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Articles 2371 - 2400 of 36682
Full-Text Articles in Electrical and Computer Engineering
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang
Graduate Theses and Dissertations
This dissertation explores the development and optimization of electrostatic discharge (ESD)-robust, low-voltage CMOS technology using 4H-silicon carbide (SiC) tailored for high-temperature applications, addressing the critical need for reliable semiconductor devices in harsh environmental conditions. The advent of SiC as a semiconductor material offers significant advantages over traditional silicon (Si) in harsh environments, including higher thermal conductivity, greater electron mobility, and improved electrical characteristics at elevated temperatures. This research explores the integration of 4H-SiC into CMOS technology to enhance device reliability and performance in extreme conditions such as those found in aerospace, automotive, and energy sectors. The study begins with a …
Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan
Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan
All Dissertations
This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …
Patterning Synthesis Of Lead Halide Perovskites Toward Photonic Application, S. M. Nayeem Arefin
Patterning Synthesis Of Lead Halide Perovskites Toward Photonic Application, S. M. Nayeem Arefin
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Lead halide perovskites (LHPs) are a fascinating class of photonic materials with the potential to revolutionize various optoelectronic applications. Their diverse crystal structures, ranging from 0D to 3D configurations, offer a unique combination of properties, including high tunability and ease of synthesis. However, their inherent instability and the difficulty of patterning them into sophisticated photonic structures using conventional methods present a significant hurdle to their widespread applications. This thesis addresses these challenges by proposing a novel synthesis method that combines soft lithography and self-assembly. By utilizing a patterned template with controlled wettability, precise manipulation of LHP crystal formation is achieved, …
Ultrashort Pulsed Laser Treatment Is Effective At Sterilizing Metal Surfaces For Planetary Protection, Kaleb Mcquillan
Ultrashort Pulsed Laser Treatment Is Effective At Sterilizing Metal Surfaces For Planetary Protection, Kaleb Mcquillan
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
To prevent forward contamination from microbes aboard spacecraft intended for exploration of solar system bodies there is a need for effective sterilization methods. However, current techniques are both time-consuming and expensive. For example, dry heat sterilization requires removal from the assembly site and several days of treatment. Furthermore, some components such as optics and electronics are not compatible with current sterilization techniques. In this thesis, a novel femtosecond laser surface processing technique for the rapid sterilization of spacecraft hardware is reported. Femtosecond lasers produce extremely high photon fluxes (1029 photons/s*cm2, ~0.03 J/cm2) in extremely short …
Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally
Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally
Electronic Theses and Dissertations
In recent years, the use of 4D flow MRI has revolutionized cardiovascular imag- ing by providing comprehensive data on blood flow dynamics over time. However, the limited spatial and temporal resolution of this imaging modality can hinder the accurate assessment of complex hemodynamic phenomena. This thesis explores the application of Physics-Informed Neural Networks (PINNs) to enhance the resolution of 4D flow MRI data, thereby improving its clinical utility. PINNs are a class of neural networks that integrate physical laws into their training process. By embedding these physics equations, PINNs can discover the underlying physics of fluid dynamics to produce more …
Novel Sensors, Algorithms And Metrics For Human-Robot Interaction., Henry Lee Reynolds
Novel Sensors, Algorithms And Metrics For Human-Robot Interaction., Henry Lee Reynolds
Electronic Theses and Dissertations
The increased presence and deployment of robotics in sectors such as the medical field results in the demand for robots to, directly and indirectly, interface with people and their environment, making human-robot interaction (HRI) a vital thrust of robotics research. Assistive robots, for example, aid humans in accomplishing tasks or by providing support in the workforce. As the demand for nurses and the aging population increases, the assistive robots deployed will be deeply rooted in environments that require constant interaction with humans. This work contributed to improving aspects of HRI through 1) Expanding accessibility of the methods used for interfacing …
Ω-Shaped Rogowski Coil Current Sensor Optimization Design In Power Electronics Applications, Xia Du
Ω-Shaped Rogowski Coil Current Sensor Optimization Design In Power Electronics Applications, Xia Du
Graduate Theses and Dissertations
Accurate switching current measurement plays a pivotal role in characterization of power devices, overcurrent protection, and real-time control of system-level operations in power electronics applications. However, the ongoing revolution in power electronics, driven by the emergence of wide bandgap power devices operating at megahertz (MHz) switching frequencies, introduces challenges for current sensor design. The urgent issue now is the need to increase current sensor bandwidth significantly to adeptly capture the rapid switching speed current. Additionally, the trend towards high power density and compact power converters in various applications demands current sensors that are not only compact and nonintrusive but can …
Mmwave Tx-Rx Self-Interference Suppression Through A High Impedance Surface Stacked Ebg, Adewale K. Oladeinde, Ehsan Aryafar, Branimir Pejcinovic
Mmwave Tx-Rx Self-Interference Suppression Through A High Impedance Surface Stacked Ebg, Adewale K. Oladeinde, Ehsan Aryafar, Branimir Pejcinovic
Electrical and Computer Engineering Faculty Publications and Presentations
This paper proposes a full-duplex (FD) antenna design with passive self-interference (SI) suppression for the 28 GHz mmWave band. The reduction in SI is achieved through the design of a novel configuration of stacked Electromagnetic Band Gap structures (EBGs), which create a high impedance path to travelling electromagnetic waves between the transmit and receive antenna elements. The EBG is composed of stacked patches on layers 1 and 2 of a four-layer stack-up configuration. We present the design, optimization, and prototyping of unit antenna elements, stacked EBGs, and integration of stacked EBGs with antenna elements. We also evaluate the design through …
Applying Circuit Theory To Describe Changes In Structural Landscape Connectivity In Response To Wildfire, Christian Ross Nielsen
Applying Circuit Theory To Describe Changes In Structural Landscape Connectivity In Response To Wildfire, Christian Ross Nielsen
School of Natural Resources: Dissertations, Theses, and Student Research
Understanding and conserving ecological connectivity is critical to the preservation of vulnerable landscapes. Circuit theory, in which landscapes are imagined as circuit boards with varying resistances to the flow of current, is being increasingly used to model spatially explicit connectivity of landscapes and to inform land management and conservation decision-making. Utilizing continuous, quantitative estimates of percent cover by five land cover functional groups to create a conductance surface, this study expanded upon an established application of circuit theory that used the open-source software Circuitscape to model species-agnostic, omnidirectional connectivity. This model was automated using Python to create time-series connectivity maps …
Development Of 3d Human Cardiovascular And Cancer Tissue Model Within A Self-Driven Microfluidic Platform For Preclinical Drug Screening, Aibhlin Alexis Esparza
Development Of 3d Human Cardiovascular And Cancer Tissue Model Within A Self-Driven Microfluidic Platform For Preclinical Drug Screening, Aibhlin Alexis Esparza
Open Access Theses & Dissertations
According to the American Heart Association and World Health Organization, cardiovascular diseases (CVDs) are the leading cause of death worldwide. Monolayer cell culture (2D) and animal models are conventional methods to study CVDs, however, they limit researcherâ??s ability to simulate the human cardiovascular cellular microenvironments and accurate predication of pharmaceutical drug responses. Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs), biomaterials, and microfluidic technologies can be combined to create a controlled, reproducible 3D platform to study physiologically-relevant cellular responses to biochemical and physical changes in the microenvironment. My dissertation work demonstrates the development of novel self-driven microfluidic devices designed with …
A Real-Time Iot-Based Data Acquisition And Monitoring System For Photovoltaic Applications, Adam Barbosa, Hamza Mubarak, Fazel Mohammadi, Mohammad J. Sanjari, Mehrdad Saif
A Real-Time Iot-Based Data Acquisition And Monitoring System For Photovoltaic Applications, Adam Barbosa, Hamza Mubarak, Fazel Mohammadi, Mohammad J. Sanjari, Mehrdad Saif
Electrical & Computer Engineering and Computer Science Faculty Publications
The transition to low-carbon energy systems, driven by climate change and fossil fuel scarcity, highlights technologies, such as Photovoltaic (PV) technology, for sustainable energy generation. This paper focuses on enhancing the efficiency of PV monitoring systems by leveraging Internet of Things (IoT) technology for accurate and real-time monitoring of essential parameters, such as voltage, current, and output power. Significant gaps in cost-effective and reliable IoT integration for PV monitoring are addressed, with an emphasis on predictive modeling. In this regard, a low-cost real-time IoT-based data acquisition and monitoring system for PV systems, as a proof of concept for future endeavors …
High-Power Power Conditioning Systems For Medium-Voltage Applications, Ahmed Rahouma Fares Rahouma
High-Power Power Conditioning Systems For Medium-Voltage Applications, Ahmed Rahouma Fares Rahouma
Graduate Theses and Dissertations
The purpose of this dissertation is to address the background, theoretical analyses, design methodologies, and evaluation techniques relevant to high-power power conditioning systems (PCSs) tailored for medium-voltage (MV) applications. Conventional PCSs, reliant on line-frequency transformers (LFTs), suffer from many problems including low power densities, inflexible designs, and scalability constraints. Employing multilevel converters (MLCs), particularly cascaded H-bridge topology, eliminates the need for these LFTs. A key focus lies in minimizing the number of cascaded building blocks by harnessing MV power switching modules. The dissertation makes two primary contributions: firstly, it offers a design methodology for MV-PCS, facilitating the selection of the …
Federated Learning In Wireless Networks, Xiang Ma
Federated Learning In Wireless Networks, Xiang Ma
All Graduate Theses and Dissertations, Fall 2023 to Present
Artificial intelligence (AI) is transitioning from a long development period into reality. Notable instances like AlphaGo, Tesla’s self-driving cars, and the recent innovation of ChatGPT stand as widely recognized exemplars of AI applications. These examples collectively enhance the quality of human life. An increasing number of AI applications are expected to integrate seamlessly into our daily lives, further enriching our experiences.
Although AI has demonstrated remarkable performance, it is accompanied by numerous challenges. At the forefront of AI’s advancement lies machine learning (ML), a cutting-edge technique that acquires knowledge by emulating the human brain’s cognitive processes. Like humans, ML requires …
Ensemble Machine Learning At The Edge Using The Codec Classifier Structure And Weak Learners Guided By Mutual Information, Aj Beckwith
All Graduate Theses and Dissertations, Fall 2023 to Present
The Codec Classifier is a low-computation, low-memory tree ensemble method that dramatically improves feasibility of image classification on resource-constrained edge devices. It achieves advantages over other tree ensemble methods due the separation of encoder and decoder tasks in the classifier. The encoder partitions feature space, and the decoder labels the regions in the partition. This functional separation of tasks enables the encoder design (partitioning) to be guided by maximizing the mutual information (MI) between class labels and the features (i.e. the encoded representation of the data) without regard to the error performance of the classifier. Experiments show maximizing MI leads …
Anomaly Detection On Wind Turbine Blades Using Aerial Imaging, Image Processing, And Deep Learning, Bridger Kohl Altice
Anomaly Detection On Wind Turbine Blades Using Aerial Imaging, Image Processing, And Deep Learning, Bridger Kohl Altice
All Graduate Theses and Dissertations, Fall 2023 to Present
In reaction to rising global temperatures and carbon dioxide emissions, many countries are looking to use energy sources other than fossil fuels. One such source of energy is wind energy, which can be harvested by wind turbines. By rotating at high speeds, the blades of these large turbines are able to convert wind energy to kinetic energy, which is then converted to electricity usable by the power grid. Traditional methods for inspecting these turbines for damages are expensive, unsafe, and susceptible to human error. These turbines are so tall and so large that inspectors run the risk of falling from …
Filter Incidence Narrowband Infrared Spectrometer For Space-Based Methane Measurement And Plume Detection, Bruno Mattos
Filter Incidence Narrowband Infrared Spectrometer For Space-Based Methane Measurement And Plume Detection, Bruno Mattos
All Graduate Theses and Dissertations, Fall 2023 to Present
Monitoring methane emissions from space is essential for reducing global warming. This dissertation introduces the Filter Incidence Narrowband Infrared Spectrometer (FINIS), a compact, lightweight instrument designed for nanosatellites to accurately measure methane emissions. FINIS uses two innovative imaging spectrometers to capture the Earth's reflected light, focusing on the strongest methane absorption feature at 1666 nm. By using tiled interference filters, each imager collects detailed spectral data, allowing precise methane detection. FINIS has been significantly improved from its prototype to its space-ready version, set to launch on the ACMES CubeSat in late 2025. The new design includes a binocular optical system …
Modification Of Time-Domain Terahertz Spectroscopy System To Polarimetry Imaging System With Application To Human Breast Cancer Surgical Specimen, Nikita Gurjar
Graduate Theses and Dissertations
Breast-conserving therapy (lumpectomy) is one of the most performed breast cancer surgeries in the United States. The best outcome of lumpectomy surgery is achieved when the surgical margins are free of cancer. When remnants of cancer are detected at the surgical margins after the initial operation, a second operation will be required to remove the cancer. Unfortunately, a significant number of patients undergo breast conserving surgery (BCS) at local hospitals that do not have access to immediate on-site pathology leading to high rates of re-excision or reoperation (greater than 30%). Therefore, there is a significant need for new intraoperative technology …
Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins
Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins
All Theses
As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …
Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral
Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral
All Theses
The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also be quick to make decisions. In Autonomous Vehicle research, the environment perception system is one of the key com- ponents of development. The environment perception system allows the vehicle to understand its surroundings using cameras, light detection and ranging (LiDAR), and other sensor systems or modalities. Deep learning computer vision algorithms have shown to be the …
Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han
Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han
Electronic Theses and Dissertations
Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …
Deep Reinforcement Learning-Based Dynamic Routing And Spectrum Access In Aeronautical Networks., Zhe Wang
Deep Reinforcement Learning-Based Dynamic Routing And Spectrum Access In Aeronautical Networks., Zhe Wang
Electronic Theses and Dissertations
As the airspace is experiencing an increasing number of aircraft, spectrum sharing among Air Vehicles (AVs) and Terrestrial Users (TUs) emerges as a compelling solution to improve spectrum utilization efficiency. I investigated three types of aeronautical communication including the single-hop Air-Air Communication Network (AACN), the multi-hop Air-Air Ad-hoc Network (AAAN), and the Aerial and Terrestrial Hybrid Network (ATHN). I assume a spectrum-limited scenario through all communication networks. Thus, the number of communication pairs is greater than that of the available channels, resulting in co-channel interference due to the reuse of the same channel among communication links. In a single-hop AACN, …
Development And Processing Of Shape Memory Polymer Composites (Smpcs) For Application In Structural Robotics And Robotic Sensors., Kavish Sudan
Electronic Theses and Dissertations
Shape Memory Polymers (SMPs) have attracted significant attention since their introduction in the 1980s due to their remarkable ability to regain their original shape from a temporarily deformed state when exposed to an external stimulus, typically heat. This shape memory effect, driven by thermal transitions such as the glass transition temperature (Tg) or melting temperature (Tm), has made SMPs highly attractive for applications in soft robotics, aerospace, and biomedical devices. However, SMPs face challenges such as limited mechanical strength, thermal stability, and electrical conductivity, which hinder their broader adoption in advanced applications. To address these challenges, …
A Heuristic Approach To Operations And Control Of Btm-Ders For Bill Management And Grid Services, Md Arshad Rashid Shaon
A Heuristic Approach To Operations And Control Of Btm-Ders For Bill Management And Grid Services, Md Arshad Rashid Shaon
UNLV Theses, Dissertations, Professional Papers, and Capstones
Behind-The-Meter (BTM) distributed energy resources (DERs) have emerged as a critical and transformative force within the energy sector. These decentralized energy assets, which include solar photovoltaic (PV) systems, battery energy storage systems (BESS), and thermostatically controlled loads (TCLs), are increasingly essential for empowering customers by granting them greater control over their energy production and consumption, thereby reducing reliance on centralized power sources. Additionally, they have the potential to play a pivotal role in enhancing grid resilience by providing grid services. This study investigates the management of customer electricity bills and grid services through the integration of various BTM-DERs, particularly solar …
Automated Measurement Of The Water Drop Penetration Time For The Analysis Of Soil Water Repellency, Danxu Wang
Automated Measurement Of The Water Drop Penetration Time For The Analysis Of Soil Water Repellency, Danxu Wang
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this work, we develop an innovative system for the automated measurement of Water Drop Penetration Time (WDPT) - a parameter that is conventionally used for evaluating soil water repellency (SWR). Increased SWR can be a reason for plant stress and poor crop yields, create a risk of potential water runoff and floods and thus can pose risks to life and property loss. Timely evaluation of soil conditions can save resources and win time for responding to environmental disasters. Manual measurements of WDPT are labor-intensive, subjective, tend to produce variability of outcomes, and also not always available in remote or …
Hardware-Oriented Protection And Acceleration For Machine Learning Application, Antian Wang
Hardware-Oriented Protection And Acceleration For Machine Learning Application, Antian Wang
All Dissertations
The security of Machine Learning (ML) grows along with the development of high-performance models and expanding application scenarios. Numerous users are benefiting from the convenience brought by transformative ML applications. In the meantime, various attackers are trying to find vulnerabilities within ML deployment service models, thereby undermining the performance of ML and jeopardizing stakeholders’ interests. The dissertation focuses on the two aspects of secure ML applications: acceleration and protection. Homomorphic Encryption (HE) emerges as a widely recognized security primitive suitable for the cloud computing service model, where the computation can be performed over ciphertext without decryption. However, evaluations in the …
Data-Driven Enhanced Energy Management System Applications For Energy Control Centers, Dulip Madurasinghe
Data-Driven Enhanced Energy Management System Applications For Energy Control Centers, Dulip Madurasinghe
All Dissertations
This dissertation explores the pressing needs of modern bulk power system operation and control and delves into enhancements to EMS applications with minimal infrastructure development. The dissertation investigates three main EMS application enhancements. The transmission network topology processing (TNTP) is a foundational application of the EMS. A physics-based hierarchical transmission network topology processing (H-TNTP), including substation configuration identification, to improve efficiency and reliability is proposed. Secondly, a multi-level distributed linear state estimation (D-LSE) approach solely based on PMUs is proposed utilizing H-TNTP as the network modeling tool. The D-LSE can conduct linear state estimation (LSE) at either substation, area or …
Time-Domain Line Protection In Presence Of Renewables, Prabin Adhikari
Time-Domain Line Protection In Presence Of Renewables, Prabin Adhikari
All Dissertations
Inverter based resources (IBRs) are crucial in integrating renewable energy sources into the power grid. However, their unique fault characteristics, significantly different from synchronous generators (SGs), present several challenges for existing line protection schemes at both transmission and distribution levels. These schemes, reliant on distance and directional relays designed in phasor domain, are not well-suited for IBRs. Most published literature addressing this problem concentrates on altering the control design of inverters. However, this approach faces practical limitations. Inverter controls, often proprietary, are not readily accessible to utilities, rendering the control-based solutions impractical for widespread implementation.
To address this challenge, this …
Computer Vision Algorithms For Assessment Of Surgical Suturing Skill Using Hand And Needle Motion, Jianxin Gao
Computer Vision Algorithms For Assessment Of Surgical Suturing Skill Using Hand And Needle Motion, Jianxin Gao
All Dissertations
Surgical suturing skill assessment is a crucial part of surgical education. Vascular surgery educators have developed a simulation-based examination called Fundamentals of Vascular Surgery, which includes a clock-face model for assessing open surgical suturing skills. The clock-face model, however, requires the valuable time of expert surgeons to determine examinees' skills. Moreover, expert surgeons have different judgments for appropriate sutures, which leads to inconsistent grading. These limitations motivate us to use sensors to measure examinees' needle motions and hand motions during the clock-face suturing exercises, and then use the measurements for objective suturing skill assessment.
To assess suturing skills based on …
Impacts Of High-Frequency Operation On Magnetics And Performance On Isolated Power Electronic Converter Design, David Arturo Porras Fernandez
Impacts Of High-Frequency Operation On Magnetics And Performance On Isolated Power Electronic Converter Design, David Arturo Porras Fernandez
Graduate Theses and Dissertations
The pursuit of high-power density and high switching frequency is a central theme in the advancement of power electronic converters. While these parameters offer significant benefits in terms of compactness and performance, they also introduce challenges related to efficiency and thermal management. This doctoral dissertation aims to provides a design framework to analyze the implications of high-frequency operation (> 100 kHz) on magnetics design and performance in power electronic converters, particularly when integrating silicon carbide (SiC) power modules. It examines the advantages and disadvantages of high-frequency operation and delves into its effects on the performance of the converter, focusing on …
Evaluation, Modeling And Application Of Gallium Nitride Field Effect Transistor, Geno Guillaume
Evaluation, Modeling And Application Of Gallium Nitride Field Effect Transistor, Geno Guillaume
Graduate Theses and Dissertations
Gallium Nitride (GaN) has emerged as one of the leading materials for power devices due to its wide band gap and high electron mobility. The band gap is the minimum energy required to excite an electron up to a state in the conduction band where it can participate in conduction. Because of this, wide band gap (WBG) materials are favorable for various electrical applications. The market for GaN high-electron-mobility transistor (HEMT) is projected to exceed $1.25 billion by 2027. With the increase of market interest, modern technologies emerge that aim to push the boundaries of efficiency for GaN power devices. …