Engineering Commons^™

Efficient Super-Ultra-Wideband Monopole Antenna Design For Multi-Band Wireless Applications, Hassan Ali Ragheb, Mariam Housam, Mostafa Salah, Angie El-Damak

Electrical Engineering

The paper describes the design of a novel super ultra-wide band antenna based on frequency independent structure and defected ground plane principles. The antenna is intended to be used for applications in WLAN, WI-MAX, S band, C band, X band, K band, and 5G mm Wave frequencies. Its compact size of 55× 40 × 1.6mm3 and utilization of FR-4 substrate, offers cost-effective manufacturing. The partial ground plane configuration enhances the antenna's bandwidth. The designed antenna was fabricated and tested where the results for S11 and VSWR were compared with those obtained from the simulation. An excellent agreement was observed between …

Iterative Power Flow Control Architecture For Dc-Ac-Ac Triple Active Bridge Converters: Design, Simulation, And Hardware Testing, Jonathan Henri Saelens

Masters Theses

Driven by widespread electrification and escalating energy demands, efficient and cost-effective converter systems are necessary to maintain and improve our nation's electrical grid. Facilitating this necessity are power electronic converters in applications such as smart grids, renewable energy integration, and electric vehicles. Guided by the demand for improved converter topologies and conversion efficiency, much research has been conducted on varying designs, development, and control implementations. One such topology gaining significant research attention is the triple active bridge (TAB) converter. The TAB is a three-port power converter enabling both bidirectional power flow on each port and galvanic isolation for safety and …

The Impact Of Dissolved Organic Matter On Photodegradation Rates, Byproduct Formations, And Degradation Pathways For Two Neonicotinoid Insecticides In Simulated River Waters, Josephus F. Borsuah, Tiffany L. Messer, Daniel D. Snow, Steven D. Comfort, Shannon Bartelt-Hunt

UK CARES Faculty Publications

The influences of dissolved organic matter (DOM) on neonicotinoid photochemical degradation and product formation in natural waters remain unclear, potentially impacting the sustainability of river systems. Therefore, our overall objective was to investigate the photodegradation mechanisms and phototransformation byproducts of two neonicotinoid pesticides, imidacloprid and thiamethoxam, under simulated sunlight at the microcosm scale, to assess the implications of DOM for insecticide degradation in rivers. Direct and indirect photolysis were investigated using twelve water matrices to identify possible reaction pathways with two DOM sources and three quenching agents. Imidacloprid, thiamethoxam, and potential degradants were measured, and reaction pathways identified. The photodegradation …

A Comprehensive Exploration Of Fundamental And Experimental Characteristics Of Nanophotonic Metasurfaces, Nasrin Razmjooei

Electrical Engineering Dissertations - Archive

The advent of diffraction gratings with periodic unit cells has led to numerous advancements in theoretical studies and practical applications. Recently, these structures have been recognized as subsets of “meta-surfaces” or “meta-materials”, employing periodically aligned features at the wavelength scale to manipulate electromagnetic wave properties for diverse applications. This manipulation extends to controlling amplitude, phase, spectral distribution, polarization state, and the local mode structure of light across various spectral expressions. A significant characteristic of these metasurfaces is their ability to couple incident light to laterally propagating leaky Bloch modes in the subwavelength regime, resulting in resonance at specific wavelengths known …

A Wearable Sensing System For High-Speed Interface Of Wide Range Electrochemical Sensor Array, Shanthala Lakshminarayana

Electrical Engineering Dissertations - Archive

Electrochemical sensing systems have emerged as indispensable tools in various fields due to their remarkable sensitivity, selectivity, and versatility. They play a pivotal role in modern research, industry, environmental monitoring, and healthcare devices. In environmental monitoring, these systems are deployed for detecting pollutants, heavy metals, and toxic gases, facilitating real-time monitoring, and ensuring environmental safety. Whereas, in the biomedical field, electrochemical sensing systems play a crucial role in diagnosing diseases, monitoring biomarkers etc, thereby revolutionizing healthcare practices.

Cost-effective wearable electrochemical sensing devices are significant for democratizing healthcare and improving public health outcomes. These devices enable continuous monitoring of physiological parameters, …

Pulsed Dielectric Breakdown And Permittivity Characterization Of Composite Solid Insulators In Pulsed Power Systems, Shawn T. Scoggin

Electrical Engineering Dissertations - Archive

In high voltage pulsed power systems, liquids and gases are often used as insulating materials because they offer high breakdown strengths, conform around complex geometries, and are self-healing, but they can introduce significant engineering challenges and restrictions when it comes to implementing them. Solid dielectrics can be desirable for improving the maintenance requirements, shelf life, and power/energy density metrics associated with insulating high voltage pulsed power systems, however they possess design challenges of their own. Solid dielectrics are not self-healing and can be difficult to manufacture, especially around complex geometries. Epoxy dielectrics are of high interest because of their naturally …

Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora

Computer Science and Engineering Theses - Archive

This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …

Development And Application Of Guided Mode Resonance Biosensor Platforms For Highly Sensitive And Real-Time Cell Killing Assays, Seyedmohsen Vaziri

Electrical Engineering Dissertations - Archive

In this work, we developed and investigated the cancer cell killing efficacy of different instances using real-time high-sensitivity measurements facilitated by Guided-Mode Resonance (GMR) sensors. The GMR biosensor technology detects shifts in the spectral peak caused by changes in the refractive index of the surrounding medium, offering a label-free method for monitoring cellular events.

A549 cell line wild type and HER2 knockout (lung cancer cells) were exposed to different concentrations of Triton X-100 and ADC (Herceptin with αHFc-CL-DMDM). The GMR-based cell killing assay demonstrated exceptional sensitivity and specificity, with shifts in wavelength exhibiting a robust correlation with cell viability and …

Li-Ion Battery Resistance During External Short Circuits And Cyclic Ageing, Kaynat Zia

Electrical Engineering Dissertations - Archive

External short circuit testing (ESCT) is one of the many steps towards ensuring lithium-ion (Li-ion) batteries are safe for different applications. The nature of testing is sensitive due to the concern of safety and data integrity. Great care and planning must be done before conducting these tests. Bouncing in recorded data is observed in literatures with high sampling rates due to switching and moving mechanical parts. This impacts the estimation accuracy of battery internal parameter values especially the effective ohmic resistance (Ro). This dissertation proposes a zero bouncing circuit design to eliminate this problem. Multi-rate Pulse Discharge Testing (MPDT) is …

All-Optical Signal Processing With Fiber-Based Parametric Wavelength Converters, Cheng Guo

Electrical Engineering Dissertations - Archive

The optical signal degradation by optical amplifier noise set the fundamental limit of link reach in the fiber-optics networks. The industrial solution is to use the optical-electrical-optical (OEO) regenerator to clean up the noise at the expense of high-speed electronics and extra cost of laser and photodetectors. All-optical signal processing, enabled by nonlinear optics and optical fiber, intrinsically provides 2-order of magnitude higher processing bandwidth and seamless interface to fiber communication channels. However, there is no robust phase-preserving regenerator that has been experimentally demonstrated without sophisticated polarization tuning and without instable interferometric structure. In this project, we explore the applications …

Analysis Of Noise Sources In Avalanche Region Of Reverse Biased P-N Junctions, Md Sakiul Islam Sudman

Electrical Engineering Theses - Archive

There is a need to understand the physical mechanisms for excess noise factor (F) in avalanche diodes for all regions of operation. The current classical theory accounts for F only for low carrier multiplication where single carrier injection starts the avalanche process. Our model fits the white noise exhibited by reverse-biased avalanche diodes in the entire operation region of four orders of current magnitude. In this sense, it is a first. The measured noise data was provided by Texas Instruments. We fitted the measured noise components with the calculated noise components where carrier multiplication takes place. The least …

Neural Net Estimation Of Discriminants Posterior Probability Vector, Harshvardhan Harshvardhan

Electrical Engineering Theses - Archive

Interpreting multi-layer perceptron (MLP) classifier outputs as posterior probabilities is a well-established practice in machine learning and is supported in the literature. However, several authors point out that MLP outputs are very poor estimates of the posterior probabilities. This is demonstrated for classifiers with and without nonlinear output activation. Achieving this reliability depends on key factors such as model complexity, sufficient training data availability, and optimization techniques' effectiveness. In practice, these requirements are not met, resulting in suboptimal probability estimates. Our approach introduces an innovative method based on the softmax output. The method aim to refine MLP discriminants into more …

Energy Harvesting Face Mask Using A Thermoelectric Generator For Powering Wearable Health Monitoring Sensors, Ugur Erturun, Cansu Yalim, James E. West

Engineering Management & Systems Engineering Faculty Publications

A wearable energy harvester (EH) incorporating a face mask with a thermoelectric generator is demonstrated. The function of this device is to generate electrical power from the heat produced by the human body, particularly breath, with the specific aim of powering wearable sensor applications. A prototype was built using a commercially available N95 face mask, a thermoelectric generator, and a heatsink. The performance of this EH device was assessed using experimental and numerical methodologies. The experimentally tested power output of the prototype was found to be ≈100 µW, with a corresponding power density of ≈30 µW/cm3, for a temperature difference …

Understanding The Link Between Conflict Profiles And Team Affective Outcomes Using Lpa And Nlp Techniques, Francisco Cima, Pilar Pazos-Lago

Engineering Management & Systems Engineering Faculty Publications

Team conflict is a naturally emerging phenomenon resulting from individuals' interactions during project execution. Cross-disciplinary teams can experience higher levels of conflict than single-discipline teams because of the increased diversity of knowledge and perspectives. Research has shown that team conflict can emerge from different types of disagreements (cognitive and interpersonal), which have different implications for team functioning. Past empirical research has focused on the impact of both conflict types independent from each other while overlooking their combined effects. This work examines the conflict profiles resulting from the combined levels of interpersonal and cognitive disagreements and their association with team outcomes. …

Evaluating Electromagnetic Interference On Gnss Receivers, Giorgi Tsintsadze

Masters Theses

"Due to high power and efficiency requirements of modern electrical drive system, inverters are utilizing fast-edge pulses as a drive signal. The high frequency pulses contain higher order harmonics can radiate electromagnetic interference above accepted levels. Modelling and understanding the mechanism that causes the radiation is studied, modelled and presented as gray-box model which contains circuit level modelling of coupling between electrical machine phase windings and low power sensor harness. The thesis consists of two main papers. In the first paper, radiated emissions from an electrical drive system is charac- terized thru gray-box modelling where coupling between electrical machine phase …

Advanced Detection Of Sars-Cov-2 And Omicron Variants Via Mxene-Graphene Hybrid Biosensors Utilizing Nucleic Acid Probes, Jiaoli Li, Yuwei Zhang, Congjie Wei, Yanxiao Li, Zhekun Peng, Hsin Yin Chuang, Logan Pearce, Adrianus Boon, Yue-Wern Huang, Dong Hyun Kim, Risheng Wang, Chenglin Wu

Biological Sciences Faculty Research & Creative Works

Low-cost biosensors that can rapidly and widely detect viruses are critical for faster diagnosis and treatment decision-making, especially for infections. The commonly used field-effect transistor is sensitive to the biomarker's detection but struggles with precise detection, particularly of nontargets such as ions and proteins. To overcome this limitation, we developed a field-effect transistor biosensor design based on MXene-graphene materials to increase the accuracy and sensitivity of virus detection. Based on the hybridization process between two complementary DNA strands, single-stranded nucleic acids were immobilized on the sensing surface via 3-aminopropyltriethoxysilane and glutaraldehyde to capture the nucleic acids of the target virus. …

Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama

Browse all Theses and Dissertations

In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key …

Design Of Waveguide Probe For Emi Characterization Of Ddr5 Sodimm, Xiangrui Su, Junho Joo, Minsu Lee, Jeongho Ju, Hyunsik Kim, Taeil Bae, Haekang Jung, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In the latest portable electronic devices, 5th generation double data rate small outline dual in-line memory modules (DDR5 SODIMMs) are more and more used and have been identified as one of the critical electromagnetic interferences (EMI) noise sources that could cause RF desensitization. In this paper, the radiation mechanism of DDR5 SODIMM deployed in a laptop is identified and investigated based on near-field scanning. It was found that a cavity formed by the SODIMM and the main board can generate strong radiation around 2.4 GHz due to their dimensions, which overlap with the Wi-Fi band. To quantify the radiation from …

Variation-Aware Non-Linear Mapping For Honey-Memristor Based Neuromorphic System, Harshvardhan Uppaluru, Md Mehedi Hasan Tanim, Md Omar Faruque, Mohammed Rafeeq Khan, Zoe Templin, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors are promising synapse candidates for neuromorphic systems due to their significant benefits, such as environmental sustainability, low production and disposal cost, non-volatile storage capability, and bio/CMOS-compatibility. In this paper, experimental evaluations of a neuromorphic system based on honey-memristors are reported. First, honey-memristors are manufactured and tested based on our in-house technology, and then the non-linear characteristics inherent to honey-memristors, which causes inaccurate weight updates and reduces the inference accuracy, are explored. A non-linear mapping (NMP) method is applied to mitigate the effects of non-linearity in honey-memristor, under different scenarios including multiple cycle-to-cycle variations and Analog-to-Digital Converter (ADC) …

Impact Of Aging On Pim And Dc Resistance Of Fabric-Over-Foam Metallic Contacts, Kalkidan W. Anjajo, Seunghun Ryu, Shengxuan Xia, Gracie Boyer, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this paper the impact of aging on the level of passive intermodulation (PIM) and DC resistance of fabric-over-foam metallic contacts is presented. These contacts are widely used to maintain metallic connections between modules and chassis in electronic devices. The PIM caused by the loose metallic contact of these materials mainly affects a receiver's RF sensitivity in mobile devices. This aging test under elevated temperature and relative humidity conditions offers an experiment-based approach with respect to various metallic contact cases. Energy dispersive spectroscopy and scanning electron microscopy are used to characterize the change in material composition and the contact surface …

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …

Ecgconvt : A Hybrid Cnn And Vision Transformer Model For 12-Lead Ecg Images Classification, Mudassar Khalid

Chulalongkorn University Theses and Dissertations (Chula ETD)

Cardiovascular diseases (CVDs) are the most common cause of human deaths globally, and they can be controlled by early diagnosis and accurate classification of the electrocardiograms. The Electrocardiogram, commonly known as an ECG, is a very affordable technique to know about the health of the heart from 12 different angles by using 12-Leads to capture the heart's electrical activity. A hybrid deep learning model is proposed in this study to classify the different heart diseases. The deep learning model is composed of a CNN(Xception) to capture all the local feature-maps of the images and a vision transformer (ViT) to study …

Comparative Analysis Of Ac Coupled And Dc Coupled Microgrids: Analyzing Electrical Performances And Economics, Sanjeev Kumar

Cal Poly Humboldt theses and projects

This study compares the electrical performance and economics of DC-coupled and AC-coupled community microgrid configurations through simulation and financial modeling of the Redwood Coast Airport Microgrid (RCAM), which integrates 2.2 MW of solar PV and 2.2 MW of battery storage. Unified load flow, short circuit, transient stability (including load impact), and efficiency studies using ETAP & SAM software tools demonstrate that the DC-coupled configuration is preferred based on efficiency, while both configurations exhibit equivalent performance with respect to selected power quality metrics. The DC setup exhibits 11% higher overall efficiency than AC coupling in converting solar energy to grid exports. …

Parameter Identifiability Analysis And Calibration For Power System Dynamic Models, Lei Wang

Electronic Theses and Dissertations

Accurate dynamic models are crucial for stable and reliable power system operation, making their validation essential. The accuracy of parameter estimation is influenced by several factors, including available observables, model structure, and estimation methods. However, in dynamic models, estimating parameters can be difficult when some of them are unidentifiable, meaning their values cannot be uniquely determined from the available data. This challenge may stem from limited impact of parameters on the measured outputs, parameter interactions, or poor data quality. Therefore, an identifiability analysis should be conducted prior to parameter estimation or model calibration. This preliminary step helps to determine which …

Open-Ended Hollow Coaxial Cable Resonance Sensing Via Permittivity Fluctuations For Applications To Exhaled Breath Health Monitoring, Peter Henry Holtmann

Masters Theses

"We report a pre-diagnostics breath analyzer based on the open-ended hollow coaxial cable resonator (OE-HCCR) to achieve real-time differentiation of healthy and compromised lung function through electromagnetic analysis of exhaled breath matter. A two-phase amplification scheme of electromagnetic signatures metered via the S11 phase curve offers high sensitivity to permittivity fluctuations in exposed airflow. The mathematical model of the breath analyzer is explained, followed by experimental validation of numerical findings from previous work. The collection of breath transient signals is performed through monitoring the reflected power magnitude and phase of the scattering parameter (S11) at the resonance frequency. Material fluctuations …

Control And Optimization Of Energy Storage System In Power Distribution System, Waqas Ur Rehman

Doctoral Dissertations

"The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, …

Optimization Of Energy From Building Integrated Photovoltaic Of High-Rise Buildings In Thailand, Min Khant

Chulalongkorn University Theses and Dissertations (Chula ETD)

This project is to find the method to optimize the energy from Building Integrated Photovoltaic System in high rise building. Firstly, the solar irradiance potential of vertical surfaces of high-rise building is analyzed in Bangkok, Thailand. With these irradiance values, the optimal size and placement of BIPV module on east, west and south façades of the building is analyzed in order to minimize the building energy usage from the electricity grid. The BIPV system is optimized using the Genetic Algorithm Optimization method in MATLAB. The output results include the optimal surface area used by BIPV module in east, west and …

Nano-Patterned Si Structures For Optical Filters And Electro-Mechanical Relays: Fabrication, Characterization, Prospects, And Limitations, Md Ataul Mamun

Theses and Dissertations

Nanofabrication technology, especially nanopatterning, is a rapidly advancing field that has already resulted in creating novel devices and holds promise for producing even more with unmatched performance. These techniques also allow us to gain insight into physical phenomena at the micro- and nanoscale. The ultimate performance of nanofabricated devices and their compatibility with existing Si-based CMOS technology hinge upon the careful selection of materials and precise design, coordinated with meticulous pattern transfer. In this work, we applied nanopatterning techniques on silicon to create optical filters for the shortwave infrared (SWIR) region and nanoelectromechanical system (NEMS) relay-based logic gates. Additionally, these …

Modeling And Mitigating Power Grid Vulnerabilities: A Comprehensive Analysis Of Renewable Energy Integration, Cascading Failures, And Microgrid Resilience, Saikat Das

Theses and Dissertations

In modern power systems, rapid integration of renewable energy and the emergence of microgrid technology emphasize the necessity for a comprehensive understanding of vulnerabilities and robust defense mechanisms. The research begins with an exploration of power grid vulnerabilities to cascading failure amidst the increasing integration of renewable energy sources. A novel power balance technique is employed for cascading failure analysis and power grid vulnerability measurement. Simulation results indicate that the growing penetration of renewable energy has a proportionally higher impact on grid vulnerability to cascading failures. After a certain level of renewable energy penetration, some systems may deteriorate rapidly, necessitating …