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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: 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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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: 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: 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: Neural mechanisms of goal-directed action selection by prefrontal cortex : implications for brain-machine interfaces
Creator: Mohebi, Ali
Date: 2014
Collection: Electronic Theses & Dissertations
Description: Initiating a movement goal and maintaining that goal throughout the planning and execution of a goal-directed action is an essential element of all goal-directed behavior. In thecontext of Brain Machine Interfaces (BMIs), a direct communication pathway between thebrain and a man-made computing device, continuous access to movement goals is essential,so as to guide the control of neuroprosthetic limbs that provide neurologically impaired subjects with an alternative to their lost motor...
Show moreInitiating a movement goal and maintaining that goal throughout the planning and execution of a goal-directed action is an essential element of all goal-directed behavior. In thecontext of Brain Machine Interfaces (BMIs), a direct communication pathway between thebrain and a man-made computing device, continuous access to movement goals is essential,so as to guide the control of neuroprosthetic limbs that provide neurologically impaired subjects with an alternative to their lost motor function. The Prefrontal cortex (PFC) has beensuggested as an executive control area of the brain that bridges the temporal gap betweenincoming sensory information and ensuing motor actions. The mechanisms underlying thedynamics of PFC neural activity, however, remain poorly understood. The main objectiveof this dissertation is to elucidate the role of PFC neurons in mediating goal initiation andmaintenance during goal-directed behavior.Using a combination of electrophysiological recordings, optogenetic and pharmacological manipulation of population activity and behavioral assays in awake behaving subjects,we demonstrate that the PFC plays a critical role in the planning and execution of a twoalternative forced choice task. In particular, PFC neurons were mostly goal selective duringthe choice epoch of the task when subjects had to select the action with the highest utility while suppressing all other unrewarded actions. Decoding PFC neural activity usingadvanced machine learning algorithms showed robust single trial prediction of motor goals,suggesting that PFC may be a candidate site for inferring volitional motor intent. In addition, results from inactivation experiments demonstrate a lateralized performance declinewith respect to the inactivation site, further confirming the critical role of the PFC in mediating the motor- but not the sensory- information during the execution of goal-directedbehavior. Taken together, our results suggest that the design of next generation BMIs couldbe further improved by incorporating goal information from cognitive control areas of thebrain, thereby augmenting the capability of current designs that only rely on decoding themoment-by-moment kinematics of intended limb movements from motor areas of the brain.
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Title: Design of an analog computer
Creator: Bush, Nyle Eugene
Date: 1948
Collection: Electronic Theses & Dissertations

Title: Theoretical analysis of electronic, thermal, and mechanical properties in gallium oxide
Creator: Domenico Santia, Marco
Date: 2019
Collection: Electronic Theses & Dissertations
Description: In recent years, Ga2O3 has proven to be a promising semiconductor candidate for a widearray of power electronics and optoelectronics devices due to its wide bandgap, high breakdownvoltage, and growth potential. However, the material suffers from a very low thermalconductivity and subsequent self-heating issues. Additionally, the complexity of the crystalstructure coupled with the lack of empirical data, has restricted the predictive power of modellingmaterial properties using traditional...
Show moreIn recent years, Ga2O3 has proven to be a promising semiconductor candidate for a widearray of power electronics and optoelectronics devices due to its wide bandgap, high breakdownvoltage, and growth potential. However, the material suffers from a very low thermalconductivity and subsequent self-heating issues. Additionally, the complexity of the crystalstructure coupled with the lack of empirical data, has restricted the predictive power of modellingmaterial properties using traditional methods. The objective of this dissertation is toprovide a detailed theoretical characterization of material properties in the wide bandgapsemiconductor Ga2O3 using first-principles methods requiring no empirical inputs. Latticethermal conductivity of bulk β − Ga2O3 is predicted using a combination of first-principlesdetermined harmonic and anharmonic force constants within a Boltzmann transport formalismthat reveal a distinct anisotropy and strong contribution to thermal conduction fromoptical phonon modes. Additionally, the quasiharmonic approximation is utilized to estimatevolumetric effects such as the anisotropic thermal expansion.To evaluate the efficacy of heat removal from β − Ga2O3 material, the thermal boundaryconductance is computed within a variance-reduced Monte-Carlo framework utilizingfirst-principles determined phonon-phonon scattering rates for layered structures containingchromium or titanium as an adhesive layer between a β − Ga2O3 substrate and Au contact.The effect of the adhesive layer improves the overall thermal boundary conductancesignificantly with the maximum value found using a 5 nm layer of chromium, exceeding themore traditional titanium adhesive layers by a factor of 2. This indicates the potential ofheatsink-based thermal management as an effective solution to the self-heating issue.Additionally, this dissertation provides a detailed characterization of the effect of strainon fundamental material properties of β−Ga2O3 . Due to the highly anisotropic nature of thecrystal, the effect strain can have on electronic, mechanical, and optical properties is largelyunknown. Using the quasi-static formalism within a DFT framework and the stress-strainapproach, the effect of strain can be evaluated and combined with the anisotropic thermalexpansion to incorporate an accurate temperature dependence. It is found that the elasticstiffness constants do not vary significantly with temperature. The computed anisotropyis unique and differs significantly from similar monoclinic crystal structures, indicating theimportant role of the polyhedral linkage to the reported anisotropy in material properties.Lastly, the dependence of the dielectric function with respect to strain is evaluated using amodified stress-strain approach. This elasto-optic, or photoelastic, effect is found to be significantfor sheared crystal configurations. This opens up a potential unexplored applicationspace for Ga2O3 as an acousto-optic modulation device
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Title: Two Studies in Nonlinear Biological System Modeling and Identification
Creator: Yan, Jinyao
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Biological systems are often complex, nonlinear and time-varying. The modeling of biological systems, therefore, presents significant challenges that are not overcome by the classical linear methods. In recent decades, intensive research has begun to produce methods for analyzing and modeling isolated classes of nonlinear systems. However, this vast class of models still presents many challenges, especially in complex biological systems. In this research, two novel methods are introduced for...
Show moreBiological systems are often complex, nonlinear and time-varying. The modeling of biological systems, therefore, presents significant challenges that are not overcome by the classical linear methods. In recent decades, intensive research has begun to produce methods for analyzing and modeling isolated classes of nonlinear systems. However, this vast class of models still presents many challenges, especially in complex biological systems. In this research, two novel methods are introduced for analyzing time series resulting from nonlinear systems. In the first approach, we study a class of dynamical systems that are nonlinear, discrete and with a latent state-space. We solve the probabilistic inference problem in these latent models using a variational autoencoder (VAE). Compared to continuous latent random variables, the inference of discrete latent variables is more difficult to solve. However, stochastic variational inference provides us with a general framework that tackles the inference problem for this class of model. We focused on an important neuroscience application – inferring pre- and post-synaptic activities from dendritic calcium imaging data. For it, we developed families of generative models, a deep convolutional neural network recognition model, and methods of inference using stochastic gradient ascent VAE. We benchmarked our model with both synthetic data, which resembles real data, and real experimental data. The framework can flexibly support rapid model prototyping. Both the generative model and recognition model can be changed without perturbing the inference. This is especially beneficial for testing different biological hypotheses. As a second approach, we treat a subclass of nonlinear autoregressive models: linear-time-invariant-in-parameters models. This class of models is useful and easy to work with. We propose an identification algorithm that simultaneously selects the model and does parameter estimation. The algorithm integrates two strategies: set-based parameter identification, and evolutionary algorithms that optimize fitness measures derived from these solutions. The algorithm can identify nonlinear models in novel noise scenarios. We show the performance of the algorithm in various simulated systems and practical datasets. We demonstrate its application to identify causal connectivity in a graph. This problem is often posed in recovering functional connectivity in the brain. The main contribution of this thesis is that we provide two framework for identifying nonlinear, biological systems from time series data. These two classes of nonlinear models and their applications are significant as each class is broad enough for modeling many complicated biological systems. We develop general, fast algorithms for learning these systems from data for these two model classes.
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Title: A state model analysis of electric power systems
Creator: Duke, Albert L.
Date: 1963
Collection: Electronic Theses & Dissertations

Title: Design study of a miniaturized multi-layered metamaterial-inspired dynamically tunable antenna
Creator: Myers, Joshua C.
Date: 2014
Collection: Electronic Theses & Dissertations
Description: A multi-layered metamaterial inspired minaturized antenna with a pixel grid loading structure is introduced in this work. The antenna consists of two layers separated by a thin dielectric substrate. The first layer contains a folded monopole antenna surrounded by a metal pixel based loading structure, while the second layer is envisioned to consist of a photo conductive pixel grid utilized to tune the antenna. The state of each pixel is controlled by a binary genetic algorithm, which is...
Show moreA multi-layered metamaterial inspired minaturized antenna with a pixel grid loading structure is introduced in this work. The antenna consists of two layers separated by a thin dielectric substrate. The first layer contains a folded monopole antenna surrounded by a metal pixel based loading structure, while the second layer is envisioned to consist of a photo conductive pixel grid utilized to tune the antenna. The state of each pixel is controlled by a binary genetic algorithm, which is implemented with a Matlab-HFSS interface. As a proof of concept, the pixel grid on the second layer is initially made of a metal conductor. HFSS simulations show that the second layer has a wide tuning ability with the appropriate state formed through optimization. A wide range of other conductivities are also shown toprovide pixel combinations that meet the required antenna characteristics. The radiation efficiency of the antenna with the second layer is also examined and optimized, and the theoretical tuning range is investigated. The fabrication of multiple antenna configurations with the pixels made of a metal conductor are explored. Thin PET films are first investigated to be used as simple loading elements that can be placed directly on the antenna. However, the airgap and misalignment between the layers caused by this method is shown to be too large to overcome. A novel multi layer fabrication technique is then investigated which uses a SU-8 photoresist as the dielectric layer. This layer can be spun directly onto the antenna, essentially eliminating any airgap problems. The alignment with this process is also much better than the previews method. Multiple antenna configurations corresponding to a wide frequency range are constructed using this fabrication method. The measured reflection coefficients and radiation patterns are shown to be in good agreement with HFSS simulations, successfully demonstrating the ability to dramatically tune the antenna with a second pixel grid
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Title: Millimeter-wave microsystems using additive manufacturing process
Creator: Qayyum, Jubaid Abdul
Date: 2020
Collection: Electronic Theses & Dissertations
Description: In recent years, researchers have been working to explore the millimeter-wave frequency domain for wireless technology to cope with the immense demand for high bandwidth for faster wireless applications such as communication and remote sensing in general. In wireless communication technology, high frequency of the mm-wave systems offers high bandwidth transmission for faster data transmission. The mm-wave frequency has also been approved by FCC for commercial applications like 5G...
Show moreIn recent years, researchers have been working to explore the millimeter-wave frequency domain for wireless technology to cope with the immense demand for high bandwidth for faster wireless applications such as communication and remote sensing in general. In wireless communication technology, high frequency of the mm-wave systems offers high bandwidth transmission for faster data transmission. The mm-wave frequency has also been approved by FCC for commercial applications like 5G communications that will deliver a more reliable, dependable and scalable cellular technology with high rate and low latency for the network users. It also promises to facilitate high data communication among devices and humans as well as other devices, the phenomena that gave rise to an emerging field known as the "Internet-of-Things". For remote sensing, higher frequencies of the mm-wave offer higher spatial and range resolution that can enable more intelligent sensor technologies.The fabrication and manufacturing process of mm-wave systems become increasingly difficult and expensive due to size reduction at smaller wavelengths. To overcome these problems, system on package (SoP) technology has gained a lot of attention. The SoP approach combines multiple integrated circuits and passive components using different packaging and interconnect approaches into a miniaturized micro-system module. Additive manufacturing (AM), also colloquially known as 3-D printing, is considered as a promising method for packaging in SoP solutions because it enables rapid prototyping and large-scale production at an affordable cost and minimal environmental impact.This work primarily focuses on the development of mm-wave microsystems by integrating chips with AM process using aerosol jet printing (AJP). Several mm-wave transceiver components that ranges from Ka-band to W-band are designed and realized in a state-of-the-art silicon-germanium IC foundry process, and are characterized to be used in complete transceiver system using 3-D printing packaging. These include a 28-60 GHz Single-Pole Double-Throw (SPDT) switch, 28-60 GHz Low-noise amplifier (LNA), 15-100 GHz downconverting mixer, K-Band upconverting mixer, V-band upconverting mixer, and a 90 GHz MMIC frequency tripler.The feasibility of using AJP in mm-wave regime and the ink characteristics were also studied. For any AM process to be an all-in-one packaging solution, it should have the capability of realizing conducting as well as dielectric materials. Silver and polyimide inks were used in this work to demonstrate a chip-to-chip interconnection and a comparison with the traditional packaging technique is also discussed. An ultra-wideband interconnect from 0.1-110 GHz was implemented using AJP. The conductivity of the silver ink and its viability to be used in flexible electronics was also considered.
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Title: A bibliography of electrical subjects
Creator: Bloemendal, George W.
Date: 1916
Collection: Electronic Theses & Dissertations

Title: Operation of interior permanent magnet synchronous machines with fractional slot concentrated windings under both healthy and faulty conditions
Creator: Foster, Shanelle Nicole
Date: 2013
Collection: Electronic Theses & Dissertations
Description: Design for fault tolerance and early detection of insulation failure are critical for automotive and aerospace applications to ensure passenger safety. Permanent magnet machines can be designed to better withstand stator insulation failures. In this work, the performance of three fault tolerant fractional slot concentrated winding machine designs experiencing stator winding insulation failure are evaluated. Two of the machines are designed with double-layer windings and one with single-layer....
Show moreDesign for fault tolerance and early detection of insulation failure are critical for automotive and aerospace applications to ensure passenger safety. Permanent magnet machines can be designed to better withstand stator insulation failures. In this work, the performance of three fault tolerant fractional slot concentrated winding machine designs experiencing stator winding insulation failure are evaluated. Two of the machines are designed with double-layer windings and one with single-layer. The single-layer fractional slot concentrated winding design is shown most reliable; however this design has the worst torque performance. A ripple reduction control technique is developed based on an analytical description of torque. This technique is shown to improve the torque performance of the single-layer fractional slot design.Fault tolerant design alone does not provide high reliability since thermal stress from aging, overloading, cycling or fast switching of the inverter causes most stator insulation failures. Early detection of incipient stator winding faults could avoid catastrophic machine failure, allow implementation of mitigation techniques to continue operation, reduce the occurrence of secondary faults and allow adequate time to plan maintenance. In this work, two of the machines designed were manufactured with windings that allow the introduction of faults with three severity levels and varying degrees of incipient faults. Through a parametric identification method, the characteristic flux linkages of the machines are extracted under both healthy and faulty conditions. It is shown that incipient stator windings faults are reflected in the machine's characteristic parameters. These parametric changes are reflected in the phase voltage for current-controlled applications. Incipient stator winding faults can be detected online, if accurate knowledge of the healthy machine parameters is available.
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Title: Nanoengineered tissue scaffolds for regenerative medicine in neural cell systems
Creator: Tiryaki, Volkan Mujdat
Date: 2013
Collection: Electronic Theses & Dissertations
Description: Central nervous system (CNS) injuries present one of the most challenging problems. Regeneration in the mammal CNS is often limited because the injured axons cannot regenerate beyond the lesion. Implantation of a scaffolding material is one of the possible approaches to this problem. Recent implantations by our collaborative research group using electrospun polyamide nanofibrillar scaffolds have shown promising results in vitro and in vivo. The physical properties of the tissue scaffolds have...
Show moreCentral nervous system (CNS) injuries present one of the most challenging problems. Regeneration in the mammal CNS is often limited because the injured axons cannot regenerate beyond the lesion. Implantation of a scaffolding material is one of the possible approaches to this problem. Recent implantations by our collaborative research group using electrospun polyamide nanofibrillar scaffolds have shown promising results in vitro and in vivo. The physical properties of the tissue scaffolds have been neglected for many years, and it has only recently been recognized that significant aspects include nanophysical properties such as nanopatterning, surface roughness, local elasticity, surface polarity, surface charge, and growth factor presentation as well as the better-known biochemical cues.The properties of: surface polarity, surface roughness, local elasticity and local work of adhesion were investigated in this thesis. The physical and nanophysical properties of the cell culture environments were evaluated using contact angle and atomic force microscopy (AFM) measurements. A new capability, scanning probe recognition microscopy (SPRM), was also used to characterize the surface roughness of nanofibrillar scaffolds. The corresponding morphological and protein expression responses of rat model cerebral cortical astrocytes to the polyamide nanofibrillar scaffolds versus comparative culture surfaces were investigated by AFM and immunocytochemistry. Astrocyte morphological responses were imaged using AFM and phalloidin staining for F-actin. Activation of the corresponding Rho GTPase regulators was investigated using immunolabeling with Cdc42, Rac1, and RhoA. The results supported the hypothesis that the extracellular environment can trigger preferential activation of members of the Rho GTPase family, with demonstrable morphological consequences for cerebral cortical astrocytes. Astrocytes have a special role in the formation of the glial scar in response to traumatic injury. The glial scar biomechanically and biochemically blocks axon regeneration, resulting in paralysis. Astrocytes involved in glial scar formation become reactive, with development of specific morphologies and inhibitory protein expressions. Dibutyryl cyclic adenosine monophosphate (dBcAMP) was used to induce astrocyte reactivity. The directive importance of nanophysical properties for the morphological and protein expression responses of dBcAMP-stimulated cerebral cortical astrocytes was investigated by immunocytochemistry, Western blotting, and AFM. Nanofibrillar scaffold properties were shown to reduce immunoreactivity responses, while PLL Aclar properties were shown to induce responses reminiscent of glial scar formation. Comparison of the responses for dBcAMP-treated reactive-like and untreated astrocytes indicated that the most influential directive nanophysical cues may differ in wound-healing versus untreated situations.Finally, a new cell shape index (CSI) analysis system was developed using volumetric AFM height images of cells cultured on different substrates. The new CSI revealed quantitative cell spreading information not included in the conventional CSI. The system includes a floating feature selection algorithm for cell segmentation that uses a total of 28 different textural features derived from two models: the gray level co-occurance matrix and local statistics texture features. The quantitative morphometry of untreated and dBcAMP-treated cerebral cortical astrocytes was investigated using the new and conventional CSI, and the results showed that quantitative astrocyte spreading and stellation behavior was induced by variations in nanophysical properties.
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Title: Robotic fish : development, modeling, and application to mobile sensing
Creator: Wang, Jianxun (Mechatronic engineer)
Date: 2014
Collection: Electronic Theses & Dissertations
Description: Robotic fish are underwater robots that emulate locomotion of live fish through actuated fin and/or body movements. They are of increasing interest due to their potential applications such as aquatic environmental monitoring and robot-animal interactions.In this work, several bio-inspired robotic fish prototypes have been developed that make use of periodic tail motions. A dynamic model for a tail-actuated robotic fish is presented by merging rigid-body dynamics with Lighthill's large...
Show moreRobotic fish are underwater robots that emulate locomotion of live fish through actuated fin and/or body movements. They are of increasing interest due to their potential applications such as aquatic environmental monitoring and robot-animal interactions.In this work, several bio-inspired robotic fish prototypes have been developed that make use of periodic tail motions. A dynamic model for a tail-actuated robotic fish is presented by merging rigid-body dynamics with Lighthill's large-amplitude elongated-body theory. The model is validated with extensive experiments conducted on a robotic fish prototype. The role of incorporating the body motion in evaluating the tail-generated hydrodynamic forces is assessed, which shows that ignoring the body motion (as often done in the literature) results in significant overestimate of the thrust force and robot speed. By exploiting the strong correlation between the angle of attack and the tail-beat bias, a computationally efficient approach is further proposed to adapt the drag coefficients of the robotic fish.It has been recognized that the flexibility of the body and fin structures has a pronounced impact on the swimming performance of biological and robotic fish. To analyze and utilize this trait, a novel dynamic model is developed for a robotic fish propelled by a flexible tail actuated at the base. The tail is modeled with multiple rigid segments connected in series through rotational springs and dampers. For comparison, a model using linear beam theory is created to capture the beam dynamics. Experimental result show that the two models have almost identical predictions when the tail undergoes small deformation, but only the proposed multi-segment model matches the experimental measurement closely for all tail motions.Motivated by the need for system analysis and efficient control of robotic fish, averaging of robots' dynamics is of interest. For dynamic models of robotic fish, however, classical or geometric averaging typically cannot produce an average model that is accurate and the in the meantime amenable to analysis or control design. In this work, a novel averaging approach for tail-actuated robotic fish dynamics is proposed. The approach consists of scaling the force and moment terms and then conducting classical averaging. Numerical investigation reveals that the scaling function for the force terms is a constant independent of tail-beat patterns, while the scaling function for the moment term depends linearly on the tail-beat bias. Existence and local stability of the equilibria for the average model are further analyzed. Finally, as an illustration of the utility of the average model, a semi-analytical framework is presented for obtaining steady turning parameters.Sampling and reconstruction of a physical field using mobile sensor networks have recently received significant interest. In this work, an adaptive sampling framework is proposed to reconstruct aquatic environmental fields (e.g., temperature, or biomass of harmful algal blooms) using schools of robotic sensor platforms. In particular, it is assumed that the field of interest can be approximated by a low rank matrix, which is exploited for successive expansion of sampling area and analytical reconstruction of the field. For comparison, an Augmented Lagrange Multiplier optimization approach is also taken to complete the matrix reconstruction using a limited number of samples. Simulation results show that the proposed approach is more computationally efficient and requires shorter travel distances for the robots.
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Title: Electro-mechanical analogies
Creator: Eggert, William C.
Date: 1917
Collection: Electronic Theses & Dissertations

Title: Adaptive independent component analysis : theoretical formulations and application to CDMA communication system with electronics implementation
Creator: Albataineh, Zaid
Date: 2014
Collection: Electronic Theses & Dissertations
Description: Blind Source Separation (BSS) is a vital unsupervised stochastic area that seeks to estimate the underlying source signals from their mixtures with minimal assumptions about the source signals and/or the mixing environment. BSS has been an active area of research and in recent years has been applied to numerous domains including biomedical engineering, image processing, wireless communications, speech enhancement, remote sensing, etc. Most recently, Independent Component Analysis (ICA) has...
Show moreBlind Source Separation (BSS) is a vital unsupervised stochastic area that seeks to estimate the underlying source signals from their mixtures with minimal assumptions about the source signals and/or the mixing environment. BSS has been an active area of research and in recent years has been applied to numerous domains including biomedical engineering, image processing, wireless communications, speech enhancement, remote sensing, etc. Most recently, Independent Component Analysis (ICA) has become a vital analytical approach in BSS. In spite of active research in BSS, however, many foundational issues still remain in regards to convergence speed, performance quality and robustness in realistic or adverse environments. Furthermore, some of the developed BSS methods are computationally expensive, sensitive to additive and background noise, and not suitable for a real4time or real world implementation. In this thesis, we first formulate new effective ICA4based measures and their corresponding robust adaptive algorithms for the BSS in dynamic "convolutive mixture" environments. We demonstrate their superior performance to present competing algorithms. Then we tailor their application within wireless (CDMA) communication systems and Acoustic Separation Systems. We finally explore a system realization of one of the developed algorithms among ASIC or FPGA platforms in terms of real time speed, effectiveness, cost, and economics of scale. Firstly, we propose a new class of divergence measures for Independent Component Analysis (ICA) for estimating sources from mixtures. The Convex Cauchy4Schwarz Divergence (CCS4DIV) is formed by integrating convex functions into the Cauchy4Schwarz inequality. The new measure is symmetric and convex with respect to the joint probability, where the degree of convexity can be tuned by a (convexity) parameter. A non4parametric (ICA) algorithm generated from the proposed divergence is developed exploiting convexity parameters and employing the Parzen window4based distribution estimates. The new contrast function results in effective parametric and non4parametric ICA4based computational algorithms. Moreover, two pairwise iterative schemes are proposed to tackle the high dimensionality of sources. Secondly, a new blind detection algorithm, based on fourth order cumulant matrices, is presented and applied to the multi4user symbol estimation problem in Direct Sequence Code Division Multiple Access (DS4CDMA) systems. In addition, we propose three new blind receiver schemes, which are based on the state space structures. These so4called blind state4space receivers (BSSR) do not require knowledge of the propagation parameters or spreading code sequences of the users but relies on the statistical independence assumption among the source signals. Lastly, system realization of one of the developed algorithms has been explored among ASIC or FPGA platforms in terms of cost, effectiveness, and economics of scale. Based on our findings of current stat4of4the4art electronics, programmable FPGA designs are deemed to be the most effective technology to be used for ICA hardware implementation at this time.In this thesis, we first formulate new effective ICA-based measures and their corresponding robust adaptive algorithms for the BSS in dynamic "convolutive mixture" environments. We demonstrate their superior performance to present competing algorithms. Then we tailor their application within wireless (CDMA) communication systems and Acoustic Separation Systems. We finally explore a system realization of one of the developed algorithms among ASIC or FPGA platforms in terms of real time speed, effectiveness, cost, and economics of scale.We firstly investigate several measures which are more suitable for extracting different source types from different mixing environments in the learning system. ICA for instantaneous mixtures has been studied here as an introduction to the more realistic convolutive mixture environments. Convolutive mixtures have been investigated in the time/frequency domains and we demonstrate that our approaches succeed in resolving the standing problem of scaling and permutation ambiguities in present research. We propose a new class of divergence measures for Independent Component Analysis (ICA) for estimating sources from mixtures. The Convex Cauchy-Schwarz Divergence (CCS-DIV) is formed by integrating convex functions into the Cauchy-Schwarz inequality. The new measure is symmetric and convex with respect to the joint probability, where the degree of convexity can be tuned by a (convexity) parameter. A non-parametric (ICA) algorithm generated from the proposed divergence is developed exploiting convexity parameters and employing the Parzen window-based distribution estimates. The new contrast function results in effective parametric and non-parametric ICA-based computational algorithms. Moreover, two pairwise iterative schemes are proposed to tackle the high dimensionality of sources. These wo pairwise non-parametric ICA algorithms are based on the new high-performance Convex Cauchy-Schwarz Divergence (CCS-DIV). These two schemes enable fast and efficient de-mixing of sources in real-world applications where the dimensionality of the sources is higher than two.Secondly, the more challenging problem in communication signal processing is to estimate the source signals and their channels in the presence of other co-channel signals and noise without the use of a training set. Blind techniques are promising to integrate and optimize the wireless communication designs i.e. equalizers/ filters/ combiners through its potential in suppressing the inter-symbol interference (ISI), adjacent channel interference, co-channel and the multi access interference MAI. Therefore, a new blind detection algorithm, based on fourth order cumulant matrices, is presented and applied to the multi-user symbol estimation problem in Direct Sequence Code Division Multiple Access (DS-CDMA) systems. The blind detection is to estimate multiple symbol sequences in the downlink of a DS-CDMA communication system using only the received wireless data and without any knowledge of the user spreading codes. The proposed algorithm takes advantage of higher cumulant matrix properties to reduce the computational load and enhance performance. In addition, we address the problem of blind multiuser equalization in the wideband CDMA system, in the noisy multipath propagation environment. Herein, we propose three new blind receiver schemes, which are based on the state space structures. These so-called blind state-space receivers (BSSR) do not require knowledge of the propagation parameters or spreading code sequences of the users but relies on the statistical independence assumption among the source signals. We then develop and derive three update-laws in order to enhance the performance of the blind detector. Also, we upgrade three semi-blind adaptive detectors based on the incorporation of the RAKE receiver and the stochastic gradient algorithms which are used in several blind adaptive signal processing algorithms, namely FastICA, RobustICA, and principle component analysis PCA. Through simulation evidence, we verify the significant bit error rate (BER) and computational speed improvements achieved by these algorithms in comparison to other leading algorithms.Lastly, system realization of one of the developed algorithms has been explored among ASIC or FPGA platforms in terms of cost, effectiveness, and economics of scale. Based on our findings of current stat-of-the-art electronics, programmable FPGA designs are deemed to be the most effective technology to be used for ICA hardware implementation at this time.
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