demonstrates the capability of measuring the time-resolved photoelectron energy spectra using single-frequency laser pairs. We further extend our exact analytic model to photoelectron emission induced by few-cycle laser pulses. The single formulation is valid from photon-driven electron emission in low intensity optical fields to field-driven emission in high intensity optical fields, and is valid for arbitrary pulse length from sub-cycle to CW excitation, and for arbitrary pulse repetition rate. We find the emitted charge per pulse oscillatorily increases with pulse repetition rate, due to varying coherent interaction of neighboring laser pulses. For a well-separated single pulse, our results recover the experimentally observed vanishing carrier-envelope phase sensitivity in the optical-field regime. We also find that applying a large dc field to the photoemitter is able to greatly enhance the photoemission current and in the meantime substantially shorten the current pulse. Finally, we construct analytical models for nonlinear photoelectron emission in a nanoscale metal-vacuum-metal gap. Our results reveal the energy redistribution of photoelectrons across the two interfaces between the gap and the metals. Additionally, we find that decreasing the gap distance tends to extend the multiphoton regime to higher laser intensity. The effect of dc bias is also studied in detail.
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