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Articles 61 - 90 of 656

Full-Text Articles in Electrical and Computer Engineering

Power Allocation And Massive Mimo Channel Modeling For 5g Wireless Communications, Zhangliang Chen May 2022

Power Allocation And Massive Mimo Channel Modeling For 5g Wireless Communications, Zhangliang Chen

Electrical Engineering Dissertations - Archive

To meet the demand for wireless communication transmission rate to reach a thousand times of the existing system in 2021, the fifth-generation (5G) mobile communication system was developed. Compared with Long-Term Evolution (LTE), the 5G mobile communication needs to be transmitted in wireless breakthrough innovation in technology to achieve the goal of ten times increase in spectrum efficiency and power efficiency. As a time series analysis tool based on vector autoregression, Granger causal analysis originated in the field of econometrics, and its staged generalized transfer entropy (TE) based on conditional co-information in information theory has been widely used in recent …

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Surface Flashover Under Various Surface Conditions, Bradley A. Hannum May 2022

Surface Flashover Under Various Surface Conditions, Bradley A. Hannum

Electrical Engineering Theses - Archive

Electrical insulators are critical components used in every high voltage application whether it is operated continuously or in a pulsed mode. Bulk dielectric breakdown and surface flashover must be prevented in all use cases, especially those that occur in polluted environments. Though electrical standards have been written as a guide to prevent insulator surface flashover, such as Underwriters Laboratories (UL) 840, they are not directly applicable to applications where size and weight are critical. UL 840 experimental design is vague, does not consider all environments, and is written primarily with the electric power utilities in mind. The research presented here …

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Development Of A Novel Sensor For Soil Moisture's Profile, Toan Canh Nguyen May 2022

Development Of A Novel Sensor For Soil Moisture's Profile, Toan Canh Nguyen

Electrical Engineering Theses - Archive

Monitoring of soil’s water content has been an important part of the irrigation system in farming, regional resources development, rainfall detection as well as disaster prevention. There has been studies and developments in this area over the decades. However, most of the works are focused on sensing the soil as a homogeneous medium, which does not accurately reflect the heterogeneous structure of soil. Works on multi-layer soil sensing have been researched and developed. Though, the current design is complex, not easy to produce and assemble. This work presents a novel low-cost and simple soil sensor design to detect the soil’s …

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Scalable Optimization Method For Generator Scheduling Under Uncertainty, Edward Arthur Quarm Jnr Dec 2021

Scalable Optimization Method For Generator Scheduling Under Uncertainty, Edward Arthur Quarm Jnr

Electrical Engineering Dissertations - Archive

Scalable optimization methods for power system operation has been subject of research over the last 60 years. State-of-the-art methods in this research area is yet to yield the scalability desired by system operators for practical operation of electric grids. This article-based dissertation makes three significant contributions. A scalable computational method is developed to tackle a mixed-integer problem commonly referred to as Stochastic Security-Constrained Unit Commitment (SSCUC), the output of which will be beneficial to Independent System Operators to manage electric grids. Secondly, an improved model for time-progressive contingencies in security-constrained optimization problems is presented. This modeling approach is more realistic …

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Distributed Estimation And Inverse Reinforcement Learning For Multi-Agent Systems, Bosen Lian Dec 2021

Distributed Estimation And Inverse Reinforcement Learning For Multi-Agent Systems, Bosen Lian

Electrical Engineering Dissertations - Archive

Consensus-based distributed Kalman filters for estimation with multiple targets have attracted considerable attention. Most of the existing Kalman filters use the average consensus approach, which tends to have a low convergence speed. They also rarely consider the impacts of limited sensing range and target mobility on the information flow topology. The robustness properties, i.e., gain margins and phase margins of distributed Kalman filtering algorithms are still open problems. In the interactions of controlled dynamical agents, it is often assumed that the agents are "rational" in the sense of attempting to act in such a way as to optimize some prescribed …

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Fast And Parallelizable Numerical Algorithms For Large Scale Conic Optimization Problems, Muhammad Adil Dec 2021

Fast And Parallelizable Numerical Algorithms For Large Scale Conic Optimization Problems, Muhammad Adil

Electrical Engineering Dissertations - Archive

Many real world problems from various application areas such as engineering, finance and operation research can be cast as optimization problems. Generally, the goal is to optimize an objective function under a set of constraints. Traditionally, convex optimization problems are solved by an interior point method (IPM). Interior point methods proved to achieve high accuracy for moderate size problems. However, the computation cost of iterations of these iterative algorithms grows non-linearly with the dimension of the problem. Although interior-point methods are robust and theoretically sound, they do not scale well for very large conic optimization programs. Computational cost, memory issues, …

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Macromodeling And Accelerated Simulations Of Electric Machines, Ajay Pratap Yadav Aug 2021

Macromodeling And Accelerated Simulations Of Electric Machines, Ajay Pratap Yadav

Electrical Engineering Dissertations - Archive

Electric machines are the most important element in the power grid. Given its centennial legacy and the rise of electric vehicles and distributed energy resources, it is imperative to bring new technologies into this area. This work tries to bridge the gap between electric machines and innovative research domains such as convex optimization and FPGA-based hardware acceleration. Problems of electric machine parameter identification and real-time simulation are considered. A convex optimization-based framework is designed to identify machine parameters. This tool is used to perform the macromodeling of a synchronous machine from its magnetic-equivalent circuit model. Furthermore, it is used to …

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Multi-Player H1 Differential Game Using On-Policy And Off-Policy Reinforcement Learning, Peiliang An Aug 2021

Multi-Player H1 Differential Game Using On-Policy And Off-Policy Reinforcement Learning, Peiliang An

Electrical Engineering Theses - Archive

This work studies a multi-player H-infinity differential game for systems of general linear dynamics. In this game, multiple players design their control inputs to minimize their cost functions in the presence of worst-case disturbances. We first derive the optimal control and disturbance policies using the solutions to Hamilton-Jacobi-Isaacs (HJI) equations. We then prove that the derived optimal policies stabilize the system and constitute a Nash equilibrium solution. Two integral reinforcement learning (IRL) -based algorithms, including the policy iteration IRL and o -policy IRL, are developed to solve the differential game online. We show that the off-policy IRL can solve the …

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Wi-Fi-Based Indoor Localization Using Model-Based And Data-Driven Approaches, Ayoub Idelhaj Aug 2021

Wi-Fi-Based Indoor Localization Using Model-Based And Data-Driven Approaches, Ayoub Idelhaj

Electrical Engineering Theses - Archive

This thesis investigates model-based and data-driven approaches for indoor localization using the Received Signal Strength Indicator (RSSI) of Wi-Fi signals. We study multiple model-based indoor localization approaches, including the free space path loss model, the log-distance path loss model, the International Telecommunication Union (ITU) model, and a nonlinear regression model. We examine their indoor localization accuracy using raw RSSI values, and filter RSSI values passed through a Moving Average filter and a Kalman filter. For data driven approaches, we employ a family of Extreme Learning Machine (ELM) algorithms including Basic-ELM, Online Sequential-ELM (OS-ELM), Hierarchical-ELM (H-ELM), and Kernel-ELM (K-ELM), to find …

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Adaptive Activations And Shift Invariance In Shallow Convolutional Neural Networks, Chinmay Appa Rane Aug 2021

Adaptive Activations And Shift Invariance In Shallow Convolutional Neural Networks, Chinmay Appa Rane

Electrical Engineering Dissertations - Archive

Deep learning training training algorithms are a huge success in recent years in many fields including speech, text,image video etc. Deeper and deeper layers are proposed with huge success with resnet structures having around 152 layers. Shallow convolution neural networks(CNN's) are still an active research, where some phenomena are still unexplanined. CNN's are assumed to be invariant to shift due to its architecture, but recent studies have shown other wise. Apart from shift invariance, activation functions used in the network are of utmost importance, as they provide non linearity to the networks. Relu's are the most commonly used activation function. …

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The Development Of Micro-Gas Chromatography System With Integrated Photonic Crystal Sensors, Priyanka Biswas Aug 2021

The Development Of Micro-Gas Chromatography System With Integrated Photonic Crystal Sensors, Priyanka Biswas

Electrical Engineering Dissertations - Archive

Miniaturization of gas chromatography (GC) systems have made it possible to utilize the analytical technique in on-site applications without having to compromise data reliability offered by the conventional benchtop GC. Various types of miniaturized microsensors and nanosensors have been developed for a micro-gas chromatography (µGC) system. However, integration of an appropriate detector in µGC systems still face significant challenge. We present a solution to the problem through integration of µGC with photonic crystal slab (PCS) sensors using transfer printing technology. This integration offers an opportunity to utilize the advantages of optical sensors such as high sensitivity, immunity to electromagnetic interference, …

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Automatic System Restoration For Industrial Power Systems, Anusha Papasani May 2021

Automatic System Restoration For Industrial Power Systems, Anusha Papasani

Electrical Engineering Dissertations - Archive

The power system industry often operates close to its limits to accommodate the increased demand posing a high risk of blackouts. Power system restoration techniques are utilized post breakout with the focus on load pickup and speedy recovery. In traditional heuristic methods, the load is considered to be constant after it is picked. However, from a system operation point of view, the load varies once picked. This is commonly observed in industrial loads. In Industrial systems, loads, which involve many induction motors, are started in sequence. The high starting currents of the induction motors leads to voltage sags that may …

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Resource Allocation And Capacity In Wireless Communications And Networks, Zikai Wang May 2021

Resource Allocation And Capacity In Wireless Communications And Networks, Zikai Wang

Electrical Engineering Dissertations - Archive

How to allocate resources in the era of Big Data in telecommunications becomes a new issue. Smartphone data could be a function of personality, as the smartphone supports interpersonal interaction, and the data collected from the smartphone usage often contains rich customer opinion and behavioral information. A bandwidth allocation method based on smartphone users' personality traits and channel condition is studied in a unified mathematical framework in this dissertation. Personalizing bandwidth allocation could be done by analyzing smartphone users' personality traits, resulting in business intelligence, a smarter and more efficient usage of the limited bandwidth, while taking channel fading conditions …

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Dynamic Equivalent Wind Farm Models For Planning, Operation, And Post-Fault Analyses, Yuhao Zhou May 2021

Dynamic Equivalent Wind Farm Models For Planning, Operation, And Post-Fault Analyses, Yuhao Zhou

Electrical Engineering Dissertations - Archive

With high penetration level of the wind power energy in the power grid, it is necessary to develop robust dynamic wind farm models for stability analysis under different scenarios. However, one single wind generator (WG) contains many parameter and control loops, it’s impractical to apply such detailed high-order model of individual wind turbine for dynamic stability analysis due to its computational burden and availability of the data. Therefore, there’s a need for deriving the dynamic equivalent model (DEM) for the wind farm. In the real world, a wind farm may contain different types of WGs coming from different manufactures/vendors with …

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Beamforming Using Quasi Optical Approach For 5g Backhaul, Pratik Ghate May 2021

Beamforming Using Quasi Optical Approach For 5g Backhaul, Pratik Ghate

Electrical Engineering Dissertations - Archive

A new method is proposed for quasi optical beamforming that will enhance performance of emerging systems such as broad deployment of 5G backhaul communications, Internet of Things (IOT), vehicular networking systems, and unmanned aerial navigation systems. It is a promising approach at higher frequencies to reduce the size, cost and improve efficiency of the beamforming operation. In this investigation candidate lens type structures are designed, studied, and analyzed using different configurations of dielectric wedges, plano-concave lens and dielectric slabs. These structures have cost, power consumption, size, weight, and bandwidth advantages, and are expected to be able to operate to higher …

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Nonlinear And Quantum Optics In Few-Mode-Fibers, Afshin Shamsshooli May 2021

Nonlinear And Quantum Optics In Few-Mode-Fibers, Afshin Shamsshooli

Electrical Engineering Dissertations - Archive

In the absence of quantum repeaters, fiber loss sets the hard limit on secure quantum communication rate. Single-photon source rate decays exponentially with the length of fiber. The only way to scale the rate up is by increasing the number of modes over which the single-photon or entangled states are transmitted, for subsequent use in. quantum communication, computing, or information processing. Entanglement in multiple degrees of freedom, e.g., in polarization, frequency, time-bin, and spatial modes has a potential for carrying larger amounts of quantum information. In this project, we explore spatial modes in the few-mode fiber for generation and processing …

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Unsupervised Data Driven Machine Learning In Hyperspectral Imaging And Echocardiography Videos, Kazi Tanzeem Shahid May 2021

Unsupervised Data Driven Machine Learning In Hyperspectral Imaging And Echocardiography Videos, Kazi Tanzeem Shahid

Electrical Engineering Dissertations - Archive

This work discusses the problem of unsupervised classification in images. Conventional methods approached this problem with the naive assumption that the relationship among the pixels' information can be expressed sufficiently in a linear manner. However, higher accuracy was established by implementing kernel-based expressions of data to express the non-linear relationship of that data in a linear manner, when mapped in a higher dimensional space. This process allows much more effective clustering performances by increasing the informativeness of the data. Hyperspectral images, being limited in spatial resolution as a tradeoff for the significantly higher number of channels compared to traditional images, …

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Robust Training Methods For Deep Neural Networks With A Variety Of Label Noise, Sree Ram Kamabattula May 2021

Robust Training Methods For Deep Neural Networks With A Variety Of Label Noise, Sree Ram Kamabattula

Electrical Engineering Dissertations - Archive

Requirement of significant amount of labeled training data is a major drawback in training deep neural networks (DNNs), due to the presence of mislabeled examples in these datasets. This label noise is shown to have an adverse effect on the generalization performance of DNNs. Thus, reducing the consequences of label noise is of much research value. In this dissertation, we focus on improving our understanding of label noise and, achieving better generalization performance. Due to the lack of ground truth with real world noisy datasets, most researchers create synthetic noisy datasets to develop robust training methods. Among these methods, stopping …

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Realization Of Compact Electrochemical Sensing Systems On A Board And A Chip For A High-Density Sensor Array, Hyusim Park May 2021

Realization Of Compact Electrochemical Sensing Systems On A Board And A Chip For A High-Density Sensor Array, Hyusim Park

Electrical Engineering Dissertations - Archive

The sensitive and cost-effective electrochemical sensors based on various classes of nanocomposites fabricated by different methods for the detection of target chemicals. Its application is boundless from reactive monitoring of food additives, human health to environmental safety. In proportion to electrochemical sensor’s usages, the researchers’ interests in electrochemical sensing system have been grown, especially in portable system to satisfy many of the requirements for on-site and in-situ measurements. The electrochemical sensing system is consisted of sensor and electric readout circuit. The one of the most efficient way to carry out the reading of a set of electrochemical sensors for portable …

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Data-Driven Decision Making And Control Of Rational Agents, Patrik Kolaric May 2021

Data-Driven Decision Making And Control Of Rational Agents, Patrik Kolaric

Electrical Engineering Dissertations - Archive

This dissertation studies the problem of data-driven optimal decision making. The 4main contributions of this work are listed here. First, we develop a model-based and data-driven techniques for learning the cost of an Ex-pert agent. This ties fields of Inverse Optimal Control and Inverse Reinforcement Learning and represents a first data-driven algorithm of this kind in the control community. Next, we have developed optimally adaptive dynamic control allocation mechanism that optimally re-configures redundant actuators in a model-free fashion, that is, based on collected data. This work pushed the multiple frontiers of control allocation research, since state-of-the-art control allocation was Next, …

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Investigation Of The Channel Hot Carrier (Chc) Stressing Effects And Identification Of The Stress-Induced Oxide Traps Leading To Rts In Pmosfets, Tanvir Ahmed Dec 2020

Investigation Of The Channel Hot Carrier (Chc) Stressing Effects And Identification Of The Stress-Induced Oxide Traps Leading To Rts In Pmosfets, Tanvir Ahmed

Electrical Engineering Dissertations - Archive

Electrical stressing mechanisms are responsible for the generation of stress-induced gate SiO2 defects, in addition to the presence of process-induced oxide traps, in MOSFETs. Random telegraph signal (RTS) can be utilized as a tool to characterize these defects. Channel hot carrier (CHC) stressing is reported to result in the worst degradation in pMOSFETs. However, the effects of CHC on RTS for pMOSFETs are under-reported. The main objective of this work is to investigate the impact of the CHC stressing on pMOSFETs by analyzing RTS. For this reason, the effects of CHC stressing on different RTS parameters are examined. Additionally, responsible …

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Heterogeneous Transcoding For Next Generation Multimedia Video Codecs For Efficient Communication, Shreyanka Subbarayappa Dec 2020

Heterogeneous Transcoding For Next Generation Multimedia Video Codecs For Efficient Communication, Shreyanka Subbarayappa

Electrical Engineering Dissertations - Archive

Innovations in the communication systems and technology are growing tremendously and the growth seen is unimaginable in the last forty years. In multimedia communication systems, technology has transformed from analog television to digital television in the video domain. Mobile phones are known as smart phones as they are used, not only to make voice calls, but also used to send emails, video calls, transfer data, GPS, taking pictures and so on. Due to the wide spread user applications, compression on data becomes important to save system resources. Video has occupied 75% of major traffic of data transfer and is expected …

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Autonomous Landing Of Quadrotor On A Moving Ugv With The Optimal Control Policies, Suhas Priyatham Manda Dec 2020

Autonomous Landing Of Quadrotor On A Moving Ugv With The Optimal Control Policies, Suhas Priyatham Manda

Electrical Engineering Theses - Archive

This thesis proposes an offline method that uses an integral reinforcement learning (IRL) technique along with the system identification to determine the optimal control of a system with completely unknown dynamics. Unmanned aerial vehicles (UAV) that are particularly deployed to track and land on an arbitrarily moving unmanned ground vehicles (UGV), demand a high performance controller to perform precise tracking. One way of designing an optimal tracking controller is developing linear quadratic integrators (LQI) with a quadratic type of cost function that solves Riccati equation. However, this approach requires prior knowledge of the linearized UAV system dynamics. We overcome this …

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Car Plate Detection Using Region-Based Convolutional Neural Networks, Shengyi Luan Dec 2020

Car Plate Detection Using Region-Based Convolutional Neural Networks, Shengyi Luan

Electrical Engineering Theses - Archive

Convolutional Neural Networks (CNN) comprise a deep learning technology which is widely used to perform image classification. In this research, we review CNN structures and explain how they can be used for finding license plates in vehicle images. We summarize how the standard CNN processes images into features and compare it to Region-Based Convolutional Neural Networks (R-CNN). After comparing their pros and cons, we decide to design a R-CNN to train our dataset for this project. We find that the one trained with the most training data has the highest testing accuracy. The first training network detector leads to the …

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Novel Vibrational Energy Harvesters Utilizing Piezoelectric Li-Doped Zno Nanowires And The Triboelectric Effect, H M Ashfiqul Hamid Aug 2020

Novel Vibrational Energy Harvesters Utilizing Piezoelectric Li-Doped Zno Nanowires And The Triboelectric Effect, H M Ashfiqul Hamid

Electrical Engineering Dissertations - Archive

Vibration sources are omnipresent everywhere in our regular lives including the automobiles, aircraft, human body motion, wind flow, and water waves. Vibrational energy harvesters are electromechanical systems that can convert the ambient vibrations into electrical energy which can be stored to power up small scale electronic devices, essentially converting them into self-powered systems. The electronics industry has always propelled towards the scaling of electronic devices for improved flexibility and reduced production cost. This scaling, combined with the power-efficient designs, is widening the scope of applications for the energy harvesters. For instance, the vibrational energy harvesters have substantial applications in small …

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Distributed Resilient Control Of Multi-Agent Systems With Applications To Microgrids, Shan Zuo Aug 2020

Distributed Resilient Control Of Multi-Agent Systems With Applications To Microgrids, Shan Zuo

Electrical Engineering Dissertations - Archive

Distributed cooperative control of multi-agent systems (MAS) has been an active research area over the last few decades. Distributed cooperative controller is locally designed using the neighborhood relative information. Such a distributed control manner, however, is vulnerable to malicious attacks, due to the absence of a centralized control architecture to effectively monitor and verify the local information flow. Those attacks could undermine cooperative performance and even cause system instability. In this work, a new concept of multi-group system is first proposed, consisting of cooperative leaders and followers, as well as adversaries. A resilient control framework is developed for general linear …

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Structured Deep Learning: Theory And Applications, Fangqi Zhu Aug 2020

Structured Deep Learning: Theory And Applications, Fangqi Zhu

Electrical Engineering Dissertations - Archive

The increasing amount of data generation has boosted the broad range of research in big data and artificial intelligence. Besides the success of the deep learning in wide range of research area, it meets its pitfalls on the following three problems: * Data hungry: current models often require to feed GB, TB even PB level of data, which is easily overfit. * Hard to generalize: deep learning constructs representations that memorize their training data rather than generalize to unseen scenarios * Missing critical information: o -the-self deep learning framework may not fully utilize the underlying information of the data We …

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Exploring Iot-Based Applications In Power Systems Monitoring, Demand Side Management And Protection, Long Zhao Aug 2020

Exploring Iot-Based Applications In Power Systems Monitoring, Demand Side Management And Protection, Long Zhao

Electrical Engineering Dissertations - Archive

The Internet-of-Things (IoT) concept allows objects to share data through wired or wireless connections for communication purposes. Currently, IoT has been involved with the development of smart grids in many applications. In this article-based dissertation, IoT applications in power systems are presented in 7 published research papers. In the first three papers, the developments of the IoT-based monitoring system are presented. Power substation monitoring for the petrochemical facility is discussed in the first paper. Internal design and detection mechanisms are emphasized in this research. The second paper presents the communication and task allocations for a generic power substation monitoring system. …

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High-Performance Optimization Methods For Emerging Power Systems, Tuncay Altun Aug 2020

High-Performance Optimization Methods For Emerging Power Systems, Tuncay Altun

Electrical Engineering Dissertations - Archive

This dissertation investigates the applications of high performance optimization techniques for emerging power systems with augmented power electronics devices. One of the main sources of complexity in the analysis of power systems is rooted in the power flow equations modeling steady-state relationship between power injections and voltages. Hence, the present work is in-part focused on addressing the complexity of power flow equations in the presence of power electronic devices. In contrast to the classic optimal power flow (OPF) solution techniques, we employ convex optimization methods to reliably find globally optimal solutions in polynomial time. The first chapter investigates the optimization …

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Multiscale Modeling And Simulation Of Clutter In Isar Imaging, Jon Mitchell May 2020

Multiscale Modeling And Simulation Of Clutter In Isar Imaging, Jon Mitchell

Electrical Engineering Dissertations - Archive

Clutter is common in applications of radar imaging and can adversely impact target imaging by contributing scattered energy that is not accounted for in target signal models. One potential source of clutter is moving foliage in the vicinity of the target, such as a target embedded in a forest. ISAR imaging of moving clutter results in an equivalent current image that changes over each imaging sample. The stochastic nature of this clutter equivalent current presents challenges in detecting and imaging a weak embedded target using traditional algorithms. This dissertation proposes a multiscale model and analysis method to characterize the multiscale …

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